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Due to increasing amount of modules and customized options in commercial vehicles, it becomes more and more difficult to verify the circuit design. In this paper, a wire segment error locating algorithm is proposed to automate the exact wire segment error locating process. When a wrong connection is found by existing tool, guided by the exact description of wire segment error, this algorithm can locate exact wire segment error in the connection by searching for the one that has at least one neighboring segment from a correct connection.

In regard to the evaluation of the performance of a hybrid electric vehicle (HEV), there are as many simulation methods as there are developers or researchers. They adopt different operational algorithms and they use diverse techniques to realize their logic. However, the relation among the various simulation methods has not been clearly defined. Thus, it is not easy to choose a method that would bring the best consequences in the most efficient way. Here, we present three types of backward-looking simulation algorithms for evaluating the fuel efficiency of a power-split HEV. Then the results and cost-effectiveness of each algorithm are analyzed using various component ratings over a representative driving mode. Based on the comparative analysis, the algorithm that uses equivalent fuel consumption is shown to be highly cost-effective. Also, an inductive or empirical base is set up with the results for a component sizing methodology using the recommended simulation.

A spark-ignition engine commonly induces tumble flow because it generates high turbulence, which is a crucial factor in determining the flame propagation speed. Since tumble affects not only the flame propagation speed but also the various in-cylinder phenomena, it predominantly determines the performance of the engine. In that sense, many studies have been conducted to investigate tumble. Although various studies have revealed the characteristics of tumble numerically and experimentally, there has been no research to identify the physical mechanisms of these characteristics. Although some studies specified the mechanisms from an angular momentum perspective, the theory was insufficient to explain the entire phenomena of tumble. Hence, this study attempts to comprehend the fundamental causes of tumble phenomena such as ‘spinning up’ and ‘vortex breakdown’ from the perspective of kinetic energy.

This paper analyzes heterogeneous distribution of branch-like structure at downstream region of the diesel spray. The liquid and vapor phase of the spray are obtained by a 35mm still camera and CCD camera in order to investigate spray structure of evaporative diesel spray. The many previous studies about diesel spray structure have yet stayed in the analyses of 2-D structure, and there is little information which is concerned with 3-D structure analysis of evaporative spray. The heterogeneous distribution of droplets in inner spray affects the mixture formation of diesel spray, and the combustion characteristics of the diesel engines. In this study, the laser beam of 2-D plane was used in order to investigate 3-D structure of evaporative spray. The incident laser beam was offset on central axis of the spray.

The volumetric efficiency for a 4-stroke, single- cylinder, spark- ignition engine is considered. The mathematical model for the gas exchange process was formulated and solved by numerical technique. The mass flow rate, the pressure-time history in cylinder, intake and exhaust pipes, and the volumetric efficiency were calculated. The important parameter affecting volumetric efficiency was the pressure in the pipes. But, the effect of valve timing on volumetric efficiency was small (1, 2)*. The experiments with 3-different cams were performed. The predicted results were compared with experimental data and satisfactory agreement was obtained. As a result, the volumetric efficiency could be predicted with a relatively simple mathematical model.

Much research has been devoted to reducing NOx and soot emissions simultaneously in diesel engines. The low temperature combustion (LTC) concept has the potential to reduce these emissions at the same time, but it has limitations to its commercialization. In-cylinder EGR stratification is another combustion concept meant to reduce both types of emissions simultaneously using non-uniform in-cylinder EGR gas distribution. The EGR stratification concept uses a locally high EGR region of the in-cylinder so that the emissions can be reduced without increasing the overall EGR rate. In this study, the EGR stratification concept was improved with a CFD-based analysis. First, a two-step piston was developed to maximize the stratified EGR effect. Then, the feasibility of combustion and emission control by stratified EGR was evaluated under cases of artificially distributed EGR stratification and conventional diesel engine conditions.

Due to the direct injection of fuel into a combustion chamber, particulate emission is a challenge in DISI engines. Specifically, a significant amount of particulate emission is produced under the cold start condition. In this research, the main interest was to investigate particulate emission characteristics under the catalyst heating condition because it is one of the significant particulate-emissionproducing stages under the cold start condition. A single-cylinder optically accessible engine was used to investigate the effect of injection strategies on particulate emission characteristics under the catalyst heating condition. The split injection strategy was applied during intake stroke with various injection pressures and injection timings. Using luminosity analysis of the soot radiation during combustion, the particulate formation characteristics of each injection strategy were studied. Moreover, the factors that affect PM formation were analyzed via fuel injection visualization.

Natural gas has been considered as an alternative fuel for a heavy duty diesel engine with its lower pollutant and carbon dioxide emissions than its counterpart. However, due to the high auto-ignition temperature of methane, this alternate fuel has been mainly used in spark-ignited engine with relatively lower compression ratio, losing full potential of achieving high efficiency. To overcome these limitations, high-pressure direct injection of the natural gas in a compression ignition engine has been proposed, and there have been several attempts to understand physical behaviors and ignition of methane jet. In this study, auto-ignition characteristics of high-pressure methane jet were investigated both through the experiment and the multi-zone modeling to suggest the applicability to such engine.

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.

In recent years, Large-Eddy Simulation (LES) is spotlighted as an engineering tool and severe research efforts are carried out on its applicability to Internal Combustion Engines (ICEs). However, there is a general lack of definitive conclusions on LES quality criteria for ICE. This paper focuses on the application of LES quality criteria to ICE and to their correlation, in order to draw a solid background on future LES quality assessments for ICE. In this paper, TCC-III single-cylinder optical engine from University of Michigan is investigated and the analysis is conducted under motored condition. LES quality is mainly affected by grid size and type, sub-grid scale (SGS) model, numeric schemes. In this study, the same grid size and type are used in order to focus on the effect on LES quality of SGS models and blending factors of numeric scheme only.

This paper proposes a reference steering wheel torque map and a torque tracking algorithm via steer-by-wire to achieve the targeted steering feel. The reference steering wheel torque map is designed using the measurement data of rack force and steering characteristic of a target performance of the vehicle at transition steering test. Since the target performance of the vehicle is only tested in nominal road condition, various road conditions such as disturbances and tire-road friction are not considered. Hence, the measurement data of the rack force that reflects the road conditions in the reference steering wheel torque map have been used. The rack force is the net force which consists of tire aligning moment, road friction force and normal force on the tire kingpin axis. A motor and a magnetorheological damper are used as actuators to generate the desired steering feel using the torque tracking algorithm.

This paper presents a stability monitoring algorithm with a combined slip tire model for maximized cornering speed of high-speed autonomous driving. It is crucial to utilize the maximum tire force with maintaining a grip driving condition in cornering situations. The model-free cruise controller has been designed to track the desired acceleration. The lateral motion has been regulated by the sliding mode controller formulated with the center of percussion. The controllers are suitable for minimizing the behavior errors. However, the high-level algorithm is necessary to check whether the intended motion is inside of the limit boundaries. In extreme diving conditions, the maximum tire force is limited by physical constraints. A combined slip tire model has been applied to monitor vehicle stability. In previous studies, vehicle stability was evaluated only by vehicle acceleration.

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.

This paper proposes a rear-wheel steering control method that can modify and improve the vehicle lateral response without tire model and parameter. The proposed control algorithm is a combination of steady-state and transient control. The steady state control input is designed to modify steady-state yaw rate response of the vehicle, i.e. understeer gradient of the vehicle. The transient control input is a feedback control to improve the transient response when the vehicle lateral behavior builds up. The control algorithm has been investigated via computer simulations. Compared to classical control methods, the proposed algorithm shows good vehicle lateral response such as small overshoot and fast response. Specifically, the proposed algorithm can alleviate stair-shaped response of the lateral acceleration.

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.

In recent years, emission regulations have been getting increasingly strict. In the development of engines that comply with these regulations, in-cylinder pressure plays a fundamental role, as it is necessary to analyze combustion characteristics and control combustion-related parameters. The analysis of in-cylinder pressure data enables the modelling of exhaust emissions in which characteristic temperature can be derived from the in-cylinder pressure, and the pressure can be used for other investigations, such as optimizing efficiency and emissions through controlling combustion. Therefore, a piezoelectric pressure sensor to measure in-cylinder pressure is an essential element in the engine research field. However, it is difficult to practice the installation of this pressure sensor on all engines and on-road vehicles owing to cost issues.

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.

Since the amount of emitted CO2 is directly related to car fuel economy, attention is being drawn to DISI (Direct-Injection Spark-Ignition) engines, which have better fuel economy than conventional gasoline engines. However, it has been a problem that the rich air-fuel mixtures associated with fuel films during cold starts due to spray impingement produce particulate matter (PM). In predicting soot formation, it is important to predict the mixture field precisely. Thus, accurate spray and film models are a prerequisite of the soot model. The previous models were well matched with low-speed collision conditions, such as those of diesel engines, which have a relatively high ambient pressure and long traveling distances. Droplets colliding at low velocities have an order of magnitude of kinetic energy similar to that of the sum of the surface tension energy and the critical energy at which the splash occurs.

Modeling of unburned hydrocarbon oxidation in an SI engine was performed in engine condition using modified one-step oxidation model. The new one-step equation was developed by modifying the Arrhenius reaction rate coefficients of the conventional one-step model. The modified model was well matched with the results of detailed chemical reaction mechanism in terms of 90 % oxidation time of the fuel. In this modification, the effect of pressure and intermediate species in the burnt gas on the oxidation rate investigated and included in developed one-step model. The effect of pressure was also investigated and included as an additional multiplying factor in the reaction equation. To simulate the oxidation process of piston crevice hydrocarbons, a computational mesh was constructed with fine mesh density at the piston crevice region and the number of cell layers in cylinder was controlled according to the motion of piston.

This paper describes a lateral control of autonomous large size buses on road with large curvature. In the case of long and wide commercial vehicle such as large bus, applying centerline tracking controllers in constrained environments such as large curved road (e.g. turning at intersection) may cause some concerns. Two concerns are considered: inner lane crossing related to collisions with curb and opposite lane crossing related to threatening surrounding vehicles. Considering relations between width and curvature of the road and length and width of the large size bus, the curvature of road at which inner or outer lane crossing begin to occur was calculated when centerline tracking controller was applied. Thus, the proposed algorithm optimizes motion of the bus by using model predictive control (MPC) using road geometry as constraints.