Advanced Dynamic Control of Air Conditioners to Reduce Energy Consumption and GHG Emissions

Summary

This research aims to implement and perform experimental tests on improved control algorithms for AC
systems based on continuous changes in the cooling load and ambient conditions. The research aims to 
design cost-effective AC hardware modifications like improved heat exchangers and electronic expansion 
devices, and consideration of transient conditions within the vapor-compression cycle. This control 
algorithm works on matching the changes in the cooling load and outside air conditions to operate the AC
with minimum energy consumption.
The research is divided into two complementary parallel paths: modeling and experiments. A dynamic AC 
model will be developed at Arizona State University in the United States (ASU-US) and the experimental 
evaluation at Ain Shams University in Egypt (ASU-EG). This dynamic model takes into account external
changes in the building geographic location, orientation, seasons and days of the year, the corresponding 
incident solar radiation, building occupancy and other loads, the outside air temperature and humidity, etc. 
In addition, instead of relying on the conventional steady-state model of the vapor-compression system it 
will include transient features such as local refrigerant temperature/pressure and flow rates that differ 
significantly between start-up and steady-state operation. The experimental component consists of a 
testbed constructed at ASU-EG to enable the evaluation and control of the system performance parameters
such as the evaporator and condenser operating temperature, pressure and humidity, the sensible and 
latent components of the cooling load, the flowrate of air passing through the evaporator and condenser 
fans, the flowrate of the refrigerant through the cycle, and the compressor speed and energy consumption.
All tests will be performed according to the ANSI/ASHRAE Standards for equipment testing and 
measurements, and the results will be used to validate the model developed at ASU-US. The validated 
dynamic model will in turn be integrated into a control algorithm, i.e., model-based predictive control, to 
achieve energy efficiency improvements without requiring costly AC hardware improvements

Goals of the Project
• Develop improved AC control algorithm to reduce AC energy consumption and greenhouse gas 
(GHG) emissions.
• Improve the reliability and reduce the energy consumption of AC systems in domestic, industrial and 
commercial applications.
• Develop AC research capacity at ASU-EG as the proposed testbed will be the first of its kind at a 
National Egyptian University. This testbed can be used to perform a variety of additional experiments 
for undergraduate and postgraduate students, and in collaboration with industry.
• When integrated with the control algorithm based in part on the dynamic model developed at ASU￾US, the capabilities of the testbed are improved and more studies concerning Artificial Intelligence 
(AI) and Internet of Things (IoT) are performed. 

Achievements

List of Publications from the Project

Partners

• Prof. Patrick Phelan

Project Members

Project Leaders