Prof. Pengfei Sun, Southwest Jiaotong University, Best Researcher Award
Prof. Pengfei Sun is an accomplished Associate Professor at the School of Electrical Engineering, Southwest Jiaotong University, specializing in Intelligent Rail Transportation Systems. Born on March 25, 1987, he holds a Ph.D. in Automation from École Centrale de Lille, France, where he focused on system engineering for railway safety. With over a decade of experience since joining academia in 2016, his expertise spans train trajectory optimization, energy-efficient train control, and automatic train systems. Prof. Sun has made significant contributions to national and enterprise-level research projects, including national key R&D initiatives and the National Natural Science Foundation of China. His research leadership is underscored by numerous accolades, such as the First Prize from the China Railway Society and the National Railway Youth Science and Technology Innovation Award. He has published extensively as a first or corresponding author in leading journals such as IEEE Transactions on Intelligent Vehicles, Computers & Industrial Engineering, and Control Engineering Practice. His academic impact is further recognized through his active peer review roles for top-tier journals. He also received a national teaching achievement award in 2023 for his role in advancing engineering education. Prof. Sun is an emerging leader in smart rail systems, bridging theoretical innovation with real-world transportation needs.
Publication Profile
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Educational Background
Prof. Pengfei Sun possesses a robust academic foundation in electrical engineering and automation, reflecting a progressive journey through prestigious institutions. He earned his Ph.D. in Automation from École Centrale de Lille, France, between 2012 and 2015. His doctoral research focused on “Model based system engineering for safety of railway critical systems,” showcasing his early commitment to enhancing railway system safety through advanced engineering methodologies. Prior to his doctoral studies, he completed a Master’s degree in Power Electronics and Drives at Southwest Jiaotong University from 2009 to 2012. His master’s dissertation, titled “Study on the relationship between the optimization scheme of electrical phase separation layout and train operation time,” highlights his focus on improving operational efficiency in rail systems. This research laid the groundwork for his future innovations in intelligent rail transportation. Prof. Sun began his academic journey at the same university, earning a Bachelor’s degree in Electrical Engineering and Automation from 2005 to 2009. Throughout his education, he developed a strong interdisciplinary foundation combining automation, power electronics, and system optimization. These academic experiences not only equipped him with technical expertise but also shaped his innovative approach to intelligent railway systems, making him a prominent figure in the field of railway engineering.
Professional Experience
Prof. Pengfei Sun has built a commendable academic career at Southwest Jiaotong University, where he has been contributing to the advancement of electrical engineering and intelligent rail transportation systems. He began his professional journey as a Lecturer in the School of Electrical Engineering in 2016, shortly after completing his Ph.D. in Automation. During his tenure as a Lecturer from 2016 to 2020, he was actively involved in teaching, mentoring students, and conducting applied research on train control systems, energy-efficient operations, and transportation automation. His innovative approach and dedication to both academia and industry-driven research led to his promotion as an Associate Professor in 2021. Since then, he has continued to play a significant role in the university’s research ecosystem, leading multiple national and enterprise-funded projects focused on intelligent train operation, control theory, and system optimization. Prof. Sun’s expertise, particularly in intelligent rail transportation, has enabled him to contribute to high-impact initiatives aligned with China’s transportation modernization goals. His experience also includes curriculum development and guiding young researchers in cutting-edge areas such as predictive control, adaptive algorithms, and energy-efficient scheduling. His career progression reflects not only academic excellence but also a sustained commitment to innovation in the rail transport sector.
Research Interests
Prof. Pengfei Sun’s research interests lie at the intersection of intelligent systems and modern rail transportation, focusing on the development of advanced solutions for smart and sustainable mobility. Within the domain of Intelligent Rail Transportation Systems, his work emphasizes train trajectory optimization, energy-efficient train control, and energy-efficient timetabling. These research areas aim to enhance the performance, safety, and sustainability of rail networks by reducing energy consumption while maintaining operational efficiency. His innovative methods contribute to maximizing regenerative braking energy utilization and improving overall system resilience under complex operating conditions. Additionally, Prof. Sun is deeply engaged in Control Theory and Control Engineering, where he specializes in automatic train control and driver assistant systems. His research in this field addresses the challenges of autonomous operation, fault-tolerant control, and adaptive algorithms to handle uncertainties, input limitations, and real-time constraints. By integrating modern control strategies with rail operation requirements, he develops intelligent systems capable of supporting next-generation high-speed, heavy-haul, and urban trains. Prof. Sun’s research not only advances theoretical understanding but also offers practical implementations for energy optimization and automation in real-world railway environments. His multidisciplinary approach bridges electrical engineering, automation, and transportation planning, contributing significantly to the evolution of smart and eco-friendly railway infrastructures
Academic and Teaching Achievements
Prof. Pengfei Sun has been widely recognized for his outstanding contributions to the fields of railway engineering and higher education through several prestigious academic and teaching awards. In 2022, he received the First Prize of the Science and Technology Progress Award from the China Railway Society for his work on “Key Technologies and Equipment for Dynamic Simulation of High-Speed Train Operation,” where he ranked sixth among the contributors. The same year, he was honored with the National Railway Youth Science and Technology Innovation Award for his pivotal role—ranking second—in the development of “Key Technologies and Applications for Precise Control of 20,000-Ton Heavy Haul Trains,” reflecting the national impact of his innovations. Earlier, in 2019, Prof. Sun earned the First Prize of the Sichuan Provincial Science and Technology Progress Award for contributions to high-speed train electric traction systems, marking his significant influence on regional scientific advancements. Beyond research, Prof. Sun has also been acknowledged for his excellence in education. In 2023, he received the Second Prize of the National Teaching Achievement Award, recognizing his role in supporting China’s Belt and Road Initiative through the reform of engineering education and the cultivation of globally competitive railway engineering talent. These accolades collectively underscore his dual excellence in scientific innovation and academic mentorship.
Research Experience
Prof. Pengfei Sun has led and participated in a broad array of pioneering research projects focused on advancing intelligent rail transportation and control systems. As a project leader, he has steered numerous high-impact initiatives, including a key national R&D plan from 2024 to 2026 on safe, stable, and energy-saving speed trajectory planning for freight trains. He also led enterprise projects on energy-saving municipal vehicle control (2023–2025), autonomous parking algorithms (2023–2024), and intelligent assistant driving for EMUs (2022–2024). His earlier projects include intelligent train control under complex operations, heavy-haul train operation methods using iterative learning (NSFC Youth Project), and the development of traction simulation and emergency self-running technologies. From 2018 to 2020, he directed national-level R&D on high-frequency circuit topology using wide bandgap semiconductors. Additionally, Prof. Sun has played a pivotal role in multiple major research collaborations, including NSFC key projects like intelligent control theory for high-speed EMUs (2024–2027), intelligent train technologies for the Sichuan-Tibet Railway (2021–2025), and high-speed train autonomous cooperative control (2020–2023). His work also covers energy storage estimation, efficient train operations, and 400 km/h intelligent control systems. These projects demonstrate his leadership in integrating control engineering, data-driven models, and energy-efficient strategies into railway innovation.
🔬 Research Focus
Prof. Pengfei Sun’s research primarily focuses on intelligent rail transportation systems, integrating control engineering, automation, and energy optimization. His work emphasizes energy-efficient train control, driver advisory systems, multi-train cooperative driving, and train trajectory optimization using data-driven and model-based approaches. He also contributes to hybrid energy systems, high-speed train safety, and real-time control algorithms. His studies span across metro, freight, and tram operations, with high-impact publications in IEEE Transactions and Energies. Notably, his research addresses complex challenges like eco-driving, regenerative braking, and Petri net modeling for railway safety-critical systems.
Publication Top Notes
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📘 Adaptive iterative learning control for high-speed train: A multi-agent approach – 105 citations 📊 – 2019 📅
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📘 Modeling and energy-optimal control for high-speed trains – 65 citations 📊 – 2020 📅
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📘 Real-time energy-efficient driver advisory system for high-speed trains – 36 citations 📊 – 2021 📅
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📘 Integrated optimization of speed profiles and power split for a tram with hybrid energy storage systems – 34 citations 📊 – 2018 📅
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📘 Cooperative eco-driving of multi-train under DC traction network – 31 citations 📊 – 2021 📅
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📘 Eco-driving control for hybrid electric trams on a signalised route – 31 citations 📊 – 2020 📅
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📘 Multi-objective trajectory optimization for freight trains based on quadratic programming – 27 citations 📊 – 2020 📅
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📘 The energy-efficient operation problem of a freight train with steep downhill sections – 27 citations 📊 – 2017 📅
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📘 Mini-me, you complete me! Data-driven drone security via DNN – 24 citations 📊 – 2021 📅
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📘 Formal modeling of French railway interlocking via HCPN – 23 citations 📊 – 2014 📅
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📘 Model-based system engineering for safety of railway critical systems – 22 citations 📊 – 2015 📅
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📘 Petri net model pattern of railway interlocking system – 22 citations 📊 – 2015 📅
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📘 Eco-driving for metro trains via convex programming – 21 citations 📊 – 2023 📅
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📘 Reinforcement learning for freight train trajectory optimization – 18 citations 📊 – 2023 📅
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📘 Train control and schedule optimization with reversible substations – 16 citations 📊 – 2022 📅