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A State-of-Health-Oriented Power Management Strategy for Multi-Source Electric Vehicles Considering Situation-Based Optimized Solutions in Real-Time
University of Duisburg-Essen.
Amity University.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
University of Duisburg-Essen.
2019 (English)In: Proceedings of the Annual Conference of the PHM Society 11 (1), Scottsdale, Arizona, USA: PHM Society , 2019, Vol. 11, p. 1-10, article id 783Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a novel situation-based power and battery health management strategy for fuel cell vehicles. In such hybrid powertrains, the synergy role of batteries is essential to minimize overall power consumption and maintain higher electrical efficiency of the fuel cell. On the other hand, lifetime degradation of the battery is associated with the recurrent charging / discharging cycles. The proposed power management strategy addresses the trade-off between these contradictory objectives. Vehicle states in each situation are defined in terms of driver-related identification parameters (power demand and speed) corporately with powertrain related ones (on-board battery's state of charge). Optimal power handling solution for each situation is searched offline considering different optimization criteria: range extension, lifetime maximization, or power consumption minimization. A weighted fusion of these optimized solutions can be implemented online based on desired driving strategy, leading to situation-based optimized solution. This contribution aims to provide flexible power handling options meeting performance requirements (energy efficiency and driveability) without scarifying battery life. Simulation tests using different driving cycles are conducted for evaluation purpose.

Place, publisher, year, edition, pages
Scottsdale, Arizona, USA: PHM Society , 2019. Vol. 11, p. 1-10, article id 783
Keywords [en]
Situation-based power management, Health monitoring
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-37566DOI: 10.36001/phmconf.2019.v11i1.783ISBN: 978-1-936263-29-5 (print)OAI: oai:DiVA.org:miun-37566DiVA, id: diva2:1364839
Conference
Annual Conference of the Prognostics and Health Management Society 2019
Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-10-30Bibliographically approved

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Publisher's full texthttp://phmpapers.org/index.php/phmconf/article/view/783

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Beganovic, Nejra

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
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  • asciidoc
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