Skip to main content

Velocity Planning of an Electric Vehicle Using an Evolutionary Algorithm

  • Conference paper
Activities of Transport Telematics (TST 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 395))

Included in the following conference series:

Abstract

This paper presents an approach to planning the driving velocity of an electric vehicle. As an object of study a prototype vehicle Mushellka has been chosen. It was built to take part in the Shell Eco-marathon competition. The competition took place in May 2012 and 2013. The paper presents the results of the determined optimum velocity for the street circuit in Rotterdam. Optimizations were performed using evolutionary algorithms. The objective function was to minimize the energy consumption. The calculations were performed in Matlab Simulink. The paper describes the mathematical modelling of the vehicle, the idea and the method of route planning, as well as the use of a prototype telematic system.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dorri, M., Shamekhi, A.H.: Design and optimization of a new control strategy in a parallel hybrid electric vehicle in order to improve fuel economy. In: Proc. IMechE, Part D: J. Automobile Engineering, vol. 225

    Google Scholar 

  2. Fröberg, A., Hellström, E., Nielsen, L.: Explicit Fuel Optimal Speed Profiles for Heavy Trucks on a Set of Topographic Road Profiles

    Google Scholar 

  3. Hellström, E., Åslund, J., Nielsen, L.: Design of an efficient algorithm for fuel optimal look-ahead control, Control Engineering Practice (2010)

    Google Scholar 

  4. Hellström, E., Ivarsson, M., Aslund, J., Nielsen, L.: Look-ahead control for heavy trucks to minimize trip time and fuel consumption. Control Engineering Practice 17, 245–254 (2008)

    Article  Google Scholar 

  5. Janssenswillen, J., Swinnen, R., Wolfs, S., Slaets, P.: Optimal Dynamic Predic-tive Cruise Control for differential driven electric vehicles. In: EVS26 International Battery, Hybrid and Fuel Cell Electric Vehicle Symposium

    Google Scholar 

  6. Li, S.E., Peng, H.: Strategies to Minimize Fuel Consumption of Passenger Cars during Car-Following Scenarios. In: 2011 American Control Conference, June 29-July 1 (2011)

    Google Scholar 

  7. Sternal, K., Cholewa, A., Skarka, W., Targosz, M.: Electric vehicle for the stu-dents’ Shell Eco-marathon competition. Design of the car and telemetry system. In: Mikulski, J. (ed.) TST 2012. CCIS, vol. 329, pp. 26–33. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  8. Targosz, M.: Test bench for efficiency evaluation of belt and chain transmissions. In: XII International Technical System Degradation Conferences, Liptowski, Mikulas, Slovakia, April 3-6 (2013)

    Google Scholar 

  9. Targosz, M., Skarka, W.: Synergia metod modelowania konstrukcji na przykładzie projektu Smart Power. Cz. 1. Mechanik 86(2) (2013)

    Google Scholar 

  10. van Keulen, T., de Jager, B., Foster, D., Steinbuch, M.: Velocity Trajectory Op-timization in Hybrid Electric Trucks

    Google Scholar 

  11. Velenis, E., Tsiotras, P.: Minimum Time vs Maximum Exit Velocity Path Opti-mization During Cornering

    Google Scholar 

  12. Deb, K.: Multi-objective optimization using evolutionary algorithms. Wiley (2009)

    Google Scholar 

  13. Rutkowski, L.: Methods and techniques of artificial intelligence. PWN, Warsaw (2005) (in Polish)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Targosz, M., Szumowski, M., Skarka, W., Przystałka, P. (2013). Velocity Planning of an Electric Vehicle Using an Evolutionary Algorithm. In: Mikulski, J. (eds) Activities of Transport Telematics. TST 2013. Communications in Computer and Information Science, vol 395. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41647-7_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-41647-7_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41646-0

  • Online ISBN: 978-3-642-41647-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics