Modeling of Lithium Battery Cells for Plug-In Hybrid Vehicles

Abstract

Online simulations are utilized to reduce time and cost in the development and performance optimization of plug-in hybrid electric vehicle (PHEV) and electric vehicles (EV) systems. One of the most important factors in an online simulation is the accuracy of the model. In particular, a model of a battery should accurately reflect the properties of an actual battery. However, precise dynamic modeling of high-capacity battery systems, which significantly affects the performance of a PHEV, is difficult because of its nonlinear electrochemical characteristics. In this study, a dynamic model of a high-capacity battery cell for a PHEV is developed through the extraction of the equivalent impedance parameters using electrochemical impedance spectroscopy (EIS). Based on the extracted parameters, a battery cell model is implemented using MATLAB/Simulink, and charging/discharging profiles are executed for comparative verification. Based on the obtained results, the model is optimized for a high-capacity battery cell for a PHEV. The simulation results show good agreement with the experimental results, thereby validating the developed model and verifying its accuracy.

Dynamic Model of Li-Ion Batteries Incorporating Electrothermal and Ageing Aspects for Electric Vehicle Applications

“…The identification of battery model parameters based on equivalent circuits can be done either by specific tests, or by electrochemical impedance spectroscopy (frequency characterization), or by temporal identification using chronopotentiometry [29]. Nevertheless, the temporal characterization method using current profiles close to the actual use of the battery is widely employed in electric power applications [30]. In this paper, the temporal identification method based on a hybrid Particle Swarm-Nelder-Mead (PSO-NM) optimization algorithm is used to identify the parameters of the Li-ion battery model.…”

Model reduction of fractional impedance spectra for time–frequency analysis of batteries, fuel cells, and supercapacitors

“…Warburg elements can thus be decomposed into a sum of first‐order RC elements, identified as a series of RC units made up of admittance and impedance 57 . (iv) The Oustaloup method could provide an approximation transfer function of non‐integer‐order systems in certain frequency ranges 58–60 . Using this method, Xue et al 61 introduced improved approximation for a fractional‐order transfer function with high accuracy.…”

“…57 (iv) The Oustaloup method could provide an approximation transfer function of non-integer-order systems in certain frequency ranges. [58][59][60] Using this method, Xue et al 61 introduced improved approximation for a fractionalorder transfer function with high accuracy. (v) Hyperbolic functions could be represented by infinite products.…”

Establishment and simulation of an electrode averaged model for a lithium-ion battery based on kinetic reactions

“…The common understanding of the Randles model is that the Warburg element represents diffusion dynamics, and the resistor represents pure ohmic resistance, while the RC component represents double layer effects. [8][9][10] However, equivalent circuit models use circuit elements to mimic the behavior of batteries 11 and have limited prediction capabilities compared to the mechanism-based pseudo 2dimensional (P2D) model proposed by Newman and Doyle et al 12 which includes diffusion, intercalation, and electrochemical kinetics based on the concentrated solution theory combined with the porous electrode theory. 13 This model involves coupled nonlinear partial differential equations (PDEs) across two spatial dimensions, 14,15 so it is time consuming to solve.…”