Among the many things consuming our home electricity are the airconditioning units, taking up around 20-30% of our electricity.
refrigeration and air conditioning units can be quite staggering.
Some factors of high power consumption are:
- Difference of temperature between the cooled area and the ambient environment.
- The overall health of the AC unit.
- If the door is closed/opened.
- Visualization of data and access to it.
So in order to alleviate such, I designed a simple dual-layer brain in order to integrate the sensor inputs as well as a capacitive engine that is able to generate OLED displays capable of interaction. Communication is dealt through a Raspberry Pi 2 running on the Raspbian OS, simply because it is the best option for project-type multi-controlling. The components are programmed with the use of Zymbit python libraries, and in order to retrieve temperature data, I used DS18B probes that were bus routed to the screw terminal of the PCB. A couple of them should do. I2C and SPi Bus units have readily available pinouts which I also utilized.
The diagram below illustrates the pinouts for the RPi's GPIO:
The process of cooling is quite simple. The compressor, condenser and evaporator are all there is to it. For it to work efficiently, proper airflow must be present for energy to be able to escape the system using the condenser. So this is the part where analytics comes in. I placed a few probs before and after at the valve in and the expansion portion. They can also run parallel to the evaporator depending on your unit.
Temperature data is collected from the following locations:
- Temperature Cooling Space
- Raw temperature of ambient air
- Raw temperature of the condenser input and output
Below is a diagram of how it all fits together: