Multi-Physics LCA-Based Design Optimization of an Interior Permanent Magnet Motor for EVs

This paper presents a multiphysics, Life Cycle Assessment (LCA)-based design optimization framework for an interior permanent-magnet traction motor tailored to electric-vehicle duty. The workflow couples driving cycle realism, electromagnetic–thermal analysis, and life cycle assessment within a unified, computationally efficient process. Representative operating points are extracted from WMTC and ECE cycles using clustering, after which a multi-level Taguchi refinement searches the design space from coarse to fine. A weighted composite objective balances machine cost and life cycle cumulative emissions under hard constraints on torque capability and hotspot temperature. The optimized design satisfies performance and thermal limits while simultaneously reducing both cost and life cycle burden, as confirmed through phase-wise assessment of raw material, use-phase, and end-of-life contributions. Iterative improvements are accompanied by rising signal-to-noise ratios and reduced parameter-level spread, indicating greater robustness to operating variability. Overall, the study demonstrates that an LCA-driven, multiphysics-constrained optimization can deliver sustainable, high-performance IPM designs that are aligned with realistic vehicle operating conditions and readily adaptable to alternative motor and drive architectures.