Skip to main content
SpringerLink
Log in

A predictive driving control strategy of electric vehicles for energy saving

  • Published:
International Journal of Precision Engineering and Manufacturing Aims and scope Submit manuscript

Abstract

The driving route of a vehicle depends on the traffic condition and road condition in which the vehicle is operating and the driver’s behavior. Different driving route will result in different energy consumption. It is very helpful for the vehicle energy saving if the most energy-efficient driving route is obtained based on the traffic preview information and provided to the drivers. This paper presents a predictive driving control strategy for pure electric vehicles for electrical energy saving. The strategy is established based on the optimal control theory and the traffic preview information in which the maximum and minimum vehicle velocity profiles for a traffic preview period and the route length over the period are included. The information is assumed to be acquired from Global Positioning System and Intelligent Transportation System. The proposed driving control strategy is implemented in a computer simulation environment for an electric vehicle and the simulation results of the strategy are compared to those of three benchmark cases. It is concluded that the battery energy of the electric vehicle is saved around 12.1%, 12.8%, and 13.8% by the proposed strategy compared to each benchmark case.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

v veh :

vehicle velocity

a veh :

vehicle acceleration

J :

performance measure

N :

prediction period

P bat,inn :

battery inner electrochemical power

P bat,ter :

battery power at terminals

I :

battery current

R :

battery internal resistance

v min :

predicted vehicle minimum velocity

v max :

predicted vehicle maximum velocity

a min :

predicted vehicle minimum acceleration

a max :

predicted vehicle maximum acceleration

L :

preview route length

H :

Hamiltonian

p :

costate

Q bat :

battery capacity

V :

battery open circuit voltage

References

  1. Manzie, C., Watson, H., and Halgamuge, S., “Fuel Economy Improvements for Urban Driving: Hybrid vs. Intelligent Vehicles,” Transportation Research Part C: Emerging Technologies, Vol. 15, No. 1, pp. 1–16, 2007.

    Article  Google Scholar 

  2. Kim, T., Manzie, C., and Watson, H., “Fuel Economy Benefits of Look-Ahead Capability in a Mild Hybrid Configuration,” Proc. of the 17th IFAC World Congress, Vol. 8, pp. 5646–5651, 2008.

    Google Scholar 

  3. Kim, T. S., Manzie, C., and Sharma, R., “Model Predictive Control of Velocity and Torque Split in a Parallel Hybrid Vehicle,” Proc. of IEEE International Conference on Systems, Man and Cybernetics, pp. 2014–2019, 2009.

    Google Scholar 

  4. Manzie, C., Kim, T. S., and Sharma, R., “Optimal Use of Telemetry by Parallel Hybrid Vehicles in Urban Driving,” Transportation Research Part C: Emerging Technologies, Vol. 25, pp. 134–151, 2012.

    Article  Google Scholar 

  5. Ngo, D. V., Hofman, T., Steinbuch, M., and Serrarens, A. F., “An Optimal Control-based Algorithm for Hybrid Electric Vehicle using Preview Route Information,” Proc. of American Control Conference (ACC), pp. 5818–5823, 2010.

    Google Scholar 

  6. Kirk, D. E., “Optimal Control Theory,” Prentice-hall, pp. 227–240, 1970.

    Google Scholar 

  7. Serrao, L. and Rizzoni, G., “Optimal Control of Power Split for a Hybrid Electric Refuse Vehicle,” Proc. of the American Control Conference, pp. 4498–4503, 2008.

    Google Scholar 

  8. Kim, N. W., Cha, S. W., and Peng, H., “Optimal Control of Hybrid Electric Vehicles based on Pontryagin's Minimum Principle,” IEEE Transactions on Control Systems Technology, Vol. 19, No. 5, pp. 1279–1287, 2011.

    Article  Google Scholar 

  9. Zheng, C. H., Kim, N. W., and Cha, S. W., “Optimal Control in the Power Management of Fuel Cell Hybrid Vehicles,” International Journal of Hydrogen Energy, Vol. 37, No. 1, pp. 655–663, 2012.

    Article  Google Scholar 

  10. Zheng, C. H., Oh, C. E., Park, Y. I., and Cha, S. W., “Fuel Economy Evaluation of Fuel Cell Hybrid Vehicles based on Equivalent Fuel Consumption,” International Journal of Hydrogen Energy, Vol. 37, No. 2, pp. 1790–1796, 2012.

    Article  Google Scholar 

  11. Zheng, C., Cha, S. W., Park, Y. I., Lim, W. S., and Xu, G., “PMPbased Power Management Strategy of Fuel Cell Hybrid Vehicles Considering Multi-Objective Optimization,” Int. J. Precis. Eng. Manuf., Vol. 14, No. 5, pp. 845–853, 2013.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Avenue, Shenzhen University Town, Shenzhen, China, 518055

    Chunhua Zheng

  2. School of electronics and information, Tongji University, 4800 Cao’an HWY, Shanghai, China, 201804

    Guoqing Xu

  3. Mae Department, The Chinese University of Hong Kong, N.T., Hong Kong, China, 999077

    Guoqing Xu

  4. School of Mechanical and Aerospace Engineering/SNU-IAMD, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, South Korea, 151-742

    Suk Won Cha

  5. Technical Division, Shenzhen Sinopoly Battery Limited, Shenzhen, China, 518054

    Quan Liang

Authors
  1. Chunhua Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guoqing Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Suk Won Cha
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Quan Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zheng, C., Xu, G., Cha, S.W. et al. A predictive driving control strategy of electric vehicles for energy saving. Int. J. Precis. Eng. Manuf. 16, 197–202 (2015). https://doi.org/10.1007/s12541-015-0026-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12541-015-0026-0

Keywords

Search

Navigation