This paper presents a extented Kalman filter based on a dynamic model of a commercial lithium ion battery pack in automotive applications, and experimental data are collected using the Noao. This vehicle is an electric track with range extender, which has been developed and produced by the association Pôle de Performance de Nevers Magny-Cours (PPNMC). This model has been developed with MATLAB/Simulink to investigate the output characteristics of lithium-ion batteries. It incorporates I–V performance of the battery, battery capacity fading, temperature effect on battery performance, and the battery temperature rise. This estimation technique is used in order to estimate some parameters, which cannot be measured directly by physical sensors such as SOC and SOH and to compensate for uncertainties in the model parameters and the measurements. The proposed model is validated by comparing simulation results with experimental data collected through battery testbed of Noao vehicle.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Characterisation of a commercial automotive lithium ion battery using extended Kalman filter


    Contributors:


    Publication date :

    2013-06-01


    Size :

    765225 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Simplified Extended Kalman Filter Observer for SOC Estimation of Commercial Power-Oriented LFP Lithium Battery Cells

    Gazzarri, Javier / Ceraolo, Massimo / Jackey, Robyn et al. | SAE Technical Papers | 2013


    Active Battery Parameter Identification Using Conditional Extended Kalman Filter

    YU HAI / LI YONGHUA | European Patent Office | 2015

    Free access

    Active battery parameter identification using conditional extended kalman filter

    YU HAI / LI YONGHUA | European Patent Office | 2017

    Free access