Zonggen Yi, Ph.D.
Advanced Vehicle Research Engineer
Research Areas: High Temperature Test Laboratory
Biography: Dr. Zonggen Yi is a researcher in Idaho National Laboratory’s Energy Storage and Advanced Vehicles department. He received his doctorate in electrical engineering from University of Notre Dame. He earned his bachelor’s, in automation, and master’s, in control engineering, from Tongji University, Shanghai, China, where he has worked on physical system state estimation and control algorithm design in networked and distributed intelligent systems. His research focus on high-efficient intelligent decision-making methodologies using advanced control, optimization, and machine learning/AI technologies. Specific research areas mainly include the autonomous driving technologies, energy management for connected and automated electric vehicles, shared autonomous electric vehicle fleet operation management, control and optimization of smart charging for electric vehicle fleet integrated to power grid, etc.
Ph.D., Electrical Engineering - University of Notre Dame
M.S., Control Theory and Control Engineering - Tongji University, Shanghai China
B.S., Automation - Tongji University, Shanghai China
Institute of Electrical and Electronics Engineers (IEEE)
Zonggen Yi, Peter H. Bauer. "Energy Aware Driving: Optimal Electric Vehicle Speed Profiles for Sustainability in Transportation." IEEE Transactions on Intelligent Transportation Systems 20.3 (2019): 1137-1148.
Zonggen Yi, and Don Scoffield. "A Data-Driven Framework for Residential Electric Vehicle Charging Load Profile Generation." 2018 IEEE Transportation Electrification Conference and Expo (ITEC). IEEE, 2018.
Zonggen Yi, John Smart, and Matthew Shirk. "Energy impact evaluation for eco-routing and charging of autonomous electric vehicle fleet: Ambient temperature consideration." Transportation Research Part C: Emerging Technologies 89 (2018): 344-363.
Zonggen Yi, Peter H. Bauer. "Optimal stochastic eco-routing solutions for electric vehicles." IEEE Transactions on Intelligent Transportation Systems 19.12 (2018): 3807-3817.
Zonggen Yi, Matthew Shirk. "Data-driven optimal charging decision making for connected and automated electric vehicles: A personal usage scenario." Transportation Research Part C: Emerging Technologies 86 (2018): 37-58.
Zonggen Yi, Peter H. Bauer. "Adaptive multiresolution energy consumption prediction for electric vehicles." IEEE Transactions on Vehicular Technology 66.11 (2017): 10515-10525.
Zonggen Yi, Peter H. Bauer. "Effects of Environmental Factors on Electric Vehicle Energy Consumption: A Sensitivity Analysis." IET Electrical Systems in Transportation (2017).
Zonggen Yi, and Peter H. Bauer. "Optimization Models for Placement of an Energy-Aware EV Charging Infrastructure". Transportation Research Part E: Logistics and Transportation Review, 91(2016):227-244.
Zonggen Yi, Peter H. Bauer. "Spatio-Temporal Energy Demand Models for Electric Vehicles." IEEE Transactions on Vehicular Technology, 65.3(2016):1030-1042.
Zonggen Yi, Peter H. Bauer. "Optimal Speed Pro les for Sustainable Driving of Electric Vehicles." Vehicle Power and Propulsion Conference (VPPC). IEEE, 2015.
Zonggen Yi, Peter H. Bauer. "Sensitivity Analysis of Environmental Factors for Electric Vehicles Energy Consumption." Vehicle Power and Propulsion Conference (VPPC). IEEE, 2015.
Zonggen Yi, Peter H. Bauer. "Spatio-Temporal Energy Demand Models for Electric Vehicles." Vehicle Power and Propulsion Conference (VPPC). IEEE, 2014.
Zonggen Yi, Peter H. Bauer. "Energy Consumption Model and Charging Station Placement for Electric Vehicles." 3rd International Conference on Smart Grids and Green IT Systems. 2014.
ZhongjieWang, Zonggen Yi. "Robust State Estimation for Network Packet Dropout with Quadratic Programming." Journal of Tongji University. Natural Science 40.6 (2012): 942-948.
Zonggen Yi, Zhongjie Wang. "Robust State Estimation Based on Quadratic Programming for Network Packet Dropout." International Conference on Electronics, Communications and Control (ICECC). IEEE, 2011. (Distinguished Paper Award)