Particle Swarm Optimization for optimal powertrain component sizing and design of fuel cell hybrid electric vehicle

In this paper, an optimal design to minimize the cost, mass and volume of the fuel cell (FC) and supercapacitor (SC) in a fuel cell hybrid electric vehicle is presented. Because of the hybrid powertrain, component sizing significantly affects vehicle performance, cost and fuel economy. Hence, during sizing, various design and control constraints should also be satisfied simultaneously. In this research, there are two optimization techniques have tested to achieve optimal design of the powertrain. These are Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The proposed schemes have been simulated by MATLAB/ SIMULINK. Simulation results have demonstrated that the optimal sizing of the powertrain components has been improved when the PSO is applied, which means high-performance operation for FCHEV.