Development of a Robust AIS Parametric Model for V8 Engines Using Design for Six Sigma Approach

2018-01-0140

04/03/2018

Features
Event
WCX World Congress Experience
Authors Abstract
Content
The automotive Air Induction System (AIS) is an important part of the engine systems which delivers the air to the engine. A well-designed AIS should have low flow restriction and radiates a good quality sound at the snorkel. The GT-Power simulation tool has been widely utilized to evaluate the snorkel noise in industry. In Fiat Chrysler Automobiles, the simulation method enhanced with Design For Six Sigma (DFSS) approach has been developed and implemented in AIS development to meet the functional requirements. The development work included different types of DFSS projects such as identifying new concept, robust optimization and robust assessment etc. In this paper, the work of a robust optimization project is presented on developing an AIS parametric model to achieve optimized snorkel noise performance for a V8 engine.
First, the theory of AIS acoustic modeling using GT-power and DFSS robust optimization using Taguchi’s parameter design method are described. Secondly, the effects of several AIS design control factors on the AIS sound attenuation and snorkel performance are studied. Finally, the eight steps of Taguchi’s parameter design method are presented on developing a parametric AIS model for a V8 engine. Based on the results from the verification step, an optimized AIS parametric model to this specified V8 engine is suggested. The optimized model is more robust against temperature variation and has better snorkel noise performance. The lessons learned from this project and future work are discussed in the conclusion section.
Meta TagsDetails
DOI
https://doi.org/10.4271/2018-01-0140
Pages
10
Citation
Zhang, W., Likich, M., and Butler, B., "Development of a Robust AIS Parametric Model for V8 Engines Using Design for Six Sigma Approach," SAE Technical Paper 2018-01-0140, 2018, https://doi.org/10.4271/2018-01-0140.
Additional Details
Publisher
Published
Apr 3, 2018
Product Code
2018-01-0140
Content Type
Technical Paper
Language
English