Modeling, design and cross-layer optimization of polysilicon solar cell based micro-scale energy harvesting systems

Mungan, Elif Selin; Lü, Chao; Raghunathan, Vijay; Roy, Kaushik

doi:10.1145/2333660.2333693

Cited by 8 publications

(6 citation statements)

References 16 publications

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“…Another way of improving fK would be to reduce NT (e.g. to 10 18 cm -3 ), leading to an fK of 8.9 MHz, which is very similar to the sC case with an fK of 9.6 MHz.…”

Section: Power Converter Designmentioning

confidence: 92%

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Effects of Deposition Process on Poly-Si Microscale Energy Harvesting Systems: A Simulation Study

Mungan

Lü

et al. 2016

IEEE Trans. Electron Devices

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Abstract-In this paper, the feasibility of a low temperature polysilicon (LTPS) micro-scale energy harvester for a wireless sensor node is investigated. For that purpose, two device level models for the LTPS solar cell and thin film transistors (TFTs) are proposed and employed in system level evaluation of an energy harvesting system. The results of our analysis indicate that (i) the maximum power operating point for the solar cell is different when connected to a lossy power converter, (ii) increasing the average grain size (GrS) of the LTPS film can reduce the circuit area by 20 times while increasing the output power by 6%, (iii) the performance of the wireless sensor node is limited by the TFT performance for an LTPS process with high trap density (NT).

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“…Another way of improving fK would be to reduce NT (e.g. to 10 18 cm -3 ), leading to an fK of 8.9 MHz, which is very similar to the sC case with an fK of 9.6 MHz.…”

Section: Power Converter Designmentioning

confidence: 92%

“…The optical generation profiles used to model solar cells with different tSis were reported in [10]. GBs are modeled as 4nm-wide regions with NT and the energy levels indicated in [11].…”

Section: Solar Cell Modelingmentioning

confidence: 99%

Effects of Deposition Process on Poly-Si Microscale Energy Harvesting Systems: A Simulation Study

Mungan

Lü

et al. 2016

IEEE Trans. Electron Devices

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“…To increase the output power, multiple cells are usually combined into modules, also known as solar panels. Individual solar cell maximum output power can also be improved by advanced design methods, such as cross-layer optimization [ 10 ]. Photovoltaic cells can be classified according to the type of material they are made of: mono-crystalline (with efficiency of 15–24%), polycrystalline (with efficiency of 14–20.4%) and thin-film (with efficiency of 8–13.2%) [ 11 , 12 ].…”

Section: Energy Sourcesmentioning

confidence: 99%

Energy Harvesting Sources, Storage Devices and System Topologies for Environmental Wireless Sensor Networks: A Review

Prauzek

Konecny

Borova

et al. 2018

Sensors

186

132

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The operational efficiency of remote environmental wireless sensor networks (EWSNs) has improved tremendously with the advent of Internet of Things (IoT) technologies over the past few years. EWSNs require elaborate device composition and advanced control to attain long-term operation with minimal maintenance. This article is focused on power supplies that provide energy to run the wireless sensor nodes in environmental applications. In this context, EWSNs have two distinct features that set them apart from monitoring systems in other application domains. They are often deployed in remote areas, preventing the use of mains power and precluding regular visits to exchange batteries. At the same time, their surroundings usually provide opportunities to harvest ambient energy and use it to (partially) power the sensor nodes. This review provides a comprehensive account of energy harvesting sources, energy storage devices, and corresponding topologies of energy harvesting systems, focusing on studies published within the last 10 years. Current trends and future directions in these areas are also covered.

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“…During operation, the array of the supercapacitors is dynamically reconfigured to change the terminal voltage and effective capacitance adaptively. In [13], a cross-layer optimization method is introduced, which derives the optimal design parameters such as PV cell silicon thickness, PV cell array configuration, and charge pump stages and frequency.…”

Section: Maximum Power Transfer Trackingmentioning

confidence: 99%

Reconfigurable Photovoltaic Array Systems for Adaptive and Fault-Tolerant Energy Harvesting

Chang¹,

Pedram

Lee

et al. 2015

Nano Devices and Circuit Techniques for Low-Energy Applications and Energy Harvesting

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This chapter introduces a reconfigurable photovoltaic (PV) cell array for adaptive and fault-tolerant energy harvesting in view of component modeling, architectures, properties, and reconfigurable algorithms for partial shading and fault tolerance. On top of traditional PV cell array-based energy harvesting research, the dynamically reconfigurable PV cell array gives additional significant benefits in both efficiency and cost. This is a representative example of how electronics design automation contributes to various problems in other domains.

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Modeling, design and cross-layer optimization of polysilicon solar cell based micro-scale energy harvesting systems

Cited by 8 publications

References 16 publications

Effects of Deposition Process on Poly-Si Microscale Energy Harvesting Systems: A Simulation Study

Effects of Deposition Process on Poly-Si Microscale Energy Harvesting Systems: A Simulation Study

Energy Harvesting Sources, Storage Devices and System Topologies for Environmental Wireless Sensor Networks: A Review

Reconfigurable Photovoltaic Array Systems for Adaptive and Fault-Tolerant Energy Harvesting

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