LAPSE:2023.34082
Published Article
LAPSE:2023.34082
An Optimal Train Speed Profile Planning Method for Induction Motor Traction System
Ziyu Wu, Chunhai Gao, Tao Tang
April 24, 2023
Optimizing the operating speed curve of trains without adding new energy storage facilities is essential in the energy-saving operation of railways. In this paper, we propose an optimal train speed curve planning method for driving trains more energy efficiently. A refined traction energy evaluation model for induction motor propulsion systems is first presented. The proposed model considers the efficiency of the traction motor at different operating points and the efficiency of the inverter and gearbox. Then, the optimal energy-efficient speed profile problem is transformed into a multistep decision problem and solved using dynamic programming (DP). To verify the effectiveness of the proposed method, a case study was conducted on an actual subway line. The results obtained indicate that the speed curve produced by the proposed method results in a 20% energy consumption saving compared with the speed curve for actual operations. Furthermore, the results of comparison with a genetic algorithm indicate that the DP algorithm is better able to satisfy the constraints of the train traction system. Solving the optimal speed curve using the proposed method and programming the onboard controller of the train according to the optimal speed curve enables the train to be driven with greater energy efficiency.
Keywords
dynamic programming, Energy Efficiency, induction motor, traction system, train speed profile
Suggested Citation
Wu Z, Gao C, Tang T. An Optimal Train Speed Profile Planning Method for Induction Motor Traction System. (2023). LAPSE:2023.34082
Author Affiliations
Wu Z: School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China; Traffic Control Technology Co., Ltd., Beijing 100070, China; National Engineering Laboratory for Urban Rail Transit Communication and Operation Control, [ORCID]
Gao C: Traffic Control Technology Co., Ltd., Beijing 100070, China; National Engineering Laboratory for Urban Rail Transit Communication and Operation Control, Beijing 100044, China
Tang T: School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
Journal Name
Energies
Volume
14
Issue
16
First Page
5153
Year
2021
Publication Date
2021-08-20
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en14165153, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2023.34082
This Record
External Link

doi:10.3390/en14165153
Publisher Version
Download
Files
Apr 24, 2023
Main Article
License
CC BY 4.0
Meta
Record Statistics
Record Views
102
Version History
[v1] (Original Submission)
Apr 24, 2023
 
Verified by curator on
Apr 24, 2023
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2023.34082
 
Original Submitter
Auto Uploader for LAPSE
Links to Related Works
Directly Related to This Work
Publisher Version