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Optimization of Piezoelectric Transformers Using Genetic Algorithm

机译:基于遗传算法的压电变压器优化

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摘要

In this work, we present the optimization work for piezoelectric transformers (PT) by using the elite Genetic Algorithm (GA). A finite-element solver, NTUPZE, is used to calculate the behaviors of piezoelectric transformers. The design parameters are the dimensions of the devices, and the design optimization objects are the device efficiency and gain. Since GA does not require a gradient function for projection and is capable of dealing with multi-objective optimization problems, it is a good optimization approach for this work. The optimal results of Rosen-type and Rosen-modal-type PTs are presented. The optimized efficiencies for both cases are close to 1 with a 100 kΩ electrical loading connected on the output electrodes.
机译:在这项工作中,我们通过使用精英遗传算法(GA)来介绍压电变压器(PT)的优化工作。有限元求解器NTUPZE用于计算压电变压器的性能。设计参数是设备的尺寸,设计优化的对象是设备的效率和增益。由于GA不需要用于投影的梯度函数,并且能够处理多目标优化问题,因此对于这项工作而言,这是一种很好的优化方法。提出了Rosen型和Rosen模态PT的最佳结果。在输出电极上连接了100kΩ的电负载后,两种情况的最佳效率都接近1。

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