• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2020, Vol. 56 ›› Issue (14): 146-151.doi: 10.3901/JME.2020.14.146

• 运载工程 • 上一篇    下一篇

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基于双卡尔曼滤波算法的动力电池内部温度估计

熊瑞, 李幸港   

  1. 北京理工大学机械与车辆学院 北京 100081
  • 收稿日期:2020-01-24 修回日期:2020-05-03 出版日期:2020-07-20 发布日期:2020-08-12
  • 通讯作者: 熊瑞(通信作者)男,1985年出生,博士,教授,博士研究生导师。主要研究方向为电动载运工具电源系统管理与综合控制。E-mail:rxiong@bit.edu.cn
  • 作者简介:李幸港,男,1994年出生,博士研究生。主要研究方向为电动车辆动力电池管理。
  • 基金资助:
    北京市科技计划高可靠性全气候电池工程化技术开发资助项目(2181100004318005)。

Battery Internal Temperature Estimation Method through Double Extended Kalman Filtering Algorithm

XIONG Rui, LI Xinggang   

  1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081
  • Received:2020-01-24 Revised:2020-05-03 Online:2020-07-20 Published:2020-08-12

摘要: 准确的内部温度估计对提高动力电池使用安全和可靠性极为重要,然而,受限于传感器和测试手段等因素,内部温度难以实时获取。通过融合Bernardi电池生热模型与热路传热模型,应用状态方程分析法实施了电池内外温度的表达,建立了温度的离散时间系统;利用双扩展卡尔曼滤波,建立电池内部温度和环境参数的实时估计模型,实现了电池内部温度在线估计。基于内置温度传感器的动力电池测试验证表明,该方法能在线估算锂离子动力电池的内部温度,估计误差小于1℃,为动力电池的实时安全监控提供了有力保障。

关键词: 电动汽车, 动力电池, 内部温度估计, 双扩展卡尔曼滤波

Abstract: Accurate battery internal temperature is very important to improve the safety and reliability of battery applications. However, due to many factors such as sensors and testing methods, its internal temperature is difficult to measure online. After integrating the Bernardi battery heat generation model and heat transfer model, the internal and external temperature of the battery is expressed using the equation of state analysis to obtain a discrete-time system of temperature; the double extended Kalman filter is used to establish the real-time temperature and environmental parameters of the battery. The estimation model realizes online estimation of the internal temperature of the battery. Results of the battery through the built-in temperature sensor show that the method can estimate the internal temperature of online with an error of <1 ℃ and high accuracy.

Key words: electric vehicle, battery, internal temperature estimation, double extended Kalman filter

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