Effect of Traction Force Distribution Control on Vehicle Dynamics

The purpose of this study is to clarify vehicle dynamics effected by traction force distribution, not only between the front and rear wheels but also between the left and right wheels. Contribution of traction force distribution to vehicle turning performance was investigated using a mathematical simulation and an experimental vehicle. The results indicates that the control of traction control distribution between the left and right wheels greatly influences vehicle turning characteristics and improve the performance even in a marginal turning condition.     

Estimation of left-turning vehicle maneuvers for the assessment of pedestrian safety at intersections

Improving pedestrian safety at intersections remains a critical issue. Although several types of safety countermeasures, such as reforming intersection layouts, have been implemented, methods have not yet been established to quantitatively evaluate the effects of these countermeasures before installation. One of the main issues in pedestrian safety is conflicts with turning vehicles. This study aims to develop an integrated model to represent the variations in the maneuvers of left-turners (left-hand traffic) at signalized intersections that dynamically considers the vehicle reaction to intersection geometry and crossing pedestrians. The proposed method consists of four empirically developed stochastic sub-models, including a path model, free-flow speed profile model, lag/gap acceptance model, and stopping/clearing speed profile model. Since safety assessment is the main objective driving the development of the proposed model, this study uses post-encroachment time (PET) and vehicle speed at the crosswalk as validation parameters. Preliminary validation results obtained by Monte Carlo simulation show that the proposed integrated model can realistically represent the variations in vehicle maneuvers as well as the distribution of PET and vehicle speeds at the crosswalk.     

Influence of vehicular traffic on urban air quality – A case study of Hyderabad,India

In the present study, impact of vehicular traffic emissions on black carbon aerosol mass concentration, trace gases and ground reaching solar radiation were analyzed during nationwide truck strike of 5–12 January, 2009 over urban environment of Hyderabad, India. A significant reduction of about 57%, 60%, 40% and 50% was observed in black carbon, particulate matter, carbon monoxide and ozone respectively during nationwide truck strike period. Results of the study are important for source apportionment of pollutants as the strike created natural laboratory for studying the impact of diesel operated trucks on urban air quality.     

Practicability study on the suitability of artificial,neural networks for the approximation of unknown steering torques

For steer-by-wire systems, the steering feedback must be generated artificially due to the system characteristics. Classical control concepts require operating-point driven optimisations as well as increased calibration efforts in order to adequately simulate the steering torque in all driving states. Artificial neural networks (ANNs) are an innovative control concept; they are capable of learning arbitrary non-linear correlations without complex knowledge of physical dependencies. The present study investigates the suitability of neural networks for approximating unknown steering torques. To ensure robust processing of arbitrary data, network training with a sufficient volume of training data is required, that represents the relation between the input and target values in a wide range. The data were recorded in the course of various test drives. In this research, a variety of network topologies were trained, analysed and evaluated. Though the fundamental suitability of ANNs for the present control task was demonstrated.     

One-dimensional model on fuel penetration in diesel sprays with gas flow

In diesel engine, spray penetration is usually changed by in-cylinder gas flow. Accurate prediction on diesel spray with gas flow is important to the optimal design of diesel fuel injection system. This paper presents a theory investigation focusing on the penetration of diesel spray with gas flow. In order to understand the effect of gas flow on the penetration of diesel spray, a one-dimensional spray model is developed from an idealized diesel spray, which is able to predict the spray behavior under different gas flow conditions. The ambient gas flow is simplified as ideal flow that has only constant flow velocity along x-axial and y-axial directions of spray. The x-axial and y-axial directions are respectively defined as along and vertical spray directions. The main assumption is that the y-axial direction gas flow has no effect on the penetration of spray along x-axial direction. The principles of conservation of mass and momentum are used in the derivation. Momentum of in-cylinder air flow is also taken into consideration. Validation of the model at stable condition is achieved by comparing model predictions with experimental measurements of diesel spray without gas flow from Naber's experiments. Furthermore, CFD simulations on penetration of diesel spray with gas flow were performed with the commercial code AVL-fire. The onedimensional model is validated by the penetration results with gas flow from CFD calculation. Results show that a reasonable estimation of the spray evolution can be obtained for both with and without ambient gas flow conditions.     

Vehicle detection system design based on stereo vision sensors

Vehicle detection is a crucial issue for driver assistance system as well as for autonomous vehicle guidance function and it has to be performed with high reliability to avoid any potential collision. The vision-based vehicle detection systems are regarded promising for this purpose because they require little infrastructure on a highway. However, the feasibility of these systems in passenger car requires accurate and robust sensing performance. In this paper, a vehicle detection system using stereo vision sensors is developed. This system utilizes feature extraction, epipoplar constraint and feature matching in order to robustly detect the initial corresponding pairs. The proposed system can detect a leading vehicle in front and can estimate its position parameters such as the distance and heading angle. After the initial detection, the system executes the tracking algorithm for the vehicles in the lane. The proposed vehicle detection system is implemented on a passenger car and its performances are verified experimentally.     

Vibration transmission reduction from a centrifugal turbo blower in a fuel cell electric vehicle

This paper presents a multi-body flexible dynamic analysis of a centrifugal turbo blower for a fuel cell electric vehicle (FCEV) based on the application of computer-aided engineering (CAE) to predict the acceleration at the mount position of the blower. This predicted acceleration is validated by using the measured acceleration data. The numerical simulation for the multi-body flexible dynamics of the blower is used not only to identify the most effective mount among four mounts in an FCEV by controlling the complex stiffness of the isolator, but also to suggest the range of complex stiffness of the isolator at the most effective mount. This numerical simulation technology can be useful for the estimation of the variation of vibration transmission for the structural modification of the turbo blower.