Holistic modelling, control configuration, and design systematics for locally concentrated Multi-Motor Drive Systems - Follow-up application

2017年批准的项目主题是工业可重构多电机驱动系统，即，其中通过齿轮箱互连的几个感应电动机共享所需功率的驱动系统。该项目由帕德博恩大学的两个部门进行，以分析和建模的电工和机械工程方面。在电力电子与电气传动系（莱亚）进行的电工任务研究工作中，出现了新的问题，这些问题将在一年的后续项目中处理。在以前的项目中，莱亚开发了第一个模型的逆变器，与控制感应电动机的相电压可以估计高精度。基于此电压估计和感应电动机的众多非线性电磁效应的建模，推导出一种用于精确的转矩和损耗估计的结构。其中包含的模型参数使用测试台上记录的测量数据离线识别。该方法与热模型相结合，首次表明同时进行电热建模和离线识别为精确的扭矩控制和有效的操作策略提供了很大的潜力。上一个项目的这些主要结果发表在几个会议和期刊论文上。到目前为止，电学和热学子模型只是轻微耦合。在后续项目中，这两个领域现在被集成到其他重要方面，例如对电机饱和行为的热影响和对电导体中的集肤效应的热影响，从而可以对感应电机进行高精度的扭矩和温度估计，从而充分利用该方法的潜力。从该多域模型中，在下一步骤中导出自适应操作策略，以便能够以效率最佳的方式在整个操作范围内操作给定的电机，并且仍然对必要的控制硬件具有低要求。在文献中，通常只有个别的非线性电机被认为是在转矩控制或在操作策略，导致显着的不准确性或可避免的损失。后续项目的其他要点涉及离线识别优化测量数据采集的结构化程序，以及对识别过程中单个测量变量（例如转子温度）可以免除的程度进行详细评估。

The subject of the project approved in 2017 were industrial reconfigurable multi-motor drive systems, i.e., drive systems in which several induction motors interconnected via a gearbox share the required power. The project was conducted by two departments of the Paderborn University in order to analyze and model both the electrotechnical and the mechanical engineering aspects. During the research work on the electrotechnical tasks, performed by the department of Power Electronics and Electrical Drives (LEA), new questions arose which are to be treated within a one-year follow-up project. In the previous project, LEA developed at first models of the inverter with which the phase voltages of a controlled induction motor can be estimated with high accuracy. Based on this voltage estimation and the modeling of numerous nonlinear electromagnetic effects of an induction motor, a structure for accurate torque and loss estimation was derived. The model parameters contained therein are identified offline using measurement data recorded on the test bench. This method was combined with a thermal model and it was shown for the first time that simultaneous electrical-thermal modeling and offline identification offers high potential for both accurate torque control and efficient operating strategy. These main results of the previous project were published in several conference and journal papers. So far, the electrical and thermal submodels were only slightly coupled. In the follow-up project, both domains are now integrated with respect to further important aspects such as the thermal influence on the saturation behavior of the motor and on the skin effect in the electrical conductors so that a highly accurate torque and temperature estimation of an induction motor is possible, thus exploiting the full potential of the approach. From this multi-domain model, an adaptive operating strategy is derived in the next step, in order to be able to operate a given motor in the complete operating range in an efficiency-optimal way and still with low demands on the necessary control hardware. In the literature, usually only individual nonlinearities of the motor are considered in the torque control or in the operating strategy, resulting in significant inaccuracies or avoidable losses. Further points of the follow-up project concern the structured procedure for optimized measurement data acquisition for offline identification and a detailed evaluation of the extent to which individual measurement variables (e.g. rotor temperature) can be dispensed with during identification.