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Positioning Method Based on Slip Ratio Compensation for Intelligent Vehicles
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Lu Xiong1, Jiaqi Zhu1, Mengyuan Chen1, Ziyao Li1, Qiang Shu2, Guirong Zhuo1
Automotive Engineering | 2025, 47(5) : 851 - 858
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Automotive Engineering | 2025, 47(5): 851-858
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Positioning Method Based on Slip Ratio Compensation for Intelligent Vehicles
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Lu Xiong1, Jiaqi Zhu1, Mengyuan Chen1, Ziyao Li1, Qiang Shu2, Guirong Zhuo1
Affiliations
  • 1 School of Automotive Studies，Tongji University，Shanghai 201804
  • 2 Shanghai Tongyu Automotive Technology Co.，Ltd.，Shanghai 201804
Published: 2025-05-25 doi: 10.19562/j.chinasae.qcgc.2025.05.006
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Accurate and reliable vehicle pose estimation is a critical input for intelligent vehicle decision, planning and motion control modules. In this paper, a positioning algorithm that integrates realtime slip ratio estimation and compensation for intelligent vehicles is proposed, which significantly enhances the fusion positioning accuracy of the Inertial Navigation System (INS) and Wheel Speed Sensor (WSS) during Global Navigation Satellite System (GNSS) interruption. Firstly, a realtime slip ratio estimation algorithm is proposed to correct the wheel speed information for different driving conditions, which uses vehicle acceleration and wheel speed data. Then, based on errorstate Kalman filter (ESKF), the corrected wheel speed data is fused with GNSS and Inertial Measurement Unit (IMU) information to achieve accurate and reliable vehicle pose estimation. The results of the realvehicle experiments show that during GNSS interruption, the Root Mean Square Error (RMSE) of velocity improves by up to 30% and the average horizontal position error mileage ratio reaches 1.68%.

intelligent vehicle  /  fusion positioning  /  slip ratio estimation  /  error-state Kalman filter
Lu Xiong, Jiaqi Zhu, Mengyuan Chen, Ziyao Li, Qiang Shu, Guirong Zhuo. Positioning Method Based on Slip Ratio Compensation for Intelligent Vehicles[J]. Automotive Engineering, 2025 , 47 (5) : 851 -858 . DOI: 10.19562/j.chinasae.qcgc.2025.05.006
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Article Info
doi: 10.19562/j.chinasae.qcgc.2025.05.006
  • Receive Date：2024-12-13
  • Online Date：2025-07-08
  • Published：2025-05-25
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  • Received：2024-12-13
  • Revised：2025-02-11
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    1 School of Automotive Studies，Tongji University，Shanghai 201804
    2 Shanghai Tongyu Automotive Technology Co.，Ltd.，Shanghai 201804
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