The invention relates to the technical field of electric vehicles, in particular to an electric vehicle remaining mileage prediction method and device, an electric vehicle and a medium, and the method comprises the steps: obtaining state data and an actual remaining charge state SOC of the electric vehicle within a first preset duration; the state data in the preset duration are input into a pre-established prediction model, the unit SOC driving mileage of the state data is output, the prediction model comprises n layers of recurrent neural network LSTM modules and a multi-layer perceptron MLP module, the state data in the preset duration are input into the n layers of LSTM modules, sequence information of the state data is obtained, the sequence information is input into the MLP module, and the MLP module outputs the unit SOC driving mileage of the state data. The unit SOC driving mileage is output; and calculating the remaining mileage of the electric vehicle according to the actual SOC and the unit SOC driving mileage. Therefore, the problems that in the prior art, the prediction accuracy of the endurance mileage is not high, so that the user cannot arrive at the destination due to insufficient electric quantity, and the car use experience of the user is reduced are solved.
本申请涉及电动汽车技术领域,特别涉及一种电动汽车剩余里程预测方法、装置、电动汽车及介质,其中,方法包括:获取电动汽车第一预设时长内的状态数据和实际剩余电荷状态SOC;将预设时长内的状态数据输入预先建立的预测模型,输出状态数据的单位SOC行驶里程,其中,预测模型包括n层循环神经网络LSTM模块和多层感知机MLP模块,将预设时长内的状态数据输入n层LSTM模块,得到状态数据的序列信息,并将序列信息输入MLP模块,输出单位SOC行驶里程;根据实际SOC和单位SOC行驶里程计算电动汽车的剩余里程。由此,解决了相关技术中对于续航里程的预测准确度不高,导致可能存在由于电量不足而无法抵达目的地,降低用户用车体验感等问题。
Electric vehicle remaining mileage prediction method and device, electric vehicle and medium
电动汽车剩余里程预测方法、装置、电动汽车及介质
2023-03-07
Patent
Electronic Resource
Chinese
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