Energy management strategy for long-life fuel cell hybrid power systems based on improved whale optimization algorithm-Reference-Cited by-同舟云学术

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Energy management strategy for long-life fuel cell hybrid power systems based on improved whale optimization algorithm

Published:2024-06-26 Issue:1 Volume:46 Page:1-16
ISSN:1556-7036
Container-title:Energy Sources, Part A: Recovery, Utilization, and Environmental Effects
language:en
Short-container-title:Energy Sources, Part A: Recovery, Utilization, and Environmental Effects

Author:

Fu Zhichao¹²,Chen Qihong¹,Zhou Ze¹^ORCID,Zhao Dongqi¹,Yu Shuiying³,Zhang Liyan¹

Affiliation:

1. School of Automation, Wuhan University of Technology, Wuhan, China

2. Fuel Cell Division, Wuhan Institute of Marine Electric Propulsion, Wuhan, China

3. Faculty of Computer and Information Technology, Wuhan Institute of Shipbuilding Technology, Wuhan, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/15567036.2024.2370336

Reference23 articles.

1. Reptile Search Algorithm (RSA): A nature-inspired meta-heuristic optimizer

2. Developments in fuel cell technologies in the transport sector

3. Student psychology based optimization algorithm: A new population based optimization algorithm for solving optimization problems

4. Optimal online energy management strategy of a fuel cell hybrid bus via reinforcement learning

5. Harel F. 2021. IEEE phm data challenge 2014. https://search-data.ubfc.fr/FR-18008901306731-2021-07-19_IEEE-PHM-Data-Challenge-2014.html.

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