State-of-the-art of battery state-of-charge determination

By V. Pop, Henk Jan Bergveld, Phl Peter Notten, P. Regtien. 2005

304 citations recorded by the source corpus.

Subfields: Automotive Engineering, Control and Systems Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/d5631a930468092258c19e9bca97c4b807b6457b

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. Mohammad Farrokhi
2. Mohammad Charkhgard
3. Zonghai Chen
4. Ali Emadi
5. P. Kollmeyer

In Control and Systems Engineering

1. Delphine M. Riu
2. Mohammad Farrokhi
3. Mohammad Charkhgard
4. Sébastien Grolleau
5. Frédéric Suard
6. Mathias Gerard
7. Anthony Barré
8. B. Deguilhem

In Electrical and Electronic Engineering

1. Mohammad Farrokhi
2. Mohammad Charkhgard

Citations in the corpus

• A survey of mathematics-based equivalent-circuit and electrochemical battery models for hybrid and electric vehicle simulation (2014, unknown): “A comprehensive overview of a variety of SOC determination techniques can be found in [44, 49, 50].”
• State-of-Charge Estimation for Lithium-Ion Batteries Using Neural Networks and EKF (2010, methodology): “The SOC estimation is not an easy task and depends on the battery type and applications [2].”
• A review on lithium-ion battery ageing mechanisms and estimations for automotive applications (2013, background): “The aims of increasing batteries performances stoke the requirement of a better understood battery ageing [12, 13].”