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Model-based internal short circuit detection of lithium-ion batteries using standard charge profiles

机译:使用标准充电曲线的基于模型的锂离子电池内部短路检测

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As a latent risk, soft internal short circuit (ISCr) occured in lithium-ion batteries may cause thermal runaway with fire and explosion. To secure battery safety for users, detection of soft ISCr is important. However, ISCr detection of existing model-based methods is totally dependent on type of load currents. Therefore, the ISCr must be detected with standard charge profiles instead of particular load currents, which are measured with high sampling rate and have big fluctuations. In this paper, using constant currents and terminal voltages for charge of the battery, a model-based ISCr detection algorithm is proposed. Equivalent circuit model of the battery is used to estimate ISCr resistance as a fault index. The proposed method is verified in simulations for varied ISCr faults. Accuracy of the estimated ISCr resistances is above 93.37%, thereby leading to early detection of the ISCr.
机译:作为潜在的风险,锂离子电池中发生的内部软短路(ISCr)可能会导致热失控,并引起火灾和爆炸。为了确保用户的电池安全,检测软ISCr至关重要。但是,现有基于模型的方法的ISCr检测完全取决于负载电流的类型。因此,必须使用标准电荷曲线而不是特定的负载电流来检测ISCr,而负载电流的采样率较高且波动较大。在本文中,使用恒定电流和端电压对电池充电,提出了一种基于模型的ISCr检测算法。电池的等效电路模型用于估计ISCr电阻作为故障指标。所提出的方法在各种ISCr故障的仿真中得到了验证。估计的ISCr电阻的准确度高于93.37%,从而可以及早发现ISCr。

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