Internal combustion engine noise analysis and production using a novel multipulse excited time series modeling technique.

Abstract

Automobile manufacturers have learned that customers have well‐defined notions as to what an automobile engine should sound like for the various vehicle segments (luxury, sportscar, economy, etc.). Therefore, it is advantageous to model and synthesize various types of engine sounds for customer evaluation. Much work has been done in the area of speech modeling and synthesis based on physical assumptions of human speech production. The intent of this paper is twofold. First discussed are the similarities and differences between speech and engine noise modeling and synthesis problems. Second, application of techniques learned for speech synthesis to that of automotive noise production is demonstrated. Early models of speech production used periodic pulse excitation in a linear predictive coding (LPC) framework. This technique is used to synthesize engine noise. It is then compared to that of a new suboptimal multipulse method proposed by the authors. It is hoped that this paper will pave the path for a better understanding of the relationship between the two systems so that much of the work performed in speech analysis and production can be applied to the analysis and synthesis of automotive internal combustion engine sounds.