Electro-hydraulic power steering system modelling for parameter fault detection based on model reference adaptive frame

O. C. Kivanc; S. B. Ozturk; R. N. Tuncay; E. Kesici; C. Yazi

doi:10.1109/IECON.2016.7793788

Electro-hydraulic power steering system modelling for parameter fault detection based on model reference adaptive frame

O. C. Kivanc
, S. B. Ozturk
, R. N. Tuncay
, E. Kesici
, C. Yazi

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

2 Atıf (Scopus)

Özet

A simple and efficient fault detection and parameter monitoring algorithm for electro-hydraulic power steering (EHPS) system is proposed using model reference adaptive system (MRAS) without any additional sensor. In a faulty situation where the hydraulic system is disabled, assisted power is provided by an electric motor. Therefore, in low speed maneuvers, during sudden direction changes and parking, some parameters of an electric motor in EHPS are affected. These changes threaten the vehicle's driving reliability and performance of EHPS. In this study, an EHPS system with rotor flux estimation based adaptive driver torque control principle has been presented. The motor winding temperature is obtained for monitoring purpose with the help of MRAS stator resistance estimation. The proposed parameter estimation method for EHPS has been simulated by using AMESim and MATLAB/Simulink cosimulation model. Simulation results demonstrate the feasibility and effectiveness of the proposed method.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society
Yayınlayan	IEEE Computer Society
Sayfalar	1808-1814
Sayfa sayısı	7
ISBN (Elektronik)	9781509034741
DOI'lar	https://doi.org/10.1109/IECON.2016.7793788
Yayın durumu	Yayınlandı - 21 Ara 2016
Harici olarak yayınlandı	Evet
Etkinlik	42nd Conference of the Industrial Electronics Society, IECON 2016 - Florence, Italy Süre: 24 Eki 2016 → 27 Eki 2016

Yayın serisi

Adı	IECON Proceedings (Industrial Electronics Conference)

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	42nd Conference of the Industrial Electronics Society, IECON 2016
Ülke/Bölge	Italy
Şehir	Florence
Periyot	24/10/16 → 27/10/16

Bibliyografik not

Publisher Copyright:
© 2016 IEEE.

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

SKH 7 Erişilebilir ve Temiz Enerji

Belgeye Erişim

10.1109/IECON.2016.7793788

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Kivanc, O. C., Ozturk, S. B., Tuncay, R. N., Kesici, E., & Yazi, C. (2016). Electro-hydraulic power steering system modelling for parameter fault detection based on model reference adaptive frame. In Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society (pp. 1808-1814). Makale 7793788 (IECON Proceedings (Industrial Electronics Conference)). IEEE Computer Society. https://doi.org/10.1109/IECON.2016.7793788

Kivanc, O. C. ; Ozturk, S. B. ; Tuncay, R. N. et al. / Electro-hydraulic power steering system modelling for parameter fault detection based on model reference adaptive frame. Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society. IEEE Computer Society, 2016. pp. 1808-1814 (IECON Proceedings (Industrial Electronics Conference)).

@inproceedings{1e10cef3464248549aa95f3027bebc72,

title = "Electro-hydraulic power steering system modelling for parameter fault detection based on model reference adaptive frame",

abstract = "A simple and efficient fault detection and parameter monitoring algorithm for electro-hydraulic power steering (EHPS) system is proposed using model reference adaptive system (MRAS) without any additional sensor. In a faulty situation where the hydraulic system is disabled, assisted power is provided by an electric motor. Therefore, in low speed maneuvers, during sudden direction changes and parking, some parameters of an electric motor in EHPS are affected. These changes threaten the vehicle's driving reliability and performance of EHPS. In this study, an EHPS system with rotor flux estimation based adaptive driver torque control principle has been presented. The motor winding temperature is obtained for monitoring purpose with the help of MRAS stator resistance estimation. The proposed parameter estimation method for EHPS has been simulated by using AMESim and MATLAB/Simulink cosimulation model. Simulation results demonstrate the feasibility and effectiveness of the proposed method.",

keywords = "Condition monitoring, Electro-hydraulic power steering sytem (EHPS), Fault diagnosis, Fault tolerant, Model reference adaptive system (MRAS), Parameter estimation, PMSM, Rotor flux estimation, Stator resistance estimation, Temperature estimation",

author = "Kivanc, \{O. C.\} and Ozturk, \{S. B.\} and Tuncay, \{R. N.\} and E. Kesici and C. Yazi",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 42nd Conference of the Industrial Electronics Society, IECON 2016 ; Conference date: 24-10-2016 Through 27-10-2016",

year = "2016",

month = dec,

day = "21",

doi = "10.1109/IECON.2016.7793788",

language = "English",

series = "IECON Proceedings (Industrial Electronics Conference)",

publisher = "IEEE Computer Society",

pages = "1808--1814",

booktitle = "Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society",

address = "United States",

}

Kivanc, OC, Ozturk, SB, Tuncay, RN, Kesici, E & Yazi, C 2016, Electro-hydraulic power steering system modelling for parameter fault detection based on model reference adaptive frame. in Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society., 7793788, IECON Proceedings (Industrial Electronics Conference), IEEE Computer Society, pp. 1808-1814, 42nd Conference of the Industrial Electronics Society, IECON 2016, Florence, Italy, 24/10/16. https://doi.org/10.1109/IECON.2016.7793788

Electro-hydraulic power steering system modelling for parameter fault detection based on model reference adaptive frame. / Kivanc, O. C.; Ozturk, S. B.; Tuncay, R. N. et al.
Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society. IEEE Computer Society, 2016. p. 1808-1814 7793788 (IECON Proceedings (Industrial Electronics Conference)).

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › bilirkişi

TY - GEN

T1 - Electro-hydraulic power steering system modelling for parameter fault detection based on model reference adaptive frame

AU - Kivanc, O. C.

AU - Ozturk, S. B.

AU - Tuncay, R. N.

AU - Kesici, E.

AU - Yazi, C.

PY - 2016/12/21

Y1 - 2016/12/21

N2 - A simple and efficient fault detection and parameter monitoring algorithm for electro-hydraulic power steering (EHPS) system is proposed using model reference adaptive system (MRAS) without any additional sensor. In a faulty situation where the hydraulic system is disabled, assisted power is provided by an electric motor. Therefore, in low speed maneuvers, during sudden direction changes and parking, some parameters of an electric motor in EHPS are affected. These changes threaten the vehicle's driving reliability and performance of EHPS. In this study, an EHPS system with rotor flux estimation based adaptive driver torque control principle has been presented. The motor winding temperature is obtained for monitoring purpose with the help of MRAS stator resistance estimation. The proposed parameter estimation method for EHPS has been simulated by using AMESim and MATLAB/Simulink cosimulation model. Simulation results demonstrate the feasibility and effectiveness of the proposed method.

AB - A simple and efficient fault detection and parameter monitoring algorithm for electro-hydraulic power steering (EHPS) system is proposed using model reference adaptive system (MRAS) without any additional sensor. In a faulty situation where the hydraulic system is disabled, assisted power is provided by an electric motor. Therefore, in low speed maneuvers, during sudden direction changes and parking, some parameters of an electric motor in EHPS are affected. These changes threaten the vehicle's driving reliability and performance of EHPS. In this study, an EHPS system with rotor flux estimation based adaptive driver torque control principle has been presented. The motor winding temperature is obtained for monitoring purpose with the help of MRAS stator resistance estimation. The proposed parameter estimation method for EHPS has been simulated by using AMESim and MATLAB/Simulink cosimulation model. Simulation results demonstrate the feasibility and effectiveness of the proposed method.

KW - Condition monitoring

KW - Electro-hydraulic power steering sytem (EHPS)

KW - Fault diagnosis

KW - Fault tolerant

KW - Model reference adaptive system (MRAS)

KW - Parameter estimation

KW - PMSM

KW - Rotor flux estimation

KW - Stator resistance estimation

KW - Temperature estimation

UR - https://www.scopus.com/pages/publications/85010064594

U2 - 10.1109/IECON.2016.7793788

DO - 10.1109/IECON.2016.7793788

M3 - Conference contribution

AN - SCOPUS:85010064594

T3 - IECON Proceedings (Industrial Electronics Conference)

SP - 1808

EP - 1814

BT - Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society

PB - IEEE Computer Society

T2 - 42nd Conference of the Industrial Electronics Society, IECON 2016

Y2 - 24 October 2016 through 27 October 2016

ER -

Kivanc OC, Ozturk SB, Tuncay RN, Kesici E, Yazi C. Electro-hydraulic power steering system modelling for parameter fault detection based on model reference adaptive frame. In Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society. IEEE Computer Society. 2016. p. 1808-1814. 7793788. (IECON Proceedings (Industrial Electronics Conference)). doi: 10.1109/IECON.2016.7793788

Electro-hydraulic power steering system modelling for parameter fault detection based on model reference adaptive frame

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap