Autonomous maximum power point tracking algorithm for ultra-low power energy harvesting

Christoph Steffan, Philipp Greiner, Carolin Kollegger, Inge Siegl, Gerald Holweg, Bernd Deutschmann

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

An ultra-low power autonomous MPPT algorithm that maximizes the efficiency of a monolithic 0.98 mm2 solar harvester is presented. Using only the pn-junctions of the standard 130 nm single n-well process, the monolithic harvester can serve as supply for wireless sensor grains. Based on the perturbation and observation method, the MPPT algorithm maximizes the output current of the integrated charge pump. The proposed approach inherently optimizes the system efficiency by automatically considering parasitic losses and source characteristics while requiring less than 100 nA supply current. This paper includes a theory section describing the maximum power flow from the illuminated pn-junction to an on-chip charge pump capacitor. Based on these results the analog algorithm is determined and described in detail introducing a resistorless high side current sensor for 100 nA to 1 mA. Concluding with measurement results regarding the tracking efficiency, a maximum deviation from the simulated loaded optimum input voltage of 3% is shown.

Original languageEnglish
Title of host publication2017 IEEE 60th International Midwest Symposium on Circuits and Systems, MWSCAS 2017
PublisherInstitute of Electrical and Electronics Engineers
Pages1372-1375
Number of pages4
Volume2017-August
ISBN (Electronic)9781509063895
DOIs
Publication statusPublished - 27 Sep 2017
Event60th IEEE International Midwest Symposium on Circuits and Systems - Boston, United States
Duration: 6 Aug 20179 Aug 2017

Conference

Conference60th IEEE International Midwest Symposium on Circuits and Systems
Abbreviated titleMWSCAS 2017
CountryUnited States
CityBoston
Period6/08/179/08/17

Keywords

  • Charge pump
  • Energy harvesting
  • Maximum power point tracking
  • Monolithic
  • On-chip solar cell
  • Perturbation and observation

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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  • Cite this

    Steffan, C., Greiner, P., Kollegger, C., Siegl, I., Holweg, G., & Deutschmann, B. (2017). Autonomous maximum power point tracking algorithm for ultra-low power energy harvesting. In 2017 IEEE 60th International Midwest Symposium on Circuits and Systems, MWSCAS 2017 (Vol. 2017-August, pp. 1372-1375). [8053187] Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/MWSCAS.2017.8053187