Robust and predictable brake force distribution for heavy vehicles

Background and Objective:
Motion control for autonomous vehicles is concerned with controlling the driving dynamics of the whole vehicle combination. It has the task to control all the available actuators in a vehicle to safely and efficiently follow the intended path along the road. One of the major challenges is ensuring and communicating a predictable behavior which other parts of the system can rely on.
Scope and Method:
A safe and predictable behavior in lateral and longitudinal behavior while braking in a straight line and corners, is heavily influenced by the brake force distribution. While an optimal solution is readily found for single vehicles with two axles, obtaining a solution for vehicle combinations is less straight forward. Driven by a need for simplicity and predictability, the brake force distribution nonetheless needs to be based on clear rules.
In the course of the thesis, these rules shall be derived for vehicle combinations, starting from a single unit, investigating tractor/semi-trailer combinations, and vehicle trains. First, straight line braking shall be investigated, later also the influence of lateral distribution while braking in turn shall be considered.
As vehicle parameters never can be known with absolute certainty, the influence of uncertainty on the resulting vehicle dynamics under braking shall be investigated, e.g. influences of center of gravity height and mass uncertainties. Based on a thorough literature review, equations governing the brake force distribution shall be derived. The resulting control laws shall be analyzed formally for robustness and stability, as well as in full-vehicle simulations and in vehicle tests.
The duration of the study will be 20 weeks (30 ETCs, MSc thesis). The thesis can also be completed in a team of two – please still send in individual applications in this case. The work will be carried out at Volvo Group. The outcome has potential to be published in a scientific journal or conference (depending on quality and ambitions). Suitable background is vehicle dynamics, control theory and signal processing. Knowledge of Matlab/Simulink or Mathematica would be beneficial.
Language: English
Starting date: January 2020
Number of students: 1-2

Tutor
Thorsten Helfrich, PhD, +46 76 5538 152

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