Indoor air pollution is complex and serious. In fact, an on-site investigation of an office building revealed that the concentration of three typical pollutants (CO2, VOCs, PM2.5) exceeded the Chinese standard. To identify a better control method to achieve good indoor air quality, an orthogonal experiment was carried out in an environmental chamber to compare the control time and energy consumption of four control methods (purifier+ and window+, purifier+ and window-, purified fresh air 240 m3/h and purified fresh air 400 m3/h) to meet the standard established for pollutants. The purifier+ and window+ method was found to be more effective in most conditions, with a control time reduced by 8.06% and energy consumption reduced by 11.91% compared with the traditional control method of purified fresh air 240 m3/h. This research highlights the optimal control strategy for the air quality in office buildings under different pollution conditions.

In the practical application of indoor air quality assurance system, it is difficult to detect the fault of air valves, CO2 sensors and other components, resulting in substandard air quality and increased energy consumption. In this paper, 16 fault conditions and 1 no fault condition were simulated by Simulink simulation software for primary return air conditioning system in summer, and a typical indoor air quality assurance system simulation fault characteristic table was obtained. It is found that PM2.5 sensor fault mainly affects indoor PM2.5 purification speed. The fault of a CO2 sensor affects indoor CO2 dilution and system energy consumption. Small resistance of return air valve increases system energy consumption. Small resistance of supply air valve, exhaust air valve and return air valve decreases the system's ability to control indoor pollutants.