Reduction of an Electrochemistry-Based Li-Ion Battery Model via Quasi-Linearization and Padé Approximation

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Battery Energy Storage System (BESS) and Battery Management System (BMS) for Grid-Scale Applications (2014, methodology): “Order reduction approaches such as proper orthogonal decomposition (POD) and quasi-linearization of the model have been used to reduce the number of equations needed to be solved, though at the cost of reduced accuracy [93], [94].”
Overview of Lithium-Ion battery modeling methods for state-of-charge estimation in electrical vehicles (2018, methodology): “Numerical methods such as integral approximation, Pade approximation, the Ritz method, the finite element method, and the finite difference method are often selected to discretize the nonlinear PDEs in the electrochemical models [47,48].”
A survey of mathematics-based equivalent-circuit and electrochemical battery models for hybrid and electric vehicle simulation (2014, unknown): “Other methods, including the Chebyshev polynomial method [77, 78], the residue grouping method [79, 80], proper orthogonal decomposition method [81], and Pad´e approximation [82] have also been used to derive reduced-order models for Li-ion batteries.”