The energy consumption by heating, ventilation, air conditioning, and refrigeration systems forms a large portion of the total energy usage in buildings. Vehicle fuel consumption and emissions are also significantly affected by air conditioning. Air conditioning is also a critical system for hybrid electric vehicles and electric vehicles as the second most energy consuming system after the electric motor. Proper design and efficient operation of air conditioning systems require accurate calculation of thermal loads as well as appropriate design and selection of the refrigeration cycle. The control logic applied to the system further defines the operational costs associated with the performance of the air conditioning or refrigeration system.The common practice in air conditioning engineering includes a primary calculation of thermal loads. Consecutively, the refrigeration system is selected to provide the required cooling or heating load. An alternate design approach in which the thermal loads are not only calculated as the initial design step but are also calculated in real-time is proposed in this thesis. Modern air conditioning systems are equipped with feedback controllers to allow the system to sustain thermal comfort. The real-time calculation and prediction of the room thermal loads improved by measurements is beneficial for energy-efficient control of air conditioning systems especially in vehicle applications that experience highly dynamic load variations. The calculation procedure can be implemented in a load-based controller to provide advanced intelligence for the system operation. This approach can optimize the system performance for the current as well as future conditions and can also be used as a tool for retrofitting existing systems.The objective of the present research is to establish intelligent real-time thermal load calculation methods that can be used to develop energy-efficient control systems in both stationary and mobile air conditioning and refrigeration applications. The proposed methodology consists of developing a variety of models for law-driven and data-driven calculation of thermal loads in mobile and stationary applications. The proposed models are applicable to heating, air conditioning, and refrigeration applications. The contributions of this study include design recommendations that can result in up to 50% increase in energy efficiency for mobile and stationary air conditioning systems.
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Thesis advisor: Bahrami, Majid
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