Perspective and comparative analysis of physics-based models for sodium-ion batteries

Physics-based electrochemical battery models are highly valuable tools in understanding 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 optimising 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 modelling methods, encompassing detailed Doyle–Fuller–Newman Model (DFN) 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 behaviour under various operating conditions. Furthermore, we examine the applicability of these models in practical applications, considering their advantages and limitations. • Comparative analysis of reduced-order and full-order physics-based models for sodium-ion batteries (SIBs). • Evaluation of SPM, SPMe, and DFN models for SIBs, with a focus on distinguishing key differences from lithium-ion battery (LIB) behaviour. • Assessment of model accuracy and computational efficiency, highlighting suitability for various SIB applications.