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Purpose <p>This paper addresses the problem of vibration transmission to sensitive cargo in heavy-duty vehicles. It aims to improve vibration isolation, ride comfort, and load protection by combining a semi-active secondary suspension with magnetorheological (MR) damping and road profile pre-diagnosis.</p> Methods <p>A predictive semi-active suspension architecture is proposed. The system uses an MR damper modeled with the Spencer hysteretic dynamic formulation. Road irregularities are estimated in advance through road-profile pre-diagnosis, enabling proactive damping control. The vehicle system is analyzed using MATLAB/Simulink with a 6-DOF vehicle model, and the controller adapts damping based on predicted road excitation and load sensitivity.</p> Results <p>The simulation results show a **42.79% reduction** in peak vertical acceleration, a **23.65% improvement** in ride comfort, and a **31.4% decrease** in RMS response amplitude. The proposed method also improves stability margins and response speed in nonlinear regions without chattering or control saturation.</p> Conclusion <p>Integrating MR damping with road pre-diagnosis provides an effective and practical solution for protecting fragile cargo from harmful vibration. The proposed semi-active suspension is superior to passive systems and more efficient than fully active alternatives, offering a feasible framework for cargo vehicles operating on stochastic road profiles.</p>

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Intelligent Semi-Active Secondary Suspension for Cargo Vehicles Using Road Profile Pre-Diagnosis and Magnetorheological Damping

  • 期刊论文

  • 发表日期：

    2026年5月7日

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  • Mostafa Jalalnezhad,
  • Paul Rodrigues,
  • Mohammed Al-Farouni,
  • A. K. Kareem,
  • Ramdevsinh Jhala,
  • Koushik V. Prasad,
  • Ankur Kulshreshta,
  • Gurpartap Singh

摘要

Purpose

This paper addresses the problem of vibration transmission to sensitive cargo in heavy-duty vehicles. It aims to improve vibration isolation, ride comfort, and load protection by combining a semi-active secondary suspension with magnetorheological (MR) damping and road profile pre-diagnosis.

Methods

A predictive semi-active suspension architecture is proposed. The system uses an MR damper modeled with the Spencer hysteretic dynamic formulation. Road irregularities are estimated in advance through road-profile pre-diagnosis, enabling proactive damping control. The vehicle system is analyzed using MATLAB/Simulink with a 6-DOF vehicle model, and the controller adapts damping based on predicted road excitation and load sensitivity.

Results

The simulation results show a **42.79% reduction** in peak vertical acceleration, a **23.65% improvement** in ride comfort, and a **31.4% decrease** in RMS response amplitude. The proposed method also improves stability margins and response speed in nonlinear regions without chattering or control saturation.

Conclusion

Integrating MR damping with road pre-diagnosis provides an effective and practical solution for protecting fragile cargo from harmful vibration. The proposed semi-active suspension is superior to passive systems and more efficient than fully active alternatives, offering a feasible framework for cargo vehicles operating on stochastic road profiles.