Yujun Shi | Magnet Motor Design | Best Researcher Award
Faculty Member, Xinjiang University, China
Dr. Yujun Shi, Associate Professor at Xinjiang University, is an accomplished researcher specializing in high-performance permanent magnet motor design, renewable energy integration, and optimized scheduling of integrated energy systems. He earned his Ph.D. in Engineering from the University of Macau and has established a strong academic record with 26 publications, including 20 SCI-indexed papers, alongside 11 authorized patents spanning U.S. and Chinese innovations. His significant contributions include enhancing torque density in permanent magnet motors through innovative use of magnetic barriers, which has advanced field-modulated motor technology. Dr. Shi has successfully led and participated in multiple provincial and national research projects, furthering technological applications in energy systems. With a citation index of 900 on Google Scholar, his work reflects global recognition and impact. Notably, he was honored with the Shenzhen Natural Science Award (2nd Class), underscoring his excellence in advancing engineering research. He now seeks recognition under the Best Researcher Award.
Profile: Scopus | Google Scholar
Featured Publications
Zhong, J., Li, Z., Takakuwa, M., Inoue, D., Hashizume, D., Jiang, Z., Shi, Y., Ou, L., … (2022). Smart face mask based on an ultrathin pressure sensor for wireless monitoring of breath conditions. Advanced Materials, 34(6), 2107758.
Shi, Y., Jian, L., Wei, J., Shao, Z., Li, W., & Chan, C. C. (2015). A new perspective on the operating principle of flux-switching permanent-magnet machines. IEEE Transactions on Industrial Electronics, 63(3), 1425–1437.
Jian, L., Shi, Y., Liu, C., Xu, G., Gong, Y., & Chan, C. C. (2013). A novel dual-permanent-magnet-excited machine for low-speed large-torque applications. IEEE Transactions on Magnetics, 49(5), 2381–2384.
Zheng, Y., Shao, Z., Lei, X., Shi, Y., & Jian, L. (2022). The economic analysis of electric vehicle aggregators participating in energy and regulation markets considering battery degradation. Journal of Energy Storage, 45, 103770.
Zhang, K., Li, Z., Zhang, J., Zhao, D., Pi, Y., Shi, Y., Wang, R., Chen, P., Li, C., … (2022). Biodegradable smart face masks for machine learning-assisted chronic respiratory disease diagnosis. ACS Sensors, 7(10), 3135–3143.