Low-Speed High-Torque Permanent Magnet Synchronous Motor And Its Control System

Centreing around the permanent magnet synchronous motor, two parts of researches on the motor optimization design and the drive control are systematically introduced in this dissertation.Based on the theory of axes transformation, the mathematic models of PMSM in three-phase stationary coordinates, two-phase stationary coordinates and two-phase rotating coordinates are analyzed in details. SVPWM method is introduced in the second chapter. The AC-AC transformation control and the double SVPWM scheme of the matrix converter are deduced from the equivalent structure of the AC-DC-AC conversion in the third chapter.In order to validate the feasibility of the SVPWM strategy for permanent magnet synchronous machine based on matrix converter and the correctness of the modulation method, the simulation model of vector control speed regulating system for a lower- speed high-torque PMSM is firstly established based on Matlab. Then the input and output characteristics of matrix converter, the speed, torque and load characteristics of the PMSM are then analysed. The simulation results show that it can realize the separate modulation of the output voltage amplitude and frequency. Besides, the excellent waveforms of input current and output voltage, unit value power factor reveal the matrix converter system has the ability of four guardant operations. It has unexampled merits on controllable input power factor, power regeneration and lack of bulky energy storage capacitors.After simulation, a PMSM control system based on matrix converter is experimented, which uses DSP TMS320F2812 as main controller and FPGA EP1C6 as coprocessor. DSP carries out space vector modulation, and FPGA carries out switch functions synthesis and four step commutations. They together accomplish the modulation of sine wave input current and output voltage. The excellent startup characteristic, high control precision, quick dynamic response and good adaptability are ensured which can be seen from the experiment results. All the data indicate again that the method in this dissertation is effective.On the subject of high nonlinear existing in optimization design, a sort of multi-objective particle swarm optimization algorithm based on fuzzy expert system is proposed in the fourth chapter. The man expert experiences on design are imported into the artificial fuzzy expert system, and then join in the speed equations of the particle swarm. Thus lead the dominant subsets move to the directions of optimal solution. Fuzzy expert system improves the optimization process of multi-objective particle swarm optimization algorithm, and advances the convergent rate and solving precision. The other novel point in this dissertation is that the optimization problem is translated into game problem. The optimized goals are regarded as the game individuals, an optimization design methods of PMSM based on game theory is proposed. Surrounding Pareto optimum under Nash equilibrium, the concession negotiation strategy between the game individuals is applied to the optimized goals in order to get a better global negotiation result. The motor design cycle is simplified by searching the unitary optimal result from non-inferior solution set. For the error due to machining and assembly and the disturbance, the robustness design idea is introduced in motor design. The non-inferior solutions are evaluated and arranging by signal noise ratio. The sensitiveness analysis idea is also introduced in motor design to reveal the interrelation between every design parameter and the optimized goals. At last, a PMSM is optimized by multi-objective particle swarm optimization algorithm based on fuzzy expert system. The result shows that the design method has the merit of high efficiency, and the integrated characteristic of the motor after optimization design is improved.