AI-Driven Safety Modelling for Solid-State Batteries
Year: 2025
Type: article
Abstract: This research explores how Artificial Intelligence (AI) can improve the safety and reliability of solid-state batteries (SSBs). While SSBs offer better safety than traditional lithium-ion batteries, challenges like thermal runaway still exist. AI techniques are used to predict potential failures and prevent thermal runaway by using machine learning models. Additionally, AI-based simulations help optimize the electrolyte composition to make the batteries more fire-resistant. By combining failure analysis with predictive AI Modelling , this approach aims to reduce risks and improve the overall safety of SSBs. The study shows how AI can help design safer and more reliable energy storage solutions, making SSBs a more effective choice for future applications.
Authors: Mali, Nikita, Kokate, Dakshata, Patil, Akshada, God, Ms .S.P.
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6893286926
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