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Three-dimensional (3D) Finite element (FE) tyre models have been widely used for tyre design, vehicle design and dynamic investigations. Such tyre models have the inherent advantage of covering a wide range of tyre modelling issues such as the detailed tyre geometry and material composition, in addition to an extensive coverage of tyre operational conditions such as the static preload, inflation pressure and driving speed. Although tyre vibration behaviour, in different frequency ranges are of general interest, both for the vehicle interior and exterior noise, the present study is limited to a frequency of 100 Hz which is prevalent in most road induced (Noise, Vibration, Harshness) NVH ride and handling problems. This study investigates tyre vibration behaviour using a proprietary FE code. Such investigation plays an important role in the study of vehicle dynamics.

This paper presents a statistical characterisation of the effects of variations in vehicle parameters on vehicle road load data using a quarter vehicle as a case study. A model of a quarter vehicle test rig constructed from a commercial SUV is created in a multi-body dynamics (MBD) simulation environment to reproduce the real-life behaviour of the SUV. The model is thereafter validated by correlating the response data collected from both the model and laboratory test rig to the same road input. In order to ensure that only the effects of the variation of the vehicle parameters are captured, a time domain drive signal for a kerb strike road event on the physical vehicle is generated from the proving ground data collected during durability testing of the vehicle.

This research proposes the use of Artificial Neural Networks (ANN) to predict the road input for road load data generation for variants of a vehicle as vehicle parameters are modified. This is important to the design engineers while the vehicle variant is still in the initial stages of development, hence no prototypes are available and accurate proving ground data acquisition is not possible. ANNs are, with adequate training, capable of representing the complex relationships between inputs and outputs. This research explores the implementation of the ANN to predict road input for vehicle variants using a quarter vehicle test rig. The training and testing data for this research are collected from a validated quarter vehicle model.

The development of intelligent tire technology from concept to application covers multi-disciplinary fields. During the course of development, the computational method can play a significant role in understanding tire behavior, assisting in the design of the intelligent tire prototype system and in developing tire parameters estimation algorithm, etc. In this paper, a finite element tire model was adopted for developing a strain-based intelligent tire system. The finite element tire model was created considering the tire's composite structure and nonlinear properties of its constituent materials, and the FE model was also validated by physical tests. The FE model is used to study tire strain characteristics by steady state simulation for straight line rolling, traction and braking, as well as cornering. Tire loading conditions were estimated by feature extraction and data fitting.

Sloped medians provide a run-off area for errant vehicles so that they can be safely stopped off-road with or without barriers placed in the sloped median. However, in order to optimize the design of sloped medians and the containment barriers, it is essential to accurately model the behavior of vehicles on such sloped terrain surfaces. In this study, models of a vehicle fleet comprising a small sedan and a pickup truck and sloped terrain surface are developed in CarSim™ to simulate errant vehicle behavior on sloped median. Full-scale crash tests were conducted using the vehicle fleet driven across a 9.754 meters wide median with a 6:1 slope at speeds ranging from 30 to 70 km/h. Measured data such as the lateral accelerations of the vehicle as well as chassis rotations (roll and pitch) were synchronized with the vehicle motion obtained from the video data.

Disc brake noise is recognized as a major problem of the automotive industry. Various experimental and numerical techniques have been developed to model the noisy brake and investigate possible solutions. Developing a virtual model of the disc brake which can accurately reproduce the behavior of the brake unit under different conditions is a considerable step forward towards reaching this goal. Among various aspects of the analytical model of a disc brake, application of the correct value of damping based on the material properties and functional frequency range of each component is a significant factor in ensuring correct prediction of the brake system behavior. Complex Eigenvalue Analysis is well established as a tool for predicting brake instabilities which can potentially lead to brake noise. However, it is known to over-predict instabilities i.e. predict instabilities which do not occur in the real brake system.

The increasing demand for ground vehicles safety has led to the requirements for effective and accurate vehicle active safety systems, such as Anti-lock Braking System (ABS) and Traction Control System (TCS). As the only link between vehicle and road, the tire is in a very privileged position in a vehicle to acquire vital information which could be used to improve vehicle dynamics control systems. Hence the requirement for an “intelligent tire” that incorporates a system that is able to sense the tire and road conditions, and then interact with the vehicle dynamics control system to optimize the vehicle performance as well as provide warning information to the driver. In this paper, an experimental tire strain-based system is used to establish the proof of concept of an intelligent tire prototype. This experimental system comprises a data acquisition device and three rectangular rosette strain sensors, which can measure the tire surface dynamic strain in real time.

Vibration testing is carried out as part of the sign-off procedure for vehicle body and power unit mounted components to ensure that the components can survive their working life without damage. The paper describes the development of numerical techniques to replicate the vibration testing of a Diesel Engine EGR Coolant Rail. A Finite element (FE) model of the coolant rail was developed and validated. Subsequently, detailed FE models of the rubber hoses were developed and added to the coolant rail model in order to carry out a forced response analysis of the structure. Results from physical tests of the structure showed good agreement with the simulation results. A method is proposed for including the effect of the rubber hoses in the FE models of body and power unit mounted components using spring-dashpot elements. This is to avoid modelling the hoses in detail with resultant savings in computational costs.

The use of accurate tire material properties is a major requirement for conducting a successful tire analysis using finite element method (FEM). Obtaining these material properties however poses a major challenge for tire modelers and researchers due to the complex nature of tire material and associated proprietary protections of constituent material properties by tire manufactures. In view of this limitation, a simple and effective procedure for generating tire materials data used in tire finite element analysis (FEA) is presented in this paper. All the tire test specimens were extracted from a tire product based on special considerations such as specimen dimension and shape, test standard, precondition of specimen and test condition for cords. The required material properties of tire rubber component, including hyperelasticity and viscoelasticity were obtained using simple uni-axial tension test.

Computer simulation has been used in vehicle dynamics studies for decades. Advances in the science of vehicle dynamics and far more improved computer technology now enable automobile manufacturers to get closer to zero-prototype production than ever before. From the computer simulation point of view, having a general path generator can present researchers with great flexibility in defining vehicle handling dynamics tests. The process used for generating the vehicle's path in this study is referred to as ‘path planning’ because of some distinctive approaches used. A vehicle model is used in conjunction with a fuzzy pilot model to generate the vehicle's path through a number of specified points through which the vehicle must pass. The simulation is carried out in the Matlab© programming environment using a Simulink© vehicle model under Fuzzy logic control intended to imitate how a real driver would steer the vehicle to create a path through the specified points.