Parameter estimation of an electrochemistry-based lithium-ion battery model

Abstract

Parameters for an electrochemistry-based Lithium-ion battery model are estimated using the homotopy optimization approach. A high-fidelity model of the battery is presented based on chemical and electrical phenomena. Equations expressing the conservation of species and charge for the solid and electrolyte phases are combined with the kinetics of the electrodes to obtain a system of differential-algebraic equations (DAEs) governing the dynamic behavior of the battery. The presence of algebraic constraints in the governing dynamic equations makes the optimization problem challenging: a simulation is performed in each iteration of the optimization procedure to evaluate the objective function, and the initial conditions must be updated to satisfy the constraints as the parameter values change. The ε-embedding method is employed to convert the original DAEs into a singularly perturbed system of ordinary differential equations, which are then used to simulate the system efficiently. The proposed numerical procedure demonstrates excellent perfor- * Corresponding author. The final publication is available at Elsevier via http://doi.org/10.1016/j.jpowsour.2015.04.154 © 2015 mance in the estimation of parameters for the Lithium-ion battery model, compared to direct methods that are either unstable or incapable of converging. The obtained results and estimated parameters demonstrate the efficacy of the proposed simulation approach and homotopy optimization procedure.

Parameter estimation of an electrochemistry-based lithium-ion battery model using a two-step procedure and a parameter sensitivity analysis

“…Moreover, since the number of parameters is large and the estimation procedure is computationally complex, it is hard to estimate all parameters in the full DFN model. For this reason, parameter estimation has been mostly applied to simplified DFN models, such as the single particle model . Most of these works relies on Gauss‐Newton method for nonlinear optimization to perform parameter estimation, while some have used a homotopy optimization method .…”

“…For this reason, parameter estimation has been mostly applied to simplified DFN models, such as the single particle model . Most of these works relies on Gauss‐Newton method for nonlinear optimization to perform parameter estimation, while some have used a homotopy optimization method . Although parameter estimation by a genetic algorithm had been successfully used to estimate parameters in Forman et al, only a few results are available on parameter estimation of the full DFN model.…”

“…Although parameter estimation by a genetic algorithm had been successfully used to estimate parameters in Forman et al, only a few results are available on parameter estimation of the full DFN model. In a number of sources, various parameters are estimated but the parameters choice remains unexplained.…”

An Inverse Method for Estimating the Electrochemical Parameters of Lithium-Ion Batteries

“…[8][9][10][11][12][13][14][15] In this case, the collected experimental data must be processed with optimization methods in order to reveal unknown parameters and properties. A literature review of the methods applied to Li-ion batteries, i.e., the Parameter Estimation methods (PE), is provided in the first part of this study.…”

Stochastic dynamic modeling of lithium battery via expectation maximization algorithm

“…It has been widely used in portable power products, hybrid electric vehicles and mobile communication [1][2][3][4]. Note that, the lithium battery failure can lead to the performance degradation, operating error or even catastrophic failure of the whole complex system [5].…”