SOURCE-LINKED INTELLIGENCE

Second-life Lithium-ion Battery Lifetime Extension through Self-healing Strategies

CORDIS · observation · Publication date unknown

consisting of three core innovations: 1) Advanced multi-timescale state estimation, enabling rapid detection of lithium plating and capacity degradation by combining field-accessible pulse tests with machine learning; 2) Optimized pulse restoration strategies that designs adaptive pulse parameter profiles to respectively suppress lithium plating and recover lost capacity, ensuring safety and durability; 3) Joint optimization for lifetime extension, implementing a multi-objective dual-loop optimization framework to continuously regulate pulse parameters under uncertain operation conditions, enabling long-term safety and durability of second-life batteries. The methodologies will integrate electrochemistry, signal processing, machine learning, and optimization, delivering a validated experimental platform and novel algorithms. Dr. Shengyu Tao, as an MSCA fellow, will receive comprehensive interdisciplinary training at Chalmers University of Technology, combining theoretical modeling, AI-driven diagnostics, and real-world battery experiments. The outputs of this project will provide sc

Read original source ↗ Open in workspace

recordType

award

status

SIGNED

region

EU

value

252180

unit

EUR