Skip to main content
SpringerLink
Log in

Direct yaw moment control for distributed drive electric vehicle handling performance improvement

  • Transport Engineering
  • Published:
Chinese Journal of Mechanical Engineering Submit manuscript

Abstract

For a distributed drive electric vehicle (DDEV) driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. And direct yaw-moment control (DYC) has been widely studied and applied to vehicle stability control. Good vehicle handling performance: quick yaw rate transient response, small overshoot, high steady yaw rate gain, etc, is required by drivers under normal conditions, which is less concerned, however. Based on the hierarchical control methodology, a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed. The upper-loop control system consists of two parts: a state feedback controller, which aims to realize the ideal transient response of yaw rate, with a vehicle sideslip angle observer; and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain. Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors, the integrated time and absolute error (ITAE) function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix. Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method: yaw rate rising time is reduced, steady yaw rate gain is increased, vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced. The control system improves vehicle handling performance under normal conditions in both transient and steady response. State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

References

  1. SHIBAHATA Y, SHIMADA K, TOMARI T. Improvement of vehicle maneuverability by direct yaw moment control[J]. Vehicle System Dynamics, 1993, 22(516): 465–481.

    Article  Google Scholar 

  2. YANG P, XIONG L, YU Z, et al. Motor/hydraulic systems combined stability control strategy for distributed electric drive vehicle[C]//AVEC’14 12th International Symposium on Advanced Vehicle Control, Tokyo, Japan, September 22–26, 2014: 421–424.

    Google Scholar 

  3. HORI Y. Future vehicle driven by electricity and control-research on four-wheel-motored“ UOT Electric March II”[J]. Industrial Electronics, IEEE Transactions on, 2004, 51(5): 954–962.

    Article  MathSciNet  Google Scholar 

  4. YU Z, FENG Y, XIONG L. Review on vehicle dynamics control of distributed drive electric vehicle[J]. Journal of Mechanical Engineering, 2013, 49(8): 105–114. (in Chinese)

    Article  Google Scholar 

  5. IKUSHIMA, SAWASE: A study on the effect of active yaw moment control[G]. SAE Paper 950303, 1995.

    Google Scholar 

  6. ONO E, HATTORI Y, MURAGISHI Y, et al. Vehicle dynamics integrated control for four-wheel-distributed steering and four-wheel-distributed traction/braking systems[J]. Vehicle System Dynamics, 2006, 44(2): 139–151.

    Article  Google Scholar 

  7. SHINO M, NAGAI M. Independent wheel torque control of small-scale electric vehicle for handling and stability improvement[J]. JSAE Review, 2003, 24(4): 449–456.

    Article  Google Scholar 

  8. KIM J, PARK C, HWANG S, et al. Control algorithm for an independent motor-drive vehicle[J]. IEEE Transactions on Vehicular Technology, 2010, 59(7): 3213–3222.

    Article  Google Scholar 

  9. XIONG L, YU Z, WANG Y, et al. Vehicle dynamics control of four in-wheel motor drive electric vehicle using gain scheduling based on tyre cornering stiffness estimation[J]. Vehicle System Dynamics, 2012, 50(6): 831–846.

    Article  Google Scholar 

  10. HE P, HORI Y. Optimum traction force distribution for stability improvement of 4WD EV in critical driving condition[C]//9th IEEE International Workshop on Advanced Motion Control, Istanbul, Turkey, 2006: 596–601.

    Google Scholar 

  11. SHINO M, NAGAI M. Yaw-moment control of electric vehicle for improving handling and stability[J]. JSAE Review, 2001, 22(4): 473–480.

    Article  Google Scholar 

  12. SHINO M, NAGAI M. Independent wheel torque control of small-scale electric vehicle for handling and stability improvement[J]. JSAE Review, 2003, 24(4): 449–456.

    Article  Google Scholar 

  13. KIM D, KIM C, KIM S, et al. Development of adaptive direct yaw-moment control method for electric vehicle based on identification of yaw-rate model[C]//2011 IEEE Intelligent Vehicles Symposium (IV), Baden-Baden, Germany, June 5–9, 2011: 1098–1103.

    Chapter  Google Scholar 

  14. MITSCHKE M, WALLENTOWITZ H. Dynamik der Kraftfahrzeuge[M]. Berlin: Springer, 2003.

    Google Scholar 

  15. DORF R, BISHOP R. Modern control systems[M]. 11th ed. Beijing: Pearson, 2011.

    MATH  Google Scholar 

  16. FENG Y, YU Z, XIONG L, et al. Torque vectoring control for distributed drive electric vehicle based on state variable feedback[C]//SAE 2014 World Congress and Exhibition, Detroit, USA, April 8–10, 2014: SAE Paper 2014-01-0155.

    Google Scholar 

  17. AWOUDA A, MAMAT R. New PID tuning rule using ITAE criteria[J]. International Journal of Engineering, 2010, 3(6): 597–608.

    Google Scholar 

  18. GUO K, FU H, DING H. Estimation of CG sideslip angle based on extended Kalman filter[J]. Automobile Technology, 2009(4): 1–3, 44. (in Chinese)

    Google Scholar 

  19. HIEMER M. Model based detection and reconstruction of road traffic accidents[M]. Karlsruhe: Universitätsverlag Karlsruhe, 2004.

    Google Scholar 

  20. GAO X, YU Z, NEUBECK J, et al. Sideslip angle estimation based on input-output linearization with tire-road friction adaptation[J]. Vehicle System Dynamics, 2010, 48(2): 217–234.

    Article  Google Scholar 

  21. GB/T 6323-1994. Controllability and stability test procedure for automobile[S]. Beijing: Standardization Administration of the People’s Republic of China, 1994. (in Chinese)

    Google Scholar 

  22. ISO 3888-2:2002. Passenger cars-Test track for severe lane-change maneuver-Part 2: Obstacle avoidance[S]. London: British Standards Institution, 2003.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Automotive Studies, Tongji University, Shanghai, 201804, China

    Zhuoping Yu, Bo Leng, Lu Xiong & Fenmiao Shi

  2. Pan Asia Technical Automotive Center Co., Ltd., Shanghai, 201201, China

    Yuan Feng

Authors
  1. Zhuoping Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bo Leng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lu Xiong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yuan Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Fenmiao Shi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lu Xiong.

Additional information

Supported by National Basic Research Program of China (973 Program, Grant No. 2011CB711200), National Science and Technology Support Program of China (Grant No. 2015BAG17B00), and National Natural Science Foundation of China (Grant No. 51475333)

YU Zhuoping, born in 1960, is currently a professor at School of Automotive Studies, Tongji University, China. His research interests include vehicle dynamics and control, intelligent vehicle and parameter estimation.

LENG Bo, born in 1991, is currently a PhD candidate at School of Automotive Studies, Tongji University, China. He received his bachelor degree from Tongji University, China, in 2014. His research interests include vehicle dynamics and control.

XIONG Lu, born in 1978, is currently an associate professor at School of Automotive Studies, Tongji University, China. His research interests include vehicle dynamics and control, unmanned ground vehicle motion control and chassis system design and development.

FENG Yuan, born in 1987, received his doctor degree from Tongji University, China, in 2015. His research interests include vehicle dynamics and control, parameter estimation.

SHI Fenmiao, born in 1988, received her master degree from Tongji University, China, in 2014. Her research interests include vehicle dynamics and control.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yu, Z., Leng, B., Xiong, L. et al. Direct yaw moment control for distributed drive electric vehicle handling performance improvement. Chin. J. Mech. Eng. 29, 486–497 (2016). https://doi.org/10.3901/CJME.2016.0314.031

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3901/CJME.2016.0314.031

Keywords

Search

Navigation