Particle swarm optimization for plug-in hybrid electric vehicle control strategy parameter

Abstract

Plug-in hybrid electric vehicles (PHEVs) differ from hybrid electric vehicles (HEVs) with their ability to use off-board electricity generation to recharge their energy storage systems. In addition to possessing charge-sustaining HEV operation capability, PHEVs use the stored electrical energy during a charge-depleting (CD) operating period to displace a significant amount of petroleum consumption. The choice of CD operating strategy directly influences the benefit derived from the PHEV technology. This paper describes the application of the particle swarm optimization (PSO) algorithm for the optimization of the control parameters in plug-in hybrid electric vehicles (HEV). In this study, based on CD operating strategy, the fitness function is defined so as to maximize the vehicle engine fuel economy (FE). The driving performance requirements are then considered as constraints. The results from the computer simulation show the effectiveness of the approach and improvement in fuel economy (FE) while ensuring that the vehicle performance is not sacrificed.