储能科学与技术 ›› 2025, Vol. 14 ›› Issue (6): 2524-2531.doi: 10.19799/j.cnki.2095-4239.2024.1209

• 储能测试与评价 • 上一篇    下一篇

钒电池核心部件可靠性模型参数估计分析

徐航1(), 史小虎2, 余龙海2, 孙彦招3, 王友1()   

  1. 1.湖北文理学院机械工程学院,湖北 襄阳 441053
    2.大力储能技术湖北有限责任公司,湖北 襄阳 441035
    3.湖北文理学院汽车与交通工程学院,湖北 襄阳 441053
  • 收稿日期:2024-12-19 修回日期:2025-01-07 出版日期:2025-06-28 发布日期:2025-06-27
  • 通讯作者: 王友 E-mail:1769280663@qq.com;wyslllo@sina.com
  • 作者简介:徐航(1997—),男,硕士研究生,研究方向为数字化设计及数值模拟,E-mail:1769280663@qq.com
  • 基金资助:
    湖北省自然科学基金联合基金项目(2023AFD036)

Parameter-estimation analyses of reliability models for the core components of a vanadium-redox-flow battery

Hang XU1(), Xiaohu SHI2, Longhai YU2, Yanzhao SUN3, You WANG1()   

  1. 1.School of Mechanical Engineering, Hubei University of Arts and Sciences, Xiangyang 441053, Hubei, China
    2.Dali Energy Storage Technology Hubei Co. , Ltd. , Xiangyang 441035, Hubei, China
    3.School of Automobile and Transportation Engineering, Hubei University of Arts and Sciences, Xiangyang 441053, Hubei, China
  • Received:2024-12-19 Revised:2025-01-07 Online:2025-06-28 Published:2025-06-27
  • Contact: You WANG E-mail:1769280663@qq.com;wyslllo@sina.com

摘要:

可靠性设计是钒电池电堆开发过程中的重要组成部分,对储能系统的安全性和经济性具有决定性作用。本工作以液流框、双极板为研究对象,建立了基于对数正态分布、二参数和三参数Weibull分布模型的钒电池核心部件可靠性模型,阐明了基于极大似然估计法和GM(1,1)方法的参数估计法,以K-S检验法和均方根误差(RMSE)为评价指标,探讨了分布模型和参数估计方法对可靠性预测结果的影响。结果表明:液流框可靠性模型的拟合优度最小值为0.89,说明采用两种参数估计方法获得的可靠性模型全部通过拟合优度检验;进一步地,可靠性模型的均方根误差最小值为0.22,说明基于GM(1,1)方法的二参数分布模型最适宜于表达液流框的可靠性模型。双极板可靠性模型的拟合优度最小值为0.03,说明极大似然估计法不适用于开展三参数Weibull分布参数估计;进一步地,可靠性模型的均方根误差最小值为0.16,说明基于GM(1,1)方法的二参数分布模型是能精确表达双极板的可靠性模型。研究结果对钒电池核心部件及系统的可靠性设计与优化具有理论指导意义。

关键词: 钒电池, 可靠性, 概率分布模型, K-S检验, 均方根误差

Abstract:

Reliability design is an important aspect of the development of vanadium-battery stacks, and it plays a decisive role in the safety and economy of energy-storage systems. Taking the liquid-flow frame and bipolar plate as the research objects, this study establishes reliability models for the core components of vanadium batteries based on the lognormal distribution and on two-parameter and three-parameter Weibull-distribution models. Parameter-estimation in this study is based on the maximum-likelihood estimation method and the GM (1,1) method. The K-S test and the root-mean-square error (RMSE) were adopted as evaluation indicators for exploring the influence of the distribution model and the parameter-estimation method on the reliability of the predictions. The results show that the minimum goodness-of-fit for the liquid-flow-frame reliability model is 0.89, indicating that the reliability models obtained using the two-parameter-estimation methods all pass the goodness-of-fit test. Further, the minimum RMSE of the reliability model is 0.22, which indicates that the two-parameter distribution model based on the GM (1,1) method is the most suitable reliability model for the liquid-flow frame. The minimum goodness-of-fit of the bipolar plate reliability model is 0.03, which indicates that the maximum-likelihood estimation method is not suitable for estimating the parameters of the three-parameter Weibull-distribution. Further, the minimum RMSE of the reliability model is 0.16, which indicates that the two-parameter distribution model based on the GM (1,1) method is the most accurate reliability model for the bipolar plate. These research results have theoretical guiding significance for the reliability design and optimization of vanadium-battery core components and systems.

Key words: vanadium battery, reliability, probability distribution model, K-S test, RMSE

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