Room temperature data measured by sensors is a crucial parameter for the operational control of room air conditioners.Asymmetric and stratified temperature distribution of the indoor space can lead to different data feedback from sensors at different locations at the same point in time,which ultimately affects the stability of room temperature control and the level of air conditioning energy consumption.The influence of sensors at different locations in the building are expounded on the stability of room temperature control and the energy consumption level of air conditioning.Twenty measurement points in the residential space are selected for the experiments,and cluster analysis is used to classify the measurement point categories based on the measured temperature data.Simulations are carried out for rooms of different sizes using FEA software,and a search model for the optimal sensor position is established,while a method of correcting parameters to adjust the initial sensor position is proposed.Therefore,it provides theoretical and practical support to improve the operation of room air conditioners.
air conditionerposition optimizationtemperature sensorthermal comfortroom temperature
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