Impact of Battery Aging on the State of Charge-Open Circuit Voltage Relationship and Its Effects on Battery Capacity Estimation

电池(电) 荷电状态 开路电压 电气工程 电压 电荷(物理) 工程类 电子工程 计算机科学 物理 功率(物理) 量子力学
作者
Gabrielle Vuylsteke,Hao Wu,William J. Moore,D. Washington
出处
期刊:SAE technical paper series 卷期号:1
标识
DOI:10.4271/2025-01-8558
摘要

<div class="section abstract"><div class="htmlview paragraph">Electrified vehicles rely on batteries to store energy for propulsion. Batteries depend on chemistry that changes over time and with use. This aging has many effects. Historically, efforts to predict and be robust to battery aging have focused on capacity loss and power loss/resistance growth. While a battery’s state of charge-open circuit voltage (SOC-OCV) relationship is typically treated as static, data illustrates that it shifts with battery age. We are not aware of any published methods to account for this effect for on-board modeling or controls. Regulations by the European Union, the Environmental Protection Agency, and the California Air Resource Board have proposed a state of certified energy (SOCE) to provide vehicle owners with a common metric reflecting the vehicle battery age. This metric captures the capacity and power loss of an aged battery. However, SOC-OCV changes with age may make accurately estimating SOCE more challenging. The upcoming regulations require accurate on-vehicle reporting of the SOCE within +5% of the true value. If SOC-OCV changes with age make it challenging to achieve this accuracy, more advanced methods may be necessary. In this work, we demonstrate the effect of battery aging on the SOC-OCV relationship, illustrate the impact the changed relationship has on SOC estimation accuracy, and discuss how the change affects capacity and energy estimation error. In some cases, the SOC estimation error caused by the aged SOC-OCV relationship is as high as 10% SOC. Capacity and energy estimation is similarly impacted, with error ranging from &lt;1% to &gt;20%. Finally, we will show that it is possible to use a semi-empirical physics-inspired SOC-OCV model to estimate the aged SOC-OCV of a battery, reduce SOC estimation error by more than 80%, and improve both capacity and energy estimation accuracy.</div></div>

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