In electric vehicles (EVs) the battery capacity is a key parameter that must be accurately estimated through the service time of the battery. This paper proposes a new machine-learning model namely a Multi-output Convolved Gaussian-Process (MCGP) model for capacity estimation of lithium-ion (Li-ion) battery cells used in an EV application. The proposed technique can be utilized in enhancing the state-of-charge (SOC) estimation accuracy and moreover it can provide an accurate prediction tool for the remaining useful life (RUL) of a battery cell. The performance of the proposed model is validated using experimental data obtained by cycling two 3.6-V/16.5-Ah Li-ion battery cells. Results show the effectiveness of the proposed model.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Multi-Output Convolved Gaussian Process Model for Capacity Estimation of Electric Vehicle Li-ion Battery Cells


    Contributors:


    Publication date :

    2019-06-01


    Size :

    478030 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    SYSTEM AND METHOD FOR HYBRID-ELECTRIC VEHICLE BATTERY CAPACITY ESTIMATION

    ENSLIN HEINRICH / GRIMES JEFFERY R | European Patent Office | 2021

    Free access


    SYSTEM AND METHOD FOR HYBRID-ELECTRIC VEHICLE BATTERY CAPACITY ESTIMATION

    ENSLIN HEINRICH / GRIMES JEFFERY R | European Patent Office | 2021

    Free access

    System and method for hybrid-electric vehicle battery capacity estimation

    ENSLIN HEINRICH / GRIMES JEFFERY R | European Patent Office | 2021

    Free access

    Incremental Capacity Analysis for Electric Vehicle Battery State-of-Health Estimation

    Schaltz, Erik / Stroe, Daniel-Ioan / Norregaard, Kjeld et al. | IEEE | 2019