Energy management of hybrid off road vehicles based on demand power prediction
1. School of Automotive Engineering, Wuhan University of Technology, Wuhan， Hubei 430070, China; 2. Hubei Key Laboratory of Advanced Technology for Automotive Components， Wuhan University of Technology, Wuhan, Hubei 430070, China; 3. Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan, Hubei 430070, China; 4. Hubei Engineering Technology Research Center for New Energy and Intelligent Network Vehicles, Wuhan, Hubei 430070, China
Abstract： To optimize the multiple power source dynamic response and fuel economy of hybrid off road vehicles, the demand power was taken as key research parameter, and the adaptive Markov chain prediction algorithm was designed to realize realtime prediction of demand power. Based on the control strategy of equivalent fuel consumption minimization, the variable area equivalent consumption minimization strategy with consideration of realtime demand power change was proposed to realize the optimization of energy management strategy. The Cruise and Simulink software were used to build the joint simulation platform for energy management of hybrid off road vehicles, and the energy management strategy simulation validation in typical off road driving cycle was carried out. The simulation results show that the designed adaptive demand power prediction algorithm by Markov chain can improve the vehicle dynamics by 6.5%. Compared with the composite rule strategy, the variable area equivalent fuel consumption minimum control strategy can increase the vehicle fuel economy by 10.5%.
