access icon openaccess Routing systems to extend the driving range of electric vehicles

This study develops a more accurate range prediction for electric vehicles (EVs) resulting in a routing system that could extend the driving range of EVs through calculating the minimum energy route to a destination, based on topography and traffic conditions of the road network. Energy expenditure of EVs under different conditions is derived using high-resolution real-world data from the SwitchEV trial. The SwitchEV trial has recorded the second-by-second driving events of 44 all-electric vehicles covering a distance of over 400 000 miles across the North East of England, between March 2010 and May 2013. Linear models are used to determine the energy expenditure equations and Dijkstra's graph search algorithm is used to find the route minimising energy consumption. The results from this study are being used to better inform the decisions of the smart navigation and eco-driving assist systems in EVs, thus improving the intelligent transport systems provisions for EV drivers. The outputs of the research are twofold: providing more accurate estimations of available range and supporting drivers’ optimisation of energy consumption and as a result extending their driving range. Both outputs could help mitigate range anxiety and make EVs a more attractive proposition to potential customers.

Inspec keywords: graph theory; search problems; road traffic; electric vehicles; vehicle routing

Other keywords: high-resolution real-world data; smart navigation; battery drain; linear models; SwitchEV trial; EV driving range; intelligent transport systems; driver optimisation; Dijkstra graph search algorithm; eco-driving assist systems; time-stamp; energy regeneration; range anxiety mitigation; energy consumption; traffic conditions; Global Positioning System; road network topography; energy expenditure equations; electric vehicle routing systems

Subjects: Combinatorial mathematics; Optimisation techniques; Systems theory applications in transportation

References

    1. 1)
      • 25. Dijkstra, E.W.: ‘A note on two problems in connexion with graphs’, Numer. Math., 1959, 1, (1), pp. 269271 (doi: 10.1007/BF01386390).
    2. 2)
      • 2. HM Government: ‘Climate change act 2008’ (Her Majesty's Stationery Office, 2008).
    3. 3)
      • 3. HM Government: ‘The carbon plan: delivering our low carbon future’ (Her Majesty's Stationery Office, 2011).
    4. 4)
      • 14. Franke, T., Krems, J.F.: ‘Interacting with limited mobility resources: psychological range levels in electric vehicle use’, Transport. Res. A: Pol., 2013, 48, pp. 109122.
    5. 5)
      • 27. http://www.smartcem-project.eu/, accessed July 2013.
    6. 6)
      • 22. Department for Transport: ‘Car purchasing behaviour and the market for EVS – insights from the existing evidence base’. Charging Ahead – An Electric Vehicle Infrastructure Best Practice Exchange Workshop, London, UK, November 2012.
    7. 7)
      • 20. Gonder, J.: ‘Route-based control of hybrid electric vehicles’. SAE 2008 World Congress, Detroit, USA, April 2008.
    8. 8)
      • 24. Larminie, J., Lowry, J.: ‘Electric vehicle technology explained’ (Wiley, 2003).
    9. 9)
      • 16. Mensing, F., Bideaux, E., Trigui, R., Tattegrain, H.: ‘Trajectory optimization for eco-driving taking into account traffic constraints’, Transport. Res. D – Tr. E, 2013, 18, pp. 5561 (doi: 10.1016/j.trd.2012.10.003).
    10. 10)
      • 7. HM Government: ‘Making the connection: the plug-in vehicle infrastructure strategy’ (Her Majesty's Stationery Office, 2011).
    11. 11)
      • 8. The Society of Motor Manufacturers and Traders (SMMT): ‘New car CO2 report 2012’ (London, 2013).
    12. 12)
      • 10. Daziano, R.A.: ‘Conditional-logit Bayes estimators for consumer valuation of electric vehicle driving range’, Resour. Energy Econ., 2013, 35, (3), pp. 429450 (doi: 10.1016/j.reseneeco.2013.05.001).
    13. 13)
      • 26. MasterMap ITN layer [GML geospatial data], Ordnance Survey, GB. Using: EDINA Digimap Ordnance Survey Service, http://digimap.edina.ac.uk/digimap/home, accessed May 2012.
    14. 14)
      • 5. Energy Technology Institute: ‘Transport – an affordable and secure energy for light vehicles in the UK’ (Loughborough, 2013).
    15. 15)
      • 17. Saboohi, Y., Farzaneh, H.: ‘Model for developing an eco-driving strategy of a passenger vehicle based on the least fuel consumption’, Appl. Energy, 2009, 86, (10), pp. 19251932 (doi: 10.1016/j.apenergy.2008.12.017).
    16. 16)
      • 18. Ericsson, E., Larsson, H., Brundell-Freij, K.: ‘Optimizing route choice for lowest fuel consumption – potential effects of a new driver support tool’, Transport. Res. C – Emerg. Technol., 2006, 14, pp. 369383 (doi: 10.1016/j.trc.2006.10.001).
    17. 17)
      • 19. Sahlholm, P., Henrik Johansson, K.: ‘Road grade estimation for look-ahead vehicle control using multiple measurement runs’, Control Eng. Pract., 2010, 18, (11), pp. 13281341 (doi: 10.1016/j.conengprac.2009.09.007).
    18. 18)
      • 6. Steinhilber, S., Wells, P., Thankappan, S.: ‘Socio-technical inertia: understanding the barriers to electric vehicles’, Energy Policy, 2013, 60, pp. 531539 (doi: 10.1016/j.enpol.2013.04.076).
    19. 19)
      • 1. Stern, N.: ‘The economics of climate change – the stern review’ (Cambridge University Press, 2006).
    20. 20)
      • 4. King, J.: ‘King review of low carbon cars’ (Her Majesty's Stationery Office, 2010).
    21. 21)
      • 11. Khan, M., Kockelman, K.M.: ‘Predicting the market potential of plug-in electric vehicles using multiday GPS data’, Energy Policy, 2012, 46, pp. 225233 (doi: 10.1016/j.enpol.2012.03.055).
    22. 22)
      • 13. Dijk, M., Orsato, R.J., Kemp, R.: ‘The emergence of an electric mobility trajectory’, Energy Policy, 2013, 52, pp. 135145 (doi: 10.1016/j.enpol.2012.04.024).
    23. 23)
      • 23. Neaimeh, M., Higgins, C., Hill, G.A., Hübner, Y., Blythe, P.T.: ‘Investigating the effects of topology on the driving efficiency of electric vehicles to better inform smart navigation’. Road Traffic Information and Control 2012 Conf., London, UK, September 2012.
    24. 24)
      • 9. Hübner, Y., Blythe, P.T., Higgins, C.A., Hill, G.A., Neaimeh, M.: ‘Use of its to overcome barriers to the introduction of electric vehicles in the North East of England’. 19th World Congress on Intelligent Transport Systems, Vienna, Austria, October 2012.
    25. 25)
      • 21. http://www.switchev.co.uk/, accessed July 2013.
    26. 26)
      • 15. Huebner, Y.: ‘Electromobility roadmap’ (ERTICO – ITS Europe, 2012).
    27. 27)
      • 12. Browne, D., O'Mahony, M., Caulfield, B.: ‘How should barriers to alternative fuels and vehicles be classified and potential policies to promote innovative technologies be evaluated?’, J. Clean. Prod., 2012, 35, pp. 140151 (doi: 10.1016/j.jclepro.2012.05.019).
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-its.2013.0122
Loading

Related content

content/journals/10.1049/iet-its.2013.0122
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading