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Date of Award
Campus Access Master's Thesis
Master of Science in Mechanical Engineering (MS)
Administrative Home Department
Department of Mechanical Engineering-Engineering Mechanics
Committee Member 1
Committee Member 2
This thesis presents three optimization-based powertrain control methods for powertrain control of multi-mode hybrid electric vehicle, as part of the “Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR)” project.
The control methods are Instantaneous Optimization, Global Optimization and Receding Horizon Control/Model Predictive Control. The Instantaneous Optimization utilizes ECMS method to determine the best operating points and best mode for powertrain control. Dynamic Programming (DP) is used in the global optimization method for optimal control. The experimentally determined mode shift fuel and electricity costs are incorporated in the algorithm to optimize the mode selection and power-split. The Receding Horizon Control utilizes the Dynamic Programming algorithm to create optimal solution within a moving prediction horizon, which has the potential for real time control.
Wang, Huanqing, "DEVELOPMENT OF DYNAMIC PROGRAMMING AND RECEDING HORIZON CONTROL STRATEGIES FOR GM VOLT II MULTI-MODE HYBRID ELECTRIC VEHICLE", Campus Access Master's Thesis, Michigan Technological University, 2018.