基于频繁项统计的流-安时积分SOC估计方法  

SOC estimation method of flow-amp-hour integral based on frequent item statistics

作　　者：李昆 赵理[1,2] 赵博阳 客汉宸 李俊丽 LI Kun;ZHAO Li;ZHAO Boyang;KE Hanchen;LI Junli(School of Mechanical and Electrical Engineering,Beijing Information Science and Technology University,Beijing 100192,China;Collaborative Innovation Center of Electric in Beijing,Beijing 100192,China;School of Artificial Intelligence and Data Science,Hebei University of Technology,Tianjin 300401,China)

机构地区：[1]北京信息科技大学机电工程学院,北京100192 [2]北京电动车辆协同创新中心,北京100192 [3]河北工业大学人工智能与数据科学学院,天津300401

出　　处：《重庆理工大学学报（自然科学）》2022年第3期19-27,共9页Journal of Chongqing University of Technology：Natural Science

基　　金：国家自然科学基金项目(52077007);北京市教育委员会科技计划项目(KM201811232003);北京信息科技大学教改项目(2021JGYB02);北京信息科技大学研究生科技创新项目(5112110835)。

摘　　要：针对传统安时积分法由于无法在线更新库仑效率而导致的难以准确估测电池剩余容量的问题,提出一种基于频繁项统计进行电流分段积分,利用不同库仑效率对分段积分后电量进行修正的流-安时积分法。该方法利用连续充放电循环对库仑效率进行在线修正,基于柯西频繁项统计算法对电流进行分段累积,利用修正后的库仑效率对分段累计电量进行校正,最后实现了电池剩余容量的准确估计。仿真和实验分析表明:基于频繁项统计的安时积分法有效减小了传统安时积分法产生的电量累积误差,提高了剩余容量及SOC的估计精度。In order to slove the problem that the traditional ampere-hour integration method can’t accurately estimate the remaining capacity of the battery due to the inability to update the coulomb efficiency online,this paper proposes an improved ampere-hour integration based on frequent item statistics for current segmentation to realize the correction of the Coulomb efficiency law.This method uses continuous charge and discharge cycles to correct the Coulomb efficiency,calculates the current segment accumulation based on frequent item statistics,and uses the corrected Coulomb efficiency to correct the segmented cumulative power,and finally realizes an accurate estimation of the remaining battery capacity.The comparative analysis of simulation and experiment shows that the ampere-hour integration method based on frequent item statistics can significantly reduce the charge accumulation error generated by the traditional ampere-hour integration method,save storage space,and enhance the estimation accuracy of remaining capacity and SOC.

关 键 词：频繁项统计 流挖掘算法 库仑效率 安时积分法 SOC估计 

分 类 号：TM912[电气工程—电力电子与电力传动]