A Fuzzy Logic-Based Automatic Gear-Shifting System for Electric Bicycles in Urban Mobility Solutions for Smart Cities
In smart cities, bicycle-sharing systems have become essential as last-mile transportation solutions, seamlessly integrating into urban mobility networks worldwide. To improve riding efficiency, the development of automatic gear-shifting systems for electric bicycles has gained significant attention...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Systems |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-8954/13/4/228 |
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| Summary: | In smart cities, bicycle-sharing systems have become essential as last-mile transportation solutions, seamlessly integrating into urban mobility networks worldwide. To improve riding efficiency, the development of automatic gear-shifting systems for electric bicycles has gained significant attention. This study presents a novel fuzzy logic controller (FLC) designed to address the challenges of frequent and unstable gear shifts in automatic bicycle transmissions. Unlike traditional systems that rely solely on velocity or cadence as inputs, the proposed FLC incorporates both acceleration and slope data to enhance shifting stability and cadence regulation. By replacing velocity with acceleration and integrating slope information, the system minimizes frequent shifting and improves overall performance. Experimental and simulation results demonstrate that the proposed approach reduces acceleration ripple, stabilizes gear-shifting, and maintains cadence within the desired range, ensuring a smoother and more comfortable riding experience. The proposed approach significantly reduces acceleration ripple by 1 m/s<sup>2</sup>, maintains target cadence, and aligns gear shifts with design intent, yielding a substantial 20% safety improvement. These advancements offer particular promise for public bicycle-sharing systems, providing a robust and adaptable solution suited to diverse cycling conditions and rider profiles. |
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| ISSN: | 2079-8954 |