Deep Learning-based Estimation

Deep Learning-Based Estimation is a deep learning-driven methodological framework within state of charge estimation that leverages hierarchically structured neural networks to automatically extract complex electrochemical discharge patterns and map voltage, current, temperature, and impedance features to battery state of charge with minimal reliance on empirical modeling or hand-crafted feature engineering.

456

Publications

28.3K

Citations

1.8K

Authors

655

Institutions

Publications per year

2017–2026

454

Authors

1.8K

  1. MS
    Molla Shahadat Hossain Lipu

    National University of Malaysia, Malaysia

    9 publications · 1.1K citations

    9

    h-index

  2. MA
    M. A. Hannan

    National University of Malaysia, Malaysia

    8 publications · 1K citations

    8

    h-index

  3. KM
    Kashem M. Muttaqi

    University of Wollongong, Australia

    7 publications · 819 citations

    7

    h-index

  4. PJ
    Pin Jern Ker

    Universiti Tenaga Nasional, Malaysia

    7 publications · 868 citations

    7

    h-index

  5. DN
    D. N. T. How

    Universiti Tenaga Nasional, Malaysia

    6 publications · 555 citations

    6

    h-index

1–5 of 1.8K

Venues

  1. Energy

    32 publications · 2.5K citations

    25

    h-index

  2. Journal of Energy Storage

    30 publications · 2.5K citations

    24

    h-index

  3. Applied Energy

    15 publications · 2K citations

    14

    h-index

  4. IEEE Access

    16 publications · 1.1K citations

    14

    h-index

  5. arXiv (Cornell University)

    Repository · 13 publications · 632 citations

    11

    h-index

1–5