Surrogate parameter identification for coupled lithium-ion cell models. Issue 5 (7th September 2015)

• Record Type: Journal Article
• Authors: Scharrer, Matthias K.; Pichler, Franz; Cifrain, Martin; Watzenig, Daniel
• Editors: Oszkár Bíró, Professor David A. Lowther and Dr Piergiorgio Alotto, Professor
• Is Part Of: Compel. Volume 34:Issue 5(2015)
• Page Start: 1578
• Page End: 1588
• Publication Date: 2015-09-07
• Subjects: Space mapping -- Equivalent circuit model -- Lithium-ion cell -- Surrogate optimization; Electrical engineering -- Data Processing -- Periodicals; Electrical engineering -- Mathematics -- Periodicals; Electrical engineering -- Periodicals; Electronics -- Data Processing -- Periodicals; Electronics -- Mathematics -- Periodicals; 621.3
• DOI: 10.1108/COMPEL-02-2015-0091
• Languages: English
• ISSNs: 0332-1649

Abstract

Abstract : Purpose: – The need to optimize and simulate lithium-ion cells is of high importance to their durability. It is possible to use semi-empirical models based on equivalent circuits to model the dynamic behavior. Still, parameter identification is a time consuming task if many equivalent circuits are coupled into a finite element-based simulation. The paper aims to discuss these issues. Design/methodology/approach: – In this paper the authors present an approach to estimate parameters in a very efficient way by using a single equivalent circuit model as a surrogate model on measurement data. The results of the surrogate model are periodically linked back to the original complex model via the so called space mapping method. The authors validate the approach and compare it to the original problem. Findings: – As a remarkable result, the authors report the achieved reduction of computational cost by approximately 87 percent, which equals a speed up factor of 8. Originality/value: – To the best of the authors' knowledge, using high and low fidelity semi-empirical models combined with space mapping is new in the field of electrical modeling of lithium-ion cells. This approach saves much time in parameterization of coupled models while maintaining high quality results for geometrical and thermal optimization of lithium-ion cells.