Slope Estimation Method of Electric Vehicles Based on Improved Sage–Husa Adaptive Kalman Filter

Jiawei Guo, Chao He, Jiaqiang Li and Heng Wei
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Jiawei Guo: School of Machinery and Transportation, Southwest Forestry University, Kunming 650224, China
Chao He: School of Machinery and Transportation, Southwest Forestry University, Kunming 650224, China
Jiaqiang Li: School of Machinery and Transportation, Southwest Forestry University, Kunming 650224, China
Heng Wei: School of Machinery and Transportation, Southwest Forestry University, Kunming 650224, China

Energies, 2022, vol. 15, issue 11, 1-17

Abstract: In order to deal with many influence factors of electric vehicles in driving under complex conditions, this paper establishes the system state equation based on the longitudinal dynamics equation of vehicle. Combined with the improved Sage–Husa adaptive Kalman filter algorithm, the road slope estimation model is established. After the driving speed and rough slope observation are input into the slope estimation model, the accurate road slope estimation at the current time can be obtained. The road slope estimation method is compared with the original Sage–Husa adaptive Kalman filter road slope estimation method through three groups of road tests in different slope ranges, and the accuracy and stability advantages of the proposed algorithm in road conditions with large slopes are verified.

Keywords: road slope estimation; adaptive Kalman filter; electric car (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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