Motion Control Research Center Develops Speed Control System for SRM Drives
- Created on Saturday, 01 April 2006
The Center for Rapid Transit Systems at Virginia Tech (Blacksburg, VA) is an internationally recognized drive systems and motion control research group with expertise in the design, simulation, and control of switched reluctance motor (SRM) drives and power converter topologies.
Because of its mechanical simplicity and low cost, the SRM has become the subject of great interest in the field of electrical motor drives. Virginia Tech sought to develop a real-time speed control system for SRM drives, which involved designing, prototyping, and deploying an experimental environment for developing new SRM simulation, control system, and drive technology.
The Center chose LabVIEW graphical development software from National Instruments (Austin, TX) to create a design and simulation platform for developing new control algorithms and power electronics. With the Lab-VIEW Simulation Module, the engineers simulated the closed-loop system dynamics of the SRM, and used the LabVIEW Control Design Toolkit to design the motor current and speed control loops. The lookup table (LUT) functions in LabVIEW represented nonlinear relationships in the simulation model.
SRMs have a nonlinear, three-dimensional relationship that relates inductance and torque to current and position. A model was added for the power electronics N+1 converter, which was invented by Virginia Tech professor Krishnan Ramu. A LabVIEW block (for the commutation logic used to control the converter) was added to the model and the block was validated using simulation.
A simulation was conducted at 1,000 rpm to prove the validity of the commutation logic and closed-loop speed control system. The simulation included a precise model of the two-phase SRM, N+1 converter, commutation logic, two proportional integral derivative (PID) controllers, and two routines to find the inductance and the torque from the magnetization characteristic LUTs of the motor. For the continuous solver method, the Runge-Kutta 4 solver was used. After tuning, the control system performed well with a speed overshoot of less than 1 percent under no-load conditions and a settling time of about 50 ms.
The control strategy development for SRM drive systems is more complicated than other types of motors because the machine inductance is a function of both the rotor and excitation current, even for small currents. Using LabVIEW, the team developed a complex dynamic simulation model in which they could include all of the programming structures of a complete programming language, such as case structures, for loops, and formula nodes. A formula node was used to easily make several control blocks, such as the model of the two-phase SRM, N+1 converter, and the commutation logic.
The LabVIEW environment also was used to model special phenomena such as the reduction of the negative torque in the running motor. In the simulation diagram, traditional LabVIEW code was mixed with model-based simulation objects such as the transfer function block. The code was portable, and the control algorithms and logic developed later in the process for real-time control could be reused. With these simulations, the team was able to validate the actual code used in the real-time target.
To demonstrate real-time speed control of the SRM, the team connected the N+1 converter and two-phase SRM to a CompactRIO industrial control and acquisition platform. The CompactRIO I/O modules and user-programmable FPGA (field programmable gate array) were used to connect the control algorithms to the actual motor hardware. The FPGA offered the ability to provide high-speed control of the power converter circuitry and motor current. The real-time control system software comprised five key modules: pulse-width modulation (PWM), commutation logic with programmable advance and commutation angles, high-speed inner current control loop, slower outer speed control loop, and self-starting logic.
The team was able to capture the multirate cascaded control system logic in an intuitive graphical embedded software application. Because the Lab-VIEW control algorithm code developed during the design and simulation phase could be reused, the team was able to fine-tune the current control loops based on PI gains calculated during simulations. Consequently, the team was able to verify the simulation models using practical, measured data and create a reconfigurable platform to iteratively improve the simulation models, power electronics, and control system designs.