Developing Intelligent Windshield Fogging Prediction and HVAC Control Model

The Indian continental region encompasses various geographical terrains and climatic conditions, which summons the automotive OEMs to build a robust Heating Ventilation Air Conditioning (HVAC) system. For a typical passenger cars and utility vehicle segments, on board HVAC primarily serves two major purpose a) providing year round thermal comfort to the passengers and b) enact defogging and defrosting action of front windshield as per regulatory requirement and customer need. Nowadays, Full Automatic Temperature Control (FATC) is introduce in nearly all segments of passenger cars. It intelligently manages HVAC system as per customer comfort. Although case of windshield fogging which deteriorates front vision through windshield is not fully automatize and actively manage. The case of repetitive unclear front vision severely affects driving safety for the occupants. Thus, customer as per their observation of fogging over windshield will manually activate/deactivate defog mode. The present work looks into upgrading the FATC system in a manner by which the chances of fogging over the windshield is judged and necessary defogging actions through an automatic control model. The predictive algorithm is based on input signals of humidity level and glass temperature at definite location over the windshield. Further, the various dominant factors affecting chances of windshield fogging is weighted into the prediction model to evaluate chances of fogging. The control model would adjust various HVAC operating state such as blower speed, air recirculation, air distributions and cooling/heating effect basis as and when the chances of fogging is predicted. This control HVAC operation would also have benefiting impact on driving range of vehicle. The integrated HVAC system and control model is tested under different ambient conditions and occupant load using climate wind tunnel and on-road drive scenario. The evaluated HVAC performance shows that control model worked well to ensure optimum human comfort and driving safety