A comparison between physics-based Li-ion battery models

Electrochimica Acta, vol. 493, pp. 144360

Abstract

Physics-based electrochemical battery models, such as the Doyle-Fuller-Newman (DFN) model, are valuable tools for simulating Li-ion battery behavior and understanding internal battery processes. However, the complexity and computational demands of such models limit their applicability for battery management systems and long-term aging simulations. Reduced-order models (ROMs), such as the Extended Single Particle Model (ESPM), Single Particle Model (SPM) and Polynomial and Padé approximations, here all referred to as simplifications, lead to faster computational speeds. Choosing the appropriate simplification method for a specific cell type and operating condition is a challenge. This study investigates the simulation accuracy and calculation speed of various simplifications for high-energy (HE) and high-power (HP) batteries at different current loading conditions and compares those to the full-order DFN model. The results indicate that among the ROMs, the ESPM consistently offers the best combination of high computational speed and relatively good accuracy in most conditions in comparison to the full-order DFN model. Among the approximations, higher-order polynomial approximation, third and fourth-order Padé approximation perform the best in terms of accuracy. The higher-order polynomial approximation shows an advantage in terms of computing speed, while the fourth-order Padé approximation achieves the highest overall accuracy among the different approximations.

Authors 6

1. Haider Adel Ali Ali Aachen Institute of Physical Chemistry

   Forschungszentrum Jülich · RWTH Aachen University

   Affiliation as printed

   Forschungszentrum Jülich GmbH, Institute of Energy and Climate Research (IEK-9), Wilhelm-Johnen-Straße, 52428 Jülich, Germany

   RWTH Aachen University, Institute of Physical Chemistry, 52074 Aachen, Germany

2. Luc H.J. Raijmakers corresponding

   Forschungszentrum Jülich

   Affiliation as printed

   Forschungszentrum Jülich GmbH, Institute of Energy and Climate Research (IEK-9), Wilhelm-Johnen-Straße, 52428 Jülich, Germany

3. Kudakwashe Chayambuka

   Forschungszentrum Jülich

   Affiliation as printed

   Forschungszentrum Jülich GmbH, Institute of Energy and Climate Research (IEK-9), Wilhelm-Johnen-Straße, 52428 Jülich, Germany

4. Dmitri L. Danilov

   Forschungszentrum Jülich · Eindhoven University of Technology

   Affiliation as printed

   Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands

   Forschungszentrum Jülich GmbH, Institute of Energy and Climate Research (IEK-9), Wilhelm-Johnen-Straße, 52428 Jülich, Germany

5. Peter H. L. Notten

   Forschungszentrum Jülich · Eindhoven University of Technology

   Affiliation as printed

   Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands

   Forschungszentrum Jülich GmbH, Institute of Energy and Climate Research (IEK-9), Wilhelm-Johnen-Straße, 52428 Jülich, Germany

6. Rüdiger‐A. Eichel Aachen Institute of Physical Chemistry

   Forschungszentrum Jülich · RWTH Aachen University

   Affiliation as printed

   Forschungszentrum Jülich GmbH, Institute of Energy and Climate Research (IEK-9), Wilhelm-Johnen-Straße, 52428 Jülich, Germany

   RWTH Aachen University, Institute of Physical Chemistry, 52074 Aachen, Germany