透视图(图形)
离子
钠
物理
纳米技术
工程物理
材料科学
计算机科学
人工智能
冶金
量子力学
作者
Vamsi Krishna Garapati,Frederik T. Huld,Hanho Lee,Jacob Joseph Lamb
标识
DOI:10.1016/j.electacta.2024.145573
摘要
Physics-based electrochemical battery models are highly valuable tools in under-standing the internal state of batteries and simulating their behaviour. These models elucidate the fundamental electrochemical processes involved, such as ion diffusion, and provide information about the parameters affected by electrode kinetics and electrolyte dynamics. This information is crucial for improving battery efficiency and reliability, as well as for computing voltage and state of charge profiles without the need for experimentation. Furthermore, these models assist in optimizing battery design and management, thereby accelerating the development of Sodium-ion batteries (SIBs). A range of models exists for different types of batteries, from lithium-ion batteries (LIBs) to SIBs. These models vary in terms of complexity, accuracy, and computational time. This study investigates various modeling methods, encompassing detailed Pseudo-2-dimensional (P2D) models that offer extensive insights, as well as simplified reduced-order models such as the Single Particle Model (SPM). These reduced-order models strike a balance between computational efficiency and precision, which is essential for real-time control of SIB behavior under various operating conditions. Furthermore, we examine the applicability of these models in practical applications, considering their advantages and limitations. Additionally, we provide insights into potential extensions and the appropriateness of these models for future applications, which may include considerations for SIB thermal and aging factors.
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