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The recent development pace of the automotive technology is so rapid worldwide. Especially in a green car, hybrid electric vehicles (HEVs) have been studied a lot due to their significant effects on the urban driving. In the vehicle energy management strategy study, the driving speed is assumed to be known in advance, however the speed is not given in a real world. Accordingly, the prediction of vehicle speed is very important. In this study, we study the prediction methodology for the speed prediction using deep learning. Based on the vehicle driving speed data, the supervised deep learning has been used and the speed prediction accuracy using deep learning shows accurate results comparing to the actual speed. The supervised deep learning is used which is suitable for driving cycle database. As a result, the speed prediction after few seconds is feasible.

It is known that SEA is a rapid and simple methodology for analyzing complex vibroacoustic systems. However, the SEA principle is not always valid and one has to be careful about the physical conditions at which the SEA principle is acceptable. In this study, the appropriate damping loss factor of the vehicle interior cavity is studied in the viewpoint of the modal overlap factor of the cavity and the decay per mean free path (DMFP) of the cavity. Virtual SEA tests are performed with an FE model combination, which is suggested by a previous study of Stelzer et al. for the simulation of the sound transmission loss (STL) of vehicle panel structure. The FE model combination is consisting of the body in white (BIW), an acoustical-excited hemisphere-shaped exterior cavity, and the interior cavity. It is found that the DMFP of the interior cavity is appropriate between 0.5 ~ 1 dB for applying SEA principle.

The electrification of the internal combustion engine is an important subject of future automotive technology. By using a motorized internal combustion engine, it is possible to recover waste energy by regeneration technology and to reduce various losses that deteriorate the efficiency of the internal combustion Engine. This paper summarizes the results of the development of an engine-integrated motor that can be applied to a 48V mild hybrid system for motorization of an internal combustion engine. Like the 48V MHSG-mounted mild hybrid system designed to replace the generator in the auxiliary belt system, the motorized internal combustion engine is designed with the scalability as the top priority to minimize the additional space for the vehicle and to mount the same engine in various models.

This paper describes a driving control algorithm based on skid steering for a Robotic Vehicle with Articulated Suspension (RVAS). The driving control algorithm consists of four parts; speed controller for tracking of the desired speeds, yaw rate controller which computes a yaw moment input to track desired yaw rates, longitudinal tire force distribution which determines an optimal desired longitudinal tire force and wheel torque controller which determines a wheel torque command at each wheel to keep slip ratio at each wheel below a limit value as well as track the desired tire force. Longitudinal and vertical tire force estimators are designed for optimal tire force distribution and wheel slip control. The dynamic model of RVAS for simulation study is validated using vehicle test data.

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.

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 this research, the influence of tire size and shape on sound radiation in the mid-frequency region was studied. First, the relationship between the structural wave propagation characteristics of a tire excited at one point and its sound radiation was identified by using FE and BE analyses. Then, by using that relationship, the effect of modifying a tire's aspect ratio, width and wheel diameter on its sound radiation between 300 Hz and 800 Hz was investigated. Finally, an optimization of the sound radiation was performed by modification of the tire structure and shape. It was found that most of a tire's structural vibration does not contribute to sound radiation. In particular, the effective radiation was found to occur at the frequencies where low wave number components of the longitudinal wave and the flexural wave first appear.

This paper mainly focuses on a lateral control law for pre-given path following which is developed by using the backstepping control design methodology. The position information of the vehicle is obtained by Real Time Kinematic DGPS, and the yaw rate and side-slip angle used in controller are estimated by Kalman estimator. To show the performance of the proposed controller under different speed and various path curvature conditions, the results are given through experiments which are executed on proving ground especially designed for high maneuvering test of which minimum radius of curvature is about 60 m.

On-center feel is a multivariate problem that a performance is represented using put-together several sub-characteristics such as torque feedback, response, torque linearity, hysteresis, returnability, etc. For the improvement of a multivariate problem, multi objective optimization should be carried out. However each characteristic which ignores correlation between characteristics is usually optimized up to now. The objective of this research, Mahalanobis Taguchi System (MTS) technique is grafted to on-center steering feel to obtain the efficient improvement. MTS technique can optimize the unified on-center index which is generated in consideration of correlation between characteristics. In this research, first an effective value of MTS technique is verified with on-center steering feel which has the multivariate characteristic. Second, on-center steering feel is improved using MTS technique and Design of Experiments (DOE).

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.

When unifying the functions of widely used two-fan, engine cooling system into a single fan unit, the noise and power issues must be addressed. The noise problem due to the increased fan radius is a serious matter especially as the cabin noise becomes quieter for sedans. Of the fan noise components, discrete noise at BPF's (Blade Passing Frequency) seriously degrades cabin sound quality. Unevenly spaced fan is developed to reduce the tones. The fan blades are spaced such that the center of mass is placed exactly on the fan axis to minimize fan vibration. The resulting fan noise is 11 dBA quieter in discrete noise level than the even bladed fan system.

This paper presents a Unified Chassis Control (UCC) strategy to improve vehicle stability and maneuverability by integrating Electronic Stability Control (ESC) and Active Front Steering (AFS). The UCC architecture consists of two parts: an estimator and a controller. The estimator is designed to estimate longitudinal and lateral tire forces and the controller is designed in two stages, namely, an upper level controller and a lower level controller. The upper level controller, provides the desired yaw moment for vehicle lateral stability by adopting a sliding control method. The lower level controller, provides the integration method of the AFS and ESC strategies for the desired yaw moment and is designed by optimal tire force coordination.

The experimental study on the automotive body panel shape has researched a way to reduce the damping material. Among each differently designed panel shapes, the curved panel shape, with high rigidity, or dynamic stiffness, and uneven deformation mode, has found to most reduce the vibration energy and damping material application. This study shows how could the panel shape influence the NVH performance, which would be measured according to several specifically designed panel shapes in order to compare with the conventional bead panel. And this research proposes the way to optimize the damping material to minimize its weight.

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.

This paper aims to establish a systematic process of developing a brand driving sound. Firstly, principal factors of a brand sound identity are extracted from factor analysis of many sample cars. As a result, brand sound positioning map is drawn using jury test data. Also, the multiple regression analysis of subjective and objective test results is carried. As a result, the principal factors are expressed by objective test data and brand sound positioning map can be easily updated from the measurement data. In addition, what should be improved for designing a target sound is reviewed. Secondly, various technologies of target sound design are discussed to involve the brand identity and vehicle’s character in driving sound. Also, an efficient tool to implement the target sound with an active sound design (ASD) system in a vehicle is introduced. This tool enables to efficiently design, tune and simulate a target sound for ASD system in a laboratory.

Hyundai Kia Motors started developing the under-floor of YF sonata, the base platform for mid-to-large size sedans, in order to reduce weight and improve body performance. For local dynamic rigidity, there are design improvement and additional support structures at suspension mounting area. The strength at the joint where longitudinal and transverse members meet is increased to improve the overall body stiffness, and also the riding comfort and handling. Impact performance and safety is also improved by straightening the major structural members and strengthening the joint areas, efficiently absorbing and inducing the impact energy through load paths. As the body of a vehicle is the constitution of numerous parts, increased strength at the joints and major structural members with more linear profiles have played crucial roles in the improvement in overall body performance.

In this paper, a reconfigurable object-oriented simulator is proposed to analyze the performance of Bluetooth Voice Communication Package (VCP) for telecom purposes like hands-free vehicular communication. It consists of a graphical user interface (GUI) for research or validation engineers to investigate system specific performance. For example, a research engineer can utilize this GUI to analyze a system performance using different noise reduction filtering techniques in vehicular hands-free applications. Also, a validation engineer can utilize this GUI to evaluate vehicular Bluetooth audio quality for different vehicles at different driving conditions (e.g. speeds, fan levels, etc.). The proposed Bluetooth VCP model consists of modules like Audio Equalization (EQ), Acoustic Echo Canceller (AEC), and Noise Suppression (NS). This dynamic GUI platform provides the scope to add and analyze new proposed filtering techniques.

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.