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An Ultra-Low Power CMOS Image Sensor with On-Chip Energy Harvesting and Power Management Capability

An ultra-low power CMOS image sensor with on-chip energy harvesting and power management capability is introduced in this paper. The photodiode pixel array can not only capture images but also harvest solar energy. As such, the CMOS image sensor chip is able to switch between imaging and harvesting modes towards self-power operation. Moreover, an on-chip maximum power point tracking (MPPT)-based power management system (PMS) is designed for the dual-mode image sensor to further improve the energy efficiency. A new isolated P-well energy harvesting and imaging (EHI) pixel with very high fill factor is introduced. Several ultra-low power design techniques such as reset and select boosting techniques have been utilized to maintain a wide pixel dynamic range. The chip was designed and fabricated in a 1.8 V, 1P6M 0.18 µm CMOS process. Total power consumption of the imager is 6.53 µW for a 96 × 96 pixel array with 1 V supply and 5 fps frame rate. Up to 30 μW of power could be generated by the new EHI pixels. The PMS is capable of providing 3× the power required during imaging mode with 50% efficiency allowing energy autonomous operation with a 72.5% duty cycle.
- School of Electronics and Information China (People's Republic of)
- Department of Electrical Engineering and Computer Science University of Michigan United States
- NANYANG TECHNOLOGICAL UNIVERSITY Singapore
- Department of Electrical Engineering and Computer Science University of Michigan United States
- Hangzhou Dianzi University China (People's Republic of)
energy harvesting, :Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision [DRNTU], Chemical technology, MPPT, 600, TP1-1185, Article, 620, DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision, CMOS image sensor, power management, ultra-low power
energy harvesting, :Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision [DRNTU], Chemical technology, MPPT, 600, TP1-1185, Article, 620, DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision, CMOS image sensor, power management, ultra-low power
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