Modeling and simulation of Energy managements for fuel cell hybrid vehicle

In recent years, the various usage of fuel cells in vehicles has absorbed attention in industry and academic area. The fuel cells, are considered as a modern power sources in transportation. Compared with the internal combustion engines, fuel cells have the advantages of high energy efficiency and near zero emissions which is important to reduce global warming. However, vehicles powered only by fuel cells have some disadvantages, such as low power density, long start-up time, and slow power response. Hybridization of the fuel cell system with a secondary peaking power source is an effective approach to overcome the disadvantages of the fuel-cell-alone-powered vehicles. One of the possible combination is fuel cell/ battery composition. Obviously, the performance of the drive train relies mainly on control quality. This work presents an enhanced method for distributing power demand through the hybrid power sources. Fuzzy logic control and operation mode control have considered for this purpose. Genetic algorithm has implemented for tuning these strategies by means of off-line simulation in two combined driving cycle. Multiple objective fitness function deals with effective parameters (such as equivalent consumption, fuel cell and energy storage efficiency, state of charge variation, dynamic response…) for getting reliable and acceptable results from optimization process. Finally, these optimized strategies present a fully-advanced method for energy management system of fuel cell hybrid vehicles.