储能科学与技术 ›› 2023, Vol. 12 ›› Issue (9): 2904-2916.doi: 10.19799/j.cnki.2095-4239.2023.0342

• 储能测试与评价 • 上一篇    下一篇

宽温度环境下基于改进电化学模型的锂电池荷电状态估计

申江卫1(), 周灿彪1, 舒星1, 陈峥1(), 刘永刚2   

  1. 1.昆明理工大学交通工程学院,云南 昆明 650000
    2.重庆大学机械与运载学院,重庆 400030
  • 收稿日期:2023-05-16 修回日期:2023-06-07 出版日期:2023-09-05 发布日期:2023-09-16
  • 通讯作者: 陈峥 E-mail:shenjiangwei6@kust.edu.cn;chen@kust.edu.cn
  • 作者简介:申江卫(1984—),男,博士,高级实验师,研究方向为新能源汽车动力电池管理,E-mail:shenjiangwei6@kust.edu.cn
  • 基金资助:
    国家自然科学基金项目(52162051);云南省基础研究计划项目(202301AT070423)

State of charge estimation for lithium batteries based on an improved electrochemical model at a wide temperature environment

Jiangwei SHEN1(), Canbiao ZHOU1, Xing SHU1, Zheng CHEN1(), Yonggang LIU2   

  1. 1.Faculty of Transportation Engineering Kunming University of Science and Technology, Kunming 650000, Yunnan, China
    2.College of Mechanical Engineering Chongqing University, Chongqing 400030, China
  • Received:2023-05-16 Revised:2023-06-07 Online:2023-09-05 Published:2023-09-16
  • Contact: Zheng CHEN E-mail:shenjiangwei6@kust.edu.cn;chen@kust.edu.cn

摘要:

为提升电化学模型的实用性以及复杂环境温度下的适用性,解决锂离子电池内部状态难以快速精确估计的难题,本文设计了一种基于改进电化学模型的荷电状态估计方法。首先,通过有限差分法和Galerkin法分别对P2D模型的固液相方程进行降阶求解以描述电池内部锂离子浓度的实时状态,同时进一步融合等效电路模型,采用2个RC网络结构表征电池内部极化过程,并包含了与温度相关的特性,形成了适合荷电状态估计的低阶常微分系统,实现了电化学模型的有效简化和降阶,节约计算成本。其次,为了处理由于模型简化导致的模型不确定性和降低噪声干扰,引入平方根容积卡尔曼滤波,设计了宽工作温度下的锂电池荷电状态估计算法。结果表明,本文提出的基于改进电化学模型的荷电状态估计方法可以在不同温度及复杂工况下实现荷电状态的精确估计,宽环境温度下的最大误差小于1.6%。

关键词: 锂电池, 改进电化学模型, 环境温度, 荷电状态, 平方根容积卡尔曼滤波

Abstract:

In order to improve the practicability of the electrochemical model and its applicability at complex temperature environments and solve the problem of difficulty in quickly and accurately estimating the internal state of lithium-ion batteries, a state-of-charge estimation method based on an improved electrochemical model is designed. First, the order reduction of the solid-liquid phase equation of the electrochemical model is solved using the finite difference method and Galerkin method to explain the real-time state of lithium-ion concentration in the battery. Simultaneously, the equivalent circuit model is integrated further, and two RC network structures are used to characterize the internal polarization process of the battery. The temperature-dependent characteristics are included to form a low-order ordinary differential system suitable for the state of charge estimation, realizing effective simplification and order reduction of the electrochemical model and saving the calculation cost. Then, to address the model uncertainty caused by model simplification and reduce noise interference, a square root volume Kalman filter was introduced to design a lithium battery state of charge estimation algorithm at full operating temperature. The results showed that the proposed state of charge estimation method based on the improved electrochemical model could accurately estimate the state of charge under different temperatures and complex working conditions, with a maximum error of less than 1.6% under diverse temperature settings.

Key words: lithium ion battery, electrochemical mode, ambient temperature, state of charge, square root cubature kalman filte

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