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As automotive technology has been developed, gear whine has become a prominent contributor for cabin noise as the masking has been decreased. Whine is not the loudest source, but it is of high tonal noise which is often highly unpleasant. The gear noise originates at gear mesh. Transmission Error acts as an excitation source and these vibrations pass through gears, shafts and bearings to the housing which vibrates to produce noise on surrounding air. As microgeometry optimization target to reduce the fundamental excitation source of the noise, it has been favored method to tackle gear whine noise, especially for manual transmission. However, practicality of microgeometry optimization for the planetary gear system has been still in question, because of complex system structure and interaction among multi mesh gear sets make it hard to predict and even harder to improve. In this paper, successful case of whine noise improvement by microgeometry is presented.

NVH analysis based on numerical simulations before actual test vehicle is available becomes common process in the automotive industry. Furthermore, the latest work scope is extending even to conceptual study in the very early design stage, beyond traditional numerical simulations simply using 3-D CAD data. In case when reasonable information is provided at this very early vehicle development stage, a better decision on the design concept would be possible, and subsequent design process can be carried out in more efficient manner. The core of this trend is that it allows us to predict vehicle performance at the conceptual design stage without 3-D CAD data, and then, with this prediction, to suggest meaningful design directions for next stage. From this point of view, FRF-Based Substructuring (FBS) methodology has potential to be used as an appropriate tool for this purpose.

A physics-based model for SCR (Selective Catalytic Reduction) was developed based on five independent SGB (Synthetic Gas Bench) tests. There are NH3 adsorption & desorption test, NO oxidation test, NH3 oxidation test, SCR reaction (NOx & NH3) test and SV (Space Velocity) test. To validate the accuracy of SCR model’s prediction, transient reactor tests were conducted at four different input conditions. A newly developed SCR model showed more than 90% prediction accuracy in transient test conditions in view of cumulative NOx. Validation of SCR model was conducted on 1.6L light duty diesel vehicle in the WLTC (Worldwide Harmonized Light vehicles Test Cycle). Based upon this SCR model, vehicle level SCR calibrations used for urea dosing control were made and validated in the emission test cycles like WLTC.

Electric Power Steering (EPS) needs to meet both functional and stability requirements, it plays significant role in controlling vehicle motion. In the meantime, customers emphasizes natural steering feel which can reflect vehicle motion and road surface information while isolate unwanted external disturbances. In general, conventional EPS control algorithms exert assist torque according to driver torque measured from torque sensor, while maintaining stability using stabilizing compensator. However, there exist significant trade-off between steering feel and stability, because the performances of assist torque control and stabilizing compensator are strongly coupled. In this paper a torque feedback control algorithm for EPS system is proposed in order to overcome the trade-off, and to achieve more natural, robust steering feel.

This paper proposes a modeling technique which is able to not only reliably and easily represent the hysteretic characteristics but also analyze the dynamic stress of a taper leaf spring. The flexible multi-body dynamic model of the taper leaf spring is developed by interfacing the finite element model and computation model of the taper leaf spring. Rigid dummy parts are attached at the places where a finite element leaf model is in contact with an adjacent one in order to apply contact model. Friction is defined in the contact model to represent the hysteretic phenomenon of the taper leaf spring. The test of the taper leaf spring is conducted for the validation of the reliability of the flexible multi-body dynamic model of the taper leaf spring developed in this paper. The test is started at an unloaded state with the excitation amplitude of 1∼2mm/sec and frequency of 132mm. First, the simulation is conducted with the same condition as the test.

This paper describes a reference steering feel tracking algorithm for Electric-Power-Steering (EPS) system. Development of the EPS system with intended steering feel has been time-consuming procedure, because the feedforward map-based method has been applied to the conventional EPS system. However, in this study, a three-dimensional reference steering feel surface, which is determined from current vehicle states, is proposed. In order to track the proposed reference steering feel surface, sliding mode approach is applied to second-order steering dynamics model considering a coulomb friction model. An adaptive technique is utilized for robustness against uncertainties. In order to validate the proposed EPS control algorithm, hardware-in-the-loop simulation (HILS) has been conducted with respect to a typical steering test. It is shown that the reference steering feel is realized well by the proposed EPS control algorithm.

Shudder vibration of a hydraulic power steering system during parking maneuver was studied with numerical and experimental methods. To quantify vibration performance of the system and recognize important stimuli for drivers, a shudder metric was derived by correlation between objective measurements and subjective ratings. A CAE model for steering wheel vibration analysis was developed and compared with measured data. In order to describe steering input dependency of shudder, a new dynamic friction modeling method, in which the magnitude of effective damping is determined by average velocity, was proposed. The developed model was validated using the measured steering wheel acceleration and the pressure change at inlet of the steering gear box. It was shown that the developed model successfully describes major modes by comparing the calculated FRF of the hydraulic system with measured one from the hydraulic excitation test.

In commercial vehicles, the exhaust brake assists the service brake to share the excess load and is used as an auxiliary brake to assist with the safety of the engine and the service brake on downhill slopes. To meet the customer's demand for auxiliary brakes, the specification of auxiliary brakes must be determined at the product proposal stage. In this study, performance design was conducted to derive exhaust brake specifications that fit the customer's requirements. For performance design, a system model was created and key design factors with high performance contribution were extracted. Optimal specifications were derived from parameter studies for key design factors. Additionally, performance analysis was performed with design tolerances using the performance design model. Performance was verified through actual vehicle evaluation and design specifications were confirmed.

Usually, fibrous materials with porosity can dissipate the energy of the sound wave penetrating them, so can be the useful sound absorbing materials to reduce the noise in the vehicle. The fibrous materials have been used for the various types of automotive components as the sound absorbing materials, which can be placed close to the noise source, in the noise paths and near the receiver such as passengers. Although all materials can absorb a little amount of sound energy, the term “acoustical material” has been primarily applied to those materials that can provide the higher sound absorption performance above the ordinary levels. One of the examples of fibrous acoustic materials for automotive components is the sound absorbing felt composed of the fibers which have the several characteristics such as the material type, the cross-sectional shape and the fiber density (can be expressed as denier) related to the sound absorbing performance.

Road friction estimation algorithms had been studied for many years because it is very important factor for safety control and fuel efficiency of vehicle. But traditional solutions are hard to adapt in automotive industry because their performance is not sufficient enough and expensive to implement. Therefore, this paper proposes a road friction estimation algorithm based on a trained artificial neural-network which is low cost and robust. The suggested method doesn’t need expensive additional sensors such as optical or lidar sensor, also it shows better performance in real car environment compared to other algorithms based on vehicle dynamics. In this paper, we would describe this algorithm in detail and analyze the test results evaluated in real road conditions.

Tuning the size and position of the cooling water holes in the head gasket during engine cooling system development is generally positioned at the final stage of the cooling system hardware design. Until now, the gasket hole tuning operation was dependent on the case study through repetitive CFD analysis. In this process, there was a difference in the optimization level by know-how and expertise of the person in charge. In this study, a gasket hole tuning technique was developed using optimization algorithms to improve the level of optimization. First, select factors and perform screening using the DOE(Design Of Experiments) method, and then find the optimal gasket hole size and arrangement through the optimal design process based on the results of the CFD analysis planned by DOE.

Broadband active noise control algorithms require high-performance so multi-channel control to ensure high performance, which results in very high computational power and expensive DSP. When the control filter update part need a huge computational power of the algorithm is separated and calculated by the server, it is possible to reduce cost by using a low-cost DSP in a local vehicle, and a performance improvement algorithm requiring a high computational power can be applied to the server. In order to achieve the above goal, this study analyzed the maximum delay time when communication speed is low and studied response measures to ensure data integrity at the receiving location considering situations where communication speed delay and data errors occur.

The reduction of intake noise is a very important factor in controlling the interior noise levels of vehicles, particularly at low and major engine operating speeds. A vehicle intake system generally consists of air cleaner box, hose, duct, and filter element. Also, resonators and porous duct are included, being used to reduce intake noise. For more accurate estimation of the transmission loss (TL), it seems important to develop a CAE model that accurately describes this system. In this paper, simple methods, which can consider the effects of filter element and vibro-acoustic coupling, are suggested which could remarkably improve estimation accuracy of the TL. The filter element is assumed as equivalent semi-rigid porous materials characterized by the flow resistivity defined by the pressure drop, velocity, and thickness.

In the early stages of vehicle development, it is critical to establish performance goals for the major systems. The fundamental modes of body and chassis frames are typically assessed using FE models that are discretized using shell elements. However, the use of the shell-based FE method is problematic in terms of fast analysis and quick decision-making, especially during the concept phase of a vehicle design because it takes much time and effort for detailed modeling. To overcome this weakness, a one-dimensional (1D) method based on beam elements has been extensively studied over several decades, but it was not successful because of low accuracy for thin-walled beam structures. This investigation proposes a 1D method based on thin-walled beam theory with comparable accuracy to shell models. Most body pillars and chassis frame members are composed of thin-walled beam structures because of the high stiffness-to-mass ratio of thin-walled cross sections.

When customers use a tailgate (or trunk), some systems such as power tailgate and smart tailgate have been introduced and implemented for improving convenience. However, they still have some problems in some use cases. Some people have to search for the outside button to open the tailgate, or they should take out the key and push a button. In some cases, they should move their leg or wait a few seconds which makes some people feel that it is a long time. In addition, they have to push the small button which is located on the inner trim in order to close the tailgate. This paper proposes a new tailgate control technology and systems based on acoustic patterns in order to solve some inconvenience. An acoustic user interaction (AUI) is a technology which responds to human’s rubbing and tapping on a specific part analyzing the acoustic patterns. The AUI has been recently spotlighted in the automotive industry as well as home appliances, mobile devices, musical instruments, etc.

In this paper, an application process is studied at which the insertion loss (IL) test data of sound insulating parts or noise control treatments are utilized for the sound transmission loss (STL) simulation of the trimmed dash structure. The considered sound barrier assemblies were composed of a felt layer, a mass layer, and a decoupler layer. Flat samples of sound barrier assemblies with several different thicknesses were prepared, and ILs of them were measured by using a sound transmission loss facility. Flat samples were assumed to have mass-spring-mass resonance frequencies. The mass was set as the area mass of the sound barrier layer of the felt layer and the mass layer. The spring constant of the decoupler layer was assumed as the multiplication of that of an air spring and a spring correction factor.

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.

The high-frequency whining noise produced by motors in modern electric vehicles causes a significant issue, leading to annoyance among passengers. This noise becomes even more noticeable due to the quiet nature of electric vehicles, which lack other noises to mask the high-frequency whining noise. To improve the noise caused by motors, it is essential to optimize various motor design parameters. However, this task requires expert knowledge and a considerable time investment. In this study, we explored the application of artificial intelligence to optimize the NVH performance of motors during the design phase. Firstly, we selected and modeled three benchmark motor types using Motor-CAD. Machine learning models were trained using Design of Experiment methods to simulate batch runs of Motor-CAD inputs and outputs.

It is an important factor in electric vehicles to show customers how much they can drive with the energy of the remaining battery. If the remaining mileage is not accurate, electric vehicle drivers will have no choice but have to feel anxious about the mileage. Additionally, the potential customers have range anxiety when they consider Electric Vehicles. If the remaining mileage to drive is wrong, drivers may not be able to get to the charging station and may not be able to drive because the battery runs out. It is important to show the remaining available driving range exactly for drivers. The previous study proposed an advanced model by predicting the remaining mileage based on actual driving data and based on reflecting the pattern of customers who drive regularly. The Bayesian linear regression model was right model in previous study.

Aerodynamic simulation results are most of the time compared to wind tunnel results. It is too often simplistically believed that it suffice to take the CAD geometry of a car, prepare and run a CFD simulation to obtain results that should be comparable. With the industry requesting accuracies of a few drag counts when comparing CFD to wind tunnel results, a careful analysis of the element susceptible of creating a difference in the results is in order. In this project a detailed 1:4 scale model of the Hyundai Genesis was tested in the model wind tunnel of the FKFS. Five different underbody panel configurations of the car were tested going from a fully paneled car to a car without panels. The impact of the moving versus static ground was also tested, providing over all ten different experimental results for this car model.