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Due to the complexity and timeliness of the dual power source control system for range extended electric vehicles, a real-time predictive fuzzy energy management strategy based on speed prediction, which comprehensively takes into account the demand power of auxiliary power unit, future average speed and driving distance is proposed in this work. Firstly, to improve the topicality and accuracy of the control system, the convolutional neural network with long short-term memory neural network (CNN-LSTM) algorithm is adopted to predict the future driving speed by the speed features and adjacent speeds.