基于遗传算法的磁互斥振动能量采集器多参数优化方法

Multi-Parameter Optimization Method for Magnetic Repulsion Vibration Energy Harvester Based on Genetic Algorithm

为了提高电磁式振动能量采集器的发电效率,为无线传感网络和可穿戴电子设备提供微型、高效、可持续的供电装置,提出了一种基于遗传算法的磁互斥振动能量采集器多参数优化方法。由于多级磁铁同极互斥结构的弹簧-阻尼-质量模型参数复杂,通过将磁铁个数、磁铁长度、线圈相数、各相线圈长度、线圈连接方式的最大发电效率问题描述为遗传算法的多参数优化问题,实现发电效率最大化条件下能量采集器结构参数组合的精确匹配。实验结果表明,参数优化后样机发电性能显著提升,在激励加速度为0.5g、频率为9.5 Hz时,优化前后样机输出电压均达到峰值,分别为2.18和4.86 V。在激励加速度分别为0.3g、0.5g、0.7g时,优化后样机最大输出电压分别为3.68、4.86、6.0 V,最大输出功率分别为9.28、16.18、24.66 mW。

In order to enhance the power generation efficiency of electromagnetic vibration energy harvesters and provide micro-sized,high-efficiency,sustainable power supply devices for wireless sensor networks and wearable electronic devices,a multi-parameter optimization method based on the genetic algorithm for a magnetic repulsion vibration energy harvester was proposed.Due to the complexity of the spring-damper-mass model parameters of the multi-stage magnet same-pole repulsion structure,by describing the issue of maximizing power generation efficiency through the number of magnets,magnet length,coil phase number,individual phase coil length,and coil connection method as a multi-parameter optimization problem for the genetic algorithm,an exact match of the structural parameter combination of the energy harvester under the condition of maximized power generation efficiency was achieved.Experimental results indicate that the power generation performance of the prototype is significantly improved after parameter optimization.With an excitation acceleration of 0.5g and a frequency of 9.5 Hz,the output voltages of the prototype reach peak values before and after optimization,at 2.18 and 4.86 V respectively.At excitation accelerations of 0.3g,0.5g,and 0.7g,the maximum output voltages of the optimized prototype are 3.68,4.86,and 6.0 V,respectively,with maximum output powers of 9.28,16.18,and 24.66 mW,respectively.