Calendar aging of commercial graphite/LiFePO4 cell - Predicting capacity fade under time dependent storage conditions

By Sébastien Grolleau, A. Delaille, Hamid Gualous, P. Gyan, R. Revel, J. Bernard, E. Redondo-Iglesias, Jéremy Peter. 2014

249 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/427b56dd8b9a804e42a82fd267b32121dd9f9bec

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Kailong Liu
2. Maitane Berecibar
3. Yi Li
4. Xiaosong Hu
5. Widanalage Dhammika Widanage
6. Aoife M. Foley
7. J. Van Mierlo
8. Elise Nanini-Maury

In Electrical and Electronic Engineering

1. Kailong Liu
2. Maitane Berecibar
3. Yi Li
4. Xiaosong Hu
5. Aoife M. Foley
6. J. Van Mierlo
7. Elise Nanini-Maury
8. Harry Ernst Hoster

Citations in the corpus

• Temperature, Ageing and Thermal Management of Lithium-Ion Batteries (2021, methodology): “at 90% and LFP/Graphite (6) [83] (blue) and LFP/Graphite (4) [92] (green) at 100% SOC.”
• Gaussian Process Regression With Automatic Relevance Determination Kernel for Calendar Aging Prediction of Lithium-Ion Batteries (2020, background): “However, reliable calendar aging prediction is still a bottleneck for the performance enhancement of EVs.”
• Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019, background): “High storage state of charge (SOC) and high temperature are the main drivers of calendar ageing [29].”