A meta-learning based multimodal neural network for multistep ahead battery thermal runaway forecasting

• Main Authors: Ding, Shuya, Dong, Chaoyu, Zhao, Tianyang, Koh, Liang Mong, Bai, Xiaoyin, Luo, Jun
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Feature Extraction; Batteries
• Online Access: https://hdl.handle.net/10356/160292
• Institution: Nanyang Technological University

An effective forecast method to trigger Thermal Runaway (TR) warning in an early stage is essential for monitoring battery safety. In this article, we propose a novel data-driven approach to perform multistep ahead forecast accurately for battery TR state at cell-level. We formulate this forecasting...