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Control-Oriented Modeling of All-Solid-State Batteries Using Physics-Based Equivalent Circuits

delete2022-06-01
delete15
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OA
AI
李洋 cover
李洋 (Yang Li)
T
Torsten Wik
C
Changjun Xie
Y
Yicun Huang
熊斌宇 cover
熊斌宇 (Binyu Xiong)
J
Jinrui Tang
C
Changfu Zou *
DOI:10.1109/TTE.2021.3131147delete
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Abstract

Abstract

En 中文
Considered as one of the ultimate energy storage technologies for electrified transportation, the emerging all-solid-state batteries (ASSBs) have attracted immense attention due to their superior thermal stability, increased power and energy densities, and prolonged cycle life. To achieve the expected high performance, practical applications of ASSBs require accurate and computationally efficient models for the design and implementation of many onboard management algorithms so that the ASSB safety, health, and cycling performance can be optimized under a wide range of operating conditions. A control-oriented modeling framework is thus established in this work by systematically simplifying a rigorous partial differential equation (PDE)-based model of the ASSBs developed from underlying electrochemical principles. Specifically, partial fraction expansion and moment matching (PFE-MM) are used to obtain ordinary differential equation-based reduced-order models (ROMs). By expressing the models in a canonical circuit form, excellent properties for control design, such as structural simplicity and full observability, are revealed. Compared to the original PDE model, the developed ROMs have demonstrated high fidelity at significantly improved computational efficiency. Extensive comparisons have also been conducted to verify its superiority to the prevailing models due to the consideration of concentration-dependent diffusion and migration. Such ROMs can thus be used for advanced control design in future intelligent management systems of ASSBs.
Keywords:
Mathematical models
Electrolytes
Electrodes
Integrated circuit modeling
Ions
Computational modeling
Solid modeling
All-solid-state battery (ASSB)
battery modeling
electrochemical model
model order reduction
moment matching

Journal

I
IEEE Transactions on Transportation Electrification
IF:
8.3
Papers:
2.9K
Citations:
1.6W

Organization

C
chalmers university of technology
Scholars:
1.5W
Papers: 1.6W
Citations: 10
W
Wuhan University of Technology
Scholars:
3.4W
Papers: 2.4W
Citations: 4.4W