Due to their high energy density, power density, and durability, lithium-ion (Li-ion) batteries are rapidly becoming the most popular energy storage method for electric vehicles. Difficulty arises in accurately estimating the amount of left capacity in the battery during operation time, commonly known as battery state of charge (SOC).This paper presents a comparative study between six different Equivalent Circuit Li-ion battery models and two different state of charge (SOC) estimation strategies. The Battery models cover the state-of-the-art of Equivalent Circuit models discussed in literature. The Li-ion battery SOC is estimated using non-linear estimation strategies i.e. Extended Kalman filter (EKF) and the Smooth Variable Structure Filter (SVSF).The models and the state of charge estimation strategies are compared against simulation data obtained from AVL CRUISE software. The effectiveness of the models and estimation strategies is then compared through a comprehensive evaluation for model complexity, model accuracy, and root mean squared error in state of charge estimation.


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    Title :

    Li-Ion Battery SOC Estimation Using Non-Linear Estimation Strategies Based on Equivalent Circuit Models


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE 2014 World Congress & Exhibition ; 2014



    Publication date :

    2014-04-01




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English