Essay: Power sources for Unmanned Aerial Vehicles (UAVs)

CHAPTER 1
INTRODUCTION
Unmanned Aerial Vehicle (UAV) is an inhabited aerial platform used for several military and civilian applications without the risk human losses due to the dangerous type of missions assigned, or extremely required accuracy that cannot be achieved by human control.
Among the military applications that UAVs can perform [1]:
Reconnaissance, Surveillance.
combat Synthetic Aperture Radar (SAR).
Deception operations.
Maritime operations.
Electronic Warfare.
Meteorology missions.
Radio and data relay
The potential uses of UAVs in the civil industry are:
Search and rescue.
Crop monitoring and spraying.
Wild fire suppression.
Communications relay.
Law enforcement.
Disaster and emergency management.
Research.
Industrial applications.
According to the flight range, UAVs have five main categories [1]:
1. Close range, which include air vehicles that the flying range less than 25 km. regularly these aircraft are extremely light and can be launched by hand.
2. Short range, which are platforms that work within a range of 25-100 km. Such systems are designed for operations within a limited area.
3. Medium range, these are UAVs capable of fly within a range of 100-200 km. UAVs of this category are defined by a more superior aerodynamic design and control systems because of their superior performance.
4. Long range, these are UAVs that be able to fly within range of 200-500 km. As in the previous category such systems are necessary to use more superior technology to achieve difficult missions. A sat link is needed to solve the communication problem (another relay platform can perform the same job ) between the GCS and the aircraft because of earth curvature.
5. Endurance, these are vehicles capable of operating in a more than 500 km range, or that flying continuously for more 20 hours or more. These can be considered the most advanced and complex member of the UAV family due to the high capabilities and superior specifications. Such UAV can be distinguished from others by their high capabilities and large dimensions.
1.1 Small Unmanned Aerial Vehicle
According to the applications, UAVs can be categorized into four sizes; micro, small, medium, and large as shown in Figure 1.1.
Figure 1.1 Four groups UAV with respect to its sizes and weights.
The military has shown the mainly recent interest in small UAVs (SUAVs) for many reasons. A SUAV is easier to use and more portable than other UAVs and requires only a single operator. A smaller reconnaissance plane can approach ground targets at closer range and can not be detected because of the less emissions and smaller RCS ( Radar Cross section )
UAV propulsion system constitutes the propulsive engine and its drive system. Most UAVs propulsion systems currently utilize either Internal Combustion Engines (ICEs) or electric motor.
ICEs are often used in large aircraft use due to high energy density of fuel compared to batteries required for electric motors, however electric motors have several significant advantages. A major advantage of electric motors is that they are small in size with respect to ICEs, hence most SUAVs use electric motors as propulsion systems, which allow for stealthier and more reliable flight with little engine failure.
1.2 Electrical Unmanned Aerial Vehicle (EUAV)
An EUAV is an UAV powered by an electric motor, instead of an ICE. Various electric energy sources are available for feeding the electric motors; consist of solar energy, hydrogen fuel cells, in addition to energy storage sources such as; super capacitors and large capacity batteries. Each source has its pros and cons. selecting an energy source depends upon the requirements, mission and size of the EUAV.
1.3 Why Fuel Cell Powered Aviation
A Fuel cell is a direct electro-chemical device that converts chemical energy to electrical energy. Today, several types of fuel cells are obtainable: for instance alkaline fuel cells, direct methanol, phosphoric acid, molten carbonate, solid oxide and proton exchange membrane fuel cells (PEMFCs). PEMFC fueled by hydrogen is acknowledged to be the most technically mature technology of fuel cell and the most well adapted to transportation-scale applications [2].
PEMFCs are designed by a solid polymer as electrolyte, absorptive electrodes combined with a platinum catalyst. Hydrogen gas is recombined with oxygen gas producing electrical energy with water vapor as emission. A closed loop system could be operated whereby the water from of the PEMFC can be electrolyzed into oxygen and hydrogen for later recycle. Oxygen is usually obtained from the surrounding air. Operating temperatures are comparatively low around 80 ”C, enabling fast starting and reduced wear. Platinum catalysts are necessary for operation and to decrease corrosion. PEMFCs are capable of supply high energy densities at low volume and weight, comparing with other fuel cell types. The pros of using PEMFCs as follows: high energy with respect to the weight, higher efficiency, less noise, non carbon emission, and low maintenance.
Fuel cells have some cons such as: sensitivity to load sudden changes, a slower dynamic response time than other sources and relatively long warming up time with respect to other options available before full power output is available.
1.4 Why Fuel Cell Hybrid Powerplants
Combining a fuel cell and a battery in one power supply allows utilization of the advantages of both devices and undermines their cons. Consequently, a fuel cell stack, a pack of Lithium-ion batteries, and a DC-DC buck converter will constitute the fuel cell-battery hybrid system, DC-DC buck converter is used to maintain voltage under sudden change in load.
On the other hand, the battery has a quick dynamic response time to fluctuations in a load, and has high power density consequently; one of the idealistic power solutions for long endurance UAV flights is the hybrid solution between the PEMFCs and Lithium-ion batteries as shown in Figure 1.2.
Figure 1.2 hybrid system
A DC’DC buck converter is planned to step-down the fuel cell stacks output voltage to a desired value. A PID controller is recommended for the DC’DC buck converter to assure a constant output voltage and to reject the disturbance from load and fuel cells stacks.
There are three different techniques to control the motor speed using; speed controller with Pulse Width Modulation (PWM), cascaded control with PWM and cascaded control with hysteresis current control.
When choosing PID parameters, ad-hoc methods are commonly used. These classical methods are better in providing some insight into the control design process, but more modern methods can be more effective. A multi-parameter optimization technique is used in this work for tuning gains of the PID controller, the result is less time and effort for tuning parameters and this proves that ad-hoc methods for tuning PID controllers over [3].
1.5 Electric Propulsion for EUAV
Electric machines advances in combination with electronics advances and electricity, are the basis of cofactors for electric UAVs. The electric motor is the main thrust component of a EUAV. Selecting a suitable type of motor with suitable rating is very important. These are the most commonly used motors for EUAVs: Switched reluctance machine, permanent magnet motor, induction machine, and Brushless DC motor. They have all been considered for different types of UAVs power applications [4]. Brushed DC motors, was popular for traction applications such as street cars, but are no longer considered a proper choice due to their bulky construction, relatively low efficiency, and their need for brush and commutator maintenance, high electromagnetic interference (EMI), lower reliability than other types, and limited relatively low speed range.
1.6 Literature Review
Although the long duration flight of fuel cell energized EUAVs have been realized only in recent five years, the conceptual design study of fuel cell energized EUAVs can be traced back to the 1980s. In 1984, NASA Langley Research Center published a conceptual design and a preliminary performance analysis of an unmanned airplane with multi-day endurance capability [5]. In the conceptual design, a mixed-mode electric power system was proposed with solar cells for daytime flight and fuel cells for nighttime flight. Based on the fuel cell technology at that time, the conceptual design study led to a class of airplanes with very low wing loadings and relatively long wing spans.
With many successful applications of the PEM fuel cells in the automotive industry, the conceptual designs of fuel cell powered UAVs in the 2000s were much closer to realization. In 2003, Jeffery conducted a performance assessment and an analytical feasibility of a fuel cell powered small electric aircraft based on the MCR-01 two-seater plane [6]. The results indicated that the flight with an off-the-shelf fuel cell may be possible with reduced speed, climb rate, range, and payload-carrying capabilities. Jeffery also highlighted the need for advanced technology of fuel cell to complete comparable reciprocating engine airplane performance. In the same year, researchers at Boeing Research & Technology – Europe initiated a fuel cell demonstrator design with a fuel cell/battery hybrid configuration [7]. A battery was needed for startup and takeoff assistance. The Boeing fuel cell demonstrator was completed in 2007, and flight was demonstrated in 2008 [8].
With the advancement of the fuel cell technology, researchers started to investigate the integrated design optimization of fuel cell energized UAVs. Among them, researchers from Georgia Tech contributed a series of papers on the multi-disciplinary design optimization of fuel cell energized UAVs [9]. They proposed a design method that optimized the design variables with respect to aircraft performance metrics. The mapping from the design variables to the aircraft performance metrics was based on subsystem level contribution analyses, in which empirical and physics-based models were used to model the subsystems. The design uncertainties were further reduced when the contribution analyses with considerable contribution to the performance metrics were validated through the experimental data. To validate the design methodology, the Georgia Tech researchers constructed and flight tested the Georgia Tech fuel cell aircraft demonstrator in 2008.
To improve the performance of fuel cell energized UAVs, many researchers have proposed a hybrid power system, in which both fuel cells and batteries are used for propulsion [10]. Fuel cells are well-known for (low power high energy) density. Batteries, on the other hand, have the properties of high power density and low energy density. The idea of hybridization allows the energy demand and power demand to be separated. Ref. [10] investigated the effect of such hybridization on the flight performance in a simulation, and concluded that the use of a fuel cell – battery hybrid system did not improve the endurance of a fuel cell energize UAV if the fuel cell system alone was sufficient to meet the power requirement. Ref. [11] also claimed that the only benefit of the hybrid power system was to decouple the design requirements of a climb flight from those of a cruise flight.
For conventional gas powered UAVs, researchers have realized that using a periodic flight path pattern can improve the endurance performance as compared to using a steady-state flight path pattern [12]. Ref. [13] confirmed this possibility for UAVs in a constant wind in 2009, in which the optimal periodic flight path was partitioned into a boost arc and a coast arc. Ref. [13] evaluated the same flight path pattern on a fuel cell powered UAV to maximize the flight endurance, which claimed that the optimal flight path for endurance was a steady level flight and that there wasn’t any benefit for a fuel cell powered UAV to fly in the periodic boost-coast flight path pattern. It seemed that trajectory optimization for a fuel cell powered UAV was not required. However, in real applications, many different flight paths other than steady state level flight are required to complete a flight mission. In addition, the dynamics of a fuel cell system on the optimal trajectories was not considered in [13]. The trajectory optimization for a fuel cell powered UAV can be appropriately addressed only if the dynamic constraints include the dynamics of a fuel cell system.
1.7 Organization of the Thesis
Thesis is divided into six chapters: chapter 2 emphasizes Traction System, while chapter 3 is the Supply system. In chapter 4, Monitoring and Interfacing System are introduced; System Controllers design and simulation are explained in chapter 5. Finally, chapter 6 is for the conclusion and future work.
CHAPTER (2)
PROPULSION SYSTEM
2.1 Introduction
Representing District for the work of the propulsion in electrical unmanned Air vehicles to replace the electric motor instead of the ICE and mounted on the electric engine fan blades, this works to push the aircraft at different speeds as a result of the special electric engine rpm. The propulsion system consists of brushless dc motor with six step inverter represents electric propulsion system. In chapter 1 we talked about the ICE and replace it using EM.
In general, the Electric motor plays a tremendous role in providing comfort to everyday life. Air conditioners (A/C), automobiles, fans, and power tools are just a few examples of systems that take advantage of the EM. In automobiles, power windows, power seats, and windshield wipers use EMs to make for a more pleasant driving experience. Cooling fans in computers are essential to maintain the temperature of today’s powerful digital signal processors (DSP’s) within safe limits. Air conditioning units would be highly ineffective without the help of an EM powered blower to circulate the cool or warm are throughout a living space. It is hard to imagine a time without these commodities since electric machines are found all around us. Advancements in power electronics have allowed for the development of advanced electric machines that be able to accomplish higher efficiencies and a wider range of operation with low maintenance requirements and high durability, for example the propulsion system of UAV. The drawback to these advanced machines is most noticeable in the added complexity due to the required power electronic converters that drive them. However, fundamental operation principles of a BLDC must be thoroughly understood.
Two similar definitions about the brushless DC motor (BLDC motor, BLDCM) have been presented by scholars. Some of them considered that only the trapezoid-Wave/square ‘ brushless motors could be called BLDC motors and Sine-Wave brushless motors is called permanent magnet synchronous motors (PMSM). However, other scholars thought that all the motors above should be considered as BLDC motor [1].
Due to high torque, high power to weight ratio, high-quality dynamic control for variable speed applications, no presence of brushes and commutator make Brushless dc (BLDC) motor, most excellent choice for high performance applications. Because of there is no brushes and commutator, consequently there is no trouble of mechanical wear of the moving parts [2], [3]. in addition, superior heat dissipation property and capability to operate at high speeds [4] make them superior to the conventional dc machine.
The application of motors has extended to all kinds of fields in nationwide economy and our everyday life as the main mechanical ‘ electrical energy-conversion device for more than a century. in order to adapt to different practical application , various types of motors, from several miliwatts to millions of kilowatts, including synchronous motors , induction motors , DC motors, switched reluctance motors and so on, emerge as the times require. although the synchronous motor has advantage of large torque, hard mechanical characteristic, high efficiency and precision. An induction motor has the advantages of simple construction, easy fabrication, reliable work and low price, but it is uneconomical to regulate the speed smoothly over a wide range and it is not easy to start up. Also, it is necessary to absorb the lagging field current from the power system.
2.2 Electric Motor Drives Overview
Over the years, electric motor drives have evolved from inefficient complex systems into drives that are easier to design and more versatile. Just a few decades ago, speed control was achieved by means of crude methods. Such methods include speed control via current limiting resistors introduced with mechanical or magnetic switches. Also, there were limitations in the selection process of a motor. If an ac motor were to be used in any application, it would have to have direct access to an alternative current (ac) source. Similarly, direct current (dc) motors were used mainly where access to a dc source was available. For many industrial applications, a dc motor was required with only the availability of an ac source. In such a case, the complex series configuration of an induction motor, dc generator, and dc motor was required. There are major expenses and inefficiencies with that set-up when compared to today’s motor drives. A modern electric motor drive system offers greater design flexibility and better overall system efficiency. Figure 2.1 is a block diagram representation of the major components that make up a modern electric motor drive system.
Figure 2.1 Block Diagram of an Electric Motor Drive
The major components are the power source, electronic converter, electric motor, mechanical load, and the controller. The power source is determined by the type of electricity that is available at the site for the electric motor drive system. For residential applications, the power source is two hundred and twenty volts alternating current. For automobile applications, a fourteen-volt direct current bus is available. The electronic converter has the task of converting the power source electricity type into that which is suitable to drive the electric motor. Electric motors are chosen to meet the torque and speed requirements of the mechanical load. The controller is design to ensure that the dynamic and steady state behavior of the motor is sufficient to match the performance demands required by the load.
Loads exhibit a wide range of torque characteristics. Some loads exhibit increased torque with increases in speed, while other loads may have the opposite behavior. In addition, the torque to speed relationship is often times non-linear. An example of a non-linear load that is highly dependant on speed is a propeller. Another load type when the torque is constant independent of its speed, such as a motor driving a water pump. The product of the torque and the speed gives the power consumed by any load. Some examples of non-linear loads are blowers and water pumps. Equation 2.1 relates power to the torque and speed for any rotation body.
P = T ” (2.1)
A variety of electric motors is available to match the performance requirements of any load. It is the task for design engineers, to choose motor type, which is best, suited for the load. Figure 2.2 summarizes the speed-torque characteristics of electric machines [5]. A low start-up torque, relative to its maximum torque, Tmax, characterizes induction motors. After the transient turn-on phase, an induction motor operates in the steady state region specified by the top portion of the curve. That operating region is mostly linear and very similar to that of a dc shunt and dc separately excited motor. Synchronous motors exhibit a constant speed under any torque condition. The speed is determined by its ac source and by the motor construction. In practice, exceeding the rated torque of a synchronous motor would certainly lower its speed and possibly damage the motor [5].
Figure 2.2 Speed vs. Torque Characteristic of Various Motors
A dc motor, connected in shunt or separately excited configuration, is characterized by small linear reductions in speed as the torque is increased. The speed-torque curve of a dc series motor is very similar to that of an automobile transmission. At low speeds, the series motor has the capability of providing a very high torque, while at high speeds the motor can only provide a small torque. The characteristics of a BLDC motor are essentially the same as that of a dc separately excited motor. Even though the motor construction is different, the operating principles are the same. The fundamental difference lies in that the current is commutated electronically by solid-state switches rather than mechanically via rotor contacts. The type of contacts normally used are wired brushes, however solid metallic spring loaded cubes may also be used to achieve mechanically controlled current commutation.
Brush technology for dc machines has been thoroughly investigated. Silver-graphite brushes arranged in parallel achieved safe current conduction of up to twenty kiloamps. However, that is a great feat allowing excellent machine performance, there is an unavoidable drawbacks to brushes. Current arcing translates to losses, which result in two problems. First, losses generating due to arcing raise the temperature of the brush-commutator system resulting in increased wear rate. Second, active machine cooling may be required to offset the temperature increase, which is costly and decreases system efficiency. Wearing of brushes may also increase the machine resistance (resulting in a significant plant variation), which can alter the performance characteristics for a motor drive system.
The power sources available for motor drives applications will be either an ac or a dc source. In ac sources, they have single-phase ac electrical energy at sixty hertz. Some may have three phase ac sources. These three phase power sources are essential in cases were high power consumption is the characteristic of a loads. a dc source, is most commonly found in a vehicle. The proposed unmanned air vehicle’s electronic system operates from a twelve-volt dc bus.
The function of a power electronic converter is to transform the available power source type into whatever power source is necessary to drive the motor. Converters add tremendous design flexibility when it comes to choosing an electric motor. For example, if a load is best suited to be driven by a dc motor and only an ac power source is available, then an ac to dc converter is used to link the to objects. The most common type of converters are shown in block diagram form, see Figure 2.3.
Figure 2.3 Common Power-Electronic Converters
At first glance, ac to ac converters may seem to be redundant systems, but these converters are required in some cases. For example, if the operating frequency of the motor must be something other than fifty hertz, then an ac to ac converter is required. Also, sometimes ac to ac converters are used to improve the quality of an ac source and to change the voltage amplitude. Similarly, dc-to-dc converters improve the quality of the voltage and have the ability to decrease or increase the voltage magnitude.
2.3 Power Electronic Driver Circuitry
Brushless-dc machines have multi-phase windings in the stator, however the most popular motor construction is that of a three-phase motor, namely phase a, b, and c. To achieve motor rotation, a waveform matching the back-emf must be applied to the three phases. For BLDC machines, the back-emf should be of trapezoidal shape as illustrated in Figure 2.4.The back-emf is a function of the rotor position ”r, which can be obtained from the hall-effect sensors. The ideal current waveform relative to rotor angular position is also given for each phase in Figure 2.4.
To produce the trapezoidal excitation voltage, a three-phase dc to ac inverter is required. For lower power drive systems, MOSFETs are used as shown in Figure 2.5, but for higher power systems, IGBTs are the switches of choice. The BLDC motor is connected as shown below and the MOSFET switching is summarized by the truth table derived from the hall-effect position sensors, see Table 2.1. The switching must follow the six-step sequence, however the first step was chosen arbitrarily.
Figure 2.4 Trapezoidal BLDC Motor Ideal Back-EMF and Current.
Figure 2.5 Three-Phase DC to AC Inverter
Table (2.1) Hall-Effect Truth Table for Switching
Switching interval Sequence no. Position sensors Switch closed Phase current
Hall a Hall b Hall c a b C
330-30 I 1 0 1 S5 S4 off – +
30-90 II 1 0 0 S1 S4 + – Off
90-150 III 1 1 0 S1 S6 + off –
150-210 IV 0 1 0 S3 S6 off + –
210-270 V 0 1 1 S3 S2 – + Off
270-330 VI 0 0 1 S5 S2 – off +
The power source in Figure 2.5 is typically a dc supply. Therefore, the purpose of the power electronic converter is to periodically apply a positive, negative, or zero dc supply voltage to the motor phase terminals to regulate the current injected into the motor phases [5].
2.4 Position Sensors
Brushless-dc machine operation requires of rotor position information to allow for appropriate solid-state switch firing. Three leading technologies are commonly used to fulfill the position information requirement. Those technologies are hall-effect sensors, resolvers, and optical encoders. The most commonly used sensor type is a hall-effect sensor set. They are low cost and provide position resolution to within thirty electrical degrees, which is adequate to operate a BLDC machine. If precise speed regulation is required, a higher resolution position sensor is required. Both optical resolvers and encoders offer much higher position resolution. The difference in the two sensors is most evident in their robustness under harsh mechanical environments. Resolvers can easily survive in automotive propulsion applications where high temperatures and extreme vibration is common. The position sensor type will always depend on the particular application. Often times, redundant position sensors are used to increase the survivability of the motor drive system [5].
2.4.1 HALL EFFECT SENSORS
When the magnetic poles of rotor pass close to the Hall sensors, they provide a low or high signal, representing the N or S pole is passing close to the sensors. Based on the mixture of three Hall sensor signals it is possible to determine the exact sequence of commutation.
Figure 2.6 the stator of BLDC motor
Figure 2.6 is an alternative N and S permanent magnet [10] shows a rotor, a cross-section of the BLDC motor. Hall sensors are embedded in the stationary part of the motor. In order to embed the Hall sensor in the stator, a deviation of the Hall sensors in relation to the rotor magnet, since an error in the determination of the rotor position is carried out, is a difficult process. In order to make simpler the process of mounting of the Hall sensor in the stator, the number of motors is the Hall sensor magnet on the rotor and may have a large magnetic rotor. They are scaled-down replica versions of the rotor. So every time the rotor rotates, causes the Hall sensor magnet, the same effects as the main attraction. Hall sensors are mounted typically on a circuit board; it is not fixed to the cap driving side. That because of achieving the best performance, so as to align the rotor magnet, can adjust the full assembly of the Hall sensor.
Figure 2.7 the view of Hall Effect sensors mounted on the shaft
2.4.2 HALL EFFECT SENSORS PRINCIPLE OF OPERATION
One simple method of determining the Hall sensors is to calculate the generated voltage from the Permanent magnet brushless dc motor and place the switching pattern of the Hall devices by using an oscilloscope. The angular positions are calculated, and the Hall devices are located at exact positions shown in Figure 2.7. In Figure 2.8 the positions for the coils are shown for a 6 slot stator with elements of the 6 coils located every 60o mechanical.
Figure 2.8 the location of Hall sensors at the beginning of the commutation cycle
Figure 2.8 and Table (2.1) show equivalent patterns for a full wave Y line configuration. a lot of other patterns are achievable, mainly with Hall devices that turn on and off for only N or S rotor magnet poles. The majority of BLDC motor designs use the rotor magnets’ leakage flux to energize the electronic switch. Though comparatively costly, the Hall device does posses temperature limitations (above 125o) [6].
2.5 Structures and Drive Circuits
2.5.1 Basic structures
The structure of modern brushless motors is extremely the same in the ac motor .Figure 2.9 illustrates the construction of a standard 3-phase BLDC motor. The windings of the stator are like those in a polyphase ac motor, and the rotor is consists of one or more permanent magnets. BLDC motors various from ac synchronous motors in that the former incorporates to find out the position of the rotor (or magnetic poles) to generate control signals to the electronic switches as shown in Figure 2.10. The most widespread position/pole sensor is the Hall element, however some motors use optical sensors. Although the mainly conventional and efficient motors are three-phase, two-phase BLDC motors are very regularly used for the simple structure and drive circuits [7].
Figure 2.9 Disassembled view of a brushless dc motor
Figure 2.10 Brushless dc motor = Permanent magnet ac motor + Electronic commutator
2.6 BLDC Machine Model
To evaluate the functionality of any controller, a precise model for the BLDC machine must be created and implemented in a computer simulation package. This chapter presents the steps taken towards the development of a precise machine model for a BLDC machine. Also, the power electronic converter was modeled in order to explicitly illustrate the current dynamics. A general model was created in MATLAB/SIMULINK to model any BLDC machine given the motor parameters (i.e. phase resistance/inductance, rotor inertia, torque sensitivity constant, etc.). Figure 2.11 illustrates the block diagram for representative motor drive setup.
Figure 2.11BLDC motor drive Simulink
The computer model must include the illustrated components, all of which are assumed ideal. Switching losses in the power electronic converter were neglected and all sensors (current, speed, and voltage) are assumed to be ideal. Therefore, no signal attenuation or delay was attributed to the feedback information [5].
2.7 Mathematical System description
2.7.1 Dynamic Model of the BLDC Motor
It is supposed that the output of the inverter is connected to the BLDC motor, while the inverter input terminals are linked to a constant voltage source. The equivalent circuit model of this circuit diagram is shown in Figure 2.12. Another assumption is that there is no loss power in the inverter and the 3-phase motor winding is a star connection.
Figure 2.12 Correspondent circuit of 3-phase PM BLDC motor.
The correspondent circuit shown in Figure 2.12 can be represented by the circuit diagram in Figure 2.13. The equations that govern this model are as follows:
v_A=v_N+v_sA
v_B=v_N+v_sB
v_C=v_N+v_sC (2.2)
Where:
vsA, vsB, vsC are the output voltages of the inverter that supply the 3 ‘ phase winding.
vA, vB, vC are the motor armature winding cross voltages.
vN ‘neutral point voltage.
Figure 2.13 Schematic representation of equation (‘2.2).
For a symmetrical winding and balanced system, the voltage equation across the motor winding is as follows:
[‘(v_A@v_B@v_C )]=[‘(R_A&0&0@0&R_B&0@0&0&R_C )][‘(i_A@i_B@i_C )]+d/dt [‘(L_A&L_AB&L_AC@L_BA&L_B&L_BC@L_CA&L_CB&L_C )][‘(i_A@i_B@i_C )]+[‘(e_A@e_B@e_C )] (2.3)
Since RA = RB = RC =R ,and inductors because the self and mutual inductances are consistent cylindrical surface permanent magnet rotor mounted and the coil is symmetrical:
L_A=L_B=L_C=L
L_AB=L_BC=L_CA=L_BA=L_AC=L_CB=M (2.4)
[‘(v_A@v_B@v_C )]=[‘(R&0&0@0&R&0@0&0&R)][‘(i_A@i_B@i_C )]+d/dt [‘(L&M&M@M&L&M@M&M&L)][‘(i_A@i_B@i_C )]+[‘(e_A@e_B@e_C )] (2.5)
For a Y-connected stator winding,
i_A+i_B+i_c=0 (2.6)
Therefore, the voltage takes the following form:
[‘(v_A@v_B@v_C )]=[‘(R&0&0@0&R&0@0&0&R)][‘(i_A@i_B@i_C )]+d/dt [‘(L_s&0&0@0&L_s&0@0&0&L_s )][‘(i_A@i_B@i_C )]+[‘(e_A@e_B@e_C )] (2.7)
Where :Ls =L’M is the synchronous inductance,
At anytime, the angle between a specific phase and the rotor. is called ”e.
Figure 2.14 clarifies the position of this angle, regarding phase A for instance. Since phase A is selected as the reference (see Figure 2.14), the electromotive forces described in the form of a matrix, the form Ea is:
E_a=K_E/p [‘(sin”_e@sin'(”_e-2/3 ”)@sin'(”_e-4/3 ”))] ‘d’_e/dt (2.8)
Figure 2.14 Explanation of the rotor position angle ”e.
for linking the input voltages and currents of the inverter with those of the output, the power equality equation, Pin = Pout is assumed at both sides.
So that, the input current of the inverter is:
i_sk=1/v_s (i_A v_sA+i_B v_sB+i_C v_sC) (2.9)
Where: vsA, vsB and vsC are the supply phase voltages.
The mechanical system shown in Figure 2.15 is defined as follows:
T_em=J_eq ‘d’_m/dt+B’_m+T_L (2.10)
Where J_eq=J_M+J_L is the equivalent moment of inertia, JM is motor moment of inertia, JL is the moments of inertia of the load, TL-load torque and B-friction coefficient [8].
Figure 2.15 Scheme of the mechanical system.
The electromagnetic torque for this 3-phase motor is reliant on the current (i), speed (”m) and electromotive force (e). The equation is:
T_em=(e_A i_A)/”_m +(e_B i_B)/”_m +(e_C i_C)/”_m =K_E (f_a (”_e )’i_A+f_b (”_e )’i_B+f_C (”_e )’i_C) (2.11)
Where,
f_a (”_e )=sin'(”_e )
f_b (”_e )=sin'(”_e-(2′)/3)
f_c (”_e )=sin'(”_e-(4’)/3) (2.12)
The function F (”_e) gives the trapizoidal waveform of the back-emf [9]. One period of this function can be written as
F(”_e )={‘(1 &0’_e<2”/3@1-6/” (”_e-2”/3)&2”/3’_e<”@'(-1 @-1+6/” (”_e-5”/3) )&'(‘_e<5”/3@5”/3’_e<2”))’ (2.13)
Integrating all the previous equations, the form of the system state-space is;
x ”=Ax+Bu (2.14)
x=[i_A i_B i_c ”_m ”_e ]^t (2.15)
x
(2.16)
(2.17)
u=[v_A v_B v_c T_L ]^t (2.18)
CHAPTER (3)
SUPPLY SYSTEM
3.1 Introduction
In the previous chapter, the BLDC motor has been selected to be the propulsive motor of the EUAV. The basic requirement for unmanned aircraft is a portable power source of electrical energy, which is transformed to mechanical energy in the electric motor for UAV propulsion.
Therefore various DC power supply sources are discussed in this chapter, highlighting their advantages and disadvantages, in order to select the proper DC power source to be considered as the EUAV supply system.
UAVs’ power supply sources must possess the following properties:
– High power and energy densities
– Fast dynamic response.
– High efficiency.
Defining the following terms to be used throughout the thesis; specific power density is the maximum available power that a supply can deliver per unit weight (W/kg) and per unit volume (W/L), respectively, while specific energy density is defined as the source’s energy storage capacity per unit weight (Wh/kg) and per unit volume (Wh/L), respectively [24].
The DC power supply sources to be discussed are: batteries, solar energy, super-capacitors and fuel cells.
3.2 Batteries
It is a constructed device from one or additional electrochemical cells with exterior connections to supply power to electrical devices [25].
In more details, a battery has a positive terminal (anode) and a negative terminal (-ve) terminal (cathode). The -ve terminal is the source of electrons that will flow and transfer energy to an external device while connected to an external circuit. When that connection happens, electrolytes are capable of move as ions within, permitting the chemical reactions to be fulfilled at the separate terminals and so supply energy to the external electric circuit. What allows current to flow out of the battery to achieve work is the movement of those ions within the battery [26]. Primary batteries (single-use or disposable) are used one time and discarded; the electrode materials are irrevocably changed during discharge. Secondary batteries (rechargeable) can be charged and discharged several times; the genuine composition of the electrodes may be recovered by reverse current. . Lead-acid and lithium-ion battery are examples of a secondary battery are used in UAVs and in portable electronics, respectively.
3.2.1 Battery Selection
The main types of rechargeable batteries used or being considered for electric and hybrid vehicle applications are:
1) Lead-acid.
2) Nickel-Cadmium (NiCd).
3) Nickel-metal-hydride (NiMH).
4) Sodium Sulfur (NaS).
5) Lithium-ion (Li-Ion).
3.2.1.1 Lead-Acid Battery
The oldest type of rechargeable battery is the lead-acid battery, founded by Gaston Plant” in 1859. The weight of the Lead-acid battery is a little concern, is more economical for large power application.
Lead acid batteries have many advantages such as; high reliability, high rates of discharge capability, low need for maintenance, low cost and low level of self-discharge. However, they have some drawbacks for example; they cannot be stored in a discharged condition, their electrolyte and lead content are environmentally unfriendly. Also, they have low energy density, poor cold temperature performance, in addition to their short calendar and limited full discharge cycles; are among the obstacles to their use in EUAVs.
3.2.1.2 Nickel-Cadmium Battery
This type of batteries has the advantages of superior low-temperature performance, flat discharge voltage, long life, excellent reliability, and low maintenance requirements. But their biggest drawbacks are the high cost and the toxicity contained in cadmium.
3.2.1.3 Nickel-Metal Hydride Battery
This type of batteries has approximately two times the energy content of lead-acid batteries of the same weight [26]. It also has a good average specific power and is also environmentally friendly.
About their disadvantages; they have relatively high cost and low cell efficiency. Electrode chare efficiency is highly affected by temperature, so there is a rapid drop in electrode charge efficiency at temperatures over 40”C. Also storage at high temperatures results in limited discharge current, degradation, limited service life, with deep cycles reducing life and high self discharge as a result.
3.2.1.4 Sodium Sulfur Battery
Sodium sulfur battery is considered the battery for the future for energy storage application, it was first developed starting l980’s. It exhibits high energy density and power, temperature stability, low cost and good safety [27].
Despite its several attractive features, there are several limitations; large size, the absence of an overcharge mechanism. Also its cell operating temperature is around 300oC, which requires adequate insulation as well as a thermal control unit.
3.2.1.5 Lithium-ion Battery
Li-Ion is the battery system in a rapid growth. Li Ion is used where high-energy density and low weight are important. They have high operating voltage levels, long cycle life, and low maintenance requirements. Their self discharge is relatively low. However they are expensive, very sensitive to over-voltages and over-discharges, and required a protection circuit which limits voltage.
3.2.2 Comparison among Battery Types for EUAV
A comparison among the mentioned types of batteries is made for some features; specific power, specific energy, energy efficiency and cycle life [28].
Table 3.1 Comparison among battery types
Battery type Specific power [W/Kg] Specific energy [Wh/Kg] Energy efficiency Cycle life
Lead-acid 150-400 35-50 80 500-1000
Nickel-Metal-Hydride 200-400 60-80 70 1000-2000
Sodium Sulfur 230 150-240 85 1000
Lithium-ion 200-350 90-160 > 90 > 1000
Based on the desirable features of batteries for EUAV applications, Table 3.1 shows that Li-Ion battery fulfills all the requirements, which makes it the most suitable choice among batteries. Also concerning gravimetric energy density, the Li-Ion technology is the best compared to nickel-cadmium, lead-acid, or nickel-metal-hydride. The nominal voltage of a Li-Ion cell is 3.7 V compared to 1.2 V for NiCd and NiMH and its capacity, in Ah depends on its size.
3.3 Solar Energy
Photo-voltaic (PV) panel is the solar energy source that converts the solar energy into electricity under insolation without any emissions. The PV panel is composed of the series and parallel connected solar cells.
The PV panel for the UAV application is required to have less weight and higher efficiency. Sizing of the PV panel should be done for the worst case of irradiance. The UAV should at least be able to work normally on the winter solstice day when the irradiance is the weakest among the whole year. Current PV cells are too inefficient and it would need a large area of cells to create even a small amount of electrical energy; consequently a large wing span is needed for fitting the PV on the wings which results in increasing the size of the UAV. Another disadvantage of using solar energy in reconnaissance UAVs is that its missions will be limited during day light only.
3.4 Supercapacitors
Supercapacitors (SCs) or ultracapacitors are energy storages having similarities with both batteries and conventional capacitors. SCs have many advantages such as; can be fully charged and discharged in seconds, almost linear voltage curves enables very accurate SOC estimations, and can be charged and discharged even up to a million times. They have a long shelf life, with low maintenance requirements, enhanced performance at low temperature, and environmental friendliness [26]. However, they have some drawbacks such as; they have very low energy densities, very high self-discharged, and their initial cost is very high.
3.5 Fuel Cells
An electrochemical device that transmits chemical energy of a reaction directly into electrical energy. Construction of the fuel cell consists of electrolyte layer in contact with the anode and cathode porous on either side. Electrical energy can be generated continuously long as they are provided with a fuel cell with fuel and oxidizer.
Since the establishment of the first fuel cell model by W.R. Grove in 1839, many sorts of fuel cells have been developed. The fuel cells are categorized according to the type of electrolyte used in the cells into [29]:
1) (AFC) Alkaline fuel cell
2) (DMFC) Direct methanol fuel cell
3) (PAFC) Phosphoric acid fuel cell
4) (MCFC) Molten carbonate fuel cell
5) (SOFC) Solid oxide fuel cell
6) (PEMFC) Proton exchange membrane fuel cell
3.5.1 Alkaline fuel cell
The AFC was one of the initial recent fuel cells to be developed, starting in 1960. The application at that time was to supply on-board electric power for the Apollo space vehicle.
AFCs have many advantages such as; excellent performance on hydrogen (H2) and oxygen (O2) compared to other candidate fuel cells due to its active O2 electrode kinetics and its elasticity to use a wide range of electro-catalysts. However, their electrolyte is highly sensitive to carbon dioxide (CO2) which necessitates the use of extremely pure H2 as a fuel [29].
3.5.2 Direct methanol fuel cell
DMFC is considered as a highly favorable power source. It has many advantages such as; lower cost, using a liquid fuel and quick refueling [30]. However, it has some drawbacks such as; efficiency is quite low for these cells, methanol is toxic, flammable and during the methanol oxidation reaction carbon monoxide (CO) is formed.
3.5.3 Phosphoric acid fuel cell
In PAFC, the phosphoric acid is used as the electrolyte, which operates at 150 to 220”C. At low temperatures, the phosphoric acid ion conductor is poor, and the electro-catalyst has a toxic co in the anode becomes severe.
PAFCs have a number of advantages for instance; less sensitive to CO than AFCs. The operating temperature is still sufficiently low to permit the use of common construction materials. Furthermore the working temperature provides substantial design flexibility for thermal management. In addition, the waste heat from PAFC can be readily used in most commercial and industrial cogeneration applications.
However, they have some drawbacks for example; cathode-side oxygen reduction is not faster than in AFC, and the use of a Platinum catalyst is required. PAFCs still need extensive fuel processing to accomplish good performance; this includes a water gas shift reactor. Finally, the highly detrimental nature of phosphoric acid need the use of costly materials in the stack.
3.5.4 Molten carbonate fuel cell
The MCFC electrolyte is normally a mixture of alkali carbonates, which is held in a ceramic matrix of LiAlO2. It works in 600 ‘ ~ 700 wherever the alkali carbonates form a greatly conductive molten salt, with carbonate ions providing ionic conduction. At higher operating temperatures in MCFCs, to promote reaction a Ni (anode) in combination with nickel oxide (cathode) are enough for the process. Noble metals are not required for operation.
The higher working temperature of the MCFC (up to 650”C) consequently no expensive electro-catalysts are needed. Both CO and certain hydrocarbons are suitable fuels for a MCFC, as they are converted to hydrogen within the stack, which improves the system efficiency. Also, high temperature waste heat enables the use of a bottoming cycle leading to further boost the system efficiency, are all considered advantages of MCFCs.
However, they have some drawbacks such as; the main challenge for MCFC developers stems from the very corrosive and mobile electrolyte. The higher temperatures reinforce material problems, affecting mechanical stability and stack life.
The main disadvantages of MCFC from the reconnaissance UAV applications point of view are the relatively large size and weight of MCFC, and slow start-up time.
3.5.5 Solid oxide fuel cell
The electrolyte in SOFC is a solid, impermeable metal oxide, generally Y2O3-stabilized ZrO2. The cell operates at 600-1000oC where ionic conduction by oxygen ions happens. usually, Co-ZrO2 or Ni-ZrO2 cermets are used as anode, and the Sr-doped LaMnO3 is used as cathode. SOFCs are considered for a wide range of applications, including stationary power generation, mobile power, auxiliary power for vehicles, and specialty applications.
Electrolyte is solid, so the cell can be casted into various shapes, planar, tubular, or monolithic are all available options. Cell corrosion problems are eliminated because of the solid ceramic construction of the unit. The materials used in SOFC are modest in cost. The high operating temperature allows use of most of the waste heat for cogeneration or in bottoming cycles.
However, the high temperature of the SOFC results in thermal expansion mismatches among materials, and difficult sealing between cells in the flat plate configurations. Corrosion of metal stack components is a challenge.
3.5.6 Proton exchange membrane fuel cell
Proton exchange membrane fuel cells, are gaining importance as the fuel cell for propulsion applications as a consequence of their low operating temperature, relatively high durability, higher power density, specific power, longevity, and efficiency.
The PEM fuel cell systems become the more suitable for electric vehicle applications for the following reasons:
PEM can be started easily at ordinary temperatures and can work at low temperatures, below 100”C.
Since they have relatively high power density, the size could be smaller.
Simple structure compared to other sorts of fuel cells, their maintenance could be simpler.
They can withstand the shock and vibrations because of their composite structure.
However, PEM fuel cells have some problems such as sensitive to sudden changes in the loads, slow dynamic response time and relatively long warming up time before full power output is available.
3.6 Comparison of the fuel cell types
A comparison among the previous mentioned fuel cell types is performed in terms of the operating temperature, power range and efficiency.
Table 3.2 Comparison of the fuel cell types
Fuel cell type Operating temperature (0C) applications Electrical power range (KW) Electrical efficiency (%)
Alkaline (AFC) 70-130 Space, military, mobile 0.1-50 50-70
Direct methanol (DMFC) 60-120 Portable, mobile 0.001-100 40
Phosphoric acid (PAFC) 175-210 Medium-to large-scale power and CHP 50-1,000 40-45
Molten carbonate (MCFC) 550-650 generation 200-100,000 50-60
Solid oxide (SOFC) 500-1,000 Medium-to large-scale power and CHP, vehicle APUs, off-grid power and micro-CHP 0.5-2,000 40-72
Proton exchange membrane (PEMFC) 60-80 Portable, space, low power generation 0.01-500 70-80
Based on the stated advantages and disadvantages of the fuel cell types in Section 3.5 and the comparison of Table 3.2, the PEMFC system is considered the most suitable choice among the fuel cell types for EUAV applications.
3.7 Hybrid power supply system
PEMFC is nowadays the most widespread fuel cell and it is the subject of the greatest development and the greatest number of applications, in particular in the field of electric vehicles, therefore it is chosen to be our EUAV primary energy source.
The ability to transiently store and redeliver high power levels is essential to the proper functioning of advanced propulsion systems. As mentioned before, among the problems associated to PEM fuel cells are the slow dynamic response time, and the relatively long warming up time before full power output is available. Therefore, some form of energy storage like a battery or supercapacitor with quick charge/discharge capability can be connected across the fuel cell system to provide supplemental power; i.e. to function as reliable power backup during any electrical load increase or decrease and also for system startup. Batteries are selected from the cost point-of-view to be the auxiliary energy source.
From the previous discussion, it was concluded that the energy density which is low in case of Li-Ion batteries is high in the case of PEMFCs, whereas the dynamic response time which is slow in case of PEMFCs is high in the case of Li-Ion batteries. Therefore, combining the PEMFC and the Li-Ion battery in one power supply system allows exploitation of the advantages of both devices and undermines their disadvantages. Hence a stack of PEMFCs; as a primary energy source, and a pack of Li-ion batteries; as a supplemental energy source, will constitute the hybrid supply system.
3.8 Construction and Modeling of PEMFC
Figure 3.1 Single PEMFC
A PEMFC consists of two electrodes (anode and cathode), with a solid polymer electrolyte membrane in between as shown in Figure 3.1.Hydrogen is injected at the anode and enters the electrolyte, leading to its ionization [31].
Anode:
(3.1)
Only protons are capable of passing through the electrolyte, so the protons pass through the electrolyte to the cathode in order to rejoin with oxygen, the freed electrons from the hydrogen atoms pass through an external circuit in order to recombine with oxygen at the cathode.
Cathode:
(3.2)
Finally, the overall chemical reaction is:
Heat + Electricity
(3.3)
The result is, hydrogen gas is recombining with oxygen gas in a process that produces electricity and water vapor as emission. This results in a closed loop system operated where the water from of the PEMFC can be electrolyzed forming hydrogen and oxygen for re-use later. Oxygen can be also obtained from the surrounding air.
Typically, a single fuel cell, can produce voltage between 0V and 1V depending on the polarization I-V curve; shown in Figure 3.2, which shows the relationship between output voltage and corresponding load current [32].
Figure 3.2 Polarization curve
This relation can be written as Equation (3.4) [33]. To produce a higher voltage, multiple cells have to be connected in series to build a stack of fuel cells. Figure 3.3 shows the fuel cell stack.
(3.4)
Figure 3.3 Simulink model of PEMFC stack
3.9 Construction and Modeling of Lithium-ion Battery Cell
Figure 3.4 shows the block diagram of the battery model used in the simulation.
Figure 3.4 Battery model block diagram
where
Icalc= Current drawn from the battery (A)
Vt = Terminal Voltage of the battery (V)
The State of Charge (SOC) represents the present capacity of the battery. It is the amount of capacity of the battery that remains after discharge from a top-of-charge condition [24]. Estimation of SOC of Battery is important, since it is used to predict the zero emissions range of the vehicle and developing the overall control strategy of the vehicle. The SOC of the battery pack is calculated from the initial state of charge (SOCinitial) and the battery current (Icalc) using the integral equation,
(3.5)
Where
SOC(t) = Instantaneous battery SOC (%)
SOCinitial = Initial battery SOC (%), at time = t0
(t – t0) = time interval under consideration (sec)
In order to integrate the Li-Ion battery into the simulation model, an equivalent electrical circuit-based model is developed. Circuit-based models use a combination of circuit elements like resistors, capacitors and dependant sources to give a circuit representation of the behavior and the functionality of the electrochemical cell. These parameters are generally determined by performing discharge and charge tests under controlled conditions, and monitoring voltage, current and temperature. Figure 3.5 shows the equivalent circuit of battery.
Figure 3.5 Lithium-ion battery model
Equations (3.6) and (3.7) are used for the model to represent a Li-Ion battery:
Discharge model (i* > 0)
(3.6)
Charge model (i* > 0)
(3.7)
where,
E0 = Constant voltage (V).
EBatt = Nonlinearity voltage (V)
Exp(s) = Exponential dynamics zone (V)
i* = Low frequency current (A).
i = Battery current (A).
K = Polarization constant (Ah’1).
it = Extracted capacity (Ah).
Sel(s) = the battery mode.
i.e. Sel(s) = 0 means battery discharge, Sel(s) = 1 means battery charging.
A = Exponential voltage (V).
Q = Battery capacity at Maximum (Ah).
B = Exponential capacity (Ah)’1
Figure 3.6 shows the Simulink model of the integrated SOC algorithm and the Li-Ion battery model.
Figure 3.6 Simulink model of lithium-ion battery
3.10 Summary
In this chapter, the most important energy storage devices; batteries, PVs, supercapacitors, and fuel cells, are discussed in detail. PEMFC as the most widespread technology of fuel cell is selected to be the EUAV primary energy source. But current PEMFCs cannot meet the requirements of fast dynamic response time, high peak power, low cost, and robustness. Therefore, a decision is made to hybrid the fuel cells with an auxiliary energy source like Li-Ion batteries to increase the overall energy efficiency of the EUAV supply system. Finally, the chapter presented the operational characteristics and the mathematical modeling of the PEMFC and the Li-Ion battery cell.
CHAPTER 4
INTERFACING AND CONTROL SYSTEM
Introduction
In the previous chapters, two systems of the whole electric propulsion system of the EUAV are discussed; specifically the supply system and the propulsive system. These two systems are connected to each other via a third system titled the ‘interfacing and control system’. This system is concerned with interfacing, monitoring, and controlling the activities of those two systems and other on-board accessories. Figure 4.1 shows the schematic of the complete EUAV propulsion system.
Figure 4.1: Schematic of EUAV propulsion system
In our case, the electric energy supply system is composed of a PEMFC stack and a Li-Ion battery pack, while the BLDC motor and its drive system comprise the propulsive system.
Fuel cell powered systems normally have a high current and a low voltage. Nevertheless, the stack output of the fuel cell is decided by the numbers of the cells in the stack and is generally not a standard voltage. Fuel cell stacks are also sensitive to abrupt changes in the loads; i.e. when the load increases, the fuel cell stacks voltage will steeply drop, which will affect the output voltage. Therefore, a DC-DC buck converter is proposed to stabilize the fuel cell stacks output voltage to be connected to the motor drive DC-link; in other words to ensure a constant output voltage and to cope with the sudden changes of loads.
High performance electrical drive systems are fundamental to modern electric vehicle propulsion systems [5]. The benefits accruing from the application of such drives are precision control of torque, and speed which promote superior electric vehicle dynamical performance [6]. consequently, both a speed controller and a current controller are proposed to control the motor performances.
4.2 DC-DC Buck Converter
Figure 4.2 shows a block diagram of a controlled buck converter. A single signal measurement is required to implement the voltage mode control of the buck converter. The reference voltage is compared to the sensed output voltage. The voltage controller is designed to make the output voltage track the reference regardless of component variations or disturbances in the compensator, pulse-width modulator, or converter power stage.
Figure 4.2 block diagram of a controlled DC-DC converter
The output Ec provides the duty ratio command for the buck converter switch T1 of this controller. This command output is used to estimate the suitable values for the timer compare registers in the PWM module. The PWM module uses this value to generate the PWM output and lastly drives the converter switch T1.
A basic buck converter shows in Figure 4.3 operates in two states (ON state and OFF state). When the switch is closed, the supply voltage Vs is connected to the inductor and the load voltage Vo. When the switch is open, the inductor transfers energy to the load resistor, decreasing the current through the system gradually. In this case, the inductor works as a source to the load keeping the flow of current in the circuit continuous.
Figure 4.3 Basic Buck Converter
The buck converter switch is mostly a power switch (transistor). PWM signal is connected to the transistor gate to control the switch ON and switch OFF state of the transistor. When the switch is ON, the supply voltage equals sum of the voltages across the inductor and the load resistor, and when it is OFF the voltages across the inductor equals the voltage across the load resistor. Varying the PWM signal between the two states the average output voltage can be controlled.
If the power device is switched at a frequency f = 1/T and conduction duty cycle D = (Ton) =T, where T is the periodic time.
The main function of the inductor is to supply constant power to the load resistor. When the switch is at OFF state, no power is supplied by the source voltage. At this stage inductor acts as a source transferring current to the load. This also reduces the abrupt change in current through the power switch when the switch in ON.
The capacitance acts as a low pass filter and must be sufficient enough to avoid voltage ripples and overshoots.
4.2.1 The States of Operation
In the ON state position, the switch is closed transferring energy from the source voltage to the inductor. At this stage, current through the inductor rises at a steady rate charging the inductor, as shown in Figure 4.4.
Figure 4.4 Buck Converter in ON State
In the OFF state, the switch is open and the inductor operates as a source maintaining steady transfer of energy to the load resistor. In this state, the diode conducts and current through the circuit decreases linearly as the inductor discharges, as shown in Figure 4.5.
Figure 4.5 Buck Converter in OFF State
Figure 4.6 Current across Different Components
Figure 4.6 shows the current across the diode (i_d), switch ( i_s) and the load (i_l) throughout the two states of operation of buck converter, where i0 represents the average current across the load.
4.3 DC-DC Buck Converter Controller
The duty cycle is the ratio of the output voltage to the input voltage considering the voltage applied on diode VF and transistor Vout as shown in Equation (4.1), and its value lies between 0 to 1.
(4.1)
The buck converter elements chosen criterion is explained as follows: the output capacitor (Cout) is chosen to filter the switching ripple; its capacitance should to be sufficently large so that impedance of the capacitance is much smaller than the load at the switching frequency, permitting most of the ripple current to flow through the capacitor, not the load. The output capacitor’s equivalent (RCout ) series resistance must also be taken into consideration because its parasitic resistance causes additional voltage ripple [18]. The output voltage ripple and the minimum output current Imin are assumed to be 1% of Vout and 10% of Iout, respectively:
The output power of the buck converter is:
P_out=V_out*I_out (4.2)
The voltage drop across RDSon is :
V_RDSon=R_DSon*I_out (4.3)
The conduction power losses of the switch PCOND is:
P_COND=R_DSon*I_RMS^2 (4.4)
Switching period (T) is:
T=1/f_SW (4.5)
On-time of the switch is:
T_on=D*T (4.6)
The minimum output capacitance value ( ) is calculated as follows:
(4.7)
The input capacitor (Cin) deals with highest ripple current. An acceptable level of the input voltage ripple is assumed to be 5% of input voltage Vin.
(4.8)
The minimum inductor value (Lmin) is calculated as follows:
(4.9)
According to the above equations, the buck converter simulink model built as shown in figure 4.7.
Figure 4.7 Buck Converter MATLAB/Simulink Model
4.4 Requirements on Propulsive System
Propulsive motors for an EUAV application demand certain characteristics as discussed in [1] and are listed as:
High torque and power density.
High starting torque.
Wide speed range.
High efficiency over wide speed and torque range including low torque operation.
High reliability and robustness appropriate to vehicle environment.
Acceptable cost.
Motor Drive System Controllers
In most propulsive applications, the drive system controllers of BLDC motor include both a speed controller and a current controller to control the motor performances. Block diagram of the propulsive system is shown in Figure 4.8
Figure 4.8 Block Diagram of the Propulsive System
4.5.1 Current Controller
In the BLDC motor drive as shown in Figure 4.9, the inner loop is a current control where the output motor current is measured directly. The torque is direct proportionate with current and is consequently directly controlled by the inner loop. The closed-loop current controller is the main core of the BLDC motor drive system. The function of the current control is to make the actual motor current follow the current reference signal. It does by comparing a feedback signal of actual motor current with the current reference.
Figure 4.9 BLDC Motor Drive
4.5.2 Speed Control
The outer loop in Figure 4.9 provides speed control. Proper rotation of BLDC motor is guaranteed by the electronic commutation circuit, but the speed of the motor depends on the amplitude of the voltage fed to the motor. Any divergence between the actual motor speed and reference speed is fed as an input to the speed controller. Based on this error signal, the controller produces a control signal for changing the ON-OFF time of the switching devices in the inverter thus control the voltage fed to the motor.
4.6 Structures of Motor Drive System
There are three structures for implementing the motor drive system. The inner current controller loop structure represents the difference among them. In the first structure, no current control is employed, and the duty cycle of the PWM is determined directly by the speed controller as shown in Figure 4.10.
Figure 4.10 Speed Control with PWM
In the second structure, a cascaded control with PWM consists of an outer speed controller and an inner current control loop, the inner current control loop is a current controller with pulse width modulator as shown in Figure 4.11,
Figure 4.11 Cascaded Control with PWM
In the third structure, a cascaded control with hysteresis current controller consists of an outer controller as a speed control and the inner current control loop is a hysteresis current controller with pulse width modulator as shown in Figure 4.12.
Figure 4.12 Cascaded Control with Hysteresis Current Control
4.7 Summary
In this chapter, the interfacing and control system is described. The procedures for designing a DC-DC buck converter with a detailed explanation for selecting criterion of its elements are presented. The drive system structures of BLDC are discussed for later designs in the next chapter.
CHAPTER (5)
CONTROLLERS DESIGN AND SIMULATION
Analysis and design of the monitoring and interfacing system component are presented in this chapter. These include the dc-dc buck converter that interfaces the fuel cell stack with the dc-link, and its associate controllers, and motor drive system controller using various control techniques; speed control with PWM, cascaded control with PWM and cascaded control with hysteresis current control.
MISSION SCENARIO
These several fling modes mission is utilized to show the capabilities and performances of the designed components.
The UAV’s mission involves several flying modes such as take-off, climbing, cruising, steady-state turning, descent and landing as shown in Figure 5.1. At start-up process, the Li-Ion battery is used to supply the power to the propulsive electric motor due to its fast dynamic response time of milliseconds. Then after 30 sec, the hydrogen fuel pump is switched ON to supply the fuel to the fuel cells, which in turn take about 30 seconds for the fuel cell reactions and the stack heating to reach power at maximum efficiency and hence the battery is switched OFF. The UAV’s mission begins with the take-off and climbing modes; using the elevator control surface, and lasts until the desired altitude is achieved. Then the UAV starts to fly horizontally towards the target destination using both the ailerons and rudder control surfaces.
After flying 9 min, the camera is switched ON to assure reaching the desired waypoint, followed with surveying using the reconnaissance devices for about 45 min. After finishing its mission, the UAV returns back to reach the landing site again using both the ailerons and rudder control surfaces, followed by descending mode using the elevator control surface.
The amounts of power consumed by the loads vary according to their resistant loads. Table 5.1 summarizes the scenario of UAV’s mission and illustrates the resistant loads of the propulsive BLDC motor [22], the control surfaces actuators and other loads.
Table 5.1 Scenario of UAV’s mission
Process Time interval [min] Description Source Loads
1 0 ‘ 1 Start up Battery ON Battery via buck BLDC
2 1 ‘ 1.15 Battery OFF Fuel cell via buck BLDC
3 1.15 ‘ 3 Climbing Fuel cell via buck BLDC + elevator
4 3 – 6 Horizontal flight Fuel cell via buck BLDC
5 6 ‘ 6.5 Turning Fuel cell via buck BLDC+ailerons+rudder
6 6.5 – 9 Horizontal flight Fuel cell via buck BLDC
7 9 ‘ 9.5 Picturing Fuel cell via buck BLDC +camera
8 9.5 – 10 Horizontal flight Fuel cell via buck BLDC
9 10 – 55 Reconnaissance Fuel cell via buck
Fuel cell directly BLDC
+ special devices
10 55 – 59 Horizontal flight Fuel cell via buck BLDC
11 59 – 60 Turning Fuel cell via buck BLDC+ailerons+rudder
12 60 – 75 Horizontal flight Fuel cell via buck BLDC
13 75 – 76 Turning Fuel cell via buck BLDC+ailerons+rudder
14 76 – 80 Horizontal flight Fuel cell via buck BLDC
15 80 – 82 Descending Fuel cell via buck BLDC + elevator
Figure 5.1 UAV mission scenario
Figure 5.2 Lithium-ion battery model
Li-Ion battery model is introduced in Figure 5.2 based on its output voltage (Vbatt) and state-of-charge equations. The output voltage is expressed as:
(5.1)
Where:
Voc and Ibatt are the battery open circuit voltage and current, respectively. Zeq is the battery equivalent internal impedance. The cell state-of-charge (SOC) is defined as the amount of charge stored within the cell at any instant in time [18]. The SOC of the battery pack is calculated from the initial state of charge as:
(5.2)
Where:
SOC(t) the Instantaneous battery SOC (%)
SOC initial the Initial battery SOC (%), at time = t0
(t – t0) the time interval under consideration (sec)
Q time independent between open-circuit voltage and SOC
The parameters of a Li-Ion battery cell (model no.:BP2546) are shown in Table 5.2 [19].
Table 5.2 Parameters of Lithium-ion battery
Nominal Voltage 3.7V
Rated Capacity 3350mAh
Charge Voltage 4.2V
5.2 DC-DC BUCK CONVERTER
The dc-dc buck converter is the interface between PEMFC stack and the DC-link. Fuel cell powered systems generally have a high current and a low voltage. However, the stack output of the fuel cell is determined by the numbers of the cells in the stack and is usually not a standard voltage. Fuel cell stacks are also sensitive to sudden changes in the loads; i.e. when the load increases, the fuel cell stacks voltage will drop steeply, which will affect the output voltage. Therefore, a DC’DC buck converter is proposed to step-down the fuel cell stacks output voltage to a desired value. To produce a higher voltage, multiple cells have to be connected in series to build a fuel cell stack. Figure 5.3 shows the used fuel cell stack, which comprises 24 cells; the parameters of each are listed in Table 5.3.
Table 5.3 Single PEMFC parameters
Open circuit voltage E 1.2 volt
Internal current density
2 mA/ cm2
Internal resistance r 0.00003 k’.cm2
Activation losses constant A 0.06 volt
Exchange current density
0.067 mA/ cm2
Concentration losses constant B 0.05 volt
Limit current density
900 mA/ cm2
Figure 5.3 Simulink model of PEMFC stack
Buck converter is a type of switching-mode power supply which is used for stepping-down DC voltage level. It uses two switches (a MOSFET and a diode), an inductor and a capacitor. In Figure 5.4, when a positive signal is applied at the MOSFET gate (g > 0), the DC input voltage Vin from the PEMFC is allowed to charge the inductor and to supply output voltage Vout across the output capacitor Cout. Charging will continue till Vout reaches to reference voltage Vref, then the control part turns OFF the switch (g = 0). The inductor will then change its voltage polarity and the current will flow in the same direction through the diode which is turned ON by switch controller part. Discharging will continue until Vout reaches below Vref, then control part again turns ON the MOSFET to compensate Vout drop and this cycle continues until complete regulation of Vout [17]. This process is accomplished by sensing the output voltage of the circuit by means of a negative feedback loop to the pulse-width-modulation (PWM) generator which controls the ON and OFF states of the MOSFET switches.
Controlling the switches, or in other words changing the duty cycle D to keep Vout equal to Vref can be explained as follows: the error voltage (VE =Vref – Vout) is compared to sawtooth ramp Vsaw generated by ramp generator, if voltage VE is higher than Vsaw as in Figure 5.4, the PWM generator reduces the duty cycle by holding ON the MOSFET gate for a short time of every cycle. While VE is lower than Vsaw, the PWM generator increases the duty cycle by holding ON the gate for the most of cycle to rectify the output voltage.
Figure 5.4 Buck converter control loop
The simulink model comprises of sources, sinks and various functional blocks. The model is represented using simple functional block so that the state space equations could be easily derived from the circuit. Instead, matlab built in state space block could also be used. In that case the data obtained does not match exactly but gives a similar behavior. The model is configured with a number of parameters as shown in Figure 5.4. The parameters are: the input capacitance, the load capacitance, the inductance, the internal resistance of each capacitor. The system model is highlighted in to two major segments: Pulse width modulator and buck converter system.
Figure 5.5 PWM Generator
as shown in Figure 5.5,There are two inputs to the model. The first input to the buck converter system is product of the constant voltage source and the duty cycle d. The duty cycle is the ration of the pulse width to the switching period. Figure 5.6 shows the pwm system which consists of a saw-tooth waveform generator, duty cycle command and a zero-crossing comparator.
Figure 5.6 PWM controlled input voltage
Controller design has centered mainly on simple, linear, proportional-integral-derivative (PID) controller. Although a PID controller is one of the earlier control strategies, it has a large range of applications in industrial control due to its easily implementation in the field environment.
A mathematical description of the PID controller is:
(5.3)
where u(t) is the input signal to the plant model, the error signal e(t) is defined as e(t) = r(t) ‘ y(t), y(t) is the output signal, and r(t) is the reference input signal. Kp, Ki, and Kd are the proportional, integral, and derivative gains, respectively.
5.3 PID Control by Ziegler and Nichols
Several empirical techniques have been developed but the widely used called Ziegler-Nichols techniques published in 1942 by John G.Ziegler and Nathaniel B.Nichols. In this thesis, empirical Z-N technique is used for the following reason:
It is popular today for its simplicity and applicability to a plan model.
It creates a set of tuning methods that translate the parameters of the constraints equation into controller parameters (P, I, D) to meet good performance levels.
It does not need to know the plant model with the reference of the Table 5.4, the tuning techniques are compared to each other in terms of advantages, disadvantages and algorithm of solution [7 and 11].
Table 5.4 PID Tuning Characteristic
Disadvantages
Advantages
Algorithm
Technique
-tuning procedures can be different
-Spend the time Simple Adding and Subtracting (K_p , K_i, K_d)
Trial and Error
Not applicable if the plant is so complicated and its mathematical model can’t be easily obtained. Accurate
Suitable for simple models
Mathematical model of plant
Analytical
Sometimes not applicable Suitable for unknown models Based on real plant
Empirical
The Ziegler-Nichols tuning is developed to provide a closed loop systems with good attenuation of load disturbances. There exist two techniques of Z-N tuning [15 and 16] the closed loop technique and the open loop technique. The transfer function of a PID controller has the following form:
(5.4)
Where Kc ‘ Kp is the proportional gain, and are the integral and derivative time constant, respectively. The controller gain is increased until a sustained oscillation takes place at gain Ku in the continuous cycling method [11 and13]. If the corresponding period of oscillation be Tu, then the parameters of the PID controller, as proposed by Ziegler and Nichols, can be calculated using Table 5.5.
Table 5.5 Z-N (continuous cycling method) Tuning Rules
Controller Parameters
Kc Ti Td
P 0.5 Ku
PI 0.45 Ku Tu/1.2
PID 0.6 Ku 0.5 Tu Tu/8
Ziegler and Nichols described in [12] two methods for tuning the parameters of PID controllers. These two methods are the Ziegler-Nichols’ closed loop method, and the Ziegler-Nichols ‘open loop method. Ziegler-Nichols’ closed loop method is applied on the system with feedback, when the system appears to involve some pure integration and/or dominant complex-conjugate poles; i.e. the response is similar to an under damped 2(nd) order response. The second method; Ziegler-Nichols’ open loop method or reaction curve method, is applied if the system’s response to a unit-step is S-shaped, indicating that the plant
Involves no pure integration and the system response is not dominated by a pair of complex-conjugate poles. This method is applied on the plant itself, without feedback [15]. The gains found by either Ziegler-Nichols’ method are regarded as starting point for a hand-tuning [13]. Hand-tuning method is a trial and error process that takes long time and effort to find the acceptable values relying on the experience and intuition of the engineers.
In this section, instead of using hand-tuning method, parameters of PID controller are tuned using SROS with gradient descent optimization technique. For setting up the tuning optimization process, initial values of PID gains are required. Since our plant does not involve any integrators nor dominant complex conjugate poles, these initial values are obtained from the Ziegler-Nichols’ open loop method. Briefly this method is considered as a way of relating the process parameters; delay time, process gain and time constant, to the controller gains. It has been developed for use on delay-followed-by-first-order-lag processes but can also be adapted to real processes [7].
Simulink Response Optimization Software (SROS) provides a GUI to assist in design of control and physical systems. With this product, optimization methods are used to adjust parameters within a nonlinear Simulink model to meet time-domain performance requirements by graphically placing constraints within a time-domain window and closely matching a reference signal [23].
Prior to the beginning of the optimization using SROS for the nonlinear system, the Signal Constraint block was connected to the V”_load signal as in Figure 5.4, where time domain constraints were placed graphically. The upper and lower constraint bounds in the Signal Constraint window were adjusted to ‘0.18; i.e., the output voltage signal was required to track the reference signal; 12V, within maximum absolute error of 0.18. For optimization method, the algorithm used was the gradient descent.
By starting the optimization, the SROS automatically converts the time domain constraints into a constrained optimization problem, and then solves the problem using the gradient descend method. The constrained optimization problem formulated by SROS iteratively calls for simulations of the nonlinear system, compares the results of the simulations with the constraint objectives, and uses gradient methods to adjust tuned PID gains to better meet the objectives.
After few iterations, an optimal and feasible solution was found. The obtained PID gains were 7.342, 29.5784, and 0.0087 related to Kp, Ki and Kd, respectively. The simulation results for the fuel cell output and converter output; are given in Figure 5.7-5.9.
When system starts, the PEMFC gives no output current (see Figure 5.10), therefore the propulsive BLDC motor is started using the battery only. One minute later, the fuel cell became capable of feeding the whole system thus the battery is disconnected. During horizontal flight as shown in Figure 5.7 and 5.8, the BLDC motor; the only load, is powered via the buck converter, the load output current drawn is 0.92A and the output voltage is 12V.
It is obvious from Figure 5.8 that the converter output current depends on the loads inserted to the system. When a sudden change occurred in the elevator actuator, the output current increased immediately to 1.32A and the output voltage decreased to 11.74V. Once this change is stopped, the output current is decreased and it is only needed to meet the requirement of the BLDC motor. When the load changed to two actuators; ailerons and rudder, the output current jumped to 1.72A. Similarly, using the camera raised the output current to 1.78A.
Since the spraying pump is powered directly from the fuel cell, therefore using the spraying pump in the interval [10:55] min affects the fuel cell output voltage and current as shown in Figure 5.9 and 5.10.
According to the equation for selection of internal component, table 5.5 summarizes the buck converter parameter.
Table 5.6 Buck converter parameters
Parameter Symbol Value Unit Parameter Symbol Value Unit
Converter output voltage Vout 12 V Duty cycle D 0.496
converter input voltage Vin 26 V Switching period T 20 ‘ sec
Nominal output current Iout 2 A On-time of the switch Ton 9.922 ‘ sec
Peak switching current Ipeak 2.2 A Inductor value used L 5650 ”
allowable Maximum peak-to-peak ripple Vripple 0.12 V Output bank capacitance Cout 166.67 ‘F
Drain to source resistance at switching on RDSon 0.1 ‘ Internal resistance of (Cout) used RCout 0.015 ‘
voltage drop across diode (in Forward) VF 0.8 V Capacitance of input bank Cin 500 ‘F
Voltage drop across RDSon VRDSon 0.2 V Internal resistance of (Cin) used RCin 0.1 ‘
Figure 5.7 Load output voltage
Figure 5.8 Load output current
Figure 5.9 PEMFC output voltage
Figure 5.10 PEMFC output current
5.4 MOTOR DRIVE SYSTEM CONTROLLERS
In this section, a comparative study of the performance characteristic of the BLDC motor using different control strategies will discuss. This comparative study done between:
Speed control with PWM,
Cascaded control with PWM,
Cascaded control with hysteresis current control.
The parameters used for the modeling BLDC motor (part no.: 80190502) are shown in Table 5.7 [10].
Table 5.7 BLDC motor technical specifications
Max. speed 8000 rpm Number of poles 4
Torque peak in 1160 mN.m Terminal resistance 0.24 ‘
Max.continuous torque 463 mN.m Torque constant 50.4 mN.m/A
Motor constant 103 mN.m/W Back-EMF constant 0.0504 V/(rad/s)
Rotor inertia 230 g.cm2 Inductance 0.6mH
The Simulink diagram; Figure 5.11, is drawn based on the standard electrical and mechanical equations of the BLDC motor found in a variety of standard references (see for example [8, 9]).
Figure 5.11 Simulink model of BLDC motor
The BLDC motor analysis is derived from the assumption for simplify and accuracy. The BLDC motor is kind of unsaturated. To complete the simulation of the speed control, a suitable model needs to be established. Anchored in the corresponding Hall effect sensor of BLDC motor shown in Figure 5.12, the BLDC motor dynamic equations can be derived as:
Figure 5.12 Hall Effect Constructions
5.4.1 SPEED CONTROL WITH PWM
Figure 5.13 shows the simulink block diagram of the closed loop operation of BLDC motor drive with speed control using PWM. Figure 5.14, 5.15 showed the control behavior of the motor under sudden change in load torque TL=0.2 NM at time 0.2 sec when speed reference is set at 4000 rpm. A torque of 1.4 NM is observed at the time of starting, at t= 0.004 motor continuous torque of 0.5 NM at time 0.05 sec. after a sudden change in load torque is applied At t=0.2 the Motor speed reached to set value of speed with in 0.05s with speed drop reaches 650 rpm from the reference speed as shown in Figure 5.14. The speed control with PWM technique is represented by single control loop with PI controller.
Figure 5.13 Speed control with PWM
After few iterations, an optimal and feasible solution was found. The obtained PI gains were 0.001 and 0.65 related to Kp and Ki, respectively. The simulation result for Speed control with PWM Figure 5.14 showed that the settling time 0.025 and the rise time 0.0185.
Figure 5.14 speed time characteristic of the drive
Figure 5.15 Output waveform of the torque of the motor
5.4.2 CASCADED CONTROL WITH PWM
Figure 5.16 Shows the simulink block diagram of the closed loop operation of BLDC motor drive with speed control using PWM, Cascaded control with PWM consists of the inner loop is a PI current controller and the outer loop represents a speed controller is a PI speed controller.
Figure 5.17, 5.18 showed that the control behavior of the motor under sudden change in load torque TL= 0.2 NM at time 0.2 sec when speed reference is set at 4000 rpm. A torque of 1NM is observed at the time of starting, at t= 0.00011 motor continuous torque of 0.5 NM at time 0.02 sec. after a sudden change in load torque is applied At t=0.2 the Motor speed reached to set value of speed with in 0.02s with speed drop reaches 241 rpm from the reference speed as shown in Figure 5.17.
Figure 5.16 Cascaded control with PWM
After few iterations, an optimal and feasible solution was found. The obtained PI current controller gains were 0.015 and 4 related to Kp and Ki, respectively and The obtained PI speed controller gains were 0.4 and 0.01 related to Kp and Ki, respectively The simulation result for Cascaded control with PWM Figure 5.17 showed that the settling time the settling time 0.0134 and the rise time 0.00795.
Figure 5.17 Cascaded control with PWM
Figure 5.18 Cascaded control with PWM
5.4.3 CASCADED CONTROL WITH HYSTERESIS CURRENT CONTROL
Figure 5.19 Shows the simulink block diagram of the closed loop operation of BLDC motor drive, Cascaded control with hysteresis current control consists of the inner loop is a hysteresis current controller with a hysteresis band h= 0.01 and the outer loop represents a speed controller is a PID speed controller.
Figure 5.22, 5.23 showed that control behavior of the motor under sudden change in load torque TL= 0.2 NM at time 0.2 sec when speed reference is set at 4000 rpm. A torque of 1NM is observed at the time of starting, at t= 0.0005 motor continuous torque of 0.45 NM at time 0.04 sec. after a sudden change in load torque is applied At t=0.2 the Motor speed reached to set value of speed with in 0.014s with speed drop reaches 40 rpm from the reference speed as shown in Figure 5.22 .
Figure 5.19 Cascaded control with hysteresis current control
The figure 5.20 shows an entire simulation of BLDC Motor Drive based on mathematical modeling. In this model, the trapezoidal back EMF waveforms are modeled as a function of rotor speed. The three phase currents are controlled to take a type of square waveform in order to synchronize with the trapezoidal back EMF to produce the constant torque according to the Hall sensor. By varying the current flow through the coil, the speed and torque of the motor can be adjusted. The most common way to control the current flow is to control the average current flow through the coil.
Table 5.8 Reference Current of BLDC motor
Rotor position ”
(Degree) Reference Current (A)
Iaref Ibref Icref
0-30 0 I I
30-90 I -I 0
90-150 I 0 -I
150-210 0 I -I
210-270 -I I 0
270-330 -I 0 I
330-360 0 -I I
The reference current as shown in table 5.8 is compared with the motor phase current in the inverter block in Figure 5.21 to obtain the desired voltage. The reference current for the three phase is I=2A.
Figure 5.20 BLDC Motor Drive Block
Figure 5.21 Inverter Block
After few iterations, an optimal and feasible solution was found. The obtained PID speed controller gains were 0.56, 3.3 and 0.005 related to Kp , Ki and Kd respectively The simulation result for Cascaded control with hysteresis current control Figure 5.22 show that the settling time 0.0271 and the rise time 0.0207
Figure 5.22 Cascaded control with hysteresis current control
Figure 5.23 Cascaded control with hysteresis current control
5.4.4 COMPARISON BETWEEN THREE CONTROL STRATEGIESS
The differences among the three control structures will be highlighted at the beginning (rise-time) and at the change in the load torque at 0.2 sec. Table 5.9 shows the comparison among the different three control structure.
Figure 5.24 Motor Speed
Figure 5.25 Output waveform of the torque of the motor
Table 5.9 Comparison among the control structures
Control structure
Comparative
item Speed control with PWM Cascaded control with PWM Cascaded control with hysteresis current control
Settling time 0.025 0.0134 0.0271
Rise time 0.0185 0.00795 0.0207
Speed drop during applying sudden load torque TL=0.2 NM 650 rpm 241 rpm 40 rpm
Time period to reach to a set value of speed after applying sudden load torque TL=0.2 NM 0.05 sec 0.02 sec 0.014 sec
As a result of the change of TL =0.2 at the time of 0.2 sec, found that the three control structure have accept behavior but the best one is the cascaded control with hysteresis current control.
CHAPTER (6)
Conclusions And Future work
6.1 Conclusion
Unmanned aerial vehicles (UAVs) have gained much popularity in several military and civilian applications. The requirements expected for an UAV to perform military missions; such as reconnaissance and surveillance, are the small size and low acoustic and heat emissions. These requirements are important for decreasing the possibility of visual, audio, and thermal.
Internal-combustion-engines are usually heavy weight, high acoustic and heat emissions, therefore powering UAVs with such engines is un-preferable. In this work, electric UAVs are proposed as alternative to internal-combustion-engine UAVs. Electric motors play significant role in electric UAVs’ propulsion systems.
Various electric energy sources are available for feeding the electric motors, include solar energy, hydrogen fuel cells and energy storage sources such as batteries and super capacitors. The advantages and disadvantages of each source are discussed for selecting of the optimal energy source.
Solar energy refers to the solar power collected from solar irradiance by photovoltaic cells. In addition to the dependence on the atmospheric conditions that makes the solar energy a lot less predictable, the requirement for long UAV’s wing-span for fixing photovoltaic cells results in increasing the UAV size, hence solar energy is undesirable for feeding the propulsion system. Super-capacitors usually have low power to weight ratio, and high self discharge rate, thus they are also excluded from our proposed energy supply system.
Batteries have many advantages such as; high power density, fast dynamic response time to fluctuations in a load, and low self-discharge properties. Unfortunately, batteries have some constraint to limit the pure battery driven vehicles; such as low energy density, long charging time, maintenance needs and limited lifetime.
Fuel cells, as renewable electric energy source, offer higher power and energy densities, lower cost, non-carbon emission, more-efficient power, lower acoustic and heat emissions, longer lifetime and are maintenance free. On the other hand, fuel cells have other disadvantages, such as; sensitivity to sudden changes in the loads, slow dynamic response time and relatively long warming up time before full power output is available. Therefore this thesis proposed a power supply system that combines fuel cells and batteries to allow exploitation of the advantages of both devices and undermines their disadvantages.
The electric motor is the main component of an electric UAV propulsion system. Selecting a proper type of motor with suitable rating is very important. Possible motor candidates for powering electric UAVs are: the induction motor, the switch reluctance motor, and the BLDC motor. BLDC motors are characterized by their capability of offering higher torque and power density together with higher reliability and efficiency, compactness, longer operating life, higher dynamic response, better speed versus torque characteristics, noiseless operation compared to the motors of the same size and other types and higher torque-to-weight ratio. Due to these advantages, BLDC motors are preferred for the electric UAVs as propulsion motors.
Complete electric UAV propulsions system is composed of BLDC motor, Inverter Bridge, rotor position sensor, controller and driver circuit.
Interfacing the fuel cell stack to the DC-link of the propulsion system requires stabilizing fuel cell stack output voltage. Therefore, a DC’DC buck converter is proposed to step-down the fuel cell stacks output voltage to a desired value. The selection criterion of the converter elements is explained and the design for the fuel cell is presented. For controlling the buck converter, a PID controller tuned by the gradient descend multi-parameter-optimization technique is designed. Simulation results verified the capability of the designed converter to maintain the fuel cell stack output voltage constant under sudden changes in the loads.
High performance electric motor drive systems are central to modern electric UAV propulsion systems. The benefits accruing from the application of such drives are precision control of torque and speed that promote superior electric UAV dynamical performance. The speed controller is designed using three different techniques; speed controller with PWM, cascaded control with PWM and cascaded control with hysteresis current control. A comparison among the three techniques is presented. Comparison proves that the three techniques have acceptable performances, and that the cascaded control with PWM has shortest rise time while the cascaded control with hysteresis current control has the best response during the sudden change in load torque (TL).
6.2 FUTURE WORK
The supply system is composed of a fuel cell stack as the main power source and batteries as the auxiliary power source to assist the propulsion of the vehicle during transients and to recover energy during deceleration. For future work, an onboard battery charger will be designed which consists of a bidirectional DC-DC converter which interfaces batteries to the DC bus.
Fuel cells are low-voltage high-current sources and therefore for future work, interfacing them with the high voltage of the DC-link of electric UAVs’ propulsion drives requires boost DC/DC converter.
In PEMFC, H2 is recombined with O2 producing electricity with water as a byproduct. For future work, a closed loop system will be designed whereby the water can be electrolyzed into oxygen and hydrogen for later re-use.
To improve the generating performance of the PEMFC and prolong its life, for future work, a controller will be designed to control the stack temperature.