This article proposes an energy management system (EMS) for shared electric bicycles. The objective is to guarantee electric assistance to the cyclist while avoiding discharging the battery. The basic working principle exploits the cycling efficiency gaps. The proposed multilayered EMS is specifically tailored to a free-floating bike-sharing setting. The innermost layer manages the assistance and energy harvesting with the objective of yielding an intuitive human-machine interface. The middle level modulates the level of assistance so to track a desired average battery power. This is an adaptive model-based controller designed on a control-oriented model of the cyclist and bicycle energy dynamics. A cyclist profiling mechanism enables the model adaptation. The outermost loop guarantees the long-term robustness by tracking a desired battery state-of-charge profile. Extensive simulations and experimental tests validate this approach in terms of usability and charge sustenance, proving that the cyclist profiling is of paramount importance.

Design of a Charge-Sustaining Energy Management System for a Free-Floating Electric Shared Bicycle

Corno M.;Duz A.;Savaresi S. M.
2022-01-01

Abstract

This article proposes an energy management system (EMS) for shared electric bicycles. The objective is to guarantee electric assistance to the cyclist while avoiding discharging the battery. The basic working principle exploits the cycling efficiency gaps. The proposed multilayered EMS is specifically tailored to a free-floating bike-sharing setting. The innermost layer manages the assistance and energy harvesting with the objective of yielding an intuitive human-machine interface. The middle level modulates the level of assistance so to track a desired average battery power. This is an adaptive model-based controller designed on a control-oriented model of the cyclist and bicycle energy dynamics. A cyclist profiling mechanism enables the model adaptation. The outermost loop guarantees the long-term robustness by tracking a desired battery state-of-charge profile. Extensive simulations and experimental tests validate this approach in terms of usability and charge sustenance, proving that the cyclist profiling is of paramount importance.
2022
Electrically assisted bicycles
energy optimization hybrid vehicles
human-in-the-loop control
intelligent transportation systems
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1208223
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