Lithium-ion batteries are widely used in electric vehicle powertrain systems. As batteries age, their state of health (SOH), indicated by their usable capacity and power capability, decreases. For reliable battery operation, accurate estimation and prediction of SOH are essential. This paper proposes an algorithm for estimating battery capacity SOH from an open-source fast charging dataset with many different charge profile types. Histogram data is created from the measured time domain data and fed into a feedforward neural network (FNN). To capture the impact of different charge profiles on aging, current and state of charge (SOC) are multiplied together to create an additional synthetic input to the estimator. To reduce the number of inputs to the FNN to only those that contain valuable information, we use principal component analysis to reduce the total number of inputs by 80%. An SOH algorithm is proposed that can estimate capacity throughout the battery's life with a 1.03% root mean square percentage error (RMSPE) and 0.68% mean absolute percentage error (MAPE).


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Lithium-ion Battery State-of-Health Estimation via Histogram Data, Principal Component Analysis, and Machine Learning


    Contributors:


    Publication date :

    2023-06-21


    Size :

    3911682 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Machine Learning Approaches for Lithium-Ion Battery Health Parameters Estimation

    Mandhana, Abhishek / Gambhir, Ameya V / Joshi, Umita Deepak | SAE Technical Papers | 2022



    Modular machine learning structure for electric vehicle battery state of health estimation

    NEGOITA GIANINA ALINA / TESKEY WESLEY / RENN JEAN-BAPTISTE et al. | European Patent Office | 2024

    Free access


    MODULAR MACHINE LEARNING STRUCTURE FOR ELECTRIC VEHICLE BATTERY STATE OF HEALTH ESTIMATION

    NEGOITA GIANINA ALINA / TESKEY WESLEY / RENN JEAN-BAPTISTE et al. | European Patent Office | 2023

    Free access