Supercapacitor Electro-Mathematical and Machine Learning Modelling for Low Power Applications

• DOI: 10.3390/electronics7040044
• Publication Date: 2018-03-29T16:51:56Z
• Authors: Borja Pozo; Jose Garate; Susana Ferreiro; Izaskun Fernandez; Erlantz Fernandez...
• Keywords: Equivalent series resistance; Electrical network

Low power electronic systems, whenever feasible, use supercapacitors to store energy instead of batteries due their fast charging capability, low maintenance and environmental footprint. To decide if are feasible requires characterising behaviour performance for the load profiles conditions target. Traditional supercapacitor models electromechanical, require complex equations knowledge physics chemical processes involved. Models based on equivalent circuits mathematical less could provide enough accuracy. The present work uses latter techniques characterize supercapacitors. data required parametrize model is obtained through tests that capacitors charge discharge under different conditions. parameters identified life cycle, voltage, time, temperature, moisture, Equivalent Series Resistance (ESR) leakage resistance. accuracy this electro-mathematical improved with a remodelling artificial neuronal networks. experimental results both compared verify weigh Results show presented determine similar complexity than electromechanical ones, thus, helping scaling systems given