三相逆变器数字孪生系统的参数辨识研究

电力电子变换器的参数辨识能提升系统控制和运行效果，然而传统的参数辨识方法难以同时辨识多组参数且辨识结果精度较低。针对此问题，提出了基于数字孪生的三相逆变器参数辨识方法。首先，构造出数字孪生三相逆变器，包括利用Runge-kutta库塔方法建立三相逆变器主电路的数学模型和控制器离散模型。然后，利用自适应粒子群优化算法更新并优化数字孪生逆变器的电路参数，直至数字孪生逆变器和物理逆变器相应的电路参数相同。最后，通过仿真和实验验证了所提参数辨识方法的有效性。结果表明，该方法在稳态与动态条件下均能快速地辨识出物理逆变器的电感、寄生电阻和开关管内阻参数，辨识结果的相对误差在2%以内。

Parameter identification of three-phase inverters based on a digital twin system

The parameter identification of a power electronic converter can improve the control and operational effect of systems. However, in traditional parameter identification methods, it is difficult to identify multiple groups of parameters at the same time, and the accuracy of the identification results is low. To solve this problem, a parameter identification method of three-phase inverters based on a digital twin is proposed. First, a digital twin three-phase inverter is constructed, including the establishment of the mathematical model of the main circuit of the three-phase inverter using a fourth-order Runge-Kutta method and the establishment of a discrete model of the controller. Then, the circuit parameters of the digital twin inverter are updated and optimized by an adaptive particle swarm optimization algorithm until the corresponding circuit parameters of the digital twin inverter and the physical inverter are the same. Finally, the effectiveness of the proposed parameter identification method is verified by simulation and experiment. The results show that the inductances, parasitic resistances and switch tube internal resistances of the physical inverter can be quickly identified under both steady and dynamic conditions, and the relative errors of identification results are within 2%.