Development of Advanced Signal Analysis Technique for Pass-by Noise Source Identification of Light Commercial Vehicle

The auto industry is one of the major contributors for noise pollution in urban areas. Specifically, highly populated heavy commercial diesel vehicle such as buses, trucks are dominant because of its usage pattern, and capacity. This noise is contributed by various vehicle systems like engine, transmission, exhaust intake, tires etc. When the pass by noise levels exceeds regulatory limit, as per IS 3028, it is important for NVH automotive engineer to identify the sources & their ranking for contribution in pass by noise. The traditional methods of source identification such as windowing technique, sequential swapping of systems and subsystems which are time consuming.Also advanced method in which data acquisition with a synchronizing technology like telemetry or Wi-Fi for source ranking are effective for correctness.However they are time and resource consuming, which can adversely impact product development timeline. This paper discusses about the advanced signal analysis technique that enables the synchronization of in-vehicle near source data with exterior pass-by noise microphone data without any external synchronization technology. The key element of this technique is the use of innovative signal processing technique to extract the vehicle engine rpm from exterior pass-by noise microphone noise color plot. Once the engine rpm at which the maximum pass-by noise occurred has been ascertained, octave analysis and contribution analysis can be carried out for source identification and ranking sources at critical engine rpm where higher pass by noise was recorded. This method was validated by identifying the transmission system as the primary contributor to higher pass-by noise in a light commercial vehicle. This exercise provides a method to synchronize and analyze data from 2 independent data acquisition systems without any external synchronizing equipment and also proves that transmission unit contribution to pass-by noise is significant and must be monitored closely.