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State of Charge Monitor for Wireless Sensor Networks

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Mobile Networks for Biometric Data Analysis

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 392))

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Abstract

Wireless sensor networks promise to become one of the most pervasive technologies in the next years. From Smart Cities to industrial safety and human health, from energy to environmental control, the potential of smart networks seems unlimited less until now. Some important features that a pervasive technology must face is its impact on the environment where the installation is made, how easy the installation is and the compatibility with existing technologies. These factors lead to realize, when possible, a network in which all devices from nodes (or routers) to end devices (or peripheral devices) are battery supplied and are as small as possible. In such a network, the batteries, the power management and the energy consumption monitoring, play a very important role, as relevant as the network functionality itself. In this work, we present a micropower battery monitor using a Coulomb to pulse frequency converter based on microcontroller. As a result, we will show that this solution can be well suited in low power applications, like wireless devices where low power consumption and wide dynamic range are important characters.

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References

  1. Zarrabi H, Al-Khalili A, Savaria Y (2011) Activity management in battery-powered embedded systems: a case study of ZigBee; WSN. In: 2011 18th IEEE international conference on electronics, circuits and systems (ICECS), pp 727–731

    Google Scholar 

  2. Scavongelli C, Franco F, Orcioni S, Conti M (2015) Battery management system simulation using system C. In: Proceedings of the IEEE 12th international workshop on intelligent solutions in embedded systems WISES2015, Ancona, Italy, pp 151–156, 29–30 Oct 2015

    Google Scholar 

  3. Conti M, Fedeli D, Virgulti M (2011) B4V2G: Bluetooth for electric vehicle to smart grid connection. In: Proceedings of the 9th international workshop on intelligent solutions in embedded systems WISES 2011, Regensburg, Germany, pp 13–18, 7–8 June 2011

    Google Scholar 

  4. Chang W-Y (2013) The state of charge estimating methods for battery: a review. ISRN applied mathematics, Hindawi Publishing Corporation, 2013, Article ID 953792, 7 p

    Google Scholar 

  5. Pang S, Farrell J, Du J, Barth M (2001) Battery state-of-charge estimation. In: Proceedings of the 2001 American control conference, 2001, vol 2, pp 1644–1649

    Google Scholar 

  6. Rodrigues S, Munichandraiah N, Shukla AK (2000) A review of state-of-charge indication of batteries by means of A.C. impedance measurements. J Power Sources 87(1–2):12–20

    Article  Google Scholar 

  7. Huet F (1998) A review of impedance measurements for determination of the state-of-charge or state-of-health of secondary batteries. J Power Sources 70(1):59–69

    Article  MathSciNet  Google Scholar 

  8. Tairov S, Stevanatto L (2011) The novel method for estimating vrla battery state of charge. In: 2011 IEEE electronics, robotics and automotive mechanics conference (CERMA), pp 211–215

    Google Scholar 

  9. Ng K-S, Moo C-S, Chen Y-P, Hsieh Y-C (2008) State-of-charge estimation for lead-acid batteries based on dynamic open-circuit voltage. In: IEEE 2nd international power and energy conference, PECon 2008, pp 972–976

    Google Scholar 

  10. Coleman M, Lee CK, Zhu C, Hurley WG (2007) State-of-charge determination from EMF voltage estimation: using impedance, terminal voltage, and current for lead-acid and lithium-ion batteries. IEEE Trans Industr Electron 54(5):2550–2557

    Article  Google Scholar 

  11. Ng K-S, Huang Y-F, Moo C-S, Hsieh Y-C (2009) An enhanced coulomb counting method for estimating state-of-charge and state-of-health of lead-acid batteries. In: 31st international telecommunications energy conference, 2009. INTELEC 2009. pp 1–5

    Google Scholar 

  12. Ng KS, Moo CS, Chen YP, Hsieh YC (2009) Enhanced Coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries. Appl Energy 86(9):1506–1511

    Article  Google Scholar 

  13. Lezhang L, Wang LY, Chen Z, Wang C, Lin F, Wang H (2013) Integrated system identification and state-of-charge estimation of battery systems. IEEE Trans Energy Convers 28(1):13–23

    Google Scholar 

  14. Maxim Integrated (2009) http://www.maximintegrated.com/datasheet/index.mvp/id/4560, Stand-Alone Fuel-Gauge IC (2009). Datasheet

  15. Texas Instruments (2013) http://www.ti.com/lsds/ti/power-management/battery-management-productsproducts.page, Products for Battery Management (Consulted in 2013). Datasheets

  16. Linear Technology (2003) http://www.linear.com/product/LTC4150, Coulomb Counter/Battery Gas Gauge (2003). Datasheet

  17. Carloni M, d’Aparo R, Scorrano P, Naticchia B, Conti M (2013) A micropower supervisor for wireless nodes with a digital pulse frequency modulator battery monitor. In: Proceedings of SPIE 2013 microtechnologies, international conference VLSI circuits and systems, vol 8764. Grenoble, France, Paper 26, pp 0P.1–0P.12, 24–26 Apr 2013

    Google Scholar 

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Correspondence to Mirko Carloni .

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Carloni, M., d’Aparo, R., Scorrano, P., Naticchia, B., Conti, M. (2016). State of Charge Monitor for Wireless Sensor Networks. In: Conti, M., Martínez Madrid, N., Seepold, R., Orcioni, S. (eds) Mobile Networks for Biometric Data Analysis. Lecture Notes in Electrical Engineering, vol 392. Springer, Cham. https://doi.org/10.1007/978-3-319-39700-9_6

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  • DOI: https://doi.org/10.1007/978-3-319-39700-9_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39698-9

  • Online ISBN: 978-3-319-39700-9

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