Modelling nonlinear vehicle dynamics with neural networks

The nonlinear modelling ability of neural networks has been widely recognised as an effective tool to identify and control dynamic systems, with applications including nonlinear vehicle dynamics which this paper focuses on using multi-layer perceptron networks. Existing neural network literature does not detail some of the factors which effect neural network nonlinear modelling ability. This paper investigates into and concludes on required network size, structure and initial weights, considering results for networks of converged weights. The paper also presents an online training method and an error measure representing the network's parallel modelling ability over a range of operating conditions. Copyright © 2010 Inderscience Enterprises Ltd.

Design trade-offs for energy regeneration and control in vehicle suspensions

This paper investigates the fundamental trade-offs involved in designing energy-regenerative suspensions, in particular, focusing on efficiency of power extraction and its effect on vehicle dynamics and control. It is shown that typical regenerative devices making use of linear-to-rotational elements can be modelled as a parallel arrangement of an inerter and a dissipative admittance. Taking account of typical adjustable parameters of the generator, it is shown, for a given suspension damping coefficient, that the power efficiency ratio scales with inertance. For a typical passenger vehicle, it is shown that there is a feasible compromise, namely that good efficiency is achievable with an inertance value that is not detrimental to vehicle performance. A prototype is designed and tested with a resistive termination and experimental results show good agreement between ideal and experimental admittances. The possibility to use dynamic (rather than purely resistive) loads to improve vehicle control without limiting the energy recovery is discussed. © 2013 Copyright Taylor and Francis Group, LLC.

Minimum maneuver time calculation using convex optimization

The problem of calculating the minimum lap or maneuver time of a nonlinear vehicle, which is linearized at each time step, is formulated as a convex optimization problem. The formulation provides an alternative to previously used quasi-steady-state analysis or nonlinear optimization. Key steps are: the use of model predictive control; expressing the minimum time problem as one of maximizing distance traveled along the track centerline; and linearizing the track and vehicle trajectories by expressing them as small displacements from a fixed reference. A consequence of linearizing the vehicle dynamics is that nonoptimal steering control action can be generated, but attention to the constraints and the cost function minimizes the effect. Optimal control actions and vehicle responses for a 90 deg bend are presented and compared to the nonconvex nonlinear programming solution. Copyright © 2013 by ASME.

Interaction between heavy vehicles and roads

This paper discusses road damage caused by heavy commercial vehicles. Chapter 1 presents some important terminology and a brief historical review of road construction and vehicle-road interaction, from ancient times to the present day. The main types of vehicle-generated road damage, and the methods that are used by pavement engineers to analyze them are discussed in Chapter 2. Attention is also given to the main features of the response of road surfaces to vehicle loads and mathematical models that have been developed to predict road response. Chapter 3 reviews the effects on road damage of vehicle features which can be studied without consideration of vehicle dynamics. These include gross vehicle weight, axle and tire configurations, tire contact conditions and static load sharing in axle group suspensions. The dynamic tire forces generated by heavy vehicles are examined in Chapter 4. The discussion includes their simulation and measurement, their principal characteristics, the effects of tires and suspension design on dynamic forces, and the potential benefits of using advanced suspensions for minimizing dynamic tire forces. Chapter 5 discusses methods for estimating the effects of dynamic tire forces on road damage. The two main approaches are either to examine the statistics of the forces themselves; or to calculate the response of a pavement model to the forces, and to calculate the resulting wear using a material damage model. The issues involved in assessing vehicles for 'road friendliness' are discussed in Chapter 6. Possible assessment methods include measuring strains in an instrumented pavement traversed by the vehicle, measuring dynamic tire forces, or measuring vehicle parameters such as the 'natural frequency' and 'damping ratio'. Each of these measurements involves different assumptions and analysis methods for converting the results into some measure of road damage. Chapter 7 includes a summary of the main conclusions of the paper and recommendations for tire and suspension design, road design and construction, and for vehicle regulations.

Identification of the steering control behaviour of five test subjects following a randomly curving path in a driving simulator

The paper is concerned with the identification of theoretical preview steering controllers using data obtained from five test subjects in a fixed-base driving simulator. An understanding of human steering control behaviour is relevant to the design of autonomous and semi-autonomous vehicle controls. The driving task involved steering a linear vehicle along a randomly curving path. The theoretical steering controllers identified from the data were based on optimal linear preview control. A direct-identification method was used, and the steering controllers were identified so that the predicted steering angle matched as closely as possible the measured steering angle of the test subjects. It was found that identification of the driver's time delay and noise is necessary to avoid bias in identification of the controller parameters. Most subjects' steering behaviour was predicted well by a theoretical controller based on the lateral/yaw dynamics of the vehicle. There was some evidence that an inexperienced driver's steering action was better represented by a controller based on a simpler model of the vehicle dynamics, perhaps reflecting incomplete learning by the driver. Copyright © 2014 Inderscience Enterprises Ltd.

A path-following driver-vehicle model with neuromuscular dynamics, including measured and simulated responses to a step in steering angle overlay

An existing driver-vehicle model with neuromuscular dynamics is improved in the areas of cognitive delay, intrinsic muscle dynamics and alpha-gamma co-activation. The model is used to investigate the influence of steering torque feedback and neuromuscular dynamics on the vehicle response to lateral force disturbances. When steering torque feedback is present, it is found that the longitudinal position of the lateral disturbance has a significant influence on whether the drivers reflex response reinforces or attenuates the effect of the disturbance. The response to angle and torque overlay inputs to the steering system is also investigated. The presence of the steering torque feedback reduced the disturbing effect of torque overlay and angle overlay inputs. Reflex action reduced the disturbing effect of a torque overlay input, but increased the disturbing effect of an angle overlay input. Experiments on a driving simulator showed that measured handwheel angle response to an angle overlay input was consistent with the response predicted by the model with reflex action. However, there was significant intra-and inter-subject variability. The results highlight the significance of a drivers neuromuscular dynamics in determining the vehicle response to disturbances. © 2012 Copyright Taylor and Francis Group, LLC.