High Precision Model by Error Compensation Method based on the Angelov Model

2019 
With the development of the microelectronics, circuit design also becomes more and more important. The circuit needs to be designed by the model, and the accuracy of the model will also determine the quality of the circuit design. In order to improve the accuracy of circuit design, it is necessary to improve the accuracy of the circuit model. This paper mainly discusses a more accurate method basing on the Angelov Model of the Gallium Nitride (GaN) based high electron mobility transistors (HEMTs). For the Angelov Model, the fitting of DC curve is the most critical. There are many parameters to fit and modify the fitting curve. Some of these parameters are of certain physical significance, while others are mainly used to improve the accuracy of curve fitting. Each parameter does not change with the bias, which will lower the accuracy of the model. In this paper, the sensitive parameters in the model are changed into a function of gate voltage and drain voltage by formula. In this way, the fitting accuracy of the model is improved. However, the improvement of the model accuracy is very limited by changing the sensitive parameters. Next, the curve is compensated by error function to improve the accuracy of the whole model. It also makes up for the defect that the Angelov Model cannot fit when the drain current is negative. In order to further improve the accuracy of the model, the weight function is used to correct the error function, which improves the fitting accuracy of the error function and makes the fitting of the output curve more accurate. Finally, the accuracy of the model was improved by 57%, which satisfied the needs of the circuit design.
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