Numerical Multi-objective Optimization of an Innovative Totally Enclosed Fan Cooled Induction Motor

Matteo De Martin (Nidec-ASI SPA R&D)

CHALLENGE - Maximize the power of a TEFC (Totally Enclosed Fan Cooled) induction machine considering the API & SHELL performance and technical constraints and minimize the specific power cost in the oil and gas market segment.












SOLUTION - To overcome the limitations of the TEFC motor structure the researchers developed a performance forecast tool, IDaphne, implementing a new hybrid analytical/2D finite element analysis approach, and integrated it with modeFRONTIER to exploit its multi-objective optimization capabilities.

BENEFITS - modeFRONTIER genetic algorithm increased the global heat exchange surface by 47% and the inner and outer cooling flows by 40%, achieving a cost reduction of 31.5%. This improvement enabled the engineers to replace the recirculation pockets with external cooling pipes maintaining the same dissipating surface, but doubling the average convection coefficient.