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Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
51
Citations
8391
World Ranking
299
National Ranking
100

Electronics and Electrical Engineering

D-Index
56
Citations
10579
World Ranking
2098
National Ranking
359

Yujie Wang 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 Yujie Wang 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: 124 publications — 8th percentile

8% of scientists in this discipline score the same or lower.

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

Yujie Wang 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 Yujie Wang 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: 56 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Yujie Wang is affiliated with the University of Science and Technology of China. Their research expertise lies primarily in engineering, with a focus on subfields such as electrical and electronic engineering, automotive engineering, control and systems engineering, safety, risk, reliability and quality, and renewable energy, sustainability and the environment.

The core topics of Wang's research encompass advanced battery technologies research, advancements in battery materials, electric vehicles and infrastructure, electric and hybrid vehicle technologies, fuel cells and related materials, fault detection and control systems, and advanced battery materials and technologies.

Wang has published extensively in notable scientific venues. Frequent publication venues include:

  • Energy
  • Journal of Energy Storage
  • Applied Energy
  • eTransportation
  • IEEE Transactions on Power Electronics

Some of Wang's recent papers are:

  • A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems, 2020, Renewable and Sustainable Energy Reviews
  • Low temperature preheating techniques for Lithium-ion batteries: Recent advances and future challenges, 2022, Applied Energy
  • A review of key issues for control and management in battery and ultra-capacitor hybrid energy storage systems, 2020, eTransportation
  • Digital twin and cloud-side-end collaboration for intelligent battery management system, 2021, Journal of Manufacturing Systems
  • Perspectives and challenges for future lithium-ion battery control and management, 2023, eTransportation

Wang collaborates frequently with other researchers. The most frequent co-authors are:

  • Zonghai Chen
  • Mince Li
  • Zhendong Sun
  • Haoxiang Xiang
  • Xingchen Zhang

In addition to journal publications, Wang has contributed to book literature. One such publication is titled AI for Status Monitoring of Utility Scale Batteries, released in 2022 by the Institution of Engineering and Technology.

Best Publications

  • A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems

    Yujie Wang;Jiaqiang Tian;Zhendong Sun;Li Wang

  • A novel Gaussian process regression model for state-of-health estimation of lithium-ion battery using charging curve

    Duo Yang;Xu Zhang;Rui Pan;Yujie Wang

  • A method for state-of-charge estimation of LiFePO4 batteries at dynamic currents and temperatures using particle filter

    Yujie Wang;Chenbin Zhang;Zonghai Chen

  • State-of-health estimation for the lithium-ion battery based on support vector regression

    Duo Yang;Yujie Wang;Rui Pan;Ruiyang Chen

  • Energy management strategy for battery/supercapacitor/fuel cell hybrid source vehicles based on finite state machine

    Yujie Wang;Zhendong Sun;Zonghai Chen

  • A novel state of health estimation method of Li-ion battery using group method of data handling

    Ji Wu;Yujie Wang;Xu Zhang;Zonghai Chen

  • Modeling and state-of-charge prediction of lithium-ion battery and ultracapacitor hybrids with a co-estimator

    Yujie Wang;Chang Liu;Rui Pan;Zonghai Chen

  • A method for joint estimation of state-of-charge and available energy of LiFePO4 batteries

    Yujie Wang;Chenbin Zhang;Zonghai Chen

  • A review of key issues for control and management in battery and ultra-capacitor hybrid energy storage systems

    Yujie Wang;Li Wang;Mince Li;Zonghai Chen

  • A novel framework for Lithium-ion battery modeling considering uncertainties of temperature and aging

    Xiaopeng Tang;Yujie Wang;Changfu Zou;Ke Yao

  • Adaptive energy management strategy for fuel cell/battery hybrid vehicles using Pontryagin's Minimal Principle

    Xiyun Li;Yujie Wang;Duo Yang;Zonghai Chen

  • Digital twin and cloud-side-end collaboration for intelligent battery management system

    Yujie Wang;Ruilong Xu;Caijie Zhou;Xu Kang

  • Development of energy management system based on a rule-based power distribution strategy for hybrid power sources

    Yujie Wang;Zhendong Sun;Zonghai Chen

  • A framework for state-of-charge and remaining discharge time prediction using unscented particle filter

    Yujie Wang;Zonghai Chen

  • A Neural Network Based State-of-Health Estimation of Lithium-ion Battery in Electric Vehicles ☆

    Duo Yang;Yujie Wang;Rui Pan;Ruiyang Chen

  • Degradation model and cycle life prediction for lithium-ion battery used in hybrid energy storage system

    Chang Liu;Yujie Wang;Zonghai Chen

  • A novel active equalization method for lithium-ion batteries in electric vehicles

    Yujie Wang;Chenbin Zhang;Zonghai Chen;Jing Xie

  • A method for state-of-charge estimation of LiFePO4 batteries based on a dual-circuit state observer

    Xiaopeng Tang;Yujie Wang;Zonghai Chen

  • An on-line estimation of battery pack parameters and state-of-charge using dual filters based on pack model

    Xu Zhang;Yujie Wang;Duo Yang;Zonghai Chen

  • A fractional-order model-based state estimation approach for lithium-ion battery and ultra-capacitor hybrid power source system considering load trajectory

    Yujie Wang;Guangze Gao;Xiyun Li;Zonghai Chen

  • Load-adaptive real-time energy management strategy for battery/ultracapacitor hybrid energy storage system using dynamic programming optimization

    Chang Liu;Yujie Wang;Li Wang;Zonghai Chen

Frequent Co-Authors

Zonghai Chen
Zonghai Chen Argonne National Laboratory
Furong Gao
Furong Gao Hong Kong University of Science and Technology

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