Existing research on the traction control system（TCS） mainly focuses on control methods, such as the PID control, fuzzy logic control, etc, aiming at achieving an ideal slip rate of the drive wheel over long control...Existing research on the traction control system（TCS） mainly focuses on control methods, such as the PID control, fuzzy logic control, etc, aiming at achieving an ideal slip rate of the drive wheel over long control periods. The initial output of the TCS （referred to as the torque base in this paper）, which has a great impact on the driving performance of the vehicle in early cycles, remains to be investigated. In order to improve the control performance of the TCS in the first several cycles, an algorithm is proposed to determine the torque base. First, torque bases are calculated by two different methods, one based on states judgment and the other based on the vehicle dynamics. The confidence level of the torque base calculated based on the vehicle dynamics is also obtained. The final torque base is then determined based on the two torque bases and the confidence level. Hardware-in-the-loop（HIL） simulation and vehicle tests emulating sudden start on low friction roads have been conducted to verify the proposed algorithm. The control performance of a PID-controlled TCS with and without the proposed torque base algorithm is compared, showing that the proposed algorithm improves the performance of the TCS over the first several cycles and enhances about 5% vehicle speed by contrast. The proposed research provides a more proper initial value for TCS control, and improves the performance of the first several control cycles of the TCS.展开更多
Fault diagnosis of traction systems is important for the safety operation of high-speed trains.Long-term operation of the trains will degrade the performance of systems,which decreases the fault detection accuracy.To ...Fault diagnosis of traction systems is important for the safety operation of high-speed trains.Long-term operation of the trains will degrade the performance of systems,which decreases the fault detection accuracy.To solve this problem,this paper proposes a fault detection method developed by a Generalized Autoencoder(GAE)for systems with performance degradation.The advantage of this method is that it can accurately detect faults when the traction system of high-speed trains is affected by performance degradation.Regardless of the probability distribution,it can handle any data,and the GAE has extremely high sensitivity in anomaly detection.Finally,the effectiveness of this method is verified through the Traction Drive Control System(TDCS)platform.At different performance degradation levels,our method’s experimental results are superior to traditional methods.展开更多
Electric locomotives on the horizon will integrate SiC inverters,promising quicker switching and lower losses than traditional setups.However,in addition to the steep rising edge,the inverter-fed motor drive system fa...Electric locomotives on the horizon will integrate SiC inverters,promising quicker switching and lower losses than traditional setups.However,in addition to the steep rising edge,the inverter-fed motor drive system faces challenges such as high common-mode voltage(CMV)and high motor terminal surge voltage swing rate(dv/dt).To tackle these hurdles,this paper proposes a novel tailored traction control system for three-phase locomotive motors.This innovative strategy utilises nearstate space vector pulse width modulation(NSVPWM),selectively removing space vectors with high CMV to generate modulation signals.Complemented by a slew rate capacitor configuration,the aim is to reduce CMV while effectively suppressing motor-side voltage slew rate.To validate this approach,experimental waveforms from on-site inverter-fed motor drive systems have been analysed to derive high-frequency parameters of long-line cables and variable frequency motors to mimic real locomotive operating conditions better.Through experimental research and comparative simulations against traditional methods,this study reveals a significant 33.3%reduction in CMV compared to traditional systems.Furthermore,it achieves an impressive decrease in the rise/fall slope,down to 86.6%,while ensuring nearly zero electrical power consumption.展开更多
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 meas...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 intelligencebased 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.展开更多
在实现“双碳”目标的背景下,城市轨道交通需要实现节能低碳运行。现有牵引供电系统(traction power supply system,TPSS)采用下垂控制策略存在再生制动能量利用率低、缺乏对系统潮流主动有效控制及优化手段等问题。该文分析双向变流器...在实现“双碳”目标的背景下,城市轨道交通需要实现节能低碳运行。现有牵引供电系统(traction power supply system,TPSS)采用下垂控制策略存在再生制动能量利用率低、缺乏对系统潮流主动有效控制及优化手段等问题。该文分析双向变流器的下垂参数对系统用电量的影响,进而提出一种实现牵引负荷功率最优分配的协同控制方法,该方法对双向变流器的下垂参数实时优化和调整,促进机车再生制动能量的流动,有效提高再生制动能量利用率,显著提升系统协同控制性能。经仿真计算,采用该方法可年节约0.17亿k W·h电量,有效助力城市轨道交通牵引供电系统安全、经济运行。展开更多
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 inter- action. Braking and traction forces depend on the norm...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 inter- action. 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 uti- lization 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 perfor- mance after re-adhesion process even if the wheel-rail contact mechanism exhibits significant adhesion uncer- tainties 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 opti- mal 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 second- order 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.展开更多
基金supported by National Natural Science Foundation of China(Grant Nos. 50905092, 51275557)Open Foundation of State Key Laboratory of Automotive Safety and Energy(Grant Nos. zz2011-052, zz2011-021)
文摘Existing research on the traction control system（TCS） mainly focuses on control methods, such as the PID control, fuzzy logic control, etc, aiming at achieving an ideal slip rate of the drive wheel over long control periods. The initial output of the TCS （referred to as the torque base in this paper）, which has a great impact on the driving performance of the vehicle in early cycles, remains to be investigated. In order to improve the control performance of the TCS in the first several cycles, an algorithm is proposed to determine the torque base. First, torque bases are calculated by two different methods, one based on states judgment and the other based on the vehicle dynamics. The confidence level of the torque base calculated based on the vehicle dynamics is also obtained. The final torque base is then determined based on the two torque bases and the confidence level. Hardware-in-the-loop（HIL） simulation and vehicle tests emulating sudden start on low friction roads have been conducted to verify the proposed algorithm. The control performance of a PID-controlled TCS with and without the proposed torque base algorithm is compared, showing that the proposed algorithm improves the performance of the TCS over the first several cycles and enhances about 5% vehicle speed by contrast. The proposed research provides a more proper initial value for TCS control, and improves the performance of the first several control cycles of the TCS.
基金supported by the National Natural Science Foundation of China(Grant Nos.U20A20186 and 62372063).
文摘Fault diagnosis of traction systems is important for the safety operation of high-speed trains.Long-term operation of the trains will degrade the performance of systems,which decreases the fault detection accuracy.To solve this problem,this paper proposes a fault detection method developed by a Generalized Autoencoder(GAE)for systems with performance degradation.The advantage of this method is that it can accurately detect faults when the traction system of high-speed trains is affected by performance degradation.Regardless of the probability distribution,it can handle any data,and the GAE has extremely high sensitivity in anomaly detection.Finally,the effectiveness of this method is verified through the Traction Drive Control System(TDCS)platform.At different performance degradation levels,our method’s experimental results are superior to traditional methods.
文摘Electric locomotives on the horizon will integrate SiC inverters,promising quicker switching and lower losses than traditional setups.However,in addition to the steep rising edge,the inverter-fed motor drive system faces challenges such as high common-mode voltage(CMV)and high motor terminal surge voltage swing rate(dv/dt).To tackle these hurdles,this paper proposes a novel tailored traction control system for three-phase locomotive motors.This innovative strategy utilises nearstate space vector pulse width modulation(NSVPWM),selectively removing space vectors with high CMV to generate modulation signals.Complemented by a slew rate capacitor configuration,the aim is to reduce CMV while effectively suppressing motor-side voltage slew rate.To validate this approach,experimental waveforms from on-site inverter-fed motor drive systems have been analysed to derive high-frequency parameters of long-line cables and variable frequency motors to mimic real locomotive operating conditions better.Through experimental research and comparative simulations against traditional methods,this study reveals a significant 33.3%reduction in CMV compared to traditional systems.Furthermore,it achieves an impressive decrease in the rise/fall slope,down to 86.6%,while ensuring nearly zero electrical power consumption.
基金supported by University of Pardubice,Czechia,Eskisehir Technical University,Turkey,and Newcastle University,United Kingdom.
文摘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 intelligencebased 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.
文摘在实现“双碳”目标的背景下,城市轨道交通需要实现节能低碳运行。现有牵引供电系统(traction power supply system,TPSS)采用下垂控制策略存在再生制动能量利用率低、缺乏对系统潮流主动有效控制及优化手段等问题。该文分析双向变流器的下垂参数对系统用电量的影响,进而提出一种实现牵引负荷功率最优分配的协同控制方法,该方法对双向变流器的下垂参数实时优化和调整,促进机车再生制动能量的流动,有效提高再生制动能量利用率,显著提升系统协同控制性能。经仿真计算,采用该方法可年节约0.17亿k W·h电量,有效助力城市轨道交通牵引供电系统安全、经济运行。
文摘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 inter- action. 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 uti- lization 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 perfor- mance after re-adhesion process even if the wheel-rail contact mechanism exhibits significant adhesion uncer- tainties 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 opti- mal 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 second- order 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.
