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AN ELECTROMAGNETIC APPROACH TO FAULT DIAGNOSTICS AND SURVIVABILITY IN ELECTRIC MACHINESAND SURVIVABILITY IN ELECTRIC MACHINES

Mahesh Krishnamurthy

Hosted by IEEE, Rock River Valley Section

Director, Electric Drives & Energy Conversion LabDirector, Grainger Power Electronics and Motor Drives Lab

Illinois Institute of Technology, ChicagoURL: http://drives.ece.iit.edu

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Unauthorized use prohibited without explicit consent from author

• Electromagnetic nature of energy conversion in electric machines

Outline

electric machines

• Introduction to failures in PM machines

• Concept of Universal Sensor

• Conclusions

• Quick Overview of IIT’s Energy Research Initiatives

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2

Electric Machines in Everyday Life

Applications of electric machines

Electric Motors have been used in power ranges from milliwatts (mW) to megawatts (MW)

Chevy Spark Electric VehicleHVAC system

Motors

(MW)

Middelgrunden Wind Farm off Copenhagen Leroy-some generator for power station

elevator

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Focus Machine: Permanent Magnet Synchronous Machine

Benefits of PMSM:

• Permanent magnets have been used in electric machines since 1821, hen Michael Farada in ented the first motor in the orld B t thewhen Michael Faraday invented the first motor in the world. But they

did not earn widespread acceptance due to the poor quality of magnetic materials

• Over the last few decades, permanent magnet machines have gaining market share as a result of advances in power electronics as well as permanent magnet quality (in spite of current PM constraints

Since no electrical energy is used or losses incurred for developing or maintaining the motor’s magnetic fieldmaintaining the motor s magnetic field

High output power to volume ratio (Power Density)

High efficiency

No slip rings or brushes4

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Research Objective

The aim of this research is to improve the reliability of permanent magnet synchronous machines and their driverspermanent magnet synchronous machines and their drivers

Two main studies using this approach:

A novel multi-faults detection method using search coils has been proposed and implemented for a permanent magnet synchronous machine.

- to improve the reliability of electric machine itself

A universal sensor including an adaptive position estimator and a currentA universal sensor including an adaptive position estimator and a current estimator based on the search coil model is designed and implemented a permanent magnet synchronous machine

- to improve the reliability of electric machine’s driver

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Rotor Position

“Black Box” Approach

Speed

TorqueVoltage (Vn)

Current (In)

Is it satisfactory?

No

Electromagnetic FieldsEnergy Conversion

Voltage (Vn+1)

Current (In+1)6

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Analyzing Electromagnetic Behavior of an Electric Machine

Electromagnetic Behavior

Field Optimization

Machine Design

Advanced Control

Strategies

Fault tolerant

operationMitigation of

noise and vibration

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Electromagnetic ApproachElectromagnetic Approach

Optimizing Local flux distribution in the machine

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5

Construction of PMSM

Courtesy of GM (2012)

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Common faults and fault diagnosis techniques for PMSM

Static eccentricity It could be caused by:

I. Eccentricity

- Static eccentricity

- Dynamic eccentricity

It could be caused by:1) Metal fatigue2) Unbalanced stress3) Improper installation4) Corrosion/Contamination

sgdd

The air-gap of a healthy machine, a static eccentricity machine and dynamic eccentricity machine

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6

- Uniform demagnetization

Common faults and fault diagnosis techniques for PMSMII. Demagnetization

0.25

Tes

la)

Conditions that could cause permanent magnets in a PMSM to demagnetize include:

1) High operation temperature/Cooling system malfunction2) Ageing of magnets3) Corrosion of magnets4) Inappropriate armature current

- Partial demagnetization

0 50 100 150 200 250 300 3500

0.05

0.1

0.15

0.2

Position (degree)

Mag

netic

flu

x de

nsity

(T

Magnetic flux density around the air-gap11

3.2 Demagnetization

3. Common faults and fault diagnosis techniques for PMSM

Maximum operating temperature of different magnet materials

Effect of increasing temperature on the operating point 12

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Inter turn shorted in one phase

Common faults and fault diagnosis techniques for PMSMIII. Stator winding short-circuit

- Inter-turn shorted in one phase

- Inter-turn shorted between phases

- Phase-ground shorted

- Phase-stator shortedShort circuit in one phase

Short circuit between phases

The reasons which cause insulation failure could be

1) M f t i d f t

Short circuit between winding and stator at the end of stator slot

Short circuit between winding and stator at the middle of stator slot

Courtesy of Electromotors WEG SA, Brazil

1) Manufacturing defect2) High operation temperature/Cooling

system malfunction3) Machine overloading4) Transient high voltage5) Friction caused due to vibration

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3. Common faults and fault diagnosis techniques for PMSM3.4 Traditional Fault Diagnosis Schemes

• Spectrum analysis - Armature current spectrum analysis- Vibration spectrum analysis- Axial flux spectrum analysis

• Parameter estimation based on current and voltage monitoring

- Negative/zero sequence currentNegative/zero sequence impedance

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- Negative/zero sequence impedance- Negative/zero sequence voltage

• Temperature monitoring

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Types of

Types of Failures

HardwareD b k

Winding short Partial

Common faults and fault diagnosis techniques for PMSM

Types of methods

Hardware Requirement

DrawbacksBearing Eccentricity

Winding short circuit/open

circuit

Partial Demagnetizati

on

Current frequency Analysis

√ √ √ √Current sensor, Raster encoder

Not good for various speed operated

machines. Eccentricity and

demagnetization have same frequency

signature.

Vibration/Noise frequency

Analysis√ √

Accelerometer/Sound recorder, Raster

encoder

Parameter estimation based on

√ √Current sensor,

Fault-free machine accurate parameters

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current and voltage

monitoring

√ √Raster encoder

accurate parameters are required.

Temperature Monitoring

√ ThermographTemperature is

affected by many factors.

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Implementation of search coils

What is an ideal solution?

Not influenced by power electronic device harmonics;

Different kinds of faults and their severity can be easily distinguished.

No electric machine parameters required

Low cost

1616

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Implementation of search coils

Flux distribution created by magnets only Flux distribution created by armature current only

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Flux distribution of a full motor

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Implementation of search coils

18Search coils on stator teeth to monitor magnetic flux 18

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FEA model

4.4 Co-simulation

4. Implementation of search coils

Σ PI

Σ PIPIΣ

ud

uq

0

iq*

ω*

dq to abc

SVPWM

PWM

ω

IGBTs

DCLink

Search coil voltage

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id

abc to ad

iqia

ib

Simulink model

voltage

Co-simulation topology with vector control

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4.4 Co-simulation

4. Implementation of search coils

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Co-simulation of vector control in Simulink

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On line data

Operating Principle

On-line data acquisition

Data Processing

Filtering

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displaying

Decoupling

21

armature component

Decoupling of Electromagnetic Fields

fi

Decoupling

22field component 22

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Fault Diagnostics

Static Eccentricity

PMSM with 0.005 (20%) inch and 0.01 (40%) inch static eccentricity.

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Field component

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Fault Diagnostics

Dynamic Eccentricity

PSMS with a 30% dynamic eccentricity

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Field component

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Fault Diagnostics

Inter-turn Short Circuit

PMSM with one, two, and three turns of the armature coils around a tooth, which is at 0 degree position, are inter-turn shorted.

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Armature component

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Fault Diagnostics

One phase-ground Short Circuit

PMSM with one of the three phases is grounded

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Armature component

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Partial Demagnetization

Fault Diagnostics

Partial Demagnetization

PMSM with one out of the four pole pairs is 20% and 50% demagnetized respectively.

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Field component

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E t i it

Experimental Results

Eccentricity

The air gap of the machine is 25 mils (0.635mm), while the displacement of shaft is about 7mils (the thickness of electrical tape, 0.1778mm), so it is about 28% eccentricity.

In process of grinding end plate to create static eccentricity

28Illustration of eccentricity

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Eccentricity

Experimental Results

Search coils voltage from 4 stator poles of phase A, in the condition of static eccentricity while 0.4 A q-axis current applied

It shows that at stator tooth A4 has highest field component

Search coils voltage from 4 stator poles of phase A

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has highest field component, while A2 has lowest filed component and A1, A3 are in between of them. This indicates an eccentricity to the direction of A4, which has the smallest air gap.

Field component of search coils in the eccentricity machine

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0 5

1

1.5

Inter-turn short circuit

Experimental Results

The amplitude of the pulses of A3 (red curve) is smaller than others, indicating a short circuit in the A3 windings.

The armature component of coil A3 is smaller than other ones due to 4 less turns

0.5 0.51 0.52 0.53 0.54 0.55 0.56 0.57 0.58 0.59 0.6-1.5

-1

-0.5

0

0.5

Time (s)

A1A2A3A4

Search coils voltage from 4 stator poles of phase A

30Armature component in an inter-turn shorted machine

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Demagnetization

Experimental Results

Part of one rotor pole, which is made with bonded NdFeB, was physically removed.

Rotor with single pole damaged to imitate partial demagnetization

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One out the eight rotor poles has approximate 15% less magnetic field

Back EMF of single pole damaged rotor 31

Advantages of proposed scheme:

Advantages and Disadvantages

g p p√Not influenced by power electronic device harmonics (Because

fundamental frequency signal is used for processing); √ Can determine static eccentricity direction and its severity;√ Can determine short-turns location and its severity;√ Can determine severity of demagnetization of each magnet pole;√ Can determine which phase is ground shorted;√ Can work as a backup position sensor;

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Challenges in the implementation of proposed scheme:×Invasive (So needed to be mounted during manufacturing)

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Novel Universal Sensor

Position estimation

Traditional position sensorless techniques types

- High frequency voltage injection (for machines with saliency, ex. IPM, SRM)

- Back EMF based

- To observe flux vector with machine model, phase voltage and current

Traditional Current sensorless techniques types

Current estimation

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Traditional Current sensorless techniques types

- Based on DC link current and switching state

- Sinusoidal current reconstruction with uniformed samples used for correction

- To observe current vector with machine model, phase voltage and flux vector

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Feature of proposed position estimator

Novel universal sensorPosition estimation

Feature of proposed position estimator

Phase resistance may deviate a lot from its nominal value

1

0

s q dq q

e

d dq s d

dR L L

u idt Kdu i

L R Ldt

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- skin effects

- temperature change

_ __

__

_ _

1

0

q s d sq s q

e sd s d

q s d s

dM Mu idt K

u d iM M

dt

34

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Novel universal sensor

Position estimation

_ed su

_eq su

sMedi

eqi

sM

_a su

ai bi ci

_b su _c su

35

1

z

2

Configuration of rotor position estimator

1n n

35

Novel universal sensorCurrent estimation

u

1

s

1

s F G

G

i

e sM J

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Configuration of current estimator

i

ieJ

36

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Actual and estimated position at steady state

Use as Universal Sensor

150

200

250

300

350

400

Pos

ition

(de

gree

)

actual

estimated

Actual and estimated position at steady state

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0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.040

50

100

Time (s)

Simulational results Experimental results

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A t l d ti t d iti t t ti ti

Use as Universal Sensor

Actual and estimated position at starting time

150

200

250

300

350

400

Pos

ition

(de

gree

)

actual

estimated

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0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.040

50

100

Time (s)

Simulational results Experimental results

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20

A t l d ti t d d i t

Use as Universal Sensor

Actual and estimated d-q axis current

-1

0

1

2

3

4

5

20

30

40

50

60

Cur

ren

t (A

)

Actual d axis current

Estimated d axis current

Actual q axis current

Estimated q axis current

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Simulational results Experimental results

1 2 3 4 5 6 7 8 9 10 11-5

-4

-3

-2

Time (s)

Actual d axis current

Estimated d axis current

Actual q axis current

Estimated q axis current

0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04

-10

0

10

Time (s)

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• Signatures of different faults are easy to distinguish.

Conclusions

• Direction and severity of eccentricity can be determined if electromagnetics of the machine is well understood.

• Location and severity of winding short-turns can be found.

• Severity of demagnetization can be determined.

• No machine parameters required.

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•Search coils can also work as a backup universal sensor

• In contrast to existing sensorless techniques, the problem of resistance variation is avoided.

• Owing to its ability to achieve position and current estimation, it improves the reliability of drive system

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• Y. Da, X. Shi, M. Krishnamurthy*, “A Novel Universal Sensor Concept for Survivable PMSMDrives,” IEEE Transactions on Power Electronics, Volume: 28, Issue: 8, Publication Year:

References

2013, pp. 5630 - 5638

• Y. Da, X. Shi, M. Krishnamurthy*, “A New Approach to Fault Diagnostics for PermanentMagnet Synchronous Machines Using Electromagnetic Signature Analysis,” IEEETransactions on Power Electronics, Volume: 28, Issue: 8, Publication Year: 2013, pp. 4104 -4112

• Y. Da, M. Krishnamurthy, “ Position and Current Estimation for Permanent MagnetSynchronous Machines Using Search Coils,” Vehicle Power and Propulsion Conference,2011. VPPC ’11. Proceedings of the 7th Annual Conference of the IEEE, pp. 1-5, 2011.

• Y. Da, X. Shi, M. Krishnamurthy, “Health monitoring, fault diagnosis and failure prognosistechniques for Brushless Permanent Magnet Machines ” 20th Vehicle Power and PropulsionConference, 2011. VPPC ’11. Proceedings of the 7th Annual Conference of the IEEE, pp.1-7, 2011.

• Y. Da, M. Krishnamurthy, “Novel Fault Diagnostic Technique for Permanent MagnetSynchronous Machines Using Electromagnetic Signature Analysis,” Vehicle Power andPropulsion Conference, 2010. VPPC ’10. Proceedings of the 6th Annual Conference of theIEEE, pp. 1-6, 2010. 41

• Hybrid, Plug‐in Hybrid and Electric Vehicles

Quick Overview of IIT’s Energy Research Initiatives

• Vehicle‐to‐Grid Systems

• Renewable Energy Systems

• Smart Grids and Micro Grids

• Core Advantage:

• IIT Owns the entire campus grid, which allows us to do several demonstration projects as a real Microgrid

• IIT Campus becomes a “live testbed”!42

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• 500 kWh

k

Battery Storage Battery Storage

• Backup power

• Peak Shaving

Chicago, IL, USA43

• 6 five‐hour 

Electric Vehicle ChargingElectric Vehicle Charging

charging stations

• 1 DC Quick Charge (15‐20 minutes)

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SAE Formula Electric Race TeamSAE Formula Electric Race Team

Chicago, IL, USA48

25

Thank you

Questions?

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Questions?

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Novel universal sensor

Current estimation

Operation principle of proposed current estimatorp p p p p

_ __

__

_ _

1

0

q s d sq s q

e sd s d

q s d s

dM Mu idt K

u d iM M

dt

1 0 0 0

0 1 0 0 i

i

0

0 0e sM J I

uJ i

50

_

_

0 0 0 1 0

0 0 0 0 1

0 0 0 0 0

0 0 0 0 0

e s

se s

se

e

M

uM

uii

ii

0 0eJ ii

50

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6. Novel universal sensor6.2 Current estimation

Based on

0

0 0e s

e

M J Iu

J ii

Based on

a sliding mode observer is designed as

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ˆ ˆ0 ˆ( )ˆ 00ˆ

e s

e

I IM Ju G sign

FJ ii

ˆ ˆ ˆ T

ˆ ˆ ˆ Ti i i

whereG: switching gain, which is equal to kIF: feedback gain matrix, which is equal to f1I+f2J˜: parameter’s nominal value when parameter’s error is consideredˆ: state variables’ estimated value

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