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This research aims presents the method classifying the noise source and evaluating the sound quality of the noise caused by operating of electric power steering wheel in an electric vehicle. The steering wheel has been operated by the motor drive by electric power and it called motor-driven electric power (MDPS) system. If the motor is attached to the steering column of the steering device, it is called C-MDPS system. The steering device of the C-MDPS system comprises of motor, bearings, steering column, steering wheel and worm shaft. Among these components the motor and bearings are main noise sources of C-MDPS system. When the steering wheel is operated in an electric vehicle, the operating noise of the steering device inside the vehicle is more annoying than that in a gasoline engine vehicle since the operating noise is not masked by engine noise. Defects in the C-MDPS system worsen the operating noise of the steering system.

This research aims to develop an inverse control method capable of adaptively simulating dynamic models of car subsystems in the rig-test condition. Accurate simulation of the actual vibration conditions is one of the most crucial factors in realizing reliable rig-test platforms. However, most typical rig tests are conducted under simple random or harmonic sweep conditions. Moreover, the conventional test methods are hard to directly adapt to the actual vibration conditions when switching the dynamic characteristics of the subsystem in the rig test. In the present work, we developed an inverse controller to adaptively control the vibration exciter referring to the target vibration signal. An adaptive LMS filter, employed for the control algorithm, updated the filter weights in real time by referring to the target and the measured acceleration signals.

This paper presents the novel active vibration control (AVC) system that controls vehicle body vibration to reduce the structural borne road noise. As a result of vehicle noise testing in an electric vehicle, the predominant frequency of vehicle body vibration that worsens interior noise is in the range of 150-250Hz. Such vibration in that frequency range, commonly masked in engine vibrations, are hard to neglect for electric vehicles. The vibration source of that frequency is the resonance of tire cavity mode. Resonator or absorption material has been applied inside the tire for the control of cavity noise as a passive method. They require an increment of weight and cost. Therefore, a novel method is necessary. The vibration amplified by resonance of cavity mode is transferred to the vehicle body throughout the suspension system. To reduce the vibration, AVC system is applied to the suspension mount.

This study presents a novel active vibration control (AVC) system on motor driven power steering (MDPS) to reduce interior noise reduction caused by operating the MDPS in an electric vehicle. MDPS is electronic power steering (EPS). The MDPS attached to the rack gear of power steering system is called R-MDPS. Operating of the R-MDPS generates a structural vibration of R-MDPS, and the vibration is transmitted to car body through mounts of car subframe. The vibrating body of car becomes a monopole and dipole sources of vibroacoustic noise generated inside car. This vibracoustic noise is a structure borne noise and makes passenger annoyance. To reduce interior noise inside a car directly, active noise control (ANC) has been used as active method and is a useful method for active cancellation of the low frequency noises less than 400Hz.

Tire tread pattern noise is a major source of road noise generated by motor vehicles. Recently, noise control technology has been developing, and low-noise motor vehicles, such as electric vehicles and hybrid vehicles, have been commercialized. The importance of low-noise tires has increased since regulations R117 for tire noise and R51.03 for motor vehicle noise have been strengthened. To evaluate the tire noise in the development stage of motor vehicles, finished products of tires are required; hence, financial and time costs should be invested. Therefore, it is highly useful to predict tire noise levels in the early stages. Recently, a technology to predict the tire pattern noise using a supervised training method of artificial neural network (ANN) has been developed. The tire tread depth is estimated using the shading of the full image of the actual tire, and the leading edge of the contact patch is calculated using tire contact patch images.

It is known that the major source of rumbling noise the combustion force of an engine. The combustion force excites the engine and induces vibrations of the powertrain. These vibrations are then transferred to the body of the vehicle via its structural transfer path. Moreover, the vibrations of the vehicle’s body emit internal vibra-acoustic noise. This noise is often referred to as the rumbling noise due to the structural borne path. If there are structural resonances among the structural paths such as the engine, transmission, mount bracket, suspension, and the vehicle’s body, the rumbling noise could be amplified. To identify the major resonances of the structural transfer path, classical transfer path analysis (CTPA) has been traditionally utilized. The method has a significant limitation in that it is necessary to decouple the substructures to obtain the contact force between individual components and to identify the transfer path of the structure-borne sound.

Automotive companies are trying to enhance the customer’s impression by improving engine sound quality. The target of this sound quality is to create a brand sound that is preferred by their customers as well as quietness of interior noise. Over the past decade there have been many studies in the field of automotive sound quality. These have included the technologies such as tuning of intake orifice and exhaust orifice, tuning of structure-borne, intake feedback devices, active exhaust valves, ANC (Active Noise Cancellation) and ASD (Active Sound Design). The three elements of the sound that affect the feeling of the customer are known as engine order arrangement, frequency balance, and linearity. Here, the most important thing in sound quality development is the order arrangement.

This paper presents a novel method predicting the variation of sound quality of interior noise depending on the change of the proprieties of absorption materials. At the first, the model predicting the interior noise corresponding to the change of the absorption material in engine room is proposed. Secondly the index to estimate the sound quality of the predicted sound is developed. Thirdly the experimental work has been conducted with seven different materials and validated the newly developed index. Finally, this index is applied for the optimization of absorption material to improve the sound quality of interior noise in a passenger car.

This paper presents the influence of radiated noise from engine surface according to assembly condition between the engine block and oil pan. At the first, the force exciting the main bearing of cylinder block is calculated by using a multi-body dynamics model of the engine crankshaft. Secondly, the modal analysis is processed to obtain the mode contribution and modal participation factors for the FEM of a virtual cylinder block. Thirdly, the radiated noise from a structure is calculated by acoustic-FEM analysis. This structure is assembled by the virtual oil pan with a rigid connection method and a soft connection method. The sandwich panel connection model is used for the soft connection method. The sound radiated from this assemble structure is calculated according to two different connection properties respectively. The sound matrices for two results are compared using an objective method.

This paper presents a systematic approach to interior engine sound design for enhancing sound character of car interior sound effectively. Nowadays an active noise control technology is widely used in vehicle industry. Particularly, an active sound design (ASD) technique using vehicle’s audio system for controlling interior sound due to powertrain has become a general method to improve sound quality or character. The ASD system using speakers has the advantage of creating various sounds relatively easy. In this study, the novel systematic approach is proposed to guide the efficient design of powerful and pleasant acceleration sound by order spectrum analysis. At first, primary attributes of powerful and pleasant sound were analyzed and sound concept was derived. Secondly, the optimal linearity and the level envelope of firing order were derived by subjective evaluation.

Recently the interior sound is actively generated by the active sound design (ASD) device in a passenger car. Therefore, the objective evaluation method for the sound quality of actively designed sounds is required. In previous research, the sound quality of interior sound has been presented with powerful and pleasant for the existing passenger car. This paper presents a novel approach method for the objective evaluation of powerfulness and pleasantness of actively designed interior sound. The powerfulness has been evaluated based on the degreed of modulation and a quantity of low frequency booming of the sound in the paper. On the other hand, the pleasantness is evaluated based on the slope ratio of harmonic orders per octave in frequency domain. These evaluation methods are successfully applied to the objective evaluation of luxury passenger car.

In this paper, the sound intensity and airborne source quantification methods were used to estimate the airborne noise radiating from a gasoline direction injection engine and the contribution of gasoline direction injection engine components to such airborne noise. In order to estimate noise contribution using airborne source quantification, the volume velocity for source should be estimated. In the previous method, the volume velocity has been estimated by using the inverse method. In this paper, the volume velocity is estimated directly. For this work, the sources of noise radiating from the engine are first identified by measuring the sound intensity of the noise sources while the car's engine is running at idle condition. The volume velocities of these sources estimated by multiplying the area of that noise source and directly measured particle velocity.

In the previous paper [1], the impact sound metric is developed for the evaluation of the impact noise in passenger cars based on the wavelet transform. In this paper, seven semantics are subjectively evaluated by 25 participants based on semantic difference method. Two major factors are selected for important factors of impact noise in passenger car. One is comfortable, the other one is impulsive. Two sound indexes for impulsive and comfort are considered for the evaluation of impact sound when a car is driven on 7 difference road surface. These indexes are developed based on new sound metric and other major sound metrics like loudness, fluctuation strength, etc. For the development of these indexes, the interior sounds of 15 passenger car are measured by using artificial head and evaluated subjectively by the participants. These two indexes are successfully applied to the improvement of the impact sound in a test vehicle.

Luxury sound is one of the most important sound qualities in a premium passenger car. Previous work has shown that, because of the effects of many different interior sounds, it is difficult to evaluate the luxury sound objectively by using only the A-weighted sound pressure level. In this paper, the characteristics of such sound were first investigated by a systematic approach and a new objective evaluation method for luxury sound-the luxury sound quality index--which was developed by the systematic combination of the seven major interior sound quality indexes based on path analysis. The seven major sounds inside a passenger car were selected by a basic investigation evaluated by the members of a luxury automotive club. Seven major interior sound quality indexes were developed by using sound metrics, which are the psychoacoustic parameters, and the multiple regression method used for the modeling of the correlation between objective and subjective evaluation.

The filtered-x LMS (FX-LMS) algorithm has been applied to the active noise control (ANC) system in an acoustic duct. This algorithm is designed based on the FIR (finite impulse response) filter, but it has a slow convergence problem because of a large number of zero coefficients. In order to improve the convergence performance, the step size of the LMS algorithm was modified from fixed to variable. However, this algorithm is still not suitable for the ANC system of a short acoustic duct since the reference signal is affected by the backward acoustic wave propagated from a secondary source. Therefore, the recursive filtered-u LMS algorithm (FU-LMS) based on infinite impulse response (IIR) is developed by considering the backward acoustic propagation. This algorithm, unfortunately, generally has a stability problem. The stability problem was improved by using an error smoothing filter.

This paper presents a practical real approach for predicting the interior noise caused by the vibration of the powertrain by using the hybrid transfer path analysis (TPA) method. The traditional TPA has been used for the identification of powertrain noise sources. However, with only experimental data for the identification of vibration and noise, it is difficult to determine the effects of modifications to the structure of a powertrain. In order to solve this problem, the vibration of the powertrain in a vehicle is numerically analyzed by using the finite element method (FEM). The vibration of other parts in a vehicle is investigated by using the experimental method based on vibro-acoustic transfer function (VATF) analysis. These two methods are combined for the prediction of interior noise caused by a powertrain.

While driving a passenger car, a driver can hear many sorts of sounds inside of the car. Among these sounds, booming and rumbling sounds are classified as the dominant sound characteristics of passenger cars. A sound quality index evaluating the quality of these two sounds objectively is therefore required and is developed by using an artificial neural network (ANN) in the present paper. Throughout this research, the booming sound and rumbling sound were found to effectively relate the loudness, sharpness and roughness. The booming sound qualities and rumbling sound qualities for interior sounds were subjectively evaluated by 21 persons for the target of the ANN. After the ANN was trained, the two outputs of this ANN were used for the booming index and rumbling index, respectively. These outputs were tested in the evaluation of the sound quality of the interior sounds which were measured inside of the sixteen passenger cars.

Rumbling sound is one of the most important sound qualities in a passenger car. In previous work, an objective evaluation method for rumbling sound was developed based on the principal component. In the present paper, the rumbling sound was found to effectively relate not only the loudness but also roughness. The last two subjective parameters are sound metrics in psychoacoustics. Principal rumble component, roughness and loudness were used as the sound metrics for the development of the rumbling index to evaluate the rumbling sound objectively. The relationship between rumbling index and these sound metrics is identified by an artificial neural network (ANN). Interior sounds of 14 passenger cars were measured, and 21 persons subjectively evaluated the rumbling sound qualities of these interior sounds. Throughout this research, it was found that the results of these evaluations and the output of a neural network have high correlation.

This paper presents practical work on the reduction of gear whine noise. In order to identify the source of the gear whine noise, transfer paths are searched and analyzed by operational deflection shape analysis and experimental modal analysis. It was found that gear whine noise has an air-borne noise path instead of structure-borne noise path. The main sources of air- borne noise were the two global modes caused by the resonance of an axle system. These modes created a vibro-acoustic noise problem. Vibro-acoustic noise can be reduced by controlling the vibration of the noise source. The vibration of noise source is controlled by the modification of structure to avoid the resonance or to reduce the excitation force. In the study, the excitation force of the axle system is attenuated by changing the tooth profile of the hypoid gear. The modification of the tooth profile yields a reduction of transmission error, which is correlated to the gear whine noise.

This paper presents a new measurement method for the measurement of the short reverberation time of a car compartment. The method is applied to the measurement of reverberation time of a compact size passenger car. The new method is based on the modified wavelet transform for the transient sound signal obtained inside of a car. The measurement error due to a small Bandwidth-Time product (BT) is reduced by using a new method.