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A brake is a mechanical device that inhibits the motion by absorbing energy from a moving system. It is used for slowing or stopping a moving vehicle, wheel, axle, or to prevent its motion, most often accomplished by friction energy. Commonly, most brakes use friction between two surfaces pressed together to convert the kinetic energy of the moving object into heat, though other methods of energy conversion may be employed. If braking is repeated or sustained in high load or high-speed conditions, the motion will be unstable and can lead to a loss of stopping power because the disc capability for braking is not enough. These phenomena are generally defined as brake fading. Brake fade is caused by an overheating brake system. This paper describes the thermal modeling and process to predict the disk temperature under a condition which causes the fade characteristics.

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.

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 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.

IQS score (hard to open/close) is a major factor in determining automotive door closing performance. There are several functions that automotive side doors must fulfill: isolation from snow/ rain/ noise/ dust/ high temperature, wind noise, and opening/closing functions. This paper focuses on side door Opening/Closing, which is not only the primary function but also the first operation that all customers experience when car shopping. As the subjective demands of customers have increased and their level of sophistication has grown, the ergonomics of automotive side door functions has become a critical issue for both designer and customer. The side door area does not generally have specifications because door operability totally relies on each customer's senses and there are no parameters to be measured by test/experimental devices. So the IQS score could become the standard for evaluating a door's difficulty of opening and closing.

A KIA Soul was instrumented to measure the relative velocity (magnitude and yaw angle) at the front of the vehicle and in-cabin sound at a location close to the side glass near the A-pillar vortex impingement. Tests were conducted at a proving ground under a range of conditions from low wind conditions (~3 m/s) to moderate (7-8 m/s) wind speeds. For any given set of atmospheric conditions the velocity and sound data at any given position on the proving ground were noted to be very repeatable, indicating that the local wakes dominated the "turbulent" velocity field. Testing was also conducted in an aeroacoustic wind tunnel in smooth flow and with a number of novel turbulence generating methods. The resulting sounds were analyzed to study the modulation at frequencies likely to result in fluctuation strength type noise.

Driveshafts are one of the most important components in power-train system in vehicle as it transfer torque generated from engine to wheels in high speeds. As a driveshaft is in rotating condition vibration problems can be observed by resonance or external force. The generated vibration problems in vehicles cause discomfort to drivers whenever they are driving. To solve these problems, there have been many attempts to control such generated vibration in vehicle. In this study, vibration control system for driveshaft has been proposed to reduce the generated vibration. The smart damper for the system is designed considering to be implemented in driveshaft with quick response and a compact size. The damper is consists of electromagnets so it can response relatively quickly compared to other damping system. When a driveshaft reaches to its natural frequency, vibration control system with the damper is activated to minimize the vibration as it shifts its natural frequency region.

It is common knowledge that body attachment stiffness is an important factor of road noise performance. Thus, a high stiffness of body attachments is required, and determining their optimized stiffness and structure is necessary. Therefore, a method for improving body attachment stiffness and validating the relationship between stiffness and road noise through CAE and experimental trials was tested. Furthermore, a guideline for optimizing body structure for road noise performance was suggested.

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.

A technology was developed to recognize and predict the urgent degradation of the state of the rotating equipment installed in Hyundai-Kia factories. It is also being applied to activities to prevent equipment failures by establishing a monitoring system using this technology. Vibration data and artificial intelligence (AI) algorithms were used to predict conditions. It was developed and installed so that maintenance engineers could predict failures in advance. This is to improve preventive diagnosis of thousands of rotating equipment in the factory. And it has the advantage of allowing a small number of engineers to monitor exponentially increasing number of equipment. Vibration data including trends and alarms were collected along with the production schedule, and wavelet-based preprocessing DB9 (Daubechies 9) was performed to remove noise such as outliers. Two different AI algorithm models were developed to recognize and predict changes in equipment state.

This paper presents a stability monitoring algorithm with a combined slip tire model for maximized cornering speed of high-speed autonomous driving. It is crucial to utilize the maximum tire force with maintaining a grip driving condition in cornering situations. The model-free cruise controller has been designed to track the desired acceleration. The lateral motion has been regulated by the sliding mode controller formulated with the center of percussion. The controllers are suitable for minimizing the behavior errors. However, the high-level algorithm is necessary to check whether the intended motion is inside of the limit boundaries. In extreme diving conditions, the maximum tire force is limited by physical constraints. A combined slip tire model has been applied to monitor vehicle stability. In previous studies, vehicle stability was evaluated only by vehicle acceleration.

As powertrain performance of vehicle improves, brake load is gradually increasing. But it is not easy to increase brake size due to increment of cost and weight despite judder and fade problems are worried in field. Cooling-duct which provides additional forced convection to cool front brake is being considered instead of increasing brake size. However, cooling-duct causes loss of aerodynamic that increases drag coefficient of vehicle. This paper covers the optimization of brake cooling system including cooling-duct, deflector on suspension parts to direct air into front brake and dust cover so that minimize aerodynamic loss and maximize brake cooling performance. The optimal solution had been derived from thermal and aerodynamic simulation with CFD and verified through experimental test with vehicle.

In CVT, it is essential to optimize Clamping Force in Pulley to improve fuel efficiency. Clamping force in pulley is shaft force to control primary pulley and secondary pulley. It is determined by pulley ratio, input engine torque in CVT and safety factor for protecting belt slip. It is difficult to calculate correct clamping force and detect belt slip. Generally speaking, CVT has a tendency to have excessive Safety factor to prevent belt slip. This excessive safety factor in clamping force leads to lower fuel efficiency. In order to find an optimal clamping force, ‘the minimum clamping force’ which will not induce belt slip should be determined even during decreasing clamping force. Furthermore, clamping force should be maintained near the ‘minimum clamping force’. For this, following logics was developed First, the logic to calculate first safety ratio of belt, Second, the logic to detect belt slip state, Third, the logic to calculate the optimal clamping force.

In the automotive sector, the structure borne noise generated by the engine and road-tire interactions is a major source of noise inside the passenger cavity. In order to increase the global acoustic comfort, predictive simulation models must be available in the design phase. The acoustic trims have a major impact on the noise level inside the car cavity. Although several publications for this kind of simulations can be found, an extensive correlation study with measurement is needed, in order to validate the modeling approaches. In this article, a detailed correlation study for a complete car is performed. The acoustic trim package of the measured car includes all acoustic trims, such as carpet, headliner, seats and firewall covers. The simulation methodology relies on the influence of the acoustic trim package on the car structure and acoustic cavities. The challenge lies in the definition of an efficient and accurate framework for acoustic trimmed bodies.

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.

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.

This paper describes a hierarchical motion planning and control framework for overtaking maneuvers under racing circumstances. Unlike urban or highway autonomous driving conditions, race track driving requires longer prediction and planning horizons in order to respond to upcoming corners at high speed. In addition, the subject vehicle should determine the optimal action among possible driving modes when opponent vehicles are present. In order to meet these requirements and secure real time performance, a hierarchical architecture for decision making, motion planning, and control for an autonomous racing vehicle is proposed. The supervisor determines whether the subject vehicle should stay behind the preceding vehicle or overtake, and its direction when overtaking. Next, a high level trajectory planner generates the desired path and velocity profile in a receding horizon fashion.

Over the last decade the electrified powertrain has been expanded due to strict fuel efficiency regulations, which leads to the development of various powertrain systems. It is recent trend to improve the overall system efficiency in which various power sources such as ICE and motor are combined with a simple gearbox. Accordingly, it is becoming indispensable to analyze the efficiency of the entire system from the initial stage of system development. In this study, a generalized numerical model is developed to predict the loss of gearbox under various power sources and power flows. This numerical model newly applied generalized equations for additional various power transmissions, including the previously verified power loss equation of gearbox components. In addition, for a reasonable and objective efficiency comparison between gearboxes, the optimal operating points are calculated in consideration of the overall powertrain system efficiency covering the total vehicle load.