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.     

Design of 2-speed transmission for electric commercial vehicle

As environmental and economic interests increase, the need for eco-friendly vehicle such as an electric vehicle (EV) has increased rapidly. Various research of enhancing EV powertrain efficiency and relibility have been studied. In this study, 2-speed shift gears mechanism is designed by using simpson type planetary gear train. This transmission has two planetary gear unit. Gear position is determinded by which ring gear is fixed. Internal components of the transmission are designed for satisfying the required specification of EV. We analyze gear strength, gear mesh efficiency, and transmission efficiency. By manufacturing the transmission prototype and performing some experiments, we verify the application suitability of this transmission.     

Analysis of train derailment after hitting the pier of tongling yangtze river bridge combined road with railwayEI北大核心

Research purposes: Precise prediction for mechanical behavior of the bridge under ship collision force is important to assess the analysis of train derailment after hitting the pier. This paper focuses on the Tongling Yangtze River Bridge Combined Road with Railway for ship collision simulation, uses the nonlinear finite element software of ANSYS/LS-DYNA to simulate the ship's bow section of 10000 t and 5000 t class hitting bridge tower column at front and axle to 20° of side in highest navigable water level, conventional navigable water level and the minimum navigable water level. Curves of collision force-period at different working conditions are summarized. On this basis, when the impact load affects as input loads, the displacement and acceleration response can be used by finite element analysis under the collision and study the dynamic response of the bridge caused by a train derailment risk. Research conclusions: (1) The impact force of the bridge is largest when a laden ship is hitting the pier at the highest navigable water level. In the most unfavorable condition, the collision have lardge impact on bridge structure and derailment risk of trains. (2) The transverse acceleration of the girder on the top of 2# pier can reach to 0.922 m/s2, but it does not exceed acceleration excitation limit (1 m/s2) when 3# piers are hitted by the 10000 t ship at the peak load of collision, so the probability of train derailment is minimal. (3) Based on the probability formula of the derailment by simplifying risk criteria, the derailment probability of train is 9×10-5~1.5×10-4 during the ship-bridge collision. (4) The research results can provide the reference for train traffic safety on railway bridge caused by ship collisions.     

A network equilibrium approach for modelling activity-travel pattern scheduling problems in multi-modal transit networks with uncertainty

An understanding of the interaction between individuals’ activities and travel choice behaviour plays an important role in long-term transit service planning. In this paper, an activity-based network equilibrium model for scheduling daily activity-travel patterns (DATPs) in multi-modal transit networks under uncertainty is presented. In the proposed model, the DATP choice problem is transformed into a static traffic assignment problem by constructing a new super-network platform. With the use of the new super-network platform, individuals’ activity and travel choices such as time and space coordination, activity location, activity sequence and duration, and route/mode choices, can be simultaneously considered. In order to capture the stochastic characteristics of different activities, activity utilities are assumed in this study to be time-dependent and stochastic in relation to the activity types. A concept of DATP budget utility is proposed for modelling the uncertainty of activity utility. An efficient solution algorithm without prior enumeration of DATPs is developed for solving the DATP scheduling problem in multi-modal transit networks. Numerical examples are used to illustrate the application of the proposed model and the solution algorithm.     

Dynamic system‐optimal traffic assignment for a city using the continuum modeling approach

This paper presents a continuum dynamic traffic assignment model for a city in which the total cost of the traffic system is minimized: the travelers in the system are organized to choose the route to their destinations that minimizes the total cost of the system. Combined with the objective function, which defines the total cost and constraints such as certain physical and boundary conditions, a continuum model can be formulated as an optimization scheme with a feasible region in the function space. To obtain an admissible locally optimal solution to this problem, we first reformulate the optimization in discrete form and then introduce a heuristic method to solve it. This method converges rapidly with attractive computational cost. Numerical examples are used to demonstrate the effectiveness of the method. Copyright © 2013 John Wiley & Sons, Ltd.     

A review of shipboard large-scale energy storage systems北大核心CSCD

储能系统是船舶中的重要设备,可为各类船舶负荷提供能源。随着电力推进技术的成熟,全电船舶已成为未来船舶设计的主要方向。在此背景下,储能系统将由主要为辅助负荷供能逐步发展到为多类型船舶负荷供能,特别是作为船舶动力系统的重要组成部分与各类船舶主/辅机配合,在满足船舶各类负荷需求的前提下提高船舶的经济/环保特性。功能角色的转变加速了大规模储能系统接入船舶,带来了储能系统的状态估计、能量管理、优化规划等一系列问题。首先,对目前的储能技术进行分类;然后,介绍典型全电船舶的分类方法并指出储能系统的应用场景;最后,提出大容量储能系统接入船舶后带来的若干亟待解决的技术问题,即船舶储能系统分布式控制、船舶储能系统适应性规划与优化,以及船舶储能系统状态评估。所做研究可为未来大规模储能系统在电力化船舶上的应用研究提供参考方向。