Abstract
In the recent years, with the advent of artificial intelligence in multidisciplinary fields, more and more efficient mechanisms, to enhance the performance of various systems, are gaining prominence. This paper exploits the technique of computational intelligence to optimize the storage efficiency of supercapacitors. While a supercapacitor is a high-value capacitor, it can be used as an energy storage device like batteries. The storage efficiency of a supercapacitor depends directly on the capacitance value and inversely on the Equivalent Series Resistance (ESR) value. Supercapacitors with high storage efficiency can be deployed in numerous applications requiring high power-handling capacity. Different optimization methods have been used to maximize the storage efficiency of supercapacitors. In this paper, Particle Swarm Optimization (PSO) technique has been used in which the values of storage efficiency obtained are higher than those from other conventional algorithms.
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Mahindar, R., Mukherjee, S., Dutta, S., Dutta, T., Ghosh, R. (2020). Particle Swarm-Based Approach for Storage Efficiency Optimization of Supercapacitors. In: Das, A., Nayak, J., Naik, B., Pati, S., Pelusi, D. (eds) Computational Intelligence in Pattern Recognition. Advances in Intelligent Systems and Computing, vol 999. Springer, Singapore. https://doi.org/10.1007/978-981-13-9042-5_38
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DOI: https://doi.org/10.1007/978-981-13-9042-5_38
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