Low-cost self-study temperature controller and its methods
A self-learning method and self-learning technology, applied in the field of low-cost self-learning thermostats, can solve problems such as increasing the cost of thermostats, complicating thermostats, and wasting energy, so as to reduce production and use costs, and achieve low-cost self-learning thermostats. Learn the thermostat and improve the effect of humanized operation
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Embodiment 1
[0055] Such as figure 1 As shown, this example provides a low-cost self-learning thermostat, including a power switch and an adjustment module, the adjustment module includes a temperature adjustment unit and an air volume adjustment unit, and also includes a processing module and a self-learning control module, the processing module Using a microprocessor unit, the microprocessor unit receives and recognizes the status information of the adjustment module or the self-learning control module, adjusts the temperature and air volume, and controls the self-learning process; the self-learning control module in this example includes a self-learning button unit. The self-learning key unit is used to select a self-learning control mode; the self-learning control module is connected to the processing module and is used to set the self-learning state.
[0056] Among them, the microprocessor unit is a central processing unit composed of integrated circuits, which is used to receive and iden...
Embodiment 2
[0060] Such as figure 2 As shown, the difference from Embodiment 1 is that the self-learning control module uses a memory key unit and a memory unit. The memory key unit is used to control the start of the self-learning process, and the memory unit is used to store self-learning data.
[0061] Among them, the memory key unit and the memory unit are respectively connected to the microprocessor unit to complete the self-learning process. After pressing the memory button of the memory key unit, the microprocessor unit receives a self-learning memory signal and responds to the air conditioner. The air volume and temperature of the room are controlled, and the microprocessor unit will use the memory unit to record the currently set self-learning data. The self-learning data includes number, switch status, FAN status, self-learning status, temperature setting and Time self-learning data, a total of 32 bits.
[0062] In this example, each piece of data is 4 bits, and the memory button is...
Embodiment 3
[0065] Such as image 3 As shown, the difference from Embodiment 2 is that the processing module in this example further includes a fuzzy estimation unit and a relay unit. The fuzzy estimation unit calculates the advance based on the self-learning data, and the advance is used to control the relay unit in advance.
[0066] The fuzzy estimation unit in this example calculates the advance amount based on the self-learning data. The user sets the temperature and air volume for the first time, or after the self-learning state is selected through the self-learning control module, the present invention records the set temperature, air volume, and achieved Over time, a total of 4 sets of self-learning data were recorded, and 4 analyses were done accordingly. Through these 4 times of analysis, the temperature, air volume and their rate of change are obtained, and the heat capacity of the corresponding air-conditioned room is calculated according to the rate of change, and finally an advan...
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