Design of high performance asynchronous motor speed controller based on vector control[Copy link]
Design of high performance asynchronous motor speed controller based on vector control
Lin Li1, Huang Shenghua2 (1.School of Electrical and Information Engineering, Shaoyang University, Shaoyang, Hunan 422004, China; 2.School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China)
Abstract: Since the vector control algorithm of asynchronous motor is relatively complex, in order to achieve high performance, dual DSP must be used, which reduces the overall cost performance of the system. To solve this problem, this paper uses field programmable gate array (FPGA) to design an intelligent controller to complete a series of complex control algorithms and realizes the dedicated integrated circuit of asynchronous motor vector control speed controller. This circuit is of great significance to the development of vector control asynchronous motor variable frequency speed regulation dedicated chip with independent intellectual property rights.
Keywords: asynchronous motor vector control field programmable gate array intelligent controller control algorithm
Reliability and real-time performance are the basic requirements for control systems. Initially, motor control used analog circuits with discrete components. With the advancement of electronic technology, variable frequency speed regulation technology based on pulse width modulation (PWM) has been widely used in motor control. Today, when the trend of digitalization is widely popular, integrated circuits and even motor control dedicated integrated circuits have been widely used in motor control. In particular, a new design concept has emerged in recent years, namely the hardware implementation technology based on field programmable gate arrays (FPGAs). This technology can be applied to asynchronous motor variable frequency speed regulation systems based on vector control. FPGA itself is a standard cell array and does not have the functions of general ICs, but users can program its internal components through special layout and wiring tools according to their needs, and design their own dedicated integrated circuits in the shortest time, thereby greatly improving the competitiveness of the product. Since FPGA performs parallel processing in a pure hardware manner and does not occupy CPU resources, the system can achieve very high performance. When this design method is applied to asynchronous motor vector control variable frequency speed regulation systems, current control is generally used as a co-processor of the DSP, and the rotor speed and rotor flux algorithms are implemented by the DSP host. Generally speaking, position control is more flexible and difficult to achieve universality, so the position link is generally completed by DSP, but speed control and current control are universal, so they can be integrated into a dedicated chip. In this way, both speed control and current control can be achieved, and the position control system can be formed together with DSP. As shown in Figure 1, if the FPGA is integrated with a CPU core, the three algorithms of position, speed, and current can be completely implemented by one FPGA, thus realizing a true system on chip [1][2] .
Fig.1 Integrated structure of asynchronous motor speed controller systemFig.2 Axis setting of three-phase winding and two-phase winding
FPGA combines the advantages of high logic integration of semi-custom devices with the advantages of short development cycle and low development cost of standard logic devices. It has the advantages of flexible structure, high density, high performance, advanced development tools, no need to test the finished product after programming, and real-time online inspection. The asynchronous motor vector control speed regulation system introduced in this paper follows the basic idea of modular design, studies the digital structure of several main functional modules such as current vector control, speed PI regulation, current PI regulation, feedback speed measurement, current flux conversion, SVPWM, Clarke transformation, Park transformation and Park inverse transformation, and completes the layout and wiring of the main modules in a single Xilinx FPGA to realize the dedicated integrated circuit of the asynchronous motor vector control speed controller [3] . 1 Basic principle of vector control Assume that the axis of the three-phase winding (A, B, C) and the two-phase winding (α, β) of the asynchronous motor are set as shown in Figure 2. The axis of the A-phase winding coincides with the axis of the α-phase winding, both of which are stationary coordinates. The corresponding AC currents are i A , i B , i C and i α , i β respectively . By adopting the absolute transformation with unchanged magnetic potential distribution and power, the magnetic potential F generated by the three-phase AC current in space is equal to the magnetic potential generated by the two-phase AC current. That is, by adopting the orthogonal transformation matrix, the forward transformation formula is: The inverse transformation formula is: The transformation from the two-phase stationary coordinate system (α, β) to the two-phase rotating coordinate system (dq) is called Park transformation. α and β are stationary coordinate systems, and dq is a rotating coordinate system rotating at an arbitrary angular velocity ω. When the α and β stationary coordinate systems are transformed into the dq rotating coordinate system, the coordinate axis is set as shown in Figure 3. In Figure 3, θ is the angle between the α axis and the d axis. The d and q windings are placed vertically in space, and the DC id and iq are added. The d and q coordinates are rotated at the synchronous speed ω, and the generated magnetic motive force is equivalent to the α-β coordinate system. The angle θ between the dq and α-β axes is a variable, which changes with the load and speed, and has different values at different times. The Park transformation, written in matrix form, has the following formula:
Figure 3 α-β coordinates
Vector control is also called field-oriented control. Its basic idea is to simulate the control method of DC motors for control. According to the principle of constant magnetic potential and power, the three-phase stationary coordinates are transformed into two-phase stationary coordinates through orthogonal transformation (Clarke transformation, i.e. 3Φ/α-β transformation, the coordinate transformation relationship is shown in Figure 2, and the quantitative relationship is shown in Formula (1)). Then, the two-phase stationary coordinates are transformed into two-phase rotating coordinates through rotation transformation (Park transformation, i.e. (α-β/dq transformation, the coordinate transformation relationship is shown in Figure 3, and the quantitative relationship is shown in Formula (3)). Under the α-β/dq transformation, the stator current vector is decomposed into two DC components id and iq ( where id is the excitation current component and iq is the torque current component) oriented according to the rotor magnetic field, and they are controlled separately. Controlling id is equivalent to controlling the magnetic flux, and controlling iq is equivalent to controlling the torque. The two DC components id and iq are respectively transformed by the speed and current PI regulators through current-voltage transformation and Clarke inverse transformation (the coordinate transformation relationship is shown in Figure 2, and the quantitative relationship is shown in formula (2)), Park inverse transformation (the coordinate transformation relationship is shown in Figure 3, and the quantitative relationship is shown in formula (4)) and voltage space vector transformation to obtain 6 PWM signals for controlling the inverter, thereby realizing variable voltage and frequency control of the asynchronous motor. 2 Digital hardware design of the controller The digital hardware design of the asynchronous motor speed controller mainly includes Clarke transformation, Clarke inverse transformation; Park transformation, Park inverse transformation; current PI regulation module, speed PI regulation module; voltage space vector module; rotor flux calculation module and speed detection module. The main circuit and data operation path of the vector control asynchronous motor speed regulation system are shown in Figure 4. 2.1 Vector transformation module design: Vector transformation includes phase coordinates and coordinate rotation forward and inverse transformation. Equations (1) to (4) give the quantitative calculation formulas of the corresponding transformations. The digital implementation of equations (1) and (2) is relatively simple. One adder and one multiplier can complete the transformation operation. The coordinate rotation forward and inverse transformation determined by equations (3) and (4) can be calculated by looking up a sine table or Taylor series expansion in engineering practice to complete the corresponding functions. 2.2 PI regulator module design
Figure 4 Data path of speed controller
Both the current inner loop and the speed outer loop are regulated according to the PI control strategy. Equation (5) is the iterative formula of the dual linear transformation PI regulator. O[n]=P[n]+I[n] (5) The iterative formula of the proportional term is: P[n]=Kp·E[n] (6) The iterative formula of the integral term is: I[n]=I[n-1]+K h (E[n]+E[n-1]) (7) Where E[n] is the error input, Kp is the proportional gain, and Kh is the integral gain. The range of Kp and Kh is determined by the motor parameters, and their specific values need to be determined through experiments. To prevent overflow, the regulator sets a saturation limit. The current PI regulator outputs a voltage command, which is sent to the SVPWM module after compensation in the form of a modulation coefficient; the speed PI regulator outputs a reference current command, which is directly sent to the current regulator. Whether it is a current regulator or a speed regulator, if the reference command value is relatively large, its integrator may establish a large error value, and due to the inertia of the integrator, this error will remain for a long time, which will lead to excessive overshoot. Therefore, when designing a PI regulator, the integral action should be turned off immediately when the output of the integrator exceeds the limit value to reduce the impact of excessive overshoot. 2.3 Design of M/T method speed measurement module The key issue of the asynchronous motor vector control variable frequency speed controller based on rotor magnetic field orientation is the measurement of rotor position and feedback speed. This scheme uses incremental photoelectric encoder and Hall element as position detection devices. When the power-on reset is performed, the Hall element roughly detects the initial position of the motor rotor for soft start. When the Z pulse of the encoder appears, accurate position information can be obtained. The position count is performed at 4 times the frequency of the two orthogonal output pulses QEP1 and QEP2 of the encoder, and its pulse waveform is shown in Figure 5. The speed is measured using the M/T method. The M/T method absorbs the advantages of the T method on the basis of the M method. The process of measuring the speed is as follows: start the timer (timing length is Tc) at the falling edge of the speed output pulse, and record the number of speed output pulses m l and the number of clock pulses m 2 at the same time. When the measurement time is up, stop counting the number of speed output pulses first, and then stop counting the clock pulses when the next falling edge of the speed output pulse arrives, so as to ensure that the output pulses of the entire speed sensor are measured. The set basic measurement time TC can avoid the disadvantage of the T method that the measurement time is reduced due to high speed; at the same time, reading the count value of the clock pulse can avoid the disadvantage of the M method that the accuracy is reduced due to the reduction of speed. Its measurement time is: (8) The m l value in the formula can no longer have an error of 1 pulse, so the measurement error of the M/T method can only be caused by the error of one pulse in the count value of m 2 , and its relative error is , and its speed measurement principle is shown in Figure 6.
Figure 5 Pulse waveform Figure 6 Principle of speed measurement using the M/T method
2.4 Voltage Space Vector Module Design The voltage space vector pulse width modulation method is also called the flux tracking PWM method. This method regards the motor and the inverter as one, focusing on obtaining a circular magnetic field with a constant amplitude for the motor. The ideal flux in the AC motor when powered by a three-phase symmetrical sinusoidal voltage is used as a reference, and the effective flux vector generated by different switching modes of the inverter is used to approximate the reference circle. Theoretical analysis and experiments show that SVPWM modulation has small pulsating torque, low noise and high DC voltage utilization (about 15% higher than ordinary SPWM modulation). This control method has been widely used in frequency converters and inverters. The voltage space vector structure block diagram is shown in Figure 7.
Figure 7 Voltage space vector hardware structure
The synthesis of the symmetrical/asymmetrical waveform generator, output logic circuit, and space vector state machine in the figure is controlled by the corresponding bits of the comparison control register. The specific working principle can be found in references [5] and [6]. In addition to the above main modules, there are also auxiliary modules such as communication module, register stack, and monitoring and protection. The communication module is mainly used to exchange data with DSP or host (see Figure 1). All these modules constitute a complete speed follow-up controller and are implemented in one FPGA. 3 FPGA implementation and experimental results of hardware design All modules in the design circuit of the high-performance asynchronous motor speed controller based on vector control are described in the hardware language VHDL. After the source code passes the functional simulation and timing simulation test, it is synthesized by SynPlify software to generate EDF netlist files, and finally implemented in Xilinx FPGA (SpartanⅡE-XC2S300E) device, where the layout and wiring of the device are completed in Xilinx integrated development environment ISE5.li. The system resource utilization is shown in Table 1. The equivalent number of gates consumed by the entire design is about 350,000, which is basically close to saturation. If future functional expansion is considered, a chip with larger capacity will be needed, but the existing design can be reused without major modifications [7] .
The clock frequency of the asynchronous motor speed controller IC system in this design can run at 33.33MHz, and the internal registers can be accessed through the host computer to set various relevant parameters in the control system. This IC chip can form a complete system with TMS320L2812 DSP and other circuits to realize position follow-up control, or it can form a speed follow-up control system alone. In the experiment to test the performance of the speed controller, the drive object is a 1.5kW asynchronous motor with a maximum speed of 4900r/min and an encoder line number of 4900, and the switching frequency and sampling frequency are both set to 12kHz. Figures 8 and 9 show the motor rotor speed tracking curve and α-axis current response curve measured under different speed commands. The speed command in Figure 8 is a step input from 0 to 1168 r/min, with a dynamic response time of less than 0.5 ms, a maximum overshoot of less than 0.8%, and a steady-state error of less than 0.02%. The speed command in Figure 9 is a ramp input, with an acceleration of 0.42 r/min/sample, a target speed of 495 r/min, a dynamic tracking error of less than 4%, and a steady-state error of about 0.03%. If the switching frequency and sampling frequency are further increased, the operating performance of the control system will be even better [8].
Fig.8 Response curve under step speed commandFig.9 Response curve under ramp speed command
Monolithic integration, hybrid integration and system integration can be regarded as different levels and forms of power electronics integration. At present, monolithic integration is limited to the small power range; hybrid integration or a combination of hybrid integration and system integration is mostly used in the medium power field; system integration is still the main form in the high power field. Monolithic integration and hybrid integration are the main development direction of future integration technology due to their higher integration and better performance [9] . The FPGA-based asynchronous motor variable frequency speed regulation dedicated IC designed in this paper integrates Clarke transformation, Park transformation, Park inverse transformation, speed PI regulation, current d-axis PI regulation, current q-axis PI regulation, rotor flux positioning and speed detection, voltage space vector pulse width modulation and PWM waveform generation algorithms. The sampling frequencies of the speed outer loop and the current inner loop can reach 35kHz and 20kHz respectively. Experimental results show that the dedicated controller has good dynamic and static performance during operation. The dedicated IC has been applied in high-performance integrated CNC systems and has achieved good practical results. It has a very important reference value for the development of vector control asynchronous motor variable frequency speed regulation dedicated chips with independent intellectual property rights. References 1 Huy H L.Microprocessors and Digital IC′s for Motion Control. Proc IEEE,1994;82(8) 2 Holtz J.Pulse Width Modulation-A Survey.IEEE Trans Ind Electron,1992;39(5) 3 Oldfield JV,Dorf R C.Field Programmable Gate Arrays.New York: Wiley,1995 4 Jenkins J H.Designing with FPGA′s and CPLD′s.Englewood Cliffs,NJ:Prentice-Hall,1994 5 Broeck HWV,Skudelny H,Stanke G V.Analysis and Rea-lization of a Pulsewidth Modulator Based on Voltage Space Vector.IEEE Trans Ind Applicate,1988;24(1) 6 Liu Heping, Yan Liping, Zhang Xuefeng, etc.TMS320LF240X DSP structure, principle and application. Beijing: Beijing University of Aeronautics and Astronautics Press, 2002 7 Morimoto M, Sato S, Sumito K et al. Single-Chip Microcom-puter Control of the Inverter by the Magnetic Flux Control PWM Method. IEEE Trans Ind Electron, 1989; 36(1) 8 Zhou Zhaoyong, Li Tiecai. FPGA implementation of high-performance AC motor speed servo controller based on vector control. Proceedings of the CSEE, 2004; 24(5) 9 Wang Zhaoan, Yang Xu, Wang Xiaobao. Current status and development direction of power electronics integration technology. Power Electronics Technology, 2003; 37(5)
We know that when there is a finite distributed force, the resultant force forms a vector operation relationship with the finite distributed force. Changing a certain distributed force to adjust the motion state is called vector control. For example, vector push. Vector control is complex and has a stable point problem (the adjustment range of each vector must be mutually restricted and cannot be unstable). But vector control is very flexible.
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Published on 2009-12-23 16:44
We know that when there is a finite distributed force, the resultant force forms a vector operation relationship with the finite distributed force. Changing a certain distributed force to adjust the motion state is called vector control. For example, vector push. Vector control is complex and has a stable point problem (the adjustment range of each vector must be mutually restricted and cannot be unstable). But vector control is very flexible.
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