The proposed FLC could be applied to a large variety of HVAC systems by utilizing low-cost sensors, without the need to significantly modify the internal design of the HVAC system. Results demonstrated that the new FLC was effective in regulating the in-cabin PMV level and CO 2 concentration, at desirable levels, by adaptively controlling the opening and closing of the recirculation flap based on in-cabin temperature and CO 2 readings, while maintaining an average-to-good energy consumption level. To evaluate the effectiveness of the proposed FLC, a cabin simulator was used to mimic the effects of different HVAC variables and indoor/outdoor environmental settings, which represented the in-cabin PMV and IAQ readings. The new FLC aimed to regulate both in-cabin PMV and CO 2 values without significantly increasing overall energy consumption. A new fuzzy logic controller (FLC) was designed and developed using the MATLAB fuzzy logic toolbox and Simulink to provide a nonlinear mapping between the measured values, i.e., PMV, temperature, CO 2, and control parameters (recirculation flaps, blower’s speed, and refrigerant mass flow rate) of a vehicle HVAC system. In this project, IAQ in the vehicle cabin was represented by its carbon dioxide (CO 2) concentration, and the occupants’ thermal comfort levels were estimated with the predicted mean vote (PMV) index. Other important parameters related to the thermal comfort and indoor air quality (IAQ) of the confined compartment have often been ignored. Conventional heating ventilation and air-conditioning (HVAC) controllers have been designed to mainly control the temperature of a confined compartment, such as a room or a cabin of a vehicle.

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