A Study And Implementation Of Battery Management System For Electric Vehicles

The research and development of Electric Vehicles(EV)is an important direction to solve energy and environmental problems,and is also an important development strategy of all countries and automobile companies.Battery management technology is one of the core technologies of EV technology.It can realize battery state monitoring,energy strategy optimization and safety protection,and its technical depth is an important evaluation index for the development level of EVs.The key technologies in Battery Management System(BMS)include the accurate real-time monitoring of battery voltage and current to provide the basis for the algorithm;State of Charge(SOC)estimation provides a reference for the continuation of the mileage;State of Power(SOP)estimation provides the basis for the power output and energy recycle;the high efficiency and stable equilibrium management to improve the battery consistency;the heat balance.to control battery temperature.In this paper,the research contents and achievements of BMS are as follows:Firstly,according to the characteristics of NCR18650 PF lithium battery for BMS and considering the difference of work capacity,the relationship between the charge/discharge ratio and temperature with the battery capacity is established.According to the relation of SOC and open circuit voltage(OCV),OCV-SOC curve of the battery is obtained by using experimental data.The first order RC equivalent circuit Thevenin model is set up after weigh the model complexity and computation accuracy.The model parameters are identified by the HPPC test data.The accuracy and efficiency of the model are proved by experiment.Secondly,the characteristics of the SOC estimation of the battery by Ampere-hour(Ah)and OCV method are summarized and analyzed.The SOC algorithm for correcting Ah on the basis of the equivalent circuit model of the battery OCV is proposed.The estimation accuracy is improved by using the correction coefficient of temperature correction coefficient,charge/discharge ratio correction coefficient and OCV method to improve the estimation accuracy.The high accuracy of SOC estimation is achieved in the BMS controller of computing power.The effectiveness of the SOC algorithm is proved by Matlab/Simulink simulation and experimental comparison.Thirdly,on the basis of existing State of Power(SOP)algorithm,the relationship between the battery thermal model and the heat balance equation is proposed to establish the relationship between the battery temperature rise and SOP.The SOP estimation is realized by the temperature constraint.The simulation results are compared between the SOP algorithm based on the voltage constraints and the SOC constraints.The results show the algorithm in this paper improve the overall accuracy of battery SOP estimation,and prove the feasibility of SOP estimation method on the temperature dimension.Finally,based on the existing battery module and electric vehicle platform,the BMS software and hardware platform is tested in real vehicle.The hardware system includes voltage and temperature signal acquisition board,current acquisition sensor and circuit,equalization control board,LCD display screen,various communication network and relays.The software system includes program operation,?C/OSIII operation system,hardware module drivers and many kinds of user function programs.Finally,the SOC algorithm,SOP algorithm and the platform designed to build BMS are verified in the road test.The experimental results show that the research algorithm and the BMS platform in this paper can satisfy the practical application requirements.