Model-Based Vehicle Dynamics Control for Active Safety

Sammanfattning: 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.