Virtual ValentinAI

The work in brief

Valentin's work centres on physics-based mathematical models of batteries and on making them fast and usable. The earliest papers (2019) develop porous-electrode models of lead-acid batteries and use asymptotic analysis to reduce them to models that run at speeds approaching equivalent circuits, and the same approach is applied to lithium-ion cells: an asymptotically derived single particle model with electrolyte, and reduced-order hierarchies of three-dimensional thermal pouch cell models. This modelling is supported by open-source software, including PyBaMM and the pack-simulation package liionpack, alongside papers on verifiable theoretical research, the case for battery modelling, and a review of the continuum of physics-based lithium-ion models.

From around 2020 the focus moves towards degradation and lifetime. This includes modelling coupled degradation mechanisms, accelerated inter-cycle simulation of ageing, and a review of "knees" in ageing trajectories. Data-driven work covers lifetime prognostics across varied ageing conditions, formation-protocol diagnostics, field-data prediction, and Bayesian analysis of electric aircraft battery degradation. Other papers address fast-charging safety control, expansion and voltage modelling, and automated materials discovery. The most recent papers (2023–2024) model electrochemical-thermal-mechanical stress and degradation in composite silicon–graphite electrodes.

AI-written from the paper titles and abstracts; Valentin hasn't reviewed it.