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Seminars, Lectures, Tutorials, Practical Assessments, Independent study
A first or upper second class honours degree or equivalent in engineering or physical sciences. In exceptional circumstances, students may be accepted with extensive experience in the automotive industry.
The course aims to equip you with the knowledge and skills to analyse and implement intelligent features and functions on road vehicles, within the context of the fundamentals of control, vehicle dynamic performance and simulation capability.
The course consists of three modules: Vehicle Dynamics, Vehicle Electrical Systems Integration and Autonomous Vehicle Systems. Vehicle Dynamics The aim of the module is to develop an understanding of vehicle dynamics concepts, from the fundamentals of ride dynamics, through to development of a vehicle handling model and objective testing on a vehicle proving ground. The module also concentrates on core areas of tyres, suspension and steering. Tyres: — Principles of the brush tyre model; the combined slip Pacejka Model — Suspension and steering; roll centre location, suspension derivatives (camber / scrub), forces and moments in the steering system, suspension jacking and anti-squat / anti-drive effects Modelling: — Use of state-space for linear models; steady-state cornering via the bicycle handling model; understeer gradient, oversteer, critical speed. — Development of a 6DOF nonlinear handling model in Matlab / Simulink comprising nonlinear tyre, lateral load transfer and roll moment distribution Computer Lab Session: — Ride modelling; analysis of simulated open-loop handling response; use of state feedback for longitudinal control Vehicle Testing at HORIBA MIRA Proving Ground: — Standard objective handling tests; vehicle test specification and execution; risk assessment; data analysis. Vehicle Electrical Systems Integration Electrical Systems: — Analysis of circuits — Basic design for electromagnetic compatibility — Introduction to vehicle electrical architecture — Introduction to application of power electronics — Controller Area Network (CAN bus) Sensors: — Basic sensors — Principles and capability - GPS, IMU, Camera, Radar, Lidar Safety and Risk: — Risk assessment methods — Reliability assessment methods — Introduction to functional safety methods Autonomous Vehicle Systems — Introduction of autonomous vehicle systems Techniques: — Control and optimization techniques — Path planning and collision avoidance — Path following — Sensor error modelling — Sensor fusion and Kalman filtering Autonomous Vehicle Path Planning: — Path planning principles — Path following algoriths Sensor Fusion and Situation Awareness: — Kalman filtering methods — Vehicle localisation (position and orientation) — External environment sensing (object detection and tracking) Autonomous Functions: — Applications and case studies Advanced Topics/Applications: — Autonomous emergency braking — Moving object tracking — Rapid mapping