Dimensionality Reduction Methods Comparison in the Application of Power Prediction for a Hybrid Electrical Vehicle-Reference-Cited by-同舟云学术

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Dimensionality Reduction Methods Comparison in the Application of Power Prediction for a Hybrid Electrical Vehicle

Published:2024-01-19 Issue: Volume: Page:1477-1482
ISSN:
Container-title:2024 4th International Conference on Neural Networks, Information and Communication (NNICE)
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Author:

Huang Wei¹,Zhang Yujun²,He Ying²,You Kun²

Affiliation:

1. University of Science and Technology of China,Key Laboratory of Environment Optics and Technology of Chinese Academy of Sciences,Hefei,China,230026

2. Hefei Institutes of Physical Science, Chinese Academy of Sciences,Key Laboratory of Environment Optics and Technology of Chinese Academy of Sciences,Hefei,China,230026

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10498130/10498125/10498126.pdf?arnumber=10498126

Reference13 articles.

1. Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles

2. Novel strategies to reduce engine emissions and improve energy efficiency in hybrid vehicles

3. Design of a power-split hybrid electric vehicle control system utilizing a rule-based controller and an equivalent consumption minimization strategy

4. An Unsupervised Machine-Learning Technique for the Definition of a Rule-Based Control Strategy in a Complex HEV

5. A comparison of rule-based and model predictive controller-based power management strategies for fuel cell/battery hybrid vehicles considering degradation

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