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With the development of permanent magnet synchronous motors (PMSMs), the accurate loss calculation is of vital significance for the performance evaluation of the PMSM system. As the loss of the PMSM system is determined by the control strategy, inverter, and the motor itself, which interact with each other mutually and complicatedly, in conventional loss calculation methods they are not considered synthetically. To calculate the PMSM system loss accurately, this paper proposes a strategy-circuit-field co-simulation methodology, which can take into account the mutual influence of control strategy, inverter, and motor. The proposed co-simulation platform synchronizes the control theory-based strategy simulation, Kirchhoff’s law-based circuit simulation, and the field-based motor simulation, which reveals the real physical process of PMSM systems. To further improve the loss calculation accuracy, a hysteresis-based iron loss calculation method is introduced and utilized. The co-simulation results show that the proposed method can reflect the behavior of the PMSM system more physically, and mutual influence between the three aspects can be presented. Finally, the corresponding experiments are conducted, and the results are compared with the simulation results, proving the proposed methodology’s feasibility and effectiveness.

Based on the mechanical model of the point absorption Wave Energy Converter (WEC), a real-time complex conjugate (CC) maximum power point tracking (MPPT) control strategy consider power peak-to-average ratio (PAR) limiting under irregular waves is proposed. In the proposed MPPT strategy, the system can not only track the maximum power, but also limit the PAR of the output power to improve the controlled generator’s utilization rate. Two parameters, $R_{epot}$ and $X_{pto}$ , that determine the command current of the PMSG and the PAR, are introduced in the mathematical model of the system to control the system. And they are identified by the Grey Wolf Optimization (GWO) algorithm. During each half cycle of the sea wave, the parameters $R_{pto}$ and $X_{pto}$ will be real time updated to satisfy the control strategy. In addition, the system parameters $A$ , $B_{\mathrm {rad}}$ and $F(\omega)$ related to wave frequency are also calculated by the advanced quantitative wave analysis (AQWA) software. Finally, the proposed strategy is verified by the comparison on the simulation and the experimental results.