Shengjin Tang

1.3k total citations · 1 hit paper
42 papers, 969 citations indexed

About

Shengjin Tang is a scholar working on Safety, Risk, Reliability and Quality, Automotive Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Shengjin Tang has authored 42 papers receiving a total of 969 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Safety, Risk, Reliability and Quality, 22 papers in Automotive Engineering and 17 papers in Electrical and Electronic Engineering. Recurrent topics in Shengjin Tang's work include Reliability and Maintenance Optimization (24 papers), Advanced Battery Technologies Research (22 papers) and Advancements in Battery Materials (16 papers). Shengjin Tang is often cited by papers focused on Reliability and Maintenance Optimization (24 papers), Advanced Battery Technologies Research (22 papers) and Advancements in Battery Materials (16 papers). Shengjin Tang collaborates with scholars based in China. Shengjin Tang's co-authors include Chuanqiang Yu, Xiaosong Guo, Xiaodong Xu, Xiaosheng Si, Xue Wang, Xiaoyan Sun, Xuebing Han, Minggao Ouyang, Xiaosheng Si and Zhijie Zhou and has published in prestigious journals such as Journal of Power Sources, Chemical Engineering Journal and Construction and Building Materials.

In The Last Decade

Shengjin Tang

37 papers receiving 952 citations

Hit Papers

Challenges and opportunities toward long-life lithium-ion... 2024 2026 2025 2024 25 50 75

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shengjin Tang China 15 557 538 429 228 168 42 969
Quan Sun China 14 98 0.2× 359 0.7× 123 0.3× 85 0.4× 207 1.2× 78 632
Sanling Song United States 12 50 0.1× 548 1.0× 74 0.2× 95 0.4× 157 0.9× 17 803
Jianbao Zhou China 7 839 1.5× 429 0.8× 618 1.4× 361 1.6× 16 0.1× 10 1.0k
Yashun Wang China 14 59 0.1× 214 0.4× 110 0.3× 40 0.2× 114 0.7× 56 602
Xuerong Ye China 12 62 0.1× 113 0.2× 260 0.6× 171 0.8× 33 0.2× 78 549
Li Cai China 10 172 0.3× 81 0.2× 177 0.4× 180 0.8× 12 0.1× 40 432
Patrick W. Kalgren United States 15 42 0.1× 123 0.2× 314 0.7× 339 1.5× 7 0.0× 41 682
J.F. Watson United Kingdom 10 22 0.0× 140 0.3× 504 1.2× 504 2.2× 10 0.1× 18 839
Szymon Gontarz Poland 8 46 0.1× 178 0.3× 67 0.2× 420 1.8× 11 0.1× 19 618

Countries citing papers authored by Shengjin Tang

Since Specialization
Citations

This map shows the geographic impact of Shengjin 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 Shengjin Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shengjin Tang more than expected).

Fields of papers citing papers by Shengjin Tang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shengjin 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 Shengjin Tang. The network helps show where Shengjin Tang may publish in the future.

Co-authorship network of co-authors of Shengjin Tang

This figure shows the co-authorship network connecting the top 25 collaborators of Shengjin Tang. A scholar is included among the top collaborators of Shengjin 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 Shengjin Tang. Shengjin 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
2.
Li, Liang, et al.. (2025). Remaining useful life prediction of lithium-ion batteries based on an implicit two-stage wiener process. Journal of Energy Storage. 133. 118041–118041.
3.
Tang, Shengjin, S.J. Shi, Xiaodong Xu, et al.. (2025). Advanced health management of lithium-ion batteries: Life extension using bidirectional pulse current regulation. Journal of Energy Storage. 125. 117050–117050. 5 indexed citations
4.
Shi, S.J., Xiaodong Xu, Shengjin Tang, et al.. (2025). Life extension of lithium-ion batteries using bidirectional pulse current: Focusing on frequency. Energy. 335. 138094–138094. 1 indexed citations
5.
Tang, Shengjin, Xuebing Han, Languang Lu, et al.. (2025). Flexible upper cut-off voltage regulation for life extension of lithium-ion batteries. Energy. 318. 134776–134776.
6.
Tang, Shengjin, Xuebing Han, Languang Lu, et al.. (2024). Aging mechanism of Ni-rich cathode-based lithium-ion batteries: Focusing on upper cut-off voltages. Chemical Engineering Journal. 500. 157026–157026. 3 indexed citations
7.
Tang, Shengjin, et al.. (2024). Approximate parameter estimation and mis-specification analysis of degradation model with asymmetric random effects. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability. 239(2). 416–439.
8.
9.
Tang, Shengjin, Xuebing Han, Languang Lu, et al.. (2023). A voltage reconstruction model for lithium-ion batteries considering the polarization process. Journal of Power Sources. 588. 233744–233744. 3 indexed citations
10.
Xu, Xiaodong, Shengjin Tang, Xuebing Han, et al.. (2023). Fast capacity prediction of lithium-ion batteries using aging mechanism-informed bidirectional long short-term memory network. Reliability Engineering & System Safety. 234. 109185–109185. 37 indexed citations
11.
Xu, Xiaodong, Shengjin Tang, Xuebing Han, et al.. (2022). Joint state estimation of lithium-ion batteries combining improved equivalent circuit model with electrochemical mechanism and diffusion process. Journal of Energy Storage. 56. 106135–106135. 37 indexed citations
12.
Tang, Shengjin, et al.. (2022). Unbiased parameters estimation and mis-specification analysis of Wiener process-based degradation model with random effects. Applied Mathematical Modelling. 109. 134–160. 26 indexed citations
13.
Yang, Jiaxin, et al.. (2022). Remaining useful life prediction of implicit linear Wiener degradation process based on multi-source information. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability. 238(1). 93–111. 5 indexed citations
14.
Liu, Zhiguo, et al.. (2020). Remaining Useful Life Prediction Under Imperfect Prior Degradation Information. IEEE Access. 8. 189262–189275. 11 indexed citations
15.
Gao, Qinhe, et al.. (2019). Improved Linear Active Disturbance Rejection Control for Lever‐Type Electric Erection System with Varying Loads and Low‐Resolution Encoder. Mathematical Problems in Engineering. 2019(1). 3 indexed citations
16.
Gao, Qinhe, et al.. (2019). Linear Active Disturbance Rejection Control for Lever-Type Electric Erection System Based on Approximate Model. Journal of Control Science and Engineering. 2019. 1–7. 2 indexed citations
17.
Tang, Shengjin, et al.. (2019). Remaining Useful Life Prediction With Fusing Failure Time Data and Field Degradation Data With Random Effects. IEEE Access. 8. 11964–11978. 13 indexed citations
18.
Tang, Shengjin, et al.. (2018). Integral finite element analysis of turntable bearing with flexible rings. IOP Conference Series Materials Science and Engineering. 322. 42011–42011. 2 indexed citations
19.
Tang, Shengjin, Xiaosong Guo, & Zhijie Zhou. (2014). Mis-specification analysis of linear Wiener process–based degradation models for the remaining useful life estimation. Proceedings of the Institution of Mechanical Engineers Part O Journal of Risk and Reliability. 228(5). 478–487. 27 indexed citations
20.
Tang, Shengjin, et al.. (2009). Improved iteration centroid algorithm based on linear CCD light-spot location. 8 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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