Mark Scott EPIC

Prognostic Health Management Techniques for Power Electronics

Presented By: Mark Scott

Date: 10/15/2018

Where are Power Electronics Found?

Consumer Electronics

Tesla Model S

Aircraft and High Speed Rail

http://www.caranddriver.com/tesla/model-s

http://www.bombardier.com/en/about-us/history.html

Google Server Room

ABB SVC: Norway

SpaceX Dragon V2

https://planetsurprises.wordpress.com/201 2/10/18/google-server-room/

http://www.abb.com/cawp/seitp202/c36f4e6 2da52ab46c1257670003690d3.aspx

http://www.electronicsweekly.com/u ncategorised/space-spacex-dragonv2-ready-crew-2014-05/

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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More Applications

250 MW PV Plant (Portugal)

Fowler Ridge Wind Farm Steve Grundy: https://flic.kr/p/aDy58Y

http://www.sfgate.com/business/article/PG-E-plansbig-investment-in-solar-power-3199510.php

Portable Oxygen Concentrator ITER Tokamak

https://www.spinlife.com/

https://www.iter.org/sci/makingitwork

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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Introduction I.

Motivation for Prognostic Health Management Systems in Power Electronics

II. Failure Mechanisms in Power Electronics  Capacitors  Semiconductor Switching Devices III. Approaches to PHM in Power Electronics IV. Electromagnetic Spectral based PHM Approach (E-PHM)  

Theory Results

V. Conclusion

Mark Scott, Ph.D.

scottmj3@miamioh.edu

4

What is PHM? Prognostic Health Management (PHM) Systems: • •

Monitor the health of individual components in a system to ensure they remain in the safe operating area.

Estimates the remaining useful life of a component or system.

Goal: • •

Minimize unexpected failures from occurring.

Extract the maximum amount of useful life from a system.

Mark Scott, Ph.D.

scottmj3@miamioh.edu

5

What is PHM? Prognostic Health Management (PHM) Systems Goals: • •

Minimize unexpected failures from occurring.

Extract the maximum amount of useful life from a system.

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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PHM: Motivation

1.

2.

3.

4.

•

Maintenance accounts for 10 % to 20 % of the total operating costs for an aircraft in the commercial airline industry ($3.6 M per aircraft per year) [1].

•

In aviation, up to 40 % of equipment is falsely diagnosed and removed as the result of ambiguous and labor intensive test procedures [1], [2].

•

It is recommended to change the DC Link capacitors in uninterruptable power supplies (UPS) after 50,000 hours even though their lifetimes is estimated at 150,000 [3].

•

Semiconductor switching devices and the capacitors are the most likely elements to fail in power electronics [4].

•

These failures primarily occur due to extreme stress and aging. Their damage indicators are often the same [4].

International Air Transport Association, Airline Maintenance Cost Executive Commentary. Montreal CA: Maintenance Cost Task Force, 2015 U. PeriyarSelvam et al., “Analysis on Costs for Aircraft Maintenance,” Advances Aerospace Science Appl. vol. 3, no. 3, pp. 177-182, 2013.

“Capacitors age and capacitors have an end of life - white paper,” in Emerson Network Power, 2015.

Y. Avenas et al., “Condition Monitoring: A Decade of Proposed Techniques,” IEEE Ind. Electron. Mag., vol. 9, No. 4, pp. 22-36, Dec. 2015.

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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Capacitors Parameters and Aging Capacitor Types: • Aluminum Electrolytic • Metalized Poly Propylene Film • Multilayer Ceramic Capacitors Parameters: • Capacitance (CDC) • Equivalent series resistance (RESR) • Equivalent series inductances (LESL)

Equivalent circuit of a non-ideal capacitor.

Capacitance and equivalent series resistance variation with degradation [1].

1.

H. Solimann et al., “A Review of Condition Monitoring of Capacitors in Power Electronics, ” in IEEE Trans. Ind. Appl., vol. 52, no. 6, pp. 4976-4987, Nov./Dec. 2016.

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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Capacitors Failure Modes Capacitor Type Aluminum Electrolytic

Failure Mechanism Electrolyte Vaporization, Electrochemical Reaction

Metalized Poly Propylene Film Multilayer Ceramic

Critical Stressor Temp, Voltage, Current

Failure Mode Open Circuit

Moisture corrosion, Temp, Voltage, Humidity dielectric loss

Open Circuit

Insulation degradation, Temp, Voltage, Vibration flex cracking

Short Circuit

Condition Monitoring: Implementation: 1. Offline 2. Online

Lifetime Indicators: 1. Capacitance (CDC) 2. RESR 3. Ripple Voltage (ΔVDC) 4. Volume 5. Temperature Mark Scott, Ph.D.

Methods: 1. Current sensors 2. Injecting signals 3. Adv. data algorithms

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PHM: Failure Mechanisms in Power Electronics Power devices: Main wear-out mechanisms for semiconductor devices [1]: • Wire bond lift-off.

• Baseplate solder joint cracking.

• Chip solder joint cracking.

Block diagram of a power module [1].

Failure Mode Wire Bond Lift-Off Solder Joint Degradation Gate Oxide Degradation Junction Temperature

Damage Indicator       

Increased forward voltage (VCE or VDS) Reduced parasitic ringing Increase in thermal resistance (RTH) Increased forward voltage (VCE or VDS) Changes in threshold voltage (VTH) Changes in on-resistance (RDS_ON) and forward voltage (VCE) Changes in switching speed (dV/dt)

[1] H. Wang et al., “Transitioning to Physics-of-Failure as a Reliability Driver in Power Electronics,” IEEE J. Emerging & Selected Topics in Power Electron., vol. 2, no. 1, pp. 97-114 , Mar. 2014.

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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E-PHM: Overview Approach: The EM spectrum is analyzed to preform PHM of the systems.

Implementation: An embedded system measures spectral content of current transducers (CT) and provides PHM feedback about power electronics.

Adv.:

(1) Enables In-situ measurements.

(2) Integrates into existing control hardware.

(3) Minimal additional components required (Primarily software based).

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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E-PHM: Basic Theory Overview: Spectral content of power electronics hardware provides a unique signature of the operating conditions and system hardware.

•

Operating Conditions: dV/dt of switching devices changes with temperature and load current. → Impacts EMI.

•

System Hardware: As passive and active components age, their associated parasitics change. → Impacts EMI.

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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E-PHM: Theoretical Analysis Theory: Using the equivalent differential mode (DM) circuit, the magnitude of the DM voltage and capacitor’s resonant frequency are impacted by aging.

DM Voltage vs. Frequency

Equivalent DM Circuit Theoretical Results • Voltage at the resonant frequency is 10 dB higher for aged capacitors.

• Resonant frequency also shifts higher from 120.3 kHz to 126.8 kHz as the components age.

Mark Scott, Ph.D.

Capacitor Parameters New

Aged

CDC

50 µF

40 µF

RESR

6 mΩ

12 mΩ

LESL

35 nH

35 nH

scottmj3@miamioh.edu

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E-PHM: Experimental Validation Approach: • Preliminary testing is performed on an EMI test bench.

• Modular three phase inverter that enables DC Link capacitors to be exchanged.

• The spectrum is measured for multiple classes of DC link capacitors.

• EMI spectrum is processed offline using a support vector machine.

Modular Three Phase Inverter.

EMI Test Setup at Miami University Mark Scott, Ph.D.

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E-PHM: Experimental Validation Cont’d Execution: • Capacitor interface board enables C DC and RESR to be altered.

• Five classes of DC link capacitors are evaluated: – N6A0, N5A1, N3A3, N1A5, N0A6.

•

50 measurements were taken for each class: – 25 were used to train the SVM. – 25 were used to evaluate the SVM.

Individual Capacitor Parameters

RESR

CDC

New

6.0 μΩ

50 μF

Aged

23.6 μΩ

45 μF

Modular Three Phase Inverter

Capacitor Interface Board Mark Scott, Ph.D.

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E-PHM Experimental Results Total Noise Measurements in 10 kHz to 200 kHz Range: • Difficult to notice differences between the spectrums.

Test Conditions New VDC

540 V

POUT

5 kW

fS

20 kHz

fc

60 Hz

Mark Scott, Ph.D.

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E-PHM Experimental Results Total Noise Measurements in 10 kHz to 200 kHz Range: • A close examination at one of the switching frequency’s harmonics shows its magnitude increases with capacitor age.

Test Conditions New VDC

540 V

POUT

5 kW

fS

20 kHz

fc

60 Hz

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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E-PHM Experimental Results Machine Learning Algorithm Results: • 250 Tests conducted with 5 capacitor classes in the DC Link: – 6 New (N6A0), 5 New &1 Aged (N5A1), 3 New & 3 Aged (N3A3), 1 New and 5 Aged (N1A5), 6 Aged (N0A6).

•

SVM succeeds at identifying the brand new and aged DC link capacitance.

Test Conditions

Test Results – 10 kHz to 200 kHz Total Noise

SVM Decision

VDC

540 V

POUT

5 kW

fS

20 kHz

fc

60 Hz

Actual

New

N6A0 N5A1 N3A3 N1A5 N0A6

N6A0 25 0 0 0 0

N5A1 0 19 0 0 0

Mark Scott, Ph.D.

N3A3 0 5 20 5 0

N1A5 0 1 5 20 0

N0A6 0 0 0 0 25

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Target Distributions Population Construction: • Sample size of 50 trials.

• Mean and standard deviation from the mean were recorded.

• Samples were modeled as a normally distributed population.

• Populations overlap without a clear boundary.

Target Distributions at 6th Harmonic New N5A1 N3A3 N1A5 Aged

→ Shows that application is suited for machine learning.

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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E-PHM: Experimental Results Additional Results: 1. Significant differences in DM noise, but CM noise is more or less the same.

2. Magnitude of noise is higher for aged (‘old’) capacitors.

3. Machine learning performs well at low frequencies; struggles at higher ones.  Validates theoretical analysis.

Experimental Results Common Mode Noise Mark Scott, Ph.D.

Experimental Results Differential Mode Noise scottmj3@miamioh.edu

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Future Work Power Devices: •

Changes in spectrum with: – Device age.

– Temperature.

Equivalent CM Circuit dV/dt for Turn On vs. Current

• •

14

•

Improving noise immunity.

Replace LISN with current sensors.

Implement SVM on an embedded system.

Switching Speed (ns)

Measurements:

16

12 10

8 6 4

Rohm (25 C) USCi (100 C) IXYS (25 C)

2

Rohm (100 C) Wolfspeed (25 C) IXYS (100 C)

USCi (25 C) WolfSpeed (100)

0

0

5

10

15

20

25

Drain Current (A) Mark Scott, Ph.D.

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Conclusions  Concept of Prognostic Health Management (PHM) Systems were introduced.  Capacitor failure mechanisms were reviewed. Wear out conditions indicated by decrease in CDC and increase in RESR.  Conditional monitor approaches for power devices were presented.  Electromagnetic Spectrum based PHM (E-PHM) method was discussed.  The approach successfully identifies changes in the health of the capacitors.  Future work for E-PWM includes developing models for power devices.

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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Thank You for your Attention.

Any Questions?

Mark Scott, Ph.D.

scottmj3@miamioh.edu

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