Optimization of control parameters in parallel hybrid electric vehicles using a hybrid genetic algorithm

This paper describes the application of a hybrid genetic algorithm for the optimization of the parameters of the control strategy in parallel hybrid electric vehicles (HEV). Considering the shortage of genetic algorithm (GA), a simulated annealing, adaptive based hybrid genetic algorithm (SAAHGA) is developed and applied to the optimization, and then based on an electric assist control strategy, an HEV optimal method combining optimization algorithm and HEV simulation tool is introduced. ADVISOR2002 is used as the vehicle simulator. The results show the effectiveness of the hybrid genetic algorithm.