Modeling, Energy Optimization and Control of Vapor Compression Refrigeration Systems for Automotive Applications

In recent years, the increasing fuel consumption in the transportation sector has forced the automotive industry to improve their fleet-average fuel economy without sacrificing the vehicle performance. The primary path towards achieving fuel economy improvements consists of improving the energy conversion efficiency of powertrain components and mitigating various forms of losses. Ancillary loads, such as the Air Conditioning (A/C) system, fans and blowers or the alternator, are considered as a significant source of energy dissipation on the vehicle, but represent also an opportunity to improve vehicle fuel economy through the implementation of advanced design and control solutions. To this extent, this dissertation focuses on the fundamental and applied research that leads to the development of control algorithms for the energy optimization of the Air Conditioning system for a light-duty vehicle. Two types of mathematical models for characterizing the dynamics of vapor compression refrigeration systems were developed and validated. A high-fidelity, controloriented model was initially developed through an original formulation of the Moving Boundary Method using the Reynolds Transport Theorem with moving control surface, providing a generic template for characterizing mass and energy transfer in presence of a phase changing fluid. Then, an energy-based model was derived from first principles to capture the relevant refrigerant pressure dynamics in the heat exchangers and the compressor power consumption affecting the fuel economy with limited complexity.