Maglev Train Research Articles

Study on the Dynamics Characteristics of HTS Maglev Train Considering the Aerodynamic Loads under Crosswinds

High-temperature Superconducting (HTS) maglev trains are vulnerable to the effects of crosswinds when operating at high speeds in open-air conditions, potentially compromising riding comfort and safety. This study established a vehicle dynamic model based on the nonlinear maglev-track relationship and added aerodynamic loads under crosswinds to the train’s simplified load center to address this issue. Using the maximum vibration acceleration limit and the Sperling index, we evaluated the riding comfort of the HTS maglev train under different conditions. Further, the vibration acceleration power spectral density was analyzed to reveal the impact of increasing the train’s operating speed and crosswind speed. The results indicated that the lateral and vertical Sperling index achieved an “excellent” rating, even at crosswind speeds of up to 20.7 m/s when the train was traveling at speeds of up to 600 km/h. However, it was noted that particular attention should be given to the riding comfort in the head car when the speed reaches 600 km/h. Moreover, the influence of the increase in train speed on the vibration frequency domain distribution of the three car bodies and the train’s riding comfort is greater than that of the increase in the crosswind speed. These findings may provide a valuable reference for the future engineering application of the HTS maglev train.

Energy‐efficient operation of medium‐speed maglev through integrated traction and train control

AbstractIn contrast to the wheel‐track trains, where the motor characteristics are considered a constant value, the motor characteristics of the medium‐speed maglev (MSM) trains are the dependent variable of the position. This article studies the integration of traction power control and train control for the MSM to minimize energy consumption. First, an innovative integrated energy‐efficient optimization model for MSM train control is constructed, considering the characteristics of the linear motors. Then, a multi‐level dynamic programming (DP) approach, which includes the train operation simulation with the linear motor, is developed to solve the optimization problem. Furthermore, a speed‐up strategy for the DP approach is proposed by a pre‐calculated target train speed band (TTSB). The results of numerical experiments show that the DP approach yields a more practical train speed profile. In contrast, the DP approach with the TTSB strategy can achieve a better trade‐off between solution accuracy and computational efficiency.

Multi-sensor information fusion localization of rare-earth suspended permanent magnet maglev trains based on adaptive Kalman algorithm.

Since the positioning accuracy of sensors degrades due to noise and environmental interference when a single sensor is used to localize a suspended rare-earth permanent magnetically levitated train, a multi-sensor information fusion method using multiple sensors and self-correcting weighting is proposed for permanent magnetic levitated train localization. A decay memory factor is introduced to reduce the weight of the influence of historical measurement data on the fusion estimation, thus enhancing the robustness of the fusion algorithm. The Kalman filtering results suffer from inaccuracy when process noise is present in the system. In this paper, we use a covariance adaptive scheme that replaces the prediction step of the Kalman filter with covariance. It uses the covariance adaptive scheme to search the posterior sequence online and reconstruct the prior error covariance. Since the process noise covariance is not used in the new adaptive scheme, the negative impact of the mismatch noise statistics is greatly reduced. Simulation and experimental results show that the use of multi-sensor information fusion and covariance adaptive Kalman algorithm has significant advantages in terms of adaptability, accuracy and simplicity.

Strain/displacement field reconstruction and load identification of bracket arm structure of high-speed maglev train based on superposition conversion algorithm

The bracket arm structure, subjected to long-term vertical levitation and transversal guidance forces, is a key load-bearing component of high-speed maglev trains. It is crucial to monitor strain, displacement, and load in real time to evaluate structural health. However, it is almost impossible to measure directly at the service site of trains due to the intricacy of the bracket arm structure and the constrained installation area. Hence, it is an effective and feasible approach to reconstruct the strain/displacement field using a limited amount of strain information from FBG sensors. In order to reconstruct the strain/displacement field and identify the load on complicated structures, a load–strain/displacement superposition conversion algorithm is proposed in this paper. The modal coordinate and the mode-shape matrix are swapped out for the load weight and the load–strain/displacement matrix, respectively. Thus, it gets around the difficulty of choosing the mode order in traditional modal theory. In addition, the algorithm can achieve full-field reconstruction of both strain and displacement by measuring only part of the nodal strain response, reducing the redundancy of the traditional algorithm. Finally, numerical simulations and experimental tests were carried out to verify the feasibility of the proposed method for field reconstruction and load identification.

Blowing away drag for maglev trains

Simulation identifies how air-blowing can reduce drag on high-speed trains and reduce required energy.

Dynamic Response Analysis of a Fiber-Reinforced Polymer Reinforced Viaduct under Full Scale Moving Maglev Train Load

Fiber-reinforced polymers (FRPs) are widely utilized in the construction of bridges all over the world and are thought to be a potential alternative to steel reinforcement, particularly in concrete structures exposed to harsh conditions or the effects of electromagnetic fields. Although some FRP bridges have already been put into service and others are still being built, there is ongoing discussion in the civil engineering community over the efficacy of FRPs in substituting steel in vibration-prone bridge parts. This study adopts finite element modeling based on numerical and analytical approaches to investigate the dynamic behavior of the viaduct during maglev train operation when the steel-reinforced girder concrete is replaced by FRP-reinforced girder concrete. In this way, a realistic coupled maglev train–viaduct system is developed and validated by comparative analysis with data from field experiments. Then, an investigation of the viaduct dynamic behavior when the girder is reinforced with polyacrylic nitrile carbon FRP or S-glass FRP reveals that system displacement is governed by viaduct stiffness, whereas acceleration is governed by structure weight. Nonetheless, the dynamic load frequency has a considerable impact on the efficacy of FRP as viaduct concrete reinforcement, which has been demonstrated to be effective at particular train speeds dependent on the structure’s natural frequency.

Parameter optimization of electromagnetic suspension-type maglev train control system based on multi-objective grey wolf non-dominated sorting hybrid algorithm-Ⅱ hybrid algorithm

This paper presents a novel hybrid algorithm based on CMOGWO-ADNSGA-II to solve the vibration stability problem during the operation of a EMS-type maglev train dynamics model subjected to strong non-linear magnetic buoyancy. The proposed algorithm optimizes the control system parameters of EMS-type maglev train suspensions by combining an improved multi-objective chaotic grey wolf algorithm (CMOGWO) with an improved non-dominated Sorting genetic algorithm-II (ADNSGA-II) to enhance the search capability of the algorithm and ensure population diversity. The efficacy of the algorithm is demonstrated by applying it to the EMS-type maglev train suspension frame control system to find the optimal control parameters. Experimental results show that the system with the optimal parameters applied significantly reduces the suspension gap amplitude and the corresponding standard deviation, as well as the vertical acceleration amplitude and the corresponding standard deviation during operation. The proposed algorithm provides a good solution for EMS-type maglev train suspension vibration control, which can improve its performance and safety.

Mechanical behaviors of the U-girder for urban maglev transit under temperature loads and train loads

The U-girder has been applied to the China’s Fenghuang Maglev Sightseeing Express for the first time around the world, but mechanical behaviors of the U-girder under different loading conditions have not been investigated comprehensively. Firstly, an elaborate finite element (FE) model of the 25 m U-girder considering the longitudinal prestressing tendons and the detailed track structure is built in the paper, and then an in-situ modal test is conducted to validate the FE model. Furthermore, a coupled dynamic model of maglev train-track-girder system is built by the MTS-DCSP distributed co-simulation platform. Secondly, the stress and deformation of the U-girder under the severe temperature gradient loads are analyzed carefully. The results indicate the maximum stresses always appear near the junction between the floor and the track supporting stands, but they are less than the strength of C55 grade concrete. The temperature-induced deflection on the rail can reach 2.91 mm. Thirdly, under jointly the severe temperature gradient loads and maglev train loads moving at 100 km/h, maglev train can run smoothly through the U-girder, deflection and acceleration amplitude of the U-girder are far less than the limits. However, the maximum transverse tensile stress near the junction reaches 3.0 MPa and exceeds slightly the tensile strength, it implies that the U-girder has the cracking risk of concrete.

Study on levitation control performance assessment of maglev train based on minimum entropy

In order to meet the strict requirements of the reliability and safety of the commercial operation of the maglev train, it is necessary to carry out the control performance evaluation of the suspension system. However, at present, variance is often used as the evaluation index of control system. This method cannot get accurate performance evaluation results when the system is affected by non-Gaussian disturbance. Therefore, aiming at the non-Gaussian control performance evaluation of maglev train suspension system, a control performance evaluation method of maglev train suspension system based on minimum entropy is proposed in this paper. In view of the non-Gaussian characteristics in the operation data of maglev train suspension system, this paper introduces the feedback invariant entropy of non-Gaussian system, and then realizes the evaluation and analysis of the control performance of maglev train suspension system based on the minimum entropy criterion. Finally, combined with the evaluation and analysis of the operation data of Changsha medium and low-speed maglev train, this paper verifies the effectiveness and accuracy of the proposed performance evaluation method for the control performance evaluation of maglev train suspension system.

Research on the impact of air-blowing on aerodynamic drag reduction and wake characteristics of a high-speed maglev train

The maglev train fills the speed gap between ground transportation and airplanes. However, the increasing train speed results in greater energy losses due to increased aerodynamic drag, impeding the green and sustainable development of high-speed railways. This study employs the numerical simulation method to explore the effects of installing air-blowing slots on the surface of the TR08 maglev train's tail car and blowing air along three different directions at two different speeds on drag reduction and the characteristics of the wake flow field. Among them, only blowing air along the streamwise direction at speeds of 12 m/s (X12) and 24 m/s (X24) shows drag reduction effects of 2.06% and 6.53%, respectively. However, considering the energy efficiency, only X12 achieves a net energy saving of 58.96%, while the energy consumption by blowing air and saving by reducing drag in X24 are roughly balanced. Air-blowing reduces the aerodynamic lift of the tail car (Cl), with blowing air along the perpendicular direction at 24 m/s (Z24) reducing the Cl by 99.57%. Additionally, Z24 reduces the maximum velocity value of the train-induced air flow (Usmax¯) by 61.91%. The research findings provide new insight and data support for the development of blowing/suction drag reduction techniques.

BrightsightNet: A lightweight progressive low-light image enhancement network and its application in “Rainbow” maglev train

To address the low-light image (LLI) problem in train driving scenarios, this paper proposes a progressive and lightweight network called BrightsightNet for LLI enhancement. First, to overcome the problem of insufficient local exposure level, two structurally identical light curve parameter estimation sub-networks are used for light enhancement in turn. Second, for real-time inference, an efficient feature extraction operator is proposed that combines depth-separable convolution and attention mechanism. Third, the overall network uses encoder–decoder architecture. For the encoder, the output features of the three layers are fused through skip connections to form an information-rich feature map. For the decoder, a hierarchical decoding approach is used to predict the light curve parameters through the three convolution layers sequentially. Experimental results show that BrightsightNet achieves a user study score (USR) of 4.43 on the proposed dataset, outperforming Zero-DCE++, SCI, RetinexDIP, and RUAS by 0.51, 0.86, 0.64, and 1.39, respectively. Moreover, BrightsightNet has parameters of only 2.6K and a single inference time of 0.052 s, which is an innovative and practical solution for low-light image enhancement in train driving scenarios, contributing to safer and more reliable train operations.

Collaborative control of a levitation module for maglev trains with physical contact prevention and user-defined convergence time

The levitation module of maglev trains is contact-prone between electromagnets and guideways due to its high nonlinearity and various external disturbances. Hence, the coupling structure between the electromagnetic points in a levitation module calls for safe and collaborative control. To achieve this goal, this study proposes a novel collaborative levitation control scheme with physical contact prevention. Considering operational safety requirements confronted by the levitation system, a barrier function is introduced to address the physical contact problem, which strictly limits the levitation gap within an allowable range. Moreover, considering the transient response of the controlled system, the predefined-time stability is synthesised, which ensures that the tracking errors converge to a very small neighbourhood of zero within an arbitrarily settling time determined by users. This brings great convenience of tuning controller parameters and avoids non-trivial tuning with a large set of parameters by trails and errors. In addition, quadratic functions are integrated to guarantee the nonsingularity of control signals to enhance practicality. A series of numerical simulations verify the effectiveness of the proposed control scheme.

Unsteady aerodynamic behaviour of high-speed maglev trains during plate braking in tailwind and headwind opening configurations

ABSTRACT High-speed maglev trains are important future rail transportation systems that require high braking performance. One approach to braking in high-speed trains is using aerodynamic plate brakes, which offer improved braking performance at high speeds but can impact the train’s aerodynamic characteristics. In this study, dynamic grid technology was used to achieve plate motion, and unsteady Reynolds-averaged Navier-Stokes (URANS) equations and shear stress transfer (SST) k-ω turbulence model were adopted to simulate the unsteady aerodynamic behaviour of a 5-car maglev train running at 600 km/h. Two wind tunnel experiments validated the method, and grid independence analysis was also conducted. The unsteady aerodynamic performance and transient flow field around the train during plate braking in tailwind and headwind opening configurations were studied and analysed. As the plates opened, there was a rapid increase in both aerodynamic drag and lift, creating a pulse-like change. The tailwind opening configuration generated relatively large peak aerodynamic forces, whereas the peak forces decreased successively downstream along the train length. As the flow stabilized, periodic fluctuations in the aerodynamic forces of the plates occurred. The interference with the convective field and the impact on the aerodynamic force of the tail car were more significant for the tailwind opening configuration. In addition, the tailwind opening plate caused significant fluctuations in the aerodynamic force of the tail car, with similar effects observed in other cars. From an aerodynamic perspective, the headwind opening configuration yielded better results. These findings can guide the design and implementation of plate brakes for high-speed maglev trains.

Protection method of traction power supply system for low and medium speed Maglev traffic based on fault traveling wave features

AbstractLow and medium speed magnetic levitation traffic with short power supply distance and complex grounding network structure, prone to power supply rail grounding faults. However, the existing fault location methods do not accurately locate the fault point, making it difficult for the protective device to act to cut off the fault. To address the above problems, this paper builds a dynamic simulation model of the low and medium speed magnetic levitation power supply rails to study the distribution characteristics of the fault traveling waves after a ground fault occurs in the power supply rails, and analyses the generation mechanism of the traveling wave spectrum through formula calculation. First, the difference in current between the positive and negative bus bars is analyzed to determine whether a ground fault has occurred. Second, the direction of the current difference between stations is compared to locate the faulty section. Finally, the fault distance is calculated from the frequency difference of the fault voltage at the double‐ended station. Through simulation, the method is validated to be unaffected by fault location, fault transition resistance, noise interference, and is applicable to short circuit faults caused by lightning strikes, and the ranging error always remains within 20 m. The method has strong robustness, can effectively solve the problem of protection misoperation and accurately locate the fault point. It is suitable for low and medium speed magnetic levitation transportation power supply rail ground fault.

Design Considerations with Different Shielding Barriers and HTS Resonance Coils for Wireless Power Charging Unit in High-Speed Magnetic Levitation Train

Design Considerations with Different Shielding Barriers and HTS Resonance Coils for Wireless Power Charging Unit in High-Speed Magnetic Levitation Train

Current status and reflection on the development of high-speed maglev transportation

PurposeHigh-speed maglev technology can address the issues of adhesion, friction, vibration and high-speed current collection in traditional wheel-rail systems, making it an important direction for the future development of high-speed rail technology.Design/methodology/approachThis paper elaborates on the demand and significance of developing high-speed maglev technology worldwide and examines the current status and technological maturity of several major high-speed maglev systems globally.FindingsThis paper summarizes the challenges in the development of high-speed maglev railways in China. Based on this analysis, it puts forward considerations for future research on high-speed maglev railways.Originality/valueThis paper describes the development status and technical maturity of several major high-speed maglev systems in the world for the first time, summarizes the existing problems in the development of China's high-speed maglev railway and on this basis, puts forward the thinking of the next research of China's high-speed maglev railway.

Virtual coupling of permanent magnetic maglev trains: An improved cooperative tracking and collision avoidance control protocol

AbstractIn the cooperative tracking task of multiple permanent magnetic maglev trains, system uncertainty, external disturbances, and collision avoidance control are issues that must be considered. Therefore, the cooperative tracking and collision avoidance control for train virtual coupling with external disturbances are studied. First, according to the idea of multi‐agent consensus control and active disturbance rejection control, a cooperative tracking controller based on a novel nonlinear extended state observer (NESO) is designed. Second, a collision avoidance control method based on an improved artificial potential field (APF) is designed. Finally, an improved cooperative tracking and collision avoidance control protocol is proposed, and the stability proof is given. Compared with the conventional protocol, the proposed protocol can achieve smooth coupling and high‐precision cruise while ensuring safe collision avoidance. It has the advantages of higher tracking accuracy and stronger anti‐interference performance.

Concise magnetic force model for Halbach-type magnet arrays and its application in permanent magnetic guideway optimization

In maglev trains, a permanent magnetic guideway (PMG) is an indispensable component that influences their levitation stability. PMG generates the magnetic repulsion force in permanent magnetic levitation and provides the pinning force via coupling with bulk superconductors in superconducting magnetic levitation. Typically, they are arranged in a Halbach array to enhance the magnetic force. However, the spatial inhomogeneous feature of magnetic field makes magnetic force acquisition of the double-sided Halbach array extremely difficult. For accurate magnetic force acquisition, this study proposes a concise analytical magnetic force model and elucidates upon its field behavior. Based on this, a finite element method (FEM) model was developed and verified. The experimental results demonstrated that the Halbach-type PMG’s field distribution was effectively reproduced. Subsequently, the accuracy of the was obtained via comparison with the FEM. The calculation results revealed that the increase in the levitation force tends to be saturated as more magnets are used. For a feasible PMG configuration in terms of high levitation force and low lateral force, the structural parameters were optimized using the multi-objective particle swarm optimization (MOSPO) algorithm combined with the identified magnetic force formulas. The results and findings of this study have significant implications for the design optimization of guideway configurations that heavily rely on permanent magnets.

A Fuzzy-Logic-System-Based Cooperative Control for the Multielectromagnets Suspension System of Maglev Trains With Experimental Verification

A maglev train is a sustainable public transport method with the characteristics of being green, pollution-free, and low-noise, as well as providing environmental protection. However, the performance of existing maglev control strategies for maglev trains may be deteriorated by various challenges, including disregard of the coordination and synchronization between multiple electromagnets, control input unidirectionality, dead zones, saturation, and finite time stability ability, etc. In this paper, an adaptive fuzzy-based suspension control method based on a multi-electromagnets dynamic coupling model is proposed that can cope with dead zone and saturation problems and guarantee the finite-time of the airgap tracking errors of multiple electromagnets simultaneously. Specifically, a fuzzy-logic system (FLS) is utilized to compensate for the nonlinear input unidirectionality, dead zone, saturation and unmodeled dynamics. Moreover, considering the coupling dynamic characteristics of adjacent electromagnet control modules, a fuzzy-based cooperative suspension controller with adaptive update law is designed. The finite time stability of the presented control strategy is proven with the Lyapunov method. Finally, the suspension frame experimental results are illustrated to validate the effectiveness and robustness of the developed method, whose superior performance is shown by being experimentally compared with some baseline methods.

Structural stability analysis for a Maglev design

Magnetic levitation train has the advantage of low vibration and noise compared with ordinary railway systems. It also has the potential to become more energy efficient if permanent magnets are properly incorporated. However, suspension forces provided by the magnetic fields may have dynamic instability that needs to be overcome before such design can be utilized. This talk presents a design of permanent magnet group that overcomes the instability of at least one degree of freedom compared with rudimentary levitation configuration. The magnetic forces between components are derived analytically and the system eigen-value problem is presented. It is shown that, in the rudimentary design, unstable modes occur in two degrees of freedom (lateral and rotational), and the new design suppresses one of the two instability modes (rotational). Initial experimental demonstration is also provided.