Modeling and Control of a PMSM Operating in Low Speeds

A permanent magnet synchronous motor is a type of motor that is used in several different application areas, not least in an autonomous robots where it is the motor that drives the wheels. Today, many actors choose simulation as a tool to save money and time when product tests are performed. This thesis covers both the process of modeling a permanent magnet synchronous motor and regulating it at low speeds, in a simulation environment. As previously mentioned, the motor is a permanent magnet synchronous motor and is a direct-driven outrunner, which means that the motor and the wheel are combined and that the rotor is spinning outside the stator. On current robots in production, there is a gear ratio between the motor and wheels to be able to regulate the motor at higher speeds and thus generate a torque. The gearing contributes to losses and is an extra cost, so the examination of a direct-drive motor is interesting. The direct-drive motor has a lower working speed and is therefore by some reasons more difficult to regulate when applying torque load to the motor. The motor is equipped with current sensors and a position sensor, which has a certain resolution. The position sensor is speed-dependent in the sense that at lower RPMs fewer measurements are obtained, which is a problem when regulating the motor. The thesis examines two different control strategies, one of which is a more classic PI control that is often used on the market in various systems and the other is model predictive control (MPC). The latter is an online optimization where, with the help of information about the system, an optimal input signal is calculated and applied. Two different non-linear Kalman filters are also examined, which are implemented with the two different control strategies, to estimate the speed with the help of the measurements from current and the position sensor. The conclusion is an ideal motor model that mimics the physical motor. MPC is able to regulate the motor between 0-50 RPM, both with and without applied torque and even better with speed estimation from a Kalman filter. The PI controller is not able to regulate the motor at 2 RPM but for speeds at 10 RPM and greater, however with over-/undershoot after an acceleration