motion energy harvesting: myths & opportunities seminar, sept 24, 2007 motion energy harvesting:...

NPL Seminar, Sept 24, 2007

Motion Energy Harvesting: Myths & Opportunities

Eric M. Yeatman

Department of Electronic & Electrical EngineeringImperial College London


Energy Scavenging

• Collecting energy available in the environment, wirelessly

• Wireless means freedom, mobility, simplicity• Wireless doesn’t just mean data!


Let’s get rid of this:


And this:


How Much Power?

Power station 100 megawatts

House 10 kilowatts

Person, lightbulb 100 watts

Laptop, heart 10 watts

Cellphone 1 watt

Wristwatch, sensor node 1 microwatt

Cellphone signal 1 nanowatt


Main Application Area: Wireless Sensor Nodes• self-contained and self-powered, mm-scale• large numbers of nodes, must be low maintenance

Biomedical Application: Body Sensor Networks• low data rates, short transmission range• on body or implanted


1 cc wireless sensor node, IMEC


Sensor Node Power Requirements:

• Sensing Element

• Signal Conditioning Electronics

• Data Transmission


Sensing Element

Simple signals - temperature, pressure, motion – require electrical power above thermal noise limit.

NT ≈ 10-20 W/Hz

For most applications, this is negligible.

For some, e.g. video, power is very high.


Signal Conditioning

Likely principal function: A/D Converter

Recent results: Sauerbrey et al., Infineon (’03)

Power < 1 μW possible for low sample rates!


16 bits/min.1 / min.16 bitsBlood oxygen

16 bits/min.1 / min.16 bitsTemperature

32 bits/min.1 / min.16 bitsBlood pressure

80 bits/min.10 / min.8 bitsHeart rate

Data RateRateDepthSignal

Data Transmission: Required Rates

Conclusion: average rates at or below 1 bit/s sufficient for many sensor types.


Data Transmission: Required Power

Conclusions:

Power independent of bit-rate for low bit-rate

-40 dBm (0.1 μW) feasible for body-scale transmission range

1000100101

50

40

30

20

10

0

-10

-20

-30

-40

-50

Range (m)

Tran

smit

Pow

er (d

Bm

)

Ideal free-space propagation

Typical indoorLoss exponent(3.5)

Figure: F. Martin, Motorola


Estimated Total Power Needs

• Peak power 1 – 100 uW

• Average power can be below 1 uW

Batteries: Present Capability

• 1 μW⋅yr for 0.1 cm3 battery feasible

• Not easy to beat!

• Useful energy reservoir for energy scavenging


Fuel-Based Power Sources

• Energy density much higher than for batteries, ≈ 10 kJ/ cm3

• Technology immature, fuel cells most promising

Micro fuel cell, Yen et al.Fraunhofer Inst.


Magnetic (induction)Piezoelectric Electrostatic

KineticVolume flow (liquids or gases)Movement and vibration

Magnetic induction (induction loop)Antennas

Magnetic and Electro-magnetic Electro-magnetic waves

Thermoelectric or Heat EngineThermal Temperature gradients

Solar CellsLight Ambient light, such as sunlight

Conversion MechanismEnergy Source

Energy Scavenging : Sources


Solar Cells

• highly developed

• suited to integration

• high power density possible:

100 mW/cm2 (strong sunlight)

• but not common:

100 μW/cm2 (office)

• Need to be exposed, and oriented correctly

Solar cell for Berkeley Pico-Radio


Heliomotes, UCLA


Thermo-Electric

• need reasonable temperature difference (5 – 10°C) in short distance

• ADS device ≈ 10 μW for 5°C

• even small ΔT hard to achieve

Heat engine, Whalen et al,

Applied Digital Solutions


US Dept of Energy


Seiko Thermic


Ambient Electromagnetic Radiation

Graph: Mantiply et al.

≈ 10 V/m needed for reasonable power: not generally available


Body Sensor Nodes : Power Scavenging

• Light not generally available

• Temperature differences small

• Motion sources attractive

• Body motion or organ motion (heart, lungs)

• Inertial scavenging safest method


Motion Energy Scavenging

• Direct force devices

• Inertial devices


Direct Force: Heel Strike

Heel strike generator: Paradiso et al, MIT


Body Motion Power Sources

• Low and varying frequency (1 – 10 Hz)

• Large variation in amplitude

Body Sensor Size Limits

• Below 1 cc desirable

• Less for implanted nodes


m

zo

y = Y cos( t)o ω

damper implements energy conversion

Available Power from Inertial Scavengersassume:• source motion amplitude Yo and frequency ω• Proof mass m, max internal displacement zo


m

zo

y = Y cos( t)o ω

damper implements energy conversion

Available Power from Inertial Scavengers

• Peak force on proof mass F = ma = mω2Yo

• Damper force < F or no movement

• Maximum work per transit W = Fzo = mω2Yozo

• Maximum power P = 2W/T = mω3Yozo/π


0.1

1

10

100

1 10 100frequency (Hz)

pow

er (u

W)

How much power is this?

Plot assumes:

• Si proof mass (higher densities possible)

• max source acceleration 1g (determines Yo for any f)

10 x 10 x 2 mm

3 x 3 x 0.6 mm


Performance Trends – progress with time

0

0.02

0.04

0.06

0.08

0.1

0.12

1996 1998 2000 2002 2004 2006

year

norm

alis

ed p

ower

electromagnetic electrostatic piezo



0

0.02

0.04

0.06

0.08

0.1

0.12

1996 1998 2000 2002 2004 2006

year

norm

alis

ed p

ower


Imperial

UC Berkeley



0

0.02

0.04

0.06

0.08

0.1

0.12

1996 1998 2000 2002 2004 2006

year

norm

alis

ed p

ower

electromagnetic electrostatic piezo • There is an upward trend

• No particular correlation of performance with transducer type

• All of the normalised power values are low – there is room for improvement


Performance Trends – as a function of volume

0

0.02

0.04

0.06

0.08

0.1

0.12

0.01 0.1 1 10

volume (cc)

norm

alis

ed p

ower


• There is an upward trend – easier to make a large device than a small device

• No particular correlation of device volume with transducer type


Performance Trends – as a function of frequency

0

0.02

0.04

0.06

0.08

0.1

0.12

1 10 100 1000

frequency (Hz)

norm

alis

ed p

ower

electromagnetic electrostatic piezo • Downward trend –parasitic damping becomes more dominant with increased frequency

• No particular correlation of transducer type with operating frequency


How does this compare to applications?

Plot assumes:

• proof mass 10 g/cc

• source acceleration 1g

0.001

0.01

0.1

1

10

100

1000

10000

100000

0.01 0.1 1 10 100 1000

volume (cc)

pow

er (m

W)

f = 1 Hzf = 10 Hz


How does this compare to applications?

Plot assumes:

• proof mass 10 g/cc

• source acceleration 1g

0.001

0.01

0.1

1

10

100

1000

10000

100000

0.01 0.1 1 10 100 1000

volume (cc)

pow

er (m

W)

f = 1 Hzf = 10 Hz

Sensor node

watch

cellphone

laptop


Implementation Issues: Resonance

Why use resonant device?• Allows use of full internal range for low Yo

Why not use resonant device?• For body sensor application, Yo > zo likely • Low resonant frequency hard to achieve for small device• Varying source frequency bad for resonant devices


Response Comparison: Harmonic Drive

Resonant devices better for large generators / small displacements, but only if operated near resonance

Non-resonant good for high displacements, wide input frequency ranges


Response Comparison: True Body Motion

• Non-resonant device wins for small generators

• Data obtained in collaboration with ETH Zurich (T. von Buren)


Implementation Issues: Mechanism

Piezoelectric?• Difficult integration of piezo material• Possible leakage time issues for low frequency use

Electromagnetic?• Needs high dφ/dt to get damper force (φ = flux)• dφ/dt = (dφ/dz )(dz/dt )• Low frequency (low dz/dt) needs very high flux gradient• Efficiency issues (coil current)


Typical Inertial Generators

Piezoelectric

Ferro solutionsWright et al, Berkeley


Typical Inertial Generators

Magnetic

Southampton U. CUHK


Implementation Issues: Mechanism

Electrostatic?• Simple implementation, no field gradient problem• Damping force can be varied via applied voltage• But needs priming voltage (or electret)


Chosen Approach: Constant Charge

Input phase Output phase

inputinputVCQ = outputoutputVCQ =

inputoutput

inputouput V

CC

V =

222

21

21

21

outputoutputinputinputouputoutput VCVCVCE ≈−=Δ

inputoutput VV >>

∴

Q


Electro-mechanical Design

Mass

Top plate (silicon)

Base plate (quartz)

Mass

Mass

Input phase

Output phase

Gap

COM

Vout

Vin

Polyimide suspension

Buck converter


Assembled generator Detail of deep-etched moving plate

Prototype MEMS Device


Device Operation

posi

tion

time

time

trajectory of moving plate

volta

ge

t2 t3t1

voltage on moving plate

upperlimit

lower limit

moving plate/ proof mass

fixed plate

discharge contact

charging contact

Output > 2 μW


Power Conditioning Circuit: Challenges

Power convertorefficiency is highly sensitive to parasitics!


Other Options: Rotating Mass

Example #1: traditional self-winding watch


Example #2: Seiko Kinetic


Large Inertial Generators

Backpack: U Penn

• 7 watts!


Large Scavenging Applications

East Japan Railway Co.

• Energy scavenging ticket gates


How else can rotating motion be used in inertial generation?

Proposal: Gyroscopic power generation


Gyroscopic power generationCan also be implemented in silicon!

Georgia Tech / u Mich


Motion Energy Harvesting for Sustainability• Power levels modest – energy saving not key motivator

• Human powered – mW levels likely practical limit

• Battery elimination: yes, except need local storage

• Pervasive sensing: major possibilities for efficient buildings, machines, processes


Motion Energy Harvesting for Sustainability• Power levels modest – energy saving not key motivator

• Human powered – mW levels likely practical limit

• Battery elimination: yes, except need local storage

• Pervasive sensing: major possibilities for efficient buildings, machines, processes

• [ plug: Imperial College Centre for Pervasive Sensing ]


Interaction with Energy Source• Typical energy scavenging implies no significant effect on

source

• i.e. effectively infinite source, power limited only by scavenger

• Otherwise not really “scavenging”

• In practice, loading of source at least power level extracted

• Alternative: collecting wasted power

• Key example: combined heat and power (CHP)


Conclusions• Power levels in the microwatt range are enough for many

wireless sensor nodes

• Inertial devices driven by body motion can achieve these levels

• Nonlinear devices are suitable for low and variable input frequencies, and for high displacement to device size ratios

• Prototype devices have been demonstrated at useful power levels

• Future challenges include associated power electronics


Thanks to:

at Imperial:Andrew Holmes, Paul Mitcheson, Tim Green

others:Joe Paradiso, MIT

Paul Wright, UC BerkeleyThomas von Büren, ETH Zurich

Contact me:[email protected]

www.imperial.ac.uk/ee

motion energy harvesting: myths & opportunities seminar, sept 24, 2007 motion energy harvesting:...

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