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首页> 外文期刊>Applied Mathematical Modelling >Online state of charge estimation of Li-ion battery based on an improved unscented Kalman filter approach
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Online state of charge estimation of Li-ion battery based on an improved unscented Kalman filter approach

机译：基于改进的无味卡尔曼滤波方法的锂离子电池在线充电状态估计

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摘要

An improved unscented Kalman filter approach is proposed to enhance online state of charge estimation in terms of both accuracy and robustness. The goal is to address the drawback associated with the unscented Kalman filter in terms of its requirement for an accurate model and a priori noise statistics. Firstly, Li-ion battery modelling and offline parameter identification is performed. Secondly, a sensitivity analysis experiment is designed to verify which model parameter has the greatest influence on state of charge estimation accuracy, in order to provide an appropriate parameter for the model adaptive algorithm. Thirdly, an improved unscented Kalman filter approach, composed of a model adaptive algorithm and a noise adaptive algorithm, is introduced. Finally, the results are discussed, which reveal that the proposed approach's estimation error is less than 1.79% with acceptable robustness and time complexity. (C) 2019 Elsevier Inc. All rights reserved.
机译：提出了一种改进的无味卡尔曼滤波器方法，以提高准确性和鲁棒性的在线电荷状态估计。目的是要解决与无味卡尔曼滤波器相关的缺点，即对精确模型和先验噪声统计的要求。首先，进行锂离子电池建模和离线参数识别。其次，设计了一个灵敏度分析实验，以验证哪个模型参数对荷电状态估计精度的影响最大，以便为模型自适应算法提供合适的参数。第三，提出了一种改进的无味卡尔曼滤波方法，该方法由模型自适应算法和噪声自适应算法组成。最后，对结果进行了讨论，结果表明该方法的估计误差小于1.79％，并且具有可接受的鲁棒性和时间复杂度。 （C）2019 Elsevier Inc.保留所有权利。

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  • 来源
    《Applied Mathematical Modelling》 |2019年第6期|532-544|共13页
  • 作者

    Chen Zewang; Yang Liwen; Zhao Xiaobing; Wang Youren; He Zhijia;

  • 作者单位

    Nanjing Univ Aeronaut & Astronaut, Coll Automat & Engn, Nanjing 211106, Jiangsu, Peoples R China;

    Nanjing Univ Aeronaut & Astronaut, Coll Automat & Engn, Nanjing 211106, Jiangsu, Peoples R China;

    Nanjing Univ Aeronaut & Astronaut, Coll Automat & Engn, Nanjing 211106, Jiangsu, Peoples R China;

    Nanjing Univ Aeronaut & Astronaut, Coll Automat & Engn, Nanjing 211106, Jiangsu, Peoples R China;

    Nanjing Univ Aeronaut & Astronaut, Coll Automat & Engn, Nanjing 211106, Jiangsu, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Li-ion battery; State of charge estimation; Unscented Kalman filter; Model adaptive; Noise adaptive;

    机译：锂离子电池;充电状态估计;无味卡尔曼滤波器;模型自适应;噪声自适应;

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