Xing Shu

2.3k total citations · 1 hit paper
52 papers, 1.7k citations indexed

About

Xing Shu is a scholar working on Automotive Engineering, Electrical and Electronic Engineering and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Xing Shu has authored 52 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Automotive Engineering, 38 papers in Electrical and Electronic Engineering and 11 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Xing Shu's work include Advanced Battery Technologies Research (41 papers), Advancements in Battery Materials (29 papers) and Electric Vehicles and Infrastructure (15 papers). Xing Shu is often cited by papers focused on Advanced Battery Technologies Research (41 papers), Advancements in Battery Materials (29 papers) and Electric Vehicles and Infrastructure (15 papers). Xing Shu collaborates with scholars based in China, United Kingdom and France. Xing Shu's co-authors include Zheng Chen, Jiangwei Shen, Yonggang Liu, Yuanjian Zhang, Guang Li, Renxin Xiao, Hongqian Zhao, Zhenzhen Lei, Guang Li and Shuhang Shen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Power Sources and Scientific Reports.

In The Last Decade

Xing Shu

46 papers receiving 1.7k citations

Hit Papers

A comparative investigation on the energy flow of pure ba... 2025 2026 2025 5 10 15 20 25
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. A comparative investigation on the energy flow of pure battery electric vehicle under different driving conditions
    2025 28 citations Renhua Feng, Jing Yu et al. profile →

Peers

Xing Shu
Prashant Shrivastava Malaysia
Zechang Sun China
Yongzhi Lai China
Xiangbao Song Hong Kong
Ephrem Chemali Canada
Mingwang Wang China
Yingzhou Wang China
Mona Faraji Niri United Kingdom
Kanendra Naidu Malaysia
Prashant Shrivastava Malaysia
Xing Shu
Citations per year, relative to Xing Shu Xing Shu (= 1×) peers Prashant Shrivastava

Countries citing papers authored by Xing Shu

Since Specialization
Citations

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

Fields of papers citing papers by Xing Shu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xing Shu

This figure shows the co-authorship network connecting the top 25 collaborators of Xing Shu. A scholar is included among the top collaborators of Xing Shu 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 Xing Shu. Xing Shu 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
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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.
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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
5.
Shen, Jiangwei, Zheng Zhang, Zheng Chen, et al.. (2024). Temperature Estimation of Multiple Places for Lithium-Ion Batteries Based on Improved Electrochemical Thermal Modeling. IEEE Transactions on Transportation Electrification. 11(1). 382–392. 2 indexed citations
6.
Shu, Xing, Zheng Chen, Jiangwei Shen, et al.. (2024). Robust State of Health Estimation for Lithium-Ion Batteries Considering Random Charging Behaviors. IEEE Transactions on Transportation Electrification. 11(2). 5545–5554. 4 indexed citations
7.
Zhao, Hongqian, Zhigang Zhao, Xing Shu, et al.. (2024). Voltage fault diagnosis and prognostic of lithium-ion batteries in electric scooters based on hybrid neural network and multiple thresholds. Journal of Power Sources. 618. 235197–235197. 7 indexed citations
8.
Liu, Yuheng, Siyu Wang, Zhi Zhang, et al.. (2024). Construction and Comparation of Critical Nitrogen Concentration Dilution Curves for Spring and Autumn Potato in China. Agronomy. 14(11). 2653–2653. 1 indexed citations
9.
Shu, Xing, Siyu Wang, Ximing Xu, et al.. (2024). The Effect of Nitrogen and Potassium Interaction on the Leaf Physiological Characteristics, Yield, and Quality of Sweet Potato. Agronomy. 14(10). 2319–2319. 5 indexed citations
10.
Zhao, Hongqian, Zheng Chen, Xing Shu, et al.. (2023). Online surface temperature prediction and abnormal diagnosis of lithium-ion batteries based on hybrid neural network and fault threshold optimization. Reliability Engineering & System Safety. 243. 109798–109798. 36 indexed citations
11.
Shen, Jiangwei, et al.. (2023). Accurate state of health estimation for lithium-ion batteries under random charging scenarios. Energy. 279. 128092–128092. 37 indexed citations
12.
Shu, Xing, Zheng Chen, Jiangwei Shen, et al.. (2023). Ensemble Learning and Voltage Reconstruction Based State of Health Estimation for Lithium-Ion Batteries With Twenty Random Samplings. IEEE Transactions on Power Electronics. 38(4). 5538–5548. 24 indexed citations
13.
Shu, Xing, Zheng Chen, Jiangwei Shen, et al.. (2022). State of Charge Estimation for Lithium-Ion Battery Based on Hybrid Compensation Modeling and Adaptive H-Infinity Filter. IEEE Transactions on Transportation Electrification. 9(1). 945–957. 28 indexed citations
14.
Shen, Jiangwei, et al.. (2022). Alternative combined co-estimation of state of charge and capacity for lithium-ion batteries in wide temperature scope. Energy. 244. 123236–123236. 40 indexed citations
15.
Shu, Xing, Shiquan Shen, Jiangwei Shen, et al.. (2022). Protocol for state-of-health prediction of lithium-ion batteries based on machine learning. STAR Protocols. 3(2). 101272–101272. 7 indexed citations
16.
Shu, Xing, Jiangwei Shen, Guang Li, et al.. (2021). A Flexible State-of-Health Prediction Scheme for Lithium-Ion Battery Packs With Long Short-Term Memory Network and Transfer Learning. IEEE Transactions on Transportation Electrification. 7(4). 2238–2248. 148 indexed citations
17.
Chen, Zheng, Hongqian Zhao, Xing Shu, et al.. (2021). Synthetic state of charge estimation for lithium-ion batteries based on long short-term memory network modeling and adaptive H-Infinity filter. Energy. 228. 120630–120630. 93 indexed citations
18.
Chen, Zheng, et al.. (2021). SOC estimation of aging lithium-ion battery based on a migration model. Energy Storage Science and Technology. 10(1). 326. 2 indexed citations
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20.
Shu, Xing, Guang Li, Yuanjian Zhang, et al.. (2020). Stage of Charge Estimation of Lithium-Ion Battery Packs Based on Improved Cubature Kalman Filter With Long Short-Term Memory Model. IEEE Transactions on Transportation Electrification. 7(3). 1271–1284. 93 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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