Robust Controller Considering Road Disturbances for a Vehicular Flywheel Battery System
At present, the stability study of the flywheel battery system under the influence of road conditions is only limited to the analysis of dynamic characteristics but also lacks effective controller considering road disturbances. In order to solve this defect and further improve the robust performance...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/15/5432 |
| _version_ | 1797414092344918016 |
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| author | Weiyu Zhang Xiaowei Gu Lindong Zhang |
| author_facet | Weiyu Zhang Xiaowei Gu Lindong Zhang |
| author_sort | Weiyu Zhang |
| collection | DOAJ |
| description | At present, the stability study of the flywheel battery system under the influence of road conditions is only limited to the analysis of dynamic characteristics but also lacks effective controller considering road disturbances. In order to solve this defect and further improve the robust performance of vehicular flywheel battery systems under road disturbances, a robust controller considering interference of road surface roughness is proposed. Firstly, on the basis of a brief introduction to flywheel battery system structure, the influence degree of the flywheel by road condition is compared to find the key areas most affected by road disturbance factors. Then the nonlinear dynamic model of the axial suspension system is constructed, and the actual road surface roughness is regarded as the unmodeled dynamics of the external disturbance emphatically. Following, the established unknown system dynamics is approximated by radial basis function (RBF) neural network based on the minimum parameter learning method, the control input is generated by sliding-mode control law, and the weight adjustment of neural network is replaced by the designed adaptive law of parameter estimation. The effects of different levels of road surface roughness on the system are simulated, and the robustness of the proposed controller is verified based on the Lyapunov method. Finally, the experimental platform to simulate road disturbances is designed ingeniously. Experimental results show that the proposed controller can make the flywheel battery system have good robustness under different road conditions. |
| first_indexed | 2024-03-09T05:28:06Z |
| format | Article |
| id | doaj.art-2ec446e0cd5841e5a37ef500d9cddacc |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T05:28:06Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-2ec446e0cd5841e5a37ef500d9cddacc2023-12-03T12:35:04ZengMDPI AGEnergies1996-10732022-07-011515543210.3390/en15155432Robust Controller Considering Road Disturbances for a Vehicular Flywheel Battery SystemWeiyu Zhang0Xiaowei Gu1Lindong Zhang2School of Electrical and Information Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, ChinaSchool of Electrical and Information Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, ChinaSchool of Electrical and Information Engineering, Jiangsu University, Xuefu Road 301, Zhenjiang 212013, ChinaAt present, the stability study of the flywheel battery system under the influence of road conditions is only limited to the analysis of dynamic characteristics but also lacks effective controller considering road disturbances. In order to solve this defect and further improve the robust performance of vehicular flywheel battery systems under road disturbances, a robust controller considering interference of road surface roughness is proposed. Firstly, on the basis of a brief introduction to flywheel battery system structure, the influence degree of the flywheel by road condition is compared to find the key areas most affected by road disturbance factors. Then the nonlinear dynamic model of the axial suspension system is constructed, and the actual road surface roughness is regarded as the unmodeled dynamics of the external disturbance emphatically. Following, the established unknown system dynamics is approximated by radial basis function (RBF) neural network based on the minimum parameter learning method, the control input is generated by sliding-mode control law, and the weight adjustment of neural network is replaced by the designed adaptive law of parameter estimation. The effects of different levels of road surface roughness on the system are simulated, and the robustness of the proposed controller is verified based on the Lyapunov method. Finally, the experimental platform to simulate road disturbances is designed ingeniously. Experimental results show that the proposed controller can make the flywheel battery system have good robustness under different road conditions.https://www.mdpi.com/1996-1073/15/15/5432flywheel battery systemmagnetic suspension systemrobust controllerroad surface roughness |
| spellingShingle | Weiyu Zhang Xiaowei Gu Lindong Zhang Robust Controller Considering Road Disturbances for a Vehicular Flywheel Battery System Energies flywheel battery system magnetic suspension system robust controller road surface roughness |
| title | Robust Controller Considering Road Disturbances for a Vehicular Flywheel Battery System |
| title_full | Robust Controller Considering Road Disturbances for a Vehicular Flywheel Battery System |
| title_fullStr | Robust Controller Considering Road Disturbances for a Vehicular Flywheel Battery System |
| title_full_unstemmed | Robust Controller Considering Road Disturbances for a Vehicular Flywheel Battery System |
| title_short | Robust Controller Considering Road Disturbances for a Vehicular Flywheel Battery System |
| title_sort | robust controller considering road disturbances for a vehicular flywheel battery system |
| topic | flywheel battery system magnetic suspension system robust controller road surface roughness |
| url | https://www.mdpi.com/1996-1073/15/15/5432 |
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