Search Results (43)

Maglev transportation has emerged as a new option for long-distance travel between cities with the rapid development of transportation infrastructure. The fatigue issues of the maglev train–track–bridge coupling system, induced by increased train speeds, have garnered considerable attention. This study focuses on the continuous girder bridge of low-to-medium-speed maglev dedicated lines. A multi-vehicle coupling model and a refined vehicle–track–bridge system were constructed. These were based on the maglev equivalent stiffness-damping theory. Dynamic stress is solved using the modal superposition method. Fatigue performance under multiple working conditions is then evaluated. This evaluation uses the rainflow counting method and Miner’s linear damage theory. Dynamic stress is solved using the modal superposition method, and fatigue performance under multiple working conditions is evaluated based on the rainflow counting method and Miner’s linear damage theory. Key findings include the following: Dynamic stress peaks in the track structure reach 29.4 MPa at high-strength bolts and 20.1 MPa at bridge fasteners, significantly exceeding those in the bridge, identifying these as fatigue-sensitive zones. During a single train passage, the stress amplitudes are mainly concentrated in the low-stress amplitude range, yet annual accumulated damage at the critical node track tie and bridge fastener junction reaches 4.99 × 10⁻⁴. Increasing the train speed to 160 km/h amplifies total damage at the track tie and bridge fastener junction by 365%, with nonlinear growth in fastener damage. This research provides theoretical insights for optimizing speed-up strategies and maintenance protocols in low-to-medium-speed maglev systems. Full article

The suspension system of high-speed maglev trains has composite time-delay factors, such as inductance delay and control circuit latency, which lead to a decrease in the tracking and robustness of the current control loop. Based on the study of electromagnetic characteristics of suspension systems, this paper proposes a composite anti-time-delay current loop based on adaptive parameter optimization. First, a finite element analysis model of the suspension electromagnet is constructed to analyze the changes in suspension force and inductance of the suspension electromagnet. A self-tuning PI current loop is constructed to achieve time-varying parameter matching. Second, to tackle the inherent time delays and disturbances in the control loop, a predictive PI control algorithm combined with an extended state observer (ESO) is introduced, which effectively estimates and compensates for disturbances and phase lags. Furthermore, a parameter optimization strategy based on the adaptive differential evolution (ADE) algorithm is proposed to address the difficulties in current loop tuning. The results demonstrate that compared to traditional current loop strategies, the dynamic performance of the designed composite anti-time-delay current loop is significantly improved, enhancing the current following control capability of the suspension system under complex operating conditions. Full article

Spatial efficiency drives the adoption of integrated station–bridge structures in maglev transit, yet the rigid coupling between track and station poses inherent challenges to vibration serviceability. This study isolates the impact of support constraints, specifically contrasting rigid connections with pinned supports, on the dynamic performance of a five-story maglev station. Using a unified, high-fidelity 3D coupled model that incorporates electromagnetic suspension nonlinearity, we evaluated structural responses under train speeds of 60–120 km/h. Simulations identify a critical operational threshold: while the waiting hall remains compliant with standard comfort criteria (DIN 4150-3), the platform floor exceeds the 1.5% g acceleration limit during dual-track operations at speeds ≥ 100 km/h. Beyond standard safety checks, the main scientific innovation of this study is revealing the mechanical transmission paths of structure-borne vibrations at the track-frame interface. The results demonstrate that rigid connections create full mechanical coupling, directly passing train-induced bending moments into the station frame. Conversely, pinned supports release the rotational degrees of freedom, which physically cuts off the primary energy transmission route. By explaining this structural decoupling mechanism, this work moves beyond a specific engineering case study to provide a fundamental theoretical framework for vibration control in complex maglev hubs. Full article

The high-speed Electromagnetic Suspension (EMS) maglev guidance system exhibits inherent characteristics of strong nonlinearity, parameter time-variation, and complex external disturbances. To further optimize and improve the control performance of the guidance system for high-speed maglev trains, a novel intelligent control strategy that integrates the Deep Deterministic Policy Gradient (DDPG) algorithm with Super-Twisting Sliding Mode Control (STSMC) is proposed. Focusing on a single-ended guidance unit with differential control of dual electromagnets, an STSMC controller is first designed based on a cascaded control framework. To overcome the limitation of offline parameter tuning in dynamic operational conditions, a reinforcement learning optimization framework employing DDPG is introduced. A multi-objective hybrid reward function is formulated, incorporating error convergence, sliding mode stability, and chattering suppression, thereby realizing the online self-tuning of core STSMC parameters via real-time interaction between the agent and the environment. Numerical simulations under typical disturbance conditions verify that the proposed DDPG-STSMC controller significantly reduces the amplitude of guidance gap variation and accelerates dynamic recovery compared to conventional PID control. Its superior performance in disturbance rejection, control accuracy, and operational adaptability is validated. This study, conducted through high-fidelity numerical simulations based on actual system parameters, provides a robust theoretical foundation for subsequent hardware-in-the-loop (HIL) experimentation. Full article

Strong crosswinds and train–tunnel aerodynamic interactions cause the aerodynamic loads acting on the train body to change more drastically when a high-speed maglev train enters a tunnel. This greatly raises the risk of safety incidents like derailment or overturning. This study employs the FLUENT 2023 R2 computational fluid dynamics simulation software with an overset grid method to numerically investigate the influence patterns of crosswinds on aerodynamic loads and relevant safety issues for a 600 km/h maglev train entering tunnels under various crosswind conditions. The findings show that (1) the marshaling location has a strong correlation with aerodynamic performance. When there is no crosswind, the head vehicle (HV) has the greatest chance of flipping, while the rear vehicle (RV) has the worst lift characteristics. All three vehicles experience significant sudden changes in lateral force coefficients prior to tunnel entry, indicating considerable derailment risks. (2) Aerodynamic loads on the HV show significantly greater sensitivity to crosswind velocity variations compared to the middle vehicle (MV) and RV, with the amplitude reduction in lateral forces in the HV showing approximately linear increase with wind speed. (3) A 50 km/h reduction in train speed decreases the amplitude of change in the lift coefficient and lateral force coefficient by approximately 4.8% and 8.9%, respectively, and the peak overturning moment in open air and tunnel by approximately 11.4% and 15.7%, respectively. These discoveries have both practical value for advancing high-speed maglev networks and theoretical significance for enhancing the safety and reliability of Chinese maglev systems. Full article

This paper proposes an evolutionary modeling method of scattering clusters based on Geometric-Based Stochastic Modeling (GBSM). In the single-bounce scenario of vacuum pipeline maglev train communication, the dynamic generation and extinction process and statistical behavior of multiple clusters at high speed are analyzed. The model abstracts the multipath component into a cluster structure. By iteratively updating the channel state and the birth and death cluster information after initialization, a dynamic model of the evolution process of scattering clusters in time-varying channels is constructed, which depicts the time evolution process of multipath clusters. Under the framework of GBSM, the correlation statistical characteristics of the scattering cluster birth and death process are further derived, and analytical integral form expression of the channel time autocorrelation function (ACF) is theoretically solved. The simulation results reveal the inherent law of channel time-varying characteristics under the joint action of high-speed train operation and closed pipe structure, and the results show that the proposed method can effectively capture the transient dynamic characteristics and long-term statistical trends of multipath clusters. The proposed model provides a practical basis for channel modeling in vacuum tube maglev wireless communication systems. Full article

The guest room and aisle of electric high-speed maglev train must be shielded from leakage magnetic flux produced by superconducting strong magnetic field. To reduce magnetic leakage, the superconducting magnetic levitation system structure is obtained by extended lagrangian optimization method. The optimized superconducting coil structure has the advantages of reducing magnetic leakage, improving magnetic field utilization, reducing the weight of the magnetic isolation plate and the weight of the maglev train, and enhancing the load-bearing capacity of the maglev train. Based on optimized superconducting coil parameters for high-speed maglev, the magnetic shielding effect at the aisle and the guest room, the magnetic flux density distribution at the magnetic shielding is calculated and analyzed through analytical calculation. The relevant conclusions indicate that the magnetic suspension structure has the advantages of reducing end coil leakage flux and the weight of the high-speed maglev train. Full article

The high-speed maglev train employs linear induction motors for propulsion and incorporates electromagnetic suspension for levitation. Ensuring the stability of the suspension control is imperative for the effective operation of the maglev train at high speeds, necessitating precise calculation of the suspension force. The commonly employed models, while simple in structure, lack the accuracy needed for high-precision suspension control. This paper conducts finite element analysis to simulate the static suspension conditions of high-speed maglev trains and refines the magnetic force calculation model using the obtained data to minimize computational inaccuracies arising from factors like magnetoresistance effects. The revised model is particularly well-suited for scenarios with significant air gaps and elevated currents, showcasing practical value for engineering applications. Full article

Racetrack NbTi superconducting coil is a key component in Maglev train systems due to its excellent mechanical processing performance and lower construction cost. However, dynamic pressures during high-speed operations can influence contact pressures and cause internal filament damage, leading to critical current degradation and quench, which threaten the stable operation of the superconducting magnet. Considering that the NbTi coil has a typical hierarchical structure and comprises thousands of filaments, this study constructs an efficient multiscale framework combining the finite element method (FEM) and self-consistent clustering analysis (SCA) to study the multiscale responses of the NbTi coil. The mechanical responses of the two-scale racetrack coil under monotonic and periodic pressures are investigated, and the effects of the friction contacts between strands are also discussed. The study reveals that internal contacts significantly influence local contact pressures and microscopic stresses, and periodic loading leads to stress accumulation with cycle times. The proposed framework efficiently captures critical microscale responses and can be applied to other multiscale materials and structures. Full article

The hybrid maglev train exhibits advantages such as a large suspension gap, high load-to-weight ratio, and low suspension energy consumption. However, challenges, including unmodeled uncertainties and multi-point coupling interference in the suspension system, may degrade control performance. To enhance the global anti-interference capability of the multi-point hybrid suspension system, an adaptive linear active disturbance rejection cooperative control (ALADRCC) method is proposed. First, dynamic models of single-point and multi-point hybrid suspension systems are established, and coupling relationships among multiple suspension points are analyzed. Second, an adaptive linear extended state observer (ALESO) is designed to improve dynamic response performance and noise suppression capability. Subsequently, a coupling cooperative compensator (CCC) is designed and integrated into the linear error feedback control law of adaptive linear active disturbance rejection control (ALADRC), enabling cross-coupling compensation between the suspension gap and its variation rate to enhance multi-point synchronization. Then, the simulation models are constructed on MATLAB/Simulink to validate the effectiveness of ALESO and CCC. Finally, a multi-point hybrid suspension experimental platform is built. Comparative experiments with PID and conventional LADRC demonstrate that the proposed ALADRC achieves faster response speed and effective system noise suppression. Additional comparisons with PID and ALADRC confirm that ALADRCC significantly reduces synchronization errors between adjacent suspension points, exhibiting superior global anti-interference performance. Full article

Based on the theory of uniform finite-length incoherent line source radiation and real vehicle online test data of Shanghai Maglev trains, a prediction model for environmental noise is established using an equivalent segmented line sound source approach. The noise produced by Shanghai high-speed Maglev trains running at speeds of 235, 300, and 430 km/h is tested and analyzed using microphones. The test data are combined with computational fluid dynamics simulations to divide the train’s sound sources equally into five sections. Theoretical calculations are carried out on the noise test data collected as the train passes by, and the source strength of each individual sub-sound source during the train operation is determined using the least-squares method. As a result, a prediction model for the environmental noise of high-speed Maglev trains, represented as a combination of multiple sources, is developed. The predicted results are compared with the measured values to validate the accuracy of the model. The proposed model can be used for environmental assessments before new train lines are launched, allowing for appropriate mitigation measures to be taken in advance to reduce the impact of Maglev noise on the surrounding residential and ecological environments. Full article

In order to solve the testing and verification problems at the early development stage of a high-speed Maglev positioning and speed measurement system (MPSS), a hardware-in-the-loop (HIL) simulation platform is presented, which includes induction loops, transmitting antennas, a power driver unit, a simulator based on a field-programmable gate array (FPGA), a host computer, etc. This HIL simulation platform simulates the operation of a high-speed Maglev train and generates the related loop-induced signals to test the performance of a real ground signal processing unit (GSPU). Furthermore, an absolute position detection method based on Gray-coded loops is proposed to identify which Gray-coded period the train is in. A relative position detection method based on height compensation is also proposed to calculate the exact position of the train in a Gray-coded period. The experimental results show that the positioning error is only 2.58 mm, and the speed error is 6.34 km/h even in the 600 km/h condition. The proposed HIL platform also effectively simulates the three kinds of operation modes of high-speed Maglev trains, which verifies the effectiveness and practicality of the HIL simulation strategy. This provides favorable conditions for the development and early validation of high-speed MPSS. Full article

In order to improve the operation control performance of high-speed maglev trains, an improved finite-time rotor magnetic Field-Oriented Control method was proposed in this paper. Aiming at the stator current control problem of long-stator linear synchronous motors under parametric perturbation, this paper investigates the double-feeding mode, combines the predefined-time stability theory and designs an improved sliding mode controller to optimise the dynamic characteristics of the inner-loop system. In the outer-loop cruise control, the predefined-time sliding mode control is combined with a finite-time disturbance observer, which effectively solves the problems of inaccurate modelling and parameter ingestion. It was verified through simulation and analysis that the control strategy has significant advantages in improving the dynamic tracking performance and anti-interference ability, with the stator current stabilisation time within 0.1 s, the absolute value of the fluctuation error within 20 A, the outer-loop response time within 0.5 s, the maximum speed error within 0.0005 m/s and the maximum displacement error within 0.0005 m. The control strategy has the advantages of improving the dynamic tracking performance and anti-interference ability. Full article

The suspension system of the Electromagnetic Suspension (EMS) maglev train is crucial for ensuring safe operation. This article focuses on data-driven modeling and control optimization of the suspension system. By the Extended Dynamic Mode Decomposition (EDMD) method based on the Koopman theory, the state and input data of the suspension system are collected to construct a high-dimensional linearized model of the system without detailed parameters of the system, preserving the nonlinear characteristics. With the data-driven model, the LQR controller and Extended State Observer (ESO) are applied to optimize the suspension control. Compared with baseline feedback methods, the optimization control with data-driven modeling reduces the maximum system fluctuation by 75.0% in total. Furthermore, considering the high-speed operating environment and vertical dynamic response of the maglev train, a rolling-update modeling method is proposed to achieve online modeling optimization of the suspension system. The simulation results show that this method reduces the maximum fluctuation amplitude of the suspension system by 40.0% and the vibration acceleration of the vehicle body by 46.8%, achieving significant optimization of the suspension control. Full article

Maglev vehicles apply the entire vehicle load uniformly onto bridges through levitation forces. In assessing the dynamic characteristics of the maglev train–bridge coupling system, it is reasonable to simplify the distributed levitation force as a concentrated force. This article theoretically derives the analytical response of bridge dynamics under the action of a single constant force and conducts numerical simulations for a moving single constant force and a series of equally spaced constant forces passing over simply supported beams and two-span continuous beams, respectively. The topic of discussion is the response of bridge dynamics when different degrees of force concentration are involved. High-precision displacement and acceleration sensors were utilized to conduct tests on the Shanghai maglev line to verify the accuracy of the simulation results. The results indicate that when simplifying the distributed levitation force into a concentrated force model, a frequency ratio can be used to analyze the conditions for resonance between the train and the bridge and to calculate the critical speed of the train; the levitation distribution force of a high-speed maglev vehicle can be simplified into four groups of concentrated forces based on the number of levitation frames to achieve sufficient accuracy, with the dynamic response of the bridge being close to that under distributed loads. Full article