State of health and charge measurements in lithium-ion batteries using mechanical stress
By John Cannarella, C. Arnold. 2014
248 citations recorded by the source corpus.
Subfields: Automotive Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/647fa1e30628c6746b79fc467cc4c5944bd58163
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
- Kailong Liu
- Maitane Berecibar
- Aoife M. Foley
- Elise Nanini-Maury
- J. Van Mierlo
- Harry Ernst Hoster
- Yi Li
- A. A. Zulke
In Electrical and Electronic Engineering
- Kailong Liu
- Maitane Berecibar
- Aoife M. Foley
- Elise Nanini-Maury
- J. Van Mierlo
- Harry Ernst Hoster
- Yi Li
- A. A. Zulke
Citations in the corpus
- Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019, background): “[71] proposed to estimate battery SOH through the measurement of cell strain, after showing that the stress resulting from electrode expansion is linearly correlated with the SOH.”