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

Descripción del proyecto

Mejorar la sostenibilidad de las baterías de iones de litio

A medida que el Pacto Verde Europeo avanza hacia la neutralidad climática para 2050, el excedente de baterías de vehículos eléctricos retiradas del servicio plantea un reto. Aunque estas baterías conservan el 80 % de su capacidad, a menudo se desechan antes de tiempo. Con el apoyo de las Acciones Marie Skłodowska-Curie, el equipo del proyecto BLESS tiene como objetivo impulsar nuevos avances en materia de sostenibilidad de las baterías mediante el desarrollo de un concepto avanzado de autorreparación para baterías de iones de litio de segunda vida. Mediante estrategias de pulsación inteligentes y la inteligencia artificial (IA), en el proyecto se supervisará el estado de la batería y se recuperará al instante cualquier pérdida de potencia. Este método está diseñado para garantizar que las baterías no solo sean seguras y duraderas a largo plazo, sino que también funcionen de manera óptima en cualquier circunstancia.

Objetivo

The European Green Deal sets an ambitious goal of achieving climate neutrality by 2050, with lithium-ion batteries (LIBs) playing a pivotal role in enabling sustainable transportation and renewable energy integration. However, millions of LIBs are prematurely retired from electric vehicles (EVs) despite retaining up to 80% of their designed capacity, leading to substantial environmental and economic challenges. Leveraging emerging self-healing (SH) techniques that utilize intelligent pulse-based interventions, the BLESS project aims to unlock the untapped potential of second-life LIBs while ensuring safety and durability.

To achieve this, BLESS will develop an integrated multi-timescale self-healing framework 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 scalable solutions for second-life LIB utilization, directly contributing to Europe’s sustainability goals while fostering industrial innovation, energy and material security.