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ISSN (Print): 2212-7976
ISSN (Online): 1874-477X

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Research Article

Research on Information Fusion Preview Control for Freight Train Speed Tracking

Author(s): Wang Li, Xinmiao Jin, Peng Jiang* and Lingzhi Yi

Volume 16, Issue 1, 2023

Published on: 11 November, 2022

Page: [87 - 98] Pages: 12

DOI: 10.2174/2212797616666221017154819

Price: $65

Abstract

Background: Accurate tracking of train speed is the key link to ensure the stability, accuracy and safety of automatic train operation. To solve the influence of multi-information of freight train speed control system on tracking accuracy, the information fusion preview control freight train speed tracking control system is constructed.

With the increase in the speed and capacity of freight trains, the safety, energy efficiency and intelligent operation of train operation have become increasingly important. Automatic freight trains operation can replace manual operation with automated control systems, which can guarantee the safety of train operation, and improve operational efficiency and reduce operational energy consumption.

Objective: Solve the problem of tracking accuracy and stability deterioration caused by multiinformation of freight train.

Methods: Global navigation satellite system, inertial navigation system and speed measuring motor are selected to construct a speed fusion measurement model by using loosely coupled integrated navigation and improved entropy weight method. The information quantity of performance index and control quantity in preview control is calculated, and the controlled quantity of information fusion optimal preview control is obtained.

Results: The average tracking error of the multi-source information fusion preview controller is 0.038m/s, which is 49% lower than that of the control experiment.

Conclusion: Multi-source information fusion preview controller can effectively reduce the tracking error of freight train speed tracking system and improve the accuracy of automatic freight trains operation.

« Previous Next »
[1]
Jiabo X, Rongjun D, Jing S. Research and prospect of key control technology for heavy-haul trains. J Electric Drive for Locomotives 2019; 1: 1-8.
[2]
Bernal E, Spiryagin M, Cole C. Onboard condition monitoring sensors, systems and techniques for freight railway vehicles: A review. IEEE Sens J 2019; 19(1): 4-24.
[http://dx.doi.org/10.1109/JSEN.2018.2875160]
[3]
Yunxin FAN. Development and trend of heavy haul electric locomotive in China. J Electric Drive for Locomotives 2019; 1: 9-12.
[4]
Lihong DENG. Development research on transportation corridors of heavy-haul railways in china. J China Railway 2020; (08): 70-5.
[5]
Heping LI, Xiaohui YAN. Development history of Rolling stock brake technology of China Railway in the past 70 years. J Railway Locomotive Car 2019; 39(05): 25-35.
[6]
Bin CHEN, Zhiwu HUANG, Rui ZHANG, Weirong LIU, Heng LI, Jing WANG, et al. Data-driven koopman model predictive control for optimal operation of high-speed trains. J IEEE Access 2021; 9: 82233-48.
[7]
Yukai WANG. Application of integrated speed measurement system and model predictive control of trains to ATO system Phd Thesis, D China Academy of Railway Sciences 2019.
[8]
Cheng R, Yu W, Song Y, Chen D, Ma X, Cheng Y. Intelligent safe driving methods based on hybrid automata and ensemble CART algorithms for multihigh-speed trains. IEEE Trans Cybern 2019; 49(10): 3816-26.
[http://dx.doi.org/10.1109/TCYB.2019.2915191] [PMID: 31144651]
[9]
Hongjiang YU. Study on high-speed train speed information fusion technology based on weighted fusion algorithm Phd Thesis, D Lanzhou Jiaotong University 2014.
[10]
Teng ZHONG. Research on train location method based on kalman filter for research on train location method based on kalman filter for multi-sensor information fusion Phd Thesis, D Beijing Jiaotong University 2018.
[11]
Yuhuan LU. Research on next generation train positioning system based on Beidou/INS/image fusion. Hindawi 2021; 2021: 1-9.
[12]
Huan GUO. Research on train speed and positioning algorithm based on multi-sensor fusion Phd Thesis, D Southwest Jiaotong University 2020. Available from: https://en.swjtu.edu.cn/RESEARCH/Research_Impact.htm
[13]
Shaolei LIU. Design and implementation of train-controlled onboard speed and distance measuring device.D Beijing university of posts and telecommunications. IOP Conf Ser Mater Sci Eng 2020; 719: 012057.
[14]
Liao F, Sun MU. Optimal preview control for linear discrete-time periodic systems. Math Probl Eng 2019; 2019(2): 1-11.
[15]
Lan YH, He JL, Li P, She JH. Optimal preview repetitive control with application to permanent magnet synchronous motor drive system. J Franklin Inst 2020; 357(15): 10194-210.
[http://dx.doi.org/10.1016/j.jfranklin.2020.04.026]
[16]
Peng DENG, Chunhui DAI, Zhiqiang LONG. Optimum design and implementation of signal processing method for position and speed measurement system of high-speed maglev train. Chinese Automation Congress Hangzhou, China 2019.

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