State and Parameter Estimation in Vehicular Systems Robert Wragge-Morley Dr. Guido Herrmann University of Bristol UKACC PhD Presentation Showcase

Slide 2 Introduction  Increased Automation in Vehicular Systems  Marketplace demand for more advanced driver aids Increased Control DependencyIncreased Control Dependency Increased capabilitiesIncreased capabilities  More detailed knowledge of vehicle parameters is required Particularly for properties that are difficult to measure directlyParticularly for properties that are difficult to measure directly  Vehicle Mass and Road Gradient CoupledCoupled Other LossesOther Losses

UKACC PhD Presentation Showcase Slide 3 Current Project Status  Developing Parameter Estimator  Composite Adaptation Algorithms Based on standard adaptive control theoryBased on standard adaptive control theory  Information fusion  Activities  Theory Development  Scaling from lab car to real car  Data Collection Vehicle BusVehicle Bus GPSGPS Adjustable Model mg M, ω 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