Optimization of automobile active suspension system using minimal order

Amertet Finecomes, Sairoel; Gebre, Fisseha L.; Mesene, Abush M.; Abebaw, Solomon · 2022 · Crossref

DOI: 10.11591/ijece.v12i3.pp2378-2392

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Summary

This paper addresses the optimization of automobile active suspension systems to enhance ride comfort, vehicle stability, and handling. The authors identify a gap in existing research where controllers are often designed without considering actuator dynamics or using reduced-order models to minimize sensor requirements. The study proposes a Linear Quadratic Regulator (LQR) control scheme for a full-car suspension model that incorporates actuator dynamics. To address the practical limitations of high-order models requiring numerous sensors, the authors apply a minimal realization technique to reduce the system’s state space from 14 to 8 variables without altering the system's dynamic behavior. The methodology involves developing a mathematical model of the full vehicle suspension, accounting for bounce, pitch, roll, and wheel displacements. The authors utilized MATLAB/Simulink for simulation and controller design. The original 14-state model was reduced to an 8-state minimal realization model, which was verified to be fully controllable and observable. An LQR controller was designed by minimizing a quadratic cost function, with weighting matrices Q and R tuned to penalize state deviations and control effort, respectively. The performance of this controller was evaluated against passive suspension systems and active systems without actuator dynamics under various road profiles, including single and double bump disturbances. Simulation results demonstrate that the proposed LQR controller with actuator dynamics significantly outperforms both passive systems and active systems excluding actuator dynamics. Specifically, the inclusion of actuator dynamics resulted in a 28.57% reduction in the peak vertical velocity compared to the LQR without actuator dynamics. In terms of chassis displacement, the active system with actuator dynamics reduced peak values by 25% compared to passive suspension and by 18.18% compared to the active system without actuator dynamics. Settling times were also drastically improved; for chassis displacement, the settling time decreased from 4.95 seconds in passive systems to 1.9 seconds in the proposed active system, representing a 61.61% improvement. Similar improvements were observed for pitch angle and angular velocity metrics. The significance of this work lies in demonstrating that incorporating actuator dynamics into the control design yields superior performance in terms of vibration isolation and stability. Furthermore, the use of minimal realization techniques allows for a more practical implementation by reducing the number of required sensors and computational complexity. The study concludes that the proposed control scheme effectively improves both ride comfort and vehicle stability, offering a viable approach for designing efficient active suspension systems.

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