Experimental Statistical Method Predicting AC Losses on Random Windings and PWM Effect Evaluation

Eraldo Preci,David Gerada,Giorgio Valente,Giampaolo Buticchi,Michele Degano,Christopher Gerada,Xin Yuan,Alessandro Galassini

doi:10.1109/tec.2020.3040265

Abstract

Nowadays, one of the challenges in transport electrification is the reduction of the components' size and weight in order to improve the power density. This is often achieved by designing electrical machines with higher rotational speeds and excitation frequencies. In addition, the converter needs to control the machine over a wide speed range given by the mission profile. Therefore, copper losses can significantly increase due to the combination of high frequency excitation and the harmonics introduced by the converter. The winding arrangement design plays a key role in the minimization of the copper losses, thus towards a higher efficiency and/or an improved power density. Different winding topologies can be adopted for high speed electrical machines and amongst them random windings are still one of the most widespread types. This paper presents an in depth study on AC losses in random windings for high frequency motor applications. An analytical method is compared against 2-D Finite Element (FE) simulation results. These are then compared to experimental measurements taken on a custom motorette. Importantly, in order to take into account the random positions of each strand within the machine slots, an Experimental Statistic Method (ESM) is proposed. The ESM allows to define the probability distribution which is useful to evaluate the winding copper losses at the design stage. The contribution of the Pulse Width Modulation (PWM) effect is also considered and experimentally evaluated.

Highlights

Nowadays, transport electrification is one of the most viable solutions to reduce CO2 emissions and meet fuel economy requirements
In production lines where the machine design is the same for all the batches, each winding manufactured presents some differences in the strands distribution, different winding losses arise
A more robust algorithm able to represent different slot layouts in FEM is planned to do with the aim to have more data from simulations and to verify if the probability distributions from experimental tests and simulations are close each other

Summary

Introduction

Transport electrification is one of the most viable solutions to reduce CO2 emissions and meet fuel economy requirements. Adopting drivetrains with high performance electrical machines is the way to meet the aforementioned requirements and to develop concepts and products capable to meet the modern markets’ standards. 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]. In very high frequency applications, Litz wires are normally used. They present some manufacturing disadvantages, such as complex shaping and impregnation, low achievable fill factor, and high manufacturing costs [7]. Random winding allow semi-automatic production and the purchasing costs are

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