Research On Control Strategy Of PHEV Power System Based On Model Predictive Control

With the increasing awareness of environmental protection and stricter emission regulation,traditional vehicle is becoming less and less adapted to the current sustainable development environment.Under the background of advocating energy conservation and environmental protection,new energy vehicle gradually comes into people's vision.Plug-in hybrid electric vehicle(PHEV),as a type of new energy vehicle,has become a hot topic of research in recent years because of their excellent economy,excellent emission and excellent endurance capacity.This paper focuses on the control strategy based on model predictive control(MPC)of plug-in hybrid electric vehicle,the work has the following aspects:Based on the structural characteristic of plug-in hybrid electric vehicle power system,basic vehicle parameters and performance indexes,the selection and parameter matching of the power system components(engine,motor and battery)and the transmission system are carried out,in Matlab / Simulink software,based on the test data,build the corresponding simulation model;The working modes of plug-in hybrid electric vehicle power system and power transmission under each working mode are analyzed,the optimal working curve of the engine is determined,the logic gate control strategy based on rule is constructed,the simulation analysis is carried out;In addition,the global optimization control strategy based on the dynamic programming(DP)is constructed,the simulation analysis is carried out,the global optimal fuel economy of plug-in hybrid electric vehicle is obtained;The control strategy based on model predictive control is the focus of this paper.Firstly,select the velocity and acceleration of the target cycle condition as the historical data information to establish one-step Markov model and multi-step Markov model of the velocity and acceleration,respectively,use the established one-step Markov model and multi-step Markov model to predict the velocity and acceleration in the prediction horizon;Then,put forward a method to improve the prediction effect by using the average speed difference of working condition,and compares the prediction effect before and after the improvement;Finally,apply the Markov model and dynamic programming to the model predictive control,select the improved one-step Markov model to predict the velocity and acceleration,the control strategy based on MPC is constructed,the simulation contrast analysis is carried out.The results show that the fuel consumption rate in 100 km of the control strategy based on MPC is between the fuel consumption rate in 100 km of the logic gate control strategy based on rule and the global optimization control strategy based on dynamic programming.Compared with the logic gate control strategy based on rule,the control strategy based on MPC can effectively improve the fuel economy of plug-in hybrid electric vehicle.