| 动态工况模拟下动力锂电池建模与参数辨识方法 |
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| 引用本文： | 李泓沛,刘桂雄,邓威. 动态工况模拟下动力锂电池建模与参数辨识方法[J]. 电子测量技术, 2022, 45(14): 103-108 |
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| 作者姓名： | 李泓沛 刘桂雄 邓威 |
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| 作者单位： | 华南理工大学机械与汽车工程学院，广东广州 510640 |
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| 基金项目： | 广东省重点领域研发计划项目(No. 2019B090908003) |
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| 摘 要： | 为提高动态工况模拟下动力电池等效电路模型参数辨识准确性、稳定性，本文提出一种动态工况模拟下动力锂电池建模与参数辨识方法，采用准确度较高、辨识难度适中Thevenin二阶等效电路模型对动力电池进行状态空间描述；设计动力锂电池模型参数辨识算法总体流程，开展OCV-SOC曲线的工况测试获取曲线的拟合系数；提出含噪声干扰动力锂电池等效电路模型参数的DEKF+GA算法辨识方法，增加GA算法，在DEKF求解初始值处进行最优解搜索，提升DEKF算法准确性、鲁棒性。实验表明，应用DEKF+GA算法比DEKF算法，URMSE、UMAX分别平均减少29mV、27.73mV。
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| 关 键 词： | 动力锂电池；参数辨识；双卡尔曼滤波；遗传算法 |
Modeling and parameter identification method for power lithium batteries under dynamic working condition simulation |
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| Li Hongpei,Liu Guixiong,Deng Wei. Modeling and parameter identification method for power lithium batteries under dynamic working condition simulation[J]. Electronic Measurement Technology, 2022, 45(14): 103-108 |
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| Authors: | Li Hongpei Liu Guixiong Deng Wei |
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| Affiliation: | School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640,.China |
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| Abstract: | Thevenin second-order equivalent circuit model is used to describe the state space of the power battery with high accuracy and moderate identification difficulty. The DEKF+GA algorithm is proposed to identify the parameters of the equivalent circuit model of Li-ion battery with noise interference, and the GA algorithm is added to search for the optimal solution at the initial value of the DEKF solution to improve the accuracy and robustness of the DEKF algorithm. Experiments show that applying the DEKF+GA algorithm reduces the URMSE and UMAX by 29mV and 27.73mV respectively on average compared to the DEKF algorithm. |
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| Keywords: | Power lithium batteries Parameter identification Dual Kalman filter Genetic algorithm |
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