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Super capacitors are very power dense devices in which charge density depends on the value of the capacitance and voltage across it. Generally, high capacitance of the Supercapacitor would support higher energy storage density, voltage remaining fixed. The load driven also does not utilize properly the entire stored charge from the Super capacitor due to inconsistency in electrical characteristics between the load and source. Storage efficiency of Super capacitor has state of charge dependencies as it is variable over the duration of charge/discharge cycles. It depends directly on the capacitance and indirectly on the ESR value. The proposed optimization technique can significantly find the maximum value of storage efficiency at a near about minimum value of ESR and maximum value of capacitance. The simulation model and results show the advantage of the said technique.

 Present work proposes a new methodology for removal of noise (artifacts) from the micrograph, which normally poses a problem during segmentation of phases and measurement of their volume percentages. Segmentation of the phases is one of the primary steps towards quantification of microstructures. Dual-phase steel micrographs, generated from light microscope, consisting of ferrite (white) and martensite (black) phases are segmented by implementation of Otsu threshold algorithm, a well-known threshold algorithm of digital image processing. After thresholding, the noise removing algorithm is applied in different modes. The obtained results are compared with the findings of a commercial metallographic image processing software (Axio Vision). The proposed scheme is found to segment ferrite-martensite dual-phase micrographs successfully.

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