An innovative approach for the evaluation of iron losses in magnetic laminations, applied to the optimization of highly saturated electric motors
نویسندگان
چکیده
ArcelorMittal is a key supplier for electrical steels in challenging applications such as high power density automotive traction machines and high speed induction machines for industry and power generation systems. Throughout the years we have focused on understanding the specific needs of each electrical machine type and aimed at developing electrical steels to optimally meet these machine demands. This paper presents a specific example of such a development. As a partner of ArcelorMittal, Valeo is a specialist in the design and manufacturing of electrical machines for automotive applications, and especially innovative e-machines aiming at "green" solutions for traction, like hybrid vehicles as a part of the current tendency in electrifying the power train. After improving its alternators towards the Stop and Start function, as a first step for vehicles hybridisation, Valeo aims to bring a substantial reduction in fuel consumption at a reasonable cost, on the basis of improved starter motors. This paper presents the optimisation potential possible for critical operating conditions of such starter motors, based on the use of a more advanced electrical steel grade. That idea triggered the collaboration between ArcelorMittal and Valeo. In order to properly structure the machine and material optimisation, the work was based on detailed magnetic modelling, using not only commercial modelling software, but also using ArcelorMittal’s improved iron loss modelling approach. The results illustrate the improved prediction power of the ArcelorMittal material model. In terms of electrical steel choice, the benefit on machine performance will be shown. Obviously in the end, a commercial evaluation needs to be made in terms of costs versus benefit, but the current study shows that even for a conventional machine, such as a starter motor, a structured optimisation approach can lead to an interesting performance improvement potential.
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