Vehicle stability control based on vehicle motion state and tire force estimation

The direct yaw moment control system is able to greatly enhance the vehicle stability when driving on challenging road surfaces. This paper introduces a direct control approach for managing the vehicle yaw moment, utilizing terminal sliding mode control and a square root cubature Kalman filter (SRCKF). Initially, the longitudinal and lateral forces acting on the vehicle’s tires are estimated through a sliding mode observer. Subsequently, the SRCKF algorithm and the four-wheel tire force are employed to accurately estimate the yaw rate and sideslip angle. Based on these estimations, additional yaw moments are determined using the terminal sliding mode control algorithm, and a combined control of yaw rate and sideslip angle is achieved through a threshold method. A rule-based braking force distribution strategy is then implemented to ensure vehicle stability control. Simulation results demonstrate that the tire force estimations from the sliding mode observer and the vehicle yaw rate and sideslip angle estimations from the SRCKF algorithm closely align with the output results from Carsim, with an error margin of less than 15%. The braking force distribution strategy, based on the direct yaw moment control using the terminal sliding mode algorithm, effectively tracks the desired yaw rate and sideslip angle.

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Publication Details

Journal
Transactions of the Canadian Society for Mechanical Engineering
Published
2024-09-09
DOI
https://doi.org/10.1139/tcsme-2024-0070
Citations
4
Primary Topic
Vehicle Dynamics and Control Systems
Type
article
Field-Weighted Citation Impact
0.81
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article

Vehicle stability control based on vehicle motion state and tire force estimation

Min Gao, Baidong Feng, Jin Luo, Jing Li et al.
4 citations
Transactions of the Canadian Society for Mechanical Engineering
Vehicle Dynamics and Control Systems
0.81
article

Vehicle stability control based on vehicle motion state and tire force estimation

Min Gao, Baidong Feng, Jin Luo, Jing Li, Le Zhang
article en
4 citations

Abstract

The direct yaw moment control system is able to greatly enhance the vehicle stability when driving on challenging road surfaces. This paper introduces a direct control approach for managing the vehicle yaw moment, utilizing terminal sliding mode control and a square root cubature Kalman filter (SRCKF). Initially, the longitudinal and lateral forces acting on the vehicle’s tires are estimated through a sliding mode observer. Subsequently, the SRCKF algorithm and the four-wheel tire force are employed to accurately estimate the yaw rate and sideslip angle. Based on these estimations, additional yaw moments are determined using the terminal sliding mode control algorithm, and a combined control of yaw rate and sideslip angle is achieved through a threshold method. A rule-based braking force distribution strategy is then implemented to ensure vehicle stability control. Simulation results demonstrate that the tire force estimations from the sliding mode observer and the vehicle yaw rate and sideslip angle estimations from the SRCKF algorithm closely align with the output results from Carsim, with an error margin of less than 15%. The braking force distribution strategy, based on the direct yaw moment control using the terminal sliding mode algorithm, effectively tracks the desired yaw rate and sideslip angle.

Transactions of the Canadian Society for Mechanical EngineeringVol. 49(2)
Yanshan University (CN)
Openalex Percentile: Top 29%
Vehicle Dynamics and Control Systems
0.81
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Vehicle stability control based on vehicle motion state and tire force estimation — Min Gao, Baidong Feng, et al. · Transactions of the Canadian Society for Mechanical Engineering (2024) | TGRS Research Map | TGRS