Search Results (84)

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

With the continuous development of maglev transportation technology, medium–low-speed maglev trains have been widely implemented in many countries. However, due to the limitations of existing specifications, the stiffness limit values of the large-span main girders used in medium–low-speed maglev trains have not been unified. To address this issue, this study takes a specific bridge on a dedicated maglev line as an example and uses self-developed software to model the vehicle–bridge dynamic system. The natural vibration characteristics and vehicle–bridge coupling vibration response of the bridge are calculated and analyzed. Based on this, the influence of pier top stiffness on the dynamic characteristics of a typical medium–low-speed maglev train–bridge system under different working conditions is investigated, with a focus on the lateral line stiffness at the pier top. The results show that vehicle speed has no significant effect on the lateral displacement of the main girder, the lateral displacement of the pier top, the lateral acceleration of the pier top, and the transverse and longitudinal angles of the beam end, and no obvious regularity is observed. However, in the double-track operating condition, the vertical deflection of the main girder is significantly higher than that in the single-track operating condition. As the lateral linear stiffness at the pier top increases, the fundamental frequency of the bridge’s lateral bending vibration gradually increases, while the fundamental frequency of longitudinal floating gradually decreases. The lateral displacements, including those of the main girder, pier top, and beam ends, all decrease, whereas the lateral and vertical vibration accelerations of the main girder and the train are less affected by the lateral stiffness at the pier top. Full article

The propulsion system is a critical component of medium–low-speed maglev trains and the single-sided linear induction motor (SLIM) has been adopted to generate thrust. However, the SLIM operates periodically in maglev trains. The temperature of the secondary plate of the SLIM rises significantly due to eddy currents when the train enters and leaves the station, where large slip occurs. Subsequently, the temperature decreases through natural cooling during the shift interval time. This periodic operating condition is rarely addressed in the existing literature and warrants attention, as the temperature accumulates over successive periods, potentially resulting in thermal damage and thrust variation. Furthermore, the conductivity of plate varies significantly in the process, which affects the losses and thrust, requiring a coupled analysis. To investigate the temperature variation patterns, this paper proposes a coupled model integrating the lumped parameter thermal network (LPTN) and the equivalent circuit (EC) of the SLIM. Given the unique structure of the F-shaped rail, the LPTN mesh is well designed to account for the skin effect. Three experiments and a finite element method (FEM)-based analysis were conducted to validate the proposed model. Finally, optimizations were performed with respect to different shift interval time, plate materials, and carriage numbers. The impact of temperature on thrust is also discussed. The results indicate that the minimum shift interval time and maximum carriage number are 70.7 s and 9, respectively, with thrust increasing by 22.0% and 22.0%. Furthermore, the use of copper as the plate material can reduce the maximum temperature by 22.01% while decreasing propulsion thrust by 26.1%. Full article

Magnetic levitation (maglev) technology offers significant advantages for rail transport, including frictionless propulsion, reduced noise, and lower maintenance costs. However, its widespread adoption has been limited due to the need for a dedicated infrastructure incompatible with conventional rail networks. The MaDe4Rail project, funded by Europe’s Rail Joint Undertaking (ERJU), explores Maglev-Derived Systems (MDSs) as means to integrate maglev-inspired solutions into existing railway corridors with minimal modifications. This paper focuses on the so-called “hybrid MDS” configuration, which refers to levitating systems that can operate on existing rail infrastructure. Unlike current maglev systems, which require dedicated tracks, the proposed MDS system is designed to operate on conventional rail tracks, allowing for its compatibility with traditional trains and ensuring the interoperability of lines. In order to identify the most viable solution, two different configurations have been analysed. The evaluated scenario could benefit from the introduction of hybrid MDSs based on magnetic levitation, where a group of single vehicles, also called pods, is used in a virtual coupling configuration. The objective of this case study is to increase the capacity of traffic on the existing railway line by significantly reducing travel time, while maintaining a similar energy consumption to that of the current conventional trains operating on this line. Simulation results indicate that the hybrid MDS can optimise railway operations by taking advantage of virtual coupling to improve traffic flow, reducing travel times and energy consumption with the optimisation of the aerodynamic drag. The system achieves a balance between increased speed and energy efficiency, making it a viable alternative for future rail transport. An initial cost–benefit analysis suggests that the hybrid MDS could deliver substantial economic advantages, positioning it as a promising solution for enhancing European railway networks with minimal infrastructure investment. Full article

Achieving accurate positioning of maglev trains is one of the key technologies for the safe operation of maglev trains and train schedules. Aiming at magnetic levitation train positioning, there are problems such as being easily interfered with by external noise, the single positioning method, and traditional weighting affected by historical data, which lead to the deviation of positioning fusion results. Therefore, this paper adopts self-corrected weighting and Sage–Husa noise estimation algorithms to improve them and proposes a research method of multi-sensor information fusion and positioning of an AUKF magnetic levitation train based on self-correcting weighting. Multi-sensor information fusion technology is applied to the positioning of maglev trains, which does not rely on a single sensor. It combines the Sage–Husa algorithm with the unscented Kalman filter (UKF) to form the AUKF algorithm using the data collected by the cross-sensor lines, INS, Doppler radar, and GNSS, which adaptively updates the statistical feature estimation of the measurement noise and eliminates the single-function and low-integration shortcomings of the various modules to achieve the precise positioning of maglev trains. The experimental results point out that the self-correction-based AUKF filter trajectories are closer to the real values, and their ME and RMSE errors are smaller, indicating that the self-correction-weighted AUKF algorithm proposed in this paper has significant advantages in terms of stability, accuracy, and simplicity. 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

To address the nonlinearity and control problems of the Maglev system caused by external disturbances and internal factors of the system, this study first established a kinematic model of a single-point levitation system. Secondly, based on the nonlinear characteristics of the kinematic model, Gaussian noise was introduced into the model as input disturbance, and a neural network was used to train the constructed model. A nonlinear autoregressive model with exogenous inputs was constructed, and the Recursive Least Squares method with Forgetting Factor (RLS-FF) was used to perform parameter identification on the levitation system by combining the training data, further constructing an accurate model of the levitation system. Then, based on the accurate model of the levitation system, the backstepping method was adopted to design an adaptive controller for the levitation system, and its stability was verified. Simulation analysis was conducted on the MATLAB/Simulink platform, and comparisons were made with the LQR control method and the Fuzzy-PID control method that verified that the designed controller had a faster response speed and better self-regulation ability. At the same time, interference signals were introduced into the simulation to simulate the actual scene, and the good anti-interference ability and adaptive performance of the designed controller were further verified. Full article

As a new type of rail transit vehicle, maglev trains have extremely high requirements for safety and reliability. With the gradual commercial operation of maglev trains, how to scientifically and effectively assess the safety and analyze the risks of train equipment has become an urgent issue to be addressed. Against the backdrop of the practical application of maglev train projects, this paper integrates domestic and international risk analysis models, proposes the steps for conducting the risk analysis of maglev rail transit, and establishes a risk analysis system for the entire lifecycle of maglev rail transit. Based on the results of fault analysis, a risk analysis of the levitation system is carried out. The theory of multi-attribute decision-making is studied, new risk evaluation indicators are established using triangular fuzzy numbers, the risk levels of the levitation system are determined, and the weak links within the system and the relationships between the pieces of equipment are identified. These efforts provide guidance for enhancing the safety and reliability of train equipment and for carrying out train maintenance work. 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

Magnetic levitation (maglev) offers unique opportunities for guided transport; however, only a few existing maglev systems have demonstrated their potential benefits. This paper explores the potential of maglev-derived systems (MDS) in conventional rail, focusing on the use of linear motors to enhance freight operations. Such traction boosters provide additional propulsion capabilities by reducing the train consist’s dependence on wheel–rail adhesion and improving performance without needing an additional locomotive. The study analyses the Gothenburg–Borås railway in Sweden, a single-track, mixed-traffic line with limited capacity and slow speeds, where installing linear motors on uphill sections would allow freight trains to match the performance of passenger trains, even under challenging adhesion conditions. Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. The results show that freight trains can achieve desired speeds but at the cost of increased energy consumption. A system-level cost–benefit analysis reveals a positive impact with a positive benefit-to-cost ratio. Although energy consumption increases, the time savings and reduced CO₂ emissions from shifting goods from road to rail demonstrate substantial economic and environmental benefits, improving the efficiency and sustainability of rail freight traffic. Full article

To ensure safety and passenger comfort, for the medium- and low-speed Maglev transportation system, very strict control standards were developed and set into action. The relevant high costs were therefore not conducive to the promotion of this advanced mode of transportation. Moving from the above described situation, field tests were carried out at the Maglev test line located in Shanghai Lin’gang. The dynamic response of the Maglev system was studied under the influence of beams of the supporting frame with a varying stiffness and under different environmental (in terms of temperature) effects. The collected data showed that the system can guarantee good stability under relatively unfavorable ambient conditions so that the effect of temperature on the dynamic response of the system lies within an acceptable range. 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

During the operation of maglev trains, they are subjected to various disturbances. The presence of these disturbances presents a significant challenge for attaining high-performance control and even poses the risk of system instability. To further enhance the anti-disturbance capability of maglev trains, this paper proposes a model information-assisted modified active disturbance rejection control (MADRC) approach. A mathematical model of the single-point suspension system of maglev trains is constructed for the design of the extended state observer (ESO), which is a modified extended state observer (MESO), and a nonlinear mechanism is incorporated to boost the performance of the ESO. Owing to the introduction of model information, the estimated quantity of disturbances by MESO no longer considers the system model deviation as a disturbance. Hence, the linear feedback control law is modified accordingly. The MESO is regarded as an ESO with time-varying gain using the equivalent gain method, and its stability is proven using the Lyapunov method. The tracking and anti-disturbance performances of different controllers are compared via simulation experiments. Suspension and anti-disturbance experiments are conducted on the single-point suspension experimental platform, verifying that the proposed MADRC has a more potent suppression ability for load disturbances in the suspension system. 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