Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control
In order to improve the driving stability of distributed-drive intelligent electric vehicles under different roadway attachment conditions, this paper proposes a multi-parameter control algorithm based on the estimation of road adhesion coefficients. First, a seven-degree-of-freedom (7-DOF) vehicle...
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MDPI AG
2025-01-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/1/38 |
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| author | Peng Ji Fengrui Han Yifan Zhao |
| author_facet | Peng Ji Fengrui Han Yifan Zhao |
| author_sort | Peng Ji |
| collection | DOAJ |
| description | In order to improve the driving stability of distributed-drive intelligent electric vehicles under different roadway attachment conditions, this paper proposes a multi-parameter control algorithm based on the estimation of road adhesion coefficients. First, a seven-degree-of-freedom (7-DOF) vehicle dynamics model is established and optimized with a layered control strategy. The upper-level control module calculates the desired yaw rate and sideslip angle using the two-degree-of-freedom (2-DOF) vehicle model and estimates the road adhesion coefficient by using the singular-value optimized cubature Kalman filtering (CKF) algorithm; the middle-level utilizes the second-order sliding mode controller (SOSMC) as a direct yaw moment controller in order to track the desired yaw rate and sideslip angle while also employing a joint distribution algorithm to control the torque distribution based on vehicle stability parameters, thereby enhancing system robustness; and the lower-level controller performs optimal torque allocation based on the optimal tire loading rate as the objective. A Speedgoat-CarSim hardware-in-the-loop simulation platform was established, and typical driving scenarios were simulated to assess the stability and accuracy of the proposed control algorithm. The results demonstrate that the proposed algorithm significantly enhances vehicle-handling stability across both high- and low-adhesion road conditions. |
| format | Article |
| id | doaj-art-32e31c3a0c474861afcce0474d62a752 |
| institution | Kabale University |
| issn | 2032-6653 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-32e31c3a0c474861afcce0474d62a7522025-01-24T13:52:51ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-01-011613810.3390/wevj16010038Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter ControlPeng Ji0Fengrui Han1Yifan Zhao2School of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, ChinaSchool of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, ChinaSchool of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, ChinaIn order to improve the driving stability of distributed-drive intelligent electric vehicles under different roadway attachment conditions, this paper proposes a multi-parameter control algorithm based on the estimation of road adhesion coefficients. First, a seven-degree-of-freedom (7-DOF) vehicle dynamics model is established and optimized with a layered control strategy. The upper-level control module calculates the desired yaw rate and sideslip angle using the two-degree-of-freedom (2-DOF) vehicle model and estimates the road adhesion coefficient by using the singular-value optimized cubature Kalman filtering (CKF) algorithm; the middle-level utilizes the second-order sliding mode controller (SOSMC) as a direct yaw moment controller in order to track the desired yaw rate and sideslip angle while also employing a joint distribution algorithm to control the torque distribution based on vehicle stability parameters, thereby enhancing system robustness; and the lower-level controller performs optimal torque allocation based on the optimal tire loading rate as the objective. A Speedgoat-CarSim hardware-in-the-loop simulation platform was established, and typical driving scenarios were simulated to assess the stability and accuracy of the proposed control algorithm. The results demonstrate that the proposed algorithm significantly enhances vehicle-handling stability across both high- and low-adhesion road conditions.https://www.mdpi.com/2032-6653/16/1/38distributed driveroad adhesion coefficientyaw momenttorque distribution |
| spellingShingle | Peng Ji Fengrui Han Yifan Zhao Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control World Electric Vehicle Journal distributed drive road adhesion coefficient yaw moment torque distribution |
| title | Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control |
| title_full | Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control |
| title_fullStr | Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control |
| title_full_unstemmed | Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control |
| title_short | Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control |
| title_sort | stability study of distributed drive vehicles based on estimation of road adhesion coefficient and multi parameter control |
| topic | distributed drive road adhesion coefficient yaw moment torque distribution |
| url | https://www.mdpi.com/2032-6653/16/1/38 |
| work_keys_str_mv | AT pengji stabilitystudyofdistributeddrivevehiclesbasedonestimationofroadadhesioncoefficientandmultiparametercontrol AT fengruihan stabilitystudyofdistributeddrivevehiclesbasedonestimationofroadadhesioncoefficientandmultiparametercontrol AT yifanzhao stabilitystudyofdistributeddrivevehiclesbasedonestimationofroadadhesioncoefficientandmultiparametercontrol |