Evaluation of explicit model predictive temperature control for on-off air conditioner

Abstract

The objective is to evaluate the performance of an explicit model predictive control for controlling the room temperature actuated by the on-off air conditioner to minimize the energy usage by reducing the working time of a compressor. There are a lot of on-off air conditioners already installed in the educational building in Thailand. To replace all of those by the inverter air conditioner or HVAC system, the high investment cost is required. Therefore, the on-off air conditioners continue to work in such building. The effective solution may be the low cost control unit which is simple like a remote control. The method is to design the remote control embedded by the temperature sensor and the explicit model predictive control that is based on the off-line optimization. The experiment is performed in the laboratory room with dimension 4×7×3.5 m (WxLxH) actuated by Saijo Denki 18,320 Btu on-off air conditioner. The experimental results reveal that the temperature reaches the desired value 25 degree Celsius within 10 minute and keeps fluctuating between 23 and 26 degree Celsius. The working time of compressor is reduced 33.33 %. The result shows that the explicit model predictive control is effective for the remote control application in terms of the implementation and energy saving.