Optimization of IP Duct Vane Articulation for Improved Cabin Airflow Directivity

2019-28-0132

10/11/2019

Event
International Conference on Advances in Design, Materials, Manufacturing and Surface Engineering for Mobility
Authors Abstract
Content
The air velocity achieved at driver and passenger aim point is one of the key parameters to evaluate the automotive air-conditioning system performance. The design of duct, vent and vanes has a major contribution in the cabin air flow directivity. However, visual appearance of vent and vane receives higher priority in design because of market demand than their performance. More iterations are carried out to finalize the HVAC duct assembly until the target velocity is achieved. The objective of this study is to develop an automated process for vane articulation study along with predicting the optimized velocity at driver and passengers. The automated simulation of vane articulation study is carried out using STAR-CCM+ and SHERPA optimization algorithm which is available in HEEDS tool. The minimum and maximum vane angle are defined as parameters and face level velocity is defined as response. Depending on the optimization technique and number of iterations defined in HEEDS, the vane angle will get updated and the design iterations proceeds automatically till the number of iterations are met. The obtained results are compared with test data and correlated well. This process will be useful to finalize the duct assembly design during the concept phase of new programs. This process extensively assists in plummeting the manual effort of design and the simulation runs are automated resulting in overall diminution of timing required for vane articulation studies.
Meta TagsDetails
DOI
https://doi.org/10.4271/2019-28-0132
Pages
6
Citation
Baskar, S., Raju, K., Gopinathan, N., and Udaya Kumar, P., "Optimization of IP Duct Vane Articulation for Improved Cabin Airflow Directivity," SAE Technical Paper 2019-28-0132, 2019, https://doi.org/10.4271/2019-28-0132.
Additional Details
Publisher
Published
Oct 11, 2019
Product Code
2019-28-0132
Content Type
Technical Paper
Language
English