Correlation Study of Low-Frequency Engine Order Noise Prediction at Compressor Inlet for a PHEV and Resonator Tuning

<div class="section abstract"><div class="htmlview paragraph">Sound pollution has become one of the major environmental concerns for the global automotive industry. Air Induction System (AIS) plays an important role in engine performance and vehicle noise. An ideal design of AIS provides debris-free air for combustion and reduces the engine noise that is heard while snorkeling. This work aims to correlate low-frequency engine order noise prediction at the compressor inlet and snorkel inlet for a 2.0L I4 turbo engine of a Plug-in hybrid vehicle (PHEV) for better acoustic performance without compromising on engine performance. 1D simulation software GT-POWER, Simcenter 3D, and Hypermesh are used for this work. Transmission loss (TL) results with respect to the frequency of the air-box with ducts and intake manifold with charge air cooler are plotted from 0 to 1000 Hz. The air intake system TL results show a good correlation between 3D and 1D till 600 Hz. Compressor and snorkel noise simulation results, especially the firing order and its harmonic orders, are compared with test results from 1500 to 5000 rpm. Helmholtz resonators are deployed on the clean side duct (CSD) to attenuate the snorkel noise. The optimized design shows better acoustic performance than the original design. Deployment of advanced software and experimental methods leads to First Time Right product development by effectively reducing valuable design cycle time and can be further used in research for future vehicle programs.</div></div>

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Publication Details

Journal
SAE technical papers on CD-ROM/SAE technical paper series
Published
2025-03-31
DOI
https://doi.org/10.4271/2025-01-8643
Primary Topic
Advanced Combustion Engine Technologies
Type
article
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article

Correlation Study of Low-Frequency Engine Order Noise Prediction at Compressor Inlet for a PHEV and Resonator Tuning

Manish Dixit
SAE technical papers on CD-ROM/SAE technical paper series
Advanced Combustion Engine Technologies
article

Correlation Study of Low-Frequency Engine Order Noise Prediction at Compressor Inlet for a PHEV and Resonator Tuning

Manish Dixit
article en

Abstract

<div class="section abstract"><div class="htmlview paragraph">Sound pollution has become one of the major environmental concerns for the global automotive industry. Air Induction System (AIS) plays an important role in engine performance and vehicle noise. An ideal design of AIS provides debris-free air for combustion and reduces the engine noise that is heard while snorkeling. This work aims to correlate low-frequency engine order noise prediction at the compressor inlet and snorkel inlet for a 2.0L I4 turbo engine of a Plug-in hybrid vehicle (PHEV) for better acoustic performance without compromising on engine performance. 1D simulation software GT-POWER, Simcenter 3D, and Hypermesh are used for this work. Transmission loss (TL) results with respect to the frequency of the air-box with ducts and intake manifold with charge air cooler are plotted from 0 to 1000 Hz. The air intake system TL results show a good correlation between 3D and 1D till 600 Hz. Compressor and snorkel noise simulation results, especially the firing order and its harmonic orders, are compared with test results from 1500 to 5000 rpm. Helmholtz resonators are deployed on the clean side duct (CSD) to attenuate the snorkel noise. The optimized design shows better acoustic performance than the original design. Deployment of advanced software and experimental methods leads to First Time Right product development by effectively reducing valuable design cycle time and can be further used in research for future vehicle programs.</div></div>

SAE technical papers on CD-ROM/SAE technical paper seriesVol. 1
Openalex Percentile: Top 95%
Advanced Combustion Engine Technologies
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Correlation Study of Low-Frequency Engine Order Noise Prediction at Compressor Inlet for a PHEV and Resonator Tuning — Manish Dixit · SAE technical papers on CD-ROM/SAE technical paper series (2025) | TGRS Research Map | TGRS