A Switching Event-Triggered Model Predictive Control for HVAC Systems

Heating, ventilation, and air conditioning (HVAC) systems have great potential for energy savings and integration with green energy sources. Advanced control of these systems could play a key role in optimizing consumption while enhancing efficiency and performance. In this paper, a new model-based methodology is proposed for real-time control of the compressor in HVAC systems, based on switching event-triggered model predictive control. The approach manages the switch among different operational modes and provides the possibility to set different constraints to be optimized, enabling a multivariable scheme. It also applies the latest model-based design standards derived from the AUTOSAR framework to adapt them for an HVAC platform that offers substantial technical value, while also preserving the model-based design structure for improved lifecycle management. The models used for the controller in each modality are developed through the system identification standards and validated u sing data acquired from the air-water heat pumps in the test field. The effectiveness and performance of the control approach are also demonstrated through Model-in-the-Loop (MIL) testing.