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Intelligent Power Management for Unmanned Aerial Vehicles James Graham Roger Dixon, Pete Hubbard Loughborough University UKACC PhD Presentation Showcase

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Intelligent Power Management for Unmanned Aerial Vehicles. James Graham Roger Dixon, Pete Hubbard Loughborough University. Introduction. Predict the thermal state of generator Use Predictions to make informed load management decisions. Method. Thermal Network Model. Kalman Filter. - PowerPoint PPT Presentation

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Page 1: Intelligent Power Management for Unmanned Aerial Vehicles

Intelligent Power Management for Unmanned Aerial Vehicles

James GrahamRoger Dixon, Pete HubbardLoughborough University

UKACC PhD Presentation Showcase

http://www.lboro.ac.uk/
http://www.lboro.ac.uk/
Page 2: Intelligent Power Management for Unmanned Aerial Vehicles

UKACC PhD Presentation Showcase Slide 2

Introduction Predict the thermal state of generator Use Predictions to make informed load

management decisions

http://www.lboro.ac.uk/
Page 3: Intelligent Power Management for Unmanned Aerial Vehicles

UKACC PhD Presentation Showcase Slide 3

Method

KalmanFilter

ThermalNetworkModel

http://www.lboro.ac.uk/
Page 4: Intelligent Power Management for Unmanned Aerial Vehicles

Thermal Network Model

UKACC PhD Presentation Showcase Slide 4

http://www.lboro.ac.uk/
Page 5: Intelligent Power Management for Unmanned Aerial Vehicles

UKACC PhD Presentation Showcase Slide 5

ResultsTime (hours)

O 51 2 3 4

• Fault occurs at 67 mins• System changes load of both Gens to prevent overheat of faulty one

http://www.lboro.ac.uk/
Page 6: Intelligent Power Management for Unmanned Aerial Vehicles

UKACC PhD Presentation Showcase Slide 6

Conclusion or summary or future work

Optimise load profiles to prevent overheat

Generator resting Load displacement to spare generators

http://www.lboro.ac.uk/

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