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...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Energy (Oxford) Ročník 243; s. 122752
Hlavní autoři:	Shi, Junzhe, Xu, Bin, Shen, Yimin, Wu, Jingbo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 15.03.2022 Elsevier BV
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!