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

机译:使用六种Sigma方法设计的V8发动机强大的AIS参数模型的开发

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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.
机译:汽车空气感应系统(AIS)是发动机系统的重要部分,其将空气传送到发动机。精心设计的AIS应具有低流量限制,并在呼吸管处辐射好的质量声音。 GT功率仿真工具已被广泛利用,以评估工业中的呼吸噪声。在Fiat克莱斯勒汽车中,在AIS开发中开发和实施了六西格玛(DFSS)方法的设计仿真方法,以满足功能要求。开发工作包括不同类型的DFSS项目,例如识别新概念,强大的优化和鲁棒评估等。在开发AIS参数模型时,介绍了强大的优化项目的工作,以实现V8的优化呼吸噪声性能引擎。首先,描述了使用GT功率和DFSS使用Taguchi的参数设计方法的AIS声学建模理论。其次,研究了几种AIS设计控制因素对AIS声音衰减和呼吸管业绩的影响。最后,在开发V8发动机的参数AIS模型上,提出了Taguchi的参数设计方法的八个步骤。基于来自验证步骤的结果,提出了对该指定V8引擎的优化AIS参数模型。优化的模型对温度变化更加坚固,具有更好的呼吸噪声性能。结论部分讨论了从该项目中学到的经验教训和未来的工作。

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