Huan Zhang, Lei Deng, Jin Zhao, Weihua Li, Haiping Du
{"title":"电动汽车变速器磁流变液双离合器非线性滞后模型的比较分析与优化","authors":"Huan Zhang, Lei Deng, Jin Zhao, Weihua Li, Haiping Du","doi":"10.1088/1361-665x/ad6ecd","DOIUrl":null,"url":null,"abstract":"Electric vehicle (EV) drivetrains have witnessed remarkable progress, prompting intensified research into advanced transmission systems. Magnetorheological fluids (MRF) clutches offer precise modulation of input currents, enabling swift and seamless torque delivery for EV transmission systems, owing to their exceptional performance. The transmission of an EV requires MRF-based clutches to deliver a precise and rapid torque transfer during gear shifting. In these scenarios, the inherent current rate-dependent hysteresis of the MRF-based clutches between the output torque and input current poses a significant challenge in accurately regulating output torque. Therefore, an accurate clutch model of the MRF-based clutches that can describe the rate-dependent hysteresis is crucial to achieve precise control of the output torque. This study investigates the nonlinear hysteresis phenomena using a prototyped MRF dual-clutch (MRFDC) for the transmission system of EVs, followed by a comprehensive analysis of three widely used hysteresis models: two parametric models, including the Bouc-Wen (BW) model and algebraic model (AM), and a non-parametric model, the NARX model. Accuracy, fitting time, and stack size are selected as the main indicators to evaluate the three models comprehensively. Results indicate that the NARX model has exceptional accuracy compared to the others, while it has a much higher memory requirement. The algebraic model shows a great advantage in computational efficiency because it has a straightforward expression. The BW model is in the middle position for all three indicators. To optimize the classic BW model (CBW), a fractional-order modified BW model (FOMBW) is proposed based on the polynomial input function and fractional-order derivatives. The proposed FOMBW model demonstrates superior capability in capturing asymmetric and rate-dependent characteristics compared to the CBW model. These findings provide the basis for choosing an appropriate model to effectively capture nonlinear current hysteresis phenomena within MRFDC with the requirement for precise torque control during gear shifting.","PeriodicalId":21656,"journal":{"name":"Smart Materials and Structures","volume":"15 1","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparative analysis and optimization of nonlinear hysteresis models for a magnetorheological fluid dual-clutch of an electric vehicle transmission\",\"authors\":\"Huan Zhang, Lei Deng, Jin Zhao, Weihua Li, Haiping Du\",\"doi\":\"10.1088/1361-665x/ad6ecd\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Electric vehicle (EV) drivetrains have witnessed remarkable progress, prompting intensified research into advanced transmission systems. Magnetorheological fluids (MRF) clutches offer precise modulation of input currents, enabling swift and seamless torque delivery for EV transmission systems, owing to their exceptional performance. The transmission of an EV requires MRF-based clutches to deliver a precise and rapid torque transfer during gear shifting. In these scenarios, the inherent current rate-dependent hysteresis of the MRF-based clutches between the output torque and input current poses a significant challenge in accurately regulating output torque. Therefore, an accurate clutch model of the MRF-based clutches that can describe the rate-dependent hysteresis is crucial to achieve precise control of the output torque. This study investigates the nonlinear hysteresis phenomena using a prototyped MRF dual-clutch (MRFDC) for the transmission system of EVs, followed by a comprehensive analysis of three widely used hysteresis models: two parametric models, including the Bouc-Wen (BW) model and algebraic model (AM), and a non-parametric model, the NARX model. Accuracy, fitting time, and stack size are selected as the main indicators to evaluate the three models comprehensively. Results indicate that the NARX model has exceptional accuracy compared to the others, while it has a much higher memory requirement. The algebraic model shows a great advantage in computational efficiency because it has a straightforward expression. The BW model is in the middle position for all three indicators. To optimize the classic BW model (CBW), a fractional-order modified BW model (FOMBW) is proposed based on the polynomial input function and fractional-order derivatives. The proposed FOMBW model demonstrates superior capability in capturing asymmetric and rate-dependent characteristics compared to the CBW model. These findings provide the basis for choosing an appropriate model to effectively capture nonlinear current hysteresis phenomena within MRFDC with the requirement for precise torque control during gear shifting.\",\"PeriodicalId\":21656,\"journal\":{\"name\":\"Smart Materials and Structures\",\"volume\":\"15 1\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-08-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Smart Materials and Structures\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1088/1361-665x/ad6ecd\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INSTRUMENTS & INSTRUMENTATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Materials and Structures","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1088/1361-665x/ad6ecd","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INSTRUMENTS & INSTRUMENTATION","Score":null,"Total":0}
Comparative analysis and optimization of nonlinear hysteresis models for a magnetorheological fluid dual-clutch of an electric vehicle transmission
Electric vehicle (EV) drivetrains have witnessed remarkable progress, prompting intensified research into advanced transmission systems. Magnetorheological fluids (MRF) clutches offer precise modulation of input currents, enabling swift and seamless torque delivery for EV transmission systems, owing to their exceptional performance. The transmission of an EV requires MRF-based clutches to deliver a precise and rapid torque transfer during gear shifting. In these scenarios, the inherent current rate-dependent hysteresis of the MRF-based clutches between the output torque and input current poses a significant challenge in accurately regulating output torque. Therefore, an accurate clutch model of the MRF-based clutches that can describe the rate-dependent hysteresis is crucial to achieve precise control of the output torque. This study investigates the nonlinear hysteresis phenomena using a prototyped MRF dual-clutch (MRFDC) for the transmission system of EVs, followed by a comprehensive analysis of three widely used hysteresis models: two parametric models, including the Bouc-Wen (BW) model and algebraic model (AM), and a non-parametric model, the NARX model. Accuracy, fitting time, and stack size are selected as the main indicators to evaluate the three models comprehensively. Results indicate that the NARX model has exceptional accuracy compared to the others, while it has a much higher memory requirement. The algebraic model shows a great advantage in computational efficiency because it has a straightforward expression. The BW model is in the middle position for all three indicators. To optimize the classic BW model (CBW), a fractional-order modified BW model (FOMBW) is proposed based on the polynomial input function and fractional-order derivatives. The proposed FOMBW model demonstrates superior capability in capturing asymmetric and rate-dependent characteristics compared to the CBW model. These findings provide the basis for choosing an appropriate model to effectively capture nonlinear current hysteresis phenomena within MRFDC with the requirement for precise torque control during gear shifting.
期刊介绍:
Smart Materials and Structures (SMS) is a multi-disciplinary engineering journal that explores the creation and utilization of novel forms of transduction. It is a leading journal in the area of smart materials and structures, publishing the most important results from different regions of the world, largely from Asia, Europe and North America. The results may be as disparate as the development of new materials and active composite systems, derived using theoretical predictions to complex structural systems, which generate new capabilities by incorporating enabling new smart material transducers. The theoretical predictions are usually accompanied with experimental verification, characterizing the performance of new structures and devices. These systems are examined from the nanoscale to the macroscopic. SMS has a Board of Associate Editors who are specialists in a multitude of areas, ensuring that reviews are fast, fair and performed by experts in all sub-disciplines of smart materials, systems and structures.
A smart material is defined as any material that is capable of being controlled such that its response and properties change under a stimulus. A smart structure or system is capable of reacting to stimuli or the environment in a prescribed manner. SMS is committed to understanding, expanding and dissemination of knowledge in this subject matter.