Particle swarm optimization for efficient selection of hybrid electric vehicle design parameters

It has been proven in literature that both the drivetrain as well as control strategy parameters have significant effects on the performance of hybrid electric vehicles (HEVs). A global optimization methodology based on particle swarm optimization (PSO) is presented in this paper for the parameter optimization of parallel hybrid electric drivetrain and control strategy simultaneously. The developed methodology aims at improvement in terms of fuel economy, without compromising driving performance. Simulation results show an improvement in the fuel economy, emissions, and overall drivetrain efficiency, which prove the potential of the optimization technique.