Abstract
In this paper, an improved online particle swarm optimization (PSO) is proposed to optimize the traditional search controller for improving the operating efficiency of the permanent magnet synchronous motor (PMSM). This algorithm combines the advantages of the attraction and repulsion PSO and the distributed PSO that can help the search controller to find the optimal d - axis air gap current quickly and accurately under non-stationary operating conditions, thereby minimizing the air gap flux and then improving the motor efficiency. To verify the effectiveness and stability of this proposed algorithm, the operating efficiency of PMSM as using this proposed algorithm is compared with that of traditional search controller under non-stationary operating conditions. The results show that the proposed algorithm can improve the operating efficiency of PMSM by 6.03% on average under non-stationary operation conditions. This indicates that the search controller based on the improved PSO has a better adaptation to the variation of external operating conditions, and can improve the operation efficiency of PMSM under non-stationary condition.
Highlights
The consumption of fossil energy, environmental pollution, and greenhouse gas emissions caused by the burning of fossil energy are becoming increasingly serious [1]
SIMULATION RESULTS BASED ON GSM-search controller (SC) To verify the effectiveness of proposed control strategy for permanent magnet synchronous motor (PMSM), Simulink was used to construct the PMSM efficiency optimization control circuit based on vector control in this paper
The reference speeds are 30rad/min, 60rad/min, and 100rad/min respectively. Under these two non-stationary conditions, the optimal d-axis current obtained by the loss controller offline search can satisfy the high efficiency operation of the PMSM, which proves the robustness of the loss controller based on the GSM-SC
Summary
The consumption of fossil energy, environmental pollution, and greenhouse gas emissions caused by the burning of fossil energy are becoming increasingly serious [1]. In [14], an infinite speed drives MTPA control was proposed to ensure that the automatic transition of different magnetic field regions can be realized before the magnetic flux is weakened This method can effectively reduce the stator copper loss, improving the PMSM efficiency. To solve these two problems, an improved PSO (AR-DPSO) that combines the advantage of the attraction and repulsion PSO (ARPSO) and the distributed PSO (DPSO) is proposed to improve the searching ability of particle swarms to find the optimal value accurately and quickly under nonstationary operation conditions This improved PSO can help particles to detect the change of motor speed, and make a self-adjustment for the change of speed under non-stationary conditions, thereby finding the optimal d-axis air gap current accurately and quickly, and improving the operating efficiency of PMSM. From (4), (9) and (16), the iron loss equivalent resistance of the PMSM can be deduced as: w2[Ld2i2sq + (Ld isd + ψf )2] Ke(1 + s2)a2ψf2 + kh(1 + s)aψf
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