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Piston Bowl Design Optimization to Improve Low End Rated Torque in BS-VI Diesel Engine Based on Multi-Dimensional Combustion Simulation
Technical Paper
2020-01-0241
ISSN: 0148-7191, e-ISSN: 2688-3627
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Abstract
In cylinder combustion and emission characteristics are dependent on piston bowl geometry design. In-cylinder fuel air mixing and flame front movement are influenced by piston bowl shape and design. These phenomena in turns affect the combustion behavior and the power developed by the diesel engine.
In this study piston bowl geometry optimization of a LMD diesel engine is carried out to improve the torque and BSFC output at low end rated operating zones. The optimized bowl geometry is also incorporated in the engine and validated on the test bed.
In this work, a commercially available CFD code AVL FIRE is used for combustion simulation and bowl geometry optimization. The validation of in-cylinder combustion simulation of a 2 liter Turbocharged LMD BS-VI diesel engine with base piston bowl geometry is carried out with the available test data. The validation of combustion simulation is performed for four engine operating speed points covering rated torque to rated power operating condition. Four key piston bowl geometry parameters were selected for the optimization study with the objective to improve the torque output at rated torque operation. Two bowl geometries from the optimization study were selected for further analysis at remaining engine operating points. Both the bowl geometries showed improvement in torque and BSFC at all the simulated operating zones. Based on the design feasibility one of the bowl geometry was selected for validation on physical engine. The results from test bed showed the optimized geometry gave torque improvement as predicted by the combustion simulation.
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Appukuttan, A., Bisht, J., Kaundabalaraman, K., and Rathi, H., "Piston Bowl Design Optimization to Improve Low End Rated Torque in BS-VI Diesel Engine Based on Multi-Dimensional Combustion Simulation," SAE Technical Paper 2020-01-0241, 2020, https://doi.org/10.4271/2020-01-0241.Data Sets - Support Documents
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