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
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
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 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.
