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Ting Zhu, Yu Gu , Tian He, Zhi -Li Zhang

eShare : A Capacitor-Driven Energy Storage and Sharing Network for Long-Term Operation( Sensys 2010). Ting Zhu, Yu Gu , Tian He, Zhi -Li Zhang Department of Computer Science and Engineering, University of Minnesota, Twin Cities Presenter: Junction Date: 2010.10.28. Outline. Motivation

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Ting Zhu, Yu Gu , Tian He, Zhi -Li Zhang

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  1. eShare: A Capacitor-Driven Energy Storage and Sharing Network for Long-Term Operation(Sensys 2010) Ting Zhu, Yu Gu, Tian He, Zhi-Li Zhang Department of Computer Science and Engineering, University of Minnesota, Twin Cities Presenter: Junction Date: 2010.10.28

  2. Outline • Motivation • System Overview • Evaluation • Conclusion & Contribution

  3. Outline • Motivation • System Overview • Evaluation • Conclusion & Contribution

  4. Motivation Battery/solar-powered (backup Bettery 6-8months) Environmental conditions: Soil moisture Leafwetness Ambient temperature Irrigation/vents control • Energy sharing  locally consumed • Allow energy to efficiently and quantitatively flow back and forth among multiple energy storage systems • Application: • Greenhouse Application (ClimateMinder’sGrowFlex Technology) • Wearable Computing Application (UbiComp 2008) Harvesting power from 6 body locations Locations ? Wrist: 115 ±106mW Arm: 1.01 ±0.46mW wired

  5. Batteries v.s. Capacitors • Requirements of energy sharing • Fast • Highly efficient • Quantitatively controllable • Limitation of batteries • Low charge efficiency (6%) • Limited charge current • Inaccurate remaining energy prediction • Capacitors • High charge efficiency (90%) • Have more than 1 million recharge cycles ( > 10 years) • Can be charged very quickly

  6. Ultra-Capacitors • Leakage • Physical size and remaining energy ↑, The leakage power ↑ 3000F capacitor: first 48hrs 29% of total energy leaked away

  7. Outline • Motivation • System Overview • Hardware Layer • Control Layer • Energy Sharing Layer • Evaluation • Conclusion & Contribution

  8. System Overview Decide the most efficient routes for energy distribution Control energy exchange between neighboring nodes 1. calculate the energy leakage rate 2. Forward leakage info, remaining/harvest pw Leakage model & energy supply/demand => control discharge/charge state 1.Remaining energy inside ultra-capacitors 2. Samples the harvesting power

  9. Outline • Motivation • System Overview • Hardware Layer • Control Layer • Energy Sharing Layer • Evaluation • Conclusion & Contribution

  10. Hardware Layer • Single v.s. capacitor array • Slow boot-up time • High remaining energy • Inflexibility in fine-grained control (A/D converter) • Requirements • Generality • Simplicity • Stability

  11. Outline • Motivation • System Overview • Hardware Layer • Control Layer • Energy Sharing Layer • Evaluation • Conclusion & Contribution

  12. Control Layer • Charging & discharging • Minimize leakage -> improve efficiency • Energy Leakage Model

  13. Charging • Basic Alternative Charging Control • Adaptive Charging Control • Based on the charge current

  14. Discharging • Serial connected capacitors • different voltage combination -> different remaining energy levels • The less energy remain, the more energy share • Adaptively discharged: higher leakage power first • Until voltage value reaches the calculated min voltage • Excluded from discharging

  15. Outline • Motivation • System Overview • Hardware Layer • Control Layer • Energy Sharing Layer • Energy Access Protocol • Energy Network Protocol • Evaluation • Conclusion & Contribution

  16. Outline • Motivation • System Overview • Hardware Layer • Control Layer • Energy Sharing Layer • Energy Access Protocol • Energy Network Protocol • Evaluation • Conclusion & Contribution

  17. Energy Access Protocol • Directly connect through power cord • Not through DC/DC converter • Consumes large amount of power • Protocol • Receiver-initiated • Both receiver and sender can terminate transmission monitor monitor

  18. Outline • Motivation • System Overview • Hardware Layer • Control Layer • Energy Sharing Layer • Energy Access Protocol • Energy Network Protocol • Evaluation • Conclusion & Contribution

  19. Energy Network Protocol • Finding the minimum energy loss path • Transfer Efficiency (eij) • Energy Sharing Efficiency (ESEij) • Energy optimal sharing among devices For node a: E = 100J ESEac = 0.9, ESEad = 0.81, ESEab = 0.72 c -> a 80J => 80 * 0.9 = 72, E = 100 – 72 = 28J d -> a ? => 28/0.81 = 34.6J E = 28 – 28 = 0

  20. Outline • Motivation • System Overview • Evaluation • Evaluation of Efficient Control • Evaluation of Energy Sharing • Conclusion & Contribution

  21. Outline • Motivation • System Overview • Evaluation • Evaluation of Efficient Control • Evaluation of Energy Sharing • Conclusion & Contribution

  22. Evaluation of Effective Control 2 Ultra-Capacitors 100F & 400F NEC / EC • Baseline & metrics • No Efficient Control (NEC) • Remaining energy & Voltage • Implementation • MICAz node (TinyOS & NesC) • (a) indoor • 56 hours Charging control selects the lowest leakage power to store energy -> low energy leaked away 48.7J 48.7J = MICAz 1% duty cycle more than 16hrs

  23. Evaluation of Effective Control • Implementation • (b) Mobile Phone Discharging • (c) Outdoor Energy Harvesting EC: 19 hrs (17.3% service time of the NEC) 872.8J (14.4% more)

  24. Outline • Motivation • System Overview • Evaluation • Evaluation of Efficient Control • Evaluation of Energy Sharing • Conclusion & Contribution

  25. Evaluation of Energy Sharing • Evaluation of Energy Access Protocol • One-to-One Many-to-One 2.5V 1.6V 2.378V 2.37V 2.35V 2.35V 1.2V 1.71V 0.4V 0.64V Energy sharing: 1 ~ 2.3(s) Energy sharing: 1 ~ 3.1(s) 113J => MICAz 1% duty cycle 38hrs

  26. Evaluation of Energy Sharing • Evaluation of Energy Network Protocol • oil pipeline monitoring • climate monitoringand control in greenhouses • NES (No Energy Sharing) • LES (Local Energy Sharing): with direct connected neighbors (baseline) • GES (Global Energy Sharing) • Network Lifetime • Wasted Energy • Energy leaked away inside the capacitor array • Energy consumption of the energy sharing control and communication • Energy loss when energy flows from on device to the other

  27. 2 days (48hrs) • Collected energy pattern -> for simulation input • Randomly generated working pattern • Mean duty cycle = 5% Experiments 46m 21m

  28. Performance Analysis • Simulation Results LES Control: 0.406J GES Control: 0.7836J A/D converter Negative > Positive

  29. Outline • Motivation • System Overview • Evaluation • Conclusion & Contribution

  30. Conclusion & Contribution • First Ultra-capacitor based energy router for sharing energy among embedded sensor devices • By energy sharing the network lifetime is extended • Efficient Control (Charge & Discharge) • Using an array of capacitors to minimize leakage based on leakage model • Energy Sharing (Supply & Demand) • Collaboration between data networks and energy networks for efficient energy management • Energy access protocol -> share energy among neighboring devices • Energy network protocol -> optimally distribute energy among network • Quantitatively control the amount of energy transferred • No experiments with real system deployment

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