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More and more stringent emission regulations and the desire to reduce fuel consumption lead to an increasing demand for precise and close-loop combustion control of diesel engines. Cylinder pressure-based combustion control is gradually used for diesel engines in order to enhance emission robustness and reduce fuel consumption. However, it increases the cost. In this paper, a new prediction method of combustion parameters is presented for diesel engines. The experiment was carried out on a test bench to obtain the ECU (Electronic Control Unit) signals of a heavy-duty diesel engine by calibration software. The combustion parameters was measured by a combustion analyzer, such as maximum cylinder pressure (MCP), maximum combustion temperature (MCT), and combustion center of gravity (CA50). A combustion model using genetic programming (GP) is built. The input parameters are chosen from the ECU signals, such as engine speed, engine load, injection quantities, inlet air flow rate.

Urea SCR technology is the most promising technique to reduce NOx emissions from heavy duty diesel engines. 32.5wt% aqueous urea solution is widely used as ammonia storage species for the urea SCR process. The thermolysis and hydrolysis of urea produces reducing agent ammonia and reduces NOx emissions to nitrogen and water. However, the application of urea SCR technology has many challenges at low temperature conditions, such as deposits formation in the exhaust pipe, lack deNOx performance at low temperature and freezing below -12°C. For preventing deposits formation, aqueous urea solution is hardly injected into exhaust gas stream at temperature below 200°C. The aqueous urea solution used as reducing agent precursor is the main obstacle for achieving high deNOx performances at low temperature conditions. This paper presents a solid SCR technology for control NOx emissions from heavy duty diesel engines.

A simulation model of catalyzed diesel particulate filter (CDPF) is established based on the CFD software FIRE and has been validated through a series of experimental comparison. This model simulates the CDPF continuous regeneration process, and the factors that influence the exhaust NO2 concentration from CDPF including oxygen concentration, exhaust temperature, space velocity, proportion of NO2/NOX and soot mass fraction are studied. The results show that the higher oxygen concentration causes an increase in NO2/NOX. The NO2/NOX is significantly increased when the exhaust temperature is about 350 °C based on the simulation conditions when the inlet oxygen concentration is at 5.79% and the space velocity is 7s−1. The space velocity in a certain degree leads to higher NO2/NOX. For the soot mass, there is no significant influence of increasing proportion of the NO2/NOX.

Particle emissions of seven gasoline vehicles were measured using an electrical low-pressure impactor (ELPI) over the new European driving cycle (NEDC). Two dilution systems were utilized: one is constant volume system (CVS) for constant exhaust volume and the other is ejector dilutor for constant dilution ratio. Then the time-resolved number concentration, size distributions and total particle number were obtained. The effects of misfire rate and oxygen sensor failure on the particle emission were also studied in order to primarily examine the on-board diagnoses of particle number emission of gasoline vehicle. The results indicate that the particles emitted by gasoline vehicles are mainly in the form of nuclei mode in diameter range from 7 nm to 55 nm. The specific number emissions vary from 1.56×1013 to 8.42×1013 particles/km and GMD ranges from 27 to 50nm.