HVAC System Noise Prediction through CFD Simulation

2019-26-0210

01/09/2019

Event
Symposium on International Automotive Technology 2019
Authors Abstract
Content
Vehicles with Heating, Ventilation and Air Conditioning (HVAC) system have shown growing demand for in-cabin acoustic comfort in recent days. This is mainly due to advancement in new generation quieter powertrains and improved cabin sealing which has made HVAC system noise more dominant inside the cabin. HVAC system noise is predominantly flow induced. Further, considering future hybrid and Electric vehicles where engine powertrain noise will be insignificant, more attention will be required for HVAC system design. Contribution of noise in the cabin from HVAC system is in the frequency range 400 Hz to 5000 Hz. The noise produced by a HVAC system is mainly due to aeroacoustics mechanisms related to the flow fluctuations due to the blower rotation and complex flow path in HVAC unit flaps, duct and vents. Air borne noise is becoming important as other noise sources reduced with advancement of material, insulation and architectural strategies. This paper discusses simulation methodology developed to predict HVAC system level noise using CAA (Computational Aeroacoustics) approach. Detached Eddy Simulation (DES) with compressibility is used to predict sound generation and propagation at different receiver locations. Design feedback for HVAC unit, ducts and vents are identified and countermeasures are suggested from this method, which resulted in noise reduction at system and thereby vehicle level. This method is found useful for design ranking, design improvements during HVAC system’s design maturation stage in vehicle. This process is validated with test, and good correlation is observed between CFD prediction and test measurements.
Meta TagsDetails
DOI
https://doi.org/10.4271/2019-26-0210
Pages
8
Citation
Kandekar, A., Nagarhalli, P., Dol, Y., Thakur, S. et al., "HVAC System Noise Prediction through CFD Simulation," SAE Technical Paper 2019-26-0210, 2019, https://doi.org/10.4271/2019-26-0210.
Additional Details
Publisher
Published
Jan 9, 2019
Product Code
2019-26-0210
Content Type
Technical Paper
Language
English