Jin-hui Li

The Active Control of Maglev Stationary Self-Excited Vibration With a Virtual Energy Harvester

This paper addresses the active control of stationary self-excited vibration, which degrades the stability of the levitation control, decreases the ride comfort, and restricts the construction cost of the maglev system. First, a minimum interaction model containing a flexible bridge and a single levitation unit is presented. Based on the minimum interaction model, the principle underlying the self-excited vibration is explored. It shows that the active property of the levitation system is the root of self-excited vibration. Consider that the energy of vibration may be absorbed by the electromagnetic energy harvester (EEH), so that a technique applying it to the bridge is proposed, and the stability of the combined system is analyzed. However, its hardware structure is complicated, and the cost of construction is prohibitive. Then the novel conception of the virtual EEH is brought forward, which uses the electromagnetic force to emulate the force of a real energy harvester acting on the bridge. With the estimation of the vertical velocity of the bridge and the frequency of vibration, the self-oscillatory is avoided as well by adding an extra control instruction to the electromagnet. After building the overall dynamic model with details, numerical simulations and field experiments are carried out, and the results illustrating the improvement of stability are provided and analyzed.

The Modeling and Analysis for the Self-Excited Vibration of the Maglev Vehicle-Bridge Interaction System

This paper addresses the self-excited vibration problems of maglev vehicle-bridge interaction system which greatly degrades the stability of the levitation control, decreases the ride comfort, and restricts the cost of the whole system. Firstly, two levitation models with different complexity are developed, and the comparison of the energy curves associated with the two models is carried out. We conclude that the interaction model with a single levitation control unit is sufficient for the study of the self-excited vibration. Then, the principle underlying the self-excited vibration is explored from the standpoint of work acting on the bridge done by the levitation system. Furthermore, the influences of the parameters, including the modal frequency and modal damping of bridge, the gain of the controller, the sprung mass, and the unsprung mass, on the stability of the interaction system are carried out. The study provides a theoretical guidance for solving the self-excited vibration problems of the vehicle-bridge interaction systems.

The Active Fractional Order Control for Maglev Suspension System

Maglev suspension system is the core part of maglev train. In the practical application, the load uncertainties, inherent nonlinearity, and misalignment between sensors and actuators are the main issues that should be solved carefully. In order to design a suitable controller, the attention is paid to the fractional order controller. Firstly, the mathematical model of a single electromagnetic suspension unit is derived. Then, considering the limitation of the traditional PD controller adaptation, the fractional order controller is developed to obtain more excellent suspension specifications and robust performance. In reality, the nonlinearity affects the structure and the precision of the model after linearization, which will degrade the dynamic performance. So, a fractional order controller is addressed to eliminate the disturbance by adjusting the parameters which are added by the fractional order controller. Furthermore, the controller based on LQR is employed to compare with the fractional order controller. Finally, the performance of them is discussed by simulation. The results illustrated the validity of the fractional order controller.

Suspension system status detection of maglev train based on machine learning using levitation sensors

The objective of this paper is to design a new method, based on machine learning, to detect the abnormal status of the suspension system of maglev train by using the real-time signals collected by the levitation sensors. The abnormal status is harmful to the operation of maglev train. It is necessary to detect the abnormity timely. Generally, the operation data of train is recorded online, but it is analyzed by experts off-line, the efficiency of this approach is very low. So, an efficient and accurate method is urgently demanded. There are 120 levitation sensors in a carriage, which measure the levitation states with nearly 40khz sampling frequency. In tradition, the information of sensors is just used as the feedback of suspension controllers. This paper will study how to use these information for detecting the abnormal status of suspension system by using support vertical machine (SVM). Firstly, some reasonable features originate from experience are extracted from levitation sensors. Secondly, considering that the fault rate is very low, resulting in less fault samples. So, the SVM method is introduced. At last, the raised machine learning model is applied in the practical usage on maglev train by using the programming in the Digital signal processor (DSP) controller. By this method, the existing abnormal status of suspension system can be diagnosed in real-time. The experiment results show that this algorithm can achieve the detection accuracy of 91.3%.

The underlying principles of self-excited vibration in maglev vehicle-bridge coupled system

The maglev stationary self-excited vibration problems degrade the stability of the levitation control, decrease the ride comfort, and restrict the construction cost of maglev system. To master the problems, the underlying principles the self-excited vibration are explored from three aspects. First of all, a minimum interaction model containing a flexible bridge and a single levitation unit is presented. Then based on the minimum interaction model, the underlying principle of the self-excited vibration from the energy transmission is explored. It shows that the active property of the levitation system is the root of self-excited vibration. Secondly, the bridge subsystem is seen as the forward channel and the levitation subsystem is viewed as the feedback channel of the coupled system. In this case, the underlying principle of the self-excited vibration from the characteristic polynomial of the coupled system is listed. Thirdly, the stability is explored from the open-loop transfer function, and four conclusions are obtained, which may provide theoretical references for the suppression of maglev stationary self-excited vibration problems.