{"title":"考虑离合器磨损和发动机温度变化的混合动力电动汽车自适应模糊协调控制策略","authors":"Aiyun Gao, Zhumu Fu, Fazhan Tao","doi":"10.1002/ese3.1754","DOIUrl":null,"url":null,"abstract":"<p>An improved method of clutch coordinated control based on the Kalman filter was proposed to solve the problem that the existing mode switching strategy of hybrid electric vehicles could not adapt to engine temperature changes and clutch wear. First, taking advantage of the relationship between the torque transmitted by the clutch and the starting resistance of the engine, combined with the characteristics of the clutch, the clutch wear was roughly calculated. Accordingly, the control strategy of the clutch in the existing mode switching was improved to adapt to the clutch wear. The adaptive control strategy proposed for clutch wear included the fuzzy control module of the initial engagement pressure, the fuzzy inference module of the clutch engaging pressure change, the clutch wear estimation module and so on. Second, the Kalman filter was used to process the results to improve the estimation accuracy of clutch wear. The engine starting resistance related to starting speed and temperature was modeled to enhance the adaptability of the control strategy to engine temperature. Finally, the designed control strategy was verified in simulation. The results show that the improved control strategy can complete the mode switching when the engine temperature is variable and the clutch is worn. The maximum impact degree increased from 5 m/s<sup>3</sup> without wear to 8.5 m/s<sup>3</sup> with wear, but it is still less than the index limit, and it can be considered that the proposed strategy can achieve the desired control effect. The fuzzy control algorithm proposed enhances the vehicle's ride comfort during mode switching from pure electric driving to hybrid driving.</p>","PeriodicalId":11673,"journal":{"name":"Energy Science & Engineering","volume":"12 9","pages":"3631-3646"},"PeriodicalIF":3.5000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.1754","citationCount":"0","resultStr":"{\"title\":\"An adaptive fuzzy coordinated control strategy for hybrid electric vehicles considering clutch wear and engine temperature variation\",\"authors\":\"Aiyun Gao, Zhumu Fu, Fazhan Tao\",\"doi\":\"10.1002/ese3.1754\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>An improved method of clutch coordinated control based on the Kalman filter was proposed to solve the problem that the existing mode switching strategy of hybrid electric vehicles could not adapt to engine temperature changes and clutch wear. First, taking advantage of the relationship between the torque transmitted by the clutch and the starting resistance of the engine, combined with the characteristics of the clutch, the clutch wear was roughly calculated. Accordingly, the control strategy of the clutch in the existing mode switching was improved to adapt to the clutch wear. The adaptive control strategy proposed for clutch wear included the fuzzy control module of the initial engagement pressure, the fuzzy inference module of the clutch engaging pressure change, the clutch wear estimation module and so on. Second, the Kalman filter was used to process the results to improve the estimation accuracy of clutch wear. The engine starting resistance related to starting speed and temperature was modeled to enhance the adaptability of the control strategy to engine temperature. Finally, the designed control strategy was verified in simulation. The results show that the improved control strategy can complete the mode switching when the engine temperature is variable and the clutch is worn. The maximum impact degree increased from 5 m/s<sup>3</sup> without wear to 8.5 m/s<sup>3</sup> with wear, but it is still less than the index limit, and it can be considered that the proposed strategy can achieve the desired control effect. The fuzzy control algorithm proposed enhances the vehicle's ride comfort during mode switching from pure electric driving to hybrid driving.</p>\",\"PeriodicalId\":11673,\"journal\":{\"name\":\"Energy Science & Engineering\",\"volume\":\"12 9\",\"pages\":\"3631-3646\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ese3.1754\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Science & Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/ese3.1754\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Science & Engineering","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ese3.1754","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
An adaptive fuzzy coordinated control strategy for hybrid electric vehicles considering clutch wear and engine temperature variation
An improved method of clutch coordinated control based on the Kalman filter was proposed to solve the problem that the existing mode switching strategy of hybrid electric vehicles could not adapt to engine temperature changes and clutch wear. First, taking advantage of the relationship between the torque transmitted by the clutch and the starting resistance of the engine, combined with the characteristics of the clutch, the clutch wear was roughly calculated. Accordingly, the control strategy of the clutch in the existing mode switching was improved to adapt to the clutch wear. The adaptive control strategy proposed for clutch wear included the fuzzy control module of the initial engagement pressure, the fuzzy inference module of the clutch engaging pressure change, the clutch wear estimation module and so on. Second, the Kalman filter was used to process the results to improve the estimation accuracy of clutch wear. The engine starting resistance related to starting speed and temperature was modeled to enhance the adaptability of the control strategy to engine temperature. Finally, the designed control strategy was verified in simulation. The results show that the improved control strategy can complete the mode switching when the engine temperature is variable and the clutch is worn. The maximum impact degree increased from 5 m/s3 without wear to 8.5 m/s3 with wear, but it is still less than the index limit, and it can be considered that the proposed strategy can achieve the desired control effect. The fuzzy control algorithm proposed enhances the vehicle's ride comfort during mode switching from pure electric driving to hybrid driving.
期刊介绍:
Energy Science & Engineering is a peer reviewed, open access journal dedicated to fundamental and applied research on energy and supply and use. Published as a co-operative venture of Wiley and SCI (Society of Chemical Industry), the journal offers authors a fast route to publication and the ability to share their research with the widest possible audience of scientists, professionals and other interested people across the globe. Securing an affordable and low carbon energy supply is a critical challenge of the 21st century and the solutions will require collaboration between scientists and engineers worldwide. This new journal aims to facilitate collaboration and spark innovation in energy research and development. Due to the importance of this topic to society and economic development the journal will give priority to quality research papers that are accessible to a broad readership and discuss sustainable, state-of-the art approaches to shaping the future of energy. This multidisciplinary journal will appeal to all researchers and professionals working in any area of energy in academia, industry or government, including scientists, engineers, consultants, policy-makers, government officials, economists and corporate organisations.