Original research

ADVANCED INTELLIGENT ARCHITECTURES FOR HIGH-PERFORMANCE ELECTRICAL DRIVE SYSTEMS: INTEGRATED DESIGN, DIGITAL OPTIMIZATION, AND SUSTAINABLE ENGINEERING PERSPECTIVE

Pages 223-248

10.61552/JEMIT.2026.03.001

Ahmed A. Abd Eltwab

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Abstract Electrical drive technologies are undergoing rapid transformation driven by increasing demands for efficiency, power density, digital connectivity, and sustainability across industrial, transportation, and renewable energy sectors. Modern electrical machine systems are no longer defined solely by electromagnetic design, but by the integration of intelligent optimization frameworks, digital modeling environments, and system-level performance management strategies. This review provides a comprehensive analysis of advanced electrical drive architectures with emphasis on integrated system design, computational optimization, smart monitoring, and sustainable engineering practices. Emerging machine configurations are examined in relation to efficiency enhancement, thermal performance, and operational reliability. The role of digital twins, data-driven performance prediction, and intelligent diagnostics is critically evaluated as enabling technologies for next-generation high-performance machines. Furthermore, the paper discusses multi-domain optimization strategies combining electromagnetic, thermal, and mechanical considerations, alongside lifecycle-oriented sustainability approaches aimed at reducing energy losses and environmental impact. Challenges related to system integration, operational robustness, and scalable deployment in electrified infrastructures are also addressed. By synthesizing recent advances in intelligent design methodologies and system-level innovation, this review provides a structured framework for the development of high-efficiency, digitally enhanced, and environmentally responsible electrical drive systems.

Keywords: Intelligent electrical drive systems, Digital optimization, Smart monitoring, Multi-domain system integration, High-efficiency machine architectures, Sustainable engineering, Data-driven diagnostics, Advanced electromagnetic systems.

Recieved: 17.10.2025. Revised: 21.01.2026. Accepted: 16.02.2026.