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Macromodeling of Microbatteries for IoT Micropower Source Integration

  • Mohammed Shemso Nesro
  • Ibrahim (Abe) M. Elfadel
Chapter

Abstract

Thin-film, solid-state microbatteries represent a viable alternative for powering small form-factor IoT microsystems or storing the power harvested by energy microsensors. One major obstacle to their widespread use in integrated IoT systems has been the absence of a high-fidelity, physics-based, compact model describing their operation and enabling their design and verification in the same CAD environment as integrated power management systems. In this chapter, we develop and validate such models using a thorough analysis of the electrochemistry of a thin-film, solid-state, lithium-ion microbattery. One of our compact models is based on a behavioral linearization step where the nonlinear partial differential equations (PDEs) describing the microbattery electrochemistry are replaced with linear ones without virtually any loss in accuracy. We then apply the well-established methodology of Arnoldi-based model order reduction (MOR) techniques to develop a compact microbattery model capable of reproducing its input-output electrical behavior with less than 1% error with respect to the full nonlinear PDEs. The use of MOR results in more than 30X speedup in transient simulation.

Keywords

Solid-state microbatteries Micropower sources Li-ion batteries Battery macromodeling 

Notes

Acknowledgements

We would like to acknowledge our SRC industrial liaison, Dr. Lizhong Sun from Applied Materials, for his guidance and input throughout this project. This work was supported by the Semiconductor Research Corporation (SRC) under contract 2012-VJ-2336 with customized funding from the Mubadala Investment Company, Abu Dhabi, UAE.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Mohammed Shemso Nesro
    • 1
  • Ibrahim (Abe) M. Elfadel
    • 1
  1. 1.Masdar Institute at Khalifa UniversityAbu DhabiUAE

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