thermal degradation of traction machines - … line condition monitoring in workshop detailed...

Thermal degradation of traction

machines

Project – DYMEDEC

PhD fellow: Zhe Huang

Project manager: Azra Selimovic

Supervisors: Mats Alaküla, Avo Reinap

Volvo Group Trucks Technology

Dynamic modeling of cooling for electrical drives (DYMEDEC)

Industrial PhD project

2013-09-01 to 2016-05-31

3 088 500 SEK

Partners: Volvo Group and Lund University

Network: BEVI, SP, Chalmers, Dahrentråd...

Advanced Technology & Research, Zhe Huang, FFI Fordonskonferens

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Project info.



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Project goal and approach –

Dynamic thermal and lifetime model

Powertrain

model

Thermal

model Electrical

machine

cooling

Electrical

machine

losses

Life model Vehicle

and drive

cycle

Qheat

Qcool

T*,*


Identify critical failure modes

Choose degradation parameters

Impelement degradation

measurement

Data collection and

postprocessing

Possible test object (full machine/

motorrete/ bearing...)

Impelement stress (lab environment: current induced thermal cycle)

EM Degradation model

Load cycles

Design EM with the

required life span

On line data monitoring

RUL

Off line condition monitoring in

workshop

Detailed diagnostics + schedule spare

part

Off line learning phase

Build degradation model

Usage of degradation model


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Advanced Technology & Research

4 4

Degradation model and test verification

Implement

Implement stress



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Results


Thermal and degradation model - Inputs: driving cycle, vhecile specifications, defined powertain

- Outputs: temperature distribution while driving, expected lifetime

- Design traction machine with required lifetime

Accelerated lifetime test - Improved test method

Stator segment VS single material Electrically heated winding and liquid cooling VS oven heating

Thermal-mechanical model - Impregnation used to enhance the heat transfer induces mechanical stress to winding

coating (primary insulation) under thermal stress improve the degradation model (thermal-mechanical stress VS insulation lifetime)

Condition monitoring model - Global physical properties changes due to local insulation material aging improve the degradation model (usage time VS insulation quality)

Prognostic measurement – State of Health (SOH) - Povide quick health check of the traction motor before vehicle start daily

- Simple hardware and software requirement (high frequency logging device needed)


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Conclusions


Zhe Huang, Francisco J. Marquez-Fernandez, Yury Loayza, Avo Reinap, and Mats Alaküla.

"Dynamic thermal modeling and application of electrical machine in hybrid drives."

International Conference on Electrical Machines (ICEM), pp. 2158-2164. IEEE, 2014.

Zhe Huang, Avo Reinap, and M. Alaküla. "Predictive monitoring of turn-to-turn insulation in

single tooth coils." 10th International Symposium on Diagnostics for Electrical Machines,

Power Electronics and Drives (SDEMPED), IEEE, 2015.

Zhe Huang, Avo Reinap, and M. Alaküla. “Degradation and Fatigue of Epoxy Impregnated

Traction Motors Due to Thermal and Thermal Induced Mechanical Stress – Part I: Thermal

Mechanical Simulation of Single Wire due to Evenly Distributed Temperature”, 8th

International Conference on Power Electronics, Machines and Drives (PEMD), IET, 2016.

Zhe Huang, Avo Reinap, and M. Alaküla. “Degradation and Fatigue of Epoxy Impregnated

Traction Motors Due to Thermal and Thermal Induced Mechanical Stress – Part II: Thermal

Mechanical Simulation of Multiple Wires due to Evenly and Unevenly Distributed

Temperature”, 8th International Conference on Power Electronics, Machines and Drives

(PEMD), IET, 2016.

Zhe Huang, Avo Reinap, and M. Alaküla. “Dielectric Properties Modeling and Measurement

of Single Tooth Coil Insulation System under Accelerated Degradation Test”, International

Conference on Electrical Machines (ICEM), IEEE, 2016, full paper submitted.


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Publications

Thanks for your attention!



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Thermal model

Mechanical Dynamics Model

Detailed Loss Model

Detailed Thermal Model (1)

Detailed Thermal Model (2)


• Degradation caused by thermal stress

Life time versus constant thermal stress

- 𝐿 = 𝐴𝑒𝐵/𝑇

- Hot spot temperature in winding is the critical

parameter for lifetime

• Life time definition

- Standard defines L50

- From L50 to Ln...

Cumulative distribution function shape factor 𝛽

150 200 250 30010

2

103

104

105

Temp [oC]

Life

Tim

e [

ho

urs

]

Polyurethane TI155

Polyester TI180

Polyesterimide TI200

Polyester&Polyamide-imide TI220

𝐹 𝑡 = 1 − 𝑒−

𝑡𝜂

𝛽

• Temperature cycle counting algorithms

- Mean edge (MIL Handbook)

- RainFlow

(Fatigue estimation; consider the deepest cycle)


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Lifetime model



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Lifetime model – results

Diving Cycle Thermal Index

[°C]

Life time by Mean edge

[hours]

Life time by RainFlow

[hours]

US06

155 4 773 2 495

180 24 389 20 550

200 124 741 105 104

220 935 644 1 005 422


12 12

High voltage DC –

leakage current

(transient: time

constant; steady state:

insulation R)

Low voltage AC –

impedance (insulation

C)

Identify critical failure modes

Choose degradation parameters

Impelement degradation

measurement

Data collection and

postprocessing

Possible test object (full machine/

motorette/ bearing...)

Impelement stress (lab environment: current induced thermal cycle)

Off line learning phase

0.040.06

0.080.1

0.120.14

0

0.005

0.01

0.015

0.02

0.025

100

120

140

160

Test set up

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Implement

Implement stress


13

Improve model step 1 – Thermal-

mechanical stress VS aging

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Improve model step 2 – Predictable

properties change VS aging

Capacitance (phase to ground) change

during degradation: measurement at

different temperature cycle stresses

Differnt winding configurations and fill factors Single tooth winding under test

Analytical modeling

for

condition monitoring

Results – Insulation resistance at different

aging time of EM and coating thickness

Results – Insulation resistance

developement during degradation:

analytical modeling VS measurement

FEA modeling for

condition monitoring


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Degradation model application – Traction

machine prognostics Theory

- Traction machine on-line condition monitoring (State of Health) by parasitic capacitance changes with machine aging

Meaurement set-up

- On a PMSM (hybrid car traction)

- Fault case: phase and ground failure

Results

- Method validation by lab equipment

- Small influence by rotor position – lock rotor

- Up to 10 Mhz logging and current sensing requirement -> higher than control need but can be

shared with battery diagnostic

Current response with and without phase to ground fault,

in time domain (left) and in frequency domain (right) PMSM under measurement


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thermal degradation of traction machines - … line condition monitoring in workshop detailed...

Documents