![]() Plus few extra things that I only needed for tuning.Ultimately this will depend on the physical heating arrangement. To power on / off AC manually you simply override schedule with a timer and you can easily adjust expected temperature.īut in need to have manual control I also have all those direct functions. User interface for managing AC unit via IRC is the same as for managing the heating. And we're talking about the real room temperature (the average of the four sensors), not temp provided by Daikin unit (integer only and inaccurate). ![]() Unfortunately the graph is quite approximate (hourly average graphed), but it gives a fairly good idea of how effective IRC is in sticking to the expected comfort temperature. ![]() It did not turn off all day, although it worked a few times in Auto mode (on overrun after being turned off by the Climate Controller)Īnd this was the actual temperatures that day. Since the living room was not really warm, Daikin was running full day in 3rd gear maximum, which is still ok. This would normally be 5th gear, which is a lot of noise.Īnd this is how fan rate control looks after passing through my tricks and logic. You can see how the IRC is struggling with the temperature around 17-18 hours. I have a living room with windows to the west, so it heats up during sunset. Then there would be a couple of AC unit turnoffs that I just wanted to avoid. You may see the IRC cooling the room down before 10:00, which is the start of the cooling period. This is raw control signal from the C2 output. You might need to zoom it in or download to see details in clear focus. A number of blocks in this diagram is not exactly required - they served me tuning and testing various solutions, but I hope the diagram is still readable. The other two tricks are mainly aimed at minimizing short-term turn-offs of AC unit, by slowing down the cooling (Trick #2) or doing an overrun (Trick #3). I've planed this logic in Excel first:Īnd here comes an implementation of that scaling - see Trick #1. However, I left it some minimal range (gears 1-3) because the controller that uses fuzzy logic would probably go crazy if suddenly the control became very ineffective. So the closer to Tc, the less noise can Daikin make. After a few trials and errors, I developed an algorithm for scaling C2 output by a factor depending on the difference between the actual and target temperature (Tc). only 0.4 degrees left to the comfort temperature. It seems completely unnecessary if there is i.e. Assigning these values in proportion to Daikin's fan rates 1-5 is not optimal as the IRC often outputs 10 and then the AC unit runs on 5th gear making a lot of noise. This integration is described in detailed here. These blocks have visualization enabled what provides manual override for automation. Blocks listed here in general are responsible for passing signals to the MQTT broker, which is used by ioBroker that directly communicates with the Daikin WiFi controller. However all those three controls are not sent directly to Daikn, but modified by my logic instead. CC controls power state of the unit, and the IRC controls fan rate and target temperature. Details of this diagram will be shown on image below, but in general IRC block is the central element here and it is linked to Climate Controler block. It includes the logic part (execution part is on the other page). My cooling automation consists of two diagrams - this is the first of them. If you have Daikin Air Condition Unit, please see my integration How-To here: Integration of Daikin Air Conditioning over WiFi Diagrams Integration of AC unit into Loxone is beyond scope of this document. This automation controls Daikin AC unit over WiFi, but most probably may be used with over AC units controlled in any way (WiFi, Modbus, KNX).
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |