机械科学与技术2017，Vol.36Issue(9)：1428-1433,6.DOI:10.13433/j.cnki.1003-8728.2017.0919
改进粒子滤波算法对电动汽车电池SOC的估计
An Improved Particle Filter Algorithm for SOC Estimation of Electric Vehicle Battery
摘要
Abstract
In order to solve the problem of lacking SIR particle filter algorithm diversity,the SIR particle filter algorithm is improved to estimate electric vehicle battery state of charge (SOC),with system state continuous approximate distribution sampling regularization filtering algorithm.By the ampere hour method to build the state space model of the battery and identify the battery model parameter,the simulation experiment is finished combined with the particle filter algorithm and improved particle filter algorithm in MATLAB.Simulation results show that,the SIR particle filter algorithm estimation errors of SOC becomes larger with the time increasing,the improved particle filtering algorithm to estimate the battery state of charge (SOC) has been close to the true value.Compared with the SIR particle filter,the improved particle filtering algorithm is of high accuracy and better adaptability than the SIR particle filter algorithm,providing a new idea for estimating SOC of batteries used in electric vehicles.关键词
粒子滤波算法/电动汽车/荷电状态/正则化滤波算法Key words
particle filter algorithm/state of charge/matlab/estimation/errors/regularization filter algorithm分类
信息技术与安全科学引用本文复制引用
高建树,刘浩,王明强,史经伦,邢书剑..改进粒子滤波算法对电动汽车电池SOC的估计[J].机械科学与技术,2017,36(9):1428-1433,6.基金项目
国家自然科学基金青年基金项目(61405246)、中央高校基本科研业务费(3122015C012)及中国民航大学科研启动基金项目(2014QD11X)资助 （61405246）
