Personalised_Controller_Strategies_for_Next_Generation_Intelligent_Adaptive_Electric_Bicycles.pdf (3.57 MB)
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Personalised controller strategies for next generation intelligent adaptive electric bicycles

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journal contribution
posted on 16.07.2020, 10:37 by Lorenzo Stilo, Heinz Lugo, Diana Segura-VelandiaDiana Segura-Velandia, Paul ConwayPaul Conway, Andrew WestAndrew West
Air pollution and increasing traffic congestion means the current way of navigating through a city needs to be rethought. One of the possible solutions is to move away from internal combustion engines and embrace electric and hybrid vehicles. Electric Bicycles can offer an alternative to traditional modes of transport and support an environmentally friendly way to navigate an urban environment, with the benefit of encouraging physical exercise. There are still several issues that constrain a large-scale acceptance of Electric Bicycles, including the need for personalised controller strategies and the energy efficiencies. Current strategies do not include any analysis of rider’s capabilities, physiological factors or pedalling techniques. The research outlined in this paper involved 30 participants that volunteered to take part in an Incremental Sub-Maximal Ramp Test with the aim of understanding and quantifying pedalling characteristics and demonstrating that a better motor controller strategy tailored toward individual requirements is possible. Gender and Cycling Experience were the most prominent factors that differentiate the capabilities of the population. Three novel controller techniques (i.e. Fixed Percentage, Torque Filling and Real-Time Power mapping) are analysed and presented as innovative methods for next generation personalised controller strategies for Electric Bicycles.

Funding

Adaptive Informatics for Intelligent Manufacturing (AI2M) : EP/K014137/1

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Transactions on Intelligent Transportation Systems

Volume

22

Issue

12

Pages

7814-7825

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Version

VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/

Acceptance date

26/06/2020

Publication date

2020-07-28

Copyright date

2020

ISSN

1524-9050

eISSN

1558-0016

Language

en

Depositor

Mr Lorenzo Stilo. Deposit date: 15 July 2020