Qianao Ju
ABSTRACT
With increasing demand of long term applications, supercapacitors have been widely chosen as energy storage devices for energy harvesting aware wireless sensor networks( WSNs) due to their long charging-discharging life cycles. However, few studies have focused on charge redistribution effect of supercapacitors in WSNs. In this paper, we investigate charge redistribution of supercapacitor and explore how it affects long term energy neutral operation (ENO). The Variable Leakage Resistance (VLR) model is used to analyze the charge redistribution effect. Our results indicate that charge redistribution may cause considerable amount of extra energy loss in long term ENO. A practical algorithm to minimize charge redistribution loss during energy neutral operation is proposed. The algorithm is computationally lightweight and can be incorporated into the state-of-the-art duty cycling power management strategies in WSNs. The proposed algorithm is proved to be effective in keeping the main branch and the delayed branch balanced and thus lowering energy dissipation from charge redistribution.
- Atmel. Atmega 128/128L datasheet. www.atmel.com, 2011.Google Scholar
- W. Dargie. Dynamic power management in wireless sensor networks: State-of-the-art. Sensors Journal, IEEE, 12(5):1518--1528, 2012.Google ScholarCross Ref
- M. Gorlatova, A. Wallwater, and G. Zussman. Networking low-power energy harvesting devices: Measurements and algorithms. Mobile Computing, IEEE Transactions on, 12(9):1853--1865, 2013. Google ScholarDigital Library
- X. Jiang, J. Polastre, and D. Culler. Perpetual environmentally powered sensor networks. In Information Processing in Sensor Networks, 2005. IPSN 2005. Fourth International Symposium on, pages 463--468. IEEE, 2005. Google ScholarDigital Library
- A. Kansal, J. Hsu, S. Zahedi, and M. B. Srivastava. Power management in energy harvesting sensor networks. ACM Transactions on Embedded Computing Systems (TECS), 6(4):32, 2007. Google ScholarDigital Library
- P. Levis, S. Madden, J. Polastre, R. Szewczyk, K. Whitehouse, A. Woo, D. Gay, J. Hill, M. Welsh, E. Brewer, et al. Tinyos: An operating system for sensor networks. In Ambient intelligence, pages 115--148. Springer, 2005.Google ScholarCross Ref
- C. Moser, L. Thiele, D. Brunelli, and L. Benini. Adaptive power management for environmentally powered systems. Computers, IEEE Transactions on, 59(4):478--491, 2010. Google ScholarDigital Library
- D. Porcarelli, D. Brunelli, and L. Benini. Improving the efficiency of air-flow energy harvesters combining active and passive rectifiers. In Proceedings of the 1st International Workshop on Energy Neutral Sensing Systems, page 6. ACM, 2013. Google ScholarDigital Library
- D. Shin, Y. Kim, Y. Wang, N. Chang, and M. Pedram. Constant-current regulator-based battery-supercapacitor hybrid architecture for high-rate pulsed load applications. Journal of Power Sources, 205:516--524, 2012.Google ScholarCross Ref
- F. Simjee and P. H. Chou. Everlast: long-life, supercapacitor-operated wireless sensor node. In Low Power Electronics and Design, 2006. ISLPED'06. Proceedings of the 2006 International Symposium on, pages 197--202. IEEE, 2006. Google ScholarDigital Library
- R. Szewczyk, A. Mainwaring, J. Polastre, J. Anderson, and D. Culler. An analysis of a large scale habitat monitoring application. In Proceedings of the 2nd international conference on Embedded networked sensor systems, pages 214--226. ACM, 2004. Google ScholarDigital Library
- TI. MSP 430 Ultra-Low-Power Microcontrollers datasheet. www.ti.com, 2011.Google Scholar
- U. Varshney. Pervasive healthcare and wireless health monitoring. Mobile Networks and Applications, 12(2-3):113--127, 2007. Google ScholarDigital Library
- C. M. Vigorito, D. Ganesan, and A. G. Barto. Adaptive control of duty cycling in energy-harvesting wireless sensor networks. In Sensor, Mesh and Ad Hoc Communications and Networks, 2007. SECON'07. 4th Annual IEEE Communications Society Conference on, pages 21--30. IEEE, 2007.Google ScholarCross Ref
- H. Yang and Y. Zhang. Self-discharge analysis and characterization of supercapacitors for environmentally powered wireless sensor network applications. Journal of Power Sources, 196(20):8866--8873, 2011.Google ScholarCross Ref
- H. Yang and Y. Zhang. Analysis of supercapacitor energy loss for power management in environmentally powered wireless sensor nodes. IEEE transactions on power electronics, 28(11):5391--5403, 2013.Google ScholarCross Ref
- Y. Zhang and H. Yang. Modeling and characterization of supercapacitors for wireless sensor network applications. Journal of Power Sources, 196(8):4128--4135, 2011.Google ScholarCross Ref
- T. Zhu, A. Mishra, D. Irwin, N. Sharma, P. Shenoy, and D. Towsley. The case for efficient renewable energy management in smart homes. In Proceedings of the Third ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings, pages 67--72. ACM, 2011. Google ScholarDigital Library
- T. Zhu, Z. Zhong, Y. Gu, T. He, and Z.-L. Zhang. Leakage-aware energy synchronization for wireless sensor networks. In Proceedings of the 7th international conference on Mobile systems, applications, and services, pages 319--332. ACM, 2009. Google ScholarDigital Library
Index Terms
- Reducing charge redistribution loss for supercapacitor-operated energy harvesting wireless sensor nodes
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