Deep learning in the state of charge estimation for li-ion batteries of electric vehicles: a review

HIGHLIGHTS

SUMMARY

    Fuzzy logic, support vector machines, and neural_networks are the current traditional machine_learning methods commonly used for the SOC estimation of the lithium batteries of EVs in the off-line condition. 1D-CNN can effectively extract the data features of Li-ion battery data, but it has lower precision of SOC estimation than other neural_network structures when it is only used in the 1D-CNN structure. TCN is designed for time series data by using the convolutional neural_network structure, but its robustness of SOC estimation is lower than that of others. 1D-CNN + X + Y . . .

     

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