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Energy Harvesting Technologiesfor Wireless Sensors

Andrew S Holmes

p ca an em con uc or ev ces roup

Department of Electrical and Electronic Engineering

Imperial College London

17th World Micromachine Summit1



Wireless Sensor Applications

Wireless sensors very well established in certain market sectors e.g. domestic

fuel monitoring

Huge opportunity for expansion in other areas such as:

• Machine/process monitoring

• Remote monitoring

- inaccessible/hostile environments

• Intelligent buildings

- , ,

• Medical telemetry

- continuous, unobtrusive monitoring

• Ubiquitous computing

- ad hoc sensor networks

•

- ‘smart dust’ concept 1 cc wireless sensor node [IMEC]




Power Sources for Wireless Sensors

Short term solutions inevitably based on chemical batteries

• High energy density (~2000 J/cm3 or ~500 mA.hr/cm3 at 1V)

• Limited life before recharging or replacement

• Disposal/recycling problematic

Fuel-burning power sources

• Very high energy density

• Technolo ies still some wa from maturit

• Limited life before refuelling, as for batteriesMeOH fuel cell

[Fraunhofer Inst.]MEMS gas turbine stage

[MIT]

nergy arves ng

• Long term storage capacity no longer an issue

• Low power density in most casese.g. cm or so ar ce n o ce env ronmen

• Intermittent supply in many cases so likely to

be used with battery/capacitor back-upPico Radio solar cell

Vibration-driven generator

1 mW @ 0.25g rms




Energy Harvesting Technologies

Energy Source Conversion Mechanism

Electromagnetic radiation

Ambient light Photovoltaic cell

Heat

Temperature gradients Thermoelectric device or

ea eng ne

Kinetic energy

Movement and vibration Electrostatic

Volume flow (of liquids or gases) Magnetic (induction)

Piezoelectric

Technology of choice will depend strongly on application environment,

average power and duty cycle requirements




Motion-driven Microgenerators




Inertial Energy Harvesters

• Single point of attachment to moving “host” e.g. machine, person…

• Peak inertial force on proof mass: F = ma = m2Ywhere a is the peak acceleration applied by the host

• Damper force < F or no internal movement ax mum wor per rans : zo = m ozo

Maximum harvested power: P = 2W/T m3Yozo/

zo

m o

damper implements energy conversion




How Much Power is Available?

Plot assumes:

• cubic device with mass occupying half of

1000

10000

,

• const. source acceleration amplitude (2Y0)

of 10 m/s2 (equiv to Y0

= 25 cm at 1 Hz)

• roof mass with densit 20 /cc

10

100

o w e r ( m W )

f = 1 Hz

f = 10 Hz sensor node *

0.01

0.1 watchcellphone

0.001

0.01 0.1 1 10 100 1000

volume (cc)

* For the sensor node, we are assuming a simple physical sensor (e.g. temp, pressure or motion)

with short-range (e.g. within room) wireless link and low data-rate




Comparison of Architectures

= excitation frequency

Normalised axes:

resonan requency

(resonant devices)

Z l /Y 0 = mass travel range

excitation amplitude

Power = P (Watts)

m 3 Y 0 2

c

Z l /Y 0

• Resonant devices better for large generators / small displacements, operated

near resonance• Non-resonant good for large displacements, wide input frequency ranges

Mitcheson P.D., Green T.C., Yeatman E.M., Holmes A.S., “Architectures for vibration-driven

micropower generators”, IEEE/ASME J. Microelectromechanical Systems 13(3), (2004), 429-440.




Machine Powered Applications

• Resonant vibration-driven generators aimed at machine/process monitoring

are the most highly developed

• Synchronous electrical machines have predictable vibration frequency,

making them ideal for resonant energy harvesters

• , . .

PMG17PMG17 from Perpetuum Ltd

Resonant generator tuned to 2nd harmonic of mains frequency – 100 or 120 Hz

4.5 mW output power (rectified DC) at 0.1g

acceleration




Human Powered Applications

Excitations are slow, large in amplitude and

irregular compared to those generally

• Non-resonant device can win at small generator sizes• Data obtained in collaboration with ETH Zurich (T. von Buren)

von Büren T., Mitcheson P.D., Green T.C., Yeatman E.M., Holmes A.S., Tröster G., “Optimization of

inertial micropower generators for human walking motion”, IEEE Sensors Journal, 6(1), (2006), 28-38.




Non-resonant Device developed at Imperial

Discharge contact

Model: MEMS parallel plate capacitor implementation:

on op p a e

Moving capacitor plate / mass

plate on baseplate

Pre-chargingcontact

Generation cycle:

• Capacitor is pre-charged when mass is at bottom (max capacitance)

• Under sufficiently large (downward) frame acceleration, capacitor plates separate

at constant charge , and work is done against electrostatic force stored

electrostatic energy and plate voltage increase

• Charge is transferred (at higher voltage) to external circuit when moving plate

reaches position of max displacement




Energy Yield per Cycle

Separation

Input phase Output phase

input input V C Q output output

V C Q

input

input

ouput V C

C V

Generated ener :

222 1

)(

111

output output input output output output input input ouput output V C V V V C V C V C E

input output V V




Measured Performance

shaker generator

• o age pro e as npu mpe ance

>1012 and dynamically measures

voltage on capacitor

voltage probe

• Net power in this experiment: 2.2 μW




Motion-driven Harvesters – are they any good?

1.6%

1.8%

EM

ES

Volume Figure of Merit defined

as:

1.2%

1.4%PZ

FoM V = Au Vol 4/3 Y 0 3 1

16

0.6%

0.8%

1%

F o M V

power to that of idealised

generators on slide 7

0.2%

0.4%

achieved only about 2%

Better devices have emerged

2000 2002 2004 2006 20080

Publication Year

,

to go...

Main issues are: 1 dam in /transduction – need to im lement stron er dam ers 2 ower

Mitcheson P.D., Yeatman E.M., Kondala Rao G., Holmes A.S., Green T.C., “Energy harvesting from human

and machine motion for wireless electronic devices”, Proc. IEEE 96 9 , 2008 , 1457-1486.

conversion electronics – difficult to make efficient; (3) adaptive operation




Flow-driven Microgenerators




Energy Scavenging from Air Flow

Basic concept:

wind turbines on a

smaller scale

(cm-scale or smaller)

x rac ne c energy

from air flow

K.E. per unit vol in flow = ½V2

K.E. per sec crossing swept area is:

= 2 = 3 100

1000

10000100000

( m W )

CP = 0.1

Betz limit (CP = 0.59)

For 1 cm-dia disc:

ava

Actual output power is:

P = ½AV3CP 0.01

0.1

1

10

O

u t p u t p o w e r

Land vehicle

Flight vehicle

where CP = power coefficient 0.0001

0.001

0.1 1 10 100 1000

Flow speed (m/sec)

HVAC duct




2-cm dia. Device developed at Imperial

• Ducted turbine with integrated axial-flux

permanent magnet generator

• mW output power levels

• Starts at low flow speeds (~3 m/s)

• Applications in HVAC duct sensing and

gas pipeline monitoring

5

6

7

e r ( m W )

3

4

r o

u t p u t p o w

speed

10.0 m/s

0

1

0 1000 2000 3000 4000 5000 6000

G e n e r a t

7.0 m/s

8.0 m/s

9.0 m/s

6.0 m/s


Rotation spe ed (RPM)



Comparison with other Flow-driven Harvesters

• Small flow-driven devices are expected to perform relatively poorly because

of high viscous losses

• Small turbines also suffer from relatively large clearances and bearing

losses

10000

100

1000

/ c m ^ 2 )

Betz lim itCp = 0.1Federspiel (2003), A = 81 sq.cmRancourt (2007), A = 13.9 sq.cmMyers (2007), A ~ 317 sq.cmHolmes (2009), A = 3.14 sq.cm

m-sca e pro o ype ev ces o

date have struggled to reach

Cp ~ 0.1

0.1

1

d e n s i t y

( mever e ess, use u m

power levels can begenerated because available

ower in flow is si nificant

0.0001

0.001

0.01

P o w e

even at modest flow speeds

Duct sensing applications

look uite viable even with0.1 1 10 100

Flow speed [m/sec]current devices

Bansal A., Howey D.A., Holmes A.S., “Cm-scale air turbine and generator for energy scavenging from

”


- , . , , , , - , . - .



HVAC Duct Sensor Concept

“Spider” mounted

ns e uc

Sensor arrayDistributed network of wireless sensors

with peer-to-peer communication to relay

Generator /

Transceiver

Monitoring of:

• Air flow and tem for HVAC control

• Air-quality e.g. RH; CO2, Ammonia, VOCs




ummary

o on- r ven energy arves ers are s per orm ng a a eve some

way below what is theoretically achievable

Current performance is adequate for some important applications such

as machine monitoring, and commercial solutions are available

Improvements in performance will be required before harvesting power

Flow-driven devices at cm-scale also have relatively low conversion

efficiencies, but the available power in the flow is such that duct sensing

applications appear viable

17th World Micromachine Summit



Acknowledgements

Motion-driven Generators:

r c ea man

Paul Mitcheson

Tim GreenPeng Miao (now with Oxford Instruments)

Bernard Stark (now with University of Bristol)

Flow-driven Generators:Keith Pullen (now with City University, London)

Anshu Bansal

David Howey




Contact

Andrew S Holmes

Professor of Micro Electro Mechanical Systems

Optical and Semiconductor Devices GroupDepartment of Electrical and Electronic Engineering

Imperial College London

Exhibition Road London SW7 2BT UK

Tel: +44 (0)20 7594 6239

Email : [email protected]

Web: http://www3.imperial.ac.uk/opticalandsemidev


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