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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.

Tires are one of the major sources of noise and vibration in vehicles. The vibration characteristic of a tire depends on its resonant frequencies and mode shapes. Hence, it is desirable to study how different parameters affect the characteristics of tires. In the current paper, experimental modal tests are performed on a tire in free-free and fixed conditions. To obtain the mode shapes and the natural frequencies, the tire is excited using a mechanical shaker and the response of the tire to the excitation is measured using three roving tri-axial accelerometers. The mode shapes and resonant frequencies of the tire are extracted using LMS PolyMax modal analysis. The obtained mode shapes in the two configurations are compared using Modal Assurance Criterion (MAC) to show how mode shapes of tires change when the tire is moved from a free-free configuration to a fixed configuration. It is shown that some modes of the tire are more sensitive to boundary conditions.

Doors inside an automotive HVAC module are essential components to ensure occupant comfort by controlling the cabin temperature and directing the air flow. For temperature control, the function of a door is not only to close/block the airflow path via the door seal that presses against HVAC wall, but also control the amount of hot and cold airflow to maintain cabin temperature. To meet the stringent OEM sealing requirement while maintaining a cost-effective product, a “V-Shape” soft rubber seal is commonly used. However, in certain conditions when the door is in the position other than closed which creates a small gap, this “V-Shape” seal is susceptible to the generation of objectionable whistle noise for the vehicle passengers. This nuisance can easily reduce end-customer satisfaction to the overall HVAC performance.

A comprehensive finite element methodology is developed to predict the compressible flow performance of a non-symmetric 7-blade axial flow fan, and to quantify the source strength and sound pressure levels at any location in the system. The acoustic and flow performances of the fan are predicted simultaneously using a computational aero-acoustic technique combining transient flow analysis and noise propagation. The calculated sound power levels compare favorably with the measured sound power data per AMCA 300-96 code.

The automotive and aerospace industries are increasingly using the light-weight material to improve the vehicle performance. However, using light-weight material can increase the airborne and structure-borne noise. A special attention needs to be paid in designing the structures and measuring their dynamics. Conventionally, the structure is excited using an impulse hammer or a mechanical shaker and the response is measured using uniaxial or multi-axial accelerometers to obtain the dynamics of the structure. However, using contact-based transducers can mass load the structure and provide data at a few discrete points. Hence, obtaining the true dynamics of the structure conventionally can be challenging. In the past few years, stereo-photogrammetry and three-dimensional digital image correlation have received special attention in collecting operating data for structural analysis. These non-contact optical techniques provide a wealth of distributed data over the entire structure.

This paper aims to study the NVH and acoustic performance of a 3-phase AC induction motor in order to develop an approach to reduce the magnetic component of noise from an electric motor in an electric vehicle (EV). The final goal of this project is to reduce the magnetic component of sound from the motor by making modifications to the end bracket of the motor housing. EVs are being considered the future of mobility mainly due to the fact that they are environment-friendly. As many companies are already investing in this technology, electric drives are set to become extremely popular in the years to come. The heart of an EV is its motor. Modern electric vehicles are quiet, furthermore with the lack of an IC engine to mask most sounds from other components, the sound from the electric motor and other auxiliary parts become more prominent.

Data-driven modeling can help improve understanding of the governing equations for systems that are challenging to model. In the current work, the Sparse Identification of Nonlinear Dynamical systems (SINDy) is used to predict the dynamic behavior of dynamic problems for NVH applications. To show the merit of the approach, the paper demonstrates how the equations of motions for linear and nonlinear multi-degree of freedom systems can be obtained. First, the SINDy method is utilized to capture the dynamic behavior of linear systems. Second, the accuracy of the SINDy algorithm is investigated with nonlinear dynamic systems. SINDy can output differential equations that correspond to the data. This method can be used to find equations for dynamical systems that have not yet been discovered or to study current systems to compare with our current understanding of the dynamical system.