World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
41
Citations
6151
World Ranking
4326
National Ranking
659

Weige Zhang publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Weige Zhang sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 143 publications — 12th percentile

12% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Weige Zhang D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Weige Zhang sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 41 D-Index — 39th percentile

39% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Overview

Weige Zhang is affiliated with Beijing Jiaotong University in China and specializes primarily in the field of Engineering, with a strong focus on Electrical and Electronic Engineering. Their research output encompasses a broad spectrum of topics related to battery technologies and automotive engineering.

The scientist's main research areas include advanced battery technologies, advancements in battery materials, electric vehicles and infrastructure, and reliability and maintenance optimization. Additional topics covered are fault detection and control systems as well as electric and hybrid vehicle technologies.

Frequent publication venues for their work include:

  • Journal of Energy Storage
  • SSRN Electronic Journal
  • Energy
  • Applied Energy
  • Energies

Weige Zhang collaborates regularly with several co-authors, among whom are:

  • Caiping Zhang
  • Bingxiang Sun
  • Linjing Zhang
  • Jiuchun Jiang
  • Jinkai Shi

Key recent papers illustrate the focus of their research on lithium-ion batteries and battery state estimation:

  • "Review on state-of-health of lithium-ion batteries: Characterizations, estimations and applications," 2021, Journal of Cleaner Production
  • "SOC estimation of Li-ion battery using convolutional neural network with U-Net architecture," 2022, Energy
  • "Fast capacity estimation for lithium-ion battery based on online identification of low-frequency electrochemical impedance spectroscopy and Gaussian process regression," 2022, Applied Energy
  • "A modified-electrochemical impedance spectroscopy-based multi-time-scale fractional-order model for lithium-ion batteries," 2021, Electrochimica Acta
  • "Economic analysis of lithium-ion batteries recycled from electric vehicles for secondary use in power load peak shaving in China," 2020, Journal of Cleaner Production

The scientist's expertise extends to automotive engineering and control and systems engineering, with research contributions addressing safety, risk, reliability, and quality as well. Their work is present in multiple subfields, reflecting a multidisciplinary approach to electrical and automotive systems. This includes investigating the reliability and maintenance aspects critical to battery performance and control systems applied to fault detection.

Best Publications

  • Lithium-ion battery aging mechanisms and life model under different charging stresses

    Yang Gao;Jiuchun Jiang;Caiping Zhang;Weige Zhang

  • Charging optimization in lithium-ion batteries based on temperature rise and charge time

    Caiping Zhang;Jiuchun Jiang;Yang Gao;Weige Zhang

  • Recognition of battery aging variations for LiFePO 4 batteries in 2nd use applications combining incremental capacity analysis and statistical approaches

    Yan Jiang;Jiuchun Jiang;Caiping Zhang;Weige Zhang

  • Adaptive unscented Kalman filter based state of energy and power capability estimation approach for lithium-ion battery

    Weige Zhang;Wei Shi;Zeyu Ma

  • Aging mechanisms under different state-of-charge ranges and the multi-indicators system of state-of-health for lithium-ion battery with Li(NiMnCo)O2 cathode

    Yang Gao;Jiuchun Jiang;Caiping Zhang;Weige Zhang

  • Study on battery pack consistency evolutions and equilibrium diagnosis for serial- connected lithium-ion batteries

    Caiping Zhang;Yan Jiang;Jiuchun Jiang;Gong Cheng

  • A rapid low-temperature internal heating strategy with optimal frequency based on constant polarization voltage for lithium-ion batteries

    Haijun Ruan;Jiuchun Jiang;Bingxiang Sun;Weige Zhang

  • State of health estimation of second-life LiFePO4 batteries for energy storage applications

    Yan Jiang;Jiuchun Jiang;Caiping Zhang;Weige Zhang

  • Evaluation of Acceptable Charging Current of Power Li-Ion Batteries Based on Polarization Characteristics

    Jiuchun Jiang;Qiujiang Liu;Caiping Zhang;Weige Zhang

  • SOC estimation of Li-ion battery using convolutional neural network with U-Net architecture

    Unknown

  • A low-temperature internal heating strategy without lifetime reduction for large-size automotive lithium-ion battery pack

    Jiuchun Jiang;Haijun Ruan;Bingxiang Sun;Leyi Wang

  • A reduced low-temperature electro-thermal coupled model for lithium-ion batteries

    Jiuchun Jiang;Haijun Ruan;Bingxiang Sun;Weige Zhang

  • Investigation of path dependence in commercial lithium-ion cells for pure electric bus applications: Aging mechanism identification

    Zeyu Ma;Zeyu Ma;Jiuchun Jiang;Wei Shi;Weige Zhang;Weige Zhang

  • Fast capacity estimation for lithium-ion battery based on online identification of low-frequency electrochemical impedance spectroscopy and Gaussian process regression

    Unknown

  • Accelerated fading recognition for lithium-ion batteries with Nickel-Cobalt-Manganese cathode using quantile regression method

    Caiping Zhang;Yubin Wang;Yang Gao;Fang Wang

  • A Review of Optimal Planning Active Distribution System: Models, Methods, and Future Researches

    Rui Li;Wei Wang;Zhe Chen;Jiuchun Jiang

  • A modified-electrochemical impedance spectroscopy-based multi-time-scale fractional-order model for lithium-ion batteries

    Haijun Ruan;Haijun Ruan;Bingxiang Sun;Jiuchun Jiang;Weige Zhang

  • Temperature dependent power capability estimation of lithium-ion batteries for hybrid electric vehicles

    Fangdan Zheng;Fangdan Zheng;Jiuchun Jiang;Bingxiang Sun;Weige Zhang

  • Estimation of State of Charge of Lithium-Ion Batteries Used in HEV Using Robust Extended Kalman Filtering

    Caiping Zhang;Jiuchun Jiang;Weige Zhang;Suleiman M. Sharkh

  • Practical state of health estimation of power batteries based on Delphi method and grey relational grade analysis

    Bingxiang Sun;Jiuchun Jiang;Fangdan Zheng;Wei Zhao

  • An Optimal Charging Method for Li-Ion Batteries Using a Fuzzy-Control Approach Based on Polarization Properties

    Jiuchun Jiang;Caiping Zhang;Jiapeng Wen;Weige Zhang

  • Optimal Allocation of Hybrid Energy Storage Systems for Smoothing Photovoltaic Power Fluctuations Considering the Active Power Curtailment of Photovoltaic

    Wei Ma;Wei Wang;Xuezhi Wu;Ruonan Hu

Frequent Co-Authors

Jiuchun Jiang
Jiuchun Jiang Hubei University of Technology
Le Yi Wang
Le Yi Wang Wayne State University
Wenzhong Gao
Wenzhong Gao University of Denver
Xiaosong Hu
Xiaosong Hu Chongqing University
Suleiman M. Sharkh
Suleiman M. Sharkh University of Southampton
Sijia Liu
Sijia Liu Michigan State University
Wei Wang
Wei Wang Beijing Jiaotong University
Zhe Chen
Zhe Chen Aalborg University
Chris Mi
Chris Mi San Diego State University
Nikolce Murgovski
Nikolce Murgovski Chalmers University of Technology

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