The paper presents and compares an optimal control allocation (CA) and model predictive control (MPC)-based torque vectoring (TV) for improved energy efficiency of electric vehicle with four independent electric motors. Offline and online (instantaneous) optimisation-based CA are designed for front-rear torque distribution. For overall wheel torque allocation, a production-ready MPC-based TV is extended with energy consumption minimisation terms. CA and MPC rely on power loss curves of differently sized front and rear powertrains that are fitted with polynomial regression models. Performance of both strategies is evaluated in high-fidelity nonlinear simulation environment in terms of energy efficiency improvement on standard driving cycles and impact on the vehicle dynamics in lateral manoeuvres. Results demonstrate consistent reduction of the energy consumption and preservation of the vehicle handling behaviour.


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    Titel :

    Energy-Efficient Optimal Torque Vectoring for a Four-Motor High-Performance Electric Vehicle


    Weitere Titelangaben:

    Lect.Notes Mechanical Engineering


    Beteiligte:
    Mastinu, Giampiero (Herausgeber:in) / Braghin, Francesco (Herausgeber:in) / Cheli, Federico (Herausgeber:in) / Corno, Matteo (Herausgeber:in) / Savaresi, Sergio M. (Herausgeber:in) / Prost, Mattéo (Autor:in) / Cvok, Ivan (Autor:in) / Velenis, Efstathios (Autor:in)

    Kongress:

    Advanced Vehicle Control Symposium ; 2024 ; Milan, Italy September 01, 2024 - September 05, 2024



    Erscheinungsdatum :

    04.10.2024


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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