Fault Diagnosis and State of Charge Estimation of Battery for Electric Vehicle Applications
Author:
Affiliation:
1. Career Point University,Kota,India
2. Maulana Azad National Institute of Technology,Bhopal,India
3. IES college of Technology, IES University,Bhopal,India
4. Rajasthan Technical University,Kota,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10351781/10351782/10351885.pdf?arnumber=10351885
Reference24 articles.
1. Electric vehicles: To what extent are environmentally friendly and cost effective? – Comparative study by european countries
2. The lithium-ion battery: State of the art and future perspectives
3. Fault prognosis of battery system based on accurate voltage abnormity prognosis using long short-term memory neural networks
4. On-board soft short circuit fault diagnosis of lithium-ion battery packs for electric vehicles using extended Kalman filter
5. A Voltage Sensor Fault Diagnosis Method Based on Long Short-Term Memory Neural Networks for Battery Energy Storage System
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