A Power Assistant Algorithm Based on Human-Robot Interaction Analysis for Improving System Efficiency and Riding Experience of E-Bikes
DC Field | Value | Language |
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dc.contributor.author | Kim, Deok Ha | - |
dc.contributor.author | Lee, Dongun | - |
dc.contributor.author | Kim, Yeongjin | - |
dc.contributor.author | Kim, Sungjun | - |
dc.contributor.author | Shin, Dongjun | - |
dc.date.accessioned | 2021-07-20T04:41:57Z | - |
dc.date.available | 2021-07-20T04:41:57Z | - |
dc.date.issued | 2021-01 | - |
dc.identifier.issn | 2071-1050 | - |
dc.identifier.issn | 2071-1050 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/47660 | - |
dc.description.abstract | As robots are becoming more accessible in our daily lives, the interest in physical human-robot interaction (HRI) is rapidly increasing. An electric bicycle (E-bike) is one of the best examples of HRI, because a rider simultaneously actuates the rear wheel of the E-bike in close proximity. Most commercially available E-bikes employ a control methodology known as a power assistant system (PAS). However, this type of system cannot offer fully efficient power assistance for E-bikes since it does not account for the biomechanics of riders. In order to address this issue, we propose a control algorithm to increase the efficiency and enhance the riding experience of E-bikes by implementing the control parameters acquired from analyses of human leg kinematics and muscular dynamics. To validate the proposed algorithm, we have evaluated and compared the performance of E-bikes in three different conditions: (1) without power assistance, (2) assistance with a PAS algorithm, and (3) assistance with the proposed algorithm. Our algorithm required 5.09% less human energy consumption than the PAS algorithm and 11.01% less energy consumption than a bicycle operated without power assistance. Our algorithm also increased velocity stability by 11.89% and acceleration stability by 27.28%, and decreased jerk by 12.36% in comparison to the PAS algorithm. | - |
dc.format.extent | 19 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | MDPI | - |
dc.title | A Power Assistant Algorithm Based on Human-Robot Interaction Analysis for Improving System Efficiency and Riding Experience of E-Bikes | - |
dc.type | Article | - |
dc.identifier.doi | 10.3390/su13020768 | - |
dc.identifier.bibliographicCitation | SUSTAINABILITY, v.13, no.2, pp 1 - 19 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000611788000001 | - |
dc.identifier.scopusid | 2-s2.0-85100187764 | - |
dc.citation.endPage | 19 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 1 | - |
dc.citation.title | SUSTAINABILITY | - |
dc.citation.volume | 13 | - |
dc.type.docType | Article | - |
dc.publisher.location | 스위스 | - |
dc.subject.keywordAuthor | electric bicycles (E-bikes) | - |
dc.subject.keywordAuthor | energy consumption | - |
dc.subject.keywordAuthor | human analysis | - |
dc.subject.keywordAuthor | leg kinematics | - |
dc.subject.keywordAuthor | muscular dynamics | - |
dc.subject.keywordAuthor | riding experience | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
dc.relation.journalWebOfScienceCategory | Green & Sustainable Science & Technology | - |
dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
dc.relation.journalWebOfScienceCategory | Environmental Studies | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
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