Extended FOC for High-Performance SPMSMs in EVs Incorporating Flux Linkage Vector Decomposition and Nonlinear Dependencies: Experimental Evaluation and Performance Enhancement

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Authors: Rubén Rodríguez Vieitez, Paulo Gabriel Rial Aspera, Jorge Rivas Vázquez, Daniel Villanueva, Nicola Bassan, Jacobo Porteiro Fresco
Cited by: 1
References: 34

Abstract

Surface-mounted permanent magnet synchronous motors (SPMSMs) are widely used in high-performance electric vehicles due to their power density; however, conventional field-oriented control (FOC) relies on simplified models in which electromagnetic torque is described as a function of the quadrature current component, together with constant parameters and idealized trajectories in the id−iq plane, limiting adaptability and reducing efficiency and operating range under real conditions. This work introduces a flux linkage vector decomposition approach for SPMSMs, in which the permanent-magnet flux is decomposed into d- and q-axis components under core saturation and integrated into an extended field-oriented control framework. An extended FOC strategy is proposed that incorporates flux linkage vector decomposition, nonlinear magnetic saturation, cross-coupling effects, and nonlinear dependencies of electrical parameters, along with resolver angle correction and dynamic modulation index management. These enhancements modify torque and voltage trajectories by shifting the voltage-limit center and improving the definition of the MTPA, FW, and MTPV regions to better match real motor behavior, enabling performance improvements. Experimental validation on an automotive powertrain using a vehicle control unit (VCU) and precalculated lookup tables (LUTs) demonstrates improvements of up to 13.5% in low-speed torque, 13.7% in high-speed power, and efficiency gains of 4–8% across operating conditions.

Fields of Study & Subjects

Sensorless Control of Electric Motors Multilevel Inverters and Converters Electric Motor Design and Analysis

Publication details

Journal / source
Energies
Publisher
MDPI AG
Volume
19
Issue
7
Pages
1690–1690
Publication date
30 March 2026
Language
EN