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Reduced‐order modeling of lead‐acid battery using cluster analysis and orthogonal cluster analysis method

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Real‐time fast simulation of lead‐acid battery (LAB) plays an important role in monitoring, control, optimization, and many other engineering fields. Hence, any improvement toward a reduction in computational time of… Click to show full abstract

Real‐time fast simulation of lead‐acid battery (LAB) plays an important role in monitoring, control, optimization, and many other engineering fields. Hence, any improvement toward a reduction in computational time of LAB simulation while maintaining the accuracy of results is of practical interest. Reduced‐order modeling (ROM) is one of the promising tools, which is computationally cost‐effective along with producing accurate results. In this study, ROM is employed in a transient one‐dimensional simulation of LABs within discharge to investigate the variation of battery parameters, eg, cell voltage, acid concentration, and state of charge (SoC). Accordingly, three reduced‐order models are implemented, namely, proper orthogonal decomposition (POD), cluster analysis (CA), and orthogonal cluster analysis (OCA), wherein the latter one is a new hybrid model of POD and CA methods proposed in the present work. The results reveal that ROM of LAB reduces the simulation time significantly (speed‐up factor about 7‐12) and provide good consistency comparing with previous experimental and numerical studies (less than 1% relative error for cell voltage, acid concentration, and SoC). In addition, the results indicate that the new hybrid method inherits the advantages of both POD and CA methods, ie, enhances the speed of POD method by 8% to 24% and accuracy of CA method by 17% to 65%.

Keywords: reduced order; analysis; cluster analysis; battery

Journal Title: International Journal of Energy Research
Year Published: 2019

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