Power assisting control for electric bicycles using an adaptive filter

Hatada, Kazuyoshi; Hirata, Kentaro

doi:10.1109/icit.2014.6894971

Cited by 8 publications

(6 citation statements)

References 6 publications

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“…It attempts to maintain the speed constant (usually based on a throttle or the rider's cadence) independent of the environmental conditions (i.e. road incline, surface resistance, wind resistance) adjusting the motor contribution accordingly [31]- [33]. The simplicity of the hardware implementation (i.e.…”

Section: Current State Of the Artmentioning

confidence: 99%

“…EU laws require electric assistance to be delivered without a throttle [37]) and (ii) could result in unstable operation as it takes control away from the rider in attempting to fix a constant speed for the bicycle. Although some authors highlight that the motor contribution [31] can be varied to account for the user's fitness level and experience, there is no evidence presented in their publications on how this should be implemented [31]- [33].…”

Section: Current State Of the Artmentioning

confidence: 99%

“…Academic literature offers few examples of studies aiming at understanding possible implementations of novel motor controllers: few studies focus of novel techniques i.e. using Fuzzy Logic [15], [16] or attempting to counterbalance environmental disturbances [31]- [33]. Limited studies have looked at energy harvesting [44] and others have mainly focused on novel hardware applications [45], [46].…”

Section: A Previous Workmentioning

confidence: 99%

See 2 more Smart Citations

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: Current State Of the Artmentioning

confidence: 99%

Section: Current State Of the Artmentioning

confidence: 99%

Section: A Previous Workmentioning

confidence: 99%

See 1 more Smart Citation

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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show abstract

“…With the growing interest in environmental protection and conservation, several research efforts have attempted to create green vehicles to decrease air pollution and enhance energy security [2, 3]. In particular, electric bikes are very suitable and effective for short‐range city commuters [4–7]. Generally speaking, there are two types of electric bikes.…”

Section: Introductionmentioning

confidence: 99%

Enhanced fuzzy‐logic‐based power‐assisted control with user‐adaptive systems for human‐electric bikes

Lee

Jiang

2019

IET Intelligent Transport Systems

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“…A practical problem is that the pedaling period of a human is not exactly constant. We addressed this problem by employing adaptive notch filters [8], [9]. Although this method works for artificial quasiperiodic signals with relatively small fluctuations, it fails to deal with actual human pedaling because real pedaling data contains signals with a wide range of frequencies.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Power Assist Control with Periodic Disturbance Observer and Its Experimental Verification Using an Electric Bicycle

Hatada

Hirata

Sato

2017

SICE Journal of Control, Measurement, and System Integration

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: This paper addresses the problem of energy-efficient power assist control for quasiperiodic motions. The simplest assist method would be to apply additional torque in proportion to the instantaneous value of torque generated by a user. In our previous study, it was shown that energy efficiency improves by flattening the torque pattern. To cope with the frequency fluctuation of our motion, we introduce a periodic disturbance observer with a frequency estimator and suppress the pulsation of the human torque based on a disturbance observer framework. The effectiveness of the proposed method is evaluated through numerical simulations and experiments with an actual electric bicycle being pedaled by a human.

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Power assisting control for electric bicycles using an adaptive filter

Cited by 8 publications

References 6 publications

Personalised Controller Strategies for Next Generation Intelligent Adaptive Electric Bicycles

Personalised Controller Strategies for Next Generation Intelligent Adaptive Electric Bicycles

Enhanced fuzzy‐logic‐based power‐assisted control with user‐adaptive systems for human‐electric bikes

Energy-Efficient Power Assist Control with Periodic Disturbance Observer and Its Experimental Verification Using an Electric Bicycle

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