Elec6076 wireless sensor networks - tan

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Elec6076 wireless sensor networks - tan

  1. 1. Tristan Brillet de Cande – tbdc1g10@soton.ac.uk ELEC6076
  2. 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 versatility2 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  3. 3. Store Distribute Scavenge Standards consumption Conclusion3 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  4. 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 NiCdbattery air batterychemistries chemistriesEnergy 3780 2880 1200 Energy 1080 860 650(J/cm3) (J/cm3) 4 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  5. 5. Available In developmentEnergy 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. 6. Electromagnetic Pow er Distribution Wires, acoustic, lightElectromagnetic Power DistributionCommon but ineffective 6 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  7. 7. Electromagnetic Power Distribution Wires, acoustic, lightWire, acoustic, lightAll of them are inappropriateWired: No wireless sensor network anymoreAcoustic wave: Too low power density.Light => laser: Too complex and not costeffective 7 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  8. 8. • Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • Vibrations8 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  9. 9. • Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • VibrationsPhotovoltaicOutput voltage we want/Stable DC Voltage/Simple conditioning to the batteryBut need to control the charging profile through more electronic => moreconsumption 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. 10. • Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • Vibrations k is the thermal conductivity of the material L is the length of the material10 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  11. 11. • Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • VibrationsHuman 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. 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. 13. • Photovoltaic • Temperature gradients • Human power • Wind • Pressure variations • VibrationsPressure variationsCould 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. 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 ratio1. 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. 15 Tristan Brillet de Cande – ELEC6076 – Wireless Sensor Networks
  16. 16. The widespread development of WSNs in the future depend onthe development of small, cheap and long life node power sourcesThere won’t be one unique alternative power source which willsolve all WSN’s power issues, but many attractive and creativesolutions do exist that can be considered on an application-by-application basisLow power systems are absolutely necessary16 Nadège Barrage – ELEC6076 – Wireless Sensor Networks
  17. 17. Internet: http://microstrain.com/white/Wilson-chapter-22.pdf http://nesl.ee.ucla.edu/fw/documents/reports/2007/Powe rAnalysis.pdf17 Nadège Barrage – ELEC6076 – Wireless Sensor Networks
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