摘要
为解决铁电电滞模型中特性参数确定困难的问题,改善模型在工程应用中受限现状,本文利用遗传算法提出一种实用的铁电模型特性参数识别方法,可根据随机试验数据完成特性参数的提取,继而重构铁电模型以模拟各种铁电电容系统的非线性电滞行为.以上方法不但可以预测各种电场条件下的电极化响应,还可预测反映系统特性的理想饱和极化响应.最后,为验证所提方法的有效性,本文进行了仿真计算验证,其结果表明,基于优化参数的电滞模型能够很好地与试验数据吻合,具有较好的精确性和鲁棒性,为铁电系统在实际工程的应用提供有效参考.
Several existing parametric models of ferroelectric materials have limited usage in engineering applications due to the uncertainty of some parameters in the model that can’t be determined appropriately by conventional methods. For this purpose, this paper intends to propose a practical method to identify ferroelectric parameters based on the genetic algorithm(GA). The method follows the procedure: i) collecting a set of polarization test data excited by arbitrary electric input, ii) identifying the characteristic parameters by using GA procedure, and iii) substituting them into the model to demonstrate the nonlinear ferroelectric hysteretic behavior of diverse ferroelectric capacitors. Computational simulations and experimental results are utilized to prove that the proposed approach is very accurate and robust in predicting the hysteresis behavior of the ferroelectric systems in both non-saturated and saturated status. The approach shows a promising potential to be applied in describing the electric polarization behavior of various ferroelectric capacitors.
出处
《力学季刊》
CSCD
北大核心
2016年第3期457-465,共9页
Chinese Quarterly of Mechanics
基金
国家自然科学基金(11172226
11502188)
关键词
铁电材料
力电特性
电滞回线
参数识别
遗传算法
ferroelectric material
electro-mechanical characteristics
electric hysteresis loop
parameter identification
genetic algorithm