Roll- and pitch-plane-coupled hydro-pneumatic suspension. Part 2: dynamic response analyses

In the first part of this study, the potential performance benefits of fluidically coupled passive suspensions were demonstrated through analyses of suspension properties, design flexibility and feasibility. In this second part of the study, the dynamic responses of a vehicle equipped with different configurations of fluidically coupled hydro-pneumatic suspension systems are investigated for more comprehensive assessments of the coupled suspension concepts. A generalised 14 degree-of-freedom nonlinear vehicle model is developed and validated to evaluate vehicle ride and handling dynamic responses and suspension anti-roll and anti-pitch characteristics under various road excitations and steering/braking manoeuvres. The dynamic responses of the vehicle model with the coupled suspension are compared with those of the unconnected suspensions to demonstrate the performance potential of the fluidic couplings. The dynamic responses together with the suspension properties suggest that the full-vehicle-coupled hydro-pneumatic suspension could offer considerable potential in realising enhanced ride and handling performance, as well as improved anti-roll and anti-pitch properties in a very flexible and energy-saving manner.     

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.     

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.     

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.     

Multi-objective control of a full-car model using linear-matrix-inequalities and fixed-order optimisation

This paper studies multi-objective control of a full-vehicle suspension excited by random road disturbances. The control problem is first formulated as a mixed ?₂/?_∞ synthesis problem and an output-feedback solution is obtained by using linear-matrix-inequalities. Next, the multi-objective control problem is re-formulated as a non-convex and non-smooth optimisation problem with controller order restricted to be less than the vehicle model order. For a range of orders, controllers are synthesised by using the HIFOO toolbox. The efficacy of the presented procedures are demonstrated by several design examples.     

Total dynamic response of a PSS vehicle negotiating asymmetric road excitations

A planar suspension system (PSS) is a novel automobile suspension system in which an individual spring–damper strut is implemented in both the vertical and longitudinal directions, respectively. The wheels in a vehicle with such a suspension system can move back and forth relative to the chassis. When a PSS vehicle experiences asymmetric road excitations, the relative longitudinal motion of wheels with respect to the chassis in two sides of the same axle are not identical, and thus the two wheels at one axle will not be aligned in the same axis. The total dynamic responses, including those of the bounce, pitch and the roll of the PSS vehicle, to the asymmetric road excitation may exhibit different characteristics from those of a conventional vehicle. This paper presents an investigation into the comprehensive dynamic behaviour of a vehicle with the PSS, in such a road condition, on both the straight and curved roads. The study was carried out using an 18 DOF full-car model incorporating a radial-spring tyre–ground contact model and a 2D tyre–ground dynamic friction model. Results demonstrate that the total dynamic behaviour of a PSS vehicle is generally comparable with that of the conventional vehicle, while PSS exhibits significant improvement in absorbing the impact forces along the longitudinal direction when compared to the conventional suspension system. The PSS vehicle is found to be more stable than the conventional vehicle in terms of the directional performance against the disturbance of the road potholes on a straight line manoeuvre, while exhibiting a very similar handling performance on a curved line.     

Real-time model predictive control of connected electric vehicles

ABSTRACT

Electric Vehicles (EVs) motors develop high torque at low speeds, resulting in a high rate of acceleration with the added advantage of being fitted with smaller gearboxes. However, a rapid rise of torque in EVs fitted with central drive powertrains can create undesired torsional oscillations, which are influenced by wheel slip and flexibility in the halfshaft. These torsional oscillations in the halfshaft lead to longitudinal oscillations in the vehicle, thus creating problems with regard to comfort and drivability. The significance of using wheel slip in addition to halfshaft torsion for design of anti-jerk controllers for EVs has already been highlighted in our previous research. In this research, we have designed a look-ahead model predictive controller (LA-MPC) that calculates the required motor torque demand to meet the dual objectives of increased traction and anti-jerk control. The designed LA-MPC will improve drivability and energy consumption in connected EVs. The real-time capability of the LA-MPC has been demonstrated through hardware-in-the-loop experiments. The performance of the LA-MPC has been compared to other controllers presented in the literature. A validated high-fidelity longitudinal-dynamics model of the Rav4EV, which is the test vehicle of our research has been used to evaluate the controller.