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Tristan Brillet de Cande – tbdc1g10@soton.ac.uk   ELEC6076
• Scaling down in size and cost of CMOS electronics has
  far outpaced the scaling of energy density in batteries
• Battery are now quite big and expensive
• Limits the lifetime of the device
• And its versatility




2          Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
Store
    Distribute
    Scavenge
    Standards consumption
    Conclusion




3         Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
Available
                                                                  In development



 Energy reservoirs: Available
 • Primary batteries are used in Wireless
   networks
 • Secondary batteries could be used in
   2 cases:
     • Recharged by a primary battery
        => too expensive to use both on
        each node
     • Recharged by scavenging devices
        (solar cell, wind mill, etc)

Primary       Zinc-    Lithium Alkaline             Secondary Lithium NiMHd NiCd
battery       air                                   battery
chemistries                                         chemistries
Energy        3780     2880          1200           Energy            1080        860   650
(J/cm3)                                             (J/cm3)
   4             Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
Available
                                                                   In development



Energy reservoirs: In development
    • Micro scale batteries
    • Micro fuel cells
    • Ultracapacitors
    • Microheat engines
    • Radioactive power sources
      •
      •   loworenergyjoule, highdensities
          Extremely high energy energy density,
          2D cost per density
          Good lifetime
          High 3D structure
      •
      •   abundant availability, for 2d but higher
          Simpleenergy density storability, and
          Short charging time
          Better
          Serious health hazard
      •
      •   ease of density for the 3d
          power transport.
          High power density
          High temperature required
          highly political and controversial topic.
      •
      •   Long bad to reduce because of temperature )
          Very lifetime still atatheorders of (4 X 10-6
          Energy density
          Difficult efficiency 1 tomicrofabricated
                       maintain 2 moment
      •   Complex that contain aqueous
          magnitude lower than batteries
          structure
      •   Limited in downsizing Material U238
          electrolyte                                  Ni63            Si32        Sr90      P32
      •   Huge heat rejecting due the low 2.23x1 1.6x108
          Complex                   Energy                             3.3x108     3.7x108   127x109
      •   efficiency (10%). in the supply => 010
          Non uniformities          (J/cm3)   bad
          reliability and cycle life

  5               Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
Electromagnetic Pow
                                                               er Distribution
                                                               Wires, acoustic, light


Electromagnetic Power Distribution
Common but ineffective




  6           Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
Electromagnetic Power
                                                                 Distribution
                                                                 Wires, acoustic, light


Wire, acoustic, light
All of them are inappropriate
Wired: No wireless sensor network anymore

Acoustic wave: Too low power density.

Light => laser: Too complex and not cost
effective




  7             Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
•   Photovoltaic
    •   Temperature gradients
    •   Human power
    •   Wind
    •   Pressure variations
    •   Vibrations




8           Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
•   Photovoltaic
                                                      •   Temperature gradients
                                                      •   Human power
                                                      •   Wind
                                                      •   Pressure variations
                                                      •   Vibrations




Photovoltaic

Output voltage we want/Stable DC Voltage/Simple conditioning to the battery

But need to control the charging profile through more electronic => more
consumption

 Conditions      Best technology          Density of             Efficiency       Power available
                                          light

 Day light       Single crystal           100 mW/cm3             15%              15 mW/cm2
 (indoors)       silicon solar cells
 Artificial      Thin film         100 μW/cm2                    10%              10 μW/cm2
 light           amorphous silicon
 (outdoors)

9              Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
•    Photovoltaic
                                             •    Temperature gradients
                                             •    Human power
                                             •    Wind
                                             •    Pressure variations
                                             •    Vibrations




                                   k is the thermal conductivity of the material
                                   L is the length of the material




10   Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
•   Photovoltaic
                                                      •   Temperature gradients
                                                      •   Human power
                                                      •   Wind
                                                      •   Pressure variations
                                                      •   Vibrations




Human power                                  “Watch working with
• 10.5 MJ of energy per day (121 W)           the kinetic energy a
• Most energy rich and most easily           of swinging arm and
  exploitable source occurs at the            the heat flow away
  foot during heel strike and in the          from the surface of
  bending of the ball of the foot                   the skin”

                                                “MIT research has
 Impractical and not cost efficient                  lead to the                  How to get the power
 to wind up each node                             development of                  from the shoe to the
                                                 piezoelectric shoe                  wireless sensor
                                                 inserts capable of                network?
                                               producing an average
                                               of 330 μW/cm2 while
                                               a person is walking. ”

11             Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
•   Photovoltaic
                                                      •   Temperature gradients
                                                      •   Human power
                                                      •   Wind
                                                      •   Pressure variations
                                                      •   Vibrations




                                                            potential power from moving air
 Wind


• Power densities from air velocity
  are quite promising
• Hard to get it small
• No work has been done on it yet




                                                  P is the power
                                                  ρ is the density of air (1.22 kg/m3)
                                                  A is the cross sectional area
                                                  v is the air velocity

 12            Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
•   Photovoltaic
                                                     •   Temperature gradients
                                                     •   Human power
                                                     •   Wind
                                                     •   Pressure variations
                                                     •   Vibrations




Pressure variations
Could work with
• a change of atmospheric conditions
         ΔE is the change in energy                Metric                        Theoretical power
         ΔP is the change in pressure                                            density/day
         V is the volume                           Difference in                 7.8 nW/cm3
                                                   atmospheric
• And a change of temperatures                     conditions
           m is mass of the gas                    Difference of                 17 μW/cm3
           R is gas constant                       temperatures
           ΔT is the change in temperature



     No work has been done on it yet.


13            Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
•    Photovoltaic
                                                                     •    Temperature gradients
                                                                     •    Human power
                                                                     •    Wind
                                                                     •    Pressure variations
                                                                     •    Vibrations




     Vibrations
     There are vibrations everywhere from 60 – 200 Hz
     and 1 – 10 m/s2
      “Example:
      Piezoelectric P is the power output 3mass
                    converter of 1 cm
                    m is the oscillating proof
      P= 200 μW A is the acceleration magnitude of the input vibrations
      Vibration : A=m2.25 frequency ofdamping ratio
                    ω is the m/s2, f=120 driving vibrations
                    ζ is the mechanical
                                           the Hz”

                       ζe is an electrically induced damping ratio

1. P is proportional to the
   oscillating mass of the
   system.
2. P is proportional to the
   square of the
   acceleration amplitude
   of the input vibrations.
3. P is inversely
   proportional to
   frequency                            Power density vs Vibration amplitude
     14                Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks





15   Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
The widespread development of WSNs in the future depend on
the development of small, cheap and long life node power sources

There won’t be one unique alternative power source which will
solve all WSN’s power issues, but many attractive and creative
solutions do exist that can be considered on an application-by-
application basis

Low power systems are absolutely necessary


16         Nadège Barrage – ELEC6076 – Wireless Sensor Networks
Internet:
 http://microstrain.com/white/Wilson-chapter-22.pdf

 http://nesl.ee.ucla.edu/fw/documents/reports/2007/Powe
   rAnalysis.pdf




17         Nadège Barrage – ELEC6076 – Wireless Sensor Networks
18

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Elec6076 wireless sensor networks - tan

  • 1. Tristan Brillet de Cande – tbdc1g10@soton.ac.uk ELEC6076
  • 2. • Scaling down in size and cost of CMOS electronics has far outpaced the scaling of energy density in batteries • Battery are now quite big and expensive • Limits the lifetime of the device • And its versatility 2 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 3. Store Distribute Scavenge Standards consumption Conclusion 3 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 4. Available In development Energy reservoirs: Available • Primary batteries are used in Wireless networks • Secondary batteries could be used in 2 cases: • Recharged by a primary battery => too expensive to use both on each node • Recharged by scavenging devices (solar cell, wind mill, etc) Primary Zinc- Lithium Alkaline Secondary Lithium NiMHd NiCd battery air battery chemistries chemistries Energy 3780 2880 1200 Energy 1080 860 650 (J/cm3) (J/cm3) 4 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 5. Available In development Energy reservoirs: In development • Micro scale batteries • Micro fuel cells • Ultracapacitors • Microheat engines • Radioactive power sources • • loworenergyjoule, highdensities Extremely high energy energy density, 2D cost per density Good lifetime High 3D structure • • abundant availability, for 2d but higher Simpleenergy density storability, and Short charging time Better Serious health hazard • • ease of density for the 3d power transport. High power density High temperature required highly political and controversial topic. • • Long bad to reduce because of temperature ) Very lifetime still atatheorders of (4 X 10-6 Energy density Difficult efficiency 1 tomicrofabricated maintain 2 moment • Complex that contain aqueous magnitude lower than batteries structure • Limited in downsizing Material U238 electrolyte Ni63 Si32 Sr90 P32 • Huge heat rejecting due the low 2.23x1 1.6x108 Complex Energy 3.3x108 3.7x108 127x109 • efficiency (10%). in the supply => 010 Non uniformities (J/cm3) bad reliability and cycle life 5 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 6. Electromagnetic Pow er Distribution Wires, acoustic, light Electromagnetic Power Distribution Common but ineffective 6 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 7. Electromagnetic Power Distribution Wires, acoustic, light Wire, acoustic, light All of them are inappropriate Wired: No wireless sensor network anymore Acoustic wave: Too low power density. Light => laser: Too complex and not cost effective 7 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 8. Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • Vibrations 8 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 9. Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • Vibrations Photovoltaic Output voltage we want/Stable DC Voltage/Simple conditioning to the battery But need to control the charging profile through more electronic => more consumption Conditions Best technology Density of Efficiency Power available light Day light Single crystal 100 mW/cm3 15% 15 mW/cm2 (indoors) silicon solar cells Artificial Thin film 100 μW/cm2 10% 10 μW/cm2 light amorphous silicon (outdoors) 9 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 10. Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • Vibrations k is the thermal conductivity of the material L is the length of the material 10 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 11. Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • Vibrations Human power “Watch working with • 10.5 MJ of energy per day (121 W) the kinetic energy a • Most energy rich and most easily of swinging arm and exploitable source occurs at the the heat flow away foot during heel strike and in the from the surface of bending of the ball of the foot the skin” “MIT research has Impractical and not cost efficient lead to the How to get the power to wind up each node development of from the shoe to the piezoelectric shoe wireless sensor inserts capable of network? producing an average of 330 μW/cm2 while a person is walking. ” 11 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 12. Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • Vibrations potential power from moving air Wind • Power densities from air velocity are quite promising • Hard to get it small • No work has been done on it yet P is the power ρ is the density of air (1.22 kg/m3) A is the cross sectional area v is the air velocity 12 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 13. Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • Vibrations Pressure variations Could work with • a change of atmospheric conditions ΔE is the change in energy Metric Theoretical power ΔP is the change in pressure density/day V is the volume Difference in 7.8 nW/cm3 atmospheric • And a change of temperatures conditions m is mass of the gas Difference of 17 μW/cm3 R is gas constant temperatures ΔT is the change in temperature No work has been done on it yet. 13 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 14. Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • Vibrations Vibrations There are vibrations everywhere from 60 – 200 Hz and 1 – 10 m/s2 “Example: Piezoelectric P is the power output 3mass converter of 1 cm m is the oscillating proof P= 200 μW A is the acceleration magnitude of the input vibrations Vibration : A=m2.25 frequency ofdamping ratio ω is the m/s2, f=120 driving vibrations ζ is the mechanical the Hz” ζe is an electrically induced damping ratio 1. P is proportional to the oscillating mass of the system. 2. P is proportional to the square of the acceleration amplitude of the input vibrations. 3. P is inversely proportional to frequency Power density vs Vibration amplitude 14 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 15.  15 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  • 16. The widespread development of WSNs in the future depend on the development of small, cheap and long life node power sources There won’t be one unique alternative power source which will solve all WSN’s power issues, but many attractive and creative solutions do exist that can be considered on an application-by- application basis Low power systems are absolutely necessary 16 Nadège Barrage – ELEC6076 – Wireless Sensor Networks
  • 18. 18