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Papers in the session cover zero-dimensional, one-dimensional, and quasi-dimensional models for simulation of SI and CI engines with respect to: engine breathing, boosting, and acoustics; SI combustion and emissions; CI combustion and emissions; fundamentals of engine thermodynamics; numerical modeling of gas dynamics; thermal management; mechanical and lubrication systems; system level models for controls; and system level models for vehicle fuel economy and emissions predictions.

Papers in the session cover zero-dimensional, one-dimensional, and quasi-dimensional models for simulation of SI and CI engines with respect to: engine breathing, boosting, and acoustics; SI combustion and emissions; CI combustion and emissions; fundamentals of engine thermodynamics; numerical modeling of gas dynamics; thermal management; mechanical and lubrication systems; system level models for controls; and system level models for vehicle fuel economy and emissions predictions.

NOx emissions from diesel passenger vehicles affect the atmospheric environment. It is difficult to evaluate the NOx emissions influenced by environmental conditions such as humidity and temperature, traffic conditions, driving patterns, etc. In the authors’ previous study, real-driving experiments were performed on city and highway routes using a diesel passenger car with only an exhaust gas recirculation system. A statistical prediction model of NOx emissions was considered for simple estimations in the real world using instantaneous vehicle data measured by the portable emissions measurement system and global positioning system. The prediction model consisted of explanatory variables, such as velocity, acceleration, road gradient, and position of transmission gear. Using the explanatory variables, NOx emissions on the city and highway routes was well predicted using a diesel vehicle without NOx reduction devices.

Hybrid electric vehicles (HEVs) are worldwide recognized as one of the best and most immediate opportunities to solve the problems of fuel consumption, pollutant emissions and fossil fuels depletion, thanks to the high reliability of engines and the high efficiencies of motors. Moreover, as transport policy is becoming day by day stricter all over the world, moving people or goods efficiently and cheaply is the goal that all the main automobile manufacturers are trying to reach. In this context, the municipalities are performing their own action plans for public transport and the efforts in realizing high efficiency hybrid electric buses, could be supported by the local policies. For these reasons, the authors intend to propose an efficient control strategy for a hybrid electric bus, with a series architecture for the power-train.

This paper focuses on an assessment of predictive combustion model using a 0D/1D simulation tool under high load, different excess air ratio λ , and different combustion stabilities (based on coefficient of variation of indicated mean effective pressure COVimep). To consider that, crank angle resolved data of experimental pressure of 500 cycles are recorded under engine speed 1000 RPM and 2000 RPM, wide-open throttle, and λ=1.0, 1.42, 1.7, and 2.0. Firstly, model calibration is conducted using 18 cases at 2000 RPM using 500 cycle-averaged in-cylinder pressure to find optimized model constants. Then, the model constants are unchanged for other cases. Next, different cycle-averaged pressure data are used as inputs in the simulation based on the COVimep for studying sensitivity of the turbulent model constants. The simulation is conducted using 1D simulation software GT-Power.