Particle Swarm Optimization for Operational Parameters of Series Hybrid Electric Vehicle

Because of the inherent advantages, i. e. increased fuel economy, reduced harmful emissions and better vehicle performance, hybrid electric vehicles (HEV), powered by internal combustion engine (ICE) and energy storage, are being given more and more attention. Since the extent of HEV improvement greatly depends on selection of the control strategy parameters, particle swarm optimization (PSO) algorithm is introduced to optimize the strategy parameters for fuel economy and emissions in this paper. Compared with one of the main strategies, Dividing RECTangles (DIRECT), the computation procedures of particle swarm optimization algorithm are discussed, and simulation study based on the model of series hybrid electric vehicle is given to illustrate the optimization validity of the particle swarm optimization algorithm.