摘要
针对传统的电力电子电路参数辨识仅对部分器件进行辨识,未辨识到所有器件特征参数值,无法准确判断电路当前状态的问题,建立了基于电感电流与输出电压的电路混杂系统模型,使用粒子群优化算法将参数辨识问题转化为目标函数优化问题,求解得到电路中所有关键元器件的特征参数值,以更好地表征电路的健康状态。仿真实验结果表明该方法的辨识精度达到98%以上,有较好的辨识效果。
This paper establishes a hybrid system model based on inductor current and output voltage,for the traditional power electronic circuit parameter identification can only get some feature parameters and cannot accurately determine the current state of the circuit. If particle swarm optimization is used to transform the parameter identification to objective function optimization,it can obtain characteristic health state of the circuit. The simulation results show that the accuracy of the method is more than 98%,and its recognition effect is good.
引文
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