micycle a self-balancing electric unicycle andrew kadis david caldecott andrew edwards matthew...
TRANSCRIPT
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MICYCLEA self-balancing electric unicycle
Andrew KadisDavid CaldecottAndrew EdwardsMatthew HaynesMiroslav JerbicRhys Madigan
Supervisor: Assoc. Prof. Ben S. CazzolatoCo-Supervisor: Dr. Zebb Prime
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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
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Literature review
Focus Designs SBUTrevor Blackwell’s SBU
The Enicycle
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Concept development
Incorporation of steering mechanism
Extensive research into steering mechanisms
Use of a rotary damper
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Concept development (2)
Lego Mockup
Preliminary Concept Model
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Components
Sensor
Power supply
Motor controller Motor
Microcontroller
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Mechanical design goals
Assembly of Micycle
Damper
Spring
Fork
Chassis assembly
Steeringmechanism
Perspexcovers
Protectiverubber
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Major mechanical components 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
Chassis plate assembly
Plate chassis
Perspex covers
Protective rubber
Fork
Damper drive
Bearing locations
Offset centre
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Steering mechanism
Uses a torsion spring and rotary damper Makes the Micycle much easier to ride Allowed steering angle ±15˚
Steering mechanism
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Mechanical design approach
Initial desig
n CoG
Analysis
Iterate design
Drafting
Structural
analysis
ANSYS Workbench
ProE
Manufacture
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Electrical system overview
IMU
MOTORCONTROLLER
MICRO-CONTROLLER
PERIPHERALS
HUB MOTOR
BATTERY
DISTRIBUTIONBOARD
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Controller design
Self-Balancing Unicycle
Mechanical
System
Control
ElectricalSystem
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Controller structure
PD controller structure used Derivative signal taken directly from the
IMU rather than differentiated to minimise latency in the sensor readings
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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
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Controller benchmarking - methodology
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
Micycle with the wheel constrained
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Controller benchmarking - results
Response of simulated system released from 30º
Response of physical system released from 30º
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Software functionality
Core
Peripheral
Safety
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Fall
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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
Effect
Cause
Mitigating
Strategies
Failure Mode
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Andrew Kadis - Software
Safety
Control
Safety
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Error codes7
Safety Trip 7 Segment Error CodeBattery drained 0
Vehicle speed too fast 1Excessive current through motor 2Pitch position outside safe range 3
Angular velocity too fast 4General operational failure in the Maxon 5
ADC outside expected bounds 6IMU did not initialise correctly 7
Maxon did not initialise correctly 8IMU - abnormal power rating 9IMU - RS232 pin disconnected A
IMU - parity check failed BIMU - indeterminate communication error C
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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
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Community exposure
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Community exposure (2)
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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
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Questions
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