http://iet.metastore.ingenta.com
1887

Method for estimating the energy consumption of electric vehicles and plug-in hybrid electric vehicles under real-world driving conditions

Method for estimating the energy consumption of electric vehicles and plug-in hybrid electric vehicles under real-world driving conditions

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Intelligent Transport Systems — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This study presents a novel framework by which the energy consumption of an electric vehicle (EV) or the zero-emissions range of a plug-in hybrid electric vehicle (PHEV) may be predicted over a route. The proposed energy prediction framework employs a neural network and may be used either ‘off-line’ for better estimating the real-world range of the vehicle or ‘on-line’ integrated within the vehicle's energy management control system. The authors propose that this approach provides a more robust representation of the energy consumption of the target EVs compared to standard legislative test procedures. This is particularly pertinent for vehicle fleet operators that may use EVs within a specific environment, such as inner-city public transport or the use of urban delivery vehicles. Experimental results highlight variations in EV range in the order of 50% when different levels of traffic congestion and road type are included in the analysis. The ability to estimate the energy requirements of the vehicle over a given route is also a pre-requisite for using an efficient charge blended control strategy within a PHEV. Experimental results show an accuracy within 20–30% when comparing predicted and measured energy consumptions for over 800 different real-world EV journeys.

References

    1. 1)
      • C.C. Chan .
        1. Chan, C.C.: ‘The state of the art of electric, hybrid, and fuel cell vehicles’, Proc. IEEE, 2007, 95, (4), pp. 704718.
        . Proc. IEEE , 4 , 704 - 718
    2. 2)
      • (2011)
        2. ICCT: ‘Global Light-duty vehicles: fuel economy and greenhouse gas emissions standards’ (International Council on Clean Transportation, 2011).
        .
    3. 3)
      • S. Heckeroth . (2006)
        3. Heckeroth, S.: ‘The struggle for clean transportation’ (Automotive Industries AI, 2006).
        .
    4. 4)
      • V. Srinivasan .
        4. Srinivasan, V.: ‘Batteries for vehicular applications’. AIP Conf. Proc., California, 2008, vol. 1044, pp. 283296.
        . AIP Conf. Proc. , 283 - 296
    5. 5)
      • G. Standley , J. Marco .
        5. Standley, G., Marco, J.: ‘The impact of vehicle usage and recharging infrastructure on the energy storage requirements of a plug-in hybrid electric vehicle’, Int. J. Electr. Hybrid Veh., 2010, 2, (3), pp. 222239.
        . Int. J. Electr. Hybrid Veh. , 3 , 222 - 239
    6. 6)
      • L. Browning , S. Unnasch .
        6. Browning, L., Unnasch, S.: ‘Hybrid electric vehicle commercialization issues’. Proc. 16th Annual Battery Conf. Applications and Advances, California, 2001, pp. 45.
        . Proc. 16th Annual Battery Conf. Applications and Advances , 45
    7. 7)
      • J. Hellgren , J. Groot .
        7. Hellgren, J., Groot, J.: ‘Energy storage system optimisation of a plug-in HEV’, Int. J. Electr. Hybrid Veh., 2008, 1, (3), pp. 319331.
        . Int. J. Electr. Hybrid Veh. , 3 , 319 - 331
    8. 8)
      • C.S.N. Shiau , C. Samaras , R. Hauffe , J.J. Michalek .
        8. Shiau, C.S.N., Samaras, C., Hauffe, R., Michalek, J.J.: ‘Impact of battery weight and charging patterns on the economic and environmental benefits of plug-in hybrid vehicles’, Energy Policy, 2009, 37, (7), pp. 26532663.
        . Energy Policy , 7 , 2653 - 2663
    9. 9)
      • 9. unece.org. (2011, Last Accessed January) Regulation 101 – Battery electric vehicles with regard to specific requirements for construction and functional safety. Available at http://www.unece.org/trans/main/wp29/wp29regs101-120.html.
        .
    10. 10)
      • E. Ericsson .
        10. Ericsson, E.: ‘Independent driving pattern factors and their influence on fuel-use and exhaust emission factors’, Transp. Res. Part D, Transp. Environ., 2001, 6, (5), pp. 325345.
        . Transp. Res. Part D, Transp. Environ. , 5 , 325 - 345
    11. 11)
      • M. André .
        11. André, M.: ‘The ARTEMIS European driving cycles for measuring car pollutant emissions’, Sci. Total Environ., 2004, 334–335, pp. 7384.
        . Sci. Total Environ. , 73 - 84
    12. 12)
      • S.H. Kamble , T.V. Mathew , G.K. Sharma .
        12. Kamble, S.H., Mathew, T.V., Sharma, G.K.: ‘Development of real-world driving cycle: case study of Pune, India’, Transp. Res. Part D: Transp. Environ., 2009, 14, pp. 132140.
        . Transp. Res. Part D: Transp. Environ. , 132 - 140
    13. 13)
      • D. Vangi , A. Virga .
        13. Vangi, D., Virga, A.: ‘Evaluation of energy-saving driving styles for bus drivers’, Proc. Inst. Mech. Eng., Part D, J. Automob. Eng., 2003, 217, (4), pp. 299305.
        . Proc. Inst. Mech. Eng., Part D, J. Automob. Eng. , 4 , 299 - 305
    14. 14)
      • I. De Vlieger .
        14. De Vlieger, I.: ‘On board emission and fuel consumption measurement campaign on petrol-driven passenger cars’, Atmos. Environ., 1997, 31, (22), pp. 37533761.
        . Atmos. Environ. , 22 , 3753 - 3761
    15. 15)
      • D.A. Howey , R.F. Martinez-Botas , B. Cussons , L. Lytton .
        15. Howey, D.A., Martinez-Botas, R.F., Cussons, B., Lytton, L.: ‘Comparative measurements of the energy consumption of 51 electric, hybrid and internal combustion engine vehicles’, Transp. Res. Part D: Transp. Environ., 2011, 16, (6), pp. 459464.
        . Transp. Res. Part D: Transp. Environ. , 6 , 459 - 464
    16. 16)
      • B.Y. Liaw , M. Dubarry .
        16. Liaw, B.Y., Dubarry, M.: ‘From driving cycle analysis to understanding battery performance in real-life electric hybrid vehicle operation’, J. Power Sour., 2007, 174, (1), pp. 7688.
        . J. Power Sour. , 1 , 76 - 88
    17. 17)
      • N. Butcher , C. Fell .
        17. Butcher, N., Fell, C.: ‘CABLED vehicle demonstrator trial in West Midlands, UK’. Hybrid and Electric Vehicles Conf., Warwick, 2011, pp. 108114.
        . Hybrid and Electric Vehicles Conf. , 108 - 114
    18. 18)
      • A. Everett , C. Walsh , K. Smith , M. Burgess , M. Harris .
        18. Everett, A., Walsh, C., Smith, K., Burgess, M., Harris, M.: ‘Ultra low carbon vehicle demonstrator programme’. Hybrid and Electric Vehicles Conf., Warwick, 2011, pp. 8797.
        . Hybrid and Electric Vehicles Conf. , 87 - 97
    19. 19)
      • A.D. Abdollahi .
        19. Abdollahi, A.D.: ‘An intelligent control strategy in a parallel hybrid vehicle’. IEEE Conf. on Electric and Hybrid Vehicles, Pune, 2006, pp. 12.
        . IEEE Conf. on Electric and Hybrid Vehicles , 1 - 2
    20. 20)
      • T. Markel , A. Simpson .
        20. Markel, T., Simpson, A.: ‘Plug-in hybrid electric vehicle energy storage system design’. Advanced Automotive Battery Conf., Baltimore, May 2006, pp. 19.
        . Advanced Automotive Battery Conf. , 1 - 9
    21. 21)
      • J. Lin , D.A. Niemeier .
        21. Lin, J., Niemeier, D.A.: ‘Regional driving characteristics, regional driving cycles’, Transp. Res. Part D: Transp. Environ., 2003, 8, (5), pp. 361381.
        . Transp. Res. Part D: Transp. Environ. , 5 , 361 - 381
    22. 22)
      • 22. ordnancesurvey. (2011, Last Accessed March) Road Type ESRI Shape Files. Available at http://www.ordnancesurvey.co.uk.
        .
    23. 23)
      • G. Standley . (2009)
        23. Standley, G.: ‘The classification of driving events and driving styles based on the measurement of vehicle parameters’ (Cranfield University, Department of Automobile Engineering, 2009).
        .
    24. 24)
      • Y.L. Murphey , Z.H. Chen , L. Kiliaris .
        24. Murphey, Y.L., Chen, Z.H., Kiliaris, L., , et al.: ‘Neural learning of driving environment prediction for vehicle power management’. IEEE Int. Joint Conf. Neural Networks, Hong Kong, June 2008, pp. 37553761.
        . IEEE Int. Joint Conf. Neural Networks , 3755 - 3761
    25. 25)
      • P.W. Newman , J.R. Kenworthy , T.J. Lyons .
        25. Newman, P.W., Kenworthy, J.R., Lyons, T.J.: ‘The ecology of urban driving II–driving cycles across a city: their validation and implications’, Transp. Res. Part A, Policy Pract., 1992, 26, (3), pp. 273290.
        . Transp. Res. Part A, Policy Pract. , 3 , 273 - 290
    26. 26)
      • T. Kohonen .
        26. Kohonen, T.: ‘The self-organizing map’, Proc. IEEE, 1990, 78, (9), pp. 14641480.
        . Proc. IEEE , 9 , 1464 - 1480
    27. 27)
      • M. Contestabile , G.J. Offer , R. Slade , F. Jaeger , M. Thoennesc .
        27. Contestabile, M., Offer, G.J., Slade, R., Jaeger, F., Thoennesc, M.: ‘Battery electric vehicles, hydrogen fuel cells and biofuels. Which will be the winner?’, Energy Environ. Sci., 2011, 4, (10), pp. 37543772.
        . Energy Environ. Sci. , 10 , 3754 - 3772
    28. 28)
      • J.P. McTague , R.M. van Druten . (2001)
        28. McTague, J.P., van Druten, R.M.: ‘The costumer, the environment and the gasoline powered vehicle: transmission design of the zero inertia powertrain’. PhD thesis, Technische Universiteit Eindhoven, 2001.
        .
    29. 29)
      • S.J. Moura , D.S. Callaway , H.K. Fathy , J.L. Stein .
        29. Moura, S.J., Callaway, D.S., Fathy, H.K., Stein, J.L.: ‘Impact of battery sizing on stochastic optimal power management in plug-in hybrid electric vehicles’. IEEE Int. Conf. Vehicular Electronics and Safety, Colombus, September 2008, pp. 96102.
        . IEEE Int. Conf. Vehicular Electronics and Safety , 96 - 102
    30. 30)
      • C.P. Quigley . (2011)
        30. Quigley, C.P.: ‘The use of vehicle navigation information and prediction of journey characteristics for the optimal control of hybrid and electric vehicles’ (SAE, 2011).
        .
    31. 31)
      • R. Shankar , J. Marco , F. Assadian .
        31. Shankar, R., Marco, J., Assadian, F.: ‘A methodology to determine drivetrain efficiency based on external environment’. IEEE Int. Electric Vehicle Conf., 2012, pp. 16.
        . IEEE Int. Electric Vehicle Conf. , 1 - 6
    32. 32)
      • W.T. Miller , R.P. Hewes , F.H. Glanz , L.G. Kraft .
        32. Miller, W.T.III, Hewes, R.P., Glanz, F.H., Kraft, L.G.III: ‘Real-time dynamic control of an industrial manipulator using a neural network-based learning controller’, IEEE Trans. Robot. Autom., 1990, 6, (1), pp. 19.
        . IEEE Trans. Robot. Autom. , 1 , 1 - 9
    33. 33)
      • N. Funabiki , Y. Takefuji .
        33. Funabiki, N., Takefuji, Y.: ‘A neural network parallel algorithm for channel assignment problems in cellular radio networks’, IEEE Trans. Veh. Technol., 1992, 41, (4), pp. 430437.
        . IEEE Trans. Veh. Technol. , 4 , 430 - 437
    34. 34)
      • C.P. Quigley , R.J. Ball , A.M. Vinsome , R.P. Jones .
        34. Quigley, C.P., Ball, R.J., Vinsome, A.M., Jones, R.P.: ‘Predicting journey parameters for the intelligent control of a hybrid electric vehicle’. Proc. 1996 IEEE Int. Symp. Intelligent Control, Dearborn, 1996, pp. 402407.
        . Proc. 1996 IEEE Int. Symp. Intelligent Control , 402 - 407
    35. 35)
      • S. Jung , S.S. Kim .
        35. Jung, S., Kim, S.S.: ‘Hardware implementation of a real-time neural network controller with a DSP and an FPGA for nonlinear systems’, IEEE Trans. Ind. Electron., 2007, 54, (1), pp. 265271.
        . IEEE Trans. Ind. Electron. , 1 , 265 - 271
    36. 36)
      • H. Li , B. Ma , C. Lee .
        36. Li, H., Ma, B., Lee, C.: ‘A vector space modeling approach to spoken language identification’, IEEE Trans. Audio, Speech, Lang. Process., 2007, 15, (1), pp. 271284.
        . IEEE Trans. Audio, Speech, Lang. Process. , 1 , 271 - 284
    37. 37)
      • A. Waibel .
        37. Waibel, A.: ‘Modular construction of time-delay neural networks for speech recognition’, Neural Comput., 1989, 1, (1), pp. 3946.
        . Neural Comput. , 1 , 39 - 46
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-its.2012.0114
Loading

Related content

content/journals/10.1049/iet-its.2012.0114
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address