The IMMa optimisation algorithm without control input parameters

The IMMa optimisation algorithm (IOA) consists of a heuristic method based on a differential evolution algorithm for choosing the Magic Formula (MF) tyre model parameters. In a previous paper, we demonstrated that the IOA improved the searching procedure of optimum MF parameters with respect to the starting value optimisation (SVO) methods. But we had to introduce some control input parameters that were fixed during the running process. Now, the new version does not require control input variables to be chosen by the user. That is, we use an algorithm with self-adapting control parameters and it continues being easy to use, robust and fast. Hence, users do not need any kind of knowledge to use the IOA.     

A passenger car driver model for higher lateral accelerations

Due to increasing demands for time and cost efficient vehicle and driver assistant systems development, numerical simulation of closed-loop manoeuvres becomes increasingly important. Thus, the driver has to be considered in the modelling. On the basis of a two-layer approach to model a driver's steering behaviour, the field of application is extended to higher lateral accelerations in this study. An analytical method to determine the driver parameters is presented, which is based on the two-wheel vehicle model. The simulation results are determined using a full vehicle model including all essential nonlinearities. Standard manoeuvres in the nonlinear range of vehicle handling behaviour are performed. A cornering manoeuvre is chosen to show the characteristics of the proposed driver model.     

Dynamic model for ride comfort evaluations of the rubber-tired light rail vehicle

The dynamic model was developed to evaluate vibration accelerations and ride comforts during the running of the Korean-standardised rubber-tired light rail vehicle. Ride comfort indexes were analysed and tested in accordance with UIC 513R by using the dynamic model and the actual vehicle in the test track. Based on the comparisons between analysis results and test results, the validity of the developed dynamic model was evaluated. It was verified whether or not the developed Korean-standardised rubber-tired light rail vehicle met the specified target specification on ride comfort. In addition, the influence of the wearing of guide wheels on ride comfort was estimated.     

Multibody dynamics modelling of the freight train bogie system

Previous work in the railway technology laboratory at Virginia Polytechnic Institute and State University (Virginia Tech) focused on better capturing the dynamics of the friction wedge, modelled using three-dimensional rigid body dynamics with unilateral contact conditions. The current study extends the previous work to a half-bogie model treated as an application of multibody dynamics with unilateral contact to model the friction wedge interactions with the bolster and the sideframe. The half-bogie model was derived using MATLAB and functions as a three dimensional, dynamic, and multibody dynamics model comprised of four rigid bodies: a bolster, two friction wedges, and a sideframe assembly. This expanded model allows each wedge four degrees of freedom: vertical displacement, longitudinal displacement (between the bolster and sideframe), pitch (rotation around the lateral axis), and yaw (rotation around the vertical axis). The bolster and the sideframe are constrained to have only the vertical degree of freedom. The geometry of these bodies can be adjusted for various simulation scenarios. The bolster can be initialised with a pre-defined yaw (rotation around the vertical axis) and the sideframe may be initialised with a pre-defined pitch/toe (rotation around the lateral axis). The results of the multibody dynamics in half-bogie model simulation are shown in comparison with results from NUCARS^®, an industry standard in train-modelling software, for similar inputs.     

Application of time-variant predictive control to modelling driver steering skill

The paper addresses the need for improved mathematical models of human steering control. A multiple-model structure for a driver's internal model of a nonlinear vehicle is proposed. The multiple-model structure potentially offers a straightforward way to represent a range of driver expertise. The internal model is combined with a model predictive steering controller. The controller generates a steering command through the minimisation of a cost function involving vehicle path error. A study of the controller performance during an aggressive, nonlinear steering manoeuvre is provided. Analysis of the controller performance reveals a reduction in the closed-loop controller bandwidth with increasing tyre saturation and fixed controller gains. A parameter study demonstrates that increasing the multiple-model density, increasing the weights on the path error, and increasing the controller knowledge range all improved the path following accuracy of the controller.     

A nonlinear virtual rider for motorcycles

This work presents a virtual rider for the guidance of a nonlinear motorcycle model. The target motion is defined in terms of roll angle and speed. The virtual rider inputs are the steering torque, the rear-wheel driving/braking torque and front-wheel braking torque. The virtual rider capability is assessed by guiding the nonlinear motorcycle model in demanding manoeuvres with roll angles of 50° and longitudinal accelerations up to 0.8 g. Considerations on the effective preview distance used by the virtual rider are included.     

On the equivalent wheelbase of a three-axle vehicle

The steady-state handling properties of a rigid vehicle with a tandem rear axle configuration are developed. This work uses conventions resulting in a parsimonious characterisation of steady-state handling of such three-axle vehicles that is shown to be a simple extension of the well-known two-axle bicycle model. Specifically the concepts of understeer and wheelbase are developed for a three-axle vehicle, and shown to play the same role in characterising vehicle handling as they do in the well-known two-axle vehicle model. An equivalent wheelbase of a three-axle vehicle is expressed in terms of vehicle geometry and cornering stiffness of each axle. The model developed in this work is reconciled with previous models that make use of simplifying assumptions found in the literature.     

Fault-tolerant control of heavy-haul trains

The fault-tolerant control (FTC) of heavy-haul trains is discussed on the basis of the speed regulation proposed in previous works. The fault modes of trains are assumed and the corresponding fault detection and isolation (FDI) are studied. The FDI of sensor faults is based on a geometric approach for residual generators. The FDI of a braking system is based on the observation of the steady-state speed. From the difference of the steady-state speeds between the fault system and the faultless system, one can get fault information. Simulation tests were conducted on the suitability of the FDIs and the redesigned speed regulators. It is shown that the proposed FTC does not explicitly worsen the performance of the speed regulator in the case of a faultless system, while it obviously improves the performance of the speed regulator in the case of a faulty system.     

Non-stationary random vibration analysis of three-dimensional train–bridge systems

The quarter car model has been used extensively to study the benefits of active, semi-active and passive suspensions. Despite the evident simplicity of the model, the insights obtained from this model have been found to have counterparts in half- and full-car suspension models. Among the most interesting results of the analysis of the quarter car are the relationships among certain transfer function and invariant points in the frequency response functions. These results are of great interest for the application of linear control techniques to the design of active suspensions and the optimisation of linearised passive suspensions. This paper attempts to show why some of the limitations implied by the model are less absolute than they at first seem.     

Virtual test rig to improve the design and optimisation process of the vehicle steering and suspension systems

A virtual test rig is presented using a three-dimensional model of the elasto-kinematic behaviour of a vehicle. A general approach is put forward to determine the three-dimensional position of the body and the main parameters which influence the handling of the vehicle. For the design process, the variable input data are the longitudinal and lateral acceleration and the curve radius, which are defined by the user as a design goal. For the optimisation process, once the vehicle has been built, the variable input data are the travel of the four struts and the steering wheel angle, which is obtained through monitoring the vehicle. The virtual test rig has been applied to a standard vehicle and the validity of the results has been proven.