电机的比功率和效率推算及飞机应用的电路保护探索

Chrysoula L. Pastra, Christopher Hall, Gokcin Cinar, Jonathan C. Gladin, D. Mavris
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引用次数: 3

摘要

本文的目的是产生具体的功率和效率预测到2050年的电动机器用于飞机的应用。进行了一般性的文献综述,以确定常用的电机类型,以及由于其高比功率和效率,哪些类型在未来的飞机应用中具有最大的潜力。建立了包含历史数据的数据库,包括重量[kg]、额定功率[kW]、比功率[kW/kg]、RPM、效率、年份、电机冷却类型、应用类型和电机类型等参数,以便进行趋势识别和准确预测。一旦收集到数据,就会根据历史数据生成多个拟合曲线,并根据保守、名义和激进的预测情景进行外推,从而得出具体功率的预测。由于数据的分散性质,效率预测采用了不同的过程。通过文献回顾确定了效率的最新水平(SoA)值,并用于创建2030年、2040年和2050年时间框架的保守、名义和激进预测。2050年EMs的效率预测值和比功率预测值分别为0.989和50kW/kg。本文还将研究电路保护,因为它是电动动力系统的附加组件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Specific Power and Efficiency Projections of Electric Machines and Circuit Protection Exploration for Aircraft Applications
The purpose of this paper is to generate specific power and efficiency projections through the year 2050 for electric machines for aircraft applications. A general literature review was performed to identify the types of electric machines that are commonly used and which types have the biggest potential for future aircraft applications due to their high specific power and efficiency. A database with historical data was built to include parameters such as weight [kg], rated power [kW], specific power [kW/kg], RPM, efficiency, year, motor cooling type, application type and motor type to allow for trend identification and accurate projections. Once the data was gathered, multiple curve fits on the historical data were generated and extrapolated to produce the projections for specific power according to conservative, nominal and aggressive projection scenarios. A different process was followed for the efficiency projections due to the scattered nature of the data. A state of the art (SoA) value for efficiency was identified through literature review and was used to create the conservative, nominal and aggressive projections for the time frames of 2030, 2040, and 2050. The efficiency and the specific power projections of EMs for 2050 are 0.989 and 50kW/kg respectively. This paper will also be examining circuit protection as it is an additional component of electric powertrains.
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