Following the development of new technologies in Vehicle Thermal Management aiming to both enhancing the MAC System efficiency and reducing the thermal load to be managed, a prediction tool based on the AMEsim platform was developed at Advanced PD EMEA.
This tool is dedicated to predict the effect of the implementation of sensors monitoring both the relative humidity and the carbon dioxide (CO2) concentration (taking into account passengers' generated moisture and CO2). This model implemented with the usual comfort inputs (CO2 and RH acceptable ranges) considers the system variables influencing the comfort and predicts the increase of both RH and CO2 concentration in the cabin compartment in any driving cycle depending on the number of occupants.
The effect of different flap control strategies based on the relative humidity and carbon dioxide sensors' inputs is compared with the extreme conditions (full Fresh Air, full Recirculation) in terms of their effect on the vehicle fuel consumption, according to various driving cycles. This tool has been developed to help evaluate the real driving benefit of these sensors' implementation.