Energy management strategy for battery/supercapacitor hybrid electric city bus based on driving pattern recognition

The rapid development of cloud techniques like Vehicle-to-Cloud (V2C) makes it possible to gather more information and develop computationally efficient energy management systems (EMS) for electric vehicles. This paper proposes a novel EMS with low computational cost targeting hybrid battery/ultraca...

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Bibliographic Details
Published in:	Energy (Oxford) Vol. 243; p. 122752
Main Authors:	Shi, Junzhe, Xu, Bin, Shen, Yimin, Wu, Jingbo
Format:	Journal Article
Language:	English
Published:	Oxford Elsevier Ltd 15.03.2022 Elsevier BV
Subjects:	Algorithms batteries Buses Buses (vehicles) Cloud computing Cluster analysis Clustering Computational efficiency Computer applications Computing costs Degradation Driving conditions Driving pattern recognition Dynamic programming Electric vehicles electrochemical capacitors energy Energy consumption Energy management Energy management systems Hybrid energy storage Optimal control Pattern recognition Power consumption Unsupervised learning Vector quantization Vehicle-to-cloud connectivity Vehicle-to-cloud connectivity Hybrid energy storage Dynamic programming Driving pattern recognition Unsupervised learning
ISSN:	0360-5442, 1873-6785
Online Access:	Get full text
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