Review of Power Electronic Device Models - Keysight · Review of Power Electronic Device Models ...

Review of Power Electronic Device Models

<Your Name>

EEsof EDA

September, 2014

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Power Electronics: Diverse Application Space

Power Device Models 2

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Diverse Material Systems and Device Technologies


*P. Martin, “HSP: A Surface-Potential-Based Compact Model of AlGaN/GaN HEMTs Power Transistors,” Compact Model Coalition (CMC) Quarterly Meeting, Dec. 2013, Washington, D.C., U.S.A.

Material Properties of Silicon, Silicon Carbide, and Gallium Nitride

Enabling Various Power Electronics Applications*

MOSFET IGBT HEMT

Si √ √

SiC √ √

GaN √

Various Device Architectures

Thermal conductivity

(W cm-1K-1)

Mobility (cm²/V.s) Saturation velocity (107 cm/s)

T max (°C)

Breakdown field

(V/µm)100

200

300

400

50100150

200

23

54

1

1.5

2

2.52000

1500

1000

500

Silicon

SiC

Towards High Current and High Frequency

GaNTowards High Power

Towards High Voltage

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Datasheets and Behavioral Models

– Datasheets

• Device ratings (ex. maximum voltage, current, power, temperature, etc.)

• Key static characteristics

• Key dynamic characteristics

• Output/transfer curves

• Other circuit characteristics (ex. switching energy, delays, etc.)

• Thermal/mechanical characteristics

– Behavioral models

• Usually built based on and reflects datasheet information

• Usually valid for specific conditions


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Needs for More Advanced Models

– Wider and more continuous coverage: bias conditions, operating temperature, various

load conditions

– More efficient circuit design and optimization

– Electro-thermal simulation to account for self-heating

– Consideration of other device characteristics (ex., noise)

– Consideration of unique device-level phenomena (ex., dynamic RON, drain lag)

– Analysis of process variations and corners

– Predictive ability for application-driven process improvement


PageOutline

– Device models for silicon HV MOS transistors, silicon

IGBTs, SiC MOSFETs, and SiC IGBTs

– Device models for GaN HEMTs

– Summary

6Power Device Models

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Silicon High-Voltage MOSFET

– Symmetric high-voltage MOSFET or asymmetric laterally double-diffused MOS

(LDMOS) transistors


*W. Yao, et all., ‘SP-HV: A scalable surface-potential-based compact model for LDMOS transistors,’ IEEE T-ED, vol. 59, no. 3, Mar. 2012, pp. 542-550

𝑉𝐷 = 3,6,9,12𝑉

Cross-section of an LDMOS Transistor* Output I-V Characteristics* Total Gate Capacitance*

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Silicon HV/LDMOS Models

– Sub-circuit based approaches

– HiSIM_HV: CMC industry standard model for

HV/LD MOS


*E. Seebacher, et al., ‘High voltage MOSFET modeling,’ in Compact Modeling: Principles, Techniques and Applications, G. Gildenblat, Ed. New York: Springer-Verlag, 2010, ch. 4, pp. 105–136.†H.J. Mattausch, et al., ‘The Second-Generation of HiSIM_HV Compact Models for High-Voltage MOSFETs,’ IEEE T-ED, vol. 60, no. 2, Feb. 2013, pp. 653-661.

Typical Sub-Circuit Topology for LDMOS

Models*

Surface-Potential-Based

Approach in HiSIM_HV†

Major Recent Improvements in

HiSIM_HV†

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Silicon Insulated-Gate Bipolar Transistor (IGBT)


*A.R. Hefner, ‘Device Models, Circuit Simulation, and Computer-Controlled Measurements for the IGBT,’ Proc. IEEE Workshop Computers in Power Electronics, Aug. 1990, pp. 233-243.

Cross-Section of One-Half of a Symmetric IGBT Cell*

GateEmitter

Collector

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Silicon IGBT Physics-based Models


*A.R. Hefner, ‘Device Models, Circuit Simulation, and Computer-Controlled Measurements for the IGBT,’ Proc. IEEE Workshop Computers in Power Electronics, Aug. 1990, pp. 233-243.†M. Miyake, et al., ‘HiSIM-IGBT: A Compact Si-IGBT Model for Power Electronic Circuit Design,’ IEEE T-ED, vol. 60, no. 2, Feb. 2013, pp. 571-579.

Formulation of the Hefner Model*

– Square-law MOST I-V

Formulation of HiSIM-IGBT Model†

– HiSIM2’s surface-potential based approach

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SiC MOSFET Models

– University of Arkansas model*

• Based on the MOSFET portion of the Hefner IGBT

model

• Two parallel MOSFETs to account for corner conduction

• Bias-dependent gate-drain overlap capacitance

• Temperature dependent material properties of SiC

implemented

– The Angelov model†

• Empirical fitting by accurately capturing key

characteristics

• SiC-specific numerical function used in I-V formulation


*T.R. McNutt, et al., ‘Silicon Carbide Power MOSFET Model and Parameter Extraction Sequence,’ IEEE T-PE, vol. 22, no. 2, Mar. 2007, pp. 353-363.†I. Angelov, ‘Compact, Equivalent Circuit Models for GaN, SiC, GaAs and CMOS FET,’ MOS-AK, Baltimore, MD, 2008.

Cross-Section of a SiC DiMOSFET*

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SiC IGBT Model

– University of Arkansas model§

• Based on the Hefner model

• Adopts the enhancements of UA SiC MOSFET model

• Updated SiC mobility high-field degradation model

– HiSIM-SiC-IGBT model†

• Based on HiSIM-IGBT model for silicon

• Updated model parameters to SiC material properties

• Detailed treatment of base carrier distribution including the

punch-through effect for improved turn-off behavior modeling


*S.H. Ryu, et al., ‘Ultra High Voltage (>12 kV), High Performance 4H-SiC IGBTs,’ Proc. IEEE IS-PSDIC, June 2012, Bruges, Belgium, pp. 257-260.§M. Saadeh, et al., “A unified silicon/silicon carbide IGBTmodel,” in Proc. IEEE Appl. Power Electron. Conf. Expo., 2012, pp. 1728–1733.†M. Miyake, et al., ‘Modeling of SiC IGBT Turn-off Behavior Valid for Over 5-kV Circuit Simulation,’ IEEE T-ED, vol. 60, no. 2, Feb. 2013, pp. 622-629.

Cross-Section of a) SiC P-IGBT, and b) SiC N-

IGBT*

a)

b)

PageOutline

– Device models for silicon HV MOS transistors, silicon IGBTs,

SiC MOSFETs, and SiC IGBTs


• Candidate models for CMC standardization

• DynaFET model

– Summary


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GaN HEMT Model Standardization Effort in CMC

– Compact Model Coalition* – an industry body that standardizes and promotes SPICE models for semiconductor

devices as well as compiled modeling interface

• Ex., standard models for silicon MOSFETs, BJTs, resistors, varactors, junction diodes

– Dedicated workgroup for GaN HEMT model standardization launched in Year 2011

– Three-phase standardization process

• Phase I: completed

- Solicitation of models and presentation to CMC

• Phase II: on-going

- Shortlisted candidate models being examined against fundamental requirements and being fitted to

measurement data for CMC evaluation

• Phase III: TBD

- Evaluation on runtime, convergence, operability, etc.

• Balloting for standardization


*Compact Model Coalition, https://www.si2.org/cmc_index.php

https://www.si2.org/cmc_index.php

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Candidate Models

– Requirements for the core model

• As exact, complete, and simple a representation of physical GaN HEMT behavior as possible

• Extensibility of the model from GaN to all III-V FET/HEMT structures would be an added

benefit but is not a strict requirement

• Physically correct in all operating regions

• No unphysical behavior

• As computationally efficient as possible

• Model should be charge based and not capacitance based, and charge conserving

– Candidate models entering Phase II evaluation

• Angelov-GaN model (Chalmers Univ.); COMON model (URV); HSP model (Leti); MVSG-HV

model (MIT);


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Angelov-GaN Model

– Extended from the Angelov model – an empirical equivalent

circuit based model for GaAs HEMT

• Continues to use inflection points as model parameters

• New math function for I-V formulation

• New RC delay circuit in the equivalent circuit for knee

walkout

• Charge based mode in addition to conventional

capacitance only approach

• ..


†I. Angelov, ‘Compact, Equivalent Circuit Models for GaN, SiC, GaAs and CMOS FET,’ MOS-AK, Baltimore, MD, 2008.

Illustration of Using Inflection Points as Model

Parameters in the Angelov-GaN Model†

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Surface Potential Based Modeling Approach

– Secondary effects & parasitics

• Self-heating, dynamic trapping/de-trapping, etc.

• Access resistance, noise, tunneling current, etc.

– Both the COMON* model and the HSP† model are based on the SP approach

17

• 𝑃𝑜𝑖𝑠𝑠𝑜𝑛 𝑒𝑞𝑢𝑎𝑡𝑖𝑜𝑛• 𝑆𝑐ℎ𝑟𝑜𝑑𝑖𝑛𝑔𝑒𝑟 𝑒𝑞𝑢𝑎𝑡𝑖𝑜𝑛

• 𝑆𝑢𝑟𝑓𝑎𝑐𝑒 𝑝𝑜𝑡𝑒𝑛𝑡𝑖𝑎𝑙• 𝑄𝑢𝑎𝑠𝑖 − 𝐹𝑒𝑟𝑚𝑖 𝑙𝑒𝑣𝑒𝑙• Mobile charge

• 𝐶𝑜𝑛𝑡𝑖𝑛𝑢𝑖𝑡𝑦 𝑒𝑞𝑢𝑎𝑡𝑖𝑜𝑛• 𝑇𝑟𝑎𝑛𝑠𝑝𝑜𝑟𝑡 𝑚𝑜𝑑𝑒𝑙

• 𝑪𝒉𝒂𝒏𝒏𝒆𝒍 𝒄𝒖𝒓𝒓𝒆𝒏𝒕 𝑰 − 𝑽• 𝑻𝒆𝒓𝒎𝒊𝒏𝒂𝒍 𝒄𝒉𝒂𝒓𝒈𝒆𝒔 (𝑸 − 𝑽)

• 𝑆𝑒𝑐𝑜𝑛𝑑𝑎𝑟𝑦 𝑒𝑓𝑓𝑒𝑐𝑡𝑠• 𝑃𝑎𝑟𝑎𝑠𝑖𝑡𝑖𝑐𝑠

• 𝑭𝒖𝒍𝒍 𝒎𝒐𝒅𝒆𝒍

*S. Khandelwal, et al., "A robust surface-potential-based compact model for GaN HEMT IC design," IEEE Trans. Electron Devices, vol. 60, no. 10, pp. 3216-3222, 2013. †P. Martin, et al., “A Compact Model of AlGaN/GaN HEMTs Power Transistors Based on a Surface-Potential Approach,” Proc. Int. Conf. MIXDES, June, 2013, Gdynia, Poland, pp. 92-95.

Power Device Models

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MIT Virtual Source GaN (MVSG) High-Voltage Model

– Inspired by the ballistic transport model over the virtual source

– Morphed for the drift-diffusion transport model

– Threshold voltage-based formulation of mobile charges


*U. Radhakrishna, "MIT Unified VS GaNFET (MVSG) Model, " CMC Quarterly Meeting, Dec. 2013, Washington, D.C.

Illustration of Carrier Injection over the

Virtual Source and Corresponding Drain

Current Formulation*

𝐼𝐷𝑊

= 𝑣𝑠𝑎𝑡𝑄𝑖𝑛𝑣.𝑠 + 𝑄𝑖𝑛𝑣,𝑑

2𝐹𝑉𝑠𝑎𝑡

𝑄𝑖𝑥𝑜 = 𝐶𝑔𝑛𝜙𝑡𝑙𝑛 1 + 𝑒𝑥𝑝𝑉𝐺∗ − 𝑉𝑇

∗ − 𝛼𝜙𝑡𝐹𝑓

𝑛𝜙𝑡

PageOutline




• Candidate models for CMC standardization

• DynaFET model

– Summary


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Characterization and Modeling Challenges of GaN HEMTs

– Measuring the DUT over the entire range of operation

– Determining stimulus signals to elicit the relevant dynamic responses & extraction

methods to model independent mechanisms

• Ex. trapping/de-trapping processes for drain lag

– Large-signal fitting often a separated process from DC/small-signal model extraction

– Design inefficiency

• Multiple model cards often required for the same circuit during different circuit

analysis (ex., DC, small signal, and large-signal)

• Different model cards often required just for different DC bias or operating

frequency


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DynaFET Modeling Flow

21

NVNA data + ANN modeling technology for advanced III-V FET simulation

ADSNVNA IC-CAP

NVNA-based device characterization system

based on large-signal waveforms

Natively implemented nonlinear component

in Keysight ADS

Advanced model extraction and

ANN training SW module

Synchronized Bias Supplies

dsgsjdsgs V V T VV 21

) , , , , , ,( 21 dsgsjdsgsD VVTVVI

Power Device Models

J. Xu, et al., “Dynamic FET Model – DynaFET - for GaN Transistors from NVNA Active Source Injection Measurements,” Proc. IEEE IMS, Tampa, FL, June, 2014

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Key Elements of DynaFET Model Technology

– Large-signal NVNA waveform data used in conjunction with DC and S-parameter

measurements for model extraction

• One single time-domain model valid for DC, small-signal, and large-signal over a

broad frequency range, various bias points, and all load conditions

– Artificial neutral networks used for Q-V and I-V formulations

• Accurate fitting and infinitely differentiable

• Robust and fast model computation during simulation

– Self-heating and gate-lag/drain lag models included

• Dynamic behavior of GaN HEMT accurately captured


𝑰𝑮 𝑰𝑫𝒅𝑸𝑮

𝒅𝒕

𝒅𝑸𝑫

𝒅𝒕

𝑮 𝑫

𝑺

𝑉𝑔𝑠

+

−

𝑉𝑑𝑠

+

−

DynaFET Core Model where 𝑰𝑮, 𝑰𝑫, 𝑸𝑮, and

𝑸𝑫 are Formulated Using ANNsJ. Xu, et al., “Dynamic FET Model – DynaFET - for GaN Transistors from NVNA Active Source Injection Measurements,” Proc. IEEE IMS, Tampa, FL, June, 2014

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Large-Signal NVNA Waveform Data Acquisition


Synchronized

Bias Supplies Keysight E5270B

or 4142B

NVNA measurements performed at various:

(1) DC biases

(2) A11 power

(3) A21 power

(4) A21 phase

(5) Ambient temperatures

A11 power A21 power

A21 phasebias biasAmbient

temperatures

PA PABias

T

Bias

T

Controlled by an automated large-signal data

acquisition software application implemented

on top of the PNA-X NVNA

Time, nsec Time, nsec Time, nsec Time, nsec

J. Xu, et al., “Dynamic FET Model – DynaFET - for GaN Transistors from NVNA Active Source Injection Measurements,” Proc. IEEE IMS, Tampa, FL, June, 2014.

T.S. Nielsen, et al., “Doherty Power Amplifier Design in Gallium Nitride Technology Using a Nonlinear Vector Network Analyzer and X-Parameters,” Proc. IEEE CSICS, 2012.

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Artificial Neural Networks


Z1 Z2 Z3 Z4

y1 y2

x1 x2 x3

Vjk

Wki

S Wki

Inputs

xi

Outputs

yj = S Vjk Zk

k

Parameters w = [Wki, Vjk]

• Universal Approx. Thm: Can fit any nonlinear function of many variables

• The model computation is very fast

• Infinitely differentiable

• Can be trained on non-gridded data in any number of dimensions

y1 = f1(x1, x2, x3)

Hidden Neuron Output

Zk = tanh( )

y2 = f2(x1, x2, x3)

Hidden

Neuron

(Ex. ID, IG)

(Ex. T0, Vds, Vgs)

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Gate-Lag/Drain-Lag Models


*J. Xu, et al., “Large-signal FET Model with Multiple Time Scale Dynamics from Nonlinear Vector Network Analyzer Data,” IEEE MTT-S Int. MWS Digest, May, 2010, pp. 417-420.

capture

RF

emit

f

11

2 4 6 8 10 12 14 16 180 20

-8

-6

-4

-2

0

2

-10

4

time, nsec

ts(v

gsin

t[2

,::]-v

sin

t[2

,::])

ts(v

gsin

t_q

[2,::])

2 4 6 8 10 12 14 16 180 20

20

25

30

35

15

40

time, nsec

ts(v

dsin

t[2

,::]-v

sin

t[2

,::])

ts(v

dsin

t_q

[2,::])

2 4 6 8 10 12 14 16 180 20

-8

-6

-4

-2

0

2

-10

4

time, nsec

ts(v

gsin

t[1

,::]-v

sin

t[1

,::])

ts(v

gsin

t_q

[1,::])

2 4 6 8 10 12 14 16 180 20

20

25

30

35

15

40

time, nsec

ts(v

dsin

t[1

,::]-v

sin

t[1

,::])

ts(v

dsin

t_q

[1,::])

2 4 6 8 10 12 14 16 180 20

-8

-6

-4

-2

0

2

-10

4

time, nsec

ts(v

gsin

t[0

,::]-v

sin

t[0

,::])

ts(v

gsin

t_q

[0,::])

2 4 6 8 10 12 14 16 180 20

20

25

30

35

15

40

time, nsec

ts(v

dsin

t[0

,::]-v

sin

t[0

,::])

ts(v

dsin

t_q

[0,::])

(t))Min(V(t) gs1 (t))Max(V(t) ds2

(t)Vds

(t)2

(t)1

(t)Vgs

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DynaFET Model Extraction


For model extraction

Auxiliary variables fixed at their steady-state large-signal values

In simulation

Auxiliary variables vary in time according to the coupled equivalent circuits

Auxiliary VariablesTerminal Voltages

(t))V(t), V(t), (t), (t), (t), T(t), V(VI(t)I dsgsjdsgsDdrain 21

NVNA

Waveforms

Auxiliary Variable

Generation

Constitutive Relation

Identification / Train Artificial Neural

Networks (ANNs)Terminal Voltages

(Vgs, Vds)

Natively Compiled

Model in ADS

Auxiliary

Variables

th0j RtV tITT )()(

))(())(( tVMax ,tVMin ds2gs1

(t))Ave(VV(t)) , Ave(VV dsdsgsgs

jT gsVdsV

21

(t))V(t), V(t), (t), (t), (t), T(t), V(VI(t)I dsgsjdsgsDdrain 21

dsgsjdsgs V V T VV 21

) , , , , , ,( 21 dsgsjdsgsD VVTVVI

ANNs used to model the detailed,

general, multi-variate coupling

• Accurate and general

• No additional assumptions

(e.g., backgating/virtual gate)

PageOutline




– Summary


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Summary

– Design efficiency and time-to-market in power electronics requires advanced device models as

the industry keeps growing and becomes more competitive

• Better fitting accuracy

• Global coverage over operating conditions and simulation analyses

• Scalability over device geometry

• Support for electro-thermal simulation, etc.

– Power device modeling is actively researched for all types of material and device architectures.

– Industry standardization of GaN HEMT models is pursued through concerted effort by CMC

– DynaFET model provides a general, accurate modeling solution with excellent results for linear

and nonlinear simulation for GaN HEMTs enabled by NVNA data and ANN technology


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Extra slides


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Drain Lag in GaN HEMT

– Degradation of drain current caused by increase of the drain voltage of the quiescent

point, usually referred to as “current collapse” or “knee walkout”


[-0.2, 4]

Vds (V)

Id (mA)

Pulsed I-V Measurements with Two Different Quiescent Points

[-0.8, 6]

“knee walkout”

Quiescent Bias PointId (mA)

Vds (V)

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Measurement Space

Copyright Keysight Technologies,

2014

31

Raytheon

6x60 mm

GaN HFET

Experiment design

covers entire

operating range;

Well beyond

static data

1-Tone, 16GHz

50ohm load

20V, 54mA

NVNA Measurements

DC

J. Xu, et al., “Dynamic FET Model – DynaFET - for GaN Transistors from NVNA Active Source Injection Measurements,” Proc. IEEE IMS, Tampa, FL, June, 2014.

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