Abstract
This paper deals with the digital implementation of a motor control algorithm based on a unified machine model, thus usable with every traditional electric machine type (induction, brushless with interior permanent magnets, surface permanent magnets or pure reluctance). Starting from the machine equations in matrix form in continuous time, the paper exposes their discrete time transformation, suitable for digital implementation. Since the solution of these equations requires integration, the virtual division of the calculation time in sub-intervals is proposed to make the calculations more accurate. Optimization of this solver enables faster runs and higher precision especially when high rotating speed requires fast calculation time. The proposed solver is presented at different implementation levels, and its speed and accuracy performance are compared with standard solvers.
Highlights
Performance Discrete Flux IntegratorIn the Field Oriented Control (FOC) of electrical machines the rotor flux direction must be known to operate the d-q axis transformation and de-couple the control scheme [1], allowing a simple and efficient control strategy
This paper deals with the digital implementation of a motor control algorithm based on a unified machine model, usable with every traditional electric machine type
A flux observer is required for any sensorless application such as permanent magnets [10], reluctance [11], or induction machines [12] that all use the machine equations to find the rotor flux angle, since this operation is intended for applications without the direct measurement of the rotor position and speed
Summary
In the Field Oriented Control (FOC) of electrical machines the rotor flux direction must be known to operate the d-q axis transformation and de-couple the control scheme [1], allowing a simple and efficient control strategy. In case of high electric speeds, PWM frequencies are kept very high to enable faster and more precise flux variations to extract more performance from the motor, such higher torque, lower ripple or higher dynamic response In this case, more speed means higher PWM frequencies and less execution step-time and, often, the limiting factor is the DSP capability to perform the calculation necessary inside the available portion of the PWM cycle. This paper describes the details of the discrete solver for flux estimation with the optimizations introduced to obtain the best trade off between computational requirements and model precision. There is the most common discretization method that substitutes the integration step with a single discrete integration This is meant to be a good implementation that can run on real-time systems, giving a baseline for speed and accuracy without optimizations.
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