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Simulation Of Mid-to-low Speed Maglev Train Regenerative Braking And Movement Energy Consumption

Posted on:2015-07-07Degree:MasterType:Thesis
Country:ChinaCandidate:B AnFull Text:PDF
GTID:2322330509960561Subject:Control Science and Engineering
Abstract/Summary:PDF Full Text Request
Mid-to-low speed maglev train is a new kind of urban rail transit, with its steadily running, high riding quality, small turning circle and excellent grade ability. Normally, the maglev train's running lines are so short and stations are so dense that its power varies much, due to its frequently booting and braking. According to the characteristic, a maglev train adopts the way of regenerative braking which is being used widely in urban rail transit. Regenerative braking means that when the train needs limiting its speed, the working condition of the motor has been changed from electric motor to generator. At the same time, the kinetic energy of the braking train has been transferred to the tractive DC electrical net as electric power. However, if the regenerative power which has accumulated in the electrical net couldn't be consumed in a short time, the voltage of the net would be too high, following the severe safety consequence because of the failure of regenerative braking. Among the other braking modes, ground rheostatic braking has been adopted as the braking way of the mid-to-low speed maglev train, because of its low cost and mature technology. This paper's main effort as follows:(1) Based on the feature of the maglev train, key analyses about maglev train's force and motion has been made when its running, on the condition of mass particle point model and traction calculation model which have already been built.(2) The urban rail transit DC traction power supply system model is made. As the dynamic model is nonlinear and time-varying, this paper adopts Broyden rank 1 algorithm which comes from Quasi-Newton method.(3) Based on the genetic algorithm, the maglev train's energy consumption on the Tangshan test line is reduced through improving working model changing strategy. And also the basic rules of energy consumption are brought up.(4) According to the actual project of Beijing S1, the simulation result could figure out the importance of the setup of ground braking resistance for Beijing S1, and suggest the capacity of the ground resistance.
Keywords/Search Tags:Maglev Train, Regenerative Braking, Ground Rheostatic Energy Consumption, Genetic Algorithm, Quasi-Newton Algorithm
PDF Full Text Request
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