Study on Artificial Neural Network Optimization for Electric Vehicle Battery State of Charge estimation-Reference-Cited by-同舟云学术

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

Published:2023-08-15 Issue: Volume: Page:
ISSN:
Container-title:2023 9th International Conference on Computer and Communication Engineering (ICCCE)
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Author:

Manoharan Aaruththiran¹,Begam K.M¹,Sooriamoorthy Denesh²,Aparow Vimal Rau¹

Affiliation:

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

2. Taylors University,School of Engineering,Subang Jaya,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10246011/10246027/10246092.pdf?arnumber=10246092

Reference37 articles.

1. Firefly Algorithms for Multimodal Optimization

2. A fast two-step search algorithm for half-pixel motion estimation;b z;IEEE Int Conf Electron Syst ICECS,2003

3. A hybrid optimizer based on firefly algorithm and particle swarm optimization algorithm;r w;J Comput Sci,2018

4. Performance Analysis on Artificial Neural Network Based State of Charge Estimation for Electric Vehicles

5. Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm

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