Peng Su | Machine Learning on Databases | Research Excellence Award

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Prof. Peng Su | Machine Learning on Databases | Research Excellence Award

Hebei University of Technology | China

Prof. Peng Su’s research centers on the advanced design, electromagnetic modeling, and performance optimization of permanent-magnet (PM) electrical machines, with a primary emphasis on flux-switching machine topologies for electric and hybrid-electric vehicle applications. With a citation record of 563 citations in total (431 since 2020), an h-index of 12 (11 since 2020), and an i10-index of 16 (12 since 2020), his contributions are well recognized within the electrical machine research community. His work significantly advances understanding of rotor-PM and stator-PM flux-switching architectures through rigorous analyses of operating principles, air-gap field modulation, hybrid-excitation mechanisms, and multi-phase configurations, enabling improved torque density, efficiency, and thermal robustness. Prof. Peng Su has delivered influential findings on PM eddy-current losses, stator-slot and rotor-pole selection, cogging-torque reduction strategies, and magnetization effects, offering practical design paths for minimizing parasitic losses and enhancing reliability under high-speed and vector-controlled drive conditions. His portfolio extends across diverse machine types—including axial-modular machines, multitooth structures, tubular PM generators, and toroidally wound direct-drive motors—demonstrating comprehensive expertise in advanced electromagnetic machine architectures. He also contributes to loss modeling in soft magnetic composites, fault behavior characterization, and performance evaluation methodologies tailored to transportation electrification requirements. Through systematic comparative studies, innovative structural proposals, and refined analytical models, Prof. Peng Su continues to shape the development of next-generation PM machines and high-efficiency energy-conversion technologies, reinforcing his position as a leading contributor to modern electrical machine engineering.

Profiles: Google Scholar | Orcid

Featured Publications

  • Hua, W., Su, P., Tong, M., & Meng, J. (2016). Investigation of a five-phase E-core hybrid-excitation flux-switching machine for EV and HEV applications. IEEE Transactions on Industry Applications, 53(1), 124–133.

  • Su, P., Hua, W., Wu, Z., Han, P., & Cheng, M. (2017). Analysis of the operation principle for rotor-permanent-magnet flux-switching machines. IEEE Transactions on Industrial Electronics, 65(2), 1062–1073.

  • Su, P., Hua, W., Wu, Z., Chen, Z., Zhang, G., & Cheng, M. (2018). Comprehensive comparison of rotor permanent magnet and stator permanent magnet flux-switching machines. IEEE Transactions on Industrial Electronics, 66(8), 5862–5871.

  • Su, P., Hua, W., Hu, M., Chen, Z., Cheng, M., & Wang, W. (2019). Analysis of PM eddy current loss in rotor-PM and stator-PM flux-switching machines by air-gap field modulation theory. IEEE Transactions on Industrial Electronics, 67(3), 1824–1835.

  • Su, P., Hua, W., Hu, M., Wu, Z., Si, J., Chen, Z., & Cheng, M. (2019). Analysis of stator slots and rotor pole pairs combinations of rotor-permanent magnet flux-switching machines. IEEE Transactions on Industrial Electronics, 67(2), 906–918.*