Research On Identification Of Physical Parameters And Excitation Parameters Of Rail Vehicle System

With the rapid development of China’s railway industry,vehicle system dynamics based on vibration mechanics and multi-body system dynamics have also developed rapidly.Optimal design is the primary task of vehicle system dynamics research.Considering various boundary conditions during vehicle operation,increase vehicle operating speed,reduce vibration generated during vehicle operation,and improve operating stability.When building a dynamic simulation model,it is necessary to accurately define the physical parameters and mechanical characteristics of the vehicle to make the simulation analysis more realistic.Therefore,the identification of physical parameters and excitation parameters of the vehicle system is the basic prerequisite for theoretical calculation and virtual prototype simulation analysis and optimization of vehicle performance.In addition,it can be checked whether the actual parameters of the prepared vehicle are consistent with the design parameters,and whether the parameters of the degraded components still meet the original design limits after the train has been in service for a period of mileage.This paper studies the above problems,and proposes a test procedure and method that can simultaneously identify the mass parameters,inertia parameters and suspension parameters of the rail vehicle system.The physical parameter identification of bogie system,vehicle system and equipment system are studied.At the same time,the identification method of excitation parameters of eccentric equipment is studied,and the time domain method and frequency domain method of excitation force identification of active equipment are improved.This paper first gives the theoretical formulas of the direct method and the indirect method for the identification of the physical parameters.The direct method is only suitable for single-degree-of-freedom systems,and the indirect method is also suitable for multi-degree-of-freedom systems.Combining the two situations of known partial physical parameters and unknown physical parameters,different identification methods are proposed.Partial physical parameters identification method requires a certain physical parameter to be known,and unknown physical parameters identification method requires additional known masses for parameter identification.A three-dimensional dynamic model of the bogie system is established and verified.A field test process and method that does not rely on professional test benches is proposed.The bogie system sprung mass,roll inertia,pitch inertia,yaw inertia,vertical stiffness,vertical damping,lateral stiffness and lateral damping parameters are identified.The recognition errors of the direct method and the indirect method are compared,and it is found that the indirect method has better recognition effect than the direct method.The recognition errors of different signal types such as displacement signal,velocity signal and acceleration signal are analyzed when the system is freely vibrating,and it is found that the acceleration signal has higher recognition accuracy than the displacement signal and the velocity signal.The physical parameter identification test is carried out on a certain type of bogie system,and the Gaussian smoothing filter is used for signal processing.Under the condition of known suspension stiffness and damping parameters,the sprung mass,roll inertia,pitch inertia and damping parameters of the bogie system are identified.A three-dimensional dynamic model of the vehicle system is established and verified.A field test process and method that does not rely on professional test benches is proposed,and the displacement signal,velocity signal and acceleration signal are obtained when the system is freely vibrating.Car body mass,car body roll inertia,car body pitch inertia,car body yaw inertia,frame mass,frame roll inertia,frame pitch inertia,frame yaw inertia,secondary vertical stiffness,secondary vertical damping,secondary lateral stiffness,secondary lateral damping,primary vertical stiffness,primary vertical damping,primary lateral stiffness and primary lateral damping are identified using indirect methods.For the same signal type,comparing the recognition errors of different recognition methods,it is found that the recognition effects of the state space method and the modal space method are basically the same.For the same recognition method,comparing the recognition errors of different signal types,it is found that the recognition error of the displacement signal is the largest.A physical parameter identification test is carried out on a small-scale rail vehicle model.Under the condition that all the physical parameters are unknown,the pitch inertia and the vehicle distance parameters are identified.For physical parameter identification of eccentric equipment.Firstly,the parameters of the equipment weight and the position of the center of gravity are obtained through the static load test.Then the inertia parameters,supporting stiffness and supporting damping parameters of the equipment are obtained through dynamic test.The influence of static load test error on dynamic parameter identification is also discussed.The excitation parameter identification method for eccentric equipment is studied,which can identify the excitation force amplitude curve and the two-dimensional eccentricity parameters of the excitation force.The analysis of the influence of frequency ratio and damping ratio on the results of excitation parameter identification shows that the larger the frequency ratio,the smaller the identification error,and the larger the damping ratio,the larger the identification error.The excitation force identification test is carried out through the equipment excitation parameter identification test bench,and the excitation force amplitude curves of different frequencies are effectively identified.Aiming at the problem that it is difficult to obtain accurate statistical characteristics of noise in practical engineering applications,which leads to the divergence of excitation force identification,the modified Sage-Husa adaptive Kalman filter is used to improve the time domain method of excitation force identification.The excitation force and excitation torque of the equipment dynamics model under the support state are identified and studied.In the laboratory,the excitation force identification test is carried out through the excitation force recognition test bench.Under different excitation frequencies,the identification value of the excitation force amplitude is very close to the actual value.Aiming at the shortcomings of the basic methods of frequency domain identification,the optimal condition number criterion is proposed to further improve the recognition effect.The least squares method and Tikhonov regularization method based on L-curve,general cross-validation,and generalized cross-validation are compared.The influence of measurement point position and measurement noise on the identification accuracy of random excitation force and harmonic excitation force is studied.It is concluded that the excitation force identification method shows different robustness to models of different complexity.The validity of the optimal condition number criterion for improving the identification accuracy is verified for the identification of excitation force of different structures.The excitation force identification test of the floor structure and the air compressor equipment are carried out respectively.The validity of the above recognition method is proved by the floor structure excitation force recognition test.The air compressor equipment excitation force is obtained through the air compressor equipment excitation force identification test.In the finality,the problems requiring further studies are discussed.