The battery pack accounts for a large share of an electric vehicle cost. In this context, making sure that the battery pack life matches the lifetime of the vehicle is critical. The present work proposes a battery aging management framework which is capable of controlling the battery capacity degradation while guaranteeing acceptable vehicle performance in terms of driving range, recharge time, and drivability. The strategy acts on the maximum battery current, and on the depth of discharge. The formalization of the battery management issue leads to a multi-objective, multi-input optimization problem for which we propose an online solution. The algorithm, given the current battery residual capacity and a prediction of the driver's behavior, iteratively selects the best control variables over a suitable control discretization step. We show that the best aging strategy depends on the driving style. The strategy is thus made adaptive by including a self-learnt, Markov-chain-based driving style model in the optimization routine. Extensive simulations demonstrate the advantages of the proposed strategy against a trivial strategy and an offline benchmark policy over a life of 200 000 (km).


    Access

    Download


    Export, share and cite



    Title :

    Active adaptive battery aging management for electric vehicles


    Contributors:

    Publication date :

    2020-01-01



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



    Active Battery Thermal Management within Electric and Plug-In Hybrid Electric Vehicles

    Mayyas, Abdel Raouf / Page, Corey / Carroll, Joshua Kurtis et al. | SAE Technical Papers | 2016


    REAL-TIME ENERGY MANAGEMENT STRATEGY FOR HYBRID ELECTRIC VEHICLES WITH REDUCED BATTERY AGING

    RIZZONI GIORGIO / TANG LI | European Patent Office | 2018

    Free access

    Active Battery Thermal Management within Electric and Plug-In Hybrid Electric Vehicles

    Carroll, Joshua Kurtis / Alzorgan, Mohammad / Page, Corey et al. | British Library Conference Proceedings | 2016


    REAL-TIME ENERGY MANAGEMENT STRATEGY FOR HYBRID ELECTRIC VEHICLES WITH REDUCED BATTERY AGING

    RIZZONI GIORGIO / TANG LI | European Patent Office | 2020

    Free access

    Battery State-of-health Adaptive Energy Management of Hybrid Electric Vehicles

    Anselma, Pier Giuseppe / Kollmeyer, Phillip / Emadi, Ali | IEEE | 2022