Combined cycling and calendar capacity fade modeling of a Nickel-Manganese-Cobalt Oxide Cell with real-life profile validation

By Joris de Hoog, Jean-Marc Timmermans, Daniel Ioan-Stroe, Maciej Swierczynski, Joris Jaguemont, S. Goutam, Noshin Omar, J. Van Mierlo, P. Bossche. 2017

208 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/880a2de3935158e8b2e934b10e6725392b9d2604

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. Aoife M. Foley
4. Elise Nanini-Maury
5. J. Van Mierlo
6. Harry Ernst Hoster
7. Yi Li
8. A. A. Zulke

In Electrical and Electronic Engineering

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

Citations in the corpus

• Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review (2019, methodology): “Illustration of the 3D-surface fitting of the developed cyclic ageing model for lifetime prediction by considering the stress factors of cycling DOD at a fixed temperature and mid-SOC [97]”
• Gaussian Process Regression With Automatic Relevance Determination Kernel for Calendar Aging Prediction of Lithium-Ion Batteries (2020, unknown): “[12] proposed a semiempirical combined model to estimate the calendar lifetime for a Nickel-manganese-Cobalt Oxide battery.”