Introduction to Energy Harvesting in IoT… Why???

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Autonomous sensor nodes are the key element for spreading IoT technology and are becoming increasingly popular. The global market is expected to grow annually up to 25.4% in the 2021–2028 period, from 381.30 billion dollars in 2021 to 1854.76 billion dollars in 2028 [1]. Considering the large number of different communication protocols that can be adapted to every case, the next big challenge in the autonomous sensor nodes field is the battery life.

As devices get smaller, powering them with traditional batteries becomes an issue because of size, environmental impact, and maintenance costs. Moreover, replacing batteries periodically, even every 5 or 10 years, is unsuitable for many applications, while photovoltaic cells are fabricated with more than 25 years of lifespan maintaining more than 80% of the efficiency [2]. In addition, facts like unforeseen battery degradation, natural ageing, or instantaneously burnout in chemical rechargeable batteries limit their utilization and are still a relevant research theme [3].

The solution to enhance the batteries’ operational life or even eradicate their use through energy harvesting techniques has also turned into a topic of interest for both academia and industry. Several ambient sources have been proposed in the last decade to power these wireless nodes with energy captured from the environment [4].

On the other hand, among the batteryless IoT systems, sensor nodes based on RFID technology have become one of the most popular for short and medium-range applications [5]. RFID tags are remotely powered by the reader, but the reader must be near the tag as received power rapidly degrades with the distance. This is the most significant limitation of the RFID technology, especially when sensor capabilities are added to the tag to measure data in addition to RFID identification. Additionally, pure batteryless RFID tags cannot operate continuously if no RF source is available in the surroundings all the time. That makes a datalogging operation mode of the sensor difficult, since no stable supply energy is available.

However, environmental energy harvesting can provide an endless energy source by collecting and storing energy from the ambient, thus having not only continuous energy for datalogging of sensor measurements, but also increasing the maximum communication range between reader and tag [6].

Depending on the application, different energy harvesting sources can substitute the traditional batteries with ambient energy transducers such as photovoltaic, piezoelectric, thermoelectric, and triboelectric modules, which convert, respectively, sunlight, vibrations, heat, or friction into electric power. Among them, solar energy provides the highest power density, producing enough power even under indoor light environments [7,8].

 

However, in indoor environments, the solar harvested power and output voltage are much lower. Therefore, in order to consider photovoltaic cells as a continuous energy source, its output needs to be adapted and managed by an electronic interface called Power Management Unit (PMU) that can supply the required voltage and power the corresponding load.

The main element of a PMU connected to a photovoltaic cell is the charge pump that raises the harvester output voltage up to the standard supply voltages of 1 V, 1.2 V, or 3.3 V required by different sensor nodes.

 

Conventionally, dc-dc boost converters have been implemented with inductor-based architectures due to their high-efficiency [9–11]. However, to reach high performances, they rely on low-resistance and high-quality inductors, which are not available on standard CMOS technologies, if a fully integrated implementation is desired [11].

Nevertheless, monolithic converters built only with capacitors are gaining popularity for some applications because they can be fully integrated on ICs, suppressing expensive and voluminous off-chip LC components. Ref. [12] has a high efficiency in indoor lighting conditions, but it needs a high minimum input voltage, and it relies on an auxiliary charge pump to start-up. Ref. [13] integrates a photodiode on-chip as a solar cell for a full miniaturized system, although limiting its use only for outdoors. Ref. [14] works under indoor lights, but the power throughput is very little.

As a part of my PhD thesis work, we present a self-sustaining energy-efficient monolithic PMU that includes a charge pump adapted to photovoltaic cells with the capability of charging a large supply capacitor and managing the stored energy efficiently to provide the required supply

voltage and power to low energy consumption wireless sensor nodes such an RFID sensor tag. More information can be found on the complete article. Previous works developed by my university team in [15] proved and validated the architecture of the charge pump with simulations.

 

Further information can be found in the published paper, which discusses the design by adding on-chip all the necessary blocks, implementing it for fabrication in silicon on the TSMC 180nm technology and the post-characterization of the energy harvester.

 

References

  1. Fortune Business Insights. Internet of Things (IoT) Market, 2021–2028. link
  2. Tan, V.; Dias, P.R.; Chang, N.; Deng, R. Estimating the Lifetime of Solar Photovoltaic Modules in Australia. Sustainability 2022, 14, 5336. link
  3. Xu, B.; Oudalov, A.; Ulbig, A.; Andersson, G.; Kirschen, D.S. Modeling of Lithium-Ion Battery Degradation for Cell Life Assessment. IEEE Trans. Smart Grid 2018, 9, 1131–1140. link
  4. Amar, A.B.; Kouki, A.B.; Cao, H. Power Approaches for Implantable Medical Devices. Sensors 2015, 15, 28889–28914. link
  5. Engmann, F.; Katsriku, F.A.; Abdulai, J.-D.; Adu-Manu, K.S.; Banaseka, F.K. Prolonging the Lifetime of Wireless Sensor Networks: A Review of Current Techniques. Wirel. Commun. Mob. Comput. 2018, 2018, 8035065. link
  6. Jauregi, I.; Solar, H.; Beriain, A.; Zalbide, I.; Jimenez, A.; Galarraga, I.; Berenguer, R. UHF RFID Temperature Sensor Assisted With Body-Heat Dissipation Energy Harvesting. IEEE Sens. J. 2017, 17, 1471–1478. link
  7. Paradiso, J.A.; Starner, T. Energy scavenging for mobile and wireless electronics. IEEE Pervasive Comput. 2005, 4, 18–27. link
  8. Liu, X.; Huang, L.; Ravichandran, K.; Sánchez-Sinencio, E. A highly efficient reconfigurable charge pump energy harvester with wide harvesting range and two-dimensional MPPT for Internet of Things. IEEE J. Solid-State Circuits 2016, 51, 1302–1312. link
  9. Hsieh, P.-H.; Chou, C.-H.; Chiang, T. An RF energy harvester with 44.1% PCE at input available power of 12 dBm. IEEE Trans. Circuits Syst. I Reg. Papers 2015, 62, 1528–1537. link
  10. Amin, S.S.; Mercier, P.P. MISIMO: A multi-input single-inductor multi-output energy harvester employing event-driven MPPT control to achieve 89% peak efficiency and a 60,000× dynamic range in 28 nm FDSOI. In Proceedings of the 2018 IEEE International Solid-State Circuits Conference—(ISSCC), San Francisco, CA, USA, 11–15 February 2018; pp. 144–146. link
  11. Huang, C.; Mok, P.K.T. An 84.7% Efficiency 100-MHz Package Bondwire-Based Fully Integrated Buck Converter with Precise DCM Operation and Enhanced Light-Load Efficiency. IEEE J. Solid-State Circuits 2013, 48, 2595–2607. link
  12. Liu, X.; Sánchez-Sinencio, E. An 86% Efficiency 12 μW Self-Sustaining PV Energy Harvesting System with Hysteresis Regulation and Time-Domain MPPT for IOT Smart Nodes. IEEE J. Solid-State Circuits 2015, 50, 1424–1437. link
  13. Chen, P.-H.; Huang, C.-Y.; Cheng, H.-C.; Chen, P.-H. A Fully Integrated Light-Powering System with Integrated CMOS Photovoltaic Cell for Batteryless IoT Devices. In Proceedings of the 2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS), Genoa, Italy, 27–29 November 2019; pp. 907–910. link
  14. Megahed, M.; Ramadass, Y.; Anand, T. A Sub 1 μW Switched Source + Capacitor Architecture Free of Top/Bottom Plate Parasitic Switching Loss Achieving Peak Efficiency of 80.66% at a Regulated 1.8 V Output in 180 nm. In Proceedings of the 2019 IEEE Custom Integrated Circuits Conference (CICC), Austin, TX, USA, 14–17 April 2019; pp. 1–4. link
  15. Lopez-Gasso, A.; Beriain, A.; Solar, H.; Berenguer, R. Switched Capacitors Charge Pump with half-floating Topology for a high-efficient Solar Energy Harvester. In Proceedings of the 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), Segovia, Spain, 18–20 November 2020; pp. 1–5. link

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