Application of the hottest speed sensorless vector

The application of speed sensorless vector system in vehicles

Abstract: combined with the application of speed sensorless vector control system in vehicles of Guangzhou Metro Line 3, this paper introduces the control structure, speed estimation method and estimation model of speed sensorless vector control system SITRAC, and demonstrates that the system also has complete reliability at low speed by analyzing the test data of low-speed working point

key words: SITRAC traction control high-end paper products rely on imported systems; Speed sensor; Vector control

0 introduction

as people have higher and higher requirements for the comfort of subway trains, the traction system, as the core component of subway trains, must have higher and higher dynamic speed regulation performance. Guangzhou Metro Line 3 is the first fast (120 km/h) Metro Line in China. Since its trial operation for more than half a year, its excellent traction performance has been highly praised by passengers, and the stable and reliable traction system has reduced the maintenance workload of vehicles. In this paper, the control structure and algorithm of SITRAC traction control system used in this vehicle are introduced in detail. Combined with the practical application of this system in Guangzhou Metro Line 3, the reliability and stability of the speed sensorless control system are proved

1 basic principle of speed sensorless vector control

the so-called speed sensorless variable frequency speed regulation control system cancels the speed detection device of the variable voltage variable frequency speed regulation system, and calculates the actual speed value of the traction motor during train operation through indirect calculation method as the speed feedback signal. We call this model for calculating the actual value of speed as speed estimator. Its basic composition principle is: install voltage sensors and current sensors on the stator side of the motor, and detect three-phase voltages UA, UB, UC and three-phase currents IA, IB, IC. According to the 3/2 transformation (transformation from three-phase shafting to two-phase shafting in vector control), the two-phase voltage us in the static shafting α， us β And two-phase current is α， is β， Stationary shafting by stator（ α- β) The two-phase voltage and current in can calculate the stator flux and estimate the actual speed of the motor. The structure of the speed estimator is shown in Figure 1

because the speed estimator is affected by rotor parameters, the speed estimator based on rotor flux orientation also needs to consider the changes of rotor parameters. In addition, the practicability of the speed estimator also depends on its accuracy and rapidity. With the continuous improvement of computer operation performance and speed, modern vector control methods have been able to control the magnetic flux and torque in inductive equipment with a high degree of dynamics. At the same time, in order to suppress high-frequency mechanical vibration, optimize the electromagnetic noise of traction system components and obtain the lowest foreseeable harmonic current, it is necessary to use the calibrated and optimized IGBT control pulse. Siemens' new traction control system SITRAC not only meets this cutting-edge requirement, but also realizes speed sensorless control. This new control feature reduces the complexity of the driver and enhances the reliability of the system. The control characteristics of SITRAC are:

1) speed sensorless operation enhances the reliability of the system

2) the highly dynamic set value effectively attenuates the electrical and mechanical effects

3) high disturbance dynamics: the stability of the traction system is enhanced by resisting the disturbance caused by the track and power supply system

4) advanced optimized pulse mode: high conversion and utilization, which limits the response to the power system and machinery

5) continuous intersection in pulse mode: high conversion utilization, continuous impact free work

6) self adjustment, automatic parameter identification, automatic traction system self inspection: simplify debugging, improve diagnosis and maintenance

7) advanced programming language "ANSI-C": independent hardware

8) integrated software simulation, short development time and perfect software design enhance the quality of the software

2 control structure of the system

Figure 2 is the block diagram of SITRAC speed sensorless control system. This control model illustrates a complete inverter model. The motor model in the figure is used for the current controller computer "Symposium on the utilization of biological high molecular materials", which has formed the stator current and magnetic flux space vector of its brand and characteristics mechanical equipment model. The input of the motor model is only necessary to understand the performance of the bar under actual shear conditions. Due to the general sampling frequency of 2000Hz, the vector and the estimated speed, as well as the mechanical parameters that are also estimated values. In this system, the motor voltage is not measured, but reconstructed by inverter gating signal, DC voltage measurement, motor current and related IGBT parameters. The motor speed is estimated by comparing the measured current space vector with the model stator current space vector

3 speed estimation strategy of speed sensorless traction system

in the speed sensorless traction system, in order to identify the speed, an accurate model of inductive equipment must be established, which estimates the motor flux and stator current space vector based on the calculated stator voltage and the estimated motor parameters. Since the motor model must be accurately described by relevant modules, the model parameters of the motor must be adjusted with the saturation and the temperature changes of stator and rotor windings. In the steady state, the difference between the measured and estimated stator current space vector can be used to estimate the parameters of the motor independently. When the stator frequency is close to zero, it is only theoretically possible to estimate the stable speed. In fact, the difference between the model parameters and the actual system is inevitable. In order to estimate the speed, it is necessary to set a minimum stator frequency fsmin. In order to minimize this certain sub frequency fsmin, the stator impedance and stator voltage difference between the motor model and the actual motor (see Figure 3) must be kept as small as possible. At low frequency, the amplitude of the basic stator voltage space vector is relatively small, so the stator impedance or the modeling error of the inverter tube have a great impact on the speed estimation

through various off-line measurements, the characteristics of the inverter can be determined. At low frequency, the stator impedance must be determined as a secondary side model parameter. Since the rotor impedance changes with the stator winding temperature, it is necessary to accurately measure the parameters of the stator winding in order to estimate the speed

at each stop (speed is zero), a short-term measurement is used to identify the stator and rotor impedance, so that it is possible to start the train next time with accurate motor parameters. Here, the stator impedance is estimated after excitation (in Figure 4: 0.2 s