Abstract

This paper presents a comparison between hairpin and random distributed winding in electrical machines for automotive applications. Indeed, the overall performance of an electrical drive system is seriously affected by its winding design. The considered electrical machine has a peak power of 115kW and a maximum operating speed of 12000 rpm. Both cost and manufacturing aspects are here discussed in detail. Two different machine topologies have been investigated and Finite Element Analysis (FEA) results are presented and discussed. Then, the comparison between hairpin and random winding configuration in terms of AC copper losses are presented for the selected geometry. The accurate AC losses estimation can be done by modelling each single conductor. In order to significantly reduce the simulation time, a domain model reduction has been adopted. Based on two different driving cycles, Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Test (HWFET), the AC losses have been evaluated. It is shown that horizontal pin segmentation can contribute to considerable AC loss reduction.

Highlights

  • There is currently wide interest in the research and development of power traction applications driven by electrical machines

  • This paper aims to compare two different distributed winding solutions for the stator of a Permanent Magnet assisted Synchronous Reluctance (PMaSynRel) machine designed for automotive application: the hairpin and the random distributed wires

  • The contribution of the skin and proximity effects are very significant in this kind of configuration, there is no circulating current, the C0( is almost double compared to the random winding

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Summary

Introduction

There is currently wide interest in the research and development of power traction applications driven by electrical machines. Governments and automotive industries are pushing their research programs to realize hybrid and pure electric powertrains for both automotive and aerospace, and in general for all transport applications. Challenging targets of 81g of CO2 emission per km (fuel consumption of around 4.1 and 3.6 L/km for petrol and diesel fuel, respectively [1]) will be compulsory for all new cars in Europe by 2025. Another important challenge in transportation industry is the maximization of the power density, in terms of power to volume (kW/L) or power to mass (kW/kg) ratios [2]. The most common machine topologies for EVs are synchronous permanent magnet, synchronous wound field, induction and synchronous reluctance machines

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