Autonomous parameter estimation for electric machines

随着汽车行业向无排放移动的转变，电动机器在汽车行业变得越来越普遍，因为它们成为公路车辆的主要推进系统。由于超过15%的新车销售是电动的，因此能够准确地描述电动机器的特征对于最大限度地提高其性能和效率至关重要。模型复制瞬态行为能力的关键预测因素是用于表征电机的参数的准确性。仅仅依靠制造商提供的信息和规格来创建一个健壮的模型是不切实际的，因为它们通常只包括机器操作所需的信息。这项工作的总体目标是开发一种程序，使电机模型的参数化自动化，以便以后在车辆开发过程中使用。电机模型有许多潜在的用例，以及许多感兴趣的电机架构。在用例和电机架构的每个组合中，适当的电机模型结构预计是不同的。通常，当需要更详细地了解运动性能时，空间和时间分辨率的水平将会增加。一旦定义了模型结构，就可以定义参数化和验证该模型所需的数据。然后，可以定义生成该数据所需的实验以及所需的仪器。该项目以电机的模型开发为重点，旨在建立模型和数据之间的端到端工作流，以提高模型的准确性和对新测试单元的适应性。这项工作将探索通用电机模型和参数化过程的潜力，该模型和参数化过程与所有可能感兴趣的电机拓扑结构兼容：磁通开关、感应和同步电机结构。它将侧重于实现自主参数表征过程，以及简化电机参数化所需数据收集背后的实验程序。电机结构变化很大，需要定制电机模型来模拟其行为。在项目前6个月的过程中，将创建一个同步电机的模型，目的是达到模型给定应用的可接受的精度水平。目前该模型是在Simulink中建立的理想矢量控制模型，与实际数据的误差在3% ~ 5%之间。下一步是增加损耗，可分为三大类：发生在电路、磁路以及机械和通风中的损耗。在400rpm以下，模型精度随转速降低，与趋势线相切。造成这种现象的原因可能是用于参数化模型的数据表不准确，或者测量仪器的限制阻碍了其准确捕获低速数据的能力。然后，电机将通过预定的AVL参数化周期进行测试，以确定机器的真实参数与制造商提供的参数之间是否存在差异。如果在低速下缺乏准确性是由于仪器的限制，则可以在不同的机器上在IAAPS设施进行相同的测试。我最初在暑期项目中研究矢量控制，以及同步机器的操作原理以及它们是如何连接的。有了内燃机和电池的背景，学习我正在使用的电机类型的基本特性是必要的。以外行的电机操作知识开始这个项目是一个挑战，可能导致项目延迟，然而，与AVL利益相关者交谈，以确定他们对项目的目标，将使我能够更有效地计划我的工作流程

Electric machines are becoming more prevalent in the automotive industry as they become the main propulsion system in road vehicles with the industry's shift towards emissions free mobility. With over 15% of new car sales being electric, being able to accurately characterise electric machines virtually is imperative for maximising their performance and efficiency. A key predictor of a model's ability to replicate transient behaviour is the accuracy of the parameters used to characterise the motor. Relying solely on the information and specifications provided by the manufacturer to create a robust model is impractical as they often only include information required for the machine's operation. The overarching aim of this work is to develop a procedure to automate the parameterisation of electric motor models for later use in the vehicle development process.There are mant potential use cases for motor models, and many motor architectures of interest. In each combination of use case and motor architecture, the appropriate motor model structure is expected to differ. Typically, the level of spatial and temporal resolution will increase when more insight into detailed motor performance is needed. Once a model structure is defined, the data required to parameterise and validate this model can be defined. Then, the experiments necessary to generate this data, along with the instrumentation required can be defined.Focusing on the model development of electric machines, this project aims to create an end to end workflow between model and data to increase model accuracy and adaptability to new units under test.The work will explore the potential for a general motor model and parameterisation procedure that is compatible with all the likely motor topologies of interest: flux switching, induction, and synchronous motor architectures. It will focus on implementing an autonomous parameter characterisation process, and on streamlining the experimental procedure behind the collection of data required for the parameterisation of an electric machine. Electric machine architectures vary enough to require bespoke motor models to simulate it's behaviour. Over the course of the first 6 months of the project, a model of a synchronous motor will be created with the aim of reaching an acceptable level of accuracy for the model's given application. The model at present is an ideal vector control model built in Simulink with a discrepancy between 3% and 5% from real world data. The next step is adding losses which can be categorised into 3 main categories: those which occur in the electrical circuit, magnetic circuit, and mechanical and ventilation losses. Furthermore, below 400rpm, the accuracy of the model decreases with speed and is near tangential with the trend line. The cause of this behiaviour could be due to an inaccurate data sheet used to parameterise the model, or limitations in the measurement instrumentation hindering its ability to accurately capture low speed data. The electric machine will then be tested through a predetermined, AVL parameterisation cycle to ascertain whether there is a variation between the true parameters of the machine and those supplied by the manufacturer. If the lack of accuracy at low speeds is due to limitations of the instrumentation, identical tests on a different machine could potentially be conducted at the IAAPS facility.I initially looked into vector control during the summer project, along with the operating principles of synchronous machines and how they were linked. With a background in ICEs and batteries, learning the fundamental characteristics of the type of electric machine I am working with is a necessity. Beginning this project with a laymans knowledge of an electric machine's operation has been a challenge and could lead to delays in the project, however, speaking to the AVL stakeholders to assertain what their objectives for the project will allow me to plan my workflowmore ef