A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles

被引:0
作者
Chen, Jie [1 ]
Wang, Ruochen [1 ]
Liu, Wei [1 ]
Sun, Dong [1 ]
Jiang, Yu [1 ]
Ding, Renkai [2 ]
机构
[1] Jiangsu Univ, Sch Automot & Traff Engn, Zhenjiang 212013, Peoples R China
[2] Jiangsu Univ, Automot Engn Res Inst, Zhenjiang 212013, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2025年 / 15卷 / 10期
基金
中国国家自然科学基金;
关键词
roll stability; vehicle dynamics; on-road vehicles; off-road vehicles; safety control; MODEL-PREDICTIVE CONTROL; YAW MOMENT CONTROL; ACTIVE SUSPENSION; COORDINATED CONTROL; LATERAL STABILITY; CONTROL-SYSTEM; COMBINE; TRACTOR; DESIGN; MOTION;
D O I
10.3390/app15105491
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Despite significant advancements in roll stability control for individual vehicle types, comparative research across on-road and off-road vehicles remains limited, hindering cross-disciplinary innovation. This study bridges this gap by systematically analyzing roll stability control in both vehicle categories, focusing on theoretical foundations, key technologies, and experimental validation methods. On-road vehicles rely on mature technologies like active suspension, braking, and steering, which enhance safety through sensor monitoring, rollover prediction, and integrated stability control. Validation is primarily performed through hardware-in-the-loop simulations and on-road testing. Off-road vehicles, operating in more complex environments with dynamic load changes and rugged terrain, emphasize adaptive leveling, direct torque control, and active steering. Their stability control strategies must also account for terrain irregularities, real-time load shifts, and extreme slopes, validated through scaled-model tests and field trials. Comparative analysis reveals that while both vehicle types face similar challenges, their control strategies differ significantly: on-road vehicles focus on handling and high-speed stability, while off-road vehicles require more robust, adaptive mechanisms to manage environmental uncertainties. Future research should explore multi-system collaborative control, such as integrating active suspension with intelligent terrain perception, to improve adaptability and robustness across both vehicle categories. Furthermore, the integration of machine learning and advanced predictive algorithms promises to enhance the intelligence and versatility of roll stability control systems.
引用
收藏
页数:31
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