Estimation of railway vehicle suspension parameters for condition monitoring

Li, Ping; Goodall, Roger M.; Weston, Paul; Ling, Chung Seng; Goodman, C.J.; Roberts, Clive

doi:10.1016/j.conengprac.2006.02.021

Cited by 129 publications

(61 citation statements)

References 12 publications

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“…The method can detect the errors in the system, but can do nothing about the obsolescence of the systems. Document [5][6][7] establishes a model of horizontal state space vehicle system. Under the normal operation state of the vehicle, it uses the algorithm of parameter estimation based on the Particle filter and the Kalman filter to estimate the secondary lateral damping, the secondary AntiRoll Bar damping and Wheelset equivalent taper.…”

Section: Introductionmentioning

confidence: 99%

Research on vehicle diagnosis based on state-space method

Xue¹,

Chai²,

Zheng³

2015

AIR

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In this paper, the vehicle faults are estimated and diagnosed by introducing wavelet transform, based on the state-space method. It monitors the state of railway vehicle suspension system, establishes a vertical dynamic state-space model of railway-vehicle system to identify the parameters of vehicle suspension system. The simulation results show that, in the circumstances of the change of the parameters which is resulted from the gradual fault or the composite fault of the suspension system, the simulation results can effectively identify the basic characteristics of its parameters, realize vehicle fault diagnosis, so as to achieve the purpose of monitoring the state of suspension system, and provide a method for rail vehicle online condition monitoring.

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Section: Introductionmentioning

confidence: 99%

Research on vehicle diagnosis based on state-space method

Xue¹,

Chai²,

Zheng³

2015

AIR

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“…The creep force applied on a wheel creep F is computed based on the distribution of shear stresses on the wheel-rail contact surface (Polach, 1999(Polach, , 2005Leva, Morando, and Colombaioni, 2008;Colombo et al, 2014;Li et al, 2007). In this regard, x and y components of the creep force have been taken to be proportional to the longitudinal creep and lateral creep, respectively.…”

Section: Frictional Forces Exerted On the Wheelsmentioning

confidence: 99%

Adaptive Fuzzy Sliding-Mode Control of Wheel Slide Protection Device for ER24PC Locomotive

Mousavi

Markazi

Masoudi

2017

Lat. Am. j. solids struct.

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Wheel Slide Protection Devices (WSPD) are employed in railway vehicles to maximize the average of the possible frictional braking force, which is a nonlinear function of the slip ratio of the wheel sets. In this paper, to control the WSPD, a low-order model is presented and un-modeled dynamics are considered as uncertainties. Due to the nonlinear dynamics of the system and presence of uncertainties, Adaptive Fuzzy Sliding-Mode Control (AFSMC) is employed to regulate the slip ratio towards the desired value. The proposed controller employs a Pulse Width Modulation (PWM) technique to generate the braking torque. The second Lyapunov theorem is used to prove the closed-loop asymptotic stability. In the simulations, the switching dynamics of WSPD is considered and the multi-body dynamics method is used for modeling the longitudinal dynamics of ER24PC locomotive. The obtained results reveal that by using the AFSMC method, the slip ratios of wheel sets converge to the reference values. Unlike the conventional method, in which the fluctuations of slip ratio diverge near the stopping time, simulation studies reveal that with the AFSMC method, the stopping time of the locomotive and the fluctuation amplitude of the slip ratios are reduced.

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“…It concludes that the on-board methods can be allocated into model-based and signal-based. The model-based methods mainly include: inverse modelling methods [5], Kalman filter [6,7], extended Kalman filter, unscented Kalman filter [8] and RaoBlackwellised particle filter [9,10]. Each model-based method has its adaptable conditions and drawbacks.…”

Section: Introductionmentioning

confidence: 99%