评估开放电路电压估计方法对离子电池SOC和SOH估计UKF性能的影响
M Mikhak-Beyranvand1, M Salehi2, M A Mohammadkhani2
1Department of Electrical Engineering, Technical and Vocational University (TVU), Tehran, Iran. mbeyranvand@tvu.ac.ir.
Scientific reports
|February 6, 2026
概括
与低电流 (LC) 方法相比,增量电流 (IC) 方法为离子电池提供了更高的电荷状态 (SOC) 估计精度和稳定性. 这通过改善健康状况 (SOH) 跟踪来影响电池管理系统 (BMS).
科学领域:
- 电池技术 电池技术
- 电化学工程 电化学工程
- 数据分析 数据分析
背景情况:
- 准确的充电状态 (SOC) 和健康状态 (SOH) 估计对于有效的电池管理系统 (BMS) 至关重要.
- 开放电路电压 (OCV-SOC) 模型的选择显著影响估计的准确性.
- 健康状态 (SOH) 通常通过内部电阻 (R0) 作为降解指标来评估.
研究的目的:
- 研究两种开放电路电压 (OCV) 建模方法 (低电流和增量电流) 对无气味卡尔曼波器 (UKF) 对 SOC 和 R0 估计性能的影响.
- 评估这些OCV方法在动态条件下跟踪健康状况 (SOH) 指标的有效性.
- 为了比较由LC和IC OCV建模方法得出的SOC和R0估计的准确性和稳定性.
主要方法:
- 使用等效电路模型 (ECM) 进行离子电池动力学.
- 采用低电流 (LC) 和增量电流 (IC) 方法用于开放电路电压 (OCV) 建模.
- 使用联邦城市驾驶时间表 (FUDS) 数据,应用无气味卡尔曼波器 (UKF) 进行电荷状态 (SOC) 估计和瞬间内电阻 (R0) 追踪.
主要成果:
- 增量电流 (IC) 方法表现出更快的收率和更高的SOC估计准确性,特别是在初始SOC错误的情况下.
- 低电流 (LC) 方法由于OCV曲线平滑而表现出显著的早期模拟错误.
- IC方法为健康状况 (SOH) 跟踪提供了更稳定的R0估计,而LC方法显示了更大的波动.
结论:
- 选择OCV提取方法对SOC估计的准确性和稳定性产生了重大影响.
- 在动态条件下,增量电流 (IC) 方法对于 SOC 估计和基于 R0 的 SOH 分析是优越的.
- 准确的OCV建模对于可靠的电池管理系统 (BMS) 性能至关重要.
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