Longitudinal Tire Force Estimation Method for 4WIDEV Based on Data-Driven Modified Recursive Subspace Identification Algorithm
For the longitudinal tire force estimation problem of four-wheel independent drive electric vehicles (4WIDEVs), traditional model-based observers have limitations such as high modeling complexity and strong parameter sensitivity, while pure data-driven methods are susceptible to noise interference a...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Algorithms |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-4893/18/7/409 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849304107617091584 |
|---|---|
| author | Xiaoyu Wang Te Chen Jiankang Lu |
| author_facet | Xiaoyu Wang Te Chen Jiankang Lu |
| author_sort | Xiaoyu Wang |
| collection | DOAJ |
| description | For the longitudinal tire force estimation problem of four-wheel independent drive electric vehicles (4WIDEVs), traditional model-based observers have limitations such as high modeling complexity and strong parameter sensitivity, while pure data-driven methods are susceptible to noise interference and have insufficient generalization ability. Therefore, this study proposes a joint estimation framework that integrates data-driven and modified recursive subspace identification algorithms. Firstly, based on the electromechanical coupling mechanism, an electric drive wheel dynamics model (EDWM) is constructed, and multidimensional driving data is collected through a chassis dynamometer experimental platform. Secondly, an improved proportional integral observer (PIO) is designed to decouple the longitudinal force from the system input into a state variable, and a subspace identification recursive algorithm based on correction term with forgetting factor (CFF-SIR) is introduced to suppress the residual influence of historical data and enhance the ability to track time-varying parameters. The simulation and experimental results show that under complex working conditions without noise and interference, with noise influence (5% white noise), and with interference (5% irregular signal), the mean and mean square error of longitudinal force estimation under the CFF-SIR algorithm are significantly reduced compared to the correction-based subspace identification recursive (C-SIR) algorithm, and the comprehensive estimation accuracy is improved by 8.37%. It can provide a high-precision and highly adaptive longitudinal force estimation solution for vehicle dynamics control and intelligent driving systems. |
| format | Article |
| id | doaj-art-43747b76576d48e2ba443e90f4e877ed |
| institution | Kabale University |
| issn | 1999-4893 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj-art-43747b76576d48e2ba443e90f4e877ed2025-08-20T03:55:49ZengMDPI AGAlgorithms1999-48932025-07-0118740910.3390/a18070409Longitudinal Tire Force Estimation Method for 4WIDEV Based on Data-Driven Modified Recursive Subspace Identification AlgorithmXiaoyu Wang0Te Chen1Jiankang Lu2School of Mechanical and Electrical Engineering, Suzhou Vocational University, Suzhou 215000, ChinaAutomotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, ChinaSchool of Mechanical and Electrical Engineering, Suzhou Vocational University, Suzhou 215000, ChinaFor the longitudinal tire force estimation problem of four-wheel independent drive electric vehicles (4WIDEVs), traditional model-based observers have limitations such as high modeling complexity and strong parameter sensitivity, while pure data-driven methods are susceptible to noise interference and have insufficient generalization ability. Therefore, this study proposes a joint estimation framework that integrates data-driven and modified recursive subspace identification algorithms. Firstly, based on the electromechanical coupling mechanism, an electric drive wheel dynamics model (EDWM) is constructed, and multidimensional driving data is collected through a chassis dynamometer experimental platform. Secondly, an improved proportional integral observer (PIO) is designed to decouple the longitudinal force from the system input into a state variable, and a subspace identification recursive algorithm based on correction term with forgetting factor (CFF-SIR) is introduced to suppress the residual influence of historical data and enhance the ability to track time-varying parameters. The simulation and experimental results show that under complex working conditions without noise and interference, with noise influence (5% white noise), and with interference (5% irregular signal), the mean and mean square error of longitudinal force estimation under the CFF-SIR algorithm are significantly reduced compared to the correction-based subspace identification recursive (C-SIR) algorithm, and the comprehensive estimation accuracy is improved by 8.37%. It can provide a high-precision and highly adaptive longitudinal force estimation solution for vehicle dynamics control and intelligent driving systems.https://www.mdpi.com/1999-4893/18/7/409state estimationmodel constructionsubspace identificationdata-drivenestimation accuracy |
| spellingShingle | Xiaoyu Wang Te Chen Jiankang Lu Longitudinal Tire Force Estimation Method for 4WIDEV Based on Data-Driven Modified Recursive Subspace Identification Algorithm Algorithms state estimation model construction subspace identification data-driven estimation accuracy |
| title | Longitudinal Tire Force Estimation Method for 4WIDEV Based on Data-Driven Modified Recursive Subspace Identification Algorithm |
| title_full | Longitudinal Tire Force Estimation Method for 4WIDEV Based on Data-Driven Modified Recursive Subspace Identification Algorithm |
| title_fullStr | Longitudinal Tire Force Estimation Method for 4WIDEV Based on Data-Driven Modified Recursive Subspace Identification Algorithm |
| title_full_unstemmed | Longitudinal Tire Force Estimation Method for 4WIDEV Based on Data-Driven Modified Recursive Subspace Identification Algorithm |
| title_short | Longitudinal Tire Force Estimation Method for 4WIDEV Based on Data-Driven Modified Recursive Subspace Identification Algorithm |
| title_sort | longitudinal tire force estimation method for 4widev based on data driven modified recursive subspace identification algorithm |
| topic | state estimation model construction subspace identification data-driven estimation accuracy |
| url | https://www.mdpi.com/1999-4893/18/7/409 |
| work_keys_str_mv | AT xiaoyuwang longitudinaltireforceestimationmethodfor4widevbasedondatadrivenmodifiedrecursivesubspaceidentificationalgorithm AT techen longitudinaltireforceestimationmethodfor4widevbasedondatadrivenmodifiedrecursivesubspaceidentificationalgorithm AT jiankanglu longitudinaltireforceestimationmethodfor4widevbasedondatadrivenmodifiedrecursivesubspaceidentificationalgorithm |