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Eyring acceleration model for predicting calendar ageing of lithium-ion batteries

机译:预测锂离子电池日历老化的Eyring加速模型

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Modelling of lithium-ion batteries calendar ageing is often based on a semi-empirical approach by using, for example the Arrhenius acceleration model. Our approach is based on Eyring acceleration model, which is not widely used for electrochemical energy storage components. Parameter identification is typically performed without taking into account the state-of-charge (SoC) drifting. However, even in rest condition, battery cells’ SoC drifts because of capacity losses (self-discharge and capacity fade). In this work we have taken into account the SoC drift during calendar ageing tests. For this, we considered available capacity (Ah) instead of SoC (%) as ageing factor. Then, the analytical solution of the problem leads to the use of the Lambert W function in the model formulation. Simulation results show that Lambert-Eyring model is more accurate and allows a reduction in the number of parameters to be identified.
机译:锂离子电池日历老化的建模通常基于半经验方法,例如使用Arrhenius加速模型。我们的方法基于Eyring加速模型,该模型并未广泛用于电化学储能组件。通常在不考虑充电状态(SoC)漂移的情况下执行参数识别。但是,即使在静止状态下,由于容量损失(自放电和容量衰减),电池的SoC也会漂移。在这项工作中,我们考虑了日历老化测试期间的SoC漂移。为此,我们将可用容量(Ah)而非SoC(%)视为老化因素。然后,问题的解析解决方案导致在模型公式中使用Lambert W函数。仿真结果表明,Lambert-Eyring模型更加准确,可以减少要识别的参数数量。

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