EV Powertrain Simulations in Saber

49
Alan Courtay October 29, 2015 Paris Saber Seminar, La Defense Modeling of PMSM Motor Drive Multi Time Scale Analysis with Saber

Transcript of EV Powertrain Simulations in Saber

Page 1: EV Powertrain Simulations in Saber

Alan Courtay

October 29, 2015

Paris Saber Seminar, La Defense

Modeling of PMSM Motor Drive Multi Time Scale Analysis with Saber

Page 2: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 2

Simplified Electric Vehicle Powertrain Modeled after Market Available Electric Vehicle

Published

PMSM Electric Motor Max power / torque: 80 kW / 280 Nm

Li-Ion Battery

Total energy: 24 kWh

Max power > 90 kW

Number of cells: 192 (2 parallel, 96 series)

Cell voltage: 3.8 V

Nominal system voltage: 364.8 V

Gear Ratio 1/7.94

Curb Weight 1521 kg

0-100 km/h ~ 10 sec

Drag Coefficient 0.28

Inverter Frequency 5 kHz

Assumed

PMSM Electric Motor Max power / torque: 100 kW / 178 Nm, 8 poles

Inverter Efficiency 90%

Gear Efficiency 97%

Wheel Radius 0.3 m

Page 3: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 3

Simplified Electric Vehicle Powertrain Modeled after Market Available Electric Vehicle

Published

PMSM Electric Motor Max power / torque: 80 kW / 280 Nm

Li-Ion Battery

Total energy: 24 kWh

Max power > 90 kW

Number of cells: 192 (2 parallel, 96 series)

Cell voltage: 3.8 V

Nominal system voltage: 364.8 V

Gear Ratio 1/7.94

Curb Weight 1521 kg

0-100 km/h ~ 10 sec

Drag Coefficient 0.28

Inverter Frequency 5 kHz

Assumed

PMSM Electric Motor Max power / torque: 100 kW / 178 Nm, 8 poles

Inverter Efficiency 90%

Gear Efficiency 97%

Wheel Radius 0.3 m

IPMSM model from

JMAG-RT Motor Model

Library

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© 2015 Synopsys, Inc. 4

1 2

3 4

• Level 1

– Behavioral Li-Ion battery

– Dynamic thermal dq inverter and PMSM

– Thermal network

• Level 2

– Average/non-switching inverter /w TLU losses

– LdLq or detailed FEA-based PMSM

• Level 3

– Ideal switch inverter /w TLU losses

• Level 4

– Improved datasheet-driven IGBT1

Abstraction Levels

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© 2015 Synopsys, Inc. 5

1

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© 2015 Synopsys, Inc. 6

1 Simplified Vehicle Dynamics

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© 2015 Synopsys, Inc. 7

1

ia,va

ib,vb

ic,vc

a

b

c

Sinusoidal currents and switching/PWM voltages are abstracted to only

retain phase and amplitude of signals in synchronous reference frame

iq

id

vq

vd

i

v

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© 2015 Synopsys, Inc. 8

1

FEA-based look-up tables used for

flux saturation Ld(id) and Lq(iq), and

speed/current dependent iron loss

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© 2015 Synopsys, Inc. 9

1 Reactance Torque

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1

N S

Reactance Torque

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© 2015 Synopsys, Inc. 11

1 Reactance Torque

angle

torque

90o

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© 2015 Synopsys, Inc. 12

1 Reluctance Torque

Br

Hc

m

The permanent magnets have low

permeability / high reluctance (~ air

gap). The rotor orients itself in the

position of least flux resistance.

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© 2015 Synopsys, Inc. 13

1 Average Inverter Model

including Efficiency Map

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© 2015 Synopsys, Inc. 14

Switching Losses 1

≈ 𝛼 ∙ 𝒗𝒐𝒇𝒇 ∙ 𝒊𝒐𝒏

on+off

𝑷𝒔𝒘 = 𝑬𝒔𝒘 ∙ 𝒇𝒔

= 𝑬𝒔𝒘 (𝒗𝒐𝒇𝒇, 𝒊𝒐𝒏) rec +

𝒊𝒐𝒏 (𝑨) 𝒗𝒐𝒇𝒇 (𝑽)

𝑬𝒔𝒘 (𝑱)

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© 2015 Synopsys, Inc. 15

v

i

one 1D look-up table: 𝑃𝑐(𝑖) = 𝑖. 𝑣(𝑖)

Conduction Losses 1

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© 2015 Synopsys, Inc. 16

1

Field Oriented Control

Vector Control

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© 2015 Synopsys, Inc. 17

1

𝑖∗2 = 𝑖𝑑

∗2 + 𝑖𝑞∗2

𝜕𝑇

𝜕𝑖∗= 0

𝑖𝑑∗ =

𝜑𝑚 − 𝜑𝑚2 + 8 𝐿𝑞 − 𝐿𝑑

2𝑖∗2

4 𝐿𝑞 − 𝐿𝑑

𝑖𝑞∗ = 𝑠𝑔𝑛(𝑖∗) 𝑖∗2 − 𝑖𝑑

∗2

Maximum Torque Per Amp

𝑖𝑑∗

𝑖𝑞∗

𝑖∗

Field Oriented Control Field Oriented Control

MTPA 𝑖∗

𝑖𝑑∗

𝜃𝑖

𝑖𝑞∗

𝑖𝑑

𝑖𝑞

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1 Flux Weakening

𝑖𝑑∗

𝑖𝑞∗

𝑖𝑑

𝑖𝑞

Field Oriented Control

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© 2015 Synopsys, Inc. 19

1 Flux Weakening

𝑖𝑑∗

𝑖𝑞∗

𝑖𝑑

𝑖𝑞

Field Oriented Control

𝑉𝑞 = 𝑅𝑖𝑞 + 𝐿𝑞𝑑𝑖𝑞𝑑𝑡

+ 𝜔 𝐿𝑑𝑖𝑑 + 𝜑𝑚

𝑉𝑑 = 𝑅𝑖𝑑 + 𝐿𝑑𝑑𝑖𝑑𝑑𝑡

− 𝜔𝐿𝑞𝑖𝑞

𝑇 =3

4𝑝 𝜑𝑚𝑖𝑞 + 𝐿𝑑 − 𝐿𝑞 𝑖𝑑𝑖𝑞

R neglected,

steady-state

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© 2015 Synopsys, Inc. 20

1 Flux Weakening

𝑖𝑑∗

𝑖𝑞∗

𝑖𝑑

𝑖𝑞

Field Oriented Control

𝑉𝑞 = 𝜔 𝐿𝑑𝑖𝑑 + 𝜑𝑚

𝑉𝑑 = −𝜔𝐿𝑞𝑖𝑞

𝑇 =3

4𝑝 𝜑𝑚𝑖𝑞 + 𝐿𝑑 − 𝐿𝑞 𝑖𝑑𝑖𝑞

At high speed, back-EMF

exceeds DC link voltage

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1 Flux Weakening

𝑖𝑑∗

𝑖𝑞∗

𝑖𝑑

𝑖𝑞

Field Oriented Control

𝑉𝑞 = 𝜔 𝐿𝑑𝑖𝑑 + 𝜑𝑚

𝑉𝑑 = −𝜔𝐿𝑞𝑖𝑞

𝑇 =3

4𝑝 𝜑𝑚𝑖𝑞 + 𝐿𝑑 − 𝐿𝑞 𝑖𝑑𝑖𝑞

Increase current angle (negative

component of id) to “weaken”

magnet flux and reduce back-EMF

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© 2015 Synopsys, Inc. 22

𝑖𝑑∗

𝑖𝑞∗

𝑖𝑑

𝑖𝑞

Field Oriented Control

MTPA 𝑖

−𝜑𝑚𝐿𝑑

𝜑𝑚𝐿𝑞 − 𝐿𝑑

𝑖𝑞

𝑖𝑑

1 Flux Weakening

𝑉𝑞 = 𝜔 𝐿𝑑𝑖𝑑 + 𝜑𝑚

𝑉𝑑 = −𝜔𝐿𝑞𝑖𝑞

𝑇 =3

4𝑝 𝜑𝑚𝑖𝑞 + 𝐿𝑑 − 𝐿𝑞 𝑖𝑑𝑖𝑞

Increase current angle (negative

component of id) to “weaken”

magnet flux and reduce back-EMF

𝑣2 = 𝑣𝑑2 + 𝑣𝑞

2

Voltage Limit Ellipse

𝑣2

𝜔2 = 𝐿𝑑𝑖𝑑 + 𝜑𝑚2 + 𝐿𝑞

2𝑖𝑞2

𝜃𝑖

Page 23: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 23

𝑖𝑑∗

𝑖𝑞∗

𝑖𝑑

𝑖𝑞

Field Oriented Control

MTPA

𝑖

−𝜑𝑚𝐿𝑑

𝜑𝑚𝐿𝑞 − 𝐿𝑑

Increasing Speed

𝑖𝑞

𝑖𝑑

1 Flux Weakening

𝑉𝑞 = 𝜔 𝐿𝑑𝑖𝑑 + 𝜑𝑚

𝑉𝑑 = −𝜔𝐿𝑞𝑖𝑞

𝑇 =3

4𝑝 𝜑𝑚𝑖𝑞 + 𝐿𝑑 − 𝐿𝑞 𝑖𝑑𝑖𝑞

Increase current angle (negative

component of id) to “weaken”

magnet flux and reduce back-EMF

𝜃𝑖

𝑣2 = 𝑣𝑑2 + 𝑣𝑞

2

Voltage Limit Ellipse

𝑣2

𝜔2 = 𝐿𝑑𝑖𝑑 + 𝜑𝑚2 + 𝐿𝑞

2𝑖𝑞2

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© 2015 Synopsys, Inc. 24

1

Field Oriented Control

𝑉𝑞 = 𝜔 𝐿𝑑𝑖𝑑 + 𝜑𝑚

𝑉𝑑 = −𝜔𝐿𝑞𝑖𝑞

𝑇 =3

4𝑝 𝜑𝑚𝑖𝑞 + 𝐿𝑑 − 𝐿𝑞 𝑖𝑑𝑖𝑞

Feedforward Compensation

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© 2015 Synopsys, Inc. 25

1 • Analyze system efficiency over long driving cycles

• Evaluate energy flow in critical regimes

(deceleration, braking)

• Handle power dissipation and cooling

• Design stable motor control (e.g. FOC)

Page 26: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 26

1 • Analyze system efficiency over long driving cycles

• Evaluate energy flow in critical regimes

(deceleration, braking)

• Handle power dissipation and cooling

• Design stable motor control (e.g. FOC)

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© 2015 Synopsys, Inc. 27

1 2

Sinusoidal currents and voltages (no switching)

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1 2

a

b

c

𝜃𝑚

𝜃𝑖

i

Accounts for

1. Mutual coupling between phases

2. Flux saturation

3. Spatial harmonics

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© 2015 Synopsys, Inc. 29

1 2

• Analyze system dynamics

• Evaluate energy flow in critical regimes

(deceleration, braking)

• Design stable motor control (e.g. FOC)

• Evaluate torque ripples

Motor

Torque

Regenerative

Braking

Sloped Terrain Startup

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© 2015 Synopsys, Inc. 30

1 2

• Analyze system dynamics

• Evaluate energy flow in critical regimes

(deceleration, braking)

• Design stable motor control (e.g. FOC)

• Evaluate torque ripples

Torque ripples due to

spatial harmonics

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© 2015 Synopsys, Inc. 31

1 2

3

• Design PWM control (e.g. compensate dead time distortion)

• Mitigate faults in critical regimes (e.g. in flux weakening mode)

Dead time distortion

(corrected and uncorrected)

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© 2015 Synopsys, Inc. 32

1 2

3 4

• Optimize gate drive tradeoff losses vs. EMI noise

• Control current/voltage overshoot

• Prevent accidental turn-on

𝑖 = 𝐶𝑐𝑔 ∙𝑑𝑉𝑐𝑒

𝑑𝑡≫ 1

Vg < Vge(th)

Rg

Vgei > Vge(th) c

e

𝑉 = 𝐿𝑒 ∙𝑑𝑖𝑐𝑑𝑡

≪ −1

Accidental turn-on

mechanisms

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© 2015 Synopsys, Inc. 33

2016.03 IGBT Tool

• Improved matching of transient

characteristics

– Cge made non-linear

– Control of turn-off voltage oscillations

– Decoupling between turn-on and turn-off

• Easier characterization

– Optimizer at most steps, including

transient characteristics

– Turn-on and turn-off characteristics

combined in one view

– Improved DC anchor points

– Library of pre-characterized components

– Numerous bug fixes

Page 34: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 34

IGBT Principle Collector/Anode

Emitter/Cathode

P+ Emitter

Gate

P

N- Base

P+

N+

• Two junctions

– J1 space charge region develops

when Vce < 0

– J2 space charge region develops

when Vce > 0 and Vge < Vge(th)

– Wide and low doped N- base region

→ large blocking voltage

• BJT+MOSFET

– Insulated gate → voltage control

– Holes injected from P+ emitter →

conductivity modulation

– High forward conduction current

density: 𝑖𝑐 = 𝑖𝑚𝑜𝑠 + 𝑖𝑝

• Slow removal of carriers in the

base → longer switching time

during turn-off and tail current

J1

J2

+

+

Page 35: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 35

IGBT Principle Collector/Anode

Emitter/Cathode

P+ Emitter

Gate

P

N- Base

Rb

PNP

N-MOS

P+

N+

imos ip

(𝛽)

+ +

+

holes

electrons

• Two junctions

– J1 space charge region develops

when Vce < 0

– J2 space charge region develops

when Vce > 0 and Vge < Vge(th)

– Wide and low doped N- base region

→ large blocking voltage

• BJT+MOSFET

– Insulated gate → voltage control

– Holes injected from P+ emitter →

conductivity modulation

– High forward conduction current

density: 𝑖𝑐 = 𝑖𝑚𝑜𝑠 + 𝑖𝑝

• Slow removal of carriers in the

base → longer switching time

during turn-off and tail current

Page 36: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 36

IGBT Principle Collector/Anode

Emitter/Cathode

P+ Emitter

Gate

P

N- Base

P+

N+

imos ip +

+

• Two junctions

– J1 space charge region develops

when Vce < 0

– J2 space charge region develops

when Vce > 0 and Vge < Vge(th)

– Wide and low doped N- base region

→ large blocking voltage

• BJT+MOSFET

– Insulated gate → voltage control

– Holes injected from P+ emitter →

conductivity modulation

– High forward conduction current

density: 𝑖𝑐 = 𝑖𝑚𝑜𝑠 + 𝑖𝑝

• Slow removal of carriers in the

base → longer switching time

during turn-off and tail current

Page 37: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 37

IGBT Principle Collector/Anode

Emitter/Cathode

P+ Emitter

Gate

P

N- Base

P+

N+

+ • Two junctions

– J1 space charge region develops

when Vce < 0

– J2 space charge region develops

when Vce > 0 and Vge < Vge(th)

– Wide and low doped N- base region

→ large blocking voltage

• BJT+MOSFET

– Insulated gate → voltage control

– Holes injected from P+ emitter →

conductivity modulation

– High forward conduction current

density: 𝑖𝑐 = 𝑖𝑚𝑜𝑠 + 𝑖𝑝

• Slow removal of carriers in the

base → longer switching time

during turn-off and tail current

Page 38: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 38

Page 39: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 39

IKW75N65EL5

Static Characteristics

Page 40: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 40

Quasi-Static Characteristics

IKW75N65EL5

Page 41: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 41

IKW75N65EL5

Quasi-Static Characteristics

Page 42: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 42

Ic

Vcc

Inductive Clamp Test Circuit

Vcc

Rg(off)

Vg(on)

Vg(off)

Lp

DUT

(IGBT)

-15V

Ic

DUT

(Diode)

Rg(on)

Vg(on)

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© 2015 Synopsys, Inc. 43 1 1

1

1

2

2

2

2

3 3

3

3

4

4

4 4

5

5

5

5

𝐶𝑟𝑒𝑠 = 𝐶𝑔𝑐 𝐶𝑖𝑒𝑠 = 𝐶𝑔𝑐 + 𝐶𝑔𝑒

𝐶𝑜𝑒𝑠 = 𝐶𝑔𝑐 + 𝐶𝑐𝑒

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© 2015 Synopsys, Inc. 44

𝐶𝑟𝑒𝑠 = 𝐶𝑔𝑐 𝐶𝑖𝑒𝑠 = 𝐶𝑔𝑐 + 𝐶𝑔𝑒

𝐶𝑜𝑒𝑠 = 𝐶𝑔𝑐 + 𝐶𝑐𝑒

Cies = dQg / dVgs

Miller plateau Vgs

~1.2nF

~1.2nF

Page 45: EV Powertrain Simulations in Saber

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IKW75N65EL5

Non Quasi-Static Characteristics

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© 2015 Synopsys, Inc. 46

IKW75N65EL5

Non Quasi-Static Characteristics

Page 47: EV Powertrain Simulations in Saber

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IKW75N65EL5

Non Quasi-Static Characteristics

Page 48: EV Powertrain Simulations in Saber

© 2015 Synopsys, Inc. 48

IKW75N65EL5

Thermal Characteristics

Cauer network Foster network

Duty cycle zero

sufficient to match

the other curves Only physical if

connected to

temperature source