The powertrain and air-conditioning (AC) system constitute the primary electricity consumption components in electric vehicles (EVs). Hence, to enhance the energy optimality of an ego vehicle that has to travel across consecutive traffic lights following a preceding vehicle with stochastic driving behavior, as presented in the benchmark challenge of CVCI 2023, a model predictive control (MPC) -based optimization method is proposed to parallel conduct kinematic optimization and AC regulation. Furthermore, a hierarchical framework is adopted in kinematic optimization for speed planning and powertrain control. To incorporate the road terrain information and enhance the feasibility of the formulated optimization problem, speed planning with MPC is formulated in the space domain with an adaptive planning horizon. Validation results exhibit that the proposed method reduces the overall electricity consumption by 12.82% to 24.84% among the five provided traffic scenarios compared with the benchmark method, demonstrating superior energy-saving potential of the proposed method.


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    Title :

    Integrated optimization of kinematic and air-conditioning states for eco-driving and eco-cooling


    Contributors:
    Zhang, Chuntao (author) / Ning, Changjiu (author) / Ma, Heyang (author) / Sun, Chao (author)


    Publication date :

    2023-10-27


    Size :

    4720727 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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