Electric Motor Research Center, Korea Electrotechnology Research Institute, Boolmosangil 70, Changwon, 641-120, Korea.
Sensors (Basel). 2010;10(7):6718-29. doi: 10.3390/s100706718. Epub 2010 Jul 9.
This paper presents an optimum design of a lightweight vehicle levitation electromagnet, which also provides a passive guide force in a magnetic levitation system for contactless delivery applications. The split alignment of C-shaped electromagnets about C-shaped rails has a bad effect on the lateral deviation force, therefore, no-split positioning of electromagnets is better for lateral performance. This is verified by simulations and experiments. This paper presents a statistically optimized design with a high number of the design variables to reduce the weight of the electromagnet under the constraint of normal force using response surface methodology (RSM) and the kriging interpolation method. 2D and 3D magnetostatic analysis of the electromagnet are performed using ANSYS. The most effective design variables are extracted by a Pareto chart. The most desirable set is determined and the influence of each design variable on the objective function can be obtained. The generalized reduced gradient (GRG) algorithm is adopted in the kriging model. This paper's procedure is validated by a comparison between experimental and calculation results, which shows that the predicted performance of the electromagnet designed by RSM is in good agreement with the simulation results.
本文提出了一种轻型车辆悬浮电磁铁的优化设计，该电磁铁在用于非接触式输送应用的磁悬浮系统中还提供被动导向力。C 形电磁铁相对于 C 形轨道的分裂对准对横向偏差力有不良影响，因此，电磁铁的无分裂定位更有利于横向性能。这通过模拟和实验得到了验证。本文提出了一种统计优化设计，使用响应面法（RSM）和克里金插值方法，使用大量设计变量在法向力的约束下降低电磁铁的重量。使用 ANSYS 对电磁铁进行二维和三维静磁分析。通过 Pareto 图提取最有效的设计变量。确定最理想的集合，并获得每个设计变量对目标函数的影响。广义缩减梯度（GRG）算法用于克里金模型。本文的程序通过实验和计算结果的比较进行了验证，结果表明，RSM 设计的电磁铁的预测性能与模拟结果吻合良好。
