Research Papers

Wheel Slip Control Using Sliding-Mode Technique and Maximum Transmissible Torque Estimation

[+] Author and Article Information
Jianqiu Li

State Key Laboratory of Automotive
Safety and Energy,
Tsinghua University,
Beijing 100084, China
e-mail: lijianqiu@tsinghua.edu.cn

Ziyou Song, Zhibin Shuai, Liangfei Xu, Minggao Ouyang

State Key Laboratory of Automotive
Safety and Energy,
Tsinghua University,
Beijing 100084, China

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received November 22, 2014; final manuscript received July 9, 2015; published online August 14, 2015. Assoc. Editor: Junmin Wang.

J. Dyn. Sys., Meas., Control 137(11), 111010 (Aug 14, 2015) (10 pages) Paper No: DS-14-1496; doi: 10.1115/1.4031056 History: Received November 22, 2014

This paper presents the analysis and design of a novel traction control system (TCS) based on sliding-mode control (SMC) and maximum transmissible torque estimation (MTTE) technique, which is employed in four-wheel independent drive electric vehicles (EVs) without detecting the vehicle velocity and acceleration. The original MTTE technique is effective with regard to the antislip control; however, it cannot sufficiently utilize the adhesive force from the tire–road surface. In the proposed TCS algorithm, only front wheels are equipped with the MTTE technique, while rear wheels are equipped with the SMC technique. As a result, the front wheel is critically controlled by the MTTE technique. Thus, its rotary speed can be used to approximately estimate the chassis velocity and acceleration, which are key input parameters of the SMC. The rear wheel slip ratio can be therefore controlled by the SMC which is robust against uncertainties and disturbances of parameters for exploiting more transmissible friction force. In addition, the stability of MTTE is analyzed in this paper because an important parameter is neglected in the original MTTE technique. As a result, the stability condition is changed, and the MTTE is modified in the proposed TCS according to the new conclusion. A half four-wheel drive (4WD) EV model is initially built using matlab/simulink. This paper investigates the proposed TCS for various adhesive conditions involving abrupt change in road friction. Compared with the original MTTE technique, the comprehensive performance, particularly the acceleration ability, is significantly improved by the proposed controller. The simulation result validates the effectiveness and robustness of the proposed TCS.

Copyright © 2015 by ASME
Your Session has timed out. Please sign back in to continue.


Khaligh, A. , and Li, Z. , 2010, “Battery, Ultracapacitor, Fuel Cell, and Hybrid Energy Storage Systems for Electric, Hybrid Electric, Fuel Cell, and Plug-In Hybrid Electric Vehicles: State of the Art,” IEEE Trans. Veh. Technol., 59(6), pp. 2806–2814. [CrossRef]
Hori, Y. , 2004, “Future Vehicle Driven by Electricity and Control-Research on Four-Wheel-Motored ‘UOT Electric March II’,” IEEE Trans. Ind. Electron., 51(5), pp. 954–962. [CrossRef]
Maeda, K. , Fujimoto, H. , and Hori, Y. , 2012, “Four-Wheel Driving-Force Distribution Method Based on Driving Stiffness and Slip Ratio Estimation for Electric Vehicle With In-Wheel Motors,” 2012 IEEE Vehicle Power and Propulsion Conference (VPPC), Seoul, Korea, Oct. 9–12, pp. 1286–1291.
Shuai, Z. , Zhang, H. , Wang, J. , Li, J. , and Ouyang, M. , 2014, “Combined AFS and DYC Control of Four-Wheel-Independent-Drive Electric Vehicles Over CAN Network With Time-Varying Delays,” IEEE Trans. Veh. Technol., 63(2), pp. 591–602. [CrossRef]
Shuai, Z. , Zhang, H. , Wang, J. , Li, J. , and Ouyang, M. , 2014, “Lateral Motion Control for Four-Wheel-Independent-Drive Electric Vehicles Using Optimal Torque Allocation and Dynamic Message Priority Scheduling,” Control Eng. Pract., 24, pp. 55–66. [CrossRef]
Yin, D. , Oh, S. , and Hori, Y. , 2009, “A Novel Traction Control for EV Based on Maximum Transmissible Torque Estimation,” IEEE Trans. Ind. Electron., 56(6), pp. 2086–2094. [CrossRef]
Yin, D. , and Hori, Y. , 2010, “Traction Control for EV Based on Maximum Transmissible Torque Estimation,” Int. J. Intell. Transp. Syst. Res., 8(1), pp. 1–9.
Suryanarayanan, S. , and Tomizuka, M. , 2007, “Appropriate Sensor Placement for Fault-Tolerant Lane-Keeping Control of Automated Vehicles,” IEEE/ASME Trans. Mechatron., 12(4), pp. 465–471. [CrossRef]
Mutoh, N. , Hayano, Y. , Yahagi, H. , and Takita, K. , 2007, “Electric Braking Control Methods for Electric Vehicles With Independently Driven Front and Rear Wheels,” IEEE Trans. Ind. Electron., 54(2), pp. 1168–1176. [CrossRef]
Saito, T. , Fujimoto, H. , and Noguchi, T. , 2002, “Yaw-Moment Stabilization Control of Small Electric Vehicle,” Industrial Instrumentation and Control, IEE, Japan, pp. 83–88.
Fujimoto, H. , Saito, T. , and Noguchi, T. , 2004, “Motion Stabilization Control of Electric Vehicle Under Snowy Conditions Based on Yaw-Moment Observer,” 8th IEEE International Workshop on Advanced Motion Control (AMC’04), Mar. 25–28, pp. 35–40.
Shino, M. , and Nagai, M. , 2001, “Yaw-Moment Control of Electric Vehicle for Improving Handling and Stability,” JSAE Rev., 22(4), pp. 473–480. [CrossRef]
Geng, C. , Mostefai, L. , Denaï, M. , and Hori, Y. , 2009, “Direct Yaw-Moment Control of an In-Wheel-Motored Electric Vehicle Based on Body Slip Angle Fuzzy Observer,” IEEE Trans. Ind. Electron., 56(5), pp. 1411–1419. [CrossRef]
Lee, H. , and Tomizuka, M. , 2003, “Adaptive Vehicle Traction Force Control for Intelligent Vehicle Highway Systems (IVHSs),” IEEE Trans. Ind. Electron., 50(1), pp. 37–47. [CrossRef]
Chen, B. C. , Chu, C. H. , and Huang, S. J. , 2010, “Fuzzy Sliding Mode Control of Traction Control System for Electric Scooter,” 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), Yantai, Shandong, China, Aug. 10–12, Vol. 2010, pp. 691–695.
Sakai, S. I. , and Hori, Y. , 2001, “Advantage of Electric Motor for Anti-Skid Control of Electric Vehicle,” EPE J., 11(4), pp. 26–32. [CrossRef]
Akiba, T. , Shirato, R. , Fujita, T. , and Tamura, J. , 2007, “A Study of Novel Traction Control Method for Electric Motor Driven Vehicle,” Power Conversion Conference-Nagoya (PCC’07), Nagoya, Japan, Apr. 2–5, pp. 699–704.
Lin, C. M. , and Hsu, C. F. , 2003, “Neural-Network Hybrid Control for Antilock Braking Systems,” IEEE Trans. Neural Networks, 14(2), pp. 351–359. [CrossRef]
Mauer, G. F. , 1995, “A Fuzzy Logic Controller for an ABS Braking System,” IEEE Trans. Fuzzy Syst., 3(4), pp. 381–388. [CrossRef]
Jalili-Kharaajoo, M. , and Besharati, F. , 2003, “Sliding Mode Traction Control of an Electric Vehicle With Four Separate Wheel Drives,” IEEE Conference on Emerging Technologies and Factory Automation (ETFA'03), Sept. 16–19, Vol. 2, pp. 291–296.
Li, S. , Nakamura, K. , Kawabe, T. , and Morikawa, K. , 2012, “A Sliding Mode Control for Slip Ratio of Electric Vehicle,” SICE Annual Conference (SICE), pp. 1974–1979.
Subudhi, B. , and Ge, S. S. , 2012, “Sliding-Mode-Observer-Based Adaptive Slip Ratio Control for Electric and Hybrid Vehicles,” IEEE Trans. Intell. Transp. Syst., 13(4), pp. 1617–1626. [CrossRef]
Tanelli, M. , Vecchio, C. , Corno, M. , Ferrara, A. , and Savaresi, S. M. , 2009, “Traction Control for Ride-by-Wire Sport Motorcycles: A Second-Order Sliding Mode Approach,” IEEE Trans. Ind. Electron., 56(9), pp. 3347–3356. [CrossRef]
Amodeo, M. , Ferrara, A. , Terzaghi, R. , and Vecchio, C. , 2010, “Wheel Slip Control Via Second-Order Sliding-Mode Generation,” IEEE Trans. Intell. Transp. Syst., 11(1), pp. 122–131. [CrossRef]
Hamzah, N. , Sam, Y. M. , Selamat, H. , Aripin, M. K. , and Ghazali, R. , 2012, “Second Order Sliding Mode Controller for Longitudinal Wheel Slip Control,” 2012, IEEE 8th International Colloquium on Signal Processing and Its Applications (CSPA), Melaka, Mar. 23–26, pp. 138–143.
Pacejka, H. B. , and Besselink, I. J. M. , 1997, “Magic Formula Tyre Model With Transient Properties,” Veh. Syst. Dyn., 27(S1), pp. 234–249. [CrossRef]
Pacejka, H. B. , and Sharp, R. S. , 1991, “Shear Force Development by Pneumatic Tyres in Steady State Conditions: A Review of Modelling Aspects,” Veh. Syst. Dyn., 20(3–4), pp. 121–175. [CrossRef]
Rill, G. , 2006, “First Order Tire Dynamics,” III European Conference on Computational Mechanics Solids, Structures and Coupled Problems in Engineering, Lisbon, Portugal, Springer, The Netherlands, Vol. 58, p. 776.
Johansson, K. H. , and Nunes, J. L. R. , 1998, “A Multivariable Laboratory Process With an Adjustable Zero,” American Control Conference, Philadelphia, PA, June 21–26, Vol. 4, pp. 2045–2049.
Sakai, S. I. , Sado, H. , and Hori, Y. , 1999, “Motion Control in an Electric Vehicle With Four Independently Driven In-Wheel Motors,” IEEE/ASME Trans. Mechatron., 4(1), pp. 9–16. [CrossRef]
Fujii, K. , and Fujimoto, H. , 2007, “Slip Ratio Estimation and Control Based on Driving Resistance Estimation Without Vehicle Speed Detection for Electric Vehicle,” The Society of Instrument and Control Engineers, pp. 1–6.
Cao, J. Y. , Cao, B. G. , and Liu, Z. , 2006, “Driving Resistance Estimation Based on Unknown Input Observer,” J. Appl. Sci., 6(4), pp. 888–891. [CrossRef]
Li, H. Z. , Li, L. , He, L. , Kang, M. X. , Song, J. , Yu, L. Y. , and Wu, C. , 2012, “PID Plus Fuzzy Logic Method for Torque Control in Traction Control System,” Int. J. Automot. Technol., 13(3), pp. 441–450. [CrossRef]


Grahic Jump Location
Fig. 1

Dynamic longitudinal model of Micro Harry

Grahic Jump Location
Fig. 2

Typical λ– Fds curves for different road conditions [27]

Grahic Jump Location
Fig. 3

Computed relaxation length characteristics [28]

Grahic Jump Location
Fig. 4

Control schema of the proposed TCS

Grahic Jump Location
Fig. 5

Control schema of MTTE [6]

Grahic Jump Location
Fig. 6

Equivalent control system for robust stability analysis

Grahic Jump Location
Fig. 7

Prototype of modeled EV Micro Harry

Grahic Jump Location
Fig. 8

Simulation with vehicle driving on a road with varying frictions

Grahic Jump Location
Fig. 9

Simulation situation schema

Grahic Jump Location
Fig. 10

Comparison between novel TCS and original MTTE: (a) Front wheel comparison, (b) rear wheel comparison, (c) torque target, (d) longitudinal force Fd, and (e) rear wheel slip ratio control (novel TCS)

Grahic Jump Location
Fig. 11

Analysis of novel TCS robustness to EV mass variation: (a) Novel TCS robustness analysis (mass increases by 400 kg) and (b) novel TCS robustness analysis (mass decreases by 400 kg)

Grahic Jump Location
Fig. 12

Analysis of novel TCS with various sliding gain: (a) Torque target in various sliding gain KSMC and (b) rear wheel slip ratio in various sliding gain KSMC



Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In