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Improved ANN for Estimation of Power Consumption of EV for Real-Time Battery Diagnosis

机译:用于实时电池诊断的电动汽车功耗估算的改进人工神经网络

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In this paper, an artificial neural network (ANN), which estimates the power consumption of an electric vehicle (EV) during the deterioration process of power storage is described. This network provides important information for real-time battery diagnosis, such as state of charge of a Li-Ion battery for an EV or HEV. The data are retrieved from a scaled experiment, based on the JC08 test cycle. The network is presented as a practical alternative to analytical and empirical methods. It can predict the power consumption by an optimal solution and categorize the deterioration of the power storage with high estimation precision and within short time.
机译:本文介绍了一种人工神经网络(ANN),用于估算电动汽车(EV)在蓄电性能恶化过程中的功耗。该网络为实时电池诊断提供了重要信息,例如EV或HEV的锂离子电池的充电状态。基于JC08测试周期,从规模化实验中检索数据。该网络是作为分析和经验方法的一种实用替代方案。它可以通过最佳解决方案预测功耗,并且可以在短时间内以较高的估算精度对蓄电装置的退化进行分类。

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