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

• Applicant: Professor Dr.-Ing. Jürgen Fleischer
• Subject Area: Production Automation and Assembly Technology
• Term: from 2017 to 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 350459107

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.

• DFG Programme: Research Grants