LAPSE:2023.29350v1
Published Article

LAPSE:2023.29350v1
Research on Model Predictive Control for Automobile Active Tilt Based on Active Suspension
April 13, 2023
Abstract
To improve the handling stability of automobiles and reduce the odds of rollover, active or semi-active suspension systems are usually used to control the roll of a vehicle. However, these kinds of control systems often take a zero-roll-angle as the control target and have a limited effect on improving the performance of the vehicle when turning. Tilt control, which actively controls the vehicle to tilt inward during a curve, greatly benefits the comprehensive performance of a vehicle when it is cornering. After analyzing the advantages and disadvantages of the tilt control strategies for narrow commuter vehicles by combining the structure and dynamic characteristics of automobiles, a direct tilt control (DTC) strategy was determined to be more suitable for automobiles. A model predictive controller for the DTC strategy was designed based on an active suspension. This allowed the reverse tilt to cause the moment generated by gravity to offset that generated by the centrifugal force, thereby significantly improving the handling stability, ride comfort, vehicle speed, and rollover prevention. The model predictive controller simultaneously tracked the desired tilt angle and yaw rate, achieving path tracking while improving the anti-rollover capability of the vehicle. Simulations of step-steering input and double-lane change maneuvers were performed. The results showed that, compared with traditional zero-roll-angle control, the proposed tilt control greatly reduced the occupant’s perceived lateral acceleration and the lateral load transfer ratio when the vehicle turned and exhibited a good path-tracking performance.
To improve the handling stability of automobiles and reduce the odds of rollover, active or semi-active suspension systems are usually used to control the roll of a vehicle. However, these kinds of control systems often take a zero-roll-angle as the control target and have a limited effect on improving the performance of the vehicle when turning. Tilt control, which actively controls the vehicle to tilt inward during a curve, greatly benefits the comprehensive performance of a vehicle when it is cornering. After analyzing the advantages and disadvantages of the tilt control strategies for narrow commuter vehicles by combining the structure and dynamic characteristics of automobiles, a direct tilt control (DTC) strategy was determined to be more suitable for automobiles. A model predictive controller for the DTC strategy was designed based on an active suspension. This allowed the reverse tilt to cause the moment generated by gravity to offset that generated by the centrifugal force, thereby significantly improving the handling stability, ride comfort, vehicle speed, and rollover prevention. The model predictive controller simultaneously tracked the desired tilt angle and yaw rate, achieving path tracking while improving the anti-rollover capability of the vehicle. Simulations of step-steering input and double-lane change maneuvers were performed. The results showed that, compared with traditional zero-roll-angle control, the proposed tilt control greatly reduced the occupant’s perceived lateral acceleration and the lateral load transfer ratio when the vehicle turned and exhibited a good path-tracking performance.
Record ID
Keywords
active suspension, handing stability, Model Predictive Control, tilt control
Subject
Suggested Citation
Yao J, Wang M, Li Z, Jia Y. Research on Model Predictive Control for Automobile Active Tilt Based on Active Suspension. (2023). LAPSE:2023.29350v1
Author Affiliations
Yao J: College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China; Department of Automotive Engineering, Clemson University, Greenville, SC 29607, USA [ORCID]
Wang M: College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
Li Z: College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
Jia Y: Department of Automotive Engineering, Clemson University, Greenville, SC 29607, USA
Wang M: College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
Li Z: College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing 210037, China
Jia Y: Department of Automotive Engineering, Clemson University, Greenville, SC 29607, USA
Journal Name
Energies
Volume
14
Issue
3
First Page
671
Year
2021
Publication Date
2021-01-28
ISSN
1996-1073
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Original Submission
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PII: en14030671, Publication Type: Journal Article
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LAPSE:2023.29350v1
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https://doi.org/10.3390/en14030671
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Apr 13, 2023
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