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A two zones combustion model suitable for the engine control design of common rail multi-jet Diesel engines is presented. The modeling approach is based on a semi-empirical two-zone combustion model coupled with identification analysis in order to implement a predictive tool for simulating the effects of control injection strategies on combustion and exhaust emissions. Fuel jet formation and combustion for both premixed and diffusive regimes are predicted, by dividing the combustion chamber into two control volumes; these account for the fuel jet and the surrounding air, composed by fresh air and residual gases; the fuel jet is divided into two zones to separate liquid and vapor phases. The simulation results have shown that the model predicts the effects of different injection parameters in case of single and multiple injection in a short computational time, suitable for the accomplishment of intensive simulations or optimization analyses over generic engine driving cycles.

The paper deals with the development of a system of phenomenological models for the simulation of combustion and NOx-Soot emissions in Common-Rail Multi-Jet Diesel engines. The system has been built by following a modular modeling approach and is suitable for the implementation in the framework of Hardware In the Loop (HIL) ECU rapid prototyping. A single-zone model simulates the ignition delay and the combustion during a sequence of pilot, pre and main fuel injections for a production 1,9 liters Diesel engine equipped with High Pressure Injection system, electronically controlled. The heat release model is based on the synthetic description of both premixed and diffusive combustion. The Zeldovich mechanism has been used to simulate the formation of NO emissions while the Soot model is based on the approach proposed by Hiroyasu. The models have been tested vs. a wide set of experimental data with a good accuracy in predicting pressure cycle and heat release.

The paper describes the research work carried out on the thermo-fluid dynamic modeling of an S.I. engine coupled to the vehicle in order to predict the engine and tailpipe emissions during the ECE European driving cycle. The numerical code GASDYN has been extended to simulate the engine + vehicle operation during the first 90 seconds of the NEDC driving cycle, taking account of the engine and exhaust system warm-up after the cold start. The chemical composition of the engine exhaust gas is calculated by means of a thermodynamic multi-zone combustion model, augmented by kinetic emission sub-models for the prediction of pollutant emissions. A simple procedure has been implemented to model the vehicle dynamic behavior (one degree of freedom model). A closed-loop control strategy (proportional-derivative) has been introduced to determine the throttle opening angle, corresponding to the engine operating point when the vehicle is following the ECE cycle.

As U.S. and European regulation of automotive emissions is getting more stringent, great interest is growing around new solutions for future emission standards. Pollutant reduction can be achieved improving both engine out emission and aftertreatment system efficiency. Engine out emission can be reduced improving combustion process especially during warm-up, friction and the engine management system. In any case engine out emission reduction involves engine sophistication increasing costs, which must be accurately evaluated, especially for small displacement large mass production engine. Since, as it is well known, 80 - 90 per cent of HC and CO emissions are produced during the first 100s of NEDC cycle, great improvement could be achieved reducing the catalyst light-off time. Different configurations of exhaust gas after treatment system have been tested to improve conversion efficiency during warm-up phases.

The new European Legislation requires new strategies in order to achieve a reliable emission diagnostic over the entire life of the vehicle (EOBD). For the validation and the fine-tuning of the new diagnostic controls, the car manufacturers must manage fleets of vehicles in order to evaluate the behavior of these diagnostics over a real aging cycle. This paper describes a useful tool that has been developed to check the most important diagnostic indexes behavior with aging, that help us in the management of a durability fleet. The system is composed of: a specific hardware added to the Engine Control Unit (ECU) a real time software for the automatic storage of the most important diagnostic parameters an off line software for data analysis. During the use of durability car the system runs automatically and does not require any additional operation to the driver (“black-box system”), and no additional skilled people is required for the data acquisition.