@article { author = {حاجی زاده, امین}, title = {Optimal Power Management of Fuel Cell Hybrid Vehicles}, journal = {Journal of Solid and Fluid Mechanics}, volume = {2}, number = {3}, pages = {55-62}, year = {2012}, publisher = {Shahrood University of Technology}, issn = {2251-9475}, eissn = {2251-9483}, doi = {10.22044/jsfm.2012.68}, abstract = {This paper presents a control strategy developed for optimizing the power flow in a Fuel Cell Hybrid Vehicle structure. This method implements an on-line power management based on the optimal fuzzy controller between dual power sources that consist of a battery bank and a Fuel Cell (FC). The power management strategy in the hybrid control structure is crucial for balancing between efficiency and performance of hybrid systems. For optimization of fuzzy control strategy, the Particle Swarm Optimization (PSO) algorithm has been considered to determine the battery’s state of charge and fuel cell power in maximum efficiency operating point. The fuel cell hybrid vehicle includes battery and fuel cell and its power train system include an Electric Motor (EM) and power electronic converters. Simulation results of hybrid system illustrate improvement in the operation efficiency of the fuel cell hybrid vehicle and the battery’s state of charge (SOC) and fuel cell utilization factor have been maintained at a reasonable level.}, keywords = {fuel cell,Battery,Hybrid Vehicle,fuzzy control,PSO,Optimization}, title_fa = {Optimal power management of fuel cell hybrid vehicles}, abstract_fa = {This paper presents a control strategy developed for optimizing the power flow in a Fuel Cell Hybrid Vehicle structure. This method implements an on-line power management based on the optimal fuzzy controller between dual power sources that consist of a battery bank and a Fuel Cell (FC). The power management strategy in the hybrid control structure is crucial for balancing between efficiency and performance of hybrid systems. For optimization of fuzzy control strategy, the Particle Swarm Optimization (PSO) algorithm has been considered to determine the battery’s state of charge and fuel cell power in maximum efficiency operating point. The fuel cell hybrid vehicle includes battery and fuel cell and its power train system include an Electric Motor (EM) and power electronic converters. Simulation results of hybrid system illustrate improvement in the operation efficiency of the fuel cell hybrid vehicle and the battery’s state of charge (SOC) and fuel cell utilization factor have been maintained at a reasonable level.}, keywords_fa = {fuel cell,Battery,Hybrid Vehicle,fuzzy control,PSO,Optimization}, url = {https://jsfm.shahroodut.ac.ir/article_68.html}, eprint = {https://jsfm.shahroodut.ac.ir/article_68_f98a84ff627d9c555a0147f2c22624e9.pdf} }