电源技术2017，Vol.41Issue(9)：1350-1352,1355,4.
无损卡尔曼滤波在估算动力电池SOC中的应用
Unscented kalman filtering for state of charge estimation of power battery
李练兵 1韩靖楠 1唐会莉1
作者信息
- 1. 河北工业大学控制科学与工程学院,天津300000
- 折叠
摘要
Abstract
State of Charge (SOC) was the core part of Battery Management System (BMS) of Electric Vehicles (EVs).Its accurate estimation was the assurance of battery safety and optimal control of charge/discharge energy.Power battery in vehicle was under the environment of nonlinear and strong coupling characteristic.An Unscented Kalman Filter (UKF-Unscented Kalman Filter) method was proposed.It combined Ampere Hour (AH) integral method which took account of Multiple and Dynamic Compensation with battery model.A simple and reliable control strategy model of battery management system (BMS) was built.Tests were made to verify the performance of model.The results indicate that our model was reliable and the method could provide accurate SOC estimation.关键词
电池管理系统/荷电状态/电池模型/无损卡尔曼滤波Key words
battery management system/state of charge/battery model/Unscented Kalman Filtering分类
信息技术与安全科学引用本文复制引用
李练兵,韩靖楠,唐会莉..无损卡尔曼滤波在估算动力电池SOC中的应用[J].电源技术,2017,41(9):1350-1352,1355,4.
