This paper presents an extended dq0-model for small delta-connected Permanent Magnet Synchronous Machines (PMSM), the design of a prototype and the parameterization of the model parameters by testbench measurement. The familiar dq-fundamental equations are thereby extended to consider harmonic effects. This allows the inclusion of the zero-sequence flux-linkage. The model, based on the dq0-flux-linkages and the stator resistance, enables the calculation of the zero-sequence current and a more precise inner torque estimation compared to state of the art fundamental models. The rotor position dependent dq-flux-linkage estimation is based on the measured dq-voltages and the solution of the simplified differential system equation. Detection of the zerosequence current yields to the zero-sequence flux-linkage. In this paper, we also present a prototype design of a PMSM machine with additional zero-sequence current sensing. Testbench measurement at constant controlled currents enables the parameter identification. For validation, the identified parameters are compared with existing Finite Element Analysis.

This paper presents an extended predictive trajectory control scheme combined with an inner torque ripple minimization considering the current-, flux-linkage-, and voltage-planes of permanent magnet synchronous machines. The extension of a fundamental machine model with flux-linkage harmonics allows the calculation of the inner torque ripple and enables its minimization. For this, the control is divided in two cases: (1) The dynamic operation or large signal behavior which uses the maximal torque gradient for the trajectory strategy during each control period for fastest dynamic operation, and (2) The stationary operation or small signal behavior, utilizing a real time capable polynomial approximation of the rotor position dependent torque hyperbolas (iso-torque curves) of permanent magnet synchronous machines for the ideal torque to current reference values. Since dynamic and steady-state operation is covered, torque to current look-up tables, such as maximum torque per ampere (MTPA)/maximum torque per volt/voltage (MTPV) look-up tables, are not required anymore. The introduced, new control approach is implemented in Matlab/Simulink based on finite element analysis and measured data. Furthermore, test-bench implementations based on measurement data are presented to show the real-time capability and precision.

This paper shows a fast online parameter identification method for permanent magnet synchronous machines (PSMs), which uses the PWM (pulse width modulation) excitations and no additional test signals. Based on the inverter induced current slopes, the corresponding applied voltages, the rotor angle and a precise machine model, the model's parameters are calculated. Thereby the machine model consists of the dq-system equations, linearized within one PWM period. For stable and precise identification of the PSM machine parameters, the machine model has to be modified with a regularization approach. The identified parameters enable self-commissioning, tuning of the control parameters, condition monitoring or inner fault detection. In this paper the theoretical approach of the suggested method and simulation results of an equivalent test-bench system are presented.

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