Layout Option
Master of Science in Automotive Systems
Date of Award
2020
Document Type
Thesis
Degree Name
Automotive Systems
Department
Engineering
First Advisor
Dr. Jennifer M. Bastiaan
Second Advisor
Dr. Edward R. Green
Third Advisor
Dr. Randall S. Beikmann
Abstract
Due to the nearly silent operation of an electric motor, it is difficult for pedestrians to detect an approaching electric vehicle. To address this safety concern, the National Highway Traffic Safety Administration issued the Federal Motor Vehicle Safety Standard (FMVSS) No. 141, “Minimum Sound Requirements for Hybrid and Electric Vehicles”. This FMVSS 141 standard requires the measurement of electric vehicle noise according to certain test protocols; however, performing these tests can be difficult since inconsistent results can occur in the presence of transient background noise. Methods to isolate background noise during static sound measurements have already been established, though these methods are not directly applicable to a pass-by noise test where neither the background noise nor the vehicle itself as it travels past the microphone produce stationary sound signals. In this work, a 2017 Chevrolet Bolt electric vehicle is used for physical testing of pass-by noise at the Kettering University GM Mobility Research Center (GMMRC), an inner-city proving ground in Flint, Michigan. Sound signal processing is performed using a multiple coherence approach including discrete time intervals to isolate background noise from the noise of the electric vehicle. The suitability of both the signal processing method and the MRC facility for pass-by noise testing of electric vehicles is investigated and presented.
Recommended Citation
Nagesh Dindgur, Manuj, "Source Noise Extraction During Electric Vehicle Pass-By Noise Testing Using Multiple Coherence" (2020). Graduate Theses. 4.
https://digitalcommons.kettering.edu/graduate_theses/4
