Dynamics analysis of an omni-directional vehicle

In a modern society, traffic congestion is a major problem in every metropolis. To solve the problem of traffic congestion an innovative omni-directional vehicle is proposed. This research has mainly focussed on developing the comprehensive vehicle dynamics model for an omni-directional road vehicle. Then the stability of the vehicle in the yaw plane was analysed under different scenarios based on the response of the side slip angle. Finally an active steering PID controller was suggested and which, according to the results of the simulation, improved the yaw plane stability.     

Nonlinear sliding mode observer for exhaust manifold pressure estimation in a light-duty diesel engine

In this paper, a sliding mode observer is proposed to estimate exhaust pressure for a diesel engine equipped with variable geometry turbocharger (VGT) and exhaust gas recirculation (EGR) systems. Since the exhaust pressure directly affects generation of the VGT power and the EGR rate in the cylinder, the exhaust pressure information is important for precise control of the VGT and EGR systems. In order to estimate the exhaust pressure accurately, a dynamic model of intake and exhaust pressure was derived. Furthermore, the mass flow rate and temperature of the air system in the diesel engines were modeled by consideration of physical phenomena and the thermodynamic law. Based on the developed models, a nonlinear sliding mode observer was designed to estimate the exhaust pressure. Convergence of the proposed observer was verified by the Lyapunov stability criterion. The proposed observer was implemented on a real-time embedded system and validated with the engine experiments. The experimental results show that the observer estimates the exhaust pressure accurately in both steady and transient engine operating conditions. Moreover, as a case study, the estimation results of the proposed observer could be applied for detecting a fault of the EGR system. The fault of the EGR system was detected precisely using the estimation result and the limited sensor information in mass-produced engines.     

Development of an autonomous braking system using the predicted stopping distance

An autonomous braking system is designed using the prediction of the stopping distance. The stopping distance needs to be determined by considering several factors such as the desired deceleration and the speed of the hydraulic brake actuator. In particular, the actuator speed is very critical because it affects the shape of the deceleration response and it determines the accuracy of the predicted stopping distance. The autonomous braking control algorithm is designed based on the predicted stopping distance. The proposed autonomous braking system has been validated in autonomous vehicle tests and demonstrates that the subject vehicle can avoid the collision effectively.     

Development of an auxiliary mode powertrain for hybrid electric scooter

This paper proposes a design and implementation of an auxiliary mode, hybrid electric scooter (HES) by means of more cost-effective way for improving scooter’s performance and efficiency. The HES is built in a parallel hybrid configuration with a 24V 370W auxiliary power electric motor, a 24V 20AH battery, and an electronically controlled fuel injection internal combustion engine (ICE) scooter. In contrast to hybrid electric vehicles (HEVs), the issues concerning cost, volume, and reliability are even more rigorous when developing hybrid electric scooters (HESs). Therefore, the drive topology and control strategy used in HEV cannot be applied to HES directly. In order to hasten the developing phase and achieve the parametric tune-up of the HES component, a dynamic simulation model for the HES is developed here. Because the powertrain system is complex and nonlinear in nature, the simulation model utilizes mathematical models in tandem with accumulated experimental data. The method about the mathematical model construction, analysis and simulation of the hybrid powertrain used in a scooter are fully described. The efficacy of the model was verified experimentally on a scooter chassis dynamometer and the performance of the proposed hybrid powertrain is studied using the developed model under a representative urban driving cycle. Finally, Simulation and experimental results confirm the feasibility and prosperity of the proposed hybrid HES and indicate that the designed hybrid system can improve the fuel consumption rate up to 15% compared with the original scooter.     

Robust design optimization of frontal structures for minimizing injury risks of Flex Pedestrian Legform Impactor

The Flexible Pedestrian Legform Impactor (Flex-PLI) consisting of a flexible femur and tibia will be tested for pedestrian protection by Euro NCAP within the next couple of years as a potential replacement for the Transport Research Laboratory (TRL) legform impactor. The injury risks that are measured when using Flex-PLI are the elongation of the anterior/posterior cruciate ligament (A/PCL), elongation of the medial collateral ligament (MCL), and tibia bending moment (TBM). In this study, we used a correlated computer-aided engineering (CAE) model to conduct a contribution analysis of each injury with regard to the changes in the location of the frontal structures based on the results of a design of experiments (DOE) and analysis of variance (ANOVA). The frontal structures that were selected as control factors were the energy absorber (EA), lower bumper stiffener (LBS), and hood angle. A kriging interpolation model was developed using the DOE results, and its results were compared with those of the CAE model. Furthermore, for robust design optimization, the speed and height of Flex-PLI were used as the noise factors. Finally, a robust design optimization was carried out using the optimal combination of the discrete control factors for minimizing MCL elongation.     

Experimental approach to developing human driver models considering driver’s human factors

A new approach to develop human driver models (HDMs) is proposed in accordance with the drivers’ generic human factors, i.e., gender, age, and experience, to develop more realistic vehicle simulations. The HDMs consist of three independent and stepwise models with functioning driver’s information processing stages based on the human factors: constructing drivers’ preview distance (PVD) models as a ‘cognition process’, implementing a finite preview optimal control algorithm as a ‘decision process’, and differentiating an ‘operation process’ according to neuromuscular efficiency. Eight different groups of 65 drivers with a 2 × 2 × 2 within-subject design participated in both the PVD estimates and neuromuscular efficiency tests to develop a set of statistically different HDMs. Regarding the preview distance models, an analysis of covariance (ANCOVA) procedure was adopted with two covariates (i.e., vehicle velocity and road curvature), while analyses of variance (ANOVAs) were performed on the neuromuscular efficiency parameters. The ANCOVA procedure produced eight significantly different cognition processes, whereas the ANOVAs revealed gender differences for the drivers’ neuromuscular systems. Moreover, an integrated vehicle simulation was configured with the HDMs using Carsim and Simulink software to observe the differential effects of both the cognition and operation processes on a double-lane-change (DLC) maneuver. During the simulations, gender differences in real-world DLC tests were also identified, especially between the male-oldexpert and the female-young-novice HDMs. The results presented in this study suggest that differentiating HDMs according to human factors is an essential process when utilizing vehicle simulations in the early stage of developing an intelligent vehicle system.     

Abnormality detection via SVDD technique of motor-generator system in HEV

This paper introduces a method to detect abnormality of MGS (Motor-Generator System) in HEV (Hybrid Electric Vehicle) using its temperature. The MGS in HEV consists of two Motor-Generators (MG1, MG2), Compound Gear Unit, and etc. The MG1 is to act as a generator in conventional internal combustion engine. And the MG2 is an electric motor to rotate wheel of vehicle using saved electricity in battery or using produced electricity via the MG1. In case of overheating, the electric motors are easily damaged because resistance of wires in motor is abnormally changed. Therefore, detection of abnormally changed temperature in motors (MG1 and MG2) is essential. In this study, the temperature distribution of two Motor-Generators is observed simultaneously in 2-dimensional space. A boundary region of normal operation temperature of two motors is obtained via SVDD technique utilizing Gaussian kernel, one of the most widely being used Mercer kernels. Linear SVDD technique generates boundary of exact ball shape, however SVDD technique using Gaussian kernel can generate nonlinear boundary of distorted ball shape. Abnormality boundary comparison is made between the obtained boundary via SVDD technique and those obtained from conventional temperature range checking method. In order to compare the performance of proposed method, the actual vehicle operation data in excessive driving condition on mountain road is adopted. In verification, simulation shows that warning time due to proposed method is faster and more efficient than those due to conventional method. It is also shown that the reliability of the Motor-Generator System can be improved by using the proposed abnormality detection method.     

Analysis of the performance of the evaporator of automotive air conditioning system

The purpose of this research was to establish a theoretical model for the evaporator of automotive air conditioning system and conducting simulations to evaluate the effect of operation parameters, environmental conditions, and design parameters on the performance of evaporator. An automotive air conditioning system primarily consists of four components: the compressor, the condenser, the refrigerant controller, and the evaporator. The refrigerant flow in the evaporator can be divided into two regions: the evaporating region and the superheat region. The refrigerant in the first region is a two-phase flow, while the refrigerant in the latter region is in the state of superheated vapor. The air flowing through the interior of the evaporator can also be divided into two zones: the unsaturated zone and the saturated zone. Water vapor is condensed in the saturated zone while in the unsaturated zone, no water condenses. Because the refrigerant flow and the airflow are perpendicular to each other, the distribution of refrigerant in the evaporating region and the superheat region does not coincide with the distribution of air in the unsaturated zone and the saturated zone. This study examines the effects of different design parameters, environmental conditions and operating parameters on the cooling capacity and superheat of an air conditioning system. Design parameters include the length of the refrigerant channel, the length of the air channel, and the thickness of the fins. Environmental conditions include the air inlet temperature and absolute humidity. Operation conditions include the refrigerant inlet enthalpy, inlet air flow rate, and refrigerant mass flow rate. Results of simulation demonstrated that fins with 50 micron meters width has the greatest cooling capacity for identical outer dimensions; thicker or thinner fins only decreased cooling capacity. Under different outer dimensions, longer refrigerant tubes and air channels created a greater cooling capacity. However, the increase in cooling capacity becomes less and less if the refrigerant flow was fixed because the heat transfer capability of the gaseous refrigerant was limited. In this study, an increase of 19% in cooling capacity can be reached as the length of refrigerant channels was increased, and the increased length of the air channels can promote the cooling capacity by 22%. Besides, it was found in this study that a decrease in the refrigerant inlet enthalpy, the inlet air flow rate, the air inlet temperature, and the inlet absolute humidity, or an increase in the refrigerant mass flow rate, would extend the superheat region and decrease the refrigerant’s superheat. It was also found that the cooling capacity of air conditioners is extremely sensitive to changes in the refrigerant mass flow rate and the inlet enthalpy, and variations more than 50% were found in the operating ranges examined in this study. However, changes in the inlet temperature, absolute humidity, and inlet air flow rate only resulted in variations between 10% and 20% in the examined ranges of conditions. Finally, a correlation among these variables and the simulated cooling capacity was obtained in this study, enabling the relevant researchers to evaluate automotive air conditioning performance under different environmental conditions and operation parameters more easily.     

Design of a compressor-power-based exhaust manifold pressure estimator for diesel engine air management

In accordance with the development of hardware configurations in diesel engines, research on model-based control for these systems has been conducted for years. To control the air management system of a diesel engine, the exhaust manifold pressure should be selected as one of the control targets due to its internal dynamic stability and its physical importance in model-based control. However, it is difficult to measure exhaust pressure using sensors due to gas flow oscillation in the exhaust manifold in a reciprocated diesel engine. Moreover, the sensor is too costly to be equipped on production engines. Hence, the estimation strategies for exhaust manifold pressure have been regarded as a primary issue in diesel engine air management control. This paper proposes a new estimation method for determining the exhaust manifold pressure based on compressor power dynamics. With its simple and robust structure, this estimation leads to improved control performance compared with that of general observers. To compensate for the compressor efficiency error that varies with turbine speed, some correction maps are adopted in the compressor power equation. To verify the control system performance with the new estimator, a HiLS (hardware in the loop simulation) of the NRTC mode is performed. Experimental verification is also conducted using a test bench for the C1-08 mode.     

Analysis of the effect of cold start on fuel economy of gasoline automatic transmission vehicle

FTP75 driving cycle is used in many countries for evaluation of vehicle fuel economy. FTP75 has 3 phases, where the Phase 1 and the Phase 3 have a same velocity profile, but the Phase1, which is known as cold start phase, shows lower fuel efficiency than the Phase 3. In order to analyze the difference of fuel economy between Phase 1 and Phase 3, vehicle tests are performed. The test results show that the differences of fuel economy is ranging from 3.9% to 18.5%. The factors of the difference of fuel economy for gasoline automatic transmission vehicles are analyzed in this research. The key factors affecting the difference of fuel economy are engine friction loss, torque converter loss and accessory loss. The quantitative analysis of these factors is performed.