Extended Kalman filter utilization for a railway traction vehicle slip control

Pichlík, Petr; Zděnek, Jiří

doi:10.1109/optim.2017.7975079

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…However, the adhesion coefficient is difficult to measure with general tools. Common processing methods include full-scale state observers, Kalman Filters [27][28][29]. This paper proposes a nonsingular terminal sliding mode observer (NTSMO) to observe the load torque of the traction motor, and obtain the real-time adhesion coefficient of the wheel-rail [22].…”

Section: Nonsingular Terminal Sliding Mode Adhesion Coefficientmentioning

confidence: 99%

Optimal Utilization of Adhesion Force for Heavy-Haul Electric Locomotive Based on Extremum Seeking with Sliding Mode and Asymmetric Barrier Lyapunov Function

Zhao

Zhang

et al. 2019

Journal of Advanced Transportation

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An optimal utilization of adhesion force based on extremum seeking with sliding mode (SMES) and asymmetric barrier Lyapunov function (ABLF) is proposed for heavy-haul electric locomotives (HHELs), which can eliminate the wheel skidding at optimal adhesion point and achieves maximum traction for HHELs. First, the state equation of wheel-rail adhesion control system is described. The optimal utilization of adhesion force and anti-slip control are analyzed considering the condition changes at the wheel-rail surface. Then, the nonsingular terminal sliding mode observer (NTSMO) is designed to achieve the accurate adhesion coefficient of the wheel-rail. Finally, the SMES method for HHEL is developed to obtain the optimal slip speed and the maximum adhesion coefficient of the uncertain wheel-rail surface. Meanwhile, the ABLF controller is designed to achieve anti-slip control for HHELs in the optimal adhesion state. Comparing with the conventional differential acceleration control (DAC) method, the simulations and experiments verify that the proposed method can achieve optimal adhesion anti-slip control with quick dynamic response, and the HHEL achieves maximum traction.

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Section: Nonsingular Terminal Sliding Mode Adhesion Coefficientmentioning

confidence: 99%

Optimal Utilization of Adhesion Force for Heavy-Haul Electric Locomotive Based on Extremum Seeking with Sliding Mode and Asymmetric Barrier Lyapunov Function

Zhao

Zhang

et al. 2019

Journal of Advanced Transportation

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“…Wheel-rail adhesion parameters are obtained using the maximum likelihood estimation from the speed and other data collected by the train sensors. In [15,16], the adhesion coefficient was detected as a function of slip velocity. The measured wheel velocity was used as input to the extended kalman filter to estimate the slip velocity.…”

Section: Introductionmentioning

confidence: 99%

An Online Super-Twisting Sliding Mode Anti-Slip Control Strategy

Huang

Chen

et al. 2020

Energies

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The variability of rail surfaces can result in wheel-rail slippage, which reduces the accuracy of subway braking systems, or even endangers the operation safety. It is necessary to conduct optimal anti-slip control with the estimation of the wheel-rail adhesion state. In this paper, an online super-twisting sliding mode anti-slip control strategy is proposed for subway vehicles. Firstly, real-time wheel-rail adhesion state estimation is performed by utilizing the recursive least squares algorithm under complex and variable rail surface conditions. Then, the differential evolution algorithm is adopted to search the current optimal slip velocity based on the wheel-rail adhesion state. The super-twisting sliding mode controller is designed to implement the optimal sliding velocity tracking. The controller exploits the high-order derivatives of the sliding mode to eliminate chatter vibration and avoid the effect of disturbance, improving the anti-slip control performance. Finally, the effectiveness of the proposed anti-slip strategy is verified by experimental results.

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“…However, the feedback gain matrix has a large effect on the accuracy of the observer. The Kalman filter method is used to estimate the locomotive adhesion coefficient in [4], which requires a larger data capacity.…”

Section: Introductionmentioning

confidence: 99%

Online Accurate Estimation of the Wheel-Rail Adhesion Coefficient and Optimal Adhesion Antiskid Control of Heavy-Haul Electric Locomotives Based on Asymmetric Barrier Lyapunov Function

Zhao

Zhang

et al. 2018

Journal of Sensors

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This paper proposes a new scheme of online accurate estimation of wheel-rail adhesion coefficient and optimal adhesion antiskid control of heavy-haul electric locomotives (HHEL) based on sliding mode and asymmetric barrier Lyapunov function (ABLF) theory. To achieve optimal adhesion control of the HHEL, it is necessary to precisely estimate the wheel-rail adhesion coefficient. However, the adhesion coefficient is difficult to be measured with a conventional physical sensor. The first novelty of this paper is to design a smart adhesion coefficient sensor based on sliding mode observer (SMO). The perception of the adhesion coefficient is transformed into the observation of load torque of the traction motors, and the wheel-rail adhesion coefficient is further calculated by using the load torque observed value. The HHEL achieves maximum traction from operating in the optimal adhesion point. However, wheel skidding is most likely to occur at this point. According to the changing trend of the adhesive coefficient characteristic curve, the operating state of a locomotive can be divided into two regions: the stable and skid regions. The second novelty of this paper is the adaptation of ABLF to guarantee that the HHEL operated at a stable region and the optimal adhesion antiskid control of HHEL is achieved. Finally, the simulation and experimental results verify the feasibility and effectiveness of the proposed method.

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Extended Kalman filter utilization for a railway traction vehicle slip control

Cited by 7 publications

References 10 publications

Optimal Utilization of Adhesion Force for Heavy-Haul Electric Locomotive Based on Extremum Seeking with Sliding Mode and Asymmetric Barrier Lyapunov Function

Optimal Utilization of Adhesion Force for Heavy-Haul Electric Locomotive Based on Extremum Seeking with Sliding Mode and Asymmetric Barrier Lyapunov Function

An Online Super-Twisting Sliding Mode Anti-Slip Control Strategy

Online Accurate Estimation of the Wheel-Rail Adhesion Coefficient and Optimal Adhesion Antiskid Control of Heavy-Haul Electric Locomotives Based on Asymmetric Barrier Lyapunov Function

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