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文章摘要
基于自适应卡尔曼滤波的矿用救生舱动力电池SOC估计
SOC estimation of power battery in mine-used lifesaving cabin based on adaptive kalman filtering
Received:May 27, 2015  Revised:June 29, 2015
DOI:
中文关键词: 矿用救生舱  磷酸铁锂动力电池  SOC估计  自适应卡尔曼滤波算法
英文关键词: mine-used lifesaving cabin, the lithium iron phosphate power battery, SOC estimation, adaptive kalman filtering algorithm
基金项目:吉林省科技发展计划项目(社发处)(20140204029);吉林省科技发展项目(高新处)(20140204026)
Author NameAffiliationE-mail
Yu Weibo* School of Electrical Electronic Engineering,Changchun University of Technology yu_weibo@126.com 
Wei Lai School of Electrical Electronic Engineering,Changchun University of Technology  
Yang Tingting School of Electrical Electronic Engineering,Changchun University of Technology  
Liu Keping School of Electrical Electronic Engineering,Changchun University of Technology  
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中文摘要:
      磷酸铁锂动力电池是矿用救生舱的重要组成部分,其电荷状态(SOC)估计的准确性直接影响避难人员的安危。针对电池SOC常用估算方法的不足,提出一种基于自适应卡尔曼滤波的矿用救生舱动力电池SOC估算方法。在电池特性分析的基础上,建立了更符合实际的改进二阶RC等效电池模型和电池的状态空间模型。通过脉冲放电实验和改进的带遗忘因子递推最小二乘算法,对模型参数进行在线辨识,并将自适应卡尔曼滤波算法(AKF)用于此模型,在线估计电池的SOC。实验结果表明:AKF可以实时修正模型误差,实时估计SOC的动态变化,估算精度高,能够满足矿用救生舱电池管理系统的要求。
英文摘要:
      The lithium iron phosphate power battery is an important component of mine-used lifesaving cabin, which state of charge (SOC) estimation accuracy directly influences the sheltering people"s safety. In view of common method in SOC estimation of battery, the paper proposed a SOC estimation of power battery in mine-used lifesaving cabin based on adaptive kalman filtering method. According to the analysis of the characteristics of the battery,The establishment of a more accord with the actual improvement equivalent second-order RC battery model and state space model of the battery. By pulse discharge experiments and improved RLS algorithm with forgetting factor, online identification model parameters, and the adaptive kalman filtering algorithm (AKF) used in this model, the online estimate the SOC of the battery. The experiment results shows that AKF can real-timely correct model error and estimate the dynamic changes of SOC with high accuracy and meet battery management system of mine-used lifesaving cabin requirements.
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