A scalable large‐signal model with self‐heating effect based on a hybrid‐scaling rule for GaN high‐electron‐mobility transistors. (19th May 2021)

• Record Type: Journal Article
• Authors: Gu, Siyu
• Other Names: Yan Su guestEditor.; Liu Yang guestEditor.
• Is Part Of: International journal of numerical modelling. Volume 34:Number 6(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-05-19
• Subjects: GaN HEMT -- hybrid‐scaling rule -- large‐signal model -- parameter extraction -- scalable model; Electric networks -- Mathematical models -- Periodicals; Electronics -- Mathematical models -- Periodicals; 621.3011
• DOI: 10.1002/jnm.2905
• Languages: English
• ISSNs: 0894-3370

Abstract

Abstract: In this paper, a novel hybrid‐scaling rule for GaN high‐electron‐mobility transistors (HEMTs) scalable large‐signal model with self‐heating effect is proposed. Due to the complex parasitic characteristics of large gate‐width GaN HEMT devices, nonlinear scaling rules are used to consider the dependence of the extrinsic inductances, extrinsic resistances, and thermal resistance on the gate width. In addition, a drain‐source current model and gate capacitance models are proposed to improve the accuracy of traditional Angelov model. A one stage resistor‐capacitor network is attached in the current model to characterize self‐heating effect. Therefore, a scalable large‐signal model based on a hybrid‐scaling rule is presented for the first time. Compared with traditional linear scalable model, the proposed model has a good prediction for multi‐bias S‐parameters and direct current (DC) I‐V curves of different size devices, and can also significantly improve the fitting degree of S22 parameter at high frequency. Moreover, the proposed scalable model shows a good prediction of large‐signal characteristics for large size GaN HEMT devices.