Lowering the energy consumption has become a prime goal for most, if not all, system developers and engineers working nowadays in building smart environments, consorting that way with the today’s world’s climate and energy policy. A smart environment like a smart home should therefore be able to provide energy efficient solutions and services. This should however be accomplished without violating the user’s personal feel-good factor. Thus, the higher goal is to develop an intelligent system that achieves and keeps a balance between the resident’s personal comfort and the energy efficiency.

HVAC (Heating, Ventilating and Air Conditioning) systems perform heating and cooling, control the humidity level and are generally responsible for providing a good air quality and a high resident’s comfort level. These systems are being deployed in homes, offices and industrial buildings and combined with the current sensing possibilities undertake the above mentioned task.

This software campus project is primarily concerned with the heating component of a HVAC system deployed in an office environment and aims at answering following questions. To which extend could the resident’s comfort be modelled as a function of the temperature and the energy costs? Which is the most appropriate predictive control concept in order to achieve faster the comfort-efficiency-equilibrium? And finally, how far is it possible for the system to automatically recognize and adapt itself in new and different environments?

Start/End

03/2016 – 06/2017

Partners

Robert Bosch GmbH

Research topics

• Connected Home
• Optimization and User-Centered HVAC systems
• Comfort-Efficiency-Equilibrium
• Smart Heating
• Model Predictive Control

Contact

• Vethi Srikanthan (email: srikanthan@teco.edu)
• Antonios Karatzoglou (emai: antonios@teco.edu)