Alessandro Mariani, Kary Thanapalan, Peter Stevenson and Jonathan Williams. An Advanced Prediction Mechanism to Analyse Pore Geometry Shapes and Identification of Blocking Effect in VRLA Battery System. International Journal of Automation and Computing, vol. 14, no. 1, pp. 21-32, 2017. DOI: 10.1007/s11633-016-1040-0
Citation: Alessandro Mariani, Kary Thanapalan, Peter Stevenson and Jonathan Williams. An Advanced Prediction Mechanism to Analyse Pore Geometry Shapes and Identification of Blocking Effect in VRLA Battery System. International Journal of Automation and Computing, vol. 14, no. 1, pp. 21-32, 2017. DOI: 10.1007/s11633-016-1040-0

An Advanced Prediction Mechanism to Analyse Pore Geometry Shapes and Identification of Blocking Effect in VRLA Battery System

  • The aim of this investigation is to define a model of an alternating current impedance response that can identify the state of health of a porous electrode due to the blocked diffusion effect. To identify and simulate different pore geometries, an analytical differential equations system was studied. Standard and low performance battery products were simulated by the model and validated with electrochemical impedance spectroscopy (EIS) experimental data. The correlation between pore structure geometries and the related battery efficiency is also addressed. This investigation may clarify the possible reasons for low performance batteries. Identifying the benchmark pore geometry, parameters may be useful for the battery producers to improve the efficiency of their products. Various recovery methods are also included in this investigation to disperse the build-up of lead sulphate crystal that limits the electrolysis process in the low performance batteries.
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