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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.

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.

A need to develop a cooling method with high cooling performance like jet impingement is increased as high power of an inverter is required. Jet Impingement on the dimpled plate would increase thermal performance than that of flat plate. Many previous researchers have dealt with the multi jet impingement on flat plate and some results of the study on dimpled plate evaluate the effect on heat transfer coefficients on several limited cases, making it difficult to apply them to inverter designs. Therefore, in this paper, heat transfer performance, pressure drop, and robustness at micro-scale of jet impingement on the dimpled plate were investigated in detail and the correlations of each performance were proposed. Finally, the optimal design was presented. The cooling performance was influenced by the jet array and the effect of depth and width of the dimples.

Monitoring driver thermal stress is an integral step for developing an automated climate control function. In this experimental study, various physiological measures for driver’s thermal stress were tracked while intentionally by altering thermal conditions of the seat with a seat air conditioning system (ACS) in summer and a seat heating system (HS) in winter. It was aimed to determine reliable physiological measures for identifying the changes in thermal status induced by the two seat climate control systems. In the first experiment, twenty experienced drivers drove a comfortable sedan for 60 minutes on a real highway while varying the intensity of the seat ACS every 10 minutes to incur ‘hot’ – ‘cool’ – ‘hot’ – ‘cool’ thermal stress. In the second experiment, a new group of eighteen drivers drove the same highway for 30 minutes while increasing the intensity of seat HS to incur ‘cold’ to ‘warm’ thermal stress.

In the path following problem, a commercial vehicle has a delay of a hydraulic steering actuator and slow steering response accordingly. In addition, there are disturbances due to the harsh driving conditions of commercial vehicles. These disturbances may include uncertainties about actuator dynamic delay, modeling error and steering angle sensor offset. Designing a lateral controller with good performance that can overcome this problem is the key to successfully carrying out autonomous driving of commercial vehicles. Usually, it is difficult to consider disturbances with uncertainties in the geometric based control methods. Therefore, this paper proposed a lateral controller using feedback augmented disturbance observer for the commercial vehicle. First, a dynamics was modeled which can describe delay of the hydraulic actuator of the commercial vehicle. After that, a lateral controller was designed based on this dynamics model.

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.

Body-in-white plays a key role in protecting passengers in the event of collision between vehicles, and also endures external forces during cornering in a vehicle. Stiffness of body-in-white is the basic characteristic of a car body, and it is closely related to the full-vehicle-level performance such as body durability, ride and handling, etc. There have been many attempts to correlate body stiffness to full-vehicle-level performance, and studying the relationship between torsional body stiffness and durability has been the popular topic among others. In general, it is believed to be true that bodies with high torsional stiffness exhibit good durability performance, and in many cases this assumption seems to be verified. However, not all cases are true to this assumption. In this paper, relationship between torsional body stiffness and body durability has been closely studied.

This paper proposes a speed controller using a disturbance observer to regulate the speed of a commercial vehicles, and presents vehicle test results to evaluate the performance of the proposed controller. Most ADAS (Advanced Driver Assistance System) and automated driving systems need to reliably regulate the vehicle's speed under any circumstances. A conventional PID controller is commonly used to control the vehicle speed, but performance of it varies depending on changes in external conditions. Commercial vehicles are even more susceptible to these changes than passenger cars and more difficult to obtain an accurate plant model. Considering these features, a speed controller using a disturbance observer is designed for commercial vehicles. The proposed controller treats changes in external conditions as disturbances. The modeling uncertainty is also treated as a disturbance.

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.

Current developments in the automotive industry such as electrification and consistent lightweight construction increasingly enable the application of active control systems for the further reduction of noise in vehicles. As different stochastic noise sources such as rolling and wind noise as well as noise radiated by the ventilation system are becoming more noticeable and as passive measures for NVH optimization tend to be heavy and construction-space intensive, current research activities focus on active reduction of noise caused by the latter mentioned sources. This paper illustrates the development, implementation and experimental investigation of an active noise control system integrated into the ventilation duct system of a passenger car.

In this study, the preliminary validation method of the steering system is constructed and the objective is to satisfy the target performance in the conceptual design stage for minimizing the problems after the detailed design. The first consideration about steering system is how to extract the reliable steering effort for parking. The tire model commonly used in MBD(Multi-Body Dynamics) has limited ability to represent deformations under heavy loads. Therefore, it is necessary to study adequate tire model to simulate the behavior due to the large deformation and friction between the ground and the tire. The two approaches related with F tire model and mathematical model are used. The second is how to extract each link’s load in the conceptual design stage. Until now, each link’s load could be derived only by actual vehicle test, and a durability analysis was performed using only pre-settled RIG test conditions.

This paper investigates the sensitivity of stiffness of front and rear suspension systems on the structure-borne road noise inside a vehicle cabin. A flexible multi-body dynamics based approach is used to simulate the structural dynamics of suspension systems including rubber bushings, suspension arms, a subframe and a twist beam. This approach can accurately predict the force transfer to the trimmed body at each suspension mounting point up to a frequency range of 0 to 300 Hz, which is validated against a force measurement test using a suspension test rig. Predicted forces at each mounting point are converted to road noise inside the cabin by multiplying it with experimentally obtained noise transfer functions. All of the suspension components are modeled as flexible bodies using Craig-Bampton component mode synthesis method.

The mass producible broad-band ANC system for road noise is developed with fully digital control system. For this configuration, installation packages are intensively considered by minimizing size of the controller, simplifying wiring system and implementing virtual microphone techniques. Virtual microphone technique enables error microphone to be installed in remote position of driver’s ear, and therefore, increases installation degree of freedom significantly. To enhance noise control performance with the minimum latency, filter design of FxLMS algorithm is optimized while additional audio compensation techniques are applied to maintain audio performance of amplifier. The present ANC system is equipped to HMC (Hyundai Motor Company) new release of hydrogen driven vehicle, which is introduced in the technology promotion event in Pyeongchang Olympic 2018.

48V mild hybrid engine is one of major eco-friendly technology for global CO2 reduction policy. The 48V mild hybrid engine enables to operate torque boost, recuperation and ISG status by MHSG(Mild Hybrid Starter and Generator). The FEAD(Front End Auxiliary Drive) system is a very important role to transfer MHSG power to crankshaft at the mild hybrid engine. The conventional FEAD configuration is relatively simple because it transfers power from crankshaft to auxiliary drive components in one direction. But the FEAD configuration of 48V mild hybrid engine is not simple due to bidirectional power transmission between crankshaft and MHSG. For instance, in case of torque boost mode, the tight side of auxiliary belt is entry span of MHSG. On the contrary, the tight side of auxiliary belt is exit span of MHSG at recuperation mode.

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.

In case of cooling module rotated by belt, many sources (vehicle’s vibration, belt’s tension and thrust force by rotated fan) are acting on it. Because it is not easy to analyze them individually, there were no rig test modes for pre-validation while developing a new vehicle. In this study, we correlated the strain gauges signal to belt’s tension and fan’s thrust force, and measured acceleration of a vehicle and cooling module by driving a vehicle on the several test roads. In that case of measured acceleration data, we could analyze it by using PDF and construct the representative rig test modes considering vibrational fatigue characteristics by using the FDS. These modes can be utilized while developing a new vehicle without measuring anymore. Also, we could understand each load’s characteristics. It is confirmed that the factors affecting the fatigue were not only the vehicle’s vibration but also the belt’s installation tension.

The tire is the vital element in vehicle dynamics, as its contact patch transmits all forces and moments to the ground (accelerating, braking, cornering, rolling).Over the recent decades tire development for passenger cars has been continuously improved and optimized in order to achieve a good overall vehicle performance in R&H that is in balance with all other tire performances (Wear, Durability, NVH, RR, Miles). This general development process has to be suitable for various vehicle types from regular passenger cars over eco-friendly hybrid or electric vehicles to high performance sport cars. The balance between Ride and Handling performance is further adjusted to local customer preferences that are usually distinguished by markets (US, EU, Asia). The tire development process, which is embedded in the overall vehicle development, is usually realized in a mutual collaboration between OEM and tire supplier.

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.

Charge boosting strategy plays an essential role in improving the power density of diesel engines while meeting stringent emissions regulations. In downsized two-stage turbocharged engines, turbocharger matching is critical to achieve desired boost pressure while maintaining sufficiently fast transient response. A numerical simulation model is developed to evaluate the effect of two-stage turbocharger configurations on the perceived vehicle acceleration. The simulation model developed in GT-SUITE consists of engine, drivetrain, and vehicle dynamics sub-models. A model-based turbocharger control logic is developed in MATLAB using an analytical compressor model and a mean-value engine model. The components of the two-stage turbocharging system evaluated in this study include a variable geometry turbine in the high-pressure stage, a compressor bypass valve in the low-pressure stage and an electrically assisted turbocharger in the low-pressure stage.

One of the ways to improve the fuel efficiency of the HEV (Hybrid and Electric Vehicles) is to optimize automotive electric system. In order to achieve this, the LDC (Low voltage DC-DC Converter) variable voltage was controlled. Using the ADAS (Advanced Driver Assistance System) map, the charge-discharge behaviors of 12V lead-acid battery was predicted during driving so that, the battery could be charged efficiently. In this study, the feedback control system for 12V battery discharging was designed to compromise between the 12V battery SOC (State of Charge) and the driving conditions at different traffic points. In contrast to earlier approaches, this experimental result indicates that the LDC variable voltage control based on ADAS is able to reduce the LDC average output power by 17.1% therefore, increasing fuel efficiency and ensuring the durability of the 12V battery.