A Road-Adaptive Vibration Reduction System with Fuzzy PI Control Approach for Electric Bicycles
Riding comfort and safety are essential requirements for any form of transportation but particularly for electric bicycles (e-bikes), which are highly affected by varying road conditions. These factors largely depend on the effectiveness of the e-bike’s control strategy. While several studies have p...
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MDPI AG
2025-05-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/5/276 |
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| author | Chao-Li Meng Van-Tung Bui Chyi-Ren Dow Shun-Ming Chang Yueh-E (Bonnie) Lu |
| author_facet | Chao-Li Meng Van-Tung Bui Chyi-Ren Dow Shun-Ming Chang Yueh-E (Bonnie) Lu |
| author_sort | Chao-Li Meng |
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| description | Riding comfort and safety are essential requirements for any form of transportation but particularly for electric bicycles (e-bikes), which are highly affected by varying road conditions. These factors largely depend on the effectiveness of the e-bike’s control strategy. While several studies have proposed control approaches that address comfort and safety, vibration—an influential factor in both structural integrity and rider experience—has received limited attention during the design phase. Moreover, many commercially available e-bikes provide manual assistance-level settings, leaving comfort and safety management to the rider’s experience. This study proposes a Road-Adaptive Vibration Reduction System (RAVRS) that can be deployed on an e-bike rider’s smartphone to automatically maintain riding comfort and safety using manual assistance control. A fuzzy-based control algorithm is adopted to dynamically select the appropriate assistance level, aiming to minimize vibration while maintaining velocity and acceleration within thresholds associated with comfort and safety. This study presents a vibration analysis to highlight the significance of vibration control in improving electronic reliability, reducing mechanical fatigue, and enhancing user experience. A functional prototype of the RAVRS was implemented and evaluated using real-world data collected from experimental trips. The simulation results demonstrate that the proposed system achieves effective control of speed and acceleration, with success rates of 83.97% and 99.79%, respectively, outperforming existing control strategies. In addition, the proposed RAVRS significantly enhances the riding experience by improving both comfort and safety. |
| format | Article |
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| institution | Kabale University |
| issn | 2032-6653 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-5f06aea3ad1f4a0abda9f9894901f2f72025-08-20T03:47:58ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-05-0116527610.3390/wevj16050276A Road-Adaptive Vibration Reduction System with Fuzzy PI Control Approach for Electric BicyclesChao-Li Meng0Van-Tung Bui1Chyi-Ren Dow2Shun-Ming Chang3Yueh-E (Bonnie) Lu4Department of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, TaiwanFaculty of Engineering and Technology, Thai Nguyen University of Information and Communication Technology Thai Nguyen 250000, VietnamDepartment of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, TaiwanDepartment of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, TaiwanDepartment of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, TaiwanRiding comfort and safety are essential requirements for any form of transportation but particularly for electric bicycles (e-bikes), which are highly affected by varying road conditions. These factors largely depend on the effectiveness of the e-bike’s control strategy. While several studies have proposed control approaches that address comfort and safety, vibration—an influential factor in both structural integrity and rider experience—has received limited attention during the design phase. Moreover, many commercially available e-bikes provide manual assistance-level settings, leaving comfort and safety management to the rider’s experience. This study proposes a Road-Adaptive Vibration Reduction System (RAVRS) that can be deployed on an e-bike rider’s smartphone to automatically maintain riding comfort and safety using manual assistance control. A fuzzy-based control algorithm is adopted to dynamically select the appropriate assistance level, aiming to minimize vibration while maintaining velocity and acceleration within thresholds associated with comfort and safety. This study presents a vibration analysis to highlight the significance of vibration control in improving electronic reliability, reducing mechanical fatigue, and enhancing user experience. A functional prototype of the RAVRS was implemented and evaluated using real-world data collected from experimental trips. The simulation results demonstrate that the proposed system achieves effective control of speed and acceleration, with success rates of 83.97% and 99.79%, respectively, outperforming existing control strategies. In addition, the proposed RAVRS significantly enhances the riding experience by improving both comfort and safety.https://www.mdpi.com/2032-6653/16/5/276e-bikeroad adaptivecontext awareriding comfort and safetye-bike vibration |
| spellingShingle | Chao-Li Meng Van-Tung Bui Chyi-Ren Dow Shun-Ming Chang Yueh-E (Bonnie) Lu A Road-Adaptive Vibration Reduction System with Fuzzy PI Control Approach for Electric Bicycles World Electric Vehicle Journal e-bike road adaptive context aware riding comfort and safety e-bike vibration |
| title | A Road-Adaptive Vibration Reduction System with Fuzzy PI Control Approach for Electric Bicycles |
| title_full | A Road-Adaptive Vibration Reduction System with Fuzzy PI Control Approach for Electric Bicycles |
| title_fullStr | A Road-Adaptive Vibration Reduction System with Fuzzy PI Control Approach for Electric Bicycles |
| title_full_unstemmed | A Road-Adaptive Vibration Reduction System with Fuzzy PI Control Approach for Electric Bicycles |
| title_short | A Road-Adaptive Vibration Reduction System with Fuzzy PI Control Approach for Electric Bicycles |
| title_sort | road adaptive vibration reduction system with fuzzy pi control approach for electric bicycles |
| topic | e-bike road adaptive context aware riding comfort and safety e-bike vibration |
| url | https://www.mdpi.com/2032-6653/16/5/276 |
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