| With the continuous development of the economy and society,the popularity of fuel vehicles has made people’s life more convenient,but it also brought about many issues such as environmental pollution and energy depletion.In order to alleviate this problem,governments have promoted the industrialization of electric vehicles.The battery energy storage system is the core source of the electric vehicle power,and its working efficiency and lifespan directly determine the mileage of the electric vehicle and user experience.Large and medium-sized electric vehicles have the characteristics of complicated working conditions and high output power,which are easy to cause unbalanced capacity and accelerate aging of the battery,so higher requirements for the balanced efficiency of the battery management system(BMS)are required.And the optimization of the BMS needs to be designed to the point to fully utilize the performance of the lithium battery system.This article relies on the Warrior Electric Vehicle Project of Dongfeng Motor Corporation to develop a battery management system for large and medium-sized electric vehicle applications.First,this paper presents new demand analysis and program design of the battery system.Then,considering the complex working conditions,large battery output power and high equilibrium requirements of large and medium-sized electric vehicles,the existing BMS management system is improved and a equilibrium optimization algorithm is proposed to improve the equilibrium efficiency.Finally,the system experiment is debugged to verify the effectiveness of the design.The specific work content is as follows.The present paper designs the battery management system as a distributed two-layer management system,in which the primary level is local control unit taking charge of acquiring the information of the cells,balancing energy and uploading data,its hardware contains controller,power source,sampling,equalizer and CAN communication;the secondary level is central control unit taking charge of controlling the whole system and acquiring information,its hardware contains controller,total voltage,total current,data storage and communication circuit.In addition,in order to calculate more accurate SOC of the Lithium battery,the open circuit voltage method is used with the Ampere hour integration in combination.First,estimate the initial SOC of single cell by the open circuit voltage method.Then,estimate the synchronous SOC value via the Ampere hour integration.When the battery stops,calibrate the initial SOC with the open circuit voltage method.Based on accurate SOC estimation,the particle swarm optimization can be used as equilibrium strategy,which has the advantages of higher efficiency and speed.Finally,analyzing the actual experimental data,and comparing it with theoretical data to calculate the accuracy of the corresponding parameters.The experimental results show that the optimized BMS in this paper equalizes the 12-series Li-ion battery pack of 126 Ah and the SOC difference of about 2%,and the speed is up to about 2800 seconds,and the accuracy is up to 0.1%.Compared with the conventional switching transformer method,the speed is increased by about 50%. |
