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2015-IACC-0389
Test Bench Model and Algorithms for Multi-Sources Light Electric Vehicle Energy Management System M A Hannana*, F A Azidinb, A Mohameda and M. N. Uddinc a
Department of Electrical, Electronic & Systems Engineering Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia b Faculty of Electronics and Computer Engineering University Technical Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia c Department of Electrical Engineering, Lakehead University Thunder Bay, Ontario P7B 5E1, Canada
[email protected];
[email protected];
[email protected],
[email protected] Abstract – Due to the increasing awareness of oil depletion and the growing appreciation for green technology, electric vehicles (EVs) are now a widespread form of vehicle transportation. Single-source EVs such as battery electric vehicles (BEVs) have the drawbacks of limited life cycles and self-discharge. This paper proposes a test bench model to evaluate the performance of a multi-source light electric vehicle (LEV) energy management system (EMS) to overcome the shortcomings of single-source EVs. The EMS model contains intelligent switching controller hardware that is designed and implemented to select the most efficient energy source. The circuit board contains a DC chopper that can drive any DC load and is connected to a dSPACE DS1104 digital signal processor (DSP) for real-time data acquisition. Experimental results validate that the multi-source powered LEV can achieve both the standard drive cycles regulations ECE-47 and ECE-15. To evaluate the power efficiency in the extended ECE-47 cycle, the multi-source LEV performs better than that of a single source vehicle, with approximately 6% power efficiency. Thus, this research demonstrates that the proposed EMS based multi-source EV could be a potential candidate for future vehicle applications.
Keywords – Test bench model; multi-source; light electric vehicle; control algorithm; energy management system. I. INTRODUCTION In recent decades, there has been growing interest in the development of EVs that use renewable energy. However, there is a great challenge as no renewable energy sources can match the fossil fuel power used in the conventional internal combustion engine (ICE). Gasoline is a good alternative in terms of delivering equal power, but it leads to harmful environmental problems such as greenhouse gases (GHG) and global warming [1-2]. Thus, the use of gasoline as a fuel for transportation is definitely not favored [3-4]. As a compromise, the use of gasoline has been reduced by combining an ICE with an electric motor in the so-called hybrid vehicle (HV). Today, the HVs are sold with a hybridization factor (HF) ranging from 0.03 to 0.64 [5-6]. Further research is still ongoing to design all-electric vehicles (AEVs) that are compatible with commercial cars. Single-source EVs, such as the BEV and the fuel cell electric vehicle (FCV) have many problems. For example, a suitable battery for a high-power vehicle and a fast recharging process that requires only a few minutes are difficult to produce. Self-discharge and lifecycles that weaken
the capacity of the battery are also a matter of concern [7]. On the positive side, batteries respond very well when high current is requested. For an FCV, low power response and fuel starvation are critical, especially given the dynamic power demand in a vehicle application [8]. In other aspects, an FCV offers a better vehicle range and a fast refueling time. Therefore, this paper proposes a new technique of multiple source hybridization for light electric vehicle applications [9]. A study on the hybridization of power systems for LEVs was reported by Hwang and Chang [10]. Their study focused on the power characteristics of the combination of a proton exchange membrane (PEM) fuel cell (FC) at a rated power of 6 kW and a lithium-ion battery module that contains four 12 V, 40 Ah cells that deliver power equal to 2.7 kW. The main propulsion power comes from the PEMFC, and the battery is used as an auxiliary power supply when high power demand or regenerative braking occurs. The vehicle is tested under various conditions such as idling, starting acceleration, and braking. The battery thus manages to counterbalance the power during power shortages that arise while using the PEMFC, and it offers storage during regenerative braking. The use of a lithium-ion battery increases the power efficiency by up to 46%. In [11] Tang et al. also investigated an hybrid system in which a PEMFC of 2 kW capacity was combined with a pack of lead acid batteries with a single battery capacity of 250 Ah at 6 V. That study focused on the current and voltage dynamic response of the PEMFC with and without assistance from the battery. During the vehicle test, the battery assisted with power output when the external load was exerting the PEMFC during acceleration and climbing conditions. The resulting system satisfies the requirements of vehicular power demand. Thus, it can be concluded that the hybridization of power sources improves the power efficiency of electric vehicles. Li et al. published a study of an energy management strategy for a hybrid vehicle to enhance fuel economy [12]. Fuzzy control was applied in the study of hybridization of an FC/battery and FC/battery/super-capacitors (SC). The hybrid vehicle system was simulated using advanced vehicle simulator (ADVISOR). The proposed strategy was tested against a standard driving cycle. The results show that the combination of FC/battery/SC delivers the most economic fuel, with hydrogen consumption at 5-30% for four types of
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driving cycles. Thus, the hybridization of power sources shows promise for use in hybrid electric vehicle design. However, the proposed control strategies had not adequately considered the balance between fuel economy and dynamic property of hybrid vehicle. Furthermore, an appropriate intelligent control strategy had not been proposed for a hybrid vehicle [13]. This paper is focused on the development of a test bench model of a multi-source LEV energy management system (EMS) using intelligent control algorithm to enhance the performance of the hybrid vehicle. II. TEST BENCH MODEL FOR THE PROPOSED EMS The basic multi-source energy system for a light electric vehicle (LEV) is shown in Fig. 1. The concept behind such a system is to incorporate more than one energy source and to use an intelligent energy management system (EMS) that uses a controller to activate one or any combination of the available sources as appropriate to the current vehicle and driving conditions [13]. A DC-DC converter is used to maintain the DC voltage obtained from the multiple sources at a value that is consistent with the machine-rated voltage and to step down the voltage to 5-12 V DC for interface circuits such as the bridge driver and sensors [14]. Electric motors that are commonly used for HEV are the DC excited motor, the AC synchronous motor and the internal permanent magnet (IPM) synchronous motor [15]. The power electronics prepare the signal to control the motor speed. The prototype switching controller for multi-energy sources for a hybrid light electric vehicle was built based on DS1104 controller board that is integrated with MATLAB/Simulink software tools [16]. This integrated environment offers many advantages, such as the fact that the source code can be written in the form of a simple block diagram in Simulink to enable the automatic generation of the interface between the source code and the hardware [17]. Thus, the test bench model based on DSP board DS1104 can be considered similar to a real-life application.
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and sent to the DSP board DS1104 for evaluation. The control algorithm and vehicle system modeling are implemented in MATLAB/Simulink. The three input sensors for a control algorithm of the EMS are the speed pedal, the battery SOC and the load current. The analog/digital converter (ADC) placed in DS 1104 converts the three analog input signals into digital signals for further input signal processing in MATLAB/Simulink. Then, the output from the control algorithm communicates with the switch controller to select the appropriate energy source to produce a PWM signal for a motor drive. The I/O and PWM peripherals in dSPACE offer a bridge between the output signal from the software tools and the hardware. III. SYSTEM INTEGRATION The MATLAB/Simulink integrated real-time interface (RTI) platform in the dSPACE control desk has the tasks of preparing the input sensor signal, determining the output of the control algorithm based on the sensor signal, controlling the PWM output and processing the vehicle system. The details of each component are explained in the following section. A. Sensors Signals As mentioned previously, there are three sensor signals in the multi-source LEV: pedal speed detection, load detection and battery state of charge (SOC). The voltage signal evaluation for the speed pedal offset is between 0-5 V analog. After passing through the A/D converter in the DS1104 peripherals, the signal is reduced to 0-0.5 V digital. This signal is amplified and filtered to reduce noise and increase its stability. Then, this speed signal is linked directly to trigger the SC. The speed pedal offset signal Po(t) can be defined as: § A · PO ( t ) = ¨ ¸ ⋅ u ( t ) ⋅ T1 © 1 + st ¹
(1)
where, u(t) is the signal from the A/D converter, t is the cutoff signal in the time domain, A is the amplification parameter and T1 is the time set by the timer relay for the SC. The power demand is measured from the current flow to the load, which depends on the offset of the speed pedal. The power demand needs to be filtered and amplified. Then, the load current signal is propagated down two paths. The first path is connected to a timer relay that activates the FC. The timer is adjusted to rely on the FC start time and a high load current interval. The equation for the power demand signal PD(t) is given by: Fig. 1. Block diagram of the basic multi-source LEV test bench model.
The multi-energy sources are a battery, a PEMFC and an SC. The EMS circuit board consists of a switching controller that can select the best energy source. The voltage source is linked to a half-bridge single-phased inverter that controls the average voltage to be sent to the load. A car light is used in place of a DC motor. The current flow to the load is detected
§ B · (2) PD ( t ) = ¨ ¸ ⋅ u (t ) ⋅ T2 © 1 + st ¹ where, T2 is the time set for the timer relay for the FC and B is the amplification parameter. The other path of the load current is used for the GUI interface to show the actual current value. The voltage signal
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is linearized with an analog ampere meter to obtain the right current measurement in amperes. During the experiment, the analog ampere meter is linked in series with the load. The load current iL(t) is related to the voltage measurement of the sensor as: i L (t ) = C ⋅ u (t )
(3)
where, C is the linearization parameter. The third signal from the A/D converter is used to measure the battery capacity as a percentage of the SOC. After going through the same step as the load current signal, its SOC equation can be described as [18]: § 100 * i ( t ) ⋅ t · (4) ¸¸ SOC = 100 − ¨¨ Q ¹ © where i(t) is the battery current, Q is the battery capacity in ampere-seconds and t is the time in seconds. B. Control Algorithms The three energy sources in this LEV test bench model are controlled by three switches that are managed by the control algorithm implemented in the EMS. A control algorithm is designed to deliver the right amount of power to the vehicle’s DC motor based on the current load and the driving conditions while maximizing energy conservation. The operational control strategies are based on eight operational states. Based on these states, either one or combinations of energy sources are activated to drive the vehicle. The three inputs come from the three basic operational input conditions: the speed pedal (PO) from the pedal offset, the high power demand (PD) from the load current and the battery capacity (BC) from the SOC. Within this system, the battery acts as the principal energy source, and its capacity becomes the critical point for changing states. Table-I presents the proposed control states that are based on the source and vehicle conditions. The states are defined to fulfill the load demand while maintaining the high performance of the vehicle. In this system, the FC is activated by the ON or OFF switch level, which causes the energy from the FC to be supplied at a full level or not at all. A sample of energy flow in the EMS based on the proposed control algorithm is shown in Fig. 2. The system starts by checking the three input sensors, namely the pedal offset (PO), the battery capacity from SOC (BC) and the power demand (PD) through the load current. Before the vehicle starts moving, both PO and PD are supposed to be low. The vehicle is powered by the FC in case the BC is low or by the battery itself if the BC is high. If the BC or the battery SOC is at a critical level, then the vehicle is powered by the FC. If there is an increase in PO, then the SC is activated to support the FC and avoid fuel starvation in the FC. If the BC is recovered again through a plug-in charge or excess energy from the FC, then the battery takes over from the FC to power up the vehicle. During this stage, if the PO and PD are both high, all of the energy sources are activated. Each time the FC is activated, the SC is automatically
triggered to momentarily compensate for the FC start delay time. Table-I: States and vehicle conditions for EMS operation State 1
Description Battery SOC level is low. Vehicle is powered by FC only since pedal offset is low and no extensive power is required. 2 Vehicle is powered by both FC and SC. It will return to state 1 after SC tank is emptied. 3 Battery cannot support FC since SOC level is low. Output result is like state 1. 4 The battery SOC is at critical level and cannot be activated. FC and SC are active and vehicle condition stays at the state 1 after SC is triggered. 5 Only battery is used to drive the motor since no high power demand or higher speed is requested. FC is reserved and will be activated in case battery charge is low. 6 In this state, vehicle accelerates and is therefore supported by both battery and SC. It will return to state 5 once all energy in SC is emptied. 7 More loads are exerted on the vehicle and consequently FC is triggered as secondary energy source to support battery. 8 Vehicle accelerates with increased load and thus causes all three of its energy sources to be switched on. * For every FC activation, SC is active to support FC start time
All of the operational states are described in the logic equations as shown in Table-II. Similarly, there are three logic inputs and three logic outputs. The logic inputs are based on detectors that recognize the vehicle’s instantaneous condition, and the logic outputs represent the selection of the energy source to be activated. Table-II: Logic table for EMS operation State 1 2 3 4 5 6 7 8
BC 0 0 0 0 1 1 1 1
Input Conditions PD 0 0 1 1 0 0 1 1
PO 0 1 0 1 0 1 0 1
SC 0 1 0 1 0 1 0 1
Output Conditions FC Battery 1 0 1 0 1 0 1 0 0 1 0 1 1 1 1 1
Fig. 2. Energy flow process in the EMS.
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C. Vehicle System The vehicle model design is based on LEVs such as autorickshaws or battery-scooters. The load of this electric vehicle project is a 55 W light car. The current flow to the load is assembled as an armature current flow to the DC machine. Electrical power, Pel and electromechanical torque, Te generated by the DC machine can be defined as:
Pel = V rated ⋅ I a
(5)
(6) Te = K T ⋅ I a where Vrated is the motor rated voltage, Ia is the armature current and KT is the torque constant. The dynamic equation for the motor is given by: dw (7) J = Te − T L − B m ω − T f dt where, Ȧ is the motor speed, Te is the developed torque, J is the total inertia, TL is the input torque, Bm is the viscous friction coefficient and Tf is the Coulombic frictional torque. The motor speed is evaluated using a vehicle model in MATLAB/Simulink. The vehicle model is designed based on three-wheeled LEVs such as auto-rickshaws or batteryscooters. Several forces that occurred during vehicle movement reduced the motor torque and its speed. The motor speed is linked through a gear ratio and the radius of the vehicle’s drive wheel. The vehicle linear velocity, v, is related to the rotational motor speed, Ȧ, tire radius, r, and the gear ratio, G, as [19]: r (8) v= ω G The forces that are present during vehicle acceleration are an acceleration force, Fa, an air friction force, Fr, a wheel friction force, Ft, and the gravitational force, Fe, as follows [20]: dv (9) Fa = m dt (10) F r = 0 . 5 ⋅ cd ⋅ d ⋅ A ⋅ v 2 F t = μ r ⋅ m ⋅ g ⋅ cos α
(11)
Fe = m ⋅ g ⋅ sin α
(12)
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The vehicle starts moving when the power of the electric motor is greater than the power of the vehicle. This can be defined as [21],
Pel ≥ Pveh
(15)
D. PWM control linearization The signal from the speed pedal is filtered and amplified to ensure its stability. Then, a calculation is performed to determine the correct linearization of the duty cycle for the PWM signal through the pedal offset, as follows: § A · (16) Pwm ( t ) = ¨ ¸ ⋅ u (t ) ⋅ B − 1 © 1 + st ¹ where, Pwm(t) is the duty cycle, u(t) is the pedal offset and A and B are the parameter gain and linearization, respectively. Then, the signal is linked to the PWM duty cycle block of the DS1104 DSP.
IV. TEST BENCH MODEL CONFIGURATION The test bench model for the proposed EMS is implemented using dSPACE DSP DS1104 controller board as shown in Fig. 3. The DSP board provides the interface to various sensors and actuators and comes with a graphical user interface (GUI) for data acquisition. The graphical presentation runs on the Windows platform and allows users to link the DS1104 peripherals via a simple drag-and-drop method. For this reason, the experiment runs completely on the real-time hardware through DS1104 board. The DS1104 board is mounted within the PCI slot of the personal computer (PC). The DS1104 software driver, called dSPACE Control Desk, is installed on the PC together with MATLAB/Simulink. The dSPACE Control Desk enables controlling and monitoring of the experimental parameters in real-time. The DS1104 peripherals are linked to the Simulink block to provide a graphical presentation in the GUI. Some of the peripherals that are available on the DS1104 for a motor drive system are digital I/O, A/D, D/A, PWM and an incremental encoder.
where m is the vehicle mass, A is the frontal area, d is the density of air, cd is the drag coefficient, ȝr is the rolling coefficient, g is the acceleration due to gravity and Į is the angle. The vehicle power, Pveh, is related to the total force, Ftotal, and linear velocity, v (depending on the drive cycle) as: F total = F a + F r + F t + F e
(13) Fig. 3. Test bench hardware configurations.
Pveh = F total ⋅ v
(14)
The EMS control circuit board is built with a voltage
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regulator, a Relay SONGLE, a Power MOSFET, a halfbridge driver, a variable resistor (Pedal Offset), Hex Buffers and Inverters and I/O connectors. A Tektronix TDS2024B digital oscilloscope is used to measure the PWM signal to the load. As the current sensor measures the current via voltage, an ampere meter is connected in series to monitor the voltage measurement from the current sensor.
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B. Test Bench Result and Discussion The system under test is compared against the ECE-47 drive cycle [22], as shown in Fig. 4. It can be clearly observed that a single-powered source with a battery or an FC of the multi-source LEV is able to follow the drive cycle. According to the flowchart shown in Fig.2, the vehicle starts by detecting the battery SOC. If it is high, then the vehicle is powered by the battery alone. Otherwise, the FC is used to power the vehicle. A multi-source powered LEV does not necessarily mean that multiple sources are activated simultaneously. The energy sources can be activated individually or in combination based on the driving and load conditions. At the beginning of the drive, the system acts as a single-powered vehicle, namely a single battery-powered or single FC-powered system. In Fig. 4, both vehicle systems manage to follow the start acceleration of the ECE-47 drive cycle with a small over-power when the speed is higher than 48 km/h.
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Both systems then slowly decelerate to follow the standard course. After 56 s, both sources are able to handle sharp braking, which is used to follow the drive cycle. Then, at a constant speed of 20 km/h, a small fluctuation is observed in both systems at the beginning of the phase, but this fluctuation continues until the middle of the phase for the FC system. At the end of the test cycle, both systems successfully stop alongside the ECE-47. The switching times of the energy sources for the battery-only powered vehicle and the FC-only powered vehicle can be observed in Figs. 5a and 5b, respectively. The activated source is the low active configuration in the logic system. Fig. 8 shows the current flow from the battery and the FC when the vehicle is trailing the ECE-47 drive cycle. The battery current rises higher than 2 A before settling down to 1.8 A. On the FC system, the current escalates to 2 A and then fluctuates down a little to 1.8 A.
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A. Experimental Setup The test bench model is a small-scale lab test model that is used primarily to conduct real-time process experiments on a multi-source LEV. The model is down-scaled from a 3-5 kW LEV to a 55 W lab test due to technical and facilities constraints. The vehicle weight and all available mechanical forces are also proportionally down-scaled. The energy sources that are implemented are a sealed lead acid (SLA) 12 V 3 Ah battery, a H-30 (30 W) FC from Horizon Fuel Cell technologies and a 2.5 V 50 F (1x5) super-capacitor set from Tecate Group. The current through the load is evaluated in the dSPACE control desk, which is linked in MATLAB/Simulink, and is then presented as a moving vehicle in the GUI.
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A test bench model is attempted to implement a real LEV moving on the open road. The LEV driver needs to control the vehicle speed by turning the throttle or the pedal speed manually. In order to compare the proposed work with other published works, the vehicle speed is controlled using the ADVISOR or other advanced simulation tools. In this test bench model, a human sets the vehicle speed. Thus, every test drive cycle has the unique result, depending on the user’s driving skills. Three test drive cycles (ECE-47, ECE-47ext and ECE-15) are tested for the power efficiency performance and to observe the power sharing of the multi-source vehicle.
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(b) Fig. 5. Switching time of multi-source LEV driven by: (a) single batterypowered, and (b) single FC-powered
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Fig. 6. Load current from battery and FC during drive cycle ECE-47
The next multi-source LEV test is for the condition where the battery SOC level is below 52%, as observed in Fig. 7. Initially, the multi-source LEV starts with battery-only power, which represents state 5 in the control algorithm. After 35 s, the battery SOC level decreases to 50%, this causes the FC to be activated together with the SC. This state is described in the control algorithm as state 2. After another 3 s, the SC is deactivated, and the vehicle is powered by the FC alone. This condition is presented as state 1. Next, after another 40 s, the SC is activated again due to the PO demand. This situation represents state 4 of the control algorithm logic. Subsequently, the system returns to state 1 until the end of the drive cycle. The changing of the corresponding logic states can be observed in Fig. 8.
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Fig. 8. State changing during test against drive cycle ECE-47 when battery SOC level below 52%.
The current and the battery SOC level for the multi source LEV are shown in Figs. 9 and 10, respectively. The current increases until it reaches a maximum of 2 A and then stays at 1.75 A to enable a constant vehicle speed of 48 km/h. Then, after 35 s, the FC overtakes the battery to power the vehicle. When trying to maintain a vehicle speed of 38 s, the tester accidently lessens the current and forces the vehicle speed to suddenly drop away from the drive cycle. Simultaneously, it increases the pedal offset too much, which results in PO detection and triggers the SC. This action explains the spike current observed after 40 s to recover the loss of vehicle speed. If the system is a single-source FC, a request for the FC to produce such a spike current may cause fuel starvation if there is no support from another energy source. Thereafter, the current is controlled to follow the vehicle drive cycle. As shown in Fig. 11, the SOC level drops significantly as the energy is being consumed from the battery. After 35 s, when the system reaches 50% of its SOC, the FC is triggered. 2. 5
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The FC current is observed to have a current drop every 10 s, which is due to water resulting from the hydrogen reaction in the FC that is pumped out from the cell. For every pump out, the hydrogen supply stops for one second. This process is necessary to avoid water congestion in the cell and to prolong the FC cell lifetime. After 50 s, the test starts, and both currents slowly decline and reach a constant 0.75 A. Here, the battery’s current is more consistent and experiences less fluctuation as compared to the FC’s current. Finally, after 100 s, both currents are reduced to 0 A as shown in Fig. 6. To test the performance of the vehicle in regenerative braking mode a resistor load is applied when load currents reach 0 A, but the vehicle still moves due to inertia. The calculation is the reverse of converting the armature current to the angular velocity through Eqs. (5) - (7). The observed negative current is the result of the estimated regenerated energy from the moving vehicle.
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Fig. 9. The load current of multi-source LEV during test against the drive cycle ECE-47 53
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Fig. 10. SOC level of multi-source LEV during test against drive cycle ECE-47
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The next test is for the condition in which the vehicle experiences higher speed demand. The extended drive cycle ECE-47ext is designed to have 33% higher speeds than the normal drive cycle. A multi-source LEV and a battery-only LEV are compared to the drive cycle ECE-47ext, as shown in Fig. 11. At first, the multi-source and battery-powered LEVs have no trouble trailing the drive cycle acceleration, and they maintain speed at 63 km/h. After 35 s, the battery-powered LEV starts to lose its maximum current and cannot maintain the speed. On the multi-source side, the FC started to support the battery 18 s after the start, when the vehicle reaches its maximum speed. Then, the FC continues to support the vehicle for another 50 s until the vehicle reduces its speed. From 60 s until the drive cycle ends, both the multi-source and the battery-powered LEVs have no trouble following the ECE-47ext drive cycle. Evaluating the power efficiency at high speed shows that the multi-source fulfills 97.9% of the drive cycle ECE-47ext and that the battery as a single source has a lower fulfillment rate of 92%.
The 12 V, 4.5 Ah SLA battery can supply a maximum of 3 A according to its standard specification. However, during the experiment, the battery was not able to supply the maximum current consistently. After several cycles of charging and discharging and occurrences of selfdischarging, the battery loses approximately 2-3% of its electrical capability. After a full recharge, the maximum current measured is only 2.7 A, and this current decreases linearly as a function of time. The current battery shows a consistent value for a longer period, only when it is discharged at below 2 A. This problem is observed in the experiment, as shown in Fig. 13. For the period from 10 s to 50 s, the current average value decreases from 2.5 A to 2.2 A before declining and staying constant at 1 A. However, the multi-source-powered system succeeds in maintaining the current at above 2.3 A and thus enables the vehicle to hold the maximum speed of 63 km/h. This fact shows that combining multiple energy sources is beneficial as compared to a single-source-powered system.
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The switching time for the multi-source system is observed in Fig. 12 and can be described as: the drive cycle represents state 5 for the first 18 s, then continues at state 8 for 2 s, then spends 20 s at state 7, next returning to state 8 for 3 s, then returning to state for the next 7 s, before finally stopping at state 5 until 120 s. SC-State 1 0.5 0
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To match urban driving conditions [23-24], the ECE-15 drive cycle is introduced into the testing phase. A comparison between multi-source-powered and single-source-powered vehicles, against the ECE-15 drive cycle, is presented in Fig. 14. As the battery SOC is high and there is no request to increase speed, the multi-source LEV is powered by the battery alone. For the first two cycles, over-speed behavior is observed. In the third cycle, a high acceleration is required, and the tester has turned the pedal more than necessary, which causes the SC to activate. 60
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For the majority of the test, it has been observed that a single-source-powered system, e.g., a battery-powered vehicle, has disadvantages in terms of power capacity. The reduction in lead acid battery capacity is already noticeable after just a few rounds of charging and discharging [25]. Although there are advanced battery technologies such as Lithium-ion and Ni-MH, these technologies have the same effect but with a longer life cycle. Therefore, by coupling the battery with a FC or other suitable renewable energy source, the sources can be used to counterbalance each other’s disadvantages while offering an extended travel distance range. Therefore, it can be concluded that the use of multisource energy is applicable for electric vehicle applications, but extensive study is still required before multi-source energy can be accepted for commercialization. A small-scale test bench model of a new energy management system for multi-source LEV utilizing DSP controller board DS1104 has been designed and tested in a real-time. An intelligent control algorithm is implemented and offers the best selection of activated energy sources. The battery and the FC can be a single-source vehicle system and the sources can be coupled together for power sharing. The SC is an auxiliary power supply to support the system whenever a rapid high current is required. Another useful activation of the SC occurs to assist the FC during its starttime and to avoid fuel starvation. The DS1104 is linked to MATLAB/Simulink to allow the user to conduct the experiment with real-time switching in the EMS and to evaluate the performance of the vehicle. From the experimental results, the multi-source LEV delivered a better result as compared to the single-source-powered vehicle. Therefore, a system equipped with an intelligent switching control algorithm has promising potential for vehicle applications in the future. Further study can be conducted to optimize the EMS control algorithm for an actual size test model.
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