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In general, when a problem occurs in a component of powertrains, various phenomena appear, and abnormal noise is one of them. The service mechanics diagnose the noise through analysis by using their ears and equipment. However, depending on their experiences, analysis time and diagnostic accuracy vary greatly. To shorten the analysis time and improve the diagnostic accuracy, we have developed a technology to diagnose powertrain parts that cause abnormal noises. To create the best deep learning model for our diagnosis, we tried to collect many abnormal noises from various parts. The collected noise data was measured under idle and various operating conditions from our vehicles and test cells. This noise data is abnormal noises generated from engines, transmissions, drive system and PE (Power Electric) parts of eco-friendly vehicles. From the collected data, we distinguished good and bad data through detailed analysis in time and frequency domain.

This paper presents a tire slip-angle based speed control race driver model. In developing a chassis control system for enhancement of high-speed driving performance, analysis of the vehicle-driver interaction at limit handling is one of the main research issues. Thus, a driver model which represents driving characteristics in a racing situation is required to develop a chassis control system. Since a race driver drives a vehicle as fast as possible on a given racing line without losing control, the proposed driver model is developed to ensure a lateral stability. In racing situation, one of the reasons which cause the lateral instabilities is an excessive corner-entry speed. The lateral instability in that moment is hard to handle with only a steering control. To guarantee the lateral stability of the vehicle while maximizing a cornering speed, a desired speed is determined to retain a tire slip-angle that maximizes lateral tire forces without front tire saturation.

In this research, the influence of tire size and shape on sound radiation in the mid-frequency region was studied. First, the relationship between the structural wave propagation characteristics of a tire excited at one point and its sound radiation was identified by using FE and BE analyses. Then, by using that relationship, the effect of modifying a tire's aspect ratio, width and wheel diameter on its sound radiation between 300 Hz and 800 Hz was investigated. Finally, an optimization of the sound radiation was performed by modification of the tire structure and shape. It was found that most of a tire's structural vibration does not contribute to sound radiation. In particular, the effective radiation was found to occur at the frequencies where low wave number components of the longitudinal wave and the flexural wave first appear.

The automotive shock absorber has various functions in car performance. Particularly, it is a dominant tuning parameter to get good primary and secondary ride characteristics within 1-35Hz ranges in car development. Thus, understanding of characteristics of shock absorber in this frequency range is indispensable to both test and analysis engineers for an effective and systematic approach. In this study, tire is also investigated from the same point of view. Frequency dependent stiffness and damping coefficient are extracted by discrete sine swept test under constant velocity of 25, 50, 100mm/sec which represent typical road surface conditions[1]. The responses are analyzed on frequency domain and the basic theoretical background for this approach is introduced.

The mobility technique is used to analyze the transfer functions of road noise between the suspension and the body structure. In the previous analyses, the suspension system and the body structure are altogether modeled as subsystems in the noise transfer path. In this paper, the mobility between the suspension and the body structure is analyzed by the dynamic stiffness at the connecting points. The measured drive point acceleration FRF at the connecting point in the transfer path was used to estimate the contributions of subsystems. The vibration modes of tire, the acoustic noise of tire's interior cavity, the vibration modes of the car's interior room, and the vibrations of body structure and the chassis are also considered to analyze the coupling effects of the road noise. Analyzing the measured results, direction for modification of car components is suggested.

This paper proposes a reference steering wheel torque map and a torque tracking algorithm via steer-by-wire to achieve the targeted steering feel. The reference steering wheel torque map is designed using the measurement data of rack force and steering characteristic of a target performance of the vehicle at transition steering test. Since the target performance of the vehicle is only tested in nominal road condition, various road conditions such as disturbances and tire-road friction are not considered. Hence, the measurement data of the rack force that reflects the road conditions in the reference steering wheel torque map have been used. The rack force is the net force which consists of tire aligning moment, road friction force and normal force on the tire kingpin axis. A motor and a magnetorheological damper are used as actuators to generate the desired steering feel using the torque tracking algorithm.

Recently, customers have been demanding increased safety features in cars. Meanwhile, auto magazines now seek to publish the stopping distance. Further, the car development period has become shorter. For all these reasons, a precise estimation of the ABS stopping distance has grown important. A few steps that can be taken to improve accurate simulations of the ABS stopping distance are as follows: 1 Development of the tire hysteresis concept, its confirmation by test results, and then its application. 2 Free diagram development of the wheel combining ideal braking force, real braking force, and specific tire quality. 3 Modeling of HCU. 4 Application of ABS and EBD logic. 5 Application of booster characteristic to the section of early braking.

This paper presents the research related to the self-driving system that has been actively carried out recently. Previous studies have been limited to ensure the path following performance in linear and steady state-alike handling region with small lateral acceleration. However, in the high speed driving, the vehicle cornering response is extended to nonlinear region where tire grips are saturated. This requires a technology to create the driving path for minimum time maneuvering while grasping the tire grip limits of the vehicle in real time. The entire controller consists of three stages-hierarchy: The target motion is determined in the supervisor phase, and the target force to follow the target behavior is calculated in the upper stage controller. Finally, the lower stage controller calculates the actuator phase control input corresponding to the target force.

Automotive OEMs have introduced a new development paradigm, modular architecture development, to improve diversity quality and production efficiency. It needs solid fundamentals of system-based performance evaluation and development for each system level and single component level. When it comes to NVH development, it is challenging to realize the modular concept because noise and vibration should be transferred through various transfer path consisting of many parts and systems, which interact with each other. It is challenging for a single system of interest to be evaluated independently of the adjacent parts and environments. In this study, a new system-based development process for a vehicle suspension was investigated by applying blocked force theory and FRF-based dynamic substructuring. The objective is to determine the better dynamic stiffness distribution of many bushes installed in a suspension system in the frequency range corresponding to road noise.

Recently, increasing system complexity and various customer demands result in the need for highly efficient vehicle development processes. Once the brake torque is predicted accurately during the driving scenario in the earlier stage, it will be able to prevent the changing the vehicle or brake system design to satisfy the legal regulation and customer requirement. As brake torque performance target allocate brake pad friction coefficient level and characteristic, the accurate friction coefficient prediction should be preceded for accurate prediction for brake torque. Generally, the friction coefficient of the brake pad is known to vary nonlinearly depending on the physical properties of the disc and the pad, as well as the brake disc rotational speed, the disc temperature, and the hydraulic pressure. Furthermore, it varies depending on the driving scenario even when other conditions are the same. Therefore, it is necessary to apply new methods to solve these challenges.

The turning radius is designed with considering sufficient gap between front tires including snow chains and front parts around wheels (e.g. side member, wheel guard, and suspension control arms). Therefore, when we don't use the snow chain needed only in winter season, there remains gap between tires and elements around front wheels. Since there is much available space between the front tire and other parts around wheel without the snow chains, we strived to increase the steering angle of the front wheels for the smaller turning radius of the vehicle. In this paper, with the idea, we strived to develop the VRS (Variable Rack Stroke) system which is invented by Hyundai Motor Company for the first time around world and is capable of varying the minimum tuning radius of the vehicle.

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.

This study provides a tire puncture sealant including NR latex and acrylic emersion, which has a reduced viscosity at -40°C, and is also excellent storage stability at -40°C to 70°C, initial sealing performance. Also, this study provides device for sealing inflatable objects. 'One- Piece Tire Repair Kit' can reduce weight and operation steps.

In this research, the influence of tire force and moment (F&M) characteristics on vehicle on-center steering performance was analyzed and then how to improve vehicle on-center performance was studied through controlling tire structure design parameter, tread pattern shape and tread grip characteristics. First, the relationship between vehicle on-center steering performance and tire F&M characteristics was identified by comparing vehicle steering measurements and tire F&M measurements. It was found that key factor of tire related with on-center performance is aligning torque at lower slip angles. As the aligning torque at slip angle 1° increases, on-center feel is improved. Second, the influence of tire design parameters on tire aligning torque was studied through F&M finite element (FE) analysis and measurement. It was found that the aligning torque at lower slip angle increases as stiffness of the tread and sidewall decreases.

This paper describes a torque steer reduction process for a front-wheel drive car with a high torque engine at the initial stage of vehicle development. Literature reviews for the reduction process and vehicle integration tradeoffs among chassis components, driveline components, and loading condition are included. Drive shaft angle and its stiffness, differential gear stiffness, and power train mount, and vehicle weight distribution are mainly considered. In addition, wheel alignment data such as kingpin offset, kingpin inclination, camber angle, ride height, and dynamic tire radius are also discussed to solve the torque steer problem. This paper introduces an example solution to improve the torque steer during vehicle development stage. In that case, the vehicle parameters should be considered the factors to achieve many requirements. In spite of that restriction of alteration, the result of improvement became better than that of its competitor.

During the vehicle lifecycle, customers are able to directly perceive the outer panel stiffness of vehicles in various environmental conditions. The outer panel stiffness is an important factor for customers to perceive the robustness of the vehicle. In the real test of outer panel stiffness after prototype production, evaluators manually press the outer panel in advance to identify vulnerable areas to be tested and evaluate the performance only in those area. However, when developing the outer panel stiffness performance using FEA (Finite Element Analysis) before releasing the drawing, it is not possible to filter out these areas, so the entire outer panel must be evaluated. This requires a significant amount of computing resources and manpower. In this study, an approach utilizing artificial intelligence was proposed to streamline the outer panel stiffness analysis and improve development reliability.

After the COVID-19 pandemic, leisure activities and cultures have undergone significant transformations. Particularly, there has been an increased demand for outdoor camping. Consequently, the need for capabilities that allow vehicles to navigate not only paved roads but also unpaved and rugged terrains has arisen. In this study, we aim to address this demand by utilizing AI to introduce a 'Stuck Probability Estimation Algorithm' for vehicles on off-road. To estimate the 'Stuck Probability' of a vehicle, a mathematical model representing vehicle behavior is essential. The behavior of off-road driving vehicles can be characterized in two main aspects: firstly, the harshness of the terrain (how uneven and rugged it is), and secondly, the extent of wheel slip affecting the vehicle's traction.

Recently, regulations on automobile emission have been significantly strengthened to address climate change. The automobile industry is responding to these regulations by developing electric vehicles that use batteries and fuel-cells. Automobile emissions are environmentally harmful, especially in the case of vehicles equipped with high-temperature and high-pressure diesel engines using compression-ignition, the proportion of nitrogen oxides (NOx) emissions reaches as high as 85%. Additionally, air pollution caused by particulate matter (PM) is six to ten times higher compared to gasoline engines. Therefore, the electrification of commercial vehicles using diesel engines could potentially yield even greater environmental benefits. For commercial vehicles battery electric vehicles (BEVs) require a large number of batteries to secure a long driving range, which reduces their maximum payload capacity.

In this study, a novel selective matching logic for a wheel/tire is proposed, to decrease the vehicle driving vibration caused by wheel/tire non-uniformity. The new logic was validated through matching simulation/in-line matching evaluation. A theoretical radial force variation model was established by considering the theoretical model of the existing references and the wheel/tire assembly mechanism. The model was validated with ZF’s high-speed uniformity equipment, which is standard in the tire industry. The validity of the new matching logic was verified through matching simulation and mass production in-line evaluation. In conclusion, the novel logic presented herein was demonstrated to effectively decrease the radial force variation caused by the wheel/tire.

In recent years, the automotive industry has been making efforts to develop vehicles that satisfy customers’ emotions rather than malfunctions by improving the durability of vehicles. The durability and reliability of vehicles sold in the U.S. can be determined through the VDS (Vehicle Dependability Study) published by JD Power. The VDS is index which is the number of complaints per 100 units released by J.D. POWER in every year. It investigates customers who have used it for 3 years after purchasing a new car and consists of 177 specific problems grouped into 8 categories such as PT, ACEN, FCD, Exterior. The VDS-4 has been strengthened since the introduction of the new evaluation system VDS-5 in 2015. In order to improve the VDS index, it is important to gather various customer complaints such as internet data, warranty data, Enprecis data and clarify the problem and cause. Enprecis data is survey of customer complaints by on-line in terms of VDS.