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The CO2 emission regulations ask a dramatic fuel consumption reduction worldwide. In this scenario, the market penetration of BEVs and PHEVs is strictly related to their electrical driving range, which is strongly affected by the ambient conditions and the passenger comfort asking for an effective thermal management that becomes an opportunity for overcoming these barriers. In this context, a virtual analysis comparing different cooling and heating architectures has been conducted; efficiency and costs aspects have been considered as driving factors as well as the lay-out aspects and vehicle integration constrains which drive component selection and influence the performance. In order to perform a robust architecture comparison and obtain more reliable results, a vehicle thermal model has been developed. The model takes into account the main thermal load contributes and the simulations which have been performed considering different selected cases.

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.