This work is to propose a new Iterative Learning Observer (ILO)-based strategy for State Of Charge (SOC) estimation. The ILO is able to estimate the SOC in real time while identifying modeling errors and/or disturbances at the same time. An Electrical-Circuit Model (ECM) is adopted to characterize the Lithium-ion battery behavior. The ILO is designed based on this ECM and the stability is proved. Several experiments are conducted and the collected data is used to extract ECM parameters. The effectiveness of the estimated SOCs via ILO is verified by the experimental results. This implies that the ILO-based SOC determination scheme is effective to identify the SOC in real time.


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    Title :

    Robust State of Charge Estimation of Lithium-Ion Batteries via an Iterative Learning Observer


    Additional title:

    Sae Technical Papers


    Contributors:
    Gorski, David (author) / Wu, Hai (author) / Li, Meng-Feng (author) / Chen, Wen (author)

    Conference:

    SAE 2012 World Congress & Exhibition ; 2012



    Publication date :

    2012-04-16




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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