State and Parameter Estimation in Vehicular Systems

Robert Wragge-Morley

Dr. Guido Herrmann

University of Bristol

UKACC PhD Presentation Showcase

UKACC PhD Presentation Showcase Slide 2

Introduction

Increased Automation in Vehicular Systems Marketplace demand for more advanced driver aids

• Increased Control Dependency• Increased capabilities

More detailed knowledge of vehicle parameters is required• Particularly for properties that are difficult to measure directly

Vehicle Mass and Road Gradient• Coupled• Other Losses

UKACC PhD Presentation Showcase Slide 3

Current Project Status

Developing Parameter Estimator Composite Adaptation Algorithms

• Based on standard adaptive control theory

Information fusion

Activities Theory Development Scaling from lab car to real car Data Collection

• Vehicle Bus• GPS

Adjustable Model

mg

M, ωM, ω

v

Parameter Adaptation Algorithm

Estimated

Parameters

u(t)

y(t)

ε(t)

ŷ(t)-

+

Θ(t)̂�

UKACC PhD Presentation Showcase Slide 4

Successes and Future Work

Effective Mass and Gradient Estimation performed With Simulation Using data gathered from real vehicle

Principle of Information fusion effective in the context of this estimation problem

Continuation of Work Information fusion Modifications to Novel Algorithms On-line, in vehicle, estimation

trials Investigate the impact of

embedded systems architecture on algorithm performance