基于SoH估计的在线手机电池熵测量

A. Cuadras, F. Meinert, P. Büschel, O. Kanoun
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引用次数: 4

摘要

电池的广泛使用需要了解其健康状态(SoH)。本文提出了一种利用熵演化作为电池老化指标的方法。手机电池的电压、电流和温度都是实时监控的。不可逆熵是由电池长时间使用的不可逆能量耗散来估计的。对简单开路电池电压Uocv模型进行了评估,并与实验室测量的Uocv进行了比较。研究发现,在电池运行过程中,熵的产生率是不断增大的,不可逆熵是电池老化的一个标志。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online cellphone battery entropy measurement for SoH estimation
The widespread use of batteries requires knowledge of their state of health (SoH). In this paper we present a method to use entropy evolution as an aging indicator for batteries. Voltage, current and temperature are monitored in battery cells used in cellphones and in real-time operation. Irreversible entropy is estimated from irreversible energy dissipation in the battery for long periods of use. Simple open circuit battery voltage Uocv models were evaluated and compared to lab measured Uocv. It was found that the entropy generation rate is always increasing during battery operation and that irreversible entropy is a fingerprint of aging for batteries.
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