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This paper presents an artificial neural network (ANN) based maximum torque per ampere (MTPA) control algorithm for interior permanent magnet synchronous motors (IPMSMs) that accounts for temperature variations. The proposed method utilizes a 3-D lookup table and ANN to estimate the d-q axis flux and adjust current commands for efficient MTPA operation without direct temperature measurements. Experimental validation on an 11 kW IPMSM demonstrates the effectiveness of the algorithm in managing torque output

Author

yingheaau

Language

EN