Data efficient open circuit voltage hysteresis modelling – Transfer fitting the trajectory correction hysteresis (TCH) model from SOH-to-SOH and different li-ion cell chemistries

IF 5.4 Q2 CHEMISTRY, PHYSICAL
Jakob Schmitt, Ivo Horstkötter, Bernard Bäker
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引用次数: 0

Abstract

The novel trajectory correction hysteresis model (TCH) is based on measuring the first-order reversal branches (FORBs). As the enormous measurement effort required for parameterisation hinders a real-world application, this paper presents the data-efficient transfer fit (TF) method. The TF methodology is validated through two application cases: ageing update and cell chemistry adaptation. Remarkably, using only 12 measurement points on the open-circuit voltage (OCV) envelopes instead of hundreds of measurement data points, the ageing update TF model attains a mean absolute error (mae) of 4.1 mV, closely approaching the accuracy of a newly parameterised target model (3.6 mV mae). Similarly, adapting an NCA cell model to an NMC target cell using selected OCV envelope points yields a 5.3 mV mae, which further reduces to 3.2 mV with an additional discharge FORB starting at 10% SOC. In addition to the selective model adjustment using continuous OCV measurement trajectories, the much more realistic adaptation by measurement points randomly distributed within the hysteresis window was successfully demonstrated. The presented TF methodology overcomes the hurdle of data efficiency while maintaining model accuracy and paves the way for the future application of the TCH model for voltage-based SOC correction.

数据高效开路电压滞后建模 - 从 SOH 到 SOH 和不同锂离子电池化学性质的轨迹修正滞后 (TCH) 模型的转移拟合
新颖的轨迹修正滞后模型(TCH)以测量一阶反转分支(FORB)为基础。由于参数化所需的大量测量工作阻碍了实际应用,本文提出了数据高效的转移拟合(TF)方法。TF 方法通过两个应用案例进行了验证:老化更新和细胞化学适应。值得注意的是,仅使用开路电压(OCV)包络线上的 12 个测量点而不是数百个测量数据点,老化更新 TF 模型的平均绝对误差(mae)就达到了 4.1 mV,接近新参数化目标模型的精度(3.6 mV mae)。同样,使用选定的 OCV 包络点将 NCA 电池模型调整为 NMC 目标电池,可获得 5.3 mV 的平均绝对误差,而从 10% SOC 开始的额外放电 FORB 可将平均绝对误差进一步降至 3.2 mV。除了使用连续的 OCV 测量轨迹进行选择性模型调整外,还成功演示了通过随机分布在滞后窗口内的测量点进行更为真实的适应性调整。所介绍的 TF 方法克服了数据效率的障碍,同时保持了模型的准确性,为未来应用 TCH 模型进行基于电压的 SOC 校正铺平了道路。
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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来源期刊
CiteScore
9.10
自引率
0.00%
发文量
18
审稿时长
64 days
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