An unscented Kalman filter-based rolling radius estimation methodology for railway vehicles with traction

Onat, Altan; Voltr, Petr; Lata, Michael

doi:10.1177/0954409717745201

Cited by 13 publications

(18 citation statements)

References 32 publications

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“…w is the rotational speed wheel, r r is the radius of the roller, and r w is the radius of the wheel. 13 The inertia and radius of the wheel and roller are shown in Table 1. Slip is defined as the normalized difference between the wheel speed and vehicle speed.…”

Section: Methodsmentioning

confidence: 99%

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An adaptive sliding mode control to stabilize wheel slip and improve traction performance

Zirek

Voltr

Lata

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part F:

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Advanced antislip control methods are available these days. However, due to increasing requirements with regard to demand and emerging technologies in the field of railways, further research on antislip control is required. Therefore, in this study, an antislip control algorithm, based on a sliding mode control, is proposed to stabilize the slip and improve the traction ability of a full-scale tram wheel test stand. To verify the validity of the control scheme, a numerical model of a tram wheel test stand has been generated using the MATLAB editor. The Freibauer and Polach contact theory has been employed to determine the coefficient of adhesion and adhesion force. Moreover, the derived algorithm was implemented on a full-scale tram wheel test stand. Experiments were carried out under several wheel-roller surface conditions. The results of the refined numerical model are in good agreement with the experimental data obtained from the tram wheel test stand. For both the experimental tests and the numerical model, the response of the proposed control algorithm is rather satisfactory with regard to the stabilization of the slip and improvement of the traction ability.

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Section: Methodsmentioning

confidence: 99%

“…Schematic view of the full-scale tram wheel test stand 13. DAQ: data acquisition device; PMSM: permanent magnet synchronous motor.…”

mentioning

confidence: 99%

An adaptive sliding mode control to stabilize wheel slip and improve traction performance

Zirek

Voltr

Lata

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part F:

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“…In order to verify results, a tram wheel test stand, which simulates the traction system of some trams with independently rotating wheels in Czechia, is considered. This test stand is a full scale, wheel on roller type roller-rig, and it was previously used for validation purpose many times [9,20,[36][37][38][41][42][43][44].…”

Section: General Structure Of the Methodologymentioning

confidence: 99%

“…In this study, measurements taken from the test stand are considered, and the use of test rigs is a common validation strategy for such applications [20,21,33,44,58]. This model has been validated several times in previous studies [36,37,39,41,43,59]. Two cases are given hereby to show that the constructed model represents the physical system.…”

Section: Validation Of the Modelmentioning

confidence: 99%

A novel anti-slip control approach for railway vehicles with traction based on adhesion estimation with swarm intelligence

Zirek

Onat

2020

Rail. Eng. Science

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Anti-slip control systems are essential for railway vehicle systems with traction. In order to propose an effective anti-slip control system, adhesion information between wheel and rail can be useful. However, direct measurement or observation of adhesion condition for a railway vehicle in operation is quite demanding. Therefore, a proportional–integral controller, which operates simultaneously with a recently proposed swarm intelligence-based adhesion estimation algorithm, is proposed in this study. This approach provides determination of the adhesion optimum on the adhesion-slip curve so that a reference slip value for the controller can be determined according to the adhesion conditions between wheel and rail. To validate the methodology, a tram wheel test stand with an independently rotating wheel, which is a model of some low floor trams produced in Czechia, is considered. Results reveal that this new approach is more effective than a conventional controller without adhesion condition estimation.

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“…Fortunately, such a linear transformation can be obtained in the majority of the previously stated applications on mechanical, electrical, electromechanical systems etc. for fault diagnosis and condition monitoring [12], [16], [17]. Furthermore, such approach also provides an indirect calculation of correlation between states and parameters.…”

Section: Introductionmentioning

confidence: 99%

A Novel and Computationally Efficient Joint Unscented Kalman Filtering Scheme for Parameter Estimation of a Class of Nonlinear Systems

Onat

2019

IEEE Access

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Unscented Kalman filter (UKF) is one type of the sigma point Kalman filters and it is based on unscented transformation. UKF is used for parameter estimation of various dynamic systems and for such purpose either joint UKF (JUKF) or dual UKF (DUKF) schemes are considered. JUKF is based on estimating states and parameters together by using only one filter. For DUKF, states and parameters are decoupled and two separate filters are considered. In this paper, a modification to standard JUKF is proposed for parameter estimation which is based on decoupling parameter vector and updating parameter estimates by considering the error transformation between measurements and transformed sigma points during measurement update into the parameter errors. A linear transformation is proposed for such a purpose. Thus, the computational complexity of the standard JUKF is reduced significantly since parameters are decoupled from the state vector while the convergence of parameter estimate(s) is guaranteed. The new modified JUKF scheme is promising to be used for the parameter estimation of dynamic systems for which a linear transformation between measurement and parameter errors can be obtained. The effectiveness of this new scheme is proven by applying it to two nonlinear dynamic systems. INDEX TERMS Kalman filter, unscented Kalman filter, joint unscented Kalman filter, parameter estimation, dynamic systems.

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An unscented Kalman filter-based rolling radius estimation methodology for railway vehicles with traction

Cited by 13 publications

References 32 publications

An adaptive sliding mode control to stabilize wheel slip and improve traction performance

An adaptive sliding mode control to stabilize wheel slip and improve traction performance

A novel anti-slip control approach for railway vehicles with traction based on adhesion estimation with swarm intelligence

A Novel and Computationally Efficient Joint Unscented Kalman Filtering Scheme for Parameter Estimation of a Class of Nonlinear Systems

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