Online accurate battery state-of-health (SOH) estimation is crucial for ensuring safe and reliable operations of electric vehicles (EVs). Yet, such estimation problem remains a challenge in reality due to complex battery degradation behaviors and dynamic EV operations. This article proposes a novel deep learning-based framework, a bilateral-branched visual transformer with dilated self-attention (Bi-ViT-DSA), for online SOH estimation. The proposed framework considers partial charging segments during incomplete charging based on two mainstream charging modes, the multistage fast-charging (MSFC) and constant-current constant-voltage (CCCV) charging. To incorporate multitimescale battery aging dynamics into SOH estimation, a novel biparty input structure is developed to convey both inner cycle and intracycle degradation information from raw data. The proposed Bi-ViT-DSA is developed to learn multitimescale high-level latent features from the biparty input in parallel for SOH estimation. A dilated self-attention (DSA) mechanism is developed to reduce redundant operations in modeling. Computational studies are conducted on datasets of batteries under different chemistries and test conditions. Results validate the feasibility and robustness of the proposed method and its superior performance over a set of state-of-the-art benchmarks.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Deep Learning Powered Online Battery Health Estimation Considering Multitimescale Aging Dynamics and Partial Charging Information


    Contributors:


    Publication date :

    2024-03-01


    Size :

    2976117 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Battery aging estimation with deep learning

    Veeraraghavan, Amirthalakshmi / Adithya, Viswa / Bhave, Ajinkya et al. | IEEE | 2017


    Online battery state of health estimation during charging

    KUOVO MIKKO / VATANEN HARRI / JUNTUNEN RAIMO | European Patent Office | 2024

    Free access

    ONLINE BATTERY STATE OF HEALTH ESTIMATION DURING CHARGING

    KUOVO MIKKO / VATANEN HARRI / JUNTUNEN RAIMO | European Patent Office | 2022

    Free access

    Partial Charging Method for Lithium-Ion Battery State-of-Health Estimation

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