Automotive applications focus to develop drive-train technologies with higher energy efficiency and lower environmental impact. Electric and hybrid vehicles are gaining popularity since they fulfill these requirements . The aim of optimal motor design is to achieve high torque and power densities, wider speed range and high efficiency within the area defining the most frequent operating points. This work presents a methodology to optimize electric motors for traction applications considering a multi-physics approach. The magnetic behavior is evaluated using a complex reluctance networks capable to compute the cross-coupling. The results of the magnetic model are the inductances, iron losses, and magnet flux linkage. The thermal behavior is evaluated using a thermal network and it is coupled with the magnetic model. The electric model is feed with the solution of the thermal and magnetic model. The electric model aims to calculate the whole operating area of the motor to allow optimizing the machine considering the most frequent operating zone. Therefore, a fast tool to evaluate different variables within the torque-speed map is convenient for this purpose. In this context, starting from a preliminary motor design, and taking into account motor cross-coupling effects and power losses, this thesis presents a new methodology for optimizing and evaluating the behavior of permanent magnet machines, such as synchronous reluctance machines, and permanent magnet assisted synchronous reluctance machines, in all operational points. Apart from the torque and efficiency, many other electrical variables can be obtained, such as the current space vector angle, power factor or electrical power among others. The proposed methodology also allows optimizing the design of the machine under a preestablished control law; thus obtaining the current set point trajectory in the dq frame and allowing a fast and accurate evaluation of motor performance.The results obtained by means of the proposed simulation tool are compared against finite element analysis simulations and experimental data, thus validating the usefulness and accuracy of the proposed methodology.
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