Advanced electrical machine drives for automotive and wind turbine applications

适用于汽车和风力涡轮机应用的先进电机驱动器

• 批准号: 2509230
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2509230
• 关键词: Advanced; electrical; machine; drives; automotive

The project is looking at development and testing of more intelligent types of electrical machine drives - where the machine control is directly linked to its condition monitoring and the awareness of existing stress. This could allow for machines to be used in a wider envelope to provide e.g. traction in EVs or power in wind turbines, where controlled overloads and lifetime management can be done in a fully informed manner. To enable the above it is required to embed a novel sensor type into the machine to enable in situ monitoring of key stress measurands (e.g. temperature, strain) - the fibre optic FBG sensors can provide this functionality and their usage will be exploited in this project. Fine sensing fibres will be embedded in prototype machines and then linked to control to test the possibility of developing advanced operating capability through linkage of sensed stress and real time control.The research aligns primarily with the electrical motors and drives/electromagnetics portfolio.

该项目着眼于开发和测试更智能类型的电机驱动，其中机器控制直接与其状态监测和现有压力的意识相关联。这可以允许机器在更广泛的范围内使用，例如为电动汽车提供牵引力或为风力涡轮机提供动力，其中可以以完全知情的方式控制过载和寿命管理。为了实现上述功能，需要在机器中嵌入一种新型传感器，以实现关键应力测量（例如温度，应变）的现场监测-光纤FBG传感器可以提供此功能，并且将在本项目中利用它们。精细传感纤维将嵌入原型机，然后连接到控制，以测试通过感应应力和实时控制的联系开发先进操作能力的可能性。该研究主要针对电机和驱动器/电磁组合。