The nexus of smart transportation: Self-powered and self-sensing node for autonomous rail rapid transit

IF 5.2 2区工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY

Measurement Pub Date : 2025-03-14 DOI:10.1016/j.measurement.2025.117303

Fujian Liang , Yuchen Gong , Jiaoyi Wu , Zutao Zhang , Dabing Luo , Rui Zou

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引用次数: 0

Abstract

Smart transportation conforms to the developing trend, autonomous rail rapid transit (ART) draws attention as a new form of public transportation. In this paper, a self-powered and self-sensing node (SSN) is proposed to detect the running state of vehicles while providing electrical energy, which can be used as a link in intelligent transportation. The self-powered part stabilizes the system’s response using a zero-pressure angle mechanism and a flywheel. Establish dynamic and kinematic models to study the system response, electrical performance, and neural network model. This paper innovatively studies the enhanced flywheel and its influence on the system, and the benefit of the enhanced flywheel set system proposed is 41.6% higher than traditional flywheel. Experiments show that the energy conversion efficiency of the SSN can reach 75%, and it only takes 60 s to charge one 1.5F supercapacitor fully. In the self-sensing part, the characteristic signals are collected and encoded to generate data sets to train and test the neural network model. The results show that the detection accuracy of the SSN reaches 99.7%, indicates that it can effectively obtain the information we need. This SSN has positive implications for driving the development of ART in smart transportation.

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来源期刊

Measurement 工程技术-工程：综合

CiteScore

10.20

自引率

12.50%

发文量

1589

审稿时长

12.1 months

期刊介绍： Contributions are invited on novel achievements in all fields of measurement and instrumentation science and technology. Authors are encouraged to submit novel material, whose ultimate goal is an advancement in the state of the art of: measurement and metrology fundamentals, sensors, measurement instruments, measurement and estimation techniques, measurement data processing and fusion algorithms, evaluation procedures and methodologies for plants and industrial processes, performance analysis of systems, processes and algorithms, mathematical models for measurement-oriented purposes, distributed measurement systems in a connected world.