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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.

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.

Platoon is a system that connects vehicles through vehicle-to-vehicle (V2V) communication technology to maintain a short distance between vehicles while driving on the road. To improve fuel efficiency, many automotive original equipment manufacturers (OEMs) are interested in developing and demonstrating real-world platoon system. However, it is hard for heavy duty trucks to develop this system due to the difficulty of maintaining the targeted intervehicle distance not only for fuel efficiency but also for safety in case of emergency braking. Because of this critical safety issue in the emergency situation, the platoon system for heavy duty trucks can be hardly demonstrated or tested in real vehicle environment. The relatively complex system and the slow response characteristic of commercial vehicles makes this even more difficult.

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 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.

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.

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.

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.

A semi-empirical index to evaluate the noise propensity of brake friction materials is introduced. The noise propensity index (NPI) is based on the ratio of surface and matrix stiffness of the friction material, fraction of high-pressure contact plateaus on the sliding surface, and standard deviation of the surface stiffness of the friction material that affect the amplitude and frequency of the stick-slip oscillation. The correlation between noise occurrence and NPI was examined using various brake linings for commercial vehicles. The results obtained from reduced-scale noise dynamometer and vehicle tests indicated that NPI is well correlated with noise propensity. The analysis of the stick-slip profiles also indicated that the surface property affects the amplitude of friction oscillation, while the mechanical property of the friction material influences the propagation of friction oscillation after the onset of vibration.

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.

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.

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.

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.

This paper presents an industrial application of the Analytical Target Cascading (ATC) methodology to the optimal design of commercial vehicle steering and suspension system. This is a pilot study about the suspension and steering design of a semi medium bus, whose objective is to develop and introduce an ATC methodology to an automobile development process. In the conventional process, it is difficult not only to find design variables which meet the target of Ride and Handling (R&H) performance using a detailed full car model, but also to figure out the interrelation between the vehicle and its subsystems. In this study, ATC methodology is used in order to obtain the optimal values such as geometric characteristics satisfying both the vehicle's R&H target and the subsystem (suspension and steering system) 's target.

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.

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.