Advanced control algorithms for electric machine drives

MRAS公司 病媒控制 扭矩 直接转矩控制 转子(电动) 控制工程 计算机科学 控制理论(社会学) 工程类 控制(管理) 电压 感应电动机 人工智能 电气工程 热力学 物理
作者
Minh C. Ta,An-Toan Nguyen
出处
期刊:Elsevier eBooks [Elsevier]
卷期号:: 454-471
标识
DOI:10.1016/b978-0-12-821204-2.00119-7
摘要

Modern motor control technology has recognized its new era in the late 1960s by the vector control (field-oriented control) for AC machine drives. Since then, numerous control techniques have been developed to improve the controlled system performance and to expand their applications. This article addresses several advanced control algorithms for electric machine drives. One of the most important waves of research activities resides in sensorless control, in which the “mechanical sensors” can be removed, since information on angular speed and/or position can be estimated from “electrical” data (such as voltage and current) by using various estimation methods. The insight on the sensorless control of induction motor (IM) drives in literature will be made. The model reference adaptive system (MRAS) will be next treated, using the instantaneous reactive power as tunning adaptation signal. The method is shown to be a very comprehensive and effective estimation technique for industry applications. In the class of permanent magnet (PM) synchronous machines (PMSM), the interior permanent magnet (IPM) machine type has gained the popularity in the last three decades thanks to their excellent features (high efficiency, high torque per volume). The maximal torque per ampere (MTPA) control and Flux-weakening (FW) strategies have been developed to exploit the advantage of reluctance torque, which is originated from the saliency characteristics of rotor. These two strategies (MTPA and FW) will be treated in detail in this article and their performance will be illustrated by simulation results using a motor for EVs.

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
刚刚
周周周关注了科研通微信公众号
刚刚
刚刚
刻苦的三德完成签到,获得积分10
1秒前
yi发布了新的文献求助10
1秒前
果汁完成签到,获得积分10
1秒前
xzy发布了新的文献求助10
1秒前
碧蓝老黑完成签到,获得积分10
2秒前
2秒前
zsr发布了新的文献求助10
2秒前
pillowdamon完成签到,获得积分10
3秒前
3秒前
kkk发布了新的文献求助20
3秒前
汉堡包应助Jane2024采纳,获得10
3秒前
3秒前
笨笨的翠发布了新的文献求助10
3秒前
y111完成签到,获得积分20
4秒前
ostinato发布了新的文献求助10
4秒前
4秒前
4秒前
DAdump1ing发布了新的文献求助10
4秒前
Birdy发布了新的文献求助10
4秒前
欧no完成签到,获得积分10
5秒前
认真匪发布了新的文献求助10
5秒前
独行侠杨进步完成签到 ,获得积分10
5秒前
6秒前
6秒前
jam完成签到,获得积分10
6秒前
zyyzyyoo完成签到,获得积分10
8秒前
uuu完成签到,获得积分20
8秒前
9秒前
emma发布了新的文献求助10
9秒前
Anonyme发布了新的文献求助10
9秒前
dadaup完成签到 ,获得积分10
9秒前
9秒前
暴欣完成签到,获得积分20
10秒前
zhu发布了新的文献求助10
11秒前
小太阳在营业举报求助违规成功
11秒前
Stella举报求助违规成功
11秒前
贪玩的秋柔举报求助违规成功
11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
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 2000
Digital Twins of Advanced Materials Processing 2000
Social Cognition: Understanding People and Events 1200
Polymorphism and polytypism in crystals 1000
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6037424
求助须知:如何正确求助?哪些是违规求助? 7760152
关于积分的说明 16217759
捐赠科研通 5183322
什么是DOI,文献DOI怎么找? 2773936
邀请新用户注册赠送积分活动 1757078
关于科研通互助平台的介绍 1641452