Optimum design for intake and exhaust system of a heavy-duty diesel engine by using DFSS methodology

In this study, an optimum design for intake and exhaust system of a heavy-duty diesel engine was conducted by using the well-known design for six sigma (DFSS) methodology. As a result of this work, the NOx emission regulation has been successfully satisfied while minimizing the fuel consumption. On...

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Bibliographic Details
Published in:Journal of mechanical science and technology 2018, 32(7), , pp.3465-3472
Main Author: Wang, Tae Joong
Format: Article
Language:English
Subjects:
Control
Design parameters
Diesel engines
Dynamical Systems
Engine tests
Engineering
Exhaust gases
Exhaust pipes
Exhaust systems
Industrial and Production Engineering
Mechanical Engineering
Nitrogen oxides
Orthogonal arrays
Superchargers
Thermodynamic efficiency
Venturi tubes
Vibration
기계공학
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Summary:In this study, an optimum design for intake and exhaust system of a heavy-duty diesel engine was conducted by using the well-known design for six sigma (DFSS) methodology. As a result of this work, the NOx emission regulation has been successfully satisfied while minimizing the fuel consumption. On the basis of this DFSS work, the design robustness of the engine system was also enhanced. Hence, it is expected that the final design proposal would reduce the variability in brake thermal efficiency (BTE) that could be caused by the harsh environment and the system aging. Especially, this work has successfully raised the amount of exhaust gas recirculation (EGR) up to the target level by adopting the venturi tubes in the intake and exhaust lines. In this study, engine cycle simulation technique was employed to assess the effect of the various design parameters and the final design proposal was verified through a real engine test. The current optimum design work has considered four control factors such as the size of turbocharger, the diameter of intake and exhaust venturi pipes, and the efficiency of EGR cooler. Here, an L9 orthogonal array was employed to efficiently choose the best design proposal among 81 design combinations (i.e., four independent control factors which individually have three different levels).
ISSN:1738-494X
1976-3824
DOI:10.1007/s12206-018-0650-6