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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.

Compressed Natural Gas (CNG), because of its low cost, high H/C ratio, and high octane number, has great potential in automotive industry, especially for heavy-duty commercial vehicles. However, relative slow flame speed of natural gas leads to long combustion duration and low thermal efficiency and tends to cause knock combustion at high load, which will aggravate engine thermal load and reliability. Enhancing turbulence intensity in combustion chamber is an effective way to accelerate flame propagation speed and improve combustion performance. In this study, the flow simulations of several piston bowls with different inner-convex forms were carried out using three-dimensional computational fluid dynamics (3D-CFD) software CONVERGE. The numerical results showed the piston bowls with inner-convex could disturb the charge swirl motion and enhance turbulence of different intensity. A hexagram geometry bowl was proved to have the best function in strengthening turbulence intensity.

Due to the rapid development of road infrastructure and vehicle population in China, the fuel consumption and emission of on-road vehicles tested in China World Transient Vehicle Cycle (C-WTVC) cannot indicate the real driving results. But the test results in China Heavy-duty Commercial Vehicle Test Cycle-Coach (CHTC-C) based on the road driving conditions in China are closer to the actual driving data. In this paper, the model for predicting the performance of heavy-duty vehicles is established and validated. The fuel consumption and NOx emission of a Euro VI heavy-duty coach under C-WTVC and CHTC-C tests are calculated by employing the developed model. Furthermore, the fuel consumption of the test coach is optimized and its sensitivity to the driving factors is analyzed.

The diesel particulate filter (DPF) is an effective technology for particulate matter (PM) and particle number (PN) reduction. On heavy-duty diesel engines, the passive regeneration by Diesel Oxidation catalysts (DOC) and catalyzed DPFs (CDPF) is widely used for its simplicity and low cost, which is generally combined with the active regeneration of exhaust fuel injection. This study investigated a DOC-CDPF system with exhaust fuel injection upstream of the DOC. The system was integrated with a 7-liter diesel engine whose engine-out PM emission was below the Euro IV level and tested on an engine dynamometer. PM and PN concentrations were measured based on the Particle Measurement Programme (PMP), and the number/size spectrum for particles was obtained by a Differential Mobility Spectrometer (DMS). The filtration efficiency of DPF on PN was higher than 99% in ESC test, while the efficiency on PM was only 58%.

Urea-based selective catalytic reduction (SCR) of nitric oxides (NOx) is a key technology for heavy-duty diesel engines to achieve the increasingly stringent NOx emission standards. The aqueous urea injection control is critical for urea-SCR systems in order to achieve high NOx conversion efficiency while restricting the tailpipe ammonia (NH3) slip. For Euro VI emission regulation, an advanced control strategy is essential for SCR systems since its NOx emission limits are tighter and test procedure are more stringent compared to Euro IV and Euro V. The complex chemical kinetics of the SCR process has motivated model-based control design approaches. However, the model is too complex to allow real-time implementation. Therefore, it is very important to have a reduced order model for SCR control system.

Urea selective catalytic reduction (SCR) is a key technology for heavy-duty diesel engines to meet the increasingly stringent nitric oxides (NOx) emission limits of regulations. The urea water solution injection control is critical for urea SCR systems to achieve high NOx conversion efficiency while keeping the ammonia (NH3) slip at a required level. In general, an open loop control strategy is sufficient for SCR systems to satisfy Euro IV and Euro V NOx emission limits. However, for Euro VI emission regulation, advanced control strategy is essential for SCR systems due to its more tightened NOx emission limit and more severe test procedure compared to Euro IV and Euro V. This work proposed an approach to achieve model based closed loop control for SCR systems to meet the Euro VI NOx emission limits. A chemical kinetic model of the SCR catalyst was established and validated to estimate the ammonia storage in the SCR catalyst.

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.