Model-based assembly optimization for the automation of electric drive production with minimum unbalance

基于模型的装配优化，实现电力驱动生产自动化，实现最小不平衡

基本信息

批准号：
350459107
负责人：
Professor Dr.-Ing. Jürgen Fleischer
金额：
--
依托单位：
Institut für Produktionstechnik (WBK)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2017
资助国家：
德国
起止时间：
2016-12-31 至 2019-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/350459107?language=en
关键词：
Model based assembly optimization automation

项目摘要

The proposed project shall elaborate on the question whether the rotor of an electric motor can be described by a model and easily measurable parameters in a way that intelligent assembly strategies can significantly reduce the initial unbalance of the rotor through optimized assembly. This issue is gaining in relevance due to the wide range of application of rotating electric machines whose range of services goes from micro-motors with just a few watts of power to traction drives and finally big motors with a power of several megawatts [1]. For nearly all applications, the rotors of electric motors must be balanced in a separate and non value adding process [2]. The balancing procedure aligns the inertia axis with the rotation axis, thus, reducing the undesired vibrations.Previous research has in particular dealt with the development of new balancing methods and the improvement of existing ones. However, very little research has been done to predict the imbalance and to avoid unbalanced masses by an optimized assembly.So far, no investigations have been conducted on to what extend the imbalance of a rigid rotor consisting of several individual components can be predicted by knowing the variables that are easy to measure (e.g. the weight of attached magnets). The envisaged work shall result in the ability to describe the rotor of a permanent magnet synchronous motor (PMSM) with the production impact of individual components in a model, allowing the calculation of the resulting imbalance. On this basis, a model-based online optimization algorithm can be developed that will significantly reduce the imbalance during rotor assembly.If this new approach can be validated, new findings will be obtained on component quality (manufacturing variances and assembly variations) and its contribution to the imbalance. With its application in industry, this new knowledge could increase the production quality of electric motors and reduce the costs. If applied in the automotive industry, the savings in cost, time and effort as well as the quality improvements would have a positive impact on the electrification of the powertrain.

该项目将详细阐述电动机的转子是否可以通过模型和易于测量的参数来描述的问题，从而智能装配策略可以通过优化装配来显着减少转子的初始不平衡。由于旋转电机的广泛应用，这个问题变得越来越重要，其服务范围从只有几瓦功率的微型电机到牵引驱动器，最后到功率为几兆瓦的大型电机[1]。对于几乎所有应用，电动机的转子必须在单独的非增值过程中进行平衡 [2]。平衡过程将惯性轴与旋转轴对齐，从而减少不需要的振动。以前的研究特别涉及新平衡方法的开发和现有平衡方法的改进。然而，很少有研究来预测不平衡并通过优化装配来避免不平衡质量。到目前为止，还没有研究在多大程度上可以通过了解由多个单独部件组成的刚性转子的不平衡来预测易于测量的变量（例如所附磁铁的重量）。设想的工作将能够描述永磁同步电机（PMSM）的转子以及模型中各个组件对生产的影响，从而允许计算由此产生的不平衡。在此基础上，可以开发基于模型的在线优化算法，该算法将显着减少转子装配过程中的不平衡。如果这种新方法能够得到验证，将获得关于部件质量（制造差异和装配差异）及其贡献的新发现到不平衡。通过在工业中的应用，这种新知识可以提高电动机的生产质量并降低成本。如果应用于汽车行业，节省成本、时间和精力以及提高质量将对动力总成的电气化产生积极影响。