摘要
复杂路况下,为提高电动汽车锂电池组健康状态SOH(state of health)估算实时性与准确性,通过扩展卡尔曼滤波算法估算荷电状态,结合锂电池组温度与单体锂电池电压,系统判断锂电池组健康状态,提示故障位置并及时更换。结果表明,通过建模对电动汽车锂电池组健康状态估算简单、方便、准确、高效。保证了锂电池处于最佳状态,提高了驾驶的舒适性与安全性,实用性强。
In order to improve the electric vehicle lithium-ion SOH(state of health)estimation the real-time and accuracy under complex road conditions,using extended Kalman filtering algorithm for estimating the state of charge,combined with the temperature of lithium-ion battery and the voltage of single lithium-ion battery,The system can accurately judge the state of health for lithium-ion battery and prompt the fault location to be replaced in time.The results show that the electric vehicle lithium-ion battery health state estimation is simple,convenient,accurate and efficient by modeling.The system can keep the lithium-ion battery at its best and improves the driving comfort and safety,strong practicability.
作者
晏勇
雷晓蔚
YAN Yong;LEI Xiaowei(College of Electronic Information and Automations,Aba Teachers University,Aba 623002,China;Department of Science and Technology,Aba Teachers University,Aba 623002,China)
出处
《青岛科技大学学报（自然科学版）》
CAS
2019年第2期113-118,共6页
Journal of Qingdao University of Science and Technology:Natural Science Edition
基金
四川省教育厅自然科学基金重点项目(17ZA0002)
