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A computational fluid dynamics (CFD) guided design optimization was conducted for the piston bowl geometry for a heavy-duty diesel engine. The optimization goal was to minimize engine-out NOx emissions without sacrificing engine peak power and thermal efficiency. The CFD model was validated with experiments and the combustion system optimization was conducted under three selected operating conditions representing low speed, maximum torque, and rated power. A hundred piston bowl shapes were generated, of which 32 shapes with 3 spray angles for each shape were numerically analyzed and one optimized design of piston bowl geometry with spray angle was selected. On average, the optimized combustion system decreased nitrogen oxide (NOx) emissions by 17% and soot emissions by 41% without compromising maximum engine power and fuel economy.

On the basis of modular pulse converter (MPC) exhaust system the authors present a new swirl exhaust system. Structural parameters on the swirl exhaust system and MPC system for N8160ZC diesel engine were calculated by a mathematical optimum method, and the two systems were tested under the same engine operation for comparison. Experimental results show that the swirl exhaust system has a better engine performance under most of the operating conditions than MPC system, but worse under the low-speed and part-load conditions. In order to understand the mechanism of this swirl exhaust system well, a three-dimensional particle dynamic analyzer (3D-PDA) was utilized to measure the steady turbulent airflow in a swirl three-branched model. The computational fluid dynamics (CFD) code KIVA was modified to simulate the flows. Computational results are in good agreement with measuring ones and reveal the swirl flow behavior in the junction.

A fluid dynamic mathematical model of the room airflow in monolith was established by an equivalent continuum approach. The commercial CFD code STAR-CD was used to simulate multi-dimensional steady flows in automotive catalytic converters. In order to verify the fluid dynamic model of the converter, a three-hole Pitot tube was adopted to measure the velocity distribution at the rear of the monolith. Computing results are in good agreement with experiments, which means the established model is feasible and can be applied to predict the flow performances of various catalytic converters. Then, the enhanced diffusion header (EDH) converters and oblique diffuser converters with different configurations were designed and simulated by the CFD code. Simulation results indicate that EDH and an oblique diffuser can improve the flow uniformity and decrease pressure loss in the converters. These results provide a useful guide for the optimum design of automotive catalytic converters.

With increasingly stringent requirements and regulations related to particulate matter(PM) emissions, manufacturers are paying more and more attention to emissions from gasoline direct injection(GDI) engines. The present paper proposes an improved two-step soot model. The model is applied in the Kiva-Chemkin program to simulate the processes of spray impinging, fuel mixture preparation, combustion and soot formation in a typical turbocharged downsized GDI engine. The simulation results show that soot formation in the GDI engine is attributed to non-uniform distribution of the air-fuel mixture and pool fire of wall film in the cylinder. Under homogeneous mode, increasing the injection advance angle can optimize fuel atomization and improve air-fuel mixing, thus reducing soot formation. However, an excessive injection advance angle may cause spray to impinge on the cylinder wall and this will sharply increase the soot emission.

A catalyst surfaced on Ag/Al2O3 substrate for the selective catalyst reduction (SCR) of NOx by ethanol was evaluated in a diesel engine, and the effect of the catalyst on the reduction of NOx from the diesel engine under the EURO III ESC test modes was also investigated. The reductant injecting device was designed by means of computational fluid dynamics (CFD) analysis, and the engine test bench including the reductant injection system for the evaluation of the NOx-SCR catalyst performance was established. On the bench, the SCR catalyst with the ethanol reductant was tested at different temperatures and space velocities (SV), and integrated with an oxidation catalyst to reduce the diesel exhaust emissions of NOx, HC and CO. Under the conditions of the SV=30,000 h-1 and the exhaust temperature range of 350∼420°C, the NOx conversion efficiency is high over 90% and low beyond the temperature range.

A feasible method was developed to reconstruct the three-dimensional flame surface of SI combustion based on 2D images. A double-window constant volume vessel was designed to simultaneously obtain the side and bottom images of the flame. The flame front was reconstructed based on 2D images with a slicing model, in which the flame characteristics were derived by slicing flame contour modeling and flame-piston collision area analysis. The flame irregularity and anisotropy were also analyzed. Two different principles were used to build the slicing model, the ellipse hypothesis modeling and deep learning modeling, in which the ellipse hypothesis modeling was applied to reconstruct the flame in the optical SI engine. And the reconstruction results were analyzed and discussed. The reconstruction results show that part of the wrinkled and folded structure of the flame front in SI engines can be revealed based on the bottom view image.

In order to improve the ignition capacity and burning rate for spark-ignited engines, pre-chamber jet ignition is a promising technique to achieve fast premixed combustion and low pollutant emissions. However, few studies focus on the interaction between multiple reacting (i.e. flamelet) or reacted (i.e. radical) jets, its effect on ignition, exotherm and flow behaviors also remain to be revealed. This paper investigated two types of jet interaction under different pre-chamber structures, including the jet-crossing and unequal nozzle designs. Optical experiments under different conditions were conducted in a constant volume combustion chamber with CH4 as fuel, using simultaneous high speed schlieren and OH* chemiluminescence method. Meanwhile, computational fluid dynamics (CFD) simulations with CH4 and NH3/CH4 blend fuels were carried out using Converge software to provide further insights of turbulent flow and ignition process.

Synthesized driving cycles which can reflect the real world driving scenarios are essential for electrification and hybridization of powertrains of heavy duty logistics vehicles (HDLV). Current synthetic methods always neglected weight variation which is crucial for logistic vehicle driving scenarios. This paper proposed a method based on multi-dimensional Markov chains and big data to generate typical driving cycles with consideration of vehicle weight and slope. The validation of the synthesized driving cycle was based on a statistical analysis and the adequacy of the representative to real world driving data was demonstrated.

With the capability of avoiding failure in advance, failure prediction model is important not only to end users, but also to the service engineers in vehicle industry. This paper proposes an approach based on anomaly detection algorithms and telematic data to predict the failure of the engine air system with Turbo charger. Firstly, the relationship between air system and all obtained features are analyzed by both physical mechanism and data-wise. Then, the features including altitude, air temperature, engine output power, and charger pressure are selected as the input of the model, with the sampling interval of 1 minute. Based on the selected features, the healthy state for each vehicle is defined by the model as benchmark. Finally, the ‘Medium surface’ is determined for specific vehicle, which is a hyperplane with the medium points of the healthy state located at, to detect the minor weakness symptom (sub-health state).