Development of a remotely-controlled electric vehicle with characterization of the ground grip
type: CreativeWork
description: This thesis focuses on traction control techniques for electric vehicles with independently driven wheels . The aim is to maximise the grip of each wheel with the ground, improving the performance as well as the stability of the whole vehicle. Hence the estimation of the friction characteristic between tyres and ground is addressed . Accurate estimat ion is required not only to control the wheels at their best working condition but also to predict their behaviour for future manoeuvres. This information could be used to calculate the braking distance or to evaluate the maximum attainable speed during cornering . A detailed knowledge of the friction characteristic would substantially improve the functionality of anti-lock braking system (ABS), anti-slip regulation (ASR), electronic stability control (ESC) and adaptive cruise control (ACC) . Estimation of ground characteristics and traction control for electric vehi­cles have been studied before, although previous research generally relies on driving manoeuvres at the limit of adhesion to obtain meaningful information about the maximum grip offered by the ground. This is not suitable during safe driving on public roads and the present thesis addresses the problem of constantly monitoring the road conditions, and forecasting the loss of adhesion instead of waiting for it . Furthermore, my approach is robust against external forces and can be applied to vehicles on tilted grounds. Hence my novel approach supersedes previous studies that assumed the vehicle on a flat surface, mostly neglecting the effects of rolling resistance and aerodynamic drag. I also propose a framework to take into cons.ideration dynamic effects such as iner­ tial forces and the distribution of the gravitational force. Taking these effects into account would lead to a more reliable estimation, particularly effective on steep or bumpy roads where adhesion loss is more likely to happen . Some of this work resulted in the publication of an IEEE confere…
abstract: This thesis focuses on traction control techniques for electric vehicles with independently driven wheels . The aim is to maximise the grip of each wheel with the ground, improving the performance as well as the stability of the whole vehicle. Hence the estimation of the friction characteristic between tyres and ground is addressed . Accurate estimat ion is required not only to control the wheels at their best working condition but also to predict their behaviour for future manoeuvres. This information could be used to calculate the braking distance or to evaluate the maximum attainable speed during cornering . A detailed knowledge of the friction characteristic would substantially improve the functionality of anti-lock braking system (ABS), anti-slip regulation (ASR), electronic stability control (ESC) and adaptive cruise control (ACC) . Estimation of ground characteristics and traction control for electric vehi­cles have been studied before, although previous research generally relies on driving manoeuvres at the limit of adhesion to obtain meaningful information about the maximum grip offered by the ground. This is not suitable during safe driving on public roads and the present thesis addresses the problem of constantly monitoring the road conditions, and forecasting the loss of adhesion instead of waiting for it . Furthermore, my approach is robust against external forces and can be applied to vehicles on tilted grounds. Hence my novel approach supersedes previous studies that assumed the vehicle on a flat surface, mostly neglecting the effects of rolling resistance and aerodynamic drag. I also propose a framework to take into cons.ideration dynamic effects such as iner­ tial forces and the distribution of the gravitational force. Taking these effects into account would lead to a more reliable estimation, particularly effective on steep or bumpy roads where adhesion loss is more likely to happen . Some of this work resulted in the publication of an IEEE confere…
author: Cecotti, M
language: en
date published: 2013
date modified: 2026-07-24T03:44:38Z
provider: Oxford Brookes University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Oxford Brookes University