5.2 Hysteresis algorithm
During the rst weeks of your Thermostat's life, only this algorithm is available. With
this algorithm, when the dierence between the room and the setpoint temperatures is
less than the sensitivity threshold, the Thermostat considers it has reached the setpoint
temperature. You can change this threshold in the advanced settings (see below).
This algorithm is recommended if you have a wood stove as it turns the boiler on and
o less frequently.
5.3 Hysteresis settings
In the advanced parameter menu, you can change the sensitivity threshold of your hysteresis
algorithm. For a small threshold (0,1 degree), the thermostat will be more reactive to
temperature and setpoint changes. For a bigger threshold, the Thermostat will be more
tolerant to temperature and setpoint changes, and will switch less often the boiler.
5.4 PID algorithm
After two weeks of Thermostat use, this algorithm activate. You can deactivate it and
come back to hysteresis algorithm if wanted. During these two rst weeks, the Thermostat
learns your home characteristics, such as your thermal inertia or your heating isolation.
These characteristics are then updated regularly.
Once those characteristics set, the Thermostat uses an advanced PID (Proportional-
Integral-Derivative) algorithm for a better temperature regulation, allowing for less oscil-
lation around the setpoint temperature.
6 Heating prediction
6.1 Heating prediction
The heating prediction is an intelligent feature of the Thermostat which continuously de-
termines the time required for your heating to reach your scheduled comfort temperatures.
During the learning period of two weeks, the Thermostat will analyse the specic char-
acteristics of your house. Then it will be able to turn your heating on when needed so you
have the comfort temperature reached when you need it.
To work correctly, the Thermostat needs to use the outdoor temperature.
Indeed, the colder it is outside, the more time your heating will need to heat your house.
And vice versa.
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