Research On Control Of Pure Electric Vehicle Integrated Thermal Management System Based On Model Predictive Control

This paper mainly studies a pure electric vehicle integrated thermal management system,which has integrated heat exchange between motor and battery,and its control strategy.The performance of the battery and motor of a pure electric vehicle is closely related to its operating temperature,and it needs to design an efficient thermal management system to provide protection.In the low temperature environment in winter,the independent battery and motor thermal management system cannot fully utilize the waste heat of the motor and electrical components,so it is necessary to integrate the battery and motor thermal management system.At the same time,the heating process of the battery has the characteristics of time lag.The accuracy that cannot be obtained by traditional PID control.Model predictive control is considered to be an effective method to improve the control performance of time-delay systems.This article does the following to solve the above problems.First,this paper designs a pure electric vehicle integrated heat management system with integrated heat exchange between the motor and the battery.It uses a plate heat exchanger to connect the battery and the motor cooling water circuit,so that it has the function of using the motor waste heat to heat the battery in a low temperature environment.Secondly,the heat generation principle of the battery and the motor is analyzed,and the heat transfer process of the thermal management system is deduced,and the simulation model of the thermal management system is established.The simulation model of the vehicle working condition is built based on the AMESim software.The thermal management model was combined with the vehicle working condition model to build a thermal management performance simulation platform based on vehicle operating conditions.Then,the control strategy of the integrated thermal management system is designed,the working mode is divided,and the control logic design of the solenoid valve,water pump and other components is designed.Based on the linear time-varying state space model predictive control strategy,the battery heating strategy is designed,and the soft constraint relaxation factor is introduced to optimize the performance of the model predictive control solution.Design a battery heat generation prediction method based on road condition information,and use the prediction results to optimize the input disturbance parameters of the model predictive control.Finally,the experimental vehicle was modified,and the accuracy of modeling was verified through experiments.The thermal management performance test and evaluation methods of high temperature,normal temperature,and low temperature environment were designed,simulation experiments were conducted and the performance of the integrated thermal management system designed in this paper was analyzed.By comparing with the PID strategy,the effect of the model predictive control strategy was verified.By comparing with the real-time battery heat input disturbance analysis,the influence of battery heat prediction based on road condition information on the model predictive control performance is verified.