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The accurate representation of Internal Combustion Engine (ICE) flows via CFD is an extremely complex task: it strongly depends on a combination of highly impacting factors, such as grid resolution (both local and global), choice of the turbulence model, numeric schemes and mesh motion technique. A well-founded choice must be made in order to avoid excessive computational cost and numerical difficulties arising from the combination of fine computational grids, high-order numeric schemes and geometrical complexity typical of ICEs. The paper focuses on the comparison between different mesh motion technologies, namely layer addition and removal, morphing/remapping and overset grids. Different grid strategies for a chosen mesh motion technology are also discussed. The performance of each mesh technology and grid strategy is evaluated in terms of accuracy and computational efficiency (stability, scalability, robustness).

This paper describes a reference steering feel tracking algorithm for Electric-Power-Steering (EPS) system. Development of the EPS system with intended steering feel has been time-consuming procedure, because the feedforward map-based method has been applied to the conventional EPS system. However, in this study, a three-dimensional reference steering feel surface, which is determined from current vehicle states, is proposed. In order to track the proposed reference steering feel surface, sliding mode approach is applied to second-order steering dynamics model considering a coulomb friction model. An adaptive technique is utilized for robustness against uncertainties. In order to validate the proposed EPS control algorithm, hardware-in-the-loop simulation (HILS) has been conducted with respect to a typical steering test. It is shown that the reference steering feel is realized well by the proposed EPS control algorithm.

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.

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.

Knock is one of the main limitations on Spark-Ignited (SI) Internal Combustion Engine (ICE) performance and efficiency and so has been the object of study for over one hundred years. Great strides have been made in terms of understanding in that time, but certain rather elementary practical problems remain. One of these is how to interpret if a running engine is knocking and how likely this is to result in damage. Knocking in a development environment is typically quantified based on numerical descriptions of the high frequency content of a cylinder pressure signal. Certain key frequencies are observed, which Draper [1] explained with fundamental acoustic theory back in 1935. Since then, a number of approaches of varying complexity have been employed to correlate what is happening within the chamber with what is measured by a pressure transducer.

The goal of this study is to develop an actively translating rear diffuser device to reduce the aerodynamic drag experienced by passenger cars. The feature of this device is hidden under the rear bumper ordinarily not to ruin the external design of the car and slips out backward under the high-speed driving condition. By this study, a movable arc-shaped semi-diffuser device is designed to maintain the streamlined automobile rear underbody configuration. It's installed under the rear bumper of a passenger car. Seven types of rear diffuser devices whose positions, slid out lengths and widths are differing with the basic shape installed in the rear bumper section of a passenger car and performed Computational Fluid Dynamics (CFD) analyses under rotating wheel and moving ground conditions. The main purpose of this study is that explains the aerodynamic drag reduction mechanism of a passenger car via an actively translating rear diffuser device at a high speed driving condition.

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 presents a longitudinal control algorithm for an adaptive cruise control (ACC) with collision avoidance (CA) in multiple vehicle traffic situations. The proposed algorithm consists of a multi-target tracking filter, a primary target selection algorithm and an integrated ACC/CA system. The multi-target tracking filter is used to smooth the sensor signal, and makes it possible to apply to a control system. The primary target selection algorithm decides an in-lane target and provides the information to an integrated ACC/CA system in order to drive a subject vehicle smoothly and improve safety in complex traffic situations. Finally, the integrated ACC/CA system computes the desired acceleration. The performance and safety benefits of the multi-vehicle ACC/CA system is investigated via simulations using real data on driving. Simulation results show that the response of multi-vehicle ACC/CA system is more smooth and safer at a change of traffic situations.

As the number of user selectable electrical modules increases for passenger car, the number of cars with different combinations of option can easily exceed 100,000 cars. It results to a situation where we can not manually verify all the logical connection by making wiring combinations for each car. In this paper, we propose an algorithm that can reduce verification time for all possible wiring with available option combinations. The algorithm separates the whole wiring circuits into independent circuits and verifies the logical connections for each independent circuit with all possible options. The algorithm is time effective so the required time to verify the connections increases logarithmically as the number of possible car increases. The algorithm was implemented as software verification tool and its effectiveness was proved to be feasible.

Discomfort models play a significant role in ergonomic simulation. More detailed and specific discomfort models are required for older drivers who represent the fastest-growing segment of the driving population. Owing to the physical degradation, various biomechanical discomfort factors should be incorporated into the model to properly evaluate discomfort for the older population group. In this experimental study we attempted to identify and quantify biomechanical factors that affect the older drivers' discomfort ratings. Different egress motion strategies (e.g., with and without using assist devices) were designed to induce various physical activities. The corresponding discomfort ratings were then produced. From the kinematic analysis using a digital human body model with reconstructed egress motion, the hip abduction was found to have the most statistically significant effect on the discomfort rating.

The recent interest in alternative non-fossil fuels has led researchers to evaluate several alcohol-based formulations. However, one of the main requirements for innovative fuels is to be compatible with existing units’ hardware, so that full replacement or smart flexible-fuel strategies can be smoothly adopted. n-Butanol is considered as a promising candidate to replace commercial gasoline, given its ease of production from bio-mass and its main physical and chemical properties similar to those of Gasoline. The compared behavior of n-butanol and gasoline was analyzed in an optically-accessible DISI engine in a previous paper [1]. CFD simulations explained the main outcomes of the experimental campaign in terms of combustion behavior for two operating conditions. In particular, the first-order role of the slower evaporation rate of n-butanol compared to gasoline was highlighted when the two fuels were operated under the same injection phasing.

CFD simulations of reacting flows are fundamental investigation tools used to predict combustion behaviour and pollutants formation in modern internal combustion engines. Focusing on spark-ignited units, most of the flamelet-based combustion models adopted in current simulations use the fuel/air/residual laminar flame propagation speed as a background to predict the turbulent flame speed. This, in turn, is a fundamental requirement to model the effective burn rate. A consolidated approach in engine combustion simulations relies on the adoption of empirical correlations for laminar flame speed, which are derived from fitting of combustion experiments. However, these last are conducted at pressure and temperature ranges largely different from those encountered in engines: for this reason, correlation extrapolation at engine conditions is inevitably accepted. As a consequence, relevant differences between proposed correlations emerge even for the same fuel and conditions.

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.

The paper presents a numerical investigation, aimed to explore the potential of 2-stroke Diesel engines, able to meet Euro VI requirements, for application to medium size commercial vehicles (power rate: 80 kW at 2600 rpm, max. torque 420 Nm from 1200 to 1400 rpm). The study is based on experimental performance of a highly developed 4-stroke engine. Two different designs are considered: Loop and Uniflow scavenging, the latter obtained through an opposed piston configuration. In both cases, no poppet valves are used, and the lubrication is provided by a 4-stroke-like oil sump. The study started with the development of a 4-stroke EURO VI engine, on the basis of a previous EURO IV version. A prototype of the new engine (named 430) was built and tested.

The paper compares two different design concepts for a range extender engine rated at 30 kW at 4500 rpm. The first project is a conventional 4-Stroke SI engine, 2-cylinder, 2-valve, equipped with port fuel injection. The second is a new type of 2-Stroke loop scavenged SI engine, featuring a direct gasoline injection and a patented rotary valve for enhancing the induction and scavenging processes. Both power units have been virtually designed with the help of CFD simulation. Moreover, for the 2-Stroke engine, a prototype has been also built and tested at the dynamometer bench, allowing the authors to make a reliable theoretical comparison with the well assessed 4-Stroke unit.

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.

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.

This paper describes a failsafe system of automated driving vehicles. The failsafe system consists of the following two parts: sliding mode observer-based environment sensor, chassis sensor fault detection, and emergency deceleration control. Two sliding mode observers are designed to reconstruct the fault of acceleration and environment sensor(Lidar) in a longitudinal direction. In the environment sensor's fault detection part, the longitudinal vehicle model receives clearance and relative velocity values. Therefore, failure diagnosis is possible regardless of environmental sensors, such as radar, lidar, and camera. This paper's sensor data is the failure of Delphi's Electronically Scanning Radar (ESR) and Ibeo's LUX Lidar installed in an autonomous vehicle. The emergency deceleration control algorithm employs the sliding mode control with adaptive convergence time. In the event of a failure, it is significant to control the vehicle within a short period safely.

This paper describes the ground system model and algorithm for a ground level simulation tool. First, the modeling of an automotive ground system will be discussed and the algorithm for a simulation tool will be explained. We divided the model into a ground tree and a ground body. The ground tree model consists of resistance formed by the wires that connect the load to ground point with various structures and the ground body model consists of resistance between ground points in the car body. The wires with large current, such as engine ground cable, was modeled in detail by dividing the resistance into wire, bolt, and clamping resistance, in order to simulate the effect of increased contact resistance after durability test. The algorithm of the ground level simulation tool was designed to adjust the currents of the alternator, battery, and ground points in order to evaluate the various driving and load conditions.

The powertrain of an automatic transmission has a wide operating range in speed, torque and temperature while driving. It is necessary to know them to achieve good shift quality in various operating conditions without tuning the parameters of the shift quality controller. All but the torque sensor is installed in the automatic transmission because of its high cost. In this study, a more precise algorithm is suggested for estimating turbine torque using a neural network model that has three inputs, i.e., engine speed, turbine speed and temperature. The performance of the suggested turbine torque estimation algorithm is validated through experimental results. To utilize the estimated turbine torque in shift control, a shift control algorithm, which shows good shift quality in various operating conditions, is developed.