An Operation Control Strategy for the Connected Maglev Trains Based on Vehicle‐Borne Battery Condition Monitoring

Zhang, Wenjing; Wu, Wenjun; Yang, Yifan; Nan, Nan

doi:10.1155/2018/5698910

Cited by 13 publications

(9 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The basic resistance is the resistance encountered when the maglev train runs along a flat orbit in an open area. Referring to Zhang et al ( 13 ), the basic resistance F b of the MSM train has three parts: air resistance f air , magnetic resistance f mag , and linear motor resistance f motor caused by the onboard linear generator. The formulas for those resistances are as follows:…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Optimal Energy Speed Profile of Medium-Speed Maglev Trains Integrating the Power Supply System and Train Control System

Lai

Liu

Haghani

et al. 2020

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

As a new type of transportation serving the suburban passengers, the medium-speed maglev (MSM) is gradually becoming the focus of scholars. This paper addressess the speed profile optimization problem for MSM train operations by integrating the power supply system and train control system under various constraints. Unlike the model for optimizing the mechanical energy of the train, this approach aims at the lowest energy consumption of the substation for the MSM system. First, a speed profile optimization model for the MSM train is built by combining the mathematical control model of the long stator synchronous linear motor and dynamic equation of train, in which the stator current is the control variable. Next, a dedicated dynamic programming approach is proposed to solve the optimization model. The results of the numerical experiments show that the proposed model outperforms the model that only considers the train mechanical energy, and the energy consumption is reduced by 10.3% and 6.5% in the two case studies, respectively. Furthermore, the relationship between energy consumption and travel time is analyzed to reflect the optimal results of the proposed model limited to different fixed travel time.

show abstract

Section: Methodsmentioning

confidence: 99%

“…According to Zhang et al ( 13 ), the line resistance F r without considering the tunnel consists of two parts: the gradient resistance f g and the curve resistance f i , which can be calculated as follows:…”

Section: Methodsmentioning

confidence: 99%

Optimal Energy Speed Profile of Medium-Speed Maglev Trains Integrating the Power Supply System and Train Control System

Lai

Liu

Haghani

et al. 2020

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

show abstract

“…Generally, the safety operation of the middle-to-high maglev train needs to satisfy the following five-speed curve limits [5,6]. The location and length of the ASA will affect the speed limit area in case the other line parameters were determined because only the ASA and station were installed with Power Rail (PR).…”

Section: __________________________________________________mentioning

confidence: 99%

“…The maglev system includes three-speed grades: low-to-middle speed maglev  100 km/h, middle-speed maglev  200 km/h and high-speed maglev  400 km/h. At present, except for the lowto-middle speed maglev uses short stator induction linear motor technology [3], the other two all take the long stator synchronous linear motor technology [4,5]. Therefore, the middle-speed maglev and high-speed maglev are similar inline settings.…”

Section: Introductionmentioning

confidence: 99%

Optimization of the auxiliary stopping area planning in the middle-to-high speed Maglev

Lai

Liu

Meng

et al. 2018

Transportation Systems and Technology

View full text Add to dashboard Cite

Background:The Auxiliary Stopping Area (ASA) is the special section that possesses power supply rail and personnel evacuation facilities, whose quantities and locations in a line are of great significance to reduce construction cost and improve transportation efficiency for the middle-to-high speed maglev.Aim: This paper focuses on optimizing the length and location of the ASA for the middle-to-high speed maglev system to improve the robustness of maglev line.Methods: Two evaluation indexes which reflect the ASA restricts on the train operation process was proposed. A model for optimizing the setting of the ASA is constructed, and solved by the genetic algorithm.Results:The result of numerical examples shows that the proposed method can effectively improve the performances of the ASA.Conclusion: This paper proposed two indexes to reflect the impact of station settings on train operations, which provides a method to optimize the ASA from qualitative optimization to quantitative optimization.

show abstract

“…The Magnetic Levitation (Maglev) based train is an efficient and frictionless transport system that fulfills such demands. Such systems have many outstanding attributes, like less noise, larger climbing slope ability, all-weather suitability, and longer life compared to a conventional wheel-rail transportation system [3]. Due to a considerable load mass variation, the suspension control system deployed in maglev trains needs to be robust to system parameter variations [4].…”

Section: Introductionmentioning

confidence: 99%

A Reference Model Assisted Adaptive Control Structure for Maglev Transportation System

2021

View full text Add to dashboard Cite

Maglev transportation system is become a hot topic for researchers because of the distinctive advantages, such as frictionless motion, low power consumption, less noise, and being environmentally friendly. The maglev transportation system’s performance gets sufficiently influenced by the control method and the magnetic levitation system’s dynamic performance, which is a critical component of the maglev transportation system. The Magnetic Levitation System (MLS) is a group of unstable, nonlinear, uncertain, and electromagnetically coupled practical application. Control objective of this study is to design a position stabilizing control strategy for Magnetic Levitation system under extreme uncertain parametric conditions using a reference model governed by a reference stabilizer and nonlinear adaptive control structure. After successful tuning the reference stabilizer with and without time-varying payload disturbance, the tracking-error dynamics are obtained in the presence of both matched and mismatched types of parametric uncertainties. Next, the close-loop stability theorem is formulated for Lyapunov stability analysis to get the design constraints, parameter update laws, and adaptive control law. Numerical simulations performed for a high range of parametric violations check the control design’s efficacy. The performance robustness gets confirmed by comparing the results with the nonlinear control approach. The MLS gets performance recovery and settles within safe limits in few seconds using the proposed methodology. However, the nonlinear controller faces permanent failure in stabilizing the MLS.

show abstract

An Operation Control Strategy for the Connected Maglev Trains Based on Vehicle‐Borne Battery Condition Monitoring

Cited by 13 publications

References 24 publications

Optimal Energy Speed Profile of Medium-Speed Maglev Trains Integrating the Power Supply System and Train Control System

Optimal Energy Speed Profile of Medium-Speed Maglev Trains Integrating the Power Supply System and Train Control System

Optimization of the auxiliary stopping area planning in the middle-to-high speed Maglev

A Reference Model Assisted Adaptive Control Structure for Maglev Transportation System

Contact Info

Product

Resources

About