电动汽车充电状态监测与多级安全预报警方法

doi:10.19595/j.cnki.1000-6753.tces.211846

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Abstract The frequent occurrence of electric vehicle burning accidents during the charging process has become a key issue restricting the development of electric vehicles. Aiming at the problem of charging safety, this paper proposes a new method of electric vehicle charging status monitoring and multi-level safe pre-warning. The method is based on convolutional neural networks (CNN) and bi-directional long-short memory (BiLSTM), uses the charging history data of electric vehicles to construct a CNN-BiLSTM multi-level safety pre-warning model; designed the charging status monitoring and multi-level safe pre-warning implementation process of the model; compared with other models, verified the prediction accuracy of the model; through the sliding window method, the pre-warning threshold of the model is determined. Experiments have shown that this method can monitor the charging process of electric vehicles in real time, find faults in time and send out pre-warning signals to ensure the safety of electric vehicle charging.

Key words： Electric vehicle charging process convolutional neural networks bi-directional long-short term memory multi-level safety pre-warning

Received: 13 November 2021

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TP277

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	Gao Dexin
	Zheng Xiaoyu
	Wang Yi
	Yang Qing

Cite this article:

Gao Dexin,Zheng Xiaoyu,Wang Yi等. A State Monitoring and Multi-Level Safety Pre-Warning Method for Electric Vehicle Charging Process[J]. Transactions of China Electrotechnical Society, 2022, 37(9): 2252-2262.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.211846 OR https://dgjsxb.ces-transaction.com/EN/Y2022/V37/I9/2252

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