Machine learning and whale optimization algorithm based design of energy management strategy for plug‐in hybrid electric vehicle-Reference-Cited by-同舟云学术

Machine learning and whale optimization algorithm based design of energy management strategy for plug‐in hybrid electric vehicle

Published:2021-06-05 Issue: Volume: Page:
ISSN:1751-956X
Container-title:IET Intelligent Transport Systems
language:en
Short-container-title:IET intell. transp. syst

Author:

Hou Zhuoran¹^ORCID,Guo Jianhua¹,Xing Jiaming¹,Guo Chong¹,Zhang Yuanjian²

Affiliation:

1. State Key Laboratory of Automotive Simulation and Control Jilin University No. 5988, Renmin Street, Nanguan District Changchun Jilin 130022 China

2. School of Mechanical and Aerospace Engineering Queen's University Belfast Belfast BT9 5AG Northern Ireland

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/itr2.12084

Reference42 articles.

1. Research on Governmental incentive mechanism of new‐energy‐vehicle industrialization based on purchasing allowance;Lu J.;J. Comput. Inf. Syst.,2012

2. Spatial distribution evolvement characteristics and influencing factors of automobile manufacturing industry under the guidance of foreign investment: A case study of Guangzhou;Xibo W.;Econ. Geogr.,2019

3. FengK. LiJ.:Challenges in reshaping the sectoral innovation system of the Chinese automobile industry. In: Liu K.C. Racherla U. (eds)Innovation Economic Development and Intellectual Property in India and China pp.415–438.Springer Singapore(2019)

4. Melo P. AraujoR.E. CastroR.D.:Overview on energy management strategies for electric vehicles ‐ Modelling trends and research perspectives. In:Proceedings of the 2011 3rd International Youth Conference on Energetics (IYCE).Leiria Portugal(2011)

5. Hafiz F. FajriP. HusainI.:Effect of brake power distribution on dynamic programming technique in plug‐in series hybrid electric vehicle control strategy. In:Energy Conversion Congress and Exposition (ECCE).Montreal Canada(2015)

Cited by 18 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Research on IoT-based hybrid electrical vehicles energy management systems using machine learning-based algorithm;Sustainable Computing: Informatics and Systems;2024-01

2. Optimal energy management strategies for hybrid electric vehicles: A recent survey of machine learning approaches;Journal of Engineering Research;2024-01

3. Performance analysis of AI-based energy management in electric vehicles: A case study on classic reinforcement learning;Energy Conversion and Management;2024-01

4. Exploration the route of information integration for vehicle design: A knowledge-enhanced energy management strategy;Energy;2023-11

5. Online Identification of Vehicle Driving Conditions Using Machine-Learned Clusters;SAE Technical Paper Series;2023-10-31