This thesis focuses on the architecture design, dynamic modeling and system control of a rapid-prototyping hybrid automotive powertrain research platform and on this basis, conducts a series of research work on the powertrain control and energy/emissions optimization of the hybrid vehicle system. This hybrid powertrain research platform leverages the fast dynamic response of a transient hydrostatic dynamometer to mimic the dynamics of various hybrid power sources and hybrid architectures and therefore, creates an accurate and highly flexible emulation tool for hybrid powertrain operations. This design will greatly speed up the research progress and reduce the economic cost of the study on various hybrid architectures and control methodologies. The design, control and optimization of this research platform include the detailed research achievements in three levels of the proposed system:1) Low-level system (hydrostatic dynamometer) design and control:with regards to the low-level system, the design, modeling, nonlinear control and experimental validation of a transient hydrostatic dynamometer are accomplished, which provides the hardware ingredient for the research platform and ensures the dynamics emulation capability of the system.2) Mid-level system (hybrid powertrain system) design and control:with regards to the mid-level system, the design and experimental investigation of the multivariable hybrid powertrain control within the hybrid powertrain research platform are achieved; on this basis, the systematic integration and coordination of the energy optimization, hybrid powertrain control, hardware-in-the-loop vehicle simulation and hybrid torque emulation are conducted within a closed-loop architecture.3) High-level system (hybrid energy and emission management) control and optimization:the high-level system design consists of the fuel efficiency optimization ("Stochastic Dynamic Programming - Extremum Seeking" hybrid energy management strategy) and transient emission optimization (Two-Mode hybrid energy management strategy), which are not only the advanced studies in the core area of the hybrid powertrain technology development, but also can be considered as the functionality demonstrations of the designed hybrid powertrain research platform.
University of Minnesota Ph.D. dissertation. January 2014. Major: Mechanical Engineering. Advisor: Zongxuan Sun. 1 compute file (PDF); xii, 184 pages.
Design, control and energy optimization of a rapid-prototyping hybrid powertrain research platform.
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