Self-optimizing and model-adaptive control of electrical drive systems with predictive planning of pulse patterns

电动汽车有很多用途，例如用于自动化生产线、发电厂、离心机、起重机和起重机，以及公路和铁路车辆。同时，大多数驱动器都是以受控方式运行的，除了主要的控制目标如速度外，还包括功率损失或磨损最小化等其他方面的影响。在过去的几十年里，人们致力于控制策略、调制和辨识方法等问题的研究。然而，大多数方法都专注于孤立的问题或特定的应用程序。提出了一种基于自优化原理的电气传动多级控制和运行管理的概念，并提出了基于自优化原理的电气传动多级控制和运行管理概念。概念集中在带有两电平逆变器的永磁同步电机上。然而，其模块化结构允许以较低的工作量扩展到其他配置(例如，感应电机或多电平逆变器)。这一概念被细分为三个层次。在最低级别，配置了对电流、扭矩、速度和位置的经典控制。这种控制的参数通过叠加的优化级别不断调整，该优化级别利用电气、热和机械模型来预测驾驶行为，并在需要的情况下干预从属控制级别。顶层包括自优化和自适应功能。后者检查从属层内的模型估计和测量之间的残差，并在运行时，即在调试期间和整个驱动寿命期间匹配模型参数。此外，通过自我优化的方式，根据外部或内部条件的变化动态调整优化目标。经过仿真研究后，所提出的控制概念将在几个试验台上进行验证，用于三种典型应用：第一：牵引驱动(轨道和公路车辆)；第二：高速连续驱动(泵、风扇等)；以及第三：伺服驱动(例如机床)。由于验证场景包括非常不同的需求配置文件，因此应该演示所提议的概念的概括性。在项目成功完成后，计划转移到进一步的驱动器配置。

Electric drives are used in many purposes, e.g. in automated production lines, power plants, centrifuges, hoists and cranes as well as in road and rail vehicles. Meanwhile, most drives are operated in a controlled fashion where, besides the primary control objective as e.g. the speed, further aspects as minimization of power losses or wear play a role. In the past decades, great research efforts have been made dedicated to issues e.g. of control strategies, modulation and identification methods. Most approaches, however, are focusing on isolated problems or specific applications. A generalizable drive or control concept, which independently configures itself to the respective application-specific requirements and adapts continuously, does not exist.This proposal presents a concept of a multi-level control and operational management for electric drives which is based on the principle of self-optimization. The concept focuses on permanent-magnet synchronous motors with 2-level inverters. However, its modular structure allows to be extended to other configurations with low effort (e.g. induction motors or multi-level inverters). The concept is subdivided into three levels. At the lowest level, the classic control for currents, torque, speed and position is allocated. The parameters of this control are continuously adapted by a superimposed optimization level which makes use of electrical, thermal and mechanical models in order to predict the drive behavior and to intervene in the subordinate control level in case of need. The top level includes functions of self-optimization and adaptation. The latter examines the residuals between model estimation and measurements within the subordinate layer and matches at runtime, i.e. both during commissioning and over the entire drive life, the model parameters. Additionally, by means of self-optimization, the optimization goals are dynamically adjusted due to changing external or internal conditions. In that way it will be ensured that the control concept can be applied for a wide range of applications without manual adjustment.After simulative studies, the proposed control concept will be validated on several test benches for three exemplary applications: 1st: traction drive (rail and road vehicles), 2nd: high-speed continuous drives (pumps, fans, etc.), and 3rd: servo drives (e.g. machine tools). As the validation scenarios include very different requirement profiles, the generalizability of the proposed concept should be demonstrated. After successful completion of the project, the transfer to further drive configurations is planned.