离子电池的健康状况和故障分析,使用混合Weibull和同等电路模型
Weiting Hu1, Quan Qian1,2,3
1School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China.
iScience
|June 17, 2024
概括
这项研究引入了一种新的电池模型,用于解释电化学阻抗光谱 (EIS) 数据,提高健康状况 (SoH) 预测准确性和电池诊断.
科学领域:
- 电化学 电化学 电化学
- 材料科学 材料科学 材料科学
- 数据科学数据科学数据科学
背景情况:
- 目前电化学阻抗光谱 (EIS) 对电池的解释模型缺乏全面的物理解释和参数化.
- 现有的模型未能完全捕捉到电池内部复杂的电化学行为和衰老过程.
研究的目的:
- 开发一个先进的等效电路模型,用于增强的电池诊断.
- 为了提高预测电池健康状况 (SoH) 曲线的准确性.
- 为了更好地了解电池老化过程中的电化学参数相互依赖.
主要方法:
- 提出了一个温度控制的二次R-CPE等效电路模型,用于非理想的电容特性.
- 使用基于Copula的联合混合Weibull模型进行参数分布分析.
- 采用多输出高斯过程回归来进行SoH曲线预测.
主要成果:
- 拟议的模型在实验验证中实现了8.5%的平均根平均平方误差 (RMSE).
- 在100个循环后,SoH曲线预测准确度平均达到9.2%的RMSE.
- 在捕获电池电化学参数分布方面表现出更高的精度.
结论:
- 开发的模型为分析电池电化学行为和老化提供了一个强大的框架.
- 结果为对电池诊断至关重要的参数相互依赖提供了更深入的见解.
- 这种方法提高了对电池退化的理解和预测.
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