Fuzzy sliding mode wheel slip ratio control for smart vehicle anti-lock braking system

Jinhong Sun, Xiangdang Xue, Ka Wai Eric Cheng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

30 Citations (Scopus)


With the development of in-wheel technology (IWT), the design of the electric vehicles (EV) is getting much improved. The anti-lock braking system (ABS), which is a safety benchmark for automotive braking, is particularly important. Installing the braking motor at each fixed position of the wheel improves the intelligent control of each wheel. The nonlinear ABS with robustness performance is highly needed during the vehicle's braking. The anti-lock braking controller (CAB) designed in this paper considered the well-known adhesion force, the resistance force from air and the wheel rolling friction force, which bring the vehicle model closer to the real situation. A sliding mode wheel slip ratio controller (SMWSC) is proposed to yield anti-lock control of wheels with an adaptive sliding surface. The vehicle dynamics model is established and simulated with consideration of different initial braking velocities, different vehicle masses and different road conditions. By comparing the braking effects with various CAB parameters, including stop distance, braking torque and wheel slip ratio, the SMWSC proposed in this paper has superior fast convergence and stability characteristics. Moreover, this SMWSC also has an added road-detection module, which makes the proposed braking controller more intelligent. In addition, the important brain of this proposed ABS controller is the control algorithm, which can be used in all vehicles' ABS controller design.

Original languageEnglish
Article number2501
Issue number13
Publication statusPublished - 1 Jan 2019


  • Anti-lock braking controller (CAB)
  • Anti-lock braking system (ABS)
  • Fuzzy control
  • PID control
  • Sliding mode wheel slip ratio controller (SMWSC)

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering


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