A new hybrid method for the prediction of the remaining useful life of a lithium-ion battery

By Yang Chang, Huajing Fang, Yong Zhang. 2017

210 citations recorded by the source corpus.

Subfields: Automotive Engineering, Control and Systems Engineering, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/7bd3daf1522826ad891de144c2374302b6d8acfe

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. Ouyang Quan
3. Kailong Liu
4. Yunlong Shang

In Control and Systems Engineering

1. Widanalage Dhammika Widanage
2. Kailong Liu

In Safety, Risk, Reliability and Quality

1. Widanalage Dhammika Widanage
2. Ouyang Quan
3. Kailong Liu
4. Yunlong Shang

Citations in the corpus

• A Data-Driven Approach With Uncertainty Quantification for Predicting Future Capacities and Remaining Useful Life of Lithium-ion Battery (2021, methodology): “such as Kalman filter [5], and particle filter [6], [7], are used to capture the battery fading dynamics.”