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

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...

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Main Authors: Jie Chen, Ruochen Wang, Wei Liu, Dong Sun, Yu Jiang, Renkai Ding
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/10/5491
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author Jie Chen
Ruochen Wang
Wei Liu
Dong Sun
Yu Jiang
Renkai Ding
author_facet Jie Chen
Ruochen Wang
Wei Liu
Dong Sun
Yu Jiang
Renkai Ding
author_sort Jie Chen
collection DOAJ
description 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.
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spelling doaj-art-e91c14fca3b543988c6a3fbb6ffd12b82025-08-20T02:33:39ZengMDPI AGApplied Sciences2076-34172025-05-011510549110.3390/app15105491A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road VehiclesJie Chen0Ruochen Wang1Wei Liu2Dong Sun3Yu Jiang4Renkai Ding5School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, ChinaSchool of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, ChinaAutomotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, ChinaDespite 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.https://www.mdpi.com/2076-3417/15/10/5491roll stabilityvehicle dynamicson-road vehiclesoff-road vehiclessafety control
spellingShingle Jie Chen
Ruochen Wang
Wei Liu
Dong Sun
Yu Jiang
Renkai Ding
A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles
Applied Sciences
roll stability
vehicle dynamics
on-road vehicles
off-road vehicles
safety control
title A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles
title_full A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles
title_fullStr A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles
title_full_unstemmed A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles
title_short A Review of Recent Advances in Roll Stability Control in On-Road and Off-Road Vehicles
title_sort review of recent advances in roll stability control in on road and off road vehicles
topic roll stability
vehicle dynamics
on-road vehicles
off-road vehicles
safety control
url https://www.mdpi.com/2076-3417/15/10/5491
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