Measurement of Tractive Force and the New Maximum Tractive Force Control by the Newly Developed Tractive Force Measurement Equipment

Kawamura, Atsuo; Takeuchi, Keiichi; Furuya, Takemasa; Cao, Meifen; Takaoka, Yosuke; Yoshimoto, Kantaro

doi:10.1541/ieejias.123.885

Cited by 6 publications

(6 citation statements)

References 5 publications

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“…Both of the adhesion model and the optimal slip velocity are unknown in real-time applications. For this reason, an optimal slip velocity seeking method must be developed to estimate the exact value of the optimal slip velocity [27].…”

Section: Optimal Slip Velocity Seeking Methodsmentioning

confidence: 99%

Re-adhesion control strategy based on the optimal slip velocity seeking method

2018

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In the railway industry, re-adhesion control plays an important role in attenuating the slip occurrence due to the low adhesion condition in the wheel-rail interaction. Braking and traction forces depend on the normal force and adhesion coefficient at the wheel-rail contact area. Due to the restrictions on controlling normal force, the only way to increase the tractive or braking effect is to maximize the adhesion coefficient. Through efficient utilization of adhesion, it is also possible to avoid wheel-rail wear and minimize the energy consumption. The adhesion between wheel and rail is a highly nonlinear function of many parameters like environmental conditions, railway vehicle speed and slip velocity. To estimate these unknown parameters accurately is a very hard and competitive challenge. The robust adaptive control strategy presented in this paper is not only able to suppress the wheel slip in time, but also maximize the adhesion utilization performance after re-adhesion process even if the wheel-rail contact mechanism exhibits significant adhesion uncertainties and/or nonlinearities. Using an optimal slip velocity seeking algorithm, the proposed strategy provides a satisfactory slip velocity tracking ability, which was demonstrated able to realize the desired slip velocity without experiencing any instability problem. The control torque of the traction motor was regulated continuously to drive the railway vehicle in the neighborhood of the optimal adhesion point and guarantee the best traction capacity after re-adhesion process by making the railway vehicle operate away from the unstable region. The results obtained from the adaptive approach based on the secondorder sliding mode observer have been confirmed through theoretical analysis and numerical simulation conducted in MATLAB and Simulink with a full traction model under various wheel-rail conditions.

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Section: Optimal Slip Velocity Seeking Methodsmentioning

confidence: 99%

Re-adhesion control strategy based on the optimal slip velocity seeking method

2018

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“…Hence the dynamic equations are given as: T e is calculated using the traction motor model in a stationary  -frame. Stator current and rotor flux are the state variables and the equations are list in Equation (2)(3)(4) to (2-7). The motor is controlled by an indirect flux oriented scheme [12], which is commonly used in railway traction and other applications.…”

Section: Traction System Modellingmentioning

confidence: 99%

“…State matrix A and Measurement matrix H are determined by system dynamic equations (2-1) to (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12). As the dynamic equations are nonlinear, extended Kalman filter is chosen to provide estimations of the state variable.…”

Section: Extended Kalman Filtermentioning

confidence: 99%

“…This phenomenon occurs more commonly when the wheel-rail surfaces are wet or contaminated with oil or leaves, as the friction coefficient may drop to very low levels. 4 To avoid this issue, re-adhesion control strategy has been studied and many different algorithms have been proposed [1][2][3][4][5][6][7][8][9]. In these algorithms, the vector control method is most commonly adopted, while the major differences lie in the way of detecting creepage and generating the torque command.…”

Section: Introductionmentioning

confidence: 99%

“…Kim et al [2] suggested a model based re-adhesion control which treats the creep force as the mechanical load of the traction motor and the creepage force is estimated by a Kalman filter. Matsumoto [3] and Kawamura [4] investigated a singleinverter for multiple-induction-motors drive system, which uses the estimated adhesion force to adjust the torque commend and suppress the slip. The advantages for these applications are that they can regulate the traction system to work around the peak of the creepage -creep force curve, but require the knowledge of the friction coefficient and the vehicle speed, which are both hard to be measured accurately.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Re-adhesion control for a railway single wheelset test rig based on the behaviour of the traction motor

Zhao

Liang

2013

Vehicle System Dynamics

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Extended Kalman Filter Design for Railway Traction Motor

Uyulan

Gökaşan

2017

Scitech

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ABSTRACT:Monitoring the adhesion force between a railway wheel and a rail surface is very essential in maintaining high acceleration and braking performance of railway vehicles. Due to the difficulties encountered in direct measurement of friction coefficient, creepage and adhesion force; state observers are used as indirect estimation methods. This paper proposes an effective estimation method, which exploits railway traction motor behaviour to give an assistance for realizing wheel slip and adhesion control in order to be used in railway applications. This method plays an active role in optimizing the use of the existing adhesion and reducing wheel wear by decreasing high creep values. With this method, adhesion force can be indirectly estimated by measuring stator currents, and angular speed of the AC traction motor and using dynamic relationships based on the extended Kalman filter (EKF) simulation model. The re-adhesion controller can be designed to regulate the motor torque command according to the maximum available adhesion depending on the estimated results. To test the proposed method, simulations were performed under different friction coefficients. Key Words: Adhesion mode, Extended Kalman filter, Full state estimation, Railway traction. Demiryolu Cer Motorları için Genişletilmiş Kalman Filtresi TasarımıÖZ: Bir demiryolu tekerleği ile rayı arasında meydana gelen tutunma kuvvetinin izlenmesi, demiryolu araçlarının yüksek hızlanma ve frenleme performansının korunmasında oldukça önemlidir. Sürtünme katsayısı, kayma ve tutunma kuvvetinin doğrudan ölçülmesinde karşılaşılan zorluklardan dolayı, durum gözetleyicilerine dayalı dolaylı tahmin yöntemleri kullanılır. Bu makale, demiryolu uygulamalarında kullanılmak üzere tekerlek kayma ve yeniden tutunma kontrolünü gerçekleştirmek için demiryolu cer motor davranışını kullanan etkili bir tahmin yöntemi önermektedir. Bu yöntem, mevcut tutunmanın kullanımını iyileştirmede ve yüksek kayma değerlerini düşürerek tekerlek aşınmasının azaltılmasında etkin bir rol oynamaktadır. Bu yöntemle, stator akımları ve asenkron cer motorun açısal hızı ölçülerek, genişletilmiş Kalman filtresi (GKF) simülasyon modeline dayanan dinamik ilişkiler kullanılarak tutunma kuvveti dolaylı olarak tahmin edilebilir. Yeniden tutunma kontrolörü, tahmin sonuçlarına bağlı olan maksimum erişilebilir tutunma özelliklerine göre motor moment komutu düzenlenerek tasarlanabilir. Önerilen yöntemi test etmek için, farklı tekerlek-ray sürtünme katsayıları altında simülasyonlar gerçekleştirilmiştir.

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Measurement of Tractive Force and the New Maximum Tractive Force Control by the Newly Developed Tractive Force Measurement Equipment

Cited by 6 publications

References 5 publications

Re-adhesion control strategy based on the optimal slip velocity seeking method

Re-adhesion control strategy based on the optimal slip velocity seeking method

Re-adhesion control for a railway single wheelset test rig based on the behaviour of the traction motor

Extended Kalman Filter Design for Railway Traction Motor

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