Basic study of model based development of lithium-ion battery using Co-simulation of vehicle system model and electrochemical cell model

2020 ◽  
Vol 2020 (0) ◽  
pp. J12102
Author(s):  
Ena ISHII ◽  
Ryosuke YAGI ◽  
Takamitsu SUNAOSHI ◽  
Norihiro YOSHINAGA
Keyword(s):  
Lithium Ion Battery ◽  
Electrochemical Cell ◽  
Cell Model ◽  
Lithium Ion ◽  
System Model ◽  
Basic Study ◽  
Model Based ◽  
Vehicle System

scholarly journals Modeling of Lithium-ion Battery for Charging/Discharging Characteristics Based on Circuit Model

2017 ◽  
Vol 13 (06) ◽  
pp. 86 ◽  
Author(s):  
Zhai Haizhou
Keyword(s):  
Lithium Ion Batteries ◽  
Lithium Ion Battery ◽  
Electrochemical Cell ◽  
Cell Model ◽  
Lithium Ion ◽  
Transient State ◽  
Strategy Management ◽  
Laboratory Setup ◽  
Negative Materials ◽  
The One

The paper describes the principle and charging/discharging characteristics of lithium-ion battery. It is as the research objects that Lithium-ion batteries with positive and negative materials of LiyMn2O4 and LixC6 were selected. A mathematical model is made for simulating the electrochemical behavior of Lithium-ion batteries. It is established that the electrochemical cell model and the one RC cell model based on aforementioned. The case of voltage, current, temperature, SOC and the charging/discharging characteristics were studied. The model is dynamic, and it reflects the transient state of the battery output. This is part of a laboratory setup used to test power system of an electric vehicle or hybrid vehicle to simulate electrochemical energy storage. The results show that accurate battery charging/discharging strategy management and SOC measurement can be achieved.

Model based insulation fault diagnosis for lithium-ion battery pack in electric vehicles

Measurement ◽  
2019 ◽  
Vol 131 ◽  
pp. 443-451 ◽  
Author(s):  
Yujie Wang ◽  
Jiaqiang Tian ◽  
Zonghai Chen ◽  
Xingtao Liu
Keyword(s):  
Fault Diagnosis ◽  
Lithium Ion Battery ◽  
Electric Vehicles ◽  
Lithium Ion ◽  
Battery Pack ◽  
Model Based

Extended Physics-Based Reduced-Order Capacity Fade Model for Lithium Ion Battery Cells

2021 ◽  
pp. 1-12
Author(s):  
Zachary Salyer ◽  
Matilde D'Arpino ◽  
Marcello Canova
Keyword(s):  
Lithium Ion Battery ◽  
Cell Model ◽  
Active Material ◽  
Lithium Ion ◽  
Calibration Procedure ◽  
Layer Growth ◽  
Operating Conditions ◽  
Capacity Fade ◽  
Computationally Efficient ◽  
Reduced Order

Abstract Aging models are necessary to accurately predict the SOH evolution in lithium ion battery systems when performing durability studies under realistic operatings, specifically considering time-varying storage, cycling, and environmental conditions, while being computationally efficient. This paper extends existing physics-based reduced-order capacity fade models that predict degradation resulting from the solid electrolyte interface (SEI) layer growth and loss of active material (LAM) in the graphite anode. Specifically, the physics of the degradation mechanisms and aging campaigns for various cell chemistries are reviewed to improve the model fidelity. Additionally, a new calibration procedure is established relying solely on capacity fade data and results are presented including extrapolation/validation for multiple chemistries. Finally, a condition is integrated to predict the onset of lithium plating. This allows the complete cell model to predict the incremental degradation under various operating conditions, including fast charging.

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