Structure-Borne Vehicle Interior Noise Estimation Using Accelerometer Based Intelligent Tires in Passenger Vehicles

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Date

2023-06-22

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Publisher

Virginia Tech

Abstract

With advancements in technology, electric vehicles are dominating the world making Internal Combustion engines less relevant, and hence vehicles are becoming quieter than ever before. But noise levels remain a significant concern for both passengers and automotive manufacturers. The vehicle's interior noise can affect the overall driving experience and even the safety of the driver and the passengers. The two main sources of vehicle interior noise are attributed to air-borne noises and structure-borne noises. A modern automobile is a complicated vibration system with several excitation sources like the engine, transmission system, tire/road interface excitation, and wind noise. With electric vehicles on the rise, the engine and transmission noise is practically eliminated, and effective preventive measures and control systems are already in place to reduce the aerodynamic-based noise, vibrations, and harshness (NVH) in modern automobiles making the structure-borne noise the most crucial of the noise sources. Tire/road interaction noise being the most dominant among the structure-borne noise is the main concern of the vehicle interior noise. The two main sources of vehicle interior noise induced by the tire pavement interaction noise are structure-borne noise induced by the low-frequency excitation and air-borne noises produced by the mid and high-frequency excitation.

The present study tested an all-season tire over varying operational conditions such as different speeds, normal loads, and inflation pressures on an asphalt surface. Two tri-axial accelerometers attached 1800 apart from each other on the inner liner of the tire of a Volkswagen Jetta were used to measure the circumferential, lateral, and radial acceleration data. An Inertial Measurement Unit (IMU) and velocity box (VBOX) were instrumented in the vehicle to measure the acceleration at the center of gravity (COG) position of the vehicle and the longitudinal velocity of the vehicle respectively. The vehicle was also equipped with a modified hybrid of Close Proximity Testing (CPX) and On-Board Sound Intensity (OBSI) sound measurement systems which were designed and manufactured in-house to measure the tire/road interaction noise at the leading and trailing edges of the tire/road contact patch. Another microphone was instrumented inside the passenger compartment of the vehicle at the passenger's seat right ear position over the tire mounted with the sound measurement system to measure the vehicle interior noise as interpreted by the passengers in the vehicle. Two data acquisition systems coupled with a real-time Simulink model were used to collect all the measured data, one for the noise signals and the other for velocity and acceleration signals.

The focus of the current study is to review different generation and amplification mechanisms of the structure-induced tire/road interaction noise and find the relevant dominant frequency ranges of the vehicle interior noise induced by the structure-borne noises using already established physics-based models and correlation techniques. It also aims to find correlations between tire acceleration, vehicle interior noise, and tire pavement interaction noise and their effect on different operational conditions like load, inflation pressure, and velocity. All the signals are studied in the time, frequency, and spectral domain and insights have been drawn on different tire/road noise generation and amplification mechanisms.

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Keywords

NVH, Intelligent Tires, In-cabin Noise, Tire Pavement Interaction Noise, Structure-Borne Noise, Signal Processing, Regression Machine Learning, Gaussian Process Regression.

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