Aihua Tang

2.3k total citations · 1 hit paper
64 papers, 1.6k citations indexed

About

Aihua Tang is a scholar working on Automotive Engineering, Electrical and Electronic Engineering and Control and Systems Engineering. According to data from OpenAlex, Aihua Tang has authored 64 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Automotive Engineering, 44 papers in Electrical and Electronic Engineering and 14 papers in Control and Systems Engineering. Recurrent topics in Aihua Tang's work include Advanced Battery Technologies Research (51 papers), Advancements in Battery Materials (26 papers) and Electric Vehicles and Infrastructure (18 papers). Aihua Tang is often cited by papers focused on Advanced Battery Technologies Research (51 papers), Advancements in Battery Materials (26 papers) and Electric Vehicles and Infrastructure (18 papers). Aihua Tang collaborates with scholars based in China, United States and Australia. Aihua Tang's co-authors include Quanqing Yu, Chun Wang, Cheng Lin, Wenwei Wang, Weixiang Shen, Yukun Huang, Lin Cheng, Rui Liu, Yuwei Nie and Lei Yao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Power Sources and IEEE Transactions on Industrial Electronics.

In The Last Decade

Aihua Tang

58 papers receiving 1.5k citations

Hit Papers

OCV-SOC-Temperature Relationship Construction and State o... 2023 2026 2024 2023 40 80 120
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. OCV-SOC-Temperature Relationship Construction and State of Charge Estimation for a Series– Parallel Lithium-Ion Battery Pack
    2023 124 citations Quanqing Yu, Yukun Huang et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Aihua Tang China 21 1.4k 1.1k 375 133 67 64 1.6k
Chunmei Yu China 23 1.5k 1.1× 1.3k 1.1× 436 1.2× 152 1.1× 44 0.7× 78 1.7k
Siyu Jin China 13 1.1k 0.8× 1.1k 0.9× 377 1.0× 188 1.4× 83 1.2× 25 1.4k
Jiaqiang Tian China 15 1.7k 1.2× 1.5k 1.3× 511 1.4× 209 1.6× 78 1.2× 50 1.9k
Ephrem Chemali Canada 12 1.5k 1.1× 1.4k 1.2× 449 1.2× 97 0.7× 33 0.5× 12 1.7k
Xiaosong Hu China 21 1.3k 1.0× 1.2k 1.0× 406 1.1× 155 1.2× 73 1.1× 48 1.6k
Mince Li China 13 1.5k 1.1× 1.4k 1.2× 386 1.0× 119 0.9× 47 0.7× 23 1.7k
Zechang Sun China 22 1.8k 1.3× 1.7k 1.5× 441 1.2× 71 0.5× 66 1.0× 85 2.1k

Countries citing papers authored by Aihua Tang

Since Specialization
Citations

This map shows the geographic impact of Aihua Tang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Aihua Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aihua Tang more than expected).

Fields of papers citing papers by Aihua Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aihua Tang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Aihua Tang. The network helps show where Aihua Tang may publish in the future.

Co-authorship network of co-authors of Aihua Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Aihua Tang. A scholar is included among the top collaborators of Aihua Tang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Aihua Tang. Aihua Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Hong, Jichao, Fengwei Liang, Kerui Li, et al.. (2025). Thermal runaway boundary recognition and early detection of lithium battery based on machine vision algorithm. Energy. 340. 139285–139285.
3.
Tang, Aihua, et al.. (2025). Adaptive engineering-assisted deep learning for battery module health monitoring across dynamic operations. Energy. 322. 135332–135332. 3 indexed citations
4.
Shu, Xing, et al.. (2025). Meta Learning Based State of Health Estimation of Lithium-Ion Batteries With Small Sampling Retraining. IEEE Transactions on Industrial Electronics. 73(2). 2462–2474.
5.
Peng, Simin, et al.. (2024). SOH early prediction of lithium-ion batteries based on voltage interval selection and features fusion. Energy. 308. 132993–132993. 49 indexed citations
6.
Shu, Xing, Xi Liu, Renhua Feng, et al.. (2024). State of health estimation for lithium-ion batteries based on voltage segment and transformer. Journal of Energy Storage. 108. 115200–115200. 10 indexed citations
7.
Tang, Aihua, et al.. (2024). Battery state of health estimation under dynamic operations with physics-driven deep learning. Applied Energy. 370. 123632–123632. 46 indexed citations
8.
Tang, Aihua, et al.. (2024). Deep learning driven battery voltage-capacity curve prediction utilizing short-term relaxation voltage. eTransportation. 22. 100378–100378. 11 indexed citations
9.
Wang, Chun, Qiang Li, Aihua Tang, & Quanqing Yu. (2024). Equivalent state of charge estimation method of hybrid energy storage system for electric vehicles based on multiple operating modes. Journal of Energy Storage. 100. 113627–113627. 4 indexed citations
10.
Tang, Aihua, et al.. (2024). Data-physics-driven estimation of battery state of charge and capacity. Energy. 294. 130776–130776. 30 indexed citations
11.
Tang, Aihua, et al.. (2024). Physics-informed battery degradation prediction: Forecasting charging curves using one-cycle data. Journal of Energy Chemistry. 101. 825–836. 11 indexed citations
12.
Tang, Aihua, Peng Gong, Yukun Huang, et al.. (2023). Orthogonal design based pulse preheating strategy for cold lithium-ion batteries. Applied Energy. 355. 122277–122277. 11 indexed citations
13.
Nie, Yuwei, et al.. (2023). Online health prognosis for lithium-ion batteries under dynamic discharge conditions over wide temperature range. eTransportation. 18. 100296–100296. 49 indexed citations
14.
Tang, Aihua, et al.. (2023). State of health estimation based on inconsistent evolution for lithium-ion battery module. Energy. 286. 129575–129575. 16 indexed citations
15.
Tang, Aihua, Yihan Jiang, Quanqing Yu, & Zhigang Zhang. (2023). A hybrid neural network model with attention mechanism for state of health estimation of lithium-ion batteries. Journal of Energy Storage. 68. 107734–107734. 96 indexed citations
16.
17.
Tang, Aihua, et al.. (2023). Week-level early warning strategy for thermal runaway risk based on real-scenario operating data of electric vehicles. eTransportation. 19. 100308–100308. 21 indexed citations
18.
Wang, Chun, Qiang Zhang, Aihua Tang, & W. Xu. (2023). State-of-Charge Estimation of Ultracapacitor Based on H Infinity Filter Considering Variable Temperature. Journal of Electrochemical Energy Conversion and Storage. 21(1). 2 indexed citations
19.
Wang, Chun, et al.. (2023). Multistate joint estimation of ultracapacitor based on trans-scale dual extended Kalman filter. Control Engineering Practice. 137. 105555–105555. 3 indexed citations
20.
Tang, Aihua, et al.. (2022). Research on Radiated Immunity Test Methods for ADAS Functions Considering Vehicle In-the-Loop. World Electric Vehicle Journal. 13(11). 211–211. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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