锂离子电池PHM

Saurabh Saxena, Yinjiao Xing, M. Pecht
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引用次数: 5

摘要

本章概述了用于锂离子电池状态估计和剩余使用寿命(RUL)预测的预测和系统健康管理(PHM)技术。锂离子电池代表复杂的电化学-机械系统,其中存在各种降解机制。充电状态(SOC)和健康状态(SOH)分别提供了对锂离子电池剩余电量和剩余可用容量的估计。本章讨论了电池荷电状态估计的方法,并给出了一些实验数据的案例研究来阐述这些方法。然后给出了一个使用贝叶斯框架进行SOH估计和RUL预测的案例研究。基于PHM的锂离子电池决策框架可以根据预测信息为任务规划和维护调度提供建议,并可以实时控制电池的使用情况,以优化电池的寿命周期性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PHM of Li-ion Batteries
This chapter presents an overview of the prognostics and systems health management (PHM) techniques used for states estimation and remaining useful life (RUL) prediction of lithium‐ion (Li‐ion) batteries. Li‐ion batteries represent complex electrochemical‐mechanical systems in which various degradation mechanisms are present. State of charge (SOC) and state of health (SOH) provide the estimates of remaining charge and remaining usable capacity of a Li‐ion battery respectively. The chapter discusses methods for battery SOC estimation and also presents a few case studies on experimental data to elaborate these methods. It then presents a case study on SOH estimation and RUL prediction using a Bayesian framework. PHM‐based decision‐making framework for Li‐ion batteries can provide recommendations for mission planning and maintenance scheduling based on the prognostic information, and can control the battery usage in real‐time to optimize the battery life‐cycle performance.
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