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Fuzzy Sliding Mode Wheel Slip Ratio Control for Smart Vehicle Anti-Lock Braking System

Author

Listed:
  • Jinhong Sun

    (Power Electronics Research Center, Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China)

  • Xiangdang Xue

    (Power Electronics Research Center, Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China)

  • Ka Wai Eric Cheng

    (Power Electronics Research Center, Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China)

Abstract

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.

Suggested Citation

  • Jinhong Sun & Xiangdang Xue & Ka Wai Eric Cheng, 2019. "Fuzzy Sliding Mode Wheel Slip Ratio Control for Smart Vehicle Anti-Lock Braking System," Energies, MDPI, vol. 12(13), pages 1-22, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:13:p:2501-:d:243867
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    References listed on IDEAS

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    1. Jiwei Feng & Chunjiang Bao & Jian Wu & Shuo Cheng & Guangfei Xu & Shifu Liu, 2018. "Research on Methods of Active Steering Control Based on Receding Horizon Control," Energies, MDPI, vol. 11(9), pages 1-15, August.
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    4. Yu-Fan Chen & I-Ming Chen & Joshua Chang & Tyng Liu, 2017. "Design and Analysis of a New Torque Vectoring System with a Ravigneaux Gearset for Vehicle Applications," Energies, MDPI, vol. 10(12), pages 1-16, December.
    5. Wanke Cao & Helin Liu & Cheng Lin & Yuhua Chang & Zhiyin Liu & Antoni Szumanowski, 2017. "Co-Design Based Lateral Motion Control of All-Wheel-Independent-Drive Electric Vehicles with Network Congestion," Energies, MDPI, vol. 10(10), pages 1-16, October.
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    Citations

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    Cited by:

    1. Mojtaba Ahmadieh Khanesar & David Branson, 2022. "Robust Sliding Mode Fuzzy Control of Industrial Robots Using an Extended Kalman Filter Inverse Kinematic Solver," Energies, MDPI, vol. 15(5), pages 1-17, March.
    2. Peter Girovský & Jaroslava Žilková & Ján Kaňuch, 2020. "Optimization of Vehicle Braking Distance Using a Fuzzy Controller," Energies, MDPI, vol. 13(11), pages 1-15, June.
    3. Xiangdang XUE & Ka Wai Eric CHENG & Wing Wa CHAN & Yat Chi FONG & Kin Lung Jerry KAN & Yulong FAN, 2021. "Design, Analysis and Application of Single-Wheel Test Bench for All-Electric Antilock Braking System in Electric Vehicles," Energies, MDPI, vol. 14(5), pages 1-12, February.
    4. Linfeng Lv & Juncheng Wang & Jiangqi Long, 2021. "Interval Type-2 Fuzzy Logic Anti-Lock Braking Control for Electric Vehicles under Complex Road Conditions," Sustainability, MDPI, vol. 13(20), pages 1-23, October.
    5. Raja Mazuir Raja Ahsan Shah & Richard Peter Jones & Caizhen Cheng & Alessandro Picarelli & Abd Rashid Abd Aziz & Mansour Al Qubeissi, 2021. "Model-Based Energy Path Analysis of Tip-In Event in a 2WD Vehicle with Range-Extender Electric Powertrain Architecture," Energies, MDPI, vol. 14(18), pages 1-18, September.

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