Comparative Study of Recurrent Neural Networks for Electric Vehicle Battery State of Charge Estimation-Reference-Cited by-同舟云学术

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Comparative Study of Recurrent Neural Networks for Electric Vehicle Battery State of Charge Estimation

Published:2023-12-13 Issue: Volume:142 Page:660-665
ISSN:
Container-title:2023 IEEE 21st Student Conference on Research and Development (SCOReD)
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Author:

Hui Choong Ting¹,Manoharan Aaruththiran²,Begam K.M.²,Sooriamoorthy Denesh³

Affiliation:

1. University of Nottingham Malaysia,Department of Electrical and Electronic Engineering,Selangor,Malaysia

2. University of Nottingham Malaysia,Intelligent Electric Vehicle System (i-EVeS) Research Group,Department of Electrical and Electronic Engineering,Selangor,Malaysia

3. Asia Pacific University, Jalan Teknologi 5, Taman Teknologi Malaysia,,School of Engineering,Kuala Lumpur,Malaysia,57000

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10562378/10563214/10563702.pdf?arnumber=10563702

Reference26 articles.

1. Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies

2. Investigation on Multiphase Multistage Bidirectional DC-DC converter for Electric Vehicles using Virtual Vehicle Driving Platform

3. Voltage Oriented Control for Electric Vehicle Regenerative Power Regulation

4. Hybrid Energy Storage System Employing Regenerative Braking and Vibration Powered Energy for Hybrid Electric Vehicle

5. Study on Artificial Neural Network Optimization for Electric Vehicle Battery State of Charge estimation

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