Georg Janisch , Andreas Kugi , Wolfgang Kemmetmüller
{"title":"用于电动汽车感应机的高性能模型预测扭矩控制概念","authors":"Georg Janisch , Andreas Kugi , Wolfgang Kemmetmüller","doi":"10.1016/j.conengprac.2024.106128","DOIUrl":null,"url":null,"abstract":"<div><div>Induction machines are widely used in electric vehicles due to their high reliability and low costs. Controlling these machines to meet the high-performance demands presents a significant challenge since they are often operated at high speed and within operating ranges where magnetic saturation plays a significant role. Furthermore, specific motor parameters are not accurately known or vary during operation, e.g., due to temperature changes. Therefore, there is still a demand for control strategies to meet these demands systematically. This paper proposes a novel control strategy combining a model predictive control (MPC) concept with a fast feedback controller and a nonlinear observer. The proposed MPC strategy is based on a magnetic nonlinear model and allows for a long prediction horizon. It features high torque dynamics while ensuring energy optimality in the steady state. The results also show excellent performance for high rotational speeds and the operation at the system limits, outperforming state-of-the-art control concepts.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A high-performance model predictive torque control concept for induction machines for electric vehicle applications\",\"authors\":\"Georg Janisch , Andreas Kugi , Wolfgang Kemmetmüller\",\"doi\":\"10.1016/j.conengprac.2024.106128\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Induction machines are widely used in electric vehicles due to their high reliability and low costs. Controlling these machines to meet the high-performance demands presents a significant challenge since they are often operated at high speed and within operating ranges where magnetic saturation plays a significant role. Furthermore, specific motor parameters are not accurately known or vary during operation, e.g., due to temperature changes. Therefore, there is still a demand for control strategies to meet these demands systematically. This paper proposes a novel control strategy combining a model predictive control (MPC) concept with a fast feedback controller and a nonlinear observer. The proposed MPC strategy is based on a magnetic nonlinear model and allows for a long prediction horizon. It features high torque dynamics while ensuring energy optimality in the steady state. The results also show excellent performance for high rotational speeds and the operation at the system limits, outperforming state-of-the-art control concepts.</div></div>\",\"PeriodicalId\":50615,\"journal\":{\"name\":\"Control Engineering Practice\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2024-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Control Engineering Practice\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0967066124002879\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Control Engineering Practice","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0967066124002879","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
A high-performance model predictive torque control concept for induction machines for electric vehicle applications
Induction machines are widely used in electric vehicles due to their high reliability and low costs. Controlling these machines to meet the high-performance demands presents a significant challenge since they are often operated at high speed and within operating ranges where magnetic saturation plays a significant role. Furthermore, specific motor parameters are not accurately known or vary during operation, e.g., due to temperature changes. Therefore, there is still a demand for control strategies to meet these demands systematically. This paper proposes a novel control strategy combining a model predictive control (MPC) concept with a fast feedback controller and a nonlinear observer. The proposed MPC strategy is based on a magnetic nonlinear model and allows for a long prediction horizon. It features high torque dynamics while ensuring energy optimality in the steady state. The results also show excellent performance for high rotational speeds and the operation at the system limits, outperforming state-of-the-art control concepts.
期刊介绍:
Control Engineering Practice strives to meet the needs of industrial practitioners and industrially related academics and researchers. It publishes papers which illustrate the direct application of control theory and its supporting tools in all possible areas of automation. As a result, the journal only contains papers which can be considered to have made significant contributions to the application of advanced control techniques. It is normally expected that practical results should be included, but where simulation only studies are available, it is necessary to demonstrate that the simulation model is representative of a genuine application. Strictly theoretical papers will find a more appropriate home in Control Engineering Practice''s sister publication, Automatica. It is also expected that papers are innovative with respect to the state of the art and are sufficiently detailed for a reader to be able to duplicate the main results of the paper (supplementary material, including datasets, tables, code and any relevant interactive material can be made available and downloaded from the website). The benefits of the presented methods must be made very clear and the new techniques must be compared and contrasted with results obtained using existing methods. Moreover, a thorough analysis of failures that may happen in the design process and implementation can also be part of the paper.
The scope of Control Engineering Practice matches the activities of IFAC.
Papers demonstrating the contribution of automation and control in improving the performance, quality, productivity, sustainability, resource and energy efficiency, and the manageability of systems and processes for the benefit of mankind and are relevant to industrial practitioners are most welcome.