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Sustainability Optimisation of Electrified Railways

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A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (20 January 2024) | Viewed by 9623

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Special Issue Editors

Dr. Yang Song

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Guest Editor

Department of Structural Engineering, Norwegian University of Science and Technology, 7030 Trondheim, Norway
Interests: railway dynamics; high-speed railway; pantograph–catenary interaction; traction power system; rail–wheel interaction
Special Issues, Collections and Topics in MDPI journals

Dr. Ruichen Wang

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Guest Editor

School of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
Interests: vehicle dynamics; energy harvesting; wheel–rail interface condition monitoring and inspection; mechanical system modeling; fault diagnosis
Special Issues, Collections and Topics in MDPI journals

Dr. Yunguang Ye

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Guest Editor

State Key Laboratory of Traction Power, Southwest Jiaotong University, Chengdu 610031, China
Interests: railway vehicle dynamics; machine learning to mechanical industry; condition monitoring

Dr. Fuchuan Duan

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Guest Editor

College of Transportation Engineering, Tongji University, Shanghai 201804, China
Interests: railway dynamics; vibration measurement; vibration abatement

Special Issue Information

Dear Colleagues,

As the cleanest and greenest high-volume transport, the electric railway has an essential role in creating sustainable lifestyles and economies. Particularly, the ever-increasing mileage of high-speed railways in the last decade around the world has demonstrated that it is the fastest and most cost-efficient way to decarbonise people’s daily mobility and logistics chains. The railway sector is not only responsible for enabling fast, comfortable and punctual train service, but also playing an important societal role in relation to ecosystems and biodiversity, both in urban and rural areas. In this context, we are pleased to announce this Special Issue with the general theme of “Sustainability Optimisation of Electrified Railways”. Possible topics include, but are not limited to, the following:

Numerical modelling of railway systems;
Experimental and field tests in railway systems;
Optimisation of rail electrification system;
Emerging power supply techniques for electric trains;
Assessment of railway system service performance;
Train driving speed optimisation for improving energy efficiency;
Regenerative braking energy harvest and utilisation of electric trains;
Timetable scheduling and optimisation of rail networks;
Intelligent monitoring and maintenance of railway infrastructures;
On-board monitoring techniques on railway vehicles;
Magnetic levitation technology;
New-concept technologies for future railways.

We invite researchers and experts to submit original research and review articles that describe the state-of-the-art and further stimulate innovations in the field.

Dr. Yang Song
Dr. Ruichen Wang
Dr. Yunguang Ye
Dr. Fuchuan Duan
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

rail electrification
railway dynamics
traction power supply systems
running safety and sustainability
smart maintenance
intelligent monitoring
on-board monitoring
railway freight vehicles
energy harvest
timetable scheduling
smart maintenance
maglev trains

Published Papers (6 papers)

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Research

16 pages, 7070 KiB

Open AccessArticle

Research on Energy Management Method of Fuel Cell/Supercapacitor Hybrid Trams Based on Optimal Hydrogen Consumption

by Qingyuan Bu, Shiwei Zhang, Ning Ma, Qinghe Luo and Baigang Sun

Sustainability 2023, 15(14), 11234; https://0-doi-org.brum.beds.ac.uk/10.3390/su151411234 - 19 Jul 2023

Cited by 1 | Viewed by 1091

Abstract

In this paper, based on the operating states and characteristics of fuel cell/supercapacitor hybrid trams, an optimal hydrogen energy management method is proposed. This method divides the operating states into two parts: traction state and non-traction state. In the traction state, the real-time loss function of the hybrid power system, which is used to obtain the fuel cell optimal output power under the different demand powers and supercapacitor voltage, is established. In the non-traction state, the constant-power charging method, which is obtained by solving the power-voltage charging model, is used to ensure the supercapacitor voltage of the beginning-state and the end-state in an entire operation cycle are the same. The RT-LAB simulation platform is used to verify that the proposed method has the ability to control the hybrid real-time system. Using the comparative experiment between the proposed method and power-follow method, the results show that the proposed method offers a significant improvement in both fuel cell output stability and hydrogen consumption in a full operation cycle. Full article

(This article belongs to the Special Issue Sustainability Optimisation of Electrified Railways)

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15 pages, 3139 KiB

Open AccessArticle

Sensitivity Analysis and Optimisation of Key Parameters for Railway Rigid Overhead System and Pantograph

by Ke Chen, Yang Song, Xiaobing Lu and Fuchuan Duan

Sustainability 2023, 15(8), 6803; https://0-doi-org.brum.beds.ac.uk/10.3390/su15086803 - 18 Apr 2023

Cited by 1 | Viewed by 1057

Abstract

This paper aims to enhance the speed of rigid overhead systems by investigating the impact of important parameters of the overhead system and pantograph on the interaction performance, specifically the contact force between the panhead of the pantograph and the contact wire of the overhead system. To accomplish this, this paper first builds a rigid overhead system model based on the finite element method. The pantograph–contact wire interaction simulation is achieved by including a three-stage lumped mass pantograph model. The Sobol sensitivity analysis method is utilised to determine the contribution of different parameters to the contact force standard deviation. Subsequently, an optimisation approach is used to minimise the contact standard deviation at various speeds by adopting five crucial parameters. The sensitivity analysis of 13 variables indicates that the span length, bending stiffness, and linear density of the conductor rail, and the masses of the pantograph head and upper frame are the most relevant variables for the contact force standard deviation. The quantification of each parameter’s contribution reveals that the increase in bending stiffness generally has a positive effect in reducing the contact force fluctuation, while the decreases in other variables are preferred. The optimisation analysis shows that the optimised contact force standard deviation decreases by 39.18%, 66.77%, and 61.02% at speeds of 90 km/h, 120 km/h, and 150 km/h, respectively, compared to the original values. Full article

(This article belongs to the Special Issue Sustainability Optimisation of Electrified Railways)

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24 pages, 3405 KiB

Open AccessArticle

Influence of Passenger Capacity on Fatigue Life of Gearbox Suspender of the Traction Transmission System in Urban Railway Vehicles

by Xianghe Huang, Jinhai Wang, Jianwei Yang, Yue Zhao and Yuzhu Wang

Sustainability 2023, 15(5), 4338; https://0-doi-org.brum.beds.ac.uk/10.3390/su15054338 - 28 Feb 2023

Viewed by 1043

Abstract

Fatigue damage is the most dangerous failure behavior for gearbox suspenders in urban railway vehicles, and passenger capacity is crucial to the dynamic load characteristics of the traction transmission system. Therefore, in this paper, a dynamic model of the motor car is established, and a numerical simulation is carried out under different speeds and curve radii to investigate the effect of passenger capacity on fatigue life. The research results show that passenger capacity is an essential factor affecting the fatigue life of suspenders. As the vehicle runs at an average speed, the fatigue life of the suspender is 1.07 × 10⁶ km when the passenger capacity is 120 people; when there are 240 people, the fatigue life reduction is 60%, while it is 86% at 339 people and 92% at 389 people. The per capita fatigue damage under a straight line is 7.27 × 10⁻¹⁰ at 20 km/h but 1.23 × 10⁻⁸ at 60 km/h. The per capita fatigue damage under a curved line is 7.18 × 10⁻⁹ in the 600 m curve but 9.00 × 10⁻⁹ in the 400 m curve. It can be concluded that the effect of speed is more significant than the curve radius. This research achievement can provide theoretical support for vehicle design and maintenance decisions. Full article

(This article belongs to the Special Issue Sustainability Optimisation of Electrified Railways)

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19 pages, 5020 KiB

Open AccessArticle

A Hybrid Algorithm for Parameter Identification of Synchronous Reluctance Machines

by Huan Wang, Guobin Lin, Yuanzhe Zhao, Sizhe Ren and Fuchuan Duan

Sustainability 2023, 15(1), 397; https://0-doi-org.brum.beds.ac.uk/10.3390/su15010397 - 26 Dec 2022

Cited by 2 | Viewed by 1179

Abstract

In rail transit traction, synchronous reluctance machines (SynRMs) are potential alternatives to traditional AC motors due to their energy-saving and low-cost characteristics. However, the nonlinearities of SynRMs are more severe than permanent magnet synchronous motors (PMSM) and induction motors (IM), which means the characteristics of SynRMs are challenging to model accurately. The parameter identification directly influences the modeling of nonlinearity, while the existing algorithms tend to converge prematurely. To overcome this problem, in this paper, a hybrid optimizer combining the SCA with the SSO algorithm is proposed to obtain the parameters of SynRMs, and the proposed Sine-Cosine self-adaptive synergistic optimization (SCSSO) algorithm preserves the self-adaptive characteristic of SSO and the exploration ability of SCA. Comprehensive numerical simulation and experimental tests have fully demonstrated that the proposed method has obviously improved parameter identification accuracy and robustness. In the dq-axis flux linkage, the mismatch between reference and estimated data of proposed algorithm is below 1% and 6%, respectively. Moreover, the best d-axis RMSE of SCSSO is 50% of the well-known algorithm CLPSO and 25% of BLPSO and its performance has improved by two orders of magnitude compared to traditional simple algorithms. In the q-axis, the best RMSE is 10% of CLPSO and 50% of Rao-3 and Jaya. Moreover, the performance of the proposed algorithm has improved nearly 90 times compared to traditional simple algorithms. Full article

(This article belongs to the Special Issue Sustainability Optimisation of Electrified Railways)

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25 pages, 2908 KiB

Open AccessArticle

Patent Data Analytics for Technology Forecasting of the Railway Main Transformer

by Yong-Jae Lee, Young Jae Han, Sang-Soo Kim and Chulung Lee

Sustainability 2023, 15(1), 278; https://0-doi-org.brum.beds.ac.uk/10.3390/su15010278 - 24 Dec 2022

Cited by 2 | Viewed by 2584

Abstract

The railway main transformer is considered one of the most important electrical equipment for trains. Companies and research institutes around the world are striving to develop high-performance railway main transformers. In order to be the first mover for railway main transformer technology, companies and research institutes should predict vacant technology based on the analysis of promising detailed technology areas. Therefore, in this study, a patent analysis to predict vacant technologies based on identified promising IPC technology areas is provided. In order to identify promising detailed IPC technology areas, the technology mapping analysis, the time series analysis, and the social network analysis are conducted based on the patent-IPC matrix, extracted from the data information of 707 patents from the patent database of Korea, China, Japan, United States, Canada, and Europe. Then, through the GTM analysis based on promising detailed IPC technology areas, one vacant technology node and three analysis target nodes surrounding the vacant technology node are obtained to predict vacant technologies. From the analysis, we predict the following three groups of vacant technologies: (1) blowerless technology, (2) oil-free technology, and (3) solid-state technology. This study provides insights on the technology trend in railway main transformers, as well as the analysis framework for the development of R&D strategies based on the patent data. Full article

(This article belongs to the Special Issue Sustainability Optimisation of Electrified Railways)

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16 pages, 8108 KiB

Open AccessArticle

An Improved Overmodulation Strategy for a Three-Level NPC Inverter Considering Neutral-Point Voltage Balance and Common-Mode Voltage Suppression

by Zhixun Ma, Haichuan Niu, Xiang Wu, Xu Zhang and Guobin Lin

Sustainability 2022, 14(19), 12558; https://0-doi-org.brum.beds.ac.uk/10.3390/su141912558 - 2 Oct 2022

Cited by 3 | Viewed by 1628

Abstract

The three-level neutral-point clamped voltage source inverter (3L-NPC-VSI) is widely used in the maglev traction systems due to its high output voltage, large output capacity and low output current harmonics. In order to improve the utilization of the DC-bus voltage, an overmodulation strategy is necessary. This paper proposes an improved overmodulation strategy based on the minimum amplitude error method for a 3L-NPC-VSI. Compared with the conventional overmodulation strategy based on the minimum amplitude error method, the utilization of the DC-bus voltage is higher. Meanwhile, a virtual space vector modulation strategy is adopted for inverter neutral-point (NP) voltage balance and common-mode voltage (CMV) suppression. Furthermore, the suppression of leakage current also has been verified. Furthermore, the implementation details of the proposed overmodulation strategy based on minimum amplitude error method is elaborated. The effectiveness of the proposed method is verified by simulation and experimental results. Full article

(This article belongs to the Special Issue Sustainability Optimisation of Electrified Railways)

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