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A DFSS Approach to Optimize the Second Row Floor Duct Using Parametric Modelling
ISSN: 0148-7191, e-ISSN: 2688-3627
Published March 28, 2017 by SAE International in United States
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The main function of mobile air conditioning system in a vehicle is to provide the thermal comfort to the occupants sitting inside the vehicle at all environmental conditions. The function of ducts is to get the sufficient airflow from the HVAC system and distribute the airflow evenly throughout the cabin. In this paper, the focus is to optimize the rear passenger floor duct system to meet the target requirements through design for six sigma (DFSS) methodology. Computational fluid dynamics analysis (CFD) has been used extensively to optimize system performance and shorten the product development time. In this methodology, a parametric modeling of floor duct design using the factors such as crossectional area, duct length, insulation type, insulation thickness and thickness of duct were created using CATIA. L12 orthogonal design array matrix has been created and the 3D CFD analysis has been carried out individually to check the velocity and temperature. The impacts of each design parameters and levels have been analyzed extensively and best combination of design parameters have been found out for the rear floor duct to meet the target requirements.
Physical testing is carried out for the optimized floor duct design by making proto parts for the optimized design. There is a good correlation agreement between simulation and test results for the optimized design. Parametric modelling of floor duct significantly aids in reducing the manual design time for simulation by 40% and the DFSS approach helps in finding out the optimized design parameters of floor duct during the design phase of new programs. This methodology can be followed for optimization of duct systems to shorten the product development cycle of the program.
CitationVasanth, B., Putcha, U., Sathish Kumar, S., nukala, R. et al., "A DFSS Approach to Optimize the Second Row Floor Duct Using Parametric Modelling," SAE Technical Paper 2017-01-0176, 2017, https://doi.org/10.4271/2017-01-0176.
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