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Figure 1. Proton exchange membrane fuel cell The Nernst equation can be used to obtain the result voltage for a standard PEMFC fuel cell in order to determine the fuel cell's reversible potential. The behavior described by this equation only applies to a single fuel cell. The (2) will power each fuel cell in the fuel cell stack:

Figure 1 Proton exchange membrane fuel cell The Nernst equation can be used to obtain the result voltage for a standard PEMFC fuel cell in order to determine the fuel cell's reversible potential. The behavior described by this equation only applies to a single fuel cell. The (2) will power each fuel cell in the fuel cell stack:

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Table 1. Toyota's Mirai fuel cell stack — 144 KW -24 voltage specification model Where Vactce represents activation voltage drop (activation losses), Vohm,ceu represents ohmic voltage dror (ohmic losses), and Veonc,cei represents concentration voltage drop (concentration losses) [20], [22]. The PEMEFC from Toyota's Mirai company used in this research is illustrated in Table 1.
Table 1. Toyota's Mirai fuel cell stack — 144 KW -24 voltage specification model Where Vactce represents activation voltage drop (activation losses), Vohm,ceu represents ohmic voltage dror (ohmic losses), and Veonc,cei represents concentration voltage drop (concentration losses) [20], [22]. The PEMEFC from Toyota's Mirai company used in this research is illustrated in Table 1.
Figure 3. DC/DC boost converter control model Figure 2. Circuit of boost converter for DC/DC The best answer is selected as the best and first vulture in this stage, the second solution is selected as the second-best vulture, and the other vultures are grouped together into a third group according to the second criterion. This phase comes after the initial population is formed in (8) [18].
Figure 3. DC/DC boost converter control model Figure 2. Circuit of boost converter for DC/DC The best answer is selected as the best and first vulture in this stage, the second solution is selected as the second-best vulture, and the other vultures are grouped together into a third group according to the second criterion. This phase comes after the initial population is formed in (8) [18].
Figure 6. System model setup The system setup model of fuel cell electric vehicle is illustrated in Figure 6. The fuel cell is suppling unidirectional DC/DC converter which is coupled to motor controller. The fuel cell is powering motor controller through DC/DC converter. The motor controller is achieved using FLC-AVOA, FLC-GA, and PI-GA. RESULTS AND DISCUSSION To evaluate the performance of the speed controller-based energy management strategy, the electric car powered by a fuel cell model has been implemented and simulated in MATLAB/Simulink, the result of the simulation. In Figure 7 it is observed that the overshoot peak value of motor speed employing fuzzy logic controller with AVOA is less than in fuzzy logic control using GA and PI control using GA, and the rising time of AVOA-based fuzzy logic control is lower than that of other methods. In the FLC-AVOA reduced the rising time for speed dynamic response by 2.31% and the maximum peak overshoot by 55.23% as compared to FLC-GA. 3. SYSTEM SETUP
Figure 6. System model setup The system setup model of fuel cell electric vehicle is illustrated in Figure 6. The fuel cell is suppling unidirectional DC/DC converter which is coupled to motor controller. The fuel cell is powering motor controller through DC/DC converter. The motor controller is achieved using FLC-AVOA, FLC-GA, and PI-GA. RESULTS AND DISCUSSION To evaluate the performance of the speed controller-based energy management strategy, the electric car powered by a fuel cell model has been implemented and simulated in MATLAB/Simulink, the result of the simulation. In Figure 7 it is observed that the overshoot peak value of motor speed employing fuzzy logic controller with AVOA is less than in fuzzy logic control using GA and PI control using GA, and the rising time of AVOA-based fuzzy logic control is lower than that of other methods. In the FLC-AVOA reduced the rising time for speed dynamic response by 2.31% and the maximum peak overshoot by 55.23% as compared to FLC-GA. 3. SYSTEM SETUP
Figure 7. DC motor speed simulation with PI-GA, FLC-GA, and FLC-AVOA
Figure 7. DC motor speed simulation with PI-GA, FLC-GA, and FLC-AVOA
Figure 8. Simulation of Fuel cells power using PI-GA, FLC-GA, and FLC-AVOA
Figure 8. Simulation of Fuel cells power using PI-GA, FLC-GA, and FLC-AVOA
Figure 9. Simulation of the output motor torque of the system using PI-GA, FLC-GA, and FLC-AVOA
Figure 9. Simulation of the output motor torque of the system using PI-GA, FLC-GA, and FLC-AVOA
Figure 10. Simulation of the output fuel cell voltage of the system using PI-GA, FLC-GA, and FLC-AVOA
Figure 10. Simulation of the output fuel cell voltage of the system using PI-GA, FLC-GA, and FLC-AVOA
Related topics:
Fuzzy Logic ControllerFuel Cell Electric Vehicle
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