Development of control logic for hydraulic active roll control system

Developed in this research is a control logic for the ARC (Active Roll Control) system that uses rotary-type hydraulic stabilizer actuators at the front and rear axles. The hydraulic components of the system were modeled in detail using AMESim, and a driving logic for the hydraulic circuit was constructed based upon the model. The performance of the driving logic was evaluated on a test bench, and it demonstrated good pressure tracking capability. The control logic was then designed with the target of reducing the roll motion of the vehicle during cornering. The control logic consists of two parts: a feedforward controller that generates anti-roll moments in response to the centrifugal force, and a feedback controller that generates anti-roll moments in order to make the roll angle to follow its target value. The developed ARC logic was evaluated on a test vehicle under various driving conditions including a slowly accelerated circular motion and a sinusoidal steering. Through the test, the ARC system demonstrated successful reduction of the roll motion under all conditions, and any discomfort due to the control delay was not observed even at a fast steering maneuver.     

Robust detection of preceding vehicles in crowded traffic conditions

This paper introduces an adaptive scheme for robustly detecting multiple preceding vehicles in crowded traffic conditions. The scheme focuses on issues frequently observed in the interpretation of traffic scenes recorded by cameras installed in vehicles: stable extraction of features and accurate classification in spite of the vehicle??s constant vibrations and dynamic changes in the distance between vehicles. To address these issues, we introduce the concept of integral features and a method of utilizing the scene geometry information. Each of the simple attributes, such as edges, shadows, and symmetry, is compiled in the window confined by the scene geometry to improve the expressiveness and robustness of the extracted features. The scene geometry information that is then estimated from the perspective view is extensively utilized in constituent system components, including not only feature extraction/integration but also neural network-based classification and distance-adaptive clustering. In addition, employing the Kalman filter along with a confidence measure makes the detection and tracking of potential vehicles robust. Experimental results prove that the system employing the proposed scheme detects and tracks multiple vehicles more effectively, even in crowded traffic conditions, with a lower rate of false positives.     

Cooling performance evaluation of height-downsized front end module for pedestrian protection

The front end module (FEM) needs enough space from hood to absorb the energy from any pedestrian collision. The FEM with downsized cooling module for pedestrian protection is important to reduce the severity of pedestrian injury. When a vehicle collision happens, the FEM with downsized cooling module is required to reduce the risk of injury to the upper legs of adults and the heads of children. In this study, the performance of cooling module to cool the engine was investigated under 25% height reduction. The heat dissipation and pressure drop characteristics have been experimentally studied with the variation of coolant flow rate, air inlet velocity and A/C operation (on/off) for the downsized cooling module. The results indicated that the cooling performance was about 94% level compared to that of the conventional cooling module. Therefore, we concluded that the cooling module had a good performance, and expected that the cooling module could meet the same cooling performance as conventional cooling module through optimization of components efficiency. This paper also deals with the development of FEM with downsized cooling module for the cooling performance level in vehicles. In the test of front end module??s heat dissipation performance, the prototype presented about 15% decrease under the conditions of all the vehicle speeds than that of conventional one.     

A Feasibility Study on Indirect Identification of Transmission Forces through Rubber Bushing in Vehicle Suspension System by Using Vibration Signals Measured on Links

This paper presents a feasibility study on using the rubber bushing itself as a sensor for the identification of transmission forces in vehicle suspension systems. The method starts from the idea that the transmission forces can be related to the deformation of the rubber bushing by an appropriate model and the deformation of the rubber bushing can be obtained by estimation of the relative vibration across the bushing. Simple theories are presented to deal with modeling of a given geometry of rubber bushing by a concentric spring and damper, correlating of measurements of the vibration on the links to the stiffness and damping parameters, and selection of the vibration measurement positions. Importance of the measurement position selection in relation to the measurement noise is illustrated by simulation studies. Then, validity of the proposed indirect approach will be shown by applications to a rear suspension system of dual link type.     

韩国350 km/h高速列车

1　概述汉城—釜山 30 0 km/ h的高速线路可望于 2 0 10年竣工。该工程的第一期称为 KTX(韩国特别快车 ) ,计划于 2 0 0 4年 4月投入运营。那时 ,汉城—大丘的新线建设将完工。剩余的大丘—釜山的 118km将建成2 5 k V6 0 Hz的电气化线路 ,用来运营以法国 TGV为基础的列车。由于     

Optimal design of an engine mount using an enhanced genetic algorithm with simplex method

This study provides an analysis of the applications of optimization routines for designing fluid mounts. After summarizing the concept of fluid mounts and their dynamic characteristics, we review the importance of the notch and resonance peak that occur in dynamic stiffness of fluid mounts. Fluid mounts are tuned for specific application so that their notch frequency coincides with the disturbance frequency, by selecting the proper parameters for the mount. Additionally, the mount parameters are selected such that the notch remains as deep (close to zero) as possible and the resonance peak is kept as short as possible. The notch depth and resonance peak present opposing requirements for the selection of mount parameters in the sense that lowering one will result in increasing the other. Using a bond graph model, this study will evaluate the effect of various parameters on the mount notch depth and resonance peak height characteristics. The results show that different parameters can have a varying effect on the notch frequency and depth, as well as the resonance frequency and peak height. The results of the study are extended by examining the effectiveness of two different optimization methods—namely, the Enhanced Genetic Algorithm (EGA) and Sequential Quadratic Programming (SQP)—for selecting the combination of parameters that can yield the deepest notch and shortest resonance peak. Using two different design cases, the study shows that SQP exhibits much more sensitivity to the initial conditions that are selected for the mount parameters than EGA. Both methods, however, are able to converge to an optimal solution within the constraints that are selected for the parameters. For both cases, EGA is able to converge to the set of parameters that provide a deep notch and a short resonance peak.     

Freight cars shunting impacts analysis using an improved dynamic model of friction draft gear

In this study, simulations of shunting impacts for groups of freight cars that include up to six cars are considered. The simulation technique employs a white-box improved dynamic model of friction draft gear considering all its components and detailed finite element models of the freight cars. The key differences between the one-to-one shunting impact and the impact of long groups of cars in terms of features of the draft gear deflections and the coupler force time history are discussed. We present an example of dynamic finite element analysis for the car body using the coupler force time history obtained from the shunting impact simulation.     

Dynamic Bandwidth Analysis for Coordinated Arterial Streets

A commonly used strategy for improving mobility along signalized arterials is to coordinate neighboring intersections to minimize vehicle stops by maximizing the duration of green bands, otherwise known as arterial bandwidth. Signal coordination has been researched, developed, and refined for five decades. In lieu of traditional methods that are based on the analysis of programmed green times (which assume all phases operate at their maximum settings), a dynamic bandwidth analysis method is presented that reproduces actual dynamic bandwidth durations using closed loop signal data. The analysis is intended to help assess the performance of semi-actuated coordinated signal systems on arterial streets. In addition, the study highlights the arterial progression benefits that result from changing coordinated intersection offsets based on optimizing the dynamic, rather than the programmed, bandwidths. Detailed analysis at three arterial sites revealed that coordinated green phase time distributions are complex and multimodal and cannot be represented by a single-valued statistic. Dynamic bandwidth analysis confirmed that programmed green bandwidth consistently underestimates the size of the actual dynamic bandwidth, and exhaustive search results highlighted the potential for further improvements in coordination. Future research will include field and simulation comparative studies and the development of efficient methods for dynamic bandwidth optimization.     

Characterizing Driver Stress Using Physiological and Operational Data from Real-World Electric Vehicle Driving Experiment

Electric Vehicle (EV) is becoming a viable and popular option, but the acceptance of the technology can be challenging and lead to an elevated driving stress. The existing studies on stress of vehicle driving has been mainly limited to the non-EVs or survey analysis. In this research, EV driving data of 40 subjects is analyzed, where each subject was asked to drive an EV over a 53 km course in a suburban city of South Korea. Physiological data including electroencephalogram (EEG) and eye-gazing were obtained along with vehicle operational data such as state of charge, altitude, and speed. The dataset was rich in information, but individual difference and nonlinear patterns made it extremely difficult to draw meaningful insights. As a solution, an information-theoretic framework is proposed to evaluate mutual information between physiological and operational data as well as the entropy of physiological data itself. The result shows two groups of subjects, one not showing much evidence of stress and the other exhibiting sufficient stress. Among the subjects who showed sufficient driving stress, 9 out of the top 10 high EEG-entropy drivers were female, one driver showed a strong pattern of range anxiety, and several showed patterns of uphill climbing anxiety.     

Using a k-means clustering algorithm to examine patterns of pedestrian involved crashes in Honolulu,Hawaii

The purpose of this paper is twofold: 1) to describe a statistical technique known as K-means clustering in term of its advantages and disadvantages in safety research; and, 2) to use this method to analyze spatial patterns of pedestrian-involved crashes in Honolulu. K-means, a partitioning clustering technique, provides a powerful tool for analyzing and visualizing spatial patterns. While there are other techniques, one of the advantages of the K-means approach is that it is a well established technique that has been used for many different applications other than traffic safety. In this paper, we compare it to hierarchical clustering techniques and suggest that both are useful in the arsenal of spatial analytic tools for safety research.