Energy Management Strategy For A Plug-in Hybrid Electric Vehicle Based On Stochastic Model Predictive Control

The plug-in hybrid electric vehicle(PHEV)is a transitional vehicle from the hybrid electric vehicle(HEV)to the electric vehicle(EV).It is widely used because it has low fuel consumption and can meet various working conditions.The energy management strategy directly affects the vehicle's fuel economy,emissions and other vehicle performance.In order to improve fuel economy and real-time performance of energy management strategy,this paper focuses on the research of energy management strategy based on explicit stochastic model predictive control.The main research contents are as follows:(1)The structural characteristics of the power split plug-in hybrid power system are analyzed,and the working conditions of the main components in each mode are analyzed.The simulation models of power transmission system and key components are established.The PI controller is used to simulate the driver model,and the forward simulation model of power shunt plug-in hybrid electric vehicle is built.(2)The problem of PHEV energy management strategy based on model predictive control is constructed.The energy management strategy based on explicit model predictive control is studied to improve the real-time performance of the algorithm.By means of multi-parameter solution method,the explicit solution of model predictive control optimization model is obtained offline,which greatly reduces the time of online calculation.The simulation results under three conditions of NEDC,UDDS and WLTP show that the strategy based on explicit model predictive control can not only achieve better fuel economy,but also greatly improve the on-line calculation speed.Further analysis shows that the fuel economy of the whole vehicle can be improved by improving the accuracy of speed prediction and optimizing the engine working point.(3)Based on the comparative analysis of the commonly used speed prediction methods and the advantages of each algorithm,a method of speed prediction based on fuzzy Markov is proposed,which achieves good results in short-term speed prediction.Based on the energy management strategy of explicit model predictive control,the energy management strategy based on stochastic model predictive control considering the transient characteristics of the engine is constructed.The strategy based on explicit stochastic model predictive control is solved by parametric solution method.The feasibility of the control strategy in the whole solution domain is guaranteed by stability analysis.By analyzing the simulation results under three working conditions,the strategy based on explicit stochastic model predictive control can improve the working point of the engine and further improve the fuel economy of the vehicle.(4)According to the battery SOC,the operation model of plug-in hybrid electric vehicle is divided,and the power and economy of the vehicle are fully considered.A rulebased energy management strategy is established.In order to fully verify the control effect of the control strategy,the energy management strategy based on global optimization is studied,and the energy management optimization problem based on dynamic programming is constructed,and the global optimal solution under various conditions is obtained.By comparing and analyzing the simulation results of various control strategies under three conditions,the strategy based on explicit stochastic model predictive control has better results in fuel economy and simulation time,that verifies the correctness and real-time performance of the control strategy proposed in the research.