Review-Development of Diagnostic Process for Commercially Available Batteries, Especially Lithium Ion Battery, by Electrochemical Impedance Spectroscopy

By T. Osaka, Daikichi Mukoyama, H. Nara. 2015

139 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/791bba48de73285384c2e5e40183c253d3b73f04

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. Xinhua Liu
2. Shichun Yang
3. Widanalage Dhammika Widanage
4. Billy Wu

In Electrical and Electronic Engineering

1. Xinhua Liu
2. Shichun Yang
3. Widanalage Dhammika Widanage
4. Billy Wu

Citations in the corpus

• Battery digital twins: Perspectives on the fusion of models, data and artificial intelligence for smart battery management systems (2020, methodology): “Osaka et al. [40] for instance presented and compared a number of different equivalent circuits used for describing battery EIS and showed how anode and cathode processes could be decoupled; helping to increase the identifiability of a system.”