The electrification of vehicles has become the mainstream trend for the future. Braking energy recovery technology, as a critical technology for new energy vehicles, can recover a portion of the energy consumed during vehicle braking processes, thereby improving the vehicle's range to some extent. It serves as an effective solution to the range anxiety issue in electric vehicles. By establishing a GWO-LSTM (Grey Wolf Optimizer-Long Short-Term Memory) operating condition recognizer and a variable time-domain speed predictor based on operating condition recognition, a fuzzy controller is designed to adjust the braking force distribution coefficient in real-time, optimizing the effectiveness of braking energy recovery and enhancing the economic performance of plug-in hybrid electric vehicles.


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    Title :

    A Braking Energy Management Algorithm Based on Variable Time Domain and Operating Condition Prediction for PHEV


    Contributors:
    Yalong, Xing (author) / Tao, Xu (author) / Chunjiang, Meng (author) / Guang, Shi (author) / Yandong, Feng (author)


    Publication date :

    2024-09-23


    Size :

    715564 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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