State of Charge Estimation of Lithium Batteries in Electric Vehicles Using IndRNN-Reference-Cited by-同舟云学术

State of Charge Estimation of Lithium Batteries in Electric Vehicles Using IndRNN

Published:2021-04-05 Issue: Volume: Page:1-11
ISSN:0377-2063
Container-title:IETE Journal of Research
language:en
Short-container-title:IETE Journal of Research

Author:

Venugopal Prakash¹,T Vigneswaran¹,Reka S Sofana¹

Affiliation:

1. School of Electronics Engineering, Vellore Institute of Technology, Chennai, India

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Computer Science Applications,Theoretical Computer Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/03772063.2021.1906770

Reference25 articles.

1. Review of electrical energy storage system for vehicular applications

2. Estimation of state-of-charge and state-of-power capability of lithium-ion battery considering varying health conditions

3. A method for state of energy estimation of lithium-ion batteries based on neural network model

4. Prakash Venugopal and Vigneswaran T. “State-of-charge estimation methods for Li-ion batteries in electric vehicles.” Int. J. Innov. Technol. Explor. Eng., Vol. 8, no. 7, pp. 37–46, 2019.

5. Effect of Ambient Temperature on Electric Vehicles’ Energy Consumption and Range: Model Definition and Sensitivity Analysis Based on Nissan Leaf Data

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