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A Light Detection And Ranging (LiDAR) is now becoming an essential sensor for an autonomous vehicle. The LiDAR provides the surrounding environment information of the vehicle in the form of a point cloud. A decision-making system of the autonomous car is able to determine a safe and comfort maneuver by utilizing the detected LiDAR point cloud. The LiDAR points on the cloud are classified as dynamic or static class depending on the movement of the object being detected. If the movement class (dynamic or static) of detected points can be provided by LiDAR, the decision-making system is able to plan the appropriate motion of the autonomous vehicle according to the movement of the object. This paper proposes a real-time process to segment the motion states of LiDAR points. The basic principle of the classification algorithm is to classify the point-wise movement of a target point cloud through the other point clouds and sensor poses.

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.

In CRDI diesel engines, the piezo injector is gradually replacing the solenoid injector due to the quick response of the actuator. Operating performance of the injectors in the CRDI diesel engine has an influence on engine emissions. Therefore, accurate injector control is one of the most important parts of the CRDI engine control. The objective of this paper is the development of a piezo injector driver for CRDI diesel engines. Electrical characteristics of the piezo injector were analyzed. A control strategy for charging and discharging the actuator are proposed. The developed injector driver is verified by experiments under various fuel pressures, injection durations and driving circuit voltages.

This paper presents a model based sensor fault detection and isolation algorithm for the vertical acceleration sensors of the Continuous Damping Control (CDC) system, installed on the sprung mass. Since sensor faults of CDC system have a critical influence on the ride performance as well as the vehicle stability, the sensor fault detection algorithm must be implemented into the overall CDC algorithm. In this paper, each vertical acceleration sensor installed on the sprung mass (two in the front corners and one in the rear) separately estimates the vertical acceleration of the center of gravity of the sprung mass. Then, the sensor fault is detected by cross-checking all three vertical acceleration estimates independently obtained by the each vertical acceleration sensor.

The paper presents a new offset compensation method of a yaw rate sensor and a lateral acceleration sensor. It is necessary to compensate the offsets of the analog sensors, such as the yaw rate sensor and the lateral acceleration sensor, to acquire accurate signals. This paper proposes two different offset compensation algorithms, the sequential compensation method and the model based compensation method. Both algorithms are combined with the algorithm map depending on the vehicle driving status. The proposed algorithm is verified by the computer simulations.

Lane keeping assistant system (LKAS) is expected to reduce the driver workload with assisting the driver during driving and is regarded as a promising active safety system. For the proposed LKAS which requires cooperative driving between driver and the assistance system, a Model Based Predictive Controller (MBPC) is proposed to minimize the effect of system overshoot caused by the time delay from the vision-based lane detection system. In order to validate the proposed LKAS controller, a HIL (Hardware In the Loop) simulator is built using steering mechanism, single camera, torque motor, sensors, etc. The performance of the proposed system is demonstrated in various roadways.

This paper describes an automated path following system using vision sensor. Lateral control law for path following is especially underlined which is developed by using the backstepping control design methodology. To establish the proposed control system, the lateral offset to the reference path, the heading angle of vehicle relative to tangent line to the path, and path curvature are required. Those inputs to the controller have been calculated through Kalman filter which is frequently adopted for the purpose. The lane mark detection has been achieved in an ECU (Electric Control Unit) platform with vision sensor. The yaw rate and side-slip angle also needed in the controller are estimated by Kalman estimator. To show the performance of the proposed controller under different speeds, experiment has been conducted on a proving ground having straight and curve sections with the curvature of about 260m.

The current sensor for motor control is one of the main components in inverters for eco-friendly vehicles. Recently, as the higher performance of torque control has become required, the current sensor measurement error and accuracy of motor controls have become more significant. Since the response time of the sensor affects the motor output power, the response delay of the sensor causes measurement errors of the current. Accordingly, the voltage vector changes, and a motor output power deviation occurs. In the case of the large response delay of the sensor, as motor speed increases, then difference between motoring and generating output power becomes larger and larger. This results in the deterioration of power performance in high-speed operation. The deviation of the voltage vector magnitude is the main cause of motor output power deviation and imbalance through the simulation.

In recent years, the emerging technology competitions in automotive industry are improving engine efficiency and electronizing for coping with stringent fuel-economy regulations. However, fuel-economy technologies such as engine down-sizing and numerous electronic parts entrust burden plastic materials acing as mainly electric insulation and housing to have to be higher performance, especially temperature endurance. Engineering plastics (EPs) have critical limitations in terms of degradation by heat. Heat-resisting additives in EP are generally used to be anti-degradation as activating non-radical decomposition of peroxide. However, it could not be effective way to impede the degradation in long term heat aging over 1,000 hours at high temperature above 180 °C. In this study, we suggested the new solution called ‘shield effect’ that is purposeful oxidation at the surface and local crystallization of EP to stop prevent penetrating oxygen to inside of that.

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.

A controller is introduced for air-to-fuel ratio management, and the control scheme is based on the feedback error learning method. The controller consists of neural networks with linear feedback controller. The neural networks are radial basis function network (RBFN) that are trained by using the feedback error learning method, and the air-to-fuel ratio is measured from the wide-band oxygen sensor. Because the RBFNs are trained by online manner, the controller has adaptation capability, accordingly do not require the calibration effort. The performance of the controller is examined through experiments in transient operation with the engine-dynamometer.

As autonomous driving vehicles are developed, automotive makers start focusing on implementing new door types, such as a falcon wing door or a B-pillarless dual sliding door, which could be one of the best-selling points. To make these doors electrically operate, applying advanced sensors like a RADAR or an Ultrasonic sensor is almost mandatory. Without these sensors, the door could be easily damaged or the customers could be seriously injured. Due to physical limitation, however, every sensor has a noise in nearby area and has a specification of the minimum detection range, which causes us not to be able to precisely detect the object in close area. If the controller cannot detect the precise distance of the object, the door could malfunction, since it could misidentify the obstacles. In this paper, we propose a method to reduce the minimum detection range by applying a prior estimation scheme.

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.

The woofer in a car should be large to cover the low frequencies, so it is heavy and needs an ample space to be installed in a passenger car. The geometry of the woofer should conform to the limited available space and layout in general. In many cases, the passengers feel that the low-frequency contents are not satisfactory although the speaker specification covers the low frequencies. In this work, a thin panel is installed between the roof liner and the roof panel, and it is used as the woofer. The vibration field is controlled by many small actuators to create the speaker and baffle zones to avoid the sound distortion due to the modal interaction. The generation of speaker and baffle zones follows the inverse vibro-acoustic rendering technique. In the actual implementation, a thin acrylic plate of 0.53x0.2 m2 is used as the radiator panel, and the control actuator array is composed of 16 moving-coil actuators.

The purpose of this paper is to develop and experimentally validate a practical and effective technique for the automatic regulation of a hydraulic semiactive vibration absorber (SAVA) for automobiles. The work relies on a consistent hydraulic model of the actuator dynamics that includes the effects of fluid compressibility and a nonlinear viscous loss characteristic. A bistate control algorithm is developed using a Lyapunov approach that seeks to dissipate the energy of the system. The performance of the proposed semiactive damper design on a quarter car model of an automobile suspension is established experimentally on a vibrating test stand. The work provides evidence that the inexpensive hardware design makes it possible to improve the ride and handling performance.

In order to apply an effective noise reduction treatment determining the contribution of different engine components to the total sound perceived inside the cabin is important. Although accelerometer or laser based vibration tests are usually performed, the sound contributions are not always captured accurately with such approaches. Microphone based methods are strongly influenced by the many reflections and other sound sources inside the engine bay. Recently, it has been shown that engine radiation can be effectively measured using microphones combined with particle velocity sensors while the engine remains mounted in the car [6]. Similar results were obtained as with a dismounted engine in an anechoic room. This paper focusses on the measurement of the transfer path from the engine to the vehicle interior in order to calculate the sound pressure contribution of individual engine sections at the listener's position.

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.

To meet the indoor air quality guideline of newly manufactured vehicles in Korea, China, and other countries, low formaldehyde grade POM (Polyoxymethylene) is used for interior parts essentially. In this paper, formaldehyde scavengers from of 2 commercial low formaldehyde grade POM pellets were identified by LC-MS (Liquid chromatograph-Mass spectrometer) as sebacic dihydrazide and dodecanedioic dihydrazide respectively. The reaction products between formaldehyde and formaldehyde scavengers were also detected, which were converted from hydrazide to hydrazone. So, this kind of additive would be gradually consumed by repetitive molding process or exposure to heat according to formaldehyde emission increase. We are expecting to apply this analytical method and result for quality control and benchmark of low formaldehyde grade POM.

As the AVN display in the car interior becomes larger and located above the center fascia, the driver's visual visibility is becoming important. In addition, since an expensive touch sensor is installed, a transparent electrode cost reduction technology for a display touch sensor that can replace an indium material, which is an expensive rare metal, is required. In this paper, we developed new transparent electrode materials and manufacturing methods for the touch sensor film which light reflectance is low and flexible without a separate low-reflection multi-layer, so that the design freedom is high and the material cost is low. By optimizing the amount of fluorine doping ratio in tin oxide, excellent electrical conductivity and high optical transmittance are secured, and the surface reflectance is reduced by adjusting the diameter and length of the silver nanowire. As a result, it was shown that the AVN display image and font readability was improved.

The experimental control findings of increasing the handling performance so that the yaw motion of the vehicle is nimble and stable utilizing the upgraded rear wheel steering system equipped with dual-link actuators are shown in this work. In most automobiles, the steering axis is well defined in front suspension. However, unless the vehicle's rear suspension is a sort of double wishbone, the steering axis is not clearly defined in regular multi-link rear suspensions. As a result, most current automobiles have a suspension geometry feature in which the camber and toe angles change at the same time when the assist link is changed to steer the back wheels. To create lateral force from the rear tire while preserving maximum tire grip, the dual-link actuators control for modifying the strokes of suspension links must keep the camber angle constant and adjust only the toe angle.