Method for Estimating Sideslip Angle of All-wheel Drive Vehicle Based on Data Fusion

doi:10.3969/j.issn.1000-1093.2020.05.002

Abstract

Abstract: A method for estimating sideslip angle based on data fusion is proposed to obtain the driving state parameters of all-wheel electric drive vehicle. On the basis of three-degree-of-freedom vehicle model and tire model, the method fully utilizes the information from a low-cost common vehicle-mounted sensor, in-wheel motor input information as well as driving signals, and the sideslip angle is estimated by using the unscented Kalman filter algorithm. Besides, the sideslip angle is estimated by signal integration method. Combined with vehicle driving conditions and road conditions, the estimated values of the unscented Kalman filtering algorithm and the signal integral algorithm are fused to obtain the final estimation of sideslip angle. A series of simulations were conducted on the hardware-in-the-loop real-time simulation platform. The results show that the proposed estimation algorithm has higher observation accuracy compared with the single estimation algorithm, which can meet the requirements of mass center sideslip angle observation under various driving conditions. Key

Key words: all-wheelindependentdriveelectricvehicle, datafusion, masscentersideslipangle, unscentedKalmanfilter

CLC Number:

TJ810.2

ZHANG Zheng， LIU Chunguang， MA Xiaojun， ZHANG Yunyin. Method for Estimating Sideslip Angle of All-wheel Drive Vehicle Based on Data Fusion[J]. Acta Armamentarii, 2020, 41(5): 842-849.

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第41卷第5期2020 年5月
兵工学报ACTA ARMAMENTARII
Vol.41No.5May2020

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