[IEEE 2019 IEEE 1st International Conference on Energy, Systems and Information Processing (ICESIP) - Chennai, India (2019.7.4-2019.7.6)] 2019 IEEE 1st International Conference on Energy, Systems and Information Processing (ICESIP) - Improved ANN Model for Predicting the AC Energy Output of a Realistic Photovoltaic Grid Connected PV System

摘要： A sub-0.5 electron read noise VGA (640H×480V) CMOS image sensor has been integrated in a standard 0.18 μm 4PM CMOS process. The low noise performance is achieved exclusively through circuit optimization without any process refinements. The presented imager relies on a 4T pixel of 6.5 μm pitch with a properly sized and biased thin oxide PMOS source follower. A full characterization of the proposed image sensor, at room temperature, is presented. With a pixel bias of 1.5 μA the sensor chip features an input-referred noise histogram from 0.25 e? rms peaking at 0.48 e? rms. The imager features a full well capacity of 6400 e? and its frame rate can go up to 80 fps. It also features a fixed pattern noise as low as 0.77%, a lag of 0.1% and a dark current of 5.6 e?/s. It is also shown that the implementation of the in-pixel n-well does not impact the quantum efficiency of the pinned photo-diode.