Muhammad Hamza

Designing high-performance electric machines demands meeting targets for power density and speed while satisfying multidisciplinary constraints. Conventional forward design workflows are often iterative, expert-dependent, and prone to late-stage rework when multidisciplinary constraints interact.

We use an inverse design methodology that begins with system level targets and searches the design space with a constrained optimization algorithm. A systematic physics informed evaluation loop screens candidates against key constraints, like structural stresses, rotor dynamic margins, thermal limits, and support/bearing capacity, so that only feasible concepts progress.

The approach reduces design time by removing iteration and preventing downstream rework. It improves efficiency and robustness of design by converging on solutions that meet targets with clear margins and sensitivity awareness. It enhances multidisciplinary integration by treating mechanical, electromagnetic, thermal and manufacturing constraints concurrently, enabling transparent trade-offs decisions.

Compared with trial-and-error or single-domain optimization strategies, this NABC-driven inverse design framework delivers faster go/no-go decisions and produces designs that are feasible by construction. It offers a practical path to accelerating innovation in high-speed electric machines and other complex engineered systems design.