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Micycle

Andrew Kadis David Caldecott Andrew Edwards Matthew Haynes Miroslav Jerbic Rhys Madigan Supervisor: Assoc. Prof. Ben S. Cazzolato Co-Supervisor: Dr. Zebb Prime. Micycle. A self-balancing electric unicycle. Introduction.

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Micycle

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  1. Andrew Kadis David Caldecott Andrew Edwards Matthew Haynes MiroslavJerbic Rhys Madigan Supervisor: Assoc. Prof. Ben S. Cazzolato Co-Supervisor: Dr. Zebb Prime Micycle A self-balancing electric unicycle

  2. Introduction Submitted paper focused on developing the system dynamics and simulating them The control response of the simulated and physical systems were then compared This presentation has a slightly different focus, concentrates on the wider Micycle system

  3. Literature review The Enicycle Trevor Blackwell’s SBU Focus Designs SBU

  4. Concept development Incorporation of steering mechanism Extensive research into steering mechanisms Use of a rotary damper

  5. Concept development (2) Lego Mockup Preliminary Concept Model

  6. Components Sensor Microcontroller Power supply Motor controller Motor

  7. Mechanical design goals Chassis assembly Protective rubber Damper Perspex covers Spring Steering mechanism Fork Assembly of Micycle

  8. Major mechanical components Plate chassis Perspex covers Protective rubber Chassis plate assembly Damper drive Bearing locations Offset centre Fork • Chassis assembly • Simple plate chassis design • Protective Perspex covers • Protective rubber • Fork design • Rotary damper drive • Offset centre for motor • Dual bearing design • Chromoly steel

  9. Steering mechanism Steering mechanism Uses a torsion spring and rotary damper Makes the Micycle much easier to ride Allowed steering angle ±15˚

  10. Mechanical design approach ProE Initial design CoG Analysis ANSYS Workbench Structural analysis Iterate design Manufacture Drafting

  11. Electrical system overview MICRO-CONTROLLER BATTERY DISTRIBUTION BOARD IMU MOTOR CONTROLLER HUB MOTOR PERIPHERALS

  12. Controller design Self-Balancing Unicycle Mechanical System • Control • ElectricalSystem

  13. Controller structure • PD controller structure used • Derivative signal taken directly from the IMU rather than differentiated to minimise latency in the sensor readings

  14. System Dynamics • The Lagrangian approach of deriving the system dynamics was applied • The dynamics were derived in terms of: • φ – the rotation of the frame about the z-axis • θ – the rotation of the wheel relative to the z axis • Full details can be found in the paper • Developed simulation in Simulink from these dynamics

  15. Controller benchmarking - methodology Micycle with the wheel constrained Needed a methodology to produce repeatable results to benchmark control system Attached a PD controller with same gains to simulated dynamics Constrained the wheel Point of comparison between physical and simulated control systems to examine response to disturbances

  16. Controller benchmarking - results Response of simulated system released from 30º Response of physical system released from 30º

  17. Software functionality Core Safety Peripheral

  18. Fall

  19. Failure modes and effect analysis (FMEA) Comprehensive, iterative process System engineering tool Both a high and low level FMEA performed Over 100 different cases considered Full FMEA is approx. 30 pages long

  20. Safety Control Safety Andrew Kadis - Software

  21. Error codes

  22. Project outcomes Designed, tested and built the Micycle A fully rideable self-balancing electric unicycle which can be learnt to ride in 30 minutes to an hour Comprehensive iterative FMEA process completed 8 hour battery life Significant exposure to the wider community

  23. Community exposure

  24. Community exposure (2)

  25. Future work Use of a more powerful motor controller to reduce the chances of actuator saturation Implementation of a model based controller Incorporation of active control in the roll direction

  26. Questions

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