摘要
梳理并分析了大数据视角下国内外对电池管理系统(Battery Management System, BMS)中荷电状态(State of Charge, SOC)估计、健康状态(State of Health, SOH)评估、故障诊断,续行驶里程预测的各种研究方法,总结了当前存在的问题并展望未来研究方向,为相关研究提供参考。
This paper sorts out and analyzes various research methods of state-of-charge estimation, health status assessment, fault diagnosis, and mileage prediction in battery management systems from the perspective of big data at home and abroad, and summarizes the existing problems and looks forward to the future research direction, so as to provide reference for relevant research.
作者
李放
张营
闵永军
Li Fang;Zhang Ying;Min Yongjun(College of Automotive and Traffic Engineering,Nanjing Forestry University,Nanjing City,Jiangsu Province 210037,China)
出处
《农业装备与车辆工程》
2022年第10期129-133,157,共6页
Agricultural Equipment & Vehicle Engineering
关键词
大数据
电动汽车
电池管理
数据驱动
big data
electric vehicles
battery management
data driven
