Review of the Remaining Useful Life Prognostics of Vehicle Lithium-Ion Batteries Using Data-Driven Methodologies

By Lifeng Wu, Xiaohui Fu, Yong Guan. 2016

180 citations recorded by the source corpus.

Lithium-ion batteries are the primary power source in electric vehicles, and the prognosis of their remaining useful life is vital for ensuring the safety, stability, and long lifetime of electric vehicles. Accurately establishing a mechanism model of a vehicle lithium-ion battery involves a complex electrochemical process. Remaining useful life (RUL) prognostics based on data-driven methods has become a focus of research. Current research on data-driven methodologies is summarized in this paper. By analyzing the problems of vehicle lithium-ion batteries in practical applications, the problems that need to be solved in the future are identified.

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

View Paper: https://www.semanticscholar.org/paper/f8ac0f7758258dc2f36b077625f4230004c5f78a

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. Lynn H. Kaack
2. Kang Li
3. Qiao Peng
4. Cheng Zhang
5. Kailong Liu
6. Felix Creutzig
7. Demis Hassabis

In Control and Systems Engineering

1. Kang Li
2. Yoshua Bengio
3. Qiao Peng
4. Cheng Zhang
5. Natasha Jaques
6. Kailong Liu
7. Demis Hassabis
8. Priya Lekha Donti

In Safety, Risk, Reliability and Quality

1. Kang Li
2. Yoshua Bengio
3. Qiao Peng
4. Cheng Zhang
5. Kailong Liu
6. Felix Creutzig
7. Alexandre Lacoste

Citations in the corpus

• A brief review on key technologies in the battery management system of electric vehicles (2018, methodology): “Similar to battery SOC estimation, data mining methods have also been applied for battery SOH estimation [77 – 87].”
• Tackling Climate Change with Machine Learning (2019, methodology): “[228] Lifeng Wu, Xiaohui Fu, and Yong Guan.”
• Failure statistics for commercial lithium ion batteries: A study of 24 pouch cells (2017, background): “(4) h(t) = f(t)/S(t), the hazard function, the fraction of survivors that fail on cycle t.”