World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
46
Citations
8505
World Ranking
5140
National Ranking
995

Teng Liu publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Teng Liu sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 161 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Teng Liu D-index placement in Engineering and Technology in 2026

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

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 46 D-Index — 49th percentile

49% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Best Publications

  • Fast charging of energy-dense lithium-ion batteries

    Unknown

  • Thermally modulated lithium iron phosphate batteries for mass-market electric vehicles

    Xiao Guang Yang;Teng Liu;Chao Yang Wang

  • Reinforcement Learning Optimized Look-Ahead Energy Management of a Parallel Hybrid Electric Vehicle

    Teng Liu;Xiaosong Hu;Shengbo Eben Li;Dongpu Cao

  • Cost-Optimal Energy Management of Hybrid Electric Vehicles Using Fuel Cell/Battery Health-Aware Predictive Control

    Xiaosong Hu;Changfu Zou;Xiaolin Tang;Teng Liu

  • Levenberg–Marquardt Backpropagation Training of Multilayer Neural Networks for State Estimation of a Safety-Critical Cyber-Physical System

    Chen Lv;Yang Xing;Junzhi Zhang;Xiaoxiang Na

  • Comparative Study of Dynamic Programming and Pontryagin’s Minimum Principle on Energy Management for a Parallel Hybrid Electric Vehicle

    Zou Yuan;Liu Teng;Sun Fengchun;Huei Peng

  • Parallel driving in CPSS: a unified approach for transport automation and vehicle intelligence

    Fei-Yue Wang;Nan-Ning Zheng;Dongpu Cao;Clara Marina Martinez

  • Reinforcement Learning of Adaptive Energy Management With Transition Probability for a Hybrid Electric Tracked Vehicle

    Teng Liu;Yuan Zou;Dexing Liu;Fengchun Sun

  • Reinforcement learning-based real-time energy management for a hybrid tracked vehicle

    Yuan Zou;Teng Liu;Dexing Liu;Fengchun Sun

  • A look into the voltage plateau signal for detection and quantification of lithium plating in lithium-ion cells

    Xiao Guang Yang;Shanhai Ge;Teng Liu;Yongjun Leng

  • Reinforcement Learning for Hybrid and Plug-In Hybrid Electric Vehicle Energy Management: Recent Advances and Prospects

    Xiasong Hu;Teng Liu;Xuewei Qi;Matthew Barth

  • A Heuristic Planning Reinforcement Learning-Based Energy Management for Power-Split Plug-in Hybrid Electric Vehicles

    Teng Liu;Xiaosong Hu;Weihao Hu;Yuan Zou

  • Deep reinforcement learning based energy management for a hybrid electric vehicle

    Unknown

  • Adaptive Hierarchical Energy Management Design for a Plug-In Hybrid Electric Vehicle

    Teng Liu;Xiaolin Tang;Hong Wang;Huilong Yu

  • Driving conditions-driven energy management strategies for hybrid electric vehicles: A review

    Teng Liu;Teng Liu;Wenhao Tan;Xiaolin Tang;Jinwei Zhang

  • Distributed Deep Reinforcement Learning-Based Energy and Emission Management Strategy for Hybrid Electric Vehicles

    Xiaolin Tang;Jiaxin Chen;Teng Liu;Yechen Qin

  • Online Markov Chain-based energy management for a hybrid tracked vehicle with speedy Q-learning

    Unknown

  • Predictive vehicle-following power management for plug-in hybrid electric vehicles

    Shaobo Xie;Xiaosong Hu;Teng Liu;Shanwei Qi

  • Double Deep Reinforcement Learning-Based Energy Management for a Parallel Hybrid Electric Vehicle with Engine Start-Stop Strategy

    Xiaolin Tang;Jiaxin Chen;Huayan Pu;Teng Liu

  • Risk Assessment and Mitigation in Local Path Planning for Autonomous Vehicles With LSTM Based Predictive Model

    Hong Wang;Bing Lu;Jun Li;Teng Liu

Frequent Co-Authors

Fengchun Sun
Fengchun Sun Beijing Institute of Technology

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