电源技术2017，Vol.41Issue(1)：17-20,172,5.
基于滑动窗自适应滤波的锂电池SOC/SOH联合估计
Estimation of SOC/SOH for 18650-type lithium battery based on sliding-mode adaptive algorithm
摘要
Abstract
The estimation of the State of Charge (SOC) and State of Health (SOH) for 18650 lithium battery wereconsidered.An inclusive model indicating the electrochemical characteristics of battery was taken into account andthe nonlinear behavior of the open-circuit voltage versus SOC was also included in the model.The online estimationof battery parameters tackled the aforementioned problems to attain a reliable estimation of the battery SOC.Moreover,an analytical method based on sliding-mode observer was considered to estimate the additive nonlinear oruncertainty term in the model.This approach leaded to a very accurate model of the battery to be used in a batterymanagement system.Lastly,an adaptive estimation algorithm based on parameter value was proposed to estimatethe battery's SOH.The proposed scheme benefited from an adaptive rule for the online estimation of the seriesresistance in the lithium-ion battery based on the accurately identified model.Experimental tests certified theperformance and feasibility of the proposed schemes.关键词
锂电池/滑动窗滤波/SOC/SOH/Kalman/参数估计Key words
lithium-ion battery/sliding-mode adaptive algorithm/SOC/SOH/Kalman/parameter estimation分类
信息技术与安全科学引用本文复制引用
汪秋婷,姜银珠,陆赟豪..基于滑动窗自适应滤波的锂电池SOC/SOH联合估计[J].电源技术,2017,41(1):17-20,172,5.基金项目
2016浙江省自然科学基金(LQ16F010004) （LQ16F010004）
2015浙江省科技计划项目(2015C33225) （2015C33225）
