A Robust Model Order Reduction Scheme for Lithium-Ion Batteries in Control-Oriented Vehicle Models

Abstract

The role of batteries in electrification of vehicles is eminent; thus, a dynamic model that represents the physics-based phenomena of the battery system at a minimum computational cost is essential in the model-based design of electrified vehicle control systems.
Furthermore, robustness of the reduced-order battery model when maintaining the dominant physics-based phenomena governing the dynamic behavior of the battery system is crucial. Characterization of the power signal applied to the lithium-ion battery in the energy management controller of a plug-in hybrid electric vehicle shows that there is a dominant frequency range in the input signal to the battery. This key feature can be considered as a basis to construct a reduced-order model in which the training input is different from the original power signal. The original idea in this paper is to generate the training input by applying a low-pass filter to the white-noise random signal to maintain the same dominant frequency range observed in the original power signal. Response of the reduced-order model, constructed using the proper orthogonal decomposition, compared to the high-fidelity battery model shows promising results; a maximum relative error of 1% was obtained for the battery state of charge while simulation time was reduced by 42.9%.

Modeling Rate Dependent Volume Change in Porous Electrodes in Lithium-Ion Batteries

“…Lithium-ion batteries are used across the globe for a variety of applications, including grid storage, [1][2][3] off-grid power combined with solar 4 or wind 5 power, portable electronic devices such as laptops and cell phones, and electric vehicles. 6,7 As battery pack designs for electric vehicles increase in energy to meet range requirements and mitigate range anxiety 8 for consumers, higher energy density materials 9 such as silicon [10][11][12][13][14][15][16][17][18] containing materials have come into focus. Silicon and other high-capacity anode materials undergo significant volume change [19][20][21][22][23] during lithiation, [24][25][26] which can ultimately impact the performance of the battery pack and electric vehicle due to the engineering changes that must be made to account for the silicon volume change.…”