Design of an automatic shift control system with self-learning ability for a bicycle

被引：3

作者：

Lin, Shir-Kuan ^{[1
]}

Yang, Shih-Wei ^{[1
]}

Cheng, Chi-Chang ^{[2
]}

机构：

[1] Natl Chiao Tung Univ, Inst Elect & Control Engn, Hsinchu 30010, Taiwan

[2] JD Components Co Ltd, Taichung 40867, Taiwan

来源：

JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS | 2015年 / 38卷 / 05期

关键词：

automatic shift control system; self-learning; pseudo pedaling speed; DYNAMICS;

D O I：

10.1080/02533839.2015.1010451

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

An automatic shift control system with self-learning ability, for a bicycle is proposed in this paper. The concept of pseudo pedaling speed is used as the shifting basis, and the pseudo pedaling speed is derived from the wheel speed read through a microcontroller. According to the pseudo pedaling speed histograms, all riders' pseudo pedaling speed histograms approach normal distribution. Hence, a straight forward algorithm of shifting using the mean and standard deviation of the riders' pseudo pedaling speed is developed. The microcontroller commands the actuators to shift up or shift down a gear with the proposed algorithm. According to the experimental results, the proposed system has been shown to function well, thus, enhancing the convenience and comfort of cycling.

引用

页码：594 / 602

页数：9

共 50 条

[41] Study on self-learning for vibration fault diagnosis system of rotating machinery
Ge, Zhihua
Niu, Yuguang
Song, Zhiping
Fu, Zhongguang
Proceedings of the ASME Power Conference 2005, Pts A and B, 2005, : 347 - 352
[42] A VR-based Support System of Self-learning Microscope Operation
Kaneko, Hikaru
Makino, Mitsunori
INTERNATIONAL WORKSHOP ON ADVANCED IMAGING TECHNOLOGY (IWAIT) 2020, 2020, 11515
[43] Evolving spiking wavelet-neuro-fuzzy self-learning system
Bodyanskiy, Ye
Dolotov, A.
Vynokurova, O.
APPLIED SOFT COMPUTING, 2014, 14 : 252 - 258
[44] Based on Clustering Algorithm Expert System of Self-learning Rule Base
Cai Guoliang
Wang Guicheng
Guan Changliang
Yin Fengfeng
Zhu Jiale
2022 34TH CHINESE CONTROL AND DECISION CONFERENCE, CCDC, 2022, : 1563 - 1566
[45] Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors
Villaverde, Monica
Perez, David
Moreno, Felix
SENSORS, 2015, 15 (11) : 29056 - 29078
[46] Neural network self-learning variable-robustness tracking control for electro-hydraulic servo system
He, YB
Zhao, H
Zhu, Y
Sheng, W
Wang, FM
ISTM/99: 3RD INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, 1999, : 489 - 492
[47] The design and evaluation of a digital learning-based English chatbot as an online self-learning method
Wu, C. H.
Lam, H. Y.
Kong, A.
Wong, W. L. H.
INTERNATIONAL JOURNAL OF ENGINEERING BUSINESS MANAGEMENT, 2023, 15
[48] A Novel Time and Voltage Based SAR ADC Design With Self-Learning Technique
Nagabhushana, Abhilash Karnatakam
Wang, Haibo
2016 ACM/EDAC/IEEE DESIGN AUTOMATION CONFERENCE (DAC), 2016,
[49] The Design of Web-based College English Self-learning Supporting Platform
Sun Yongjie
Wang Chundong
EDUCATION AND EDUCATION MANAGEMENT, 2011, 2 : 545 - +
[50] Power system stabilizer based on a self-learning adaptive network fuzzy inference system
Malik, OP
Hariri, A
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2002, 24 (02) : 153 - 173

← 1 2 3 4 5 →