Evaluation of macroscopic polarization and actuation abilities of electrostrictive dipolar polymers...

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Systèmes auto-alimentés et sans fil: Recupération d’energie avec des matériaux ferroélectriques

Daniel GuyomarDaniel Guyomar

LGEF, INSA Lyon, Villeurbanne, France Email : [email protected]

mailto:[email protected]

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Introduction to self-powered wireless systems

Introduction to ferroelectric materials (piezo/pyro electric)

Non-linear processing principle for energy conversion improvement

Applications to:* Self-powered semi-active vibration control* Energy harvesting* On vibrations* On temperature fluctuations

Conclusions

Outline

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Conclusions

13

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Seminaire-El-Jadida

What is a smart system?Self powering and wireless data

transfer

RF receiver

Micro-controller+Actuator

High power supply 230V/50 Hz

Energy harvester (smart

material)

Energy management

Sensor+processi

ng

RF Transmitter

Ambient energy (solar, vibration, heat…)

EM waves

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Seminaire-El-Jadida

Advantages of self-powered (battery-less) wireless systems1) Ecological benefit (no batteries disposal/ reduction of

chemical pollution)2) High industrial reliability (no wiring, no plugging)3) Cost reduction (no wiring, no plugging)4) Maintenance free5) No connection to external power supply

Two main favorable trends: 1) Electronic component consumption has drastically

decreased lately (cell phone effect)2) Energy harvester performances have been significantly increased

Self-powered wireless systems (sensors network powering , intelligent switch, structural health monitoring,…)

To increase self-powered systems performances Need to increase the harvested energy Need to improve the mechanical to electrical energy conversion in the piezoelectric material Non-linear processing of the output voltage

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Exemples de systèmes intelligents

Capteur

Émetteur RF

récupération de l’énergie vibratoire ambiante

Structure

Applications:TempératurePressionContrôle de santé

Amortissement vibratoire

Structure

Dispositif électromécanique autoalimenté assurant l’amortissement vibratoire de la structure

Récupération d’énergie

16

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Seminaire-El-Jadida

Emetteur RF (<1mW)

Amortissement vibratoire

Récupération d’énergie

Raquette et ski Head ®

Autres exemples

Réseau de capteurs sans fil

Interrupteur sans fil Enocean ®

17

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Seminaire-El-Jadida

K2 & ACX

18

LGEF

Seminaire-El-Jadida





Conclusions

19

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-4000

-3000

-2000

-1000

0

1000

2000

3000

4000

0 200 400 600 800 1000 1200

Cham

p ap

pliqué

(V/m

m)

Champ appliqué en volts/mm

20

LGEF

Seminaire-El-JadidaDonne la valeur de la permitivité autour de E=0 (epsilon)

Polarisation en fonction du champ appliqué

Zone linéarisation autour de la polarisation remanente

Les ferroelectriques présentent une polarisation non nulle (rémanente) à champ nul

P(E) 0,1Hz

-4,00E-01

-3,00E-01

-2,00E-01

-1,00E-01

0,00E+00

1,00E-01

2,00E-01

3,00E-01

4,00E-01

-4000 -3000 -2000 -1000 0 1000 2000 3000 4000

Electric field (V/mm)

Pola

riza

tion

(C/

m²)

21

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Seminaire-El-Jadida

Déformation en fonction de la polarisation

Zone linéarisation

Donne la valeur de la déformation à contrainte nulle (g)

La deformation est electrostrictive (paire avec la polarisation) comme une majorité de dielectriques. Dans un piezo,elle serait lineaire avec la polarisationPMN-40PT ceramic 0,1Hz

-0,15

-0,10

-0,05

0,00

0,05

0,10

0,15

-4,00E-01 -3,00E-01 -2,00E-01 -1,00E-01 0,00E+00 1,00E-01 2,00E-01 3,00E-01 4,00E-01

Polarization (C/m²)

Stra

in (

%)

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Seminaire-El-Jadida

Déformation en fonction du champ appliqué

Zone linéarisation

Donne la déformation en fonction du champ à contrainte nulle(d)

S(E) 0,1Hz

-0,15

-0,10

-0,05

0,00

0,05

0,10

0,15

0,20

-4000 -3000 -2000 -1000 0 1000 2000 3000 4000

Electric field (V/mm)

Stra

in (

%)

En combinant P(E) et S(P), on obtient le cycle S(E)

Tout se passe comme si le materiau était piezoelectrique mais avec un fort couplage

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Seminaire-El-Jadida

A partir de ces linéarisations, on trouve

La raideur du materiau varie en fonction de l’impedance aux bornes La capacité du matériau varie en fonction de l’état de contrainte

On voit que l’on peut créer:- une déformation à contrainte nulle!!- une contrainte à déformation nulle!!- un champ électrique à induction nulle!!- une induction (des charges) à champ nul!!

Cette propriété, un peu surprenante, est liée au couplagemultiphysique entre les phénomènes électriques et les phénomènes mécaniques

Equations mécaniques EeScT tE

DhScT tD

Equations électriques eSED S

hSDE S

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What’s “Piezoelectric Effect”CONVERSE PIEZOELECTRIC EFFECT

IgniterMicrophonePressure Sensor

DIRECT PIEZOELECTRIC EFFECT

ClockSpeakerActuator

25

LGEF

Seminaire-El-Jadida

X 3

Polarisation en fonction de la températureZone

linéaire

Donne la polar en fonction de la température (effet pyro=p)

26

LGEF

Seminaire-El-Jadida

Polarisation en fonction de la température pour différents champs

Champ E croissant

Zone linéarisation

Point de Curie125°C

Coefficient pyro (p) pour différents champs

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Si on veut recupérer de l’énergie avec un système “solid-state”, il faut un matériau qui convertisse très efficacement l’énergie ambiante. Autrement dit un materiau à très fort couplage energétique

Par exemple* un bon matériau piezoélectrique pour convertir l’énergie vibratoire* un bon matériau pyroélectrique pour convertir l’energie liée aux fluctuations de température

Les matériaux ferroelectriques remplissent ces deux fonctions. Le couplage dans ces matériaux peut être augmenter en jouant sur la structure physico-chimique mais il semble que nous ayons atteint un palier…

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Can the mechanical to electrical energy conversion in a piezomaterial be improved by shaping out the output piezo-voltage? …..Can be done but requires a non-linear voltage processing!

The energy conversion is an important issue since most of the structures are poorly coupled (Piezo-element bonded on a mechanical structure)

Need to increase the coupling for most applications but mainly for energy harvesting and Self-powered wireless systems (the energy source being low, a good conversion is needed to harvest a useable energy)

29

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Conclusions

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t

V2(t)u(t)

Very short Switching time

t

V(t)

V1(t)

Voltage V(t) = V1(t) +V2(t)V1(t) = Image of the strain (open-circuit voltage)V2(t) = Piecewise function proportionnal to

• Switching generates a dry friction force on the system• frequency independant works in low frequency regime

V2(t)V1(t)

t

V(t)=Switched voltage

t

)(usign When switching occurs at max or min

Non-linear processing principleCantilever beam

Piezo-element

31

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Seminaire-El-Jadida

t

t

VM

tIQMeV 2

Voltage Voltage

Current

0

Mechanical period

Switching time

First stage of the electrical ringing

The voltage inversion is done with a coil

To avoid the voltage ringing, the switch is opened when the current vanishes.

This resonant frequency is purely electric. There is no tuning on the mechanical resonance!.

The resonant frequency being high, the inductance value is small and….the coil is not buckly even for low mechanical resonances!

Non-linear processing principle

32

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Seminaire-El-Jadida

-30

-20

-10

0

10

20

30

0 0,05 0,1 0,15 0,2TIM E IN SECO NDS

PIEZ

O VOL

T. O

R DI

SPL.in

mm

DISPL.

OPENVO LTAG E

SSDS VOLT.

SSDI VO LT.

Piezoelectric elem ents

T1

T2 D2 D1

Switch control Voltage

monitoring

Dual M OSFET switch

Switching inductor

L

C o

Energy is required only for driving the transistors and for the switch control. Low energy requirements, the system can be easily self-powered


The switching results in a voltage magnification (better energy conversion) and a voltage shift in the time domain.

If the frequency of the vibration changes, switching will occur on the new max and min, The technique is insensitive to frequency drifts (variation of the BC, environmental changes). Broadband system, no tuning needed

33

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Seminaire-El-Jadida

Displacement U

Switched voltage V

No contro

l

SSDS

SSDI-30

-20

-10

0

10

20

30

0 0,05 0,1 0,15 0,2TIM E IN SECONDS

PIEZ

O V

OLT. O

R DI

SPL.in

mm

Voltage time waveforms

du.V. Area of the cycle= Converted energy

Unlike viscous forces, the shape of the cycle does not depend on the frequency Converted energy is independant of the frequency


34

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Seminaire-El-Jadida

Energy balance derived from dynamic equation

Input energy Mechanical energies Mechanical losses Converted energy

Maximize

2 EF udt Muudt K udt Cu dt Vudt

convW Vudt

Optimization of converted energy How to shape the function versus ?

()u t()V t

Converted energy Electrostatic Energy

stored on the piezo itself

Extracted energyLosses in the

coilEnergy stored in

the storage capacitance

VIdtVCdtuVWconv2

021


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LGEF

Seminaire-El-Jadida

Dissipated energy

(viscous)21

02SE Vudt C V VIdt

Coupled energy Electrostatic energy

Extracted energy

No losses during the switch ( Resonant system driven by a pulsed force)

Fast conversion of the energyMechanical energy converted in electrical energy


0 0.02 0.04 0.06 0.08 0.1 0.12-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

0 0.02 0.04 0.06 0.08 0.10

0.2

0.4

0.6

0.8

1V(t)u(t) Supplied energy

Mechanical energy

Electrostatic energy

Extracted energy

Time Time

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LGEF

Seminaire-El-Jadida

V(t)

Slower energy conversion Vibration damping 10 times higher than the tuned resistance (purely passive approach)Mechanical energy Electrostatic energy Losses during the voltage inversion

Real case: Losses during the switch

=0.85

0 0.05 0.1 0.15 0.2 0.25-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1 u(t)

0 0.05 0.1 0.15 0.2 0.250

0.2

0.4

0.6

0.8

1


Supplied energy

Mechanical energy

Extracted energy

Electrostatic energy

Dissipated energy (viscous)

Time Time

37

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Conclusions

38

LGEF

Seminaire-El-Jadida

Semi-active vibration control

2

14 11 1

SSDI

m

Ak Q

2 0.0092200 21dB

0.7m SSDI

kQ A

52 54 56 58 600

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

52 54 56 58 600

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Without control SSDITheoretic

alExperimental

F [Hz]

single mode and narrowband driving

coeffinversion

Unlike inductive passive damping, no tuning is needed The system is fully adaptative

Semi-active+self-powered system looks like purely passive device with increased damping performances

39

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Seminaire-El-Jadida

Switching Strategy for multi-modal broadband systems

V

How to shape versus ?

What is best : Switching on all max (min)or Switching on specific ones ?

t

t

V???


Time

Displacement

21 k

N

kVdtuV

Vu

N high|Vk| low

N low|Vk| high

switch theduring jump voltage switch, ofnumber kVN

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LGEF

Seminaire-El-Jadida

Switching strategy

for broadband signals

Find the optimal switching sequence that maximizes

Need for a fast estimation of the time signal peak distribution to select the interesting maxima (highest peaks)

Can be done by computing a short term Probability Density Function of the voltage or displacement signals

2

1

N

kk

V

PSW 1

v²

FV² (v²)

2minv

22 2 2

VF v P V v

Switching condition:If the voltage reaches a amplitude greater than vmin , the switch occurs on the next maxima

2 2min

0dVdt

V v

Voltage Threshold


41

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Seminaire-El-Jadida

W ithout Control

voltage inversion at each extremum

Probabilistic approach PSW=0.1

Normalized strain Piezovoltage [V]

t [s]

t [s]

t [s] 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 -1

-0.5

0 0.5

1

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 -50

-25

0 25

50

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 -1

-0.5

0 0.5

1

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 -100

-50

0 50

100

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 -1

-0.5

0 0.5

1

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 -200

-100

0 100

200

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4-1

-0.5

0

0.5

1

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4-1

-0.5

0

0.5

1

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4-1

-0.5

0

0.5

1

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4-1

-0.5

0

0.5

1

W ithout Control


t [s]

t [s]

t [s]

[mm]

[mm]

[mm] Probabilistic approach PSW=0.1

Strain and voltage Free end beam displacement

Control Law AEdB Quadratic displacement mean value

AudB Energy criterion

Switch on each extremum

-4.89 dB -3.81 dB

Probabilistic – PSW=0.1

-6.50 dB -7.67 dB

Semi-active vibration control: pulsed signal

42

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Seminaire-El-Jadida42

W ithout Control


Probabilistic approach

Normalized strain Piezovoltage [V]

t [s]

t [s]

t [s] 1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2 -1

-0.5

0

0.5

1

1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2 -10

-5

0

5

10

1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2 -1

-0.5

0

0.5

1

1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2 -10

-5

0

5

10

1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2 -1

-0.5

0

0.5

1

1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2 -20

-10

0

10

20

1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2-0.2

-0.1

0

0.1

0.2

1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2-0.2

-0.1

0

0.1

0.2

1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2-0.2

-0.1

0

0.1

0.2

1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2-0.2

-0.1

0

0.1

0.2


Probabilistic approach

t [s]

t [s]

t [s]

[mm]

[mm]

[mm]

W ithout Control

Strain and voltage Beam free end displacement

White noise excitation – Vibration control simulation results (1)

The same random sequence was played in all cases

43

LGEF

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t [s]

[V]

14.9 14.92 14.94 14.96 14.98 15

Probabilist approach[V]

14.9 14.92 14.94 14.96 14.98 15-10

-5

0

5

10

Open-circuit voltage [V]

14.9 14.92 14.94 14.96 14.98 15-10

-5

0

5

10

Switching on all max/min

-10

-5

0

5

10

t [s]

t [s]

-15.6-4.1 0

[dB]

0 200 400 600 800 1000 1200-70

-60

-50-40

-30-20-10

0

Open circuit voltage

-8.0 -10.5-21.8

[dB]

0 200 400 600 800 1000 1200-70

-60-50-40

-30-20-10

0

Switching on all max/min

-12.6 -16.2 -19.2

[dB]

f [Hz]0 200 400 600 800 1000 1200-70

-60-50-40

-30-20-100

Probabilist approach

Time waveforms

Displacement waveform spectrum

Voltage time waveforms

Semi-active vibration control: white noise signal

44

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Energy requirements for self powering are compatible with the energy that could be harvestedA specific DSP component is under development

Advantage of the statistical moments approach: good result and robust easy to implement (few computation steps…low energy required)

0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

tim e (s)

velo

city

(m/s)

with control

0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

tim e (s)

velo

city

(m/s)

without control

Experimental results for a beam driven by a random signal

Beam tip velocity

With control

No control

Same time sequence

Semi-active vibration control: statistical approach

)()( uSTDumeanEstimator

Energy requirements for probability approach are too high

Simplified approach based on statistical moments (mean,STD..)

8 dB

45

LGEF

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Conclusions

46

LGEF

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Load

structure

piezoelement

I

Rectifier circuit

StorageSSHI

structure

piezoelement

I

SSHI Load

AC

DC

Derived from Synchronized Switched Damping (SSD) technique

Energy harvesting on vibrations

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Standard approach (fixed displacement)V,VDC,u

I

t

t

2max 21

eEkPk

Optimal resistance

Max harvested power

opt02R

C

102 103 104 105 106 107 1080

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1P

Harvested power versus the load R

Energy cycle

R

V

u-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

I

rectifier

Storage capacitance

V

VDC

load

structure

Piezo-element

R


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SSHI approach (fixed displacement)

t

t

V,VDC,u

I,IS

2

max 2211

eEkPk

Optimal resistance

Max harvested power

opt0 1

RC

load

structure

Piezo-element

rectifier Storage capacitanceSSHI

V

VDC

I

IS

R


102 103 104 105 106 107 108 109 10100

1

2

3

4

5

6

7

8

9

10

P in mW

R-1-0.8-0.6-0.4-0.20 0.20.40.60.81

-10-8-6-4-20246810

Energy cycle V

u

Harvested power versus the load R

Factor of 10

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ElectromagnetDisplacementsensor

Cantileverbeam

Piezo

PARAMETERGenerator using PMN-0,25PT

material

CERAMIC SINGLE CRYSTAL

Short circuit res. Freq. f0 (Hz)Open circuit res. Freq. f1 (Hz)Open circuit damping coef. (10-3)Mech. Quality factor QmC0 (pF)k coupling coef.

936,4938,41,752006460,065

883,7918,11,7820012000,271

Piezoelectric element:10 x 7 x 1 mm3

40 mm

7 mmThickness 1.5 mm

Steel beam

Piezo-element

x 4

Influence of material PMN-PTceramic/ PMN-PTsingle

crystal

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Standard

Parallel SSHI

Ceramic Single crystal25 µW

180 µW

490 µW

4.0 mW

Displacement amplitude: 150 µm

Factor x 20

Factor x 8

Performance comparison

Overall gain=160 !Influence of material: Factor 20

(coupling coefficient)Influence of harvesting strategy: Factor 8

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V(t)

u(t)

Vrect(t)

W(t)

u(t)

Vrect(t)

V(t)

W(t)

Pulsed power response (experimental)

SSH Control DC

Without control DC

SSH control DC

Ratio

Harvested Energy

5.6mJ 7.6mJ 1.35

Harvesting time 6s 2s 0.33Max power 3mW 9mW 3

Standard DC

For pulsed vibrations (finite energy), the transfer from mechanical to electrical energy damps the signal and limits the conversion

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Conclusions

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The principles of standard and SSHI energy harvesting techniques remain the same for piezo and pyro harvester

It means that the switching approach can be applied directly for harvesting on temperature Standard technique:

Parallel SSHI M

AlpW 22

maxpyrostand

MAlpW 22

maxpyroSSHI2

Gain of 6 for =0.7

Energy harvesting on temperature variations

:Voltage inversion coefficient

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Experimental validation

Drier command

SSHI harvesting circuit

PVDF films Drier

Gain of 5.65

0 20 40 60 80 1000

20

40

60

80

100

120

140

160

180

V DC

Harv

ested

Energy

per c

ycle (

J)

Theoretical standardExperimental standardTheoretical SSHIExperimental SSHI

Frequency=0.5HzTemp varia=1.27 K

Power=0.5mW

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Conclusions

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Energy conversion improvement can be done using a non-linear approachEasy to integrate (no bulky electronics, electronic patch bonded on the piezo)Self adaptative (no resonance shift influence), no tuning neededPossible extension or the approach to other coupled systems (thermoelectric..)

Conclusion

Semi-passive vibration controlLeads to damping performances between purely passive and active controlSelf-powered/ adaptative/ broadbandNo needs for bulky amplifier or fast computer (no heavy computation involved)

Energy Harvesting on temperature variationsHarvested energy X 6 (based on SSHI approach)Energy is high but power remains low due to the slowness of thermal processes

Energy Harvesting on vibrationsHarvested energy X 10For a sismic harvester, the harvested energy in around 3mW/ Cubic centimeter/ 1gHarvested energy can be independant of electric load (the gain drops to 5)Efficient in the pulsed regime

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Self-powered structural Health monitoringSelf-powered structural Health monitoringPrinciple: The energy harvested on the bending modes is used to generate HF Lamb waves to monitor the structureThe structure is instrumented with a array of combined elements (US emitter/energy harvesters/ RF emitter)Once the harvested energy is high enough, a RF code is sent to let the receiver know which emitter is going to launch a Lamb wave. The receiver/ energy harvester makes a low energy consuming processing that monitors the waveform evolution between two successive shots. If the difference between two shots is higher than a threshold, a RF code is sent to a central unit (warning code)

Lamb wave Lamb wave receiver and receiver and energyenergy harvesterharvester

Autonomous Wireless Transmitter and Autonomous Wireless Transmitter and Energy HarvesterEnergy Harvester

ROUTEUR

Or

CENTRAL UNIT

RF link

Instrumented Structure

Instrumented Structure

Lamb wave

RF linkRF link

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Structural Health monitoring/ Structural Health monitoring/ Experimental set-up

Voltage and Energy requirement V= 2V to 8V E 5mJ

2 main functions driven by a PIC IDN code RF emission Lamb Wave emission

Structure of the self-powered Autonomous Wireless Transmitter (AWT)

– Notch 1: 0.2 mm deep– Notch 2: 0.3 mm deep

P1 Harvesting element

P2 Lamb wave emitter

P3 Lateral stress sensor

P4Lamb wave sensor

Wave processingand RF link

Notch

IDN

P1

SSH module

batte

ry

PIC16F688 dr

ive

r

P2 Lamb wave

IDN

VB

DO0 DO1

AI0

RF emitter GFRP beam

Thickness: 3mmLength: 40 cm

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– AWT energy consumption :

Structural Health monitoringStructural Health monitoring

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– Damage Index definition: trade-off computation cost/sensitivity

RMS-based Damage Index Energy requirement for RMS processing:1.5mJ for a 4ms signal duration

Structural Health monitoringStructural Health monitoring

2

1

2

1

)(

)()(v

v

v

v

dvvF

dvvFDvFDI

Standard

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Mechanical energyElectrical energy

EAPE W

Electro-active polymersEnergy conversion in both ways

Actuators

Harvester or sensors

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The EA polymer approach (Advantages) Work limited to nano( macro)-filled polymers

(composite polymers) Light (spatial applications) Very Flexible (large deformation without breaking) A different trade-off in terms of mechanical potential

energy (large deformation, low modulus) Large strain (>20% for realistic modulus (similar to

muscle)) The max strain of a single crystal is around 0.3% !!! Properties can be modulated in a significant manner by

playing with the filler ratio (unlike ceramics) Easy and fast processes Can be spread over large surfaces Can be spread over almost any surface shape Low cost materials

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The EA polymer approach (drawbacks ) Electroding is tricky due to the very large strain (electrodes are torn off fro high strains)

Polymer conduction varies rapidly around percolation.

Max strain decreases when conduction takes place Nano-micro particles are difficult to disperse in the polymer matrix. A certain lack of reproductibility

Properties vary with temperature close to transitions

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The EA polymer approach at LGEF Conductive particle instead of ferroelectric particles Based on the belief that to increase d33 increase with

epsilon33 (true for ceramic) No conduction for large ratio, but the electrical field

does not get into the particle (ratio>100 in epsilon) In conductive particles the field is zero (for sure). To

cancel the imposed field, electrical charges accumulate at the interface. From outside, the conductive particle looks like a poled particles once included in an insulator

Polymer sample conduction around percolation threshold

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The EA polymer approach at LGEF Conductive particle instead of ferroelectric particles Several routes to disperse the fillers

( carbon black particles, SIC carbon coated particles, CNT): Mechanical mixing of the fillers in the matrix

(mainly PU)+ Sonication Incorporate already dispersed elements (inks) in

the polymer Dye-cast or/ and spin coating

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H Voltage Ampli

Sig Gene

Current amplifier Ampli

Signal gene

Electro-magnet

Displacement sensor

A

dcdc ASEYMI .....2 1*13

3,4.1e-192602.2Polyéthylène1,4.1e-19280012Nylon4,19.1e-18408,2PU 1%C2,06.1e-18804,8PU 0.5%SiC3,40.1e-18 404,8PU pur

M*31 (m²/V²)Y(Mpa)εrType

Y

εr

Basic energy harvesting on electrostrictive polymers

Need to create a coupling strain/ electrical field

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Current modeling

I: CurrentS : StrainT :StressE : Electrical fieldD : InductionM13 : Electrostriction coefficientY : Young’s modulussE : Compliance coeffεT : Permittivity

A polymer surface (at rest)

A

dcdc ASEYMI .....2 1*13

11123311 .. TsEMS E

13313333 ...2. TEMED T

A field or a polar has to be imposed on the polymer to convert mechanical energy into electrical energy

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Polymers for actuatorsNano-loaded Polymers: are they good actuators?Strain: >20% (larger than muscle)Light (spatial)A trade-off different from ferro-ceramic:High modulus but small strain for ceramics (difficult to transfert the power ! Small modulus but high strain for polymers

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Relaxation when working in the glassy/rubber transition

Not favorable for broadband actuatorsCreep and relaxation effect

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ApplicationsA large number or applications can be developped an probably will since thé Self-powered wireless technology is important nowdays. What scale? (macro-elemts (centimetric scale?) or micro elements based on micro-electronic technologiesFully self-powered systems can be developped but that requires to rethink the whole system (for instance in the health monitoring, thé signal process can’t be based on a Fourier approach…find something as efficient but less consummingVibration control: my feeling is that we can still improve performances in broad-band/ it can also be coupled with active control to end up with a non-bucky systemEA PolymersA competitive technology for actuators (with ceramic most or the thrust is used to compensate thé mechanical margins)Light, easy to make and low cost technologyCan be spread on large surface (compensate for the low coupling)Properties can be tailored by playing with thé fillersNon-linear techniques may be usefull to boost EAP performances in energy harvesting and/or vib damping

Conclusion

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Resonance sharpening

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• Epoxy cantilever with piezo inserts

•Electronic circuit for driving the switching of the voltage sources

• Measurement devices

Resonance sharpening: experimental set-up

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Quality factor augmentation up to 50%

Vibration amplification, and resonance frequency shifting

Non linearity and resonance hysteresis

Energy is fed to the system in this case1

1,5

2

2,5

3

3,5

4

4,5

5

Frequency (Hz)

Displacement (mm)

Open circuit0 V2 V3,5 V5 V7,5 V9 V11,5 V13 V

Resonance sharpening: Experimental results

The driving force is constant!!

11.7 HZ 12.2 Hz

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Les différentes familles de EAP

“Artificial Muscle”

Electrostrictive Polymer

Dielectric Elastomer Dielectric Elastomer a.k.a. a.k.a.

ElectroelastomersElectroelastomers

IPMC

Conducting Polymers

GelsThermal and Others

Nanotubes

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In the case of integrated devices (e.g. MEMS harvester), a particular emphasis should be put on the low voltage level

This low level is a problem for voltage gaps of discrete components (such as the rectifier)

It is possible to limit these effects using particular configurations or techniques:

SSHI-MR

“Thresholdless rectifier’

Vthresh=2VD/m

US-Europe Worshop 81

LGEF-Standard interface:

2

0

2

maxstand

222

0

2

stand

2

2

M

M

L

L

uC

P

uCR

RP

A. Badel, 2005. “Récupération d’énergie et contrôle vibratoire par éléments piézoélectriques suivant une approche non linéaire”.

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-With the parallel SSHI, the voltage inversion is done after the harvesting process, on displacement extrema

maxstandmaxpara

222

0

2

para

1214

PP

uCR

RP ML

L

Guyomar et al., 2005. “Towards energy harvesting using active materials and conversion improvement by nonlinear processing”, IEEE Trans. Ultrason., Ferroelect., Freq. Contr..

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-With the series SSHI, the voltage inversion is done in the same time than the harvesting process, on displacement extrema

maxstandmaxser

222

0

22

ser

11

11214

PP

uCR

RP ML

L

Taylor et al., 2001. “The Energy Harvesting Eel: A Small Subsurface Ocean/River Power Generator”, IEEE J. Oceanic Eng..

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2

2SECE 0 stand max

04 4c M cuP f u P

C

Lefeuvre et al., 2005. “Piezoelectric Energy Harvesting Device Optimization by Synchronous Electric Charge Extraction”, J. Intell. Mater. Syst. Struct.

In SECE the harvested energy is independent from the load

2 2

SECE 22

824

M MCF

M

k Q FPCk Q

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An intermediate capacitor can be used to decouple the extraction stage from the storage stage (DSSH):

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Harvesting on low level vibration

Smooth the harvesting process (higher availability of low level vib)

Harvesting on high frequency / low amplitude vibrations

Little energy per cycle but the number of cycles/seconds is high………….significant power

Piezoelement are sensitive to strain (not to the strain rate)…Voltage in range of diode gap …......… the standard harvesting techniques are not effective

Voltage transformer approach

The voltage gap is strongly reduced (divided by the transformer ratio)

The transformer increases the output voltage (better compatibility with electronic circuits)

Power management for low level Vibrations

The voltage gap is strongly reduced (divided by the transformer ratio)

The transformer increases the output voltage (better compatibility with electronic circuits)

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Harvested energy versus displacement

0 5 10 15 20 250

100

200

300

400

Displacem ent m agnitude (m )

Maximal harvested

powe

r (W)

Experim ental results

0 10 200

10

20

0 5 10 15 20 250

100

200

300

400

Displacem ent m agnitude (m )

Maximal harvested

powe

r (W)

Theoretical predictions

StandardSeries SSHISSHI-M R0 10 200

10

20

Experimental maximal output power as a function of the displacement magnitude

Displacement threshold for Standard and SSHI

Additional mass to lower the resonant frequency (1KHz)

The piezo generator is driven by a shaker A standard transformer is used in the experiment

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102 104 1060

200

400

Load value

Harv

este

dPo

wer

( W)

Experimental results

102 1040

20

40

102 104 1060

200

400

Load value

Harv

este

dPo

wer ( W

)

Theoretical predictions

102 104

0

20

40

StandardSeries SSHISSHI-MR

StandardSeries SSHISSHI-MR

Parameters Value

Vibration frequency f0

1kHz

Force factor 8.3 mN.V-1

Diode threshold voltage VD

0.23 V

Clamped capacitance C0

312.5 nF

Inversion factor

0.33 for the series SSHI0.52 for the SSHI-MR

Transformer ratio m 22

Harvested energy versus load value

Gain of 60 compared to standard and 30 compared to SSHI

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Without Control DC

V(t)

u(t) Vrect(t)Vrect(t)u(t)

V(t)

Forced harmonic strain (experimental)

R=130k P=1.8mW R=560k P=8.4mW

SSH Control DC

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V(t)

u(t)

Vrect(t)

W(t)

u(t)

Vrect(t)

V(t)

W(t)

Pulsed power response (experimental)

SSH Control DC

Without control DC

SSH control DC

Ratio

Harvested Energy

5.6mJ 7.6mJ 1.35

Harvesting time 6s 2s 0.33Max power 3mW 9mW 3

Standard DC

For pulsed vibrations (finite energy), the transfer from mechanical to electrical energy damps the signal and limits the conversion

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0

0.2

0.4

0.6

0.8

1

1/ W ithout control 2/ Switch on each extremum 3/ Probabilistic approach with PSW=0.1

AE

1 2 3

Control Law AEdB AudB


-4.89 dB -3.81 dB

Probabilistic – PSW=0.1

-6.50 dB -7.67 dB

91

Pulsed excitation – Vibration control simulation results (2)

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Control Law AEdB AudB


-4.27 dB -2.96 dB

Probabilistic – PSW=0.1 -6.32 dB -8.49 dB0

0.2

0.4

0.6

0.8

1

1/ W ithout control 2/ Switch on each extremum 3/ Probabilistic approach with PSW=0.1

AE

1 2 3

White noise excitation – Vibration control simulation results (2)

Evaluation of macroscopic polarization and actuation abilities of electrostrictive dipolar polymers...

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