A comprehensive review of the aging mechanism and degradation costs of fresh and second-life batteries based on analytical and deterministic methods

Energy Storage Pub Date : 2024-06-12 DOI:10.1002/est2.661
Musa Terkes, Alpaslan Demirci, Erdin Gokalp
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引用次数: 0

Abstract

Batteries' aging evolution and degradation functions may vary depending on the application area and various stress factors. Studies on its aging characteristics are ongoing, considering the unpredictable tendency of battery degradation during first and secondary usage periods. Battery degradation directly affects operating costs and prevents many stakeholders from making reliable short- or long-term investment plans. Thus, this review study first introduces the battery models commonly used by researchers and provides an overview of the aging mechanism and estimation methods for health status and remaining capacity. Analytical and deterministic aging/degradation functions/models proposed by the researchers are discussed in detail, and cost equations based on degradation are reviewed. This approach was followed for the fresh and second-life batteries by further investigating the impact of stress factors on the aging process and cost. The details of aging prediction approaches based on traditional methods, machine learning, and artificial intelligence are out of the scope of this review article. Discussing the shortcomings of aging analyses/functions and introducing different perspectives on the degradation characteristics will help researchers and provide a roadmap for many stakeholders.

基于分析和确定性方法对新电池和二次寿命电池的老化机制和降解成本进行全面审查
电池的老化演变和降解功能可能因应用领域和各种应力因素而异。考虑到电池在第一次和第二次使用期间不可预测的退化趋势,对其老化特性的研究仍在进行中。电池老化会直接影响运营成本,使许多利益相关者无法制定可靠的短期或长期投资计划。因此,本综述研究首先介绍了研究人员常用的电池模型,并概述了老化机制以及健康状况和剩余容量的估算方法。详细讨论了研究人员提出的分析性和确定性老化/降解函数/模型,并回顾了基于降解的成本方程。通过进一步研究应力因素对老化过程和成本的影响,对新电池和二次寿命电池采用了这种方法。基于传统方法、机器学习和人工智能的老化预测方法的细节不在本综述文章的讨论范围之内。讨论老化分析/功能的不足之处并介绍有关降解特征的不同观点将有助于研究人员的工作,并为许多利益相关者提供路线图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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