What is the Angelov model for a GaN HEMT and when is it appropriate to use?

The Angelov model (also known as the Chalmers model, developed by Iltcho Angelov at Chalmers University) is the most widely used nonlinear transistor model for GaN and GaAs HEMT power amplifier design. It models the drain current using hyperbolic tangent functions: I_DS = I_PK × (1 + tanh(psi)) × tanh(alpha × V_DS), where psi = P1 × (V_GS - V_PK) + P2 × (V_GS - V_PK)² + P3 × (V_GS - V_PK)³ + ... The parameters: I_PK = peak transconductance current, V_PK = gate voltage at peak transconductance, P1, P2, P3 = polynomial coefficients that shape the transfer characteristic, alpha = channel modulation parameter (controls the knee region). Why the Angelov model is preferred for GaN PA design: (1) Accurate representation of the GaN I-V characteristics: the tanh function naturally captures the saturation behavior of the drain current (the current increases linearly at low V_DS, then saturates). The polynomial psi function accurately models the bell-shaped transconductance (g_m peaks at V_PK and rolls off at both higher and lower V_GS). (2) Charge-conservative model: the gate capacitances (C_gs, C_gd) are derived from a charge model (Q_gs(V_GS, V_DS), Q_gd(V_GS, V_DS)) that ensures charge conservation. This is essential for accurate harmonic and intermodulation simulation (non-charge-conservative models can produce unphysical current at harmonics). (3) Dispersion model: the Angelov model includes separate DC and RF drain current sources. The RF current source uses different parameters than the DC source, capturing the current collapse and trap effects in GaN. This is critical for GaN PA design (the RF load line and efficiency differ significantly from the DC prediction due to trap-induced current collapse). When to use: PA design (the model is optimized for large-signal behavior). Mixer and oscillator design (the harmonic distortion and nonlinear capacitance are accurately captured). Any circuit design using GaN or GaAs HEMTs where nonlinear behavior matters.