Remaining useful life prediction of lithium-ion battery based on improved cuckoo search particle filter and a novel state of charge estimation method
Remaining useful life prediction of lithium-ion battery based on improved cuckoo search particle filter and a novel state of charge estimation method
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基于改进布谷鸟搜索粒子滤波器和新型荷电状态估计方法的锂离子电池剩余寿命预测
DOI：
10.1016/j.jpowsour.2020.227700
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发表时间：
2020-02
影响因子：
9.2
通讯作者：
Wang Shuangfeng
中科院分区：
文献类型：
--
作者：
Qiu Xianghui;Wu Weixiong;Wang Shuangfeng
对于电池管理系统来说，准确估计电池的荷电状态（SOC）和健康状态（SOH）以及剩余使用寿命（RUL）的预测具有重要意义。为了提高SOC估计的精度和收敛速度，提出了向后平滑平方根立方卡尔曼滤波（BS-SRCKF）。然后，将BS-SRCKF和扩展卡尔曼滤波器（EKF）组成的多尺度混合卡尔曼滤波器（MHKF）用于SOC和SOH的联合估计。此外，将改进的杜鹃搜索（ICS）算法嵌入到标准粒子滤波器（PF）中，通过将先验分布区域的粒子转移到最大似然区域来提高其性能。最后，利用SOC和SOH的联合估计和改进的布谷鸟搜索粒子滤波器（ICS-PF）估计的SOH信息实现RUL预测。仿真结果表明，与基于PF和unscented particle filter （UPF）的两种预测方法相比，本文提出的RUL预测方法具有更高的精度、置信度和重采样率。
For battery management system, accurate estimation of state of charge (SOC) and state of health (SOH), as well as prediction of remaining useful life (RUL) are of great significance. Herein, backward smoothing square root cubature Kalman filter (BS-SRCKF) is proposed to improve accuracy and convergence speed of SOC estimation. Then the multiscale hybrid Kalman filter (MHKF), which consists of BS-SRCKF and extended Kalman filter (EKF), is employed for the joint estimation of SOC and SOH. Furthermore, improved cuckoo search (ICS) algorithm is embedded in the standard particle filter (PF) to improve its performance, by transferring the particles in the prior distribution region to the maximum likelihood region. Eventually, RUL prediction is achieved based on the SOH information estimated by the joint estimation of SOC and SOH and the improved cuckoo search particle filter (ICS-PF). The simulation results demonstrate that the method for RUL prediction present in this paper has improved accuracy, confidence level and resampling rate compared with two existing methods based on PF and unscented particle filter (UPF).
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影响因子：
3.2
作者：
Bizhong Xia;Haiqing Wang;Mingwang Wang;Wei Sun;Zhihui Xu;Yongzhi Lai
通讯作者：
Bizhong Xia;Haiqing Wang;Mingwang Wang;Wei Sun;Zhihui Xu;Yongzhi Lai
DOI：
10.1061/(asce)0733-9496(2003)129:3(210
发表时间：
2003-05-01
影响因子：
3.1
作者：
Eusuff, MM;Lansey, KE
通讯作者：
Lansey, KE
基于高斯-厄米粒子滤波器的锂离子电池剩余寿命预测
影响因子：
4.8
作者：
Ma, Yan;Chen, Yang;Chen, Hong
通讯作者：
Chen, Hong
DOI：
10.1149/ma2010-03/1/736
发表时间：
2011-04
期刊：
--
影响因子：
--
作者：
후차오;윤병동;정재식
通讯作者：
후차오;윤병동;정재식
影响因子：
9.4
作者：
Hao Yang;Xianzhong Sun;Yabin An;Xiong Zhang;Tongzhen Wei;Yanwei Ma
通讯作者：
Hao Yang;Xianzhong Sun;Yabin An;Xiong Zhang;Tongzhen Wei;Yanwei Ma