| 引用本文: | 姚昌兴,李 昕,邢丽坤.基于多时间尺度锂电池在线参数辨识及 SOC 和 SOH 估计(J/M/D/N,J:杂志，M：书，D：论文，N：报纸).期刊名称,2023，40（5）：48-54 |
| CHEN X. Adap tive slidingmode contr ol for discrete2ti me multi2inputmulti2 out put systems[ J ]. Aut omatica, 2006, 42(6): 4272-435 |
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| 摘要: |
| 电池的荷电状态和健康状态是衡量电池续航和寿命的重要指标,为解决电池参数的时变性问题,提高电池
SOC(State of Charge)估算精度,减少硬件计算量,提出一种多时间尺度在线参数辨识双扩展卡尔曼滤波联合算法。
以 18650 三元锂电池为研究对象,采用基于二阶 RC 等效电路模型的多时间尺度 DEKF 算法,针对电池参数的慢变
特性和状态的快变特性进行双时间尺度在线参数辨识和 SOC 估算;通过联邦城市驾驶计划 (FUDS) 测试验证,得
出多时间尺度 DEKF 算法和传统离线辨识 EKF 算法对 SOC 估计的平均绝对误差分别为 0. 97%和 2. 46%,均方根
误差为 1. 19%和 2. 69%,容量估计值对参考值最大误差仅为 0. 007 72 Ah;实验结果表明:所提出的多时间尺度
DEKF 算法,具有更好的鲁棒性和 SOC 估算精度并能实时反应 SOH 变化趋势。 |
| 关键词: 多时间尺度 二阶等效电路 DEKF SOC SOH |
| DOI： |
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| On-line Parameter Identification and SOC and SOH Estimation of Lithium Battery Based on Multi-time Scale |
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YAO Changxing, LI Xing, XING Likun
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School of Electrical and Information Engineering, Anhui University of Science and Technology, Anhui Huainan 232001,
China
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| Abstract: |
| The state of charge SOC and state of health SOH of a battery are important indicators of battery endurance
and lifetime. In order to solve the problem of time-varying battery parameters improve the accuracy of SOC estimation
and reduce the hardware computation a joint multi-timescale online parameter identification algorithm with a doubleextended Kalman filter was proposed. The multi-timescale DEKF algorithm based on the second-order RC equivalent
circuit model was used for the online parameter identification and SOC estimation of the 18 650 ternary lithium battery with
the slow-varying characteristics of the battery parameters and the fast-varying characteristics of the battery state. Through
the test verification of the Federal Urban Driving Program FUDS the average absolute errors of the SOC estimation of
the multi-time scale DEKF algorithm and the traditional offline identification EKF algorithm were 0. 97% and 2. 46%
respectively the rms errors were 1. 19% and 2. 69% and the maximum error of the capacity estimation to the reference
value was only 0. 007 72 Ah. The experimental results show that the proposed time-scale DEKF algorithm has better
robustness and SOC estimation accuracy and can respond to the SOH variation trend in real time. |
| Key words: multi-time scales second-order equivalent circuit DEK F SOC SOH |
