Key Takeaways & Executive Findings
- •• A novel switching control strategy balances ride comfort and handling stability in full-car suspension systems. • The 14-DOF full-car model is simplified to three 2-DOF models (vertical, pitch, roll), simplifying controller design. • The proposed rollover risk indicator enables effective multi-modal switching between comfort and stability control. • Experimental results show significant reductions in vertical, roll, and pitch accelerations (up to 14.13%) and rollover risk metrics (up to 29.96%).
Abstract
The cooperative control of ride comfort and handling stability in automobile suspension systems presents a significant challenge in intelligent chassis system design. This complexity arises from the high degrees of freedom, diverse operating conditions, and inherent trade-offs between performance metrics in full-car suspension systems. In this paper, a novel switching control strategy is proposed to better balance ride comfort and handling stability for a full-car suspension system. The system integrates a ride comfort controller and an anti-rollover controller, guided by a new rollover risk assessment indicator that requires fewer state variables. First, a vehicle suspension simplification model approach is introduced, reducing the fourteen-degree-of-freedom full-car suspension model to three two-degree-of-freedom models: vertical, pitch and roll. Based on these simplified models, vertical, roll, and pitch controllers are designed, simplifying the controller design process for full-car suspension systems. The ride comfort controller is constructed using the modal energy method in conjunction with the simplified model controllers, while the roll controller functions as the anti-rollover controller. The proposed rollover risk assessment indicator serves as the switching criterion between handling stability and ride comfort control. Experimental results demonstrate that the proposed switching control strategy effectively adapts to various road conditions, enabling the semi-active variable damping suspension system to perform multi-modal switching. Compared to a well-tuned passive suspension, vertical, roll, and pitch accelerations are reduced by 14.13%, 13.02% and 13.08%, respectively, significantly improving ride comfort. Additionally, the system effectively mitigates rollover risk, achieving reductions in roll angle, roll speed, and roll acceleration by 19.69%, 16.40%, and 29.96%, respectively, thereby greatly enhancing vehicle safety. Overall, the proposed switching control strategy achieves a successful balance between ride comfort and handling stability, enhancing overall driving performance.
1. Introduction
Vehicle handling stability and ride comfort are critical performance factors in the design of vehicle suspension and intelligent chassis systems. Handling stability ensures safe driving, as vehicle rollovers, often accompanied by severe impacts, pose significant threats to both driver safety and vehicle integrity [1]. Uneven road surfaces and various vehicle operating states induce vertical, pitch, and roll vibrations, directly affecting ride comfort. Human sensitivity to vibration is pronounced at frequencies between 0.5–2 Hz in the horizontal direction and 4–10 Hz range in the vertical direction. These performance indicators are interdependent, as improvements in one often compromise the other, making the balance between ride comfort and handling stability a key challenge in chassis system design.
Researchers have employed various control methods to address this balance. Sun et al. [2] proposed an innovative control method that effectively solves the problems of vibration suppression and adaptability to complex road conditions by combining H∞ performance and adaptive robust control technology. Aljarbouh et al. [3] proposed a new dynamic model of the vehicle suspension system and designed a hybrid sliding mode control method to optimize road stability and ride comfort. Liao et al. [4] proposed the Infinite horizon one-step MPC algorithm, which combines the infinite prediction range with the one-step control range, reduces computational complexity and increases efficiency through linearization constraints, and realizes efficient and real-time control performance. Čorić et al. [5] optimized control variables to mitigate disturbances from cosine-shaped bumpy roads, demonstrating that fully active suspensions can enhance ride comfort while maintaining wheel grip. Yuen et al. [6] used multi-objective optimization.
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Fubao Xu, Xiangjun Xia, Jing Cao, Pengfei Liu, Donghong Ning, Haiping Du (2025). Multi-model Switching Control Study of a Full-Car Suspension System for Balancing Ride Comfort and Handling Stability. Chinese Journal of Mechanical Engineering. https://doi.org/10.1186/s10033-025-01340-5
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Frequently Asked Questions
What is the main contribution of this paper?
The paper proposes a novel switching control strategy for full-car suspension systems that balances ride comfort and handling stability by integrating a ride comfort controller and an anti-rollover controller, guided by a new rollover risk assessment indicator.
How does the proposed method simplify the full-car suspension model?
The method reduces the fourteen-degree-of-freedom full-car suspension model to three two-degree-of-freedom models (vertical, pitch, and roll), simplifying the controller design process.
What are the key performance improvements reported?
Compared to a passive suspension, the proposed strategy reduces vertical, roll, and pitch accelerations by 14.13%, 13.02%, and 13.08%, respectively, and reduces roll angle, roll speed, and roll acceleration by 19.69%, 16.40%, and 29.96%, respectively.
What is the significance of the rollover risk assessment indicator?
The indicator serves as the switching criterion between handling stability and ride comfort control, enabling the system to adapt to various road conditions and perform multi-modal switching effectively.
What type of suspension system is used in the study?
The study uses a semi-active variable damping suspension system, which allows for multi-modal switching based on the control strategy.
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