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Charging Cost Optimization of Plug-in Hybrid Electric Vehicles
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
2015 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The future success of chargeable vehicles will, among other factors, depend on their charging costs and their ability to charge with minimal disturbances to the national, local and household electrical grid. To be able to minimize costs and schedule charging sessions, there has to be knowledge of how the charging power varies with time. This is called charging profile. A number of charging profiles for a Volvo V60 plug‑in hybrid electric vehicle have been recorded. For charging currents above 10 A they prove to be more complex than are assumed in most current research papers.


The charging profiles are used together with historical electricity prices to calculate charging costs for 2013 and 2014. Charging is assumed to take place during the night, between 18:00 and 07:00, with the battery being totally depleted at 18:00. By using a timer to have the charging start at 01:00, instead of immediately at 18:00, annual charging costs are reduced by approximately 7 to 8%. By using dynamic programming to optimize the charging sessions, annual charging costs are reduced by approximately 10 to 11%. An interesting issue regarding dynamic programming was identified, namely when using a limited set of predetermined discrete control signals, interpolation returns unrealizable cost-to-go values. This occurs specifically for instances crossing the zero cost-to-go area boundary.


It is concluded that the mentioned savings are realizable, via implementing timers or optimization algorithms into consumer charging stations. Finally, by using these decentralized charging planning tools and seen from a power usage perspective, at least 30% of the Swedish vehicle fleet could be chargeable and powered by the electrical grid.

Place, publisher, year, edition, pages
2015. , 98 p.
Keyword [en]
charging cost optimization profiles dynamic programming electric vehicles
National Category
Vehicle Engineering
URN: urn:nbn:se:liu:diva-119566ISRN: LiTH-ISY-EX--15/4829--SEOAI: diva2:824705
Subject / course
Vehicular Systems
2015-06-11, Systemet, Linköping University, Linköping, 13:15 (English)
Available from: 2015-06-22 Created: 2015-06-22 Last updated: 2015-12-10Bibliographically approved

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