Automated Vehicle Sideslip Angle Estimation Considering Signal Measurement Characteristic
Abstract
Vehicle slip angle (VSA) estimation is of paramount importance for connected automated vehicle dynamic control, especially in critical lateral driving scenarios. In this paper, a novel kinematic-model-based VSA estimation method is proposed by fusing information from a global navigation satellite system (GNSS) and an inertial measurement unit (IMU). First, to reject the gravity components induced by the vehicle roll and pitch, a vehicle attitude angle observer based on the square-root cubature Kalman filter (SCKF) is designed to estimate the roll and pitch. A novel feedback mechanism based on the vehicle intrinsic information (the steering angle and wheel speed) for the pitch and roll is designed. Then, the integration of the reverse smoothing and grey prediction is adopted to compensate for the cumulative velocity errors during the relatively low sampling interval of the GNSS. Moreover, the GNSS signal delay has been addressed by an estimation-prediction integrated framework. Finally, the results confirm that the proposed method can estimate the VSA under both the slalom and double lane change (DLC) scenarios.
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For all the aforementioned methods, time delays are assumed to be known and time-invariant.
“For all the aforementioned methods, time delays are assumed to be known and time-invariant.”
From Novel reaching law based predictive sliding mode control for lateral motion control of in‐wheel motor drive electric vehicle with delay estimation (2024) · cites this paper as [12]
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- Authors
- Liu, W., Xia, X., Xiong, L., Lu, Y., Gao, L., & Yu, Z.
- Affiliations
- Tongji University (CN)
- Venue
- IEEE Sensors Journal
- Published
- 2021-10-01
- Volume
- 21
- Issue
- 19
- Pages
- 21675-21687
- ISSN
- 1530-437X (ISSN-L)
- 1558-1748
- 2379-9153
- OpenAlex
- W3202375294
- Cited by
- 165
- References
- 35
- Citations by year
- 2026: 2 · 2025: 23 · 2024: 28 · 2023: 104 · 2022: 8
- FWCI
- 11.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Sensors Journal (publishedVersion)
- Funders
- National Nature Science Foundation of China (51975414)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Vehicle Dynamics and Control Systems
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Keywords
- sideslip, kinematic modeling, attitude estimation, square-root cubature Kalman filter, roll and pitch estimation, grey forecasting, double lane change, slalom maneuver, connected and automated vehicles, vehicle lateral dynamics
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