储能科学与技术2024，Vol.13Issue(10)：3400-3422,23.DOI:10.19799/j.cnki.2095-4239.2024.0282
化学电源内阻测量及状态监测策略分析研究
Internal resistance measurement and condition monitoring strategy for chemical power systems
摘要
Abstract
Internal resistance is a crucial parameter for assessing both the lifespan and battery operation state,serving as a key indicator of the challenges associated with electron and ion migration or diffusion within the electrodes.However,accurately measuring internal resistance can be challenging due to its sensitivity to environmental factors such as temperature and pressure.Precise detection of internal resistance is essential for enhancing the accuracy of battery management systems.Given the current challenges in internal resistance measurement,such as the influence of multiple variables,significant errors,and limited application scope,this paper reviews and analyzes recent research on five typical methods for measuring the internal resistance of lithium batteries,namely,the mixed pulse power characteristic method,DC internal resistance testing method,AC injection method,DC discharge method and electrochemical impedance spectroscopy method.The study focuses on the specific influence of internal and external environments on internal resistance and innovatively explore the relationship between internal resistance and battery life,operational status,and safety alerts.These insights offer a pathway to improve the accuracy of chemical power performance evaluations,predict chemical power life,and optimize chemical power use.Finally,the strategies for improving internal resistance measurement methods,including the integration of machine learning models,are examined and discussed.It proposes quantitative metrics,such as short test time,high test consistency,and superior accuracy,to further refine measurement methods and expand their applications.These advancements are expected to significantly enhance the accuracy of the internal resistance measurement in chemical power systems,improving the monitoring and analysis of battery modules,and provide new ideas for optimizing battery performance across various types of chemical power systems.关键词
交流阻抗/直流阻抗/电池寿命预测/健康状态/机器学习Key words
AC impedance/DC impedance/life prediction of battery/state of health/machine learning分类
信息技术与安全科学引用本文复制引用
蒋杭廷,张倩倩,张松通,祝夏雨,孟闻捷,邱景义,明海..化学电源内阻测量及状态监测策略分析研究[J].储能科学与技术,2024,13(10):3400-3422,23.基金项目
国家自然科学基金项目(62075002,21703285). （62075002,21703285）
