Estimation of vehicle sideslip angle via pseudo-multisensor information fusion method

• Autorzy: Chen T. , Chen L. , Cai Y. , Xu X.

Identyfikatory

DOI

10.24425/123902

• Języki publikacji: EN

Abstrakty

EN

This paper presents a novel sideslip angle estimator based on the pseudo-multi-sensor fusion method. The kinematics-based and dynamics-based sideslip angle estimators are designed for sideslip angle estimation. Also, considering the influence of ill-conditioned matrix and model uncertainty, a novel sideslip angle estimator is proposed based on the wheel speed coupling relationship using a modified recursive least squares algorithm. In order to integrate the advantages of above three sideslip angle estimators, drawing lessons from the multisensory information fusion technology, a novel thinking of sideslip angle estimator design is presented through information fusion of pseudo-multi-sensors. Simulations and experiments were carried out, and effectiveness of the proposed estimation method was verified.

Słowa kluczowe

EN

vehicle state estimation; sideslip angle; recursive least squares; multi-sensor information fusion; pseudo-measurements

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2018
• Tom: Vol. 25, nr 3
• Strony: 499--516
• Opis fizyczny: Bibliogr. 36 poz., rys., tab., wykr., wzory

Twórcy

autor

Chen T.

• Jiangsu University, School of Automotive and Traffic Engineering, Zhenjiang 212013, China

autor

Chen L.

• Jiangsu University, School of Automotive and Traffic Engineering, Zhenjiang 212013, China
• Jiangsu University, Automotive Engineering Research Institute, Zhenjiang 212013, China

autor

Cai Y.

• Jiangsu University, School of Automotive and Traffic Engineering, Zhenjiang 212013, China
• Jiangsu University, Automotive Engineering Research Institute, Zhenjiang 212013, China

autor

Xu X.

• Jiangsu University, School of Automotive and Traffic Engineering, Zhenjiang 212013, China
• Jiangsu University, Automotive Engineering Research Institute, Zhenjiang 212013, China

Bibliografia

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Uwagi

EN

1. This work was supported by the National Natural Science Foundation of China (grant numbers U1664258 and U1564201), Six Major Talent Project of Jiangsu Province (grant number 2014-JXQC-004), 333 Project of Jiangsu Province (grant number BRA2016445), Key R&D Plan of Jiangsu Province (grant number BE 2017129), and Natural Science Foundation of Jiangsu Province (grant number BK 20160525).

PL

2. Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).