Automated power semiconductor switchingperformance feature extraction from experimental

double-pulse waveform data

Mark A. H. Broadmeadow, Geoffrey R. Walker and Gerard F. LedwichSchool of Electrical Engineering and Computer Science

Queensland University of TechnologyBrisbane, Australia

Email: mark.broadmeadow@qut.edu.au

Abstract—Double-pulse tests are commonly used as a methodfor assessing the switching performance of power semiconductorswitches in a clamped inductive switching application. Datagenerated from these tests are typically in the form of sampledwaveform data captured using an oscilloscope. In cases whereit is of interest to explore a multi-dimensional parameter spaceand corresponding result space it is necessary to reduce the datainto key performance metrics via feature extraction. This paperpresents techniques for the extraction of switching performancemetrics from sampled double-pulse waveform data. The reportedtechniques are applied to experimental data from characterisationof a cascode gate drive circuit applied to power MOSFETs.

Index Terms—Feature extraction, measurement, powerMOSFETs, switching circuits.

I. INTRODUCTION

Double-pulse tests are commonly used to investigate exper-imentally the switching performance of power semiconductorsin clamped inductive switching applications. These tests canbe used to investigate any number of parameters, ranging fromoperating conditions (voltage, current, temperature), differentsemiconductor devices (MOSFETs, IGBTs, JFETs etc) andgate-drive topologies. Typically one parameter is manipulatedover a limited range, switching waveforms are captured viaoscilloscope and the performance metrics of interest are cal-culated and presented [1].

More rigorous experimental characterisation requires theexploration of multi-dimensional parameter spaces [2]. Whenmore than one degree of freedom is investigated the size ofthe collected dataset rapidly increases with the sample numberof any of the independent variables. Manual extraction ofswitching performance metrics from waveform data for multi-dimensional parameter spaces quickly becomes impractical.Instead, a methodology is proposed in this paper for the collec-tion and automated post processing of double-pulse waveformdata to extract the metrics of interest.

In this paper the proposed automated switching characteris-tic feature extraction techniques are applied to an experimentaldataset collected to assess the performance of cascode gatedrive [3] applied to power MOSFETs in a clamped inductiveswitching application. Double-pulse waveforms are collectedacross a three-dimensional parameter space of gate resistance,gate-source capacitance and load current as investigated in [4].Example feature extraction outputs for these data are presentedalong with visualisation of the switching performance over themulti-dimensional parameter space.

iL

vds

+

–

vgs+

–

Vdrive

Vbusid

Current probe

DUT

Fig. 1. Circuit configuration for a double-pulse test.

II. DOUBLE-PULSE TESTING

The typical double-pulse test fixture is shown in figure 1.A power MOSFET under conventional gate drive is shown asthe device under test (DUT). Note that this is usually the sametest circuit utilised by semiconductor manufacturers whenpresenting switching characteristics on datasheets, includingthe datasheet for the 650V device used in this work [5]. TheDUT is driven with two short on-pulses as shown in figure 2.Pulse one is used to ramp-up the current through the loadinductor. The length of pulse one along with the inductorvalue and bus voltage sets the load current, IL. At the endof pulse one the DUT is driven off and current commutates toand circulates through the clamping diode. Given the forwardvoltage drop of the clamping diode is small compared withthe bus voltage, any decay of the inductor current will benegligible so long as the off period is kept short.

The DUT is then driven on for pulse two, and now turnson under the load current established through the inductor.For a turn-on test, the rising edge of pulse two is the switchingtransient of interest. The length of pulse two can be minimisedto reduce power dissipation of the DUT and the peak inductorcurrent as only the leading edge is of interest. The drain-sourcevoltage, vds, and drain current, id , are the primary quantitiesof interest, though other waveforms such as the gate-sourcevoltage, vgs, may also be captured. Note that it is possible, andoften convenient, to measure the drain current on the sourceside of the DUT, as this point is ground-referenced.

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t

t

IL

Vbusvds(t)

id(t)

t

Vdrive

vgs(t)

Pulse one Pulse two

Switching transient

of interest (turn-on)

Fig. 2. Idealised double-pulse switching waveforms. The switching transientof interest is the second turn-on transient under load current IL.

III. SWITCHING PERFORMANCE METRICS

Key performance metrics that can be used to assess theeffect of drive parameters on switching performance includeswitching loss, dV/dt and di/dt metrics (maximum and aver-age), rise/fall times and switching losses. Maximum dV/dt isparticularly of interest with respect to the dV/dt ruggednessof opposing switching devices in a half-bridge configuration.Maximum di/dt is of interest from the perspective of EMIconsiderations as well as affecting peak reverse recovery andjunction capacitance charge/discharge currents. The switchingloss metric captures to some extent a range of switchingfeatures, but particularly gives a good sense of the totalswitching time and average rise/fall times.

IV. EXPERIMENTAL DATA COLLECTION

The experimental prototype with which double-pulse test-ing (400V, 10A nominal) was conducted is shown in figure 3.The drain-source voltage was measured using a 500MHz 10xpassive probe. The gate-source voltage and voltage across a100mΩ current sense resistor were measured using 500MHzhigh-voltage differential probes. Traces were recorded for theentire double-pulse waveform at a 2.5GHz sample rate witha 16x averaging acquisition mode. An example oscilloscopetrace recorded from the experiment is shown in figure 4;the upper window shows the entire double-pulse waveform,while the lower window shows the turn-on transient of interest,corresponding to the B-trigger point in the waveform. Furtherdetails of the experimental prototype are available in [4].

V. RECONSTRUCTION OF TRUE CURRENT FROM DI/DTPOLLUTED SHUNT RESISTOR MEASUREMENTS

The use of resistive shunts to measure current is commonpractice [6] and the method used to collect the experimentaldata in this work. For a pure resistance the measured terminalvoltage will be directly proportional to current. When used

SiC Schottky diode

InductorCascode/Clamp LV

MOSFET pair

HV MOSFET

Current sense

resistor

Bus capacitorsCommutation loop

36mm

Fig. 3. Experimental prototype used to conduct double-pulse tests showingkey components and the load current commutation loop.

R Ls

Cp

Fig. 5. Lumped circuit model of a non-ideal resistor.

to measure switching transients, however, the frequency re-sponse of the shunt resistor must be considered. High rates ofchange of current (di/dt) exist during the switching transition,often exceeding 200A/µs. The contribution of parasitic seriesinductances to the terminal voltage of the shunt resistor canbe of magnitudes exceeding the resistive contribution. Forswitching performance analysis the true current must firstlybe reconstructed from the measured voltage across the senseresistor.

The lumped circuit model of a non-ideal resistor is shownin figure 5 and consists of a series inductance and shuntcapacitance. The value of the parasitic elements depends ona wide range of factors including resistor construction andplacement in-circuit. The effect of resistor placement in circuitis determined largely by the geometry of the load and sensecurrent loops, which will be affected by resistor placement andorientation, the routing of traces and placement of planes.

Assuming that the parasitic shunt capacitance of the currentsense resistor is negligible, the transfer function that describethe relationship between the true current and the resistorterminal voltage is:

V (s)I(s)

= R+ sLs = R(

1+ sLs

R

)(1)

Here the sLs term is the frequency dependant gain error termwhich we want to eliminate. We can apply a filter of the form[7]:

G(s) =1

1+ s LsR

(2)

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Fig. 4. Example double-pulse switching waveforms recorded during the experimental exploration of the multi-dimensional parameter space. Shown are thedrain-source voltage (CH1, 100V/div), drain current (CH2, 25A/div) and gate-source voltage (CH3, 5V/div).

to compensate for the frequency dependant term in equation(1):

V ′(s)I(s)

=V (s)G(s)

I(s)= R

(1+ s

Ls

R

)· 1

1+ s LsR

= R (3)

The filter given by equation (2) is effectively a first-order lowpass filter with a time constant given by Ls/R. This filter maybe implemented in hardware by a simple RC network tunedsuch that CRc = Ls/R [7]. Alternatively the voltage across theterminals of the current sense resistor can be captured and therecorded waveform data post-processed to reconstruct the truecurrent, the approach taken in this work. If the post-processingoption is used the filter given by equation (2) may be modifiedto additionally compensate for the gain of the current senseresistor:

H(s) =1R

G(s) =1

R+ sLs(4)

The nominal value of the shunt resistor is known (tosome tolerance) and so the only unknown parameter for thereconstruction filter design is the value of the parasitic seriesinductance Ls. For a given experimental set-up, this valueshould be relatively constant across all tests, and largelydependant on the circuit geometry. Discussion of the processfor selection of this value is outside the scope of this paper,however, reasonable bounds can be calculated based on thegeometry of the current loops and post-experimental tuningperformed using the collected waveforms and the applicationof reasonable assumptions and knowledge about the shape ofthe switching transients.

VI. AUTOMATED FEATURE EXTRACTION TECHNIQUES

A. Offset removal

Where active probes, such as high-voltage differentialprobes, are used to record the waveform data, DC offsets

may be present in the recorded waveforms due to drift overtime and temperature. Fortunately, the double pulse waveformprovides opportunities to detect and remove any DC offsets.For both the drain current and gate-source voltage traces theexpected current and voltage respectively are zero before thefirst pulse. Any offsets can therefore be calculated by takingthe mean value of the waveform samples over an intervalwithin the clean leading edge of the captured waveform data.The averaging window can be selected to be a fixed length,as long as the window length never exceeds the length ofthe clean leading edge of the waveform, or the window timecan be adaptively controlled based on extracted timing data(see section VI-F). The calculated mean value can then besubtracted from the entire waveform to remove any offset.

Note that this process is not suitable for removing anyoffset in the drain-source voltage trace, drain-source voltagetransitions between the bus voltage and the on-voltage of theswitch under test, which is non-zero. As a passive voltageprobe was used to capture the gate-source voltage waveform,this was not an issue as no offset was present.

Similarly de-skew in time may be required between oscil-loscope channels where different types of probe are used dueto different propagation delays. In the experimental work out-lined in this paper probes were de-skewed using oscilloscopesettings, so channel-channel skew was not present in the data.If this feature were not available, an appropriate offset wouldneed to be added to the sample times of the relevant channelsto bring them into time-alignment.

B. Extraction of bus voltage, Vbus

Extraction of the bus voltage can be achieved via the sameprocess as described in section VI-A by taking the mean ofthe drain-source voltage trace over a window within the cleanleading edge of the waveform.

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C. Pulse timing extraction

Many of the extraction techniques described in the sub-sequent sections require information to locate the appropriatesection of the captured waveform. The drain-source voltagewaveform is the most appropriate source for determining thepulse timing due to the large signal levels (0-40V for a nominal400V bus using a 10x voltage probe) and high transition rates(typically in excess of 40V/ns) leading to clean switchingedges.

The proposed methodology selects an arbitrary drain-source voltage level, Vtrig, to define a voltage transition, andhence, edge of a pulse. Half of the extracted bus voltage,Vtrig = Vbus/2, is selected as a reasonable value to avoid anyfalse triggering due to ring at the leading or trailing edge ofthe transition.

The leading edge of the first pulse is detected by findingthe first fall in the bus voltage below Vtrig. A hold-off period of100ns is then implemented by advancing the waveform pointerby 250 samples to avoid re-triggering. The trailing edge ofthe first pulse is then detected by finding the next rise indrain-source voltage above Vtrig. A hold-off interval is againimplemented to avoid re-triggering. This process is repeatedto find the leading and trailing edges of the second pulse.Detecting these four time instants fully maps the double-pulsetiming from the waveform data.

D. Extraction of the test (load) current, IL

The test load current is determined by the length of thefirst pulse, during which current ramps up though the inductor.We assume that during the off period between pulse one andtwo that any decay in the inductor current is negligible; areasonable assumption given that the forward voltage of theclamping diode is small, compared with the bus voltage, andthe delay between pulses is short.

If only the drain current of the switching device under testis instrumented, we only have information about the inductorcurrent while the device is on. We also can not rely on themeasured drain current being representative of the inductorcurrent during the switching transient.

Given these issues, we select the interval defined by thefirst pulse as the portion of the waveform from which to extractthe test current; the inductor current at the end of this intervalshould be approximately equal to the load current. We note,however, that the inductor current begins to commutate fromthe device under test to the clamping diode before the end ofthe pulse, that is, before the drain-source voltage transitions.We therefore cannot interpolate the test current value from thedrain-current trace.

Instead we propose fitting a line to the current ramp for theload inductor and extrapolating to the end of the pulse definedby the time instant at which the drain-source voltage falls asdescribed in section VI-C. For an ideal inductor a linear fitshould be suitable, however, where the series resistance is notnegligible and/or saturation effects are present, a higher-orderpolynomial fit may be more appropriate.

For the experimental data collected in this work a 4th orderpolynomial was selected. A line is fitted to the drain current

data samples over the interval defined by the first pulse. Thefitted polynomial equation is evaluated at the time instantcorresponding to the falling edge of the first pulse to extractthe test current value.

E. Extraction of maximum dV/dt and di/dt

Sampled waveforms captured from an oscilloscope are nottypically suitable for directly calculating approximate deriva-tives due to the presence of high-frequency random noise,or depending on the oscilloscope, the discretisation of thesamples over the vertical scale. A more appropriate method forextraction of the time-derivative of the captured waveforms isthrough the application of a smoothing filter.

The use of a Savitzky-Golay filter is recommended forthis task [8]. The Savitzky-Golay filter is a digital filter thatuses a process of convolution to fit a low-order polynomial tosuccessive adjacent windows of the waveform by least squares.Through a suitable selection of the filter window length andorder good smoothing can be achieved while maintaining thecharacteristic shape of the waveforms.

Importantly, as a polynomial is fitted locally to each datapoint the local first derivative (and higher order derivativesif desired) can be trivially calculated. A good choice of filterorder and window length can usually be achieved by inspectionby plotting the smoothed waveform on top of the raw data. Forthe experimental data used in this work a 9th order filter withwindow length of 71 points (corresponding to a window lengthof 28.4ns) is selected to smooth and perform differentiation ofthe voltage traces.

In the case of the drain current, smoothing will not benecessary if the current reconstruction method presented insection V has been used, as the low-pass filter process will dealwith the issues highlighted above. There is, however, likely tobe high-frequency ringing present in the observed current. Interms of the switching performance metrics this componentof the current may not be of interest as it does not describethe shape of the current rise, but rather, is due to ringing ofparasitic elements in the circuit.

A low-order Savitzky-Golay filter is proposed to rejectthe high-frequency ringing present in the current waveformbut maintain the characteristic shape of the current transient.Additionally the application of the Savitzky-Golay filter allowsthe di/dt to be calculated at each sample point.

Finally, maximum dV/dt and di/dt can be extracted bytaking the maximum of the smoothed drain-source voltage anddrain current first derivatives respectively over the region ofinterest. For a double pulse test the region of interest is centredaround the leading edge of the second pulse as extracted insection VI-C. Note that the dV/dt will be negative for a turnon transient (fall in voltage) in which case the minimum valueshould be taken.

F. Extraction of rise, fall and switching times

The 10-90% rise and fall times from drain current anddrain-source voltage respectively can be calculated based onthe extracted values for Vbus and IL. Firstly the 10% and 90%thresholds for current and voltage are calculated. The intervalof interest from the waveforms is then isolated, specifically

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the rising edge of the second pulse. The selected waveforminterval is then searched for the first current sample abovethe 10% and 90% thresholds and the first voltage samplesbelow the 90% and 10% thresholds. The rise/fall times aresubsequently calculated from the time difference between theidentified samples. Total switching time can be calculated asthe time interval between the 10% rise in drain current to the10% fall in drain-source voltage.

This method limits the timing resolution to that of thesample time; if more resolution is desired interpolation of thewaveforms would be required. Another alternative is to use thesmoothed waveform data rather than the raw sampled data. Thesmoothed data would not only better facilitate interpolation ifbetter resolution is required, but may also avoid false triggeringdue to any high-frequency content in the data. Note also thatthe rise time metric does not capture information regardingany overshoot of the drain current above the load current.

G. Extraction of other switching performance metrics

Any number of other waveform features can be extractedby using and combining the techniques presented in sectionsVI-A through VI-F. Three additional switching metrics ofinterest are peak drain current, gate-drive voltage and switchingloss. Peak drain current can be extracted by simply taking themaximum drain current over the interval of interest (centred atthe rising edge of the second pulse). The gate drive voltage canbe determined by taking the mean of the gate-source voltagewaveform during the first pulse (shortened slightly to excludethe charge/discharge transients). Switching loss is determinedby calculating the instantaneous power by taking the productof the drain current and drain-source voltage waveforms andintegrating over the interval of interest.

Care should be taken to ensure the suitable versions of thewaveform data are used, that is, the raw or filtered/smoothedversions. For example, it would be suitable to use the un-smoothed version of the gate-source waveform to extract thegate drive voltage, but may be preferential to use the smoothedversion of the drain current to extract the effective peak currentwhile rejecting the high-frequency ring.

In the techniques presented above there is also a lot ofinformation discarded. Significantly more information can beextracted from the waveform data with appropriate additionalpost-processing. Particularly, there are another three switchingedges which have not been analysed: a zero-current turn-onedge and two turn-off edges, one at the load current and oneat a slightly higher current. Only minor modification to theprocessing described above would be required to extract thisadditional information.

VII. VISUALISATION AND VALIDATION OF EXTRACTEDFEATURES

Where large quantities of waveforms are to processedautomatically it is critical that mechanisms be put in placeto validate quickly that feature extraction has been successful.This is most easily achieved visually, which requires a visualsummary of the various steps of the feature extraction processas well as the final results. Plots showing the original/post-processed waveforms annotated with visual representations of

0 50 100 150 200 250 300 350 400−60

−40

−20

0

20

40

60

Time (ns)

HV

MO

SFET

dra

in c

urre

nt, I

d (A)

Current reconstruction

10 11 12 13 14 15 16 17 18 19−5

0

5

10

15

Id = 10.2 A

Load current extraction

Time (µs)

HV

MO

SFET

dra

in c

urre

nt, I

d (A)

0 50 100 150 200 250 300 350 400−5

0

5

10

15

20

25Ipeak = 24.0 A

Time (ns)

HV

MO

SFET

dra

in c

urre

nt, I

d (A)

Current smoothing for di/dt extraction

Current sense resistor voltage (scaled) Reconstructed current

Reconstructed current Fitted line

Reconstructed current Smoothed current

Fig. 6. Extract of a feature extraction report showing post-processing stepsand feature extraction for the drain current waveform.

the extracted features, as well as the points from which featureshave been extracted, provide a good solution.

Figures 6 and 7 show example reports generated for experi-mental waveform data following the automated feature extrac-tion process. These figures summarise the feature extractionprocess and allow errors in the automated feature extraction tobe easily identified.

VIII. APPLICATION OF FEATURE EXTRACTION TOEXPERIMENTAL DATA

A MATLAB script was developed to implement the featureextraction techniques described in section VI. An experimentalexploration of the gate drive parameter space for a cascode gatedrive of power MOSFETs was performed using the experimen-tal set-up described in section IV. Gate resistance, gate-sourcecapacitance and load current were controlled resulting in 385double-pulse data sets being recorded across the (Rg,Cgs, IL)parameter space. The input to the MATLAB script was thecollection of recorded waveforms and an Excel spreadsheetlinking test conditions to the waveform filenames (whichwere sequentially numbered according to the test sequences).The Excel spreadsheet also allowed for a subset of the totaldataset (5× 7× 10 = 350 waveforms) to be processed (somerecorded waveforms were used for timing calibration of theexperimental fixture only).

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−6

0

6

12

18

24

30

10%

90%

Dra

in c

urre

nt, I

d (A)

0 50 100 150 200 250 300 350 400−100

0

100

200

300

400

500

10%

90%

Time (ns) HV

MO

SFET

dra

in−s

ourc

e vo

ltage

, Vds

(V)

Turn−on timing extraction

0 50 100 150 200 250 300 350 400−600

−400

−200

0

200

400

600

800 di/dtmax = 737.9 A/us

Time (ns)

Inst

anta

neou

s di

/dt (

A/µs)

di/dt extraction

0 50 100 150 200 250 300 350 400−50

−40

−30

−20

−10

0

10

dV/dtmax = −42.6 V/ns

Time (ns)

Inst

anta

neou

s dV

/dt (

V/ns

)

dV/dt extraction

Fig. 7. Extract of a feature extraction report showing timing and d/dt featureextraction.

Each set of experimental waveform data was processedby the MATLAB script. Two outputs were automaticallygenerated for each individual test: a feature extraction reportin PDF format and the post-processed waveform and featurevariables as a MATLAB structure. One output was generatedfrom the entire dataset: a MATLAB structure containing alltest conditions and extracted switching performance metrics.Extracts of an example feature extraction report are presentedin figures 6 and 7 while a sample visualisation of the resultdataset is shown in figure 8.

IX. CONCLUSION

An automated approach to the extraction of switching per-formance metrics from experimental double-pulse waveformdata has been successfully demonstrated. The feature extrac-tion techniques presented allow large experimental datasetsto be easily and quickly post-processed and reduced to amanageable result space of targeted performance metrics.The automated feature extraction process has been validatedthrough application to an experimental dataset collected forthe purpose of exploring the switching performance of apower MOSFET under cascode gate drive, allowing switchingperformance result surfaces to be plotted across the (Rg,Cgs)parameter space.

100150

200250

10-1010-910-810-750

100

150

200

250

300

350

400

Gate resistance, R gle(Ω)

Gate-source capacitance, Cgshe (F)

Turn

-on

switc

hing

loss

es, E

loss

(µJ)

2 A

10 A

Load

cur

rent

, IL

Fig. 8. Visualisation of turn-on switching losses over the (Rg,Cgs, IL) pa-rameter space using data extracted from experimental double-pulse waveformsvia automated feature extraction. Result surfaces are plotted for constant loadcurrents increasing from 2A (bottom) to 10A (top).

ACKNOWLEDGEMENTS

This work was supported in part by Surtek Pty Ltd.

Computational (and/or data visualisation) resources andservices used in this work were provided by the HPC and Re-search Support Group, Queensland University of Technology,Brisbane, Australia.

REFERENCES

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[2] J. Hernandez, L. Petersen, M. Andersen, and N. Petersen, “Ultrafastswitching superjunction mosfets for single phase pfc applications,” inApplied Power Electronics Conference and Exposition (APEC), 2014Twenty-Ninth Annual IEEE, March 2014, pp. 143–149.

[3] M. A. H. Broadmeadow, G. F. Ledwich, and G. R. Walker, “An improvedgate driver for power MOSFETs using a cascode configuration,” in PowerElectronics, Machines and Drives (PEMD 2014), 7th IET InternationalConference on, April 2014, pp. 1–6.

[4] M. A. H. Broadmeadow, G. R. Walker, and G. F. Ledwich, “Comparisonof the gate drive parameter space for driving power MOSFETs using con-ventional and cascode configurations,” in Energy Conversion Congressand Exposition (ECCE), 2014 IEEE, Sept 2014 (in press).

[5] Infineon. (2012) IPL60R199CP data sheet. [Online].Available: http://www.infineon.com/dgdl/IPL60R199CP 22.pdf?folderId=db3a3043163797a6011637d4bae7003b&fileId=db3a3043284aacd801284dca135b29ba

[6] S. Ziegler, R. Woodward, H.-C. Iu, and L. Borle, “Current sensingtechniques: A review,” Sensors Journal, IEEE, vol. 9, no. 4, pp. 354–376,April 2009.

[7] E. Dallago, M. Passoni, and G. Sassone, “Lossless current sensing in low-voltage high-current DC/DC modular supplies,” Industrial Electronics,IEEE Transactions on, vol. 47, no. 6, pp. 1249–1252, Dec 2000.

[8] S. Krishnan and C. Seelamantula, “On the selection of optimum Savitzky-Golay filters,” Signal Processing, IEEE Transactions on, vol. 61, no. 2,pp. 380–391, Jan 2013.

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