摘要
开路电压是电动汽车动力电池的重要参数之一,对电池电量(SOC)参数的估计具有关键作用。然而,在电动汽车实际使用过程中,动力电池的稳定开路电压状态却往往很难得到。传统的试验获取开路电压的方法难以满足动力电池复杂的实际工况条件。为准确获取实车动力电池的开路电压值,通过大数据分析电动汽车在充电完成状态及下次启动状态的动力电池电压状况,利用随机森林回归(RFR)算法预测动力电池电压变化特性,实现了对充电完成状态的开路电压预估,估计精度可以达到87%,为SOC标定、电池等效电路参数辨识和SOH估计工作实现奠定了基础。
Open Circuit Voltage(OCV)is an important parameter of electric vehicle power batteries,which plays a key role for estimating parameter of State Of Charge(SOC).However,in the practical use of electric vehicles,the stable OCV state of power batteries is often difficult to obtain.The traditional experimental method of obtaining OCV is difficult to meet the complex working conditions of power batteries.In order to obtain the accurate OCV of the power batteries,this paper analyzes the power battery voltage of the electric vehicles in the charging completion state and the next starting state through big data,using Random Forest Regression(RFR)algorithm to predict the voltage variation characteristics of the power batteries,and realizing the estimation of the OCV in the charging completion state.Verification tests indicate that the estimation accuracy can reach 87%,which is the basis for SOC calibration,It lays a foundation for the realization of battery equivalent circuit parameter identification and State Of Health(SOH)estimation.
作者
潘垂宇
李雪
许立超
张志
陈雷
Pan Chuiyu;Li Xue;Xu lichao;Zhang Zhi;Chen Lei(New Energy Vehicle Development Institute,China FAW Corporation Limited,Changchun 130013;State Key Laboratory of Comprehensive Technology on Automobile Vibration and Noise&Safety Control,Changchun 130013)
出处
《汽车文摘》
2022年第4期24-29,共6页
Automotive Digest
关键词
动力电池
大数据
充电电压恢复率
开路电压
Power battery
Big data
Charging voltage recovery rate
Open Circuit Voltage(OCV)
