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In contrast to highway, there are some sections not well maintained in urban roads. In these sections, there may be faint lane marks or static obstacles due to construction or some other reasons. Therefore, an automated vehicle following system such as traffic jam assistant should consider these sections to guarantee the safety of the system. In order to achieve this purpose, a model predictive control (MPC) scheme has been developed. The objectives of MPC are to compute the sequence of optimal steering input for vehicle following with obstacle avoidance. For this, the MPC uses the lead vehicle's state and obstacle's position obtained by lidars. For this purpose, a simplified nonlinear model of the vehicle was used to predict the future evolution of the system. Based on this prediction, performance index is optimized under operating constraints at each time step. A test vehicle equipped with two lidars on left and right corner of the front bumper has been developed.

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.

Two-mode hybrid architectures with three planetary gear sets and four clutches will bring both flexibility and complexity to energy management of powertrains. In order to take full advantage of the increased degrees of freedom, highly delicate operation strategies are needed. We develop transmission efficiency models for power-split modes, and present a mode shift strategy assuming no battery power. When battery load leveling is additionally considered, the respective optimal operation set for each mode can be obtained and compared to yield a mode shift algorithm for general hybrid operation situations. The investigation of the strategies shows how frequently each mode is used, and verifies the effectiveness of fixed gear operations. We check the validity of the strategies by applying the algorithm to dynamic optimization and by predicting how it works during an actual driving simulation.

As fuel injection strategies in spark-ignition (SI) engines have been diversified, inhomogeneous mixing of the fuel-air mixture can occur to varying extents during mixture preparation. In this study, we analyzed the effect of inhomogeneous mixing on the knocking characteristics of iso-octane and air mixture under a standardized fuel testing condition for research octane number (RON), based on ASTM D2699. For this purpose, we assumed that both lean spots and rich spots existed in unburned gas during compression stroke and flame propagation and calculated the thermodynamic state of the spots by using an in-house multi-zone, zero-dimensional SI engine model. Then, the ignition delay was measured over the derived thermodynamic profiles by using rapid compression machine (RCM), and we calculated ξ, the ratio of sound speed to auto-ignition propagation speed, based on Zel’dovich and Bradley’s ξ − ε theory to estimate knock intensity.

Fatigue life of a V-belt pulley, which is commonly used in automotive powertrain to transfer power to other parts, is predicted based on damage analysis by finite element analysis (FEA). Load conditions on pulley are analyzed by considering interactions among the pulley, V belt, bracket and bolts. Both normal force and traction force on the contact surfaces between the pulley and V belt were calculated. Assembly load due to the tightening of the bolts as well as operation load was considered to describe the actual load conditions in durability test. Static analysis at initial position of the pulley after assembly was performed with given load conditions. As the pulley rotated every ten degrees, consecutive static analyses were followed to find out the stress history of the pulley during operation. Using stress history data calculated from FE analysis, damage over one rotation of pulley was calculated and fatigue life, number of rotation to failure, was estimated.

A gasoline homogeneous charged compression ignition (HCCI) called the controlled auto ignition (CAI) engine is an alternative to conventional gasoline engines with higher efficiency and lower emission levels. However, noise and vibration are currently major problems in the CAI engine. The problems result from fast burning speeds during combustion, because in the CAI engine combustion is controlled by auto-ignition rather than the flame. Thus, the ignition delay of the local mixture has to vary according to the location in the combustion chamber to avoid noise and vibration. For making different ignition delays, stratification of temperature or mixing ratio was tested in this study. In charge stratification, which determines the difference between the start of combustion among charges with different properties, two kinds of mixtures with different properties flow into two intake ports.

Exterior shape of automobile can be represented by shape function through this study so that aerodynamic shape parameters can be easily controlled and changed. Also ordinary geometric information can be extracted easily from shape function model by simple calculations. It is possible to predict the aerodynamic performance of functional virtual car models which are transformed continually by developing automated program in initial design stage that includes all of above process. Innovative vehicle design process with exterior design guide will be proposed for stylist, engineer and packaging department in order to achieve low aerodynamic drag and high fuel efficiency targets.

This paper presents a closed-loop evaluation of the Vehicle Stability Control (VSC) systems using a vehicle simulator. Human driver-VSC interactions have been investigated under realistic operating conditions in the laboratory. Braking control inputs for vehicle stability enhancement have been directly derived from the sliding control law based on vehicle planar motion equations with differential braking. A driving simulator which consists of a three-dimensional vehicle dynamic model, interface between human driver and vehicle simulator, three-dimensional animation program and a visual display has been validated using actual vehicle driving test data. Real-time human-in-the loop simulation results in realistic driving situations have shown that the proposed controller reduces driving effort and enhances vehicle stability.

Ground systems in automobiles become more important as more electric devices are installed and the amount of currents flowing increases. The performance of the devices depends on the ground voltage, which is generated between ground points by I-R voltage drops. Therefore, low ground voltages are required for the reduction of the unnecessary power dissipation as well as the reliable performance of the devices. In this paper, we propose an automotive ground system model to analyze ground structure and reveal the main cause of ground voltages. The equivalent resistor network model is presented to describe the relationship between ground points. Then, we validate the model by comparing the simulation results with the measurements in a real car. The presented analysis can provide guidance on designing a reliable ground system such as how to reduce the ground voltages for the proper operation of devices.

The role of 1D simulation tool is growing as the engine system is becoming more complex with the adoption of a variety of new technologies. For the reliability of the 1D simulation results, it is necessary to improve the accuracy and applicability of the combustion model implemented in the 1D simulation tool. Since the combustion process in SI engine is mainly determined by the turbulence, many models have been concentrating on the prediction of the evolution of in-cylinder turbulence intensity. In this study, two turbulence models which can resemble the turbulence intensity close to that of 3D CFD tool were utilized. The first model is dedicated to predicting the evolution of turbulence intensity during intake and compression strokes so that the turbulence intensity at the spark timing can be estimated properly. The second model is responsible for predicting the turbulence intensity of burned and unburned zone during the combustion process.

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.

Large-eddy simulation (LES) applications for internal combustion engine (ICE) flows are constantly growing due to the increase of computing resources and the availability of suitable CFD codes, methods and practices. The LES superior capability for modeling spatial and temporal evolution of turbulent flow structures with reference to RANS makes it a promising tool for describing, and possibly motivating, ICE cycle-to-cycle variability (CCV) and cycle-resolved events such as knock and misfire. Despite the growing interest towards LES in the academic community, applications to ICE flows are still limited. One of the reasons for such discrepancy is the uncertainty in the estimation of the LES computational cost. This in turn is mainly dependent on grid density, the CFD domain extent, the time step size and the overall number of cycles to be run. Grid density is directly linked to the possibility of reducing modeling assumptions for sub-grid scales.

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.

Improving fuel efficiency and emission characteristics are significant issues in engine research. Because the engine has complex systems and various operating parameters, the experimental research is limited by cost and time. One-dimensional (1D) simulation has attracted the attention of researchers because of its effectiveness and relatively high accuracy. In a 1D simulation, the applied model must be accurate for the reliability of the simulation results. Because in-cylinder turbulence mainly determines the combustion characteristics, and mean flow velocity affects the in-cylinder heat transfer and efficiency in a spark-ignited (SI) engine, a number of sophisticated models have been developed to predict in-cylinder turbulence and mean flow velocity. In particular, tumble is a significant factor of in-cylinder turbulence in SI engine.

Validation of a vehicle simulation model of the Chevrolet Volt 2016 was conducted. The Chevrolet Volt 2016 is equipped with the new “Voltec” extended-range propulsion system introduced into the market in 2016. The second generation Volt powertrain system operates in five modes, including two electric vehicle modes and three extended-range modes. Model development and validation were conducted using the test data performed on the chassis dynamometer set in a thermal chamber of Argonne National Laboratory’s Advanced Powertrain Research Facility. First, the components of the vehicle, such as the engine, motor, battery, wheels, and chassis, were modeled, including thermal aspects based on the test data. For example, engine efficiency changes dependent on the coolant temperature, or chassis heating or air-conditioning operations according to the ambient and cabin temperature, were applied.

Radiative heat transfer analysis in a finite cylindrical enclosure with non-gray media and internal heat generations have been conducted. Solutions are generated by a recently developed spherical harmonics method for a finite cylindrical configuration with the weighted sum of gray gases model. Numerical solutions are obtained for temperature and heat flux distributions with the variations of optical thickness and wall emissivity. The results show that with an increase in the absorption coefficient, the heat flux distribution along the lateral wall becomes symmetric regardless of the source distributions. The dependence of heat flux on the wall emissivity is reduced as well. The present solution technique seems to be easily extended to the coupled mode of heat transfer with convection in an engine cylinder.

This paper presents a methodology of trajectory planning for the surrounding-aware lane change maneuver of autonomous vehicles based on a data-driven method. The lateral motion is planned by sampling candidate patterns which are defined based on quintic polynomial functions over time. Based on the cost evaluation among the sampled candidates, the optimal lateral motion pattern is selected as a reference and tracked by the controller. The longitudinal motion is planned and controlled using Model Predictive Control (MPC) which is an optimal control method designed considering the surrounding traffic information. To realize the lane change motion similar to the human driving behavior in the surrounding traffic situation, the human driving pattern is modeled in the form of motion parameters and considered in planning the lateral and longitudinal motion.

Regulations regarding vehicles’ CO2 emissions are continuing to become stricter due to global warming. The CO2 regulations urge automobile manufacturers to develop gasoline engines with improved efficiency; however, the main obstacle to the improvement is the knock phenomenon in spark-ignition engines. If knock is predicted, the efficiency potential can be maximized in an engine by applying modest spark timing. Several research regarding knock prediction modeling have been conducted, and typically Livengood-Wu integral model is used to predict the knock occurrence. For the prediction, knock onset should be determined on a given pressure signal of given knock cycles for establishing the 0D ignition delay model. Several methodologies for knock onset determination have been developed because checking all the knock onset position by hand is impossible considering the breadth of data sets.

As a result of stringent global regulations on fuel economy and CO2 emissions, the development of high-efficiency SI engines is more urgent now than ever before. Along with advanced techniques in friction reduction, many researchers endeavor to decrease the B/S (bore-to-stroke) ratio from 1.0 (square) to a certain value, which is expected to reduce the heat loss and enhance the burning rate of SI engines. In this study, the effects of B/S ratios were investigated in aspects of efficiency and knock characteristics using a single-cylinder LIVC (late intake valve closing) GDI (gasoline direct injection) engine. Three B/S ratios (0.68, 0.83 and 1.00) were tested under the same mechanical compression ratio of 12:1 and the same displacement volume of 0.5 L. The head tumble ratio was maintained at the same level to solely investigate the effects of geometrical changes caused by variations in the B/S ratio.

As the mobility being developed becomes more complex and numerous, it is becoming difficult and inefficient to apply current vehicle-test-based development. To overcome this, research on combining test and simulation models has been actively conducted to perform objective and subjective evaluations more accurately and efficiently in the advance stage without a vehicle over the years. At first, test models for various systems such as tire, suspension and body were made compatible with simulation models by using various methodologies such as blocked forces, FBS decoupling, and Virtual Point Transformation (VPT). The second step was to objectively estimate road noise by using FBS coupling with system models and to deeply analyze transfer paths and system’s sensitivity. The results were verified by comparing with what was measured and analyzed on vehicle.