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Pollutant emissions and the fuel/energy consumption of vehicles in real driving conditions are increasingly becoming the focus of public and legislative attention. According to the Euro 6d standard, vehicles must comply with emission limits on the test bed and on the road (Real Driving Emissions, RDE). This paper discusses a methodology that enables RDE compliance and robustness testing of engines and propulsion systems using a new phenomenological traffic simulation approach. The approach is based on virtual test driving and can be used in pure simulation as well as for testing at test beds based on the road-to-rig concept. A real route is digitized and a vehicle model (digital twin) of the target vehicle is built that models the driving resistances and vehicle dynamics properties of the real car. Finally, a virtual driver (driver model) drives the vehicle model on the digitized route considering also traffic objects, road signs and traffic lights.

Advanced thermal management systems in passenger cars present a possibility to increase efficiency of current and future vehicles. However, a vehicle integrated thermal management of the combustion engine is essential to optimize the overall thermal system. This paper shows results of an experimental heat flux analysis of a state-of-the-art automotive diesel engine with common rail injection, map-controlled thermostat and split cooling system. Measurements on a climatic chamber engine test bench were performed to investigate heat fluxes and energy balance in steady-state operation and during engine warm-up from different engine start temperatures. The analysis includes the influence of the operating point and operating parameters like EGR rate, injection strategy and coolant temperature on the engine energy balance.

Homogeneous Charge Compression Ignition (HCCI) offers a significant potential to reduce CO2 as well as NOx and particulate emissions. However ensuring stable and efficient HCCI combustion in practical use is a challenge and requires sophisticated control concepts. In the present paper a closed loop control concept is investigated for this purpose. In order to optimize the closed loop control, adaptations with neural networks are introduced. Different sensor concepts for HCCI combustion control are presented and the benefit of the analysis of crankshaft movements is analyzed.