Bouilly, J., Lafossas, F., Mohammadi, A., and Van Wissen, R., "Evaluation of Fuel Economy Potential of an Active Grille Shutter by the Means of Model Based Development Including Vehicle Heat Management," SAE Int. J. Engines 8(5):2394-2401, 2015, doi:10.4271/2015-24-2536.
In the automotive field, reducing harmful pollutant, CO2 emissions and fuel consumption of vehicles while increasing customer comfort is a continuous challenge that requires more and more sophisticated technology implementations. However, it is often difficult to anticipate the advantages and drawbacks of a technology without having its prototype parts and/or knowing the optimal control strategy. In order to meet these challenges, the authors have developed a vehicle thermal model in AMESim platform to evaluate the benefits of an Active Grille Shutter (AGS) on fuel economy when applied. The vehicle model was based on a C-Segment vehicle powered by a 1.4L Diesel engine. The complete oil and coolant circuits were modeled as well as a friction model based on engine coolant and oil temperature. The entire model was validated on the European homologation cycle (NEDC) at −7°C and +25°C ambient temperature and achieved an accurate estimation of the fuel consumption, coolant and oil temperatures. Then, an AGS model was developed and integrated into the vehicle thermal model in order to assess the control of the coolant temperature (radiator cooling efficiency) and the vehicle road load (drag coefficient). Several control strategies were investigated on an in-house country-highway driving cycle to clarify the best compromise among fuel consumption reduction, engine coolant temperature control stability and AGS durability. The model demonstrated a potential fuel economy of 1.7% and 2.0% at +25°C ambient temperature on NEDC and in-house country-highway driving cycles respectively. In addition, the model showed further fuel economy up to 2.4% on NEDC at −7°C ambient temperature thanks to the combined effects of reduced frictions and road load. Finally, simulation and experimental results were compared and the fuel economy predicted by the model achieved a deviation lower than 0.3%.