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Integrated Model Predictive Control and Adaptive Unscented Kalman Filter for Semi-Active Suspension System Based on Road Classification
Technical Paper
2020-01-0999
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The accuracy of state estimation and optimal control for controllable suspension system is a challenging task for the vehicle suspension system under various road excitations. How to effectively acquire suspension states and choose the reasonable control algorithm become a hot topic in both academia and industry. Uncertainty is unavoidable for the suspension system, e.g., varying sprung or unsprung mass, suspension damping force or spring stiffness. To tackle the above problems, a novel observer-based control approach, which combines adaptive unscented Kalman filter (AUKF) observer and model predictive control (MPC), is proposed in the paper. A quarter semi-active suspension nonlinear model and road profile model are first established. Secondly, using the road classification identification method based on system response, an AUKF algorithm is employed to estimate accurately the state of suspension system. Due to the nonlinear of semi-active suspension damping force in the movement process, the methods of observer-based and model predictive control are used to design the optimal predictive controller under various road excitations. Finally, compared with passive suspension system, the constrained optimal control (COC) algorithm and the model predictive control (MPC) algorithm, the road handing and ride comfort indexes are analyzed. Simulation results show that the performance of the proposed model predictive control algorithm compared with passive mode for the semi-suspension system improves more than 10% under the same road excitation condition.
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Authors
- Zhenfeng Wang - China Automotive Technology and Research Center Co., Ltd.
- Shengjie Xu - China Automotive Technology and Research Center Co., Ltd.
- Fei Li - China Automotive Technology and Research Center Co., Ltd.
- Xinyu Wang - China Automotive Technology and Research Center Co., Ltd.
- Jiansen Yang - China Automotive Technology and Research Center Co., Ltd.
- Jing Miao - Suzhou University of Science and Technology
Topic
Citation
Wang, Z., Xu, S., Li, F., Wang, X. et al., "Integrated Model Predictive Control and Adaptive Unscented Kalman Filter for Semi-Active Suspension System Based on Road Classification," SAE Technical Paper 2020-01-0999, 2020, https://doi.org/10.4271/2020-01-0999.Data Sets - Support Documents
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