Application of Particle Swarm Optimization for Component Sizes in Parallel Hybrid Electric Vehicles

Abstract

This paper describes an approach for the optimization of parallel Hybrid Electric Vehicle (HEV) component sizing using Particle Swarm Optimization (PSO) algorithm. In this study, the fitness function is defined to minimize the vehicle engine fuel consumption (FC) and emissions. The driving performance requirements are then considered as constraints. Finally, the optimization process is performed over the test procure TEST CYCLE HYWT, in which a vehicle model named ADVISOR is used as the analysis tool. The results from the computer simulation show the effectiveness of the approach and reduction in FC, emissions while ensuring that the vehicle performance is not sacrificed.