• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.5
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• pp.243-250
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• 2018

In this paper, design technique using genetic algorithms(GA) for design optimization of composite leaf springs is presented here. After the initial design has been validated by the car plate spring as a finite element model, the genetic algorithm suggests the process of optimizing the number of layers of composite materials and their angles. Through optimization process, the weight reduction process of leaf springs and the number of repetitions are compared to the existing algorithm results. The safety margin is calculated by organizing a finite element model to verify the integrity of the structure by applying an additive sequence optimized through the genetic algorithm to the structure. When GA is applied, layer thickness and layer angle of complex leaf springs have been obtained, which contributes to the achievement of minimum weight with appropriate strength and stiffness. A reduction of 65.6% original weight is reached when a leaf steel spring is replaced with a leaf composite spring under identical requirement of design parameters and optimization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8187-8194
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• 2015

To accelerate a heavy roller coaster train with over 1G force, a lot of thrust is required and linear synchronous motor(LSM) as propulsion method is suitable for this kind of system. To increase the propulsion efficiency of LSM, precise and real-time position information of vehicle is required for accurate phase control. However, the discontinuous position information with relatively long time interval is usually transmitted from the hall-sensors on the track every magnet length. In this paper, the basic motor model based on traditional dq-axis equations is described and the motor dynamic model is produced by considering the cogging force and friction loss. To improve the position accuracy, the position estimator is also proposed for LSM control system. Simulations were performed to check the characteristics of the torque control system which includes the position estimator based on the motor model. Simulation results based on the linearized model show that this control system has an enough bandwidth and phase margin and the executed algorithm achieves an ideal effect to follow the real-time position signal. Therefore, the feasibility of position estimator is also confirmed.