Electrochemical-acoustic time of flight: in operando correlation of physical dynamics with battery charge and health

By Andrew G. Hsieh, S. Bhadra, B. Hertzberg, Peter J Gjeltema, Alexandre Goy, J. Fleischer, Dan Steingart. 2015

221 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/81a5f98b980bddc13abdbc046506bcc025086d6a

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. Widanalage Dhammika Widanage
2. Xinhua Liu
3. Shichun Yang
4. Billy Wu
5. Valentin Sulzer
6. Anna G. Stefanopoulou
7. David A. Howey

In Electrical and Electronic Engineering

1. Widanalage Dhammika Widanage
2. Xinhua Liu
3. Shichun Yang
4. Billy Wu
5. Valentin Sulzer
6. Anna G. Stefanopoulou
7. David A. Howey

Citations in the corpus

• Battery digital twins: Perspectives on the fusion of models, data and artificial intelligence for smart battery management systems (2020, methodology): “One such approach presented by Hsieh et al. [47] used acoustic time-of-flight measurements to infer changes in the density of electrodes during lithiation/delithiation.”
• The challenge and opportunity of battery lifetime prediction from field data (2021, background): “We note that mechanical [71] or acoustic [72] measurements have been proposed as a means to address the lack of observability, but such measurements are not yet widely used.”