An Intelligent Logic Rule-Based Energy Management Strategy for Power-Split Plug-in Hybrid Electric Vehicle

Abstract

This paper develops an intelligent logic rule-based energy management strategy to improve fuel economy for power-split plug-in hybrid electric vehicle (PHEV). Unlike conventional rules-based energy management control strategy designed only with battery state of charge, the thresholds of the optimal working area of the engine are also taken into consideration so that the engine operates in a high efficiency region. Firstly, battery state of charge and driver's power demand are used to design rule-based energy management strategy. Then, the threshold parameters of rule-based energy management strategy are optimized by particle swarm optimization algorithm (PSO). To improve the adaptability of control strategy, multiple historical driving cycles are used to optimize parameters and obtain a rule-based energy management control strategy which is adaptive to unknown driving cycles. Finally, several contrastive simulation results are presented to demonstrate the comparative advantage of the proposed energy management control strategy on the efficiency of engine and the adaptability to unknown driving conditions by using GT-SUITE PHEY simulitor and MATLAB/Simulink software platform.