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This study presents an approach to calculating the temperature increase in the internal components of permanent magnet synchronous machines by applying lumped-parameter thermal networks and analytical methods. Accordingly, the thermal equivalent circuit method is employed to obtain the temperatures of the machine’s internal components. Furthermore, this analytical method predicts the temperature distribution in the slot area. The 24/6 prototype was used to evaluate the proposed model by comparing the calculated and finite element method simulation.

Distance magnetic nanoparticle detections were investigated by using a magnetoelectric based magnetic sensor with a long type bilayer Metglas/PZT laminate composite. In homogeneous magnetic fields, the sensor exhibits a sensitivity of 307.4 mV/Oe, which is possible for a detection limit of 2.7 × 10-7 emu. This sensor can detect an amount of 0.31 μg of the superparamagnetic Fe3O4-chitosan fluid at 2 mm height above the sensor surface. To detect a spot with magnetic nanoparticles at a distance of about 7.6 mm, it should contain at least 50 μg of iron oxide. This approach can develop the local detection of magnetic nanoparticles at a depth of centimeters in the body during clinical interventions.