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Model-Based Vehicle Dynamics Control for Active Safety

Schofield, Brad LU (2008) In PhD Theses TFRT-1083.
Abstract
The functionality of modern automotive vehicles is becoming increasingly

dependent on control systems. Active safety is an area in which control

systems play a pivotal role. Currently, rule-based control algorithms are

widespread throughout the automotive industry. In order to improve per-

formance and reduce development time, model-based methods may be em-

ployed.

The primary contribution of this thesis is the development of a ve-

hicle dynamics controller for rollover mitigation. A central part of this

work has been the investigation of control allocation methods, which are

used to transform high-level controller commands to actuator inputs in

the... (More)
The functionality of modern automotive vehicles is becoming increasingly

dependent on control systems. Active safety is an area in which control

systems play a pivotal role. Currently, rule-based control algorithms are

widespread throughout the automotive industry. In order to improve per-

formance and reduce development time, model-based methods may be em-

ployed.

The primary contribution of this thesis is the development of a ve-

hicle dynamics controller for rollover mitigation. A central part of this

work has been the investigation of control allocation methods, which are

used to transform high-level controller commands to actuator inputs in

the presence of numerous constraints. Quadratic programming is used to

solve a static optimization problem in each sample. An investigation of the

numerical methods used to solve such problems was carried out, leading

to the development of a modified active set algorithm.

Vehicle dynamics control systems typically require input from a num-

ber of supporting systems, including observers and estimation algorithms.

A key parameter for virtually all VDC systems is the friction coefficient.

Model-based friction estimation based on the physically-derived brush

model is investigated. (Less)
Please use this url to cite or link to this publication:
author
supervisor
opponent
  • Professor Johansen, Tor Arne, Norwegian University of Science and Technology, Norway
organization
publishing date
type
Thesis
publication status
published
subject
keywords
Control Allocation, Vehicle Dynamics Control, Friction Estimation, Model-Based Control Design
in
PhD Theses
volume
TFRT-1083
pages
186 pages
publisher
Department of Automatic Control, Lund Institute of Technology, Lund University
defense location
Room M:B, M-building, Ole Römers väg 1, Faculty of Engineering, Lund University
defense date
2008-09-19 10:15
ISSN
0280-5316
language
English
LU publication?
yes
id
3349cd27-9ed8-483e-8d17-2d0b25f03b1c (old id 1219680)
date added to LUP
2008-08-27 07:53:30
date last changed
2016-09-19 08:44:47
@phdthesis{3349cd27-9ed8-483e-8d17-2d0b25f03b1c,
  abstract     = {The functionality of modern automotive vehicles is becoming increasingly<br/><br>
dependent on control systems. Active safety is an area in which control<br/><br>
systems play a pivotal role. Currently, rule-based control algorithms are<br/><br>
widespread throughout the automotive industry. In order to improve per-<br/><br>
formance and reduce development time, model-based methods may be em-<br/><br>
ployed.<br/><br>
The primary contribution of this thesis is the development of a ve-<br/><br>
hicle dynamics controller for rollover mitigation. A central part of this<br/><br>
work has been the investigation of control allocation methods, which are<br/><br>
used to transform high-level controller commands to actuator inputs in<br/><br>
the presence of numerous constraints. Quadratic programming is used to<br/><br>
solve a static optimization problem in each sample. An investigation of the<br/><br>
numerical methods used to solve such problems was carried out, leading<br/><br>
to the development of a modified active set algorithm.<br/><br>
Vehicle dynamics control systems typically require input from a num-<br/><br>
ber of supporting systems, including observers and estimation algorithms.<br/><br>
A key parameter for virtually all VDC systems is the friction coefficient.<br/><br>
Model-based friction estimation based on the physically-derived brush<br/><br>
model is investigated.},
  author       = {Schofield, Brad},
  issn         = {0280-5316},
  keyword      = {Control Allocation,Vehicle Dynamics Control,Friction Estimation,Model-Based Control Design},
  language     = {eng},
  pages        = {186},
  publisher    = {Department of Automatic Control, Lund Institute of Technology, Lund University},
  school       = {Lund University},
  series       = {PhD Theses},
  title        = {Model-Based Vehicle Dynamics Control for Active Safety},
  volume       = {TFRT-1083},
  year         = {2008},
}