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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.

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.

There are some problems “windows fog up a lot” for ventilation system. We have Test Development Procedure to prevent the fog problems. But, Many fog problems occurred in the cars that we made. So in this paper, new ventilation system is needed and developed. The Smart Ventilation System automatically controls indoor air quality even though the blower motor is off. There are two sensors that is used for AutoDefogSensor system and CO2 CONTROL system.. The sensor is on when blower motor and heater control is off. We use these signals and make new ventilation logics. We evaluate this system in chamber & '13 winter test in USA.

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 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.

The purpose of this study is to develop a dynamic model that can accurately predict the motion of the door handle and counterweight during side impact crash tests. The door locking system, mainly composed of the door outside handle and door latch, is theoretically modeled, and it is assumed that the door outer panel can rotate and translate in all three directions during a side impact crash. Additionally, the numerical results are compared with real crash video footage, and satisfactory qualitative agreement is found. Finally, the simplified test rig that efficiently reflects the real crash test is introduced, and its operation is analyzed.

In order to utilize in-vehicle systems efficiently, many vehicles are becoming equipped with integrated controls near the center fascia or the control box. However, the placement of these control systems can cause safety issues and risks due to visual distractions. In this study, we proposed a new integrated touch screen on the steering wheel. For this experiment, a control system was placed on the steering wheel or the center fascia. 15 participants were required to drive while utilizing vent and navigation control tasks regarding four different locations. Three of these locations were based on the steering wheel (center, upper right, lower right) and one location on the center fascia. Afterwards, the task completion time and visual distraction rate of the different locations were measured and compared. The results showed that a touch screen placed on the upper right section of the steering wheel had better performance and lower user discomfort.

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.

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.

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.

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.

Reductions in powertrain noise have led to an increased proportion of road noise, prompting various studies aimed at mitigating it. Road excitation primarily traverses through the vehicle suspension system, necessitating careful optimization of the characteristics of bushings at connection points. However, optimizing at the vehicle assembly stage is both time-consuming and costly. Therefore, it is essential to proceed with optimization at the subsystem level using appropriate objective functions. In this study, the blocked force and energy-based index derived from complex power were used to optimize the NVH performance. Calculating the complex power in each bushing enables computing the power flow, thereby providing a basis for evaluating the NVH performance. Through stiffness injection, the frequency response functions (FRF) of the system can be predicted according to arbitrary changes in the bushing stiffness.

In this study, a co-operative regenerative braking control algorithm was developed for an electric vehicle (EV) equipped with an electronic wedge brake (EWB) for its front wheels and an electronic mechanical brake (EMB) for its rear wheels. The co-operative regenerative braking control algorithm was designed considering the road friction characteristic to increase the recuperation energy while avoiding wheel lock. A powertrain model of an EV composed of a motor, and batteries and a MATLAB model of the control algorithm were also developed. They were linked to the CarSim model of the vehicle under study to develop an EV simulator. The EMB and EWB were modeled with an actuator, screw, and wedge to develop an EMB and EWB simulator. A co-simulator for an EV equipped with an EWB for the front wheels and an EMB for the rear wheels was fabricated, composed of the EV and the EMB and EWB simulator.

The windshield is an integral part of almost every modern passenger car. Combined with current developments in the automotive industry such as electrification and the integration of lightweight material systems, the reduction of interior noise caused by stochastic and transient wind excitation is deemed to be an increasing challenge for future NVH measures. Active control systems have proven to be a viable alternative compared to traditional passive NVH measures in different areas. However, for windshield actuation there are neither comparative studies nor actually established actuation concepts available to the automotive industry. This paper illustrates a comparative conceptual study on windshield actuation for the active control of wind noise in a passenger car. Making use of an experimental modal analysis of the windshield installed in a medium-sized vehicle, a reduced order numerical simulation model is derived.

This paper proposes a torque tracking algorithm via steer by wire to achieve the target steering feel and proposed a modified friction model to obtain return-ability. A three dimensional reference steering wheel torque map is designed using the measurement data of the steering characteristics of the target vehicle at a transition test and a weave test. In order to track the reference steering wheel torque, a sliding mode control is used in the tracking algorithm. In addition, to achieve return-ability, the modified friction model for steer by wire is used instead of the friction model defined in the reference steering wheel torque map. The modified friction model is composed of various models according to the angular velocity. The angular velocity and the angular acceleration used in the control algorithm are estimated using a kalman filter.

The fuel economy of a vehicle can be improved by recuperating the kinetic energy when the vehicle is decelerated. However, if there is no electrical traction component, the recuperated energy can be used only by the other electrical systems of the vehicle. Thus, the fuel economy improvement can be maximized by balancing the recuperated energy and the consumed energy. Also, suitable alternator and battery management is required to maximize the fuel economy. This paper describes a design optimization process of the alternator and battery system equipped with recuperation control algorithms for a mid-sized sedan based on the fuel economy and system cost. A vehicle model using AVL Cruise is developed for cycle simulations and validated with experimental data. The validated model is used for the parametric study and design optimization of the alternator and battery systems with single and dual energy storage.

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.

Accelerated simulation of vehicle corrosion in a controlled environment not only involves large chambers for actual vehicle tests, but also requires careful consideration of interactions between various parameters given a short time period within which the test is bounded. A new corrosion durability test mode reproducing various field conditions using salt spray, climatic, sunlight simulation and cold chambers has been developed. Verification of the test mode is carried out using four actual vehicle corrosion tests correlated against used cars of Nort h America and Northern Europe. The process of new corrosion test mode is discussed along with the characteristics of the test chambers.

The Rollover CAE model is developed for Rollover sensing algorithm in this paper. By using suggested CAE model, it is possible to make sensing data of rollover test matrix and these data can be used for calibration of rollover sensing algorithm. Developed vehicle model consists of three parts: a vehicle parts, an occupant parts and a ground boundary conditions. The vehicle parts include detailed suspension model and FE structure model. The occupant parts include ATD (anthropomorphic test device) male dummy and restraint systems: Curtain Airbag and Seat-Belt. We find analytical value of the suspension model through correlation with vehicle drop test, simulate this model under the conditions of untripped (Embankment, Corkscrew) and tripped (Curb-Trip, Soil-Trip) rollover scenarios. Comparison of the simulation and experimental data shows that the simulation results of suggested CAE model can be substituted for the experimental ones in calibration of rollover sensing algorithm.