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Thermal cabin comfort is the largest consumer of battery energy second only to propulsion in Battery Electric Vehicles (BEV’s). Accurate prediction of thermal comfort in the vehicle cabin with fast turnaround times will allow engineers to study the impact of various thermal comfort technologies and develop energy efficient Heating, Ventilation and Air Conditioning (HVAC) systems. In this study a novel data-driven model based on physics-guided Sparse Identification of Nonlinear Dynamics (SINDy) method was developed to predict Equivalent Homogeneous Temperature (EHT), Mean Radiant Temperature (MRT) and cabin air temperature under transient conditions and drive cycles. EHT is a recognized measure of the total heat loss from the human body that can be used to characterize highly non-uniform thermal environments such as a vehicle cabin. The SINDy model was trained on drive cycle data from Climatic Wind Tunnel (CWT) for a representative Battery Electric Vehicle.

Two-stroke diesel engines could be a promising solution for reducing carbon dioxide (CO2) emissions from light-duty vehicles. The main objective of this study was to assess the potential of two-stroke engines in achieving a substantial reduction in CO2 emissions compared to four-stroke diesel baselines. As part of this study 1-D models were developed for loop scavenged two-stroke and opposed piston two-stroke diesel engine concepts. Based on the engine models and an in-house vehicle model, projections were made for the CO2 emissions for a representative light-duty vehicle over the New European Driving Cycle and the Worldwide Harmonized Light Vehicles Test Procedure. The loop scavenged two-stroke engine had about 5-6% lower CO2 emissions over the two driving cycles compared to a state of the art four-stroke diesel engine, while the opposed piston diesel engine had about 13-15% potential benefit.