Automated cycling ergometer with built-in ability to produce resistance profiles

Chakravorti, Nandini; Lugo, Heinz; Philpott, Lydia; Conway, Paul; West, Andrew A.

doi:10.1109/smc.2014.6974383

Cited by 1 publication

(1 citation statement)

References 9 publications

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“…Mechanical variables (i.e. torque and cadence) were recorded using a fully instrumented cycling ergometer developed at Loughborough University [66] that enables a 200Hz sampling frequency and the capability to control active mechanical resistance both in terms of torque and power. 1 constituted 40% of the participants suggesting possible interest in e-bikes for this group.…”

Section: B Design Of Experimentsmentioning

confidence: 99%

Personalised Controller Strategies for Next Generation Intelligent Adaptive Electric Bicycles

Stilo

Lugo

Segura-Velandia

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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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 towards 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.

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Section: B Design Of Experimentsmentioning

confidence: 99%