## 2 Optimized Geometric and Operational Design of an Induction Motor
### Finite Element Method (FEM) Simulation  
After establishing the preliminary design, FEM analysis was used to simulate the motor's electromagnetic performance. This involved solving [PERSON]'s equations to understand the flux distribution, torque, losses, and thermal effects. The analysis refined the rotor and stator slot geometry to minimize losses, particularly core and copper losses, ensuring the motor operated efficiently under nominal conditions. This study's methodology considered the unique operational characteristics of ship propulsion systems, including load variations, extended operational hours, and harsh environmental conditions such as humidity and temperature fluctuations. The design of the motors was tailored to meet these specific requirements, with a focus on optimizing efficiency and reliability under dynamic operating conditions. In particular, the finite element analysis (FEA) and sensitivity analysis conducted in this study considered marine-specific constraints to ensure that a realistic and practical design approach was devised. The simulation utilized a mesh convergence study to ensure result accuracy, with three levels of mesh density progressively being refined until variations in key performance indicators, such as torque and flux density, were below 2%. Boundary conditions were meticulously defined, applying fixed constraints to the stator and appropriate current excitations to the windings, reflecting realistic operational scenarios. A constant temperature of 75 \({}^{\circ}\)C was imposed on the stator housing, reflecting cooling performance for marine-grade propulsion drives. The outer stator was assumed to be mechanically fixed with zero radial and axial displacement. Rotor movement was modeled with rotational periodicity and ideal airgap preservation. Rated supply conditions were used, and appropriate winding configurations were applied based on manufacturer data. To validate the FEA models, our results were compared with established benchmarks from the recent literature, demonstrating a high degree of correlation and thus confirming the model's reliability [40; 41; 42]. * Optimization  
After the initial design and the FEM simulation, the geometry was optimized by performing a sensitivity analysis on the key dimensions (e.g., stator slot width, rotor bar height). The objective was to minimize losses, including both core and copper losses, and ensure smooth torque with minimal ripple for smooth sailing. Using optimization techniques, the motor's final geometry was selected, which minimized the objective function of losses while maintaining high performance. As is known, an advanced induction motor is powered by a converter and not directly from the network. This fact offers the possibility, during the optimization of the initially designed motor, to vary the current density supplied to the stator windings, within the limits of the thermal resistance of the windings as well as the slip, in order to find an  
Figure 2: Efficiency vs. Slip curve. optimal operating point of the motor that will deliver the rated torque and at the same time increase its efficiency. To achieve maximum motor efficiency, it is sufficient to achieve a balance between electric and magnetic charging. The methodology for the 10 MW induction motor design combined preliminary analytical modeling with Finite Element Method (FEM) simulations for optimization. The initial design featured a 14-pole (7 pole pairs) squirrel-cage induction motor with 42 stator slots and 54 rotor bars. Geometrical dimensions included a stator outer diameter of 3100 mm, inner diameter of 2300 mm, and axial length of 720 mm. The air gap length was set to 5.8 mm to balance efficiency and thermal management. Distributed double-layer winding was used to minimize harmonic distortions and torque ripple. The nominal performance metrics before optimization included an efficiency of 92.74% and significant copper losses (241.54 kW in the stator and 372.60 kW in the rotor). The total losses amounted to 782.14 kW.