Optimisation of Solid-State Batteries: A Modelling Approach to Battery Design

Solid-state batteries (SSBs) present a promising advancement in energy storage technology, with the potential to achieve higher energy densities and enhanced safety compared to conventional lithium-ion batteries. However, their commercialisation is hindered by technical limitations and fragmented research efforts that predominantly focus on materials or individual performance parameters. This narrow scope limits SSB design and optimisation, potentially delaying the transition to commercial cells. Addressing these challenges requires a systematic framework that integrates key design and performance considerations. This study introduces a modelling framework that addresses these challenges by offering a systematic approach to SSB design. The model streamlines the design process by enabling users to define material selections and cell configurations while calculating key performance indicators (KPIs), such as energy density, power density, and resistance, as well as the specifications required for cell manufacturing. A material compatibility validation feature ensures appropriate selection of anode, cathode, and electrolyte materials, while an integrated sensitivity analysis (SA) function identifies critical design parameters for performance optimisation. The model’s accuracy and applicability were validated through comparisons with experimental data, established design frameworks, and the reverse-engineering of commercial SSB prototypes. Results show that the model predicts energy densities within a ±4% deviation in most cases. Additionally, the application of SA highlights its effectiveness in refining design parameters and optimising cell configurations. Despite certain limitations, the model remains a valuable tool in the early stages of battery concept development. It offers researchers and industry professionals a practical means to assess the feasibility of SSB designs and support future scale-up and industrialisation efforts.