World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
70
Citations
18883
World Ranking
387
National Ranking
52

Zhenpo Wang publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Zhenpo Wang sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 263 publications — 64th percentile

64% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Zhenpo Wang D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Zhenpo Wang sits on this spectrum.

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 70 D-Index — 89th percentile

89% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

Overview

Zhenpo Wang is a researcher affiliated with the Beijing Institute of Technology in China, focusing primarily on engineering disciplines. Their research covers a range of specialized subfields including automotive engineering, electrical and electronic engineering, control and systems engineering, safety, risk, reliability and quality, and mechanical engineering.

Their work concentrates on several key topics, notably advanced battery technologies research, electric vehicles and infrastructure, advancements in battery materials, electric and hybrid vehicle technologies, vehicle dynamics and control systems, fault detection and control systems, and reliability and maintenance optimization.

Zhenpo Wang frequently contributes to multiple academic venues, with a significant number of publications appearing in these journals and conferences:

  • IEEE Transactions on Transportation Electrification
  • Journal of Energy Storage
  • Energy
  • IEEE Transactions on Vehicular Technology
  • Applied Energy

Their recent papers demonstrate a focus on lithium-ion batteries and electric vehicle technologies. These publications include:

  • "Sustainable Recycling Technology for Li-Ion Batteries and Beyond: Challenges and Future Prospects", 2020, Chemical Reviews
  • "Battery Fault Diagnosis for Electric Vehicles Based on Voltage Abnormality by Combining the Long Short-Term Memory Neural Network and the Equivalent Circuit Model", 2020, IEEE Transactions on Power Electronics
  • "State of health estimation for Li-ion battery via partial incremental capacity analysis based on support vector regression", 2020, Energy
  • "China's battery electric vehicles lead the world: achievements in technology system architecture and technological breakthroughs", 2022, Green Energy and Intelligent Transportation
  • "Energy consumption analysis and prediction of electric vehicles based on real-world driving data", 2020, Applied Energy

Collaborative work is a significant aspect of their research, with frequent co-authors including Peng Liu, Zhaosheng Zhang, Lei Zhang, Junjun Deng, and Shuo Wang. These collaborations indicate a network of research partners contributing to related topics in energy storage and vehicle electrification.

Best Publications

  • Sustainable Recycling Technology for Li-Ion Batteries and Beyond: Challenges and Future Prospects.

    Ersha Fan;Li Li;Zhenpo Wang;Jiao Lin

  • A review of supercapacitor modeling, estimation, and applications: A control/management perspective

    Lei Zhang;Lei Zhang;Xiaosong Hu;Zhenpo Wang;Fengchun Sun

  • A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors

    Changfu Zou;Lei Zhang;Xiaosong Hu;Zhenpo Wang

  • State of health estimation for Li-Ion battery using incremental capacity analysis and Gaussian process regression

    Xiaoyu Li;Changgui Yuan;Xiaohui Li;Zhenpo Wang

  • Remaining useful life prediction for lithium-ion batteries based on a hybrid model combining the long short-term memory and Elman neural networks

    Xiaoyu Li;Lei Zhang;Zhenpo Wang;Peng Dong

  • China’s Battery Electric Vehicles Lead the World: Achievements in Technology System Architecture and Technological Breakthroughs

    Unknown

  • Grid Power Peak Shaving and Valley Filling Using Vehicle-to-Grid Systems

    Unknown

  • State-of-health estimation for Li-ion batteries by combing the incremental capacity analysis method with grey relational analysis

    Xiaoyu Li;Zhenpo Wang;Lei Zhang;Changfu Zou

  • Fault and defect diagnosis of battery for electric vehicles based on big data analysis methods

    Yang Zhao;Peng Liu;Zhenpo Wang;Lei Zhang

  • Fault prognosis of battery system based on accurate voltage abnormity prognosis using long short-term memory neural networks

    Jichao Hong;Jichao Hong;Zhenpo Wang;Yongtao Yao

  • Multiobjective Optimal Sizing of Hybrid Energy Storage System for Electric Vehicles

    Lei Zhang;Xiaosong Hu;Zhenpo Wang;Fengchun Sun

  • An Overview on Thermal Safety Issues of Lithium-ion Batteries for Electric Vehicle Application

    Jianan Zhang;Lei Zhang;Fengchun Sun;Zhenpo Wang

  • Prognostic health condition for lithium battery using the partial incremental capacity and Gaussian process regression

    Xiaoyu Li;Zhenpo Wang;Jinying Yan

  • Battery Fault Diagnosis for Electric Vehicles Based on Voltage Abnormality by Combining the Long Short-Term Memory Neural Network and the Equivalent Circuit Model

    Da Li;Zhaosheng Zhang;Peng Liu;Zhenpo Wang

  • State of health estimation for Li-ion battery via partial incremental capacity analysis based on support vector regression

    Xiaoyu Li;Changgui Yuan;Zhenpo Wang

  • Energy consumption analysis and prediction of electric vehicles based on real-world driving data

    Jin Zhang;Zhenpo Wang;Peng Liu;Zhaosheng Zhang

  • Overcharge-to-thermal-runaway behavior and safety assessment of commercial lithium-ion cells with different cathode materials: A comparison study

    Zhenpo Wang;Jing Yuan;Xiaoqing Zhu;Hsin Wang

  • Voltage fault diagnosis and prognosis of battery systems based on entropy and Z-score for electric vehicles

    Zhenpo Wang;Jichao Hong;Peng Liu;Lei Zhang

  • Battery Aging Assessment for Real-World Electric Buses Based on Incremental Capacity Analysis and Radial Basis Function Neural Network

    Chengqi She;Zhenpo Wang;Fengchun Sun;Peng Liu

  • Co-estimation of capacity and state-of-charge for lithium-ion batteries in electric vehicles

    Xiaoyu Li;Zhenpo Wang;Lei Zhang

  • Overcharge investigation of large format lithium-ion pouch cells with Li(Ni0.6Co0.2Mn0.2)O2 cathode for electric vehicles: Thermal runaway features and safety management method

    Xiaoqing Zhu;Xiaoqing Zhu;Zhenpo Wang;Yituo Wang;Hsin Wang

  • A comparative study of equivalent circuit models of ultracapacitors for electric vehicles

    Lei Zhang;Lei Zhang;Zhenpo Wang;Xiaosong Hu;Fengchun Sun

  • A novel fault diagnosis method for lithium-Ion battery packs of electric vehicles

    Xiaoyu Li;Zhenpo Wang

  • Thermal runaway behavior during overcharge for large-format Lithium-ion batteries with different packaging patterns

    Lvwei Huang;Zhaosheng Zhang;Zhenpo Wang;Lei Zhang

  • Fractional-order modeling and State-of-Charge estimation for ultracapacitors

    Lei Zhang;Lei Zhang;Xiaosong Hu;Zhenpo Wang;Fengchun Sun

  • Longitudinal Vehicle Speed Estimation for Four-Wheel-Independently-Actuated Electric Vehicles Based on Multi-Sensor Fusion

    Xiaolin Ding;Zhenpo Wang;Lei Zhang;Cong Wang

Frequent Co-Authors

David G. Dorrell
David G. Dorrell University of Turku
Fengchun Sun
Fengchun Sun Beijing Institute of Technology
Xiaosong Hu
Xiaosong Hu Chongqing University
Hsin Wang
Hsin Wang Oak Ridge National Laboratory
Yang Zhao
Yang Zhao Beijing Institute of Technology
Dongpu Cao
Dongpu Cao University of Waterloo
Dirk Uwe Sauer
Dirk Uwe Sauer RWTH Aachen University
Le Yi Wang
Le Yi Wang Wayne State University
Zhenyu Sun
Zhenyu Sun Beijing University of Chemical Technology
Yanfei Gao
Yanfei Gao University of Tennessee at Knoxville

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