Nowadays, the active safety systems that control the dynamics of passenger cars usually rely on real-time monitoring of vehicle side-slip angle (VSA). The VSA can’t be measured directly on the production vehicles since it requires the employment of high-end and expensive instrumentation. To realiably overcome the VSA estimation problem, different model-based techniques can be adopted. The aim of this work is to compare the performance of different model-based state estimators, evaluating both the estimation accuracy and the computational cost, required by each algorithm. To this purpose Extended Kalman Filters, Unscented Kalman Filters and Particle Filters have been implemented for the vehicle system under analysis. The physical representation of the process is represented by a single-track vehicle model adopting a simplified Pacejka tyre model. The results numerical results are then compared to the experimental data acquired within a specifically designed testing campaign, able to explore the entire vehicle dynamic range. To this aim an electric go-kart has been employed as a vehicle, equipped with steering wheel encoder, wheels angular speed encoder and IMU, while an S-motion has been adopted for the measurement of the experimental VSA quantity.

A benchmark study on the model-based estimation of the go-kart side-slip angle / D'Inverno, M.; Arricale, V. M.; Zanardi, A.; Frazzoli, E.; Sakhnevych, A.; Timpone, F.. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6588. - 2090:1(2021), pp. 1-20. (Intervento presentato al convegno 10th International Conference on Mathematical Modeling in Physical Sciences, IC-MSQUARE 2021 tenutosi a Grecia nel 2021) [10.1088/1742-6596/2090/1/012156].

A benchmark study on the model-based estimation of the go-kart side-slip angle

Arricale V. M.;Sakhnevych A.;Timpone F.
2021

Abstract

Nowadays, the active safety systems that control the dynamics of passenger cars usually rely on real-time monitoring of vehicle side-slip angle (VSA). The VSA can’t be measured directly on the production vehicles since it requires the employment of high-end and expensive instrumentation. To realiably overcome the VSA estimation problem, different model-based techniques can be adopted. The aim of this work is to compare the performance of different model-based state estimators, evaluating both the estimation accuracy and the computational cost, required by each algorithm. To this purpose Extended Kalman Filters, Unscented Kalman Filters and Particle Filters have been implemented for the vehicle system under analysis. The physical representation of the process is represented by a single-track vehicle model adopting a simplified Pacejka tyre model. The results numerical results are then compared to the experimental data acquired within a specifically designed testing campaign, able to explore the entire vehicle dynamic range. To this aim an electric go-kart has been employed as a vehicle, equipped with steering wheel encoder, wheels angular speed encoder and IMU, while an S-motion has been adopted for the measurement of the experimental VSA quantity.
2021
A benchmark study on the model-based estimation of the go-kart side-slip angle / D'Inverno, M.; Arricale, V. M.; Zanardi, A.; Frazzoli, E.; Sakhnevych, A.; Timpone, F.. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6588. - 2090:1(2021), pp. 1-20. (Intervento presentato al convegno 10th International Conference on Mathematical Modeling in Physical Sciences, IC-MSQUARE 2021 tenutosi a Grecia nel 2021) [10.1088/1742-6596/2090/1/012156].
File in questo prodotto:
File Dimensione Formato  
GokartSideslipKalmans.pdf

accesso aperto

Tipologia: Versione Editoriale (PDF)
Licenza: Dominio pubblico
Dimensione 1.11 MB
Formato Adobe PDF
1.11 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/866342
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? ND
social impact