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Optimized FOC control strategy for dual stators permanent magnet machine
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Optimized FOC control strategy for dual stators permanent magnet machine
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Optimized FOC control strategy for dual stators permanent magnet machine
Optimized FOC control strategy for dual stators permanent magnet machine
Journal Article

Optimized FOC control strategy for dual stators permanent magnet machine

2025
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Overview
The rapid adoption of electric vehicles (EVs) has driven the continuous evolution of traction systems, necessitating efficiency, reliability, and performance improvements. Conventional motor designs, such as single-stator permanent magnet synchronous machines (PMSMs) and induction motors, often suffer from limited torque density, inefficient thermal dissipation, high torque ripple, and reduced fault tolerance. These challenges hinder optimal EV performance, particularly under varying load conditions. Dual-stator machines (DSMs) have emerged as a promising alternative. They offer higher torque density, improved power distribution, enhanced thermal management, and increased redundancy, making them more resilient to faults. This paper presents a comprehensive mathematical modelling and operational analysis of DSMs, emphasizing their advantages over traditional motor architectures. Furthermore, the Field-Oriented Control (FOC) strategy, a widely adopted method for high-performance motor control, is explored in depth for its suitability in DSM applications. The challenge here is to designate one stator as the primary induction system, ensuring its power is effectively controlled. When the first stator reaches its maximum power capacity, the second stator compensates accordingly. The control design was specifically developed to achieve this objective. MATLAB-based simulations are conducted to assess efficiency, torque response, and fault-tolerant capability, demonstrating the superior performance of DSMs in EV traction systems. The findings highlight the potential of DSMs to redefine next-generation EV propulsion by enhancing power efficiency, reliability, and operational stability.