黄海宏,汪宇航,王海欣.基于粒子群优化粒子滤波算法的 SOC 估算研究[J].电子测量与仪器学报,2022,36(2):245-253
基于粒子群优化粒子滤波算法的 SOC 估算研究
Research on SOC estimation based on particle swarmalgorithm and particle filter algorithm
  
DOI:
中文关键词:  粒子滤波  粒子群算法  SOC 估计  等效电路模型
英文关键词:particle filter  particle swarm optimization  SOC estimation  equivalent circuit model
基金项目:安徽省科技重大专项项目 (18030901064)资助
作者单位
黄海宏 1.合肥工业大学电气与自动化工程学院 
汪宇航 1.合肥工业大学电气与自动化工程学院 
王海欣 1.合肥工业大学电气与自动化工程学院 
AuthorInstitution
Huang Haihong 1.School of Electrical Engineering and Automation, Hefei University of Technology 
Wang Yuhang 1.School of Electrical Engineering and Automation, Hefei University of Technology 
Wang Haixin 1.School of Electrical Engineering and Automation, Hefei University of Technology 
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中文摘要:
      准确的获得电池的荷电状态(SOC)有助于缓解汽车行驶过程中的里程焦虑。 针对粒子滤波估算 SOC 中存在的粒子退 化的问题,将粒子群算法与粒子滤波融合的改进粒子滤波算法(GPSO-PF)算法应用于 SOC 的估计。 在迭代中不断优化粒子所 处位置,从而解决了粒子贫化的问题,提高了 SOC 的估算精度。 同时,针对 SOC 估算容易受到温度的影响,建立基于温度的等 效电路模型,并将其应用于提出的 SOC 估算算法中。 选取两节相同型号的磷酸铁锂电池,分别在不同工况下利用 GPSO-PF 算 法估算 SOC 值,SOC 的最大估算误差均低于 0. 72%。 通过对比,与基于温度等效电路模型相结合后,GPSO-PF 算法能够有效提 高 SOC 的估算精度。
英文摘要:
      Battery state of charge (SOC) estimation is helpful to alleviate the mileage anxiety in the process of driving. Aiming at the problem of particle degradation in the estimation of SOC by particle filter, this paper proposes to apply the Gaussian particle swarm optimization particle filter ( GPSO-PF). Compared to estimation of SOC by particle filter, GPSO-PF combines particle swarm optimization algorithm and particle filter to estimate SOC. GPSO-PF solve the problem of particle dilution and improve the estimation accuracy of SOC by continuously optimizing the position of particles in the iteration. As SOC estimation is easily affected by temperature, an equivalent circuit model based on temperature is established and applied to the proposed SOC estimation algorithm. Two LiFePO4 batteries of the same type are selected and the GPSO-PF algorithm is used to estimate the SOC value under different working conditions. The maximum estimation error of SOC is less than 0. 72%. By comparison, GPSO-PF algorithm combined with equivalent circuit model based on temperature can effectively improve the estimation accuracy of SOC.
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