PhD Thesis

Model-Based Vehicle Dynamics Control for Active Safety

Brad Schofield


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.


Vehicle Dynamics Control, Vehicle Modeling, Vehicle Rollover, Friction Estimation, Control Allocation

PhD Thesis ISRN LUTFD2/TFRT--1083--SE, Department of Automatic Control, Lund University, Sweden, September 2008.

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