Review of high speed electrical machines in gas turbine electrical power generation

航空航天 可靠性(半导体) 汽车工程 机身 扭矩 电力 电力系统 涡轮机 电动机 转矩密度 发电机 计算机科学 汽车工业 功率(物理) 工程类 可靠性工程 机械工程 电气工程 电磁线圈 航空航天工程 物理 热力学 量子力学
作者
Xiaohe Ma,Rong Su,K.J. Tseng,Shuai Wang,Xiaolong Zhang,Viswanathan Vaiyapuri,Gajanayake Chandana,Gupta Amit,Sivakumar Nadarajan
标识
DOI:10.1109/tencon.2015.7372765
摘要

The concept of a More Electric Aircraft (MEA) demands a highly optimized airframe power system which is achieved by replacing pneumatic and hydraulic systems with energy efficient electrical systems. With increasing power offtake requirements, the More Electric Engine (MEE) could play a key role in future MEA, where more electrical power will be drawn from gas turbine shaft using the conventional gear driven electrical machine, which is known to present inefficiencies and reliability issues. Embedding an electrical machine directly at the engine shaft would help eliminate the need for the accessory gearbox along with potentially improving the reliability and efficiency of the whole system. However embedding the electrical machine presents significant design challenges to meet the key requirements. Some of these include: the necessity of the electrical machine to operate in high temperatures and high vibration environments, the mechanical constraints such as space limitations, and the need to operate at high speeds. Other requirements include the need for high power density, high torque density, high efficiency and maintenance-free operation of the electrical machines. At present, different electrical machine topologies have been developed for a number of challenging industrial and automotive applications where some of the requirements and criteria have been partially met. In this paper the detailed investigation and the trade study carried out of the various electrical machine topologies to understand their advantages, constraints and drawbacks is presented to provide a preliminary evaluation of their suitability for meeting the stringent requirements of embedded machines in aerospace applications.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
cslc发布了新的文献求助30
刚刚
1秒前
1秒前
范东乐发布了新的文献求助10
1秒前
背后的诗双应助xlogeman采纳,获得10
2秒前
汉堡包应助qiuqiu采纳,获得10
3秒前
5秒前
tangzhidi发布了新的文献求助20
6秒前
6秒前
6秒前
hahanhan发布了新的文献求助10
6秒前
李键刚完成签到 ,获得积分10
7秒前
在水一方应助羽化采纳,获得10
7秒前
你好完成签到,获得积分10
8秒前
scott910806完成签到,获得积分10
8秒前
秋秋完成签到,获得积分20
9秒前
旺旺仙貝完成签到 ,获得积分10
10秒前
FashionBoy应助zzy采纳,获得10
10秒前
黄先生发布了新的文献求助10
11秒前
zzzqqq完成签到,获得积分10
11秒前
哈哈哈完成签到,获得积分10
11秒前
Wayne应助xxs采纳,获得10
11秒前
晚风做酒发布了新的文献求助10
12秒前
12秒前
碧蓝青梦发布了新的文献求助10
12秒前
imcwj发布了新的文献求助10
15秒前
16秒前
Sober完成签到,获得积分10
16秒前
害羞向日葵完成签到 ,获得积分10
16秒前
17秒前
17秒前
ssrs完成签到 ,获得积分10
18秒前
老实幻姬完成签到,获得积分10
18秒前
华仔应助范东乐采纳,获得10
20秒前
20秒前
DavidSun完成签到,获得积分10
20秒前
chen完成签到,获得积分10
20秒前
Xiong发布了新的文献求助10
20秒前
华仔应助Sober采纳,获得10
20秒前
22秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Research for Social Workers 1000
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
Kinesiophobia : a new view of chronic pain behavior 500
《The Emergency Nursing High-Yield Guide》 (或简称为 Emergency Nursing High-Yield Essentials) 500
The Dance of Butch/Femme: The Complementarity and Autonomy of Lesbian Gender Identity 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5889218
求助须知:如何正确求助?哪些是违规求助? 6653080
关于积分的说明 15712961
捐赠科研通 5010521
什么是DOI,文献DOI怎么找? 2698871
邀请新用户注册赠送积分活动 1643744
关于科研通互助平台的介绍 1596403