检索结果-内蒙古大学图书馆

A nonlinear hysteresis compensation control of hydro-viscous drive in air transport operations

Chinese Journal of Aeronautics 2025年第2期38卷 161-174页

作者： Liang WANG Jianjian LIANG Lin ZHANG Shoukun WANG Junzheng WANG School of Automation and Software Shanxi UniversityTaiyuan 030031China Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China

The Hydro-Viscous Drive(HVD)speed regulating system finds extensive application in air transport transmission systems to regulate the stepless speed or conduct overload ***,its intrinsic hysteretic behaviors,such as the asymmetric hysteretic and dead zone,could introduce inaccuracy and delay in control applications,posing challenges to system *** paper investigates a Nonlinear Hysteresis Compensation Control(NHCC)that consists of two parts to control the HVD output speed by operating the valve under different engine operating *** the first part,the Inverse Hysteresis Compensator(IHC)based on major loop data is introduced for the asymmetric hysteresis characterization and compensation of the HVD speed control system of the power generation and distribution,which aims to reduce the hysteresis and dead zone effect and expand the effective input *** the second part,the Active Disturbance Rejection Controller(ADRC)is employed to mitigate the hysteresis effects of the compensated system and remove the steady-state error,which allows real-time compensation of the estimated perturbations as state feedback to achieve the required *** experimental laboratory station has been fabricated to evaluate the proposed *** test results show that the NHCC method can regulate the fan speed to the desired value(45 r/min at steady state)and broaden the effective input range to the full range under different engine ***,the proposed control method can reduce the non-linearity of the input and output curves(from 18%to 4%)and compensate for the asymmetric hysteresis(from 38%to 5%).

关键词： Hydro-viscous drive Nonlinear hysteresis compensation Inverse hysteresis compensation Speed regulating system ADRC

来源：评论

学校读者我要写书评

暂无评论

Five-layer IoT and Fog Computing Framework Towards Digital Twinning of Battery Management systems for e-Transportation 4

Five-layer IoT and Fog Computing Framework Towards Digital T...

引用

4th International Conference on Smart Grid and Renewable Energy, SGRE 2024

作者： Karnehm, Dominic Samanta, Akash Neve, Antje Williamson, Sheldon University of the Bundeswehr Munich Institute of Intelligent Distributed Systems Neubiberg Germany Ontario Tech University Electrical Computer and Software Engineering Oshawa Canada

ISBN: (纸本)9798350306262

It is needless to mention that the proven capability of cloud computing and digital twin-based monitoring and control systems will play a major role in the implementation of digital twin-based lithium-ion battery management systems (BMS) for e-transportation. In this context, the combination of the Internet of Things (IoT) and fog computing emerges as an enabling technology that facilitates bidirectional data communication and processing. This paper proposes a five-layer IoT framework for the implementation of cloud-based battery monitoring and BMS. Additionally, it critically analyzes the existing IoT frameworks applied to BMS and justifies the suitability of the five-layer architecture. Furthermore, the advantages of fog computing, such as low latency, fault tolerance, limitless systems, multiple applications, and shared responsibility, are discussed. The paper also explores four previously proposed computing-enabled architectures: centralized, hybrid, distributed, and hybrid-distributed computing. Moreover, the potential of utilizing hybrid computing architectures, incorporating fog computing as a supplement to cloud computing, is highlighted to address fault, privacy, or latency issues in cloud-based BMS. © 2024 IEEE.

关键词： Battery management systems

来源：评论

学校读者我要写书评

暂无评论

Voltage Relaxation Pattern Recognition for Efficient Sorting of Healthy Cells for Second-Life Applications of Retired Electric Vehicle Batteries 25

Voltage Relaxation Pattern Recognition for Efficient Sorting...

引用

25th IEEE International Conference on Industrial technology, ICIT 2024

作者： Samanta, Akash Karnehm, Dominic Neve, Antje Williamson, Sheldon Ontario Tech University Electrical Computer And Software Engineering Oshawa Canada Institute Of Intelligent Distributed Systems University Of The Bundeswehr Munich Neubiberg Germany

ISBN: (纸本)9798350340266

First-generation electric vehicle (EV) batteries are now retiring from their first life with 70-80%of their initial capacity and are becoming available in the market. To harness the remaining capacity of retired batteries before they reach the end of their life, researchers have proposed various methods, including backup and emergency power supplies for homes, grid-tied stationary energy storage, and storage for renewable energy applications. These applications are collectively termed second-life applications. The first step in utilizing these retired batteries is the selection of healthy cells, as cells in an EV battery pack do not degrade evenly. State-of-the-art cell selection and sorting techniques are either ineffective for industrial-grade applications or highly time-consuming processes. Therefore, this paper proposes a charging voltage relaxation pattern recognition method to efficiently sort healthy cells, powered by data-driven machine learning algorithms. A wide range of battery cycling data collected under different ambient and charging conditions is used for training, testing, and validating the proposed sorting strategy. Furthermore, a comparative analysis is conducted to demonstrate the effectiveness of the proposed strategy compared to state-of-the-art methods. © 2024 IEEE.

关键词： Battery management systems

来源：评论

学校读者我要写书评

暂无评论

Temporal Sensitivity Analysis of Internal Temperature Informed Charging Algorithms and Rapid Thermal Management System for E-mobility

Temporal Sensitivity Analysis of Internal Temperature Inform...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Samanta, Akash Chetri, Chandan Karnehm, Dominic Neve, Antje Williamson, Sheldon Ontario Tech University Department of Electrical Computer and Software Engineering Oshawa Canada Bundeswehr University Munich Institute of Intelligent Distributed Systems Neubiberg Germany

ISBN: (纸本)9798350376067

The experimental studies presented in this paper reveal that existing thermal management systems (TMS) and temperature-informed charging algorithms exhibit a response time lag of at least 5.3 minutes due to their reliance on surface temperature measurements. The results indicate that changes in the internal thermal state of lithium-ion batteries (LIBs), induced by variations in charging currents, take an average of 2 minutes to manifest on the battery surface, particularly evident in cylindrical cells. Current thermal management systems for automotive battery packs solely rely on surface temperature measurements, neglecting the approximately 5.8°C temperature difference between the core and surface in TMS control. Consequently, changes in the battery's thermal state due to internal heat losses are not promptly detected by surface-mounted temperature sensors. This delayed response time accelerates battery degradation and increases the risk of thermal runaway events. In this study, temperature-informed fast charging algorithms, tested under various ambient conditions for LIBs, along with a comparative analysis, demonstrate that response time can be reduced by at least 2 minutes by considering internal temperature rather than relying solely on surface temperature measurements. Moreover, accounting for the temperature difference between the core and surface facilitates rapid TMS control and health-conscious fast charging, thereby mitigating the risk of thermal runaway events. © 2024 IEEE.

关键词： Surface measurement

来源：评论

学校读者我要写书评

暂无评论

Student academic performance prediction via hypergraph and TabNet

引用

Journal of Big Data 2025年第1期12卷 1-24页

作者： Yang, Yisheng Zhao, Shiyu An, Sufang Li, Xiaoyong Zhang, Yong Beijing Key Laboratory of Multimedia and Intelligent Software Technology Beijing University of Technology Beijing China Academic Affairs Office Beijing Open University Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China

Student academic performance prediction plays a very important role in student management. With the development of deep learning, there has been some related research work on predicting student academic performance. Although many factors influence students’ academic performance, students at the same university tend to have similar intellectual levels and learning environments. Therefore, learning behaviors can significantly impact their academic performance. Thus, modeling students’ behavior can enable the prediction of their academic performance. However, existing methods mostly focus on modeling individual student behaviors, neglecting the complex associations among students hidden within campus behavioral data. In reality, the associations between students often involve higher-order, multi-to-multi relationships, rather than simple, pairwise connections. At the same time, most data-driven deep learning models are not interpretable. But in fact, the analysis of behaviors that affect student academic performance is more useful in many cases. To address these issues, this paper proposes a student academic performance prediction model that combines hypergraphs and TabNet. This method first processes and extracts usable behavior features from collected multi-source campus behavior data;secondly, it utilizes K-Nearest Neighbors (KNN) to construct a hypergraph to describe the higher-order associations among students;then, it uses hypergraph convolution to aggregate neighborhood features to learn sample embedding representations;finally, the academic performance of students are predicted by the TabNet model. Experimental results on real student behavior datasets indicate that the precision, recall, and F1 score of the method proposed in this paper are improved compared to baseline methods. Additionally, using hypergraphs and TabNet can help to explain the relationship between student behavior and performance at the feature level. © The Author(s) 2025.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Towards Digital Twining of Lithium-ion Battery Management systems: An Extended Kalman Filter for State-of-Charge Estimation in Cloud-platform

Towards Digital Twining of Lithium-ion Battery Management Sy...

引用

2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Karnehm, Dominic Anekal, Latha Samanta, Akash Neve, Antje Williamson, Sheldon Bundeswehr University Munich Institute of Intelligent Distributed Systems Neubiberg Germany Ontario Tech University Electrical Computer and Software Engineering ONL1G 0C5 Canada

ISBN: (纸本)9798350316445

In practice, extended Kalman filter (EKF) is one of the most popular lithium-ion battery (LIB) state of charge (SOC) estimation algorithms in electric vehicles onboard battery management system (BMS). With the increasing necessity of off-loading the computational burden and data storage capacity of onboard BMS, the application of battery digital twin and cloud-BMS are getting popularity. Therefore, to assess the performance of EKF in terms of accuracy, the computational time, and overall request and execution time, an EKF-based SOC estimation method is developed in the cloud platform of Amazon Web Services (AWS). For a specific battery test data set, the cloud-based EKF demonstrated a mean absolute error of 0.00226 and a request time of 0.028s that are highly satisfactory towards developing a digital twin enabled cloud-based BMS. © 2023 IEEE.

关键词： cloud Computing computational cost electric vehicles intelligent state estimation transportation electrification

来源：评论

学校读者我要写书评

暂无评论

Sliced Online Model Checking for Optimizing the Beam Scheduling Problem in Robotic Radiation Therapy

arXiv

引用

arXiv 2024年

作者： Beckers, Lars Gerlach, Stefan Lübke, Ole Schlaefer, Alexander Schupp, Sibylle Institute for Software Systems Institute of Medical Technology and Intelligent Systems Hamburg University of Technology Hamburg Germany

In robotic radiation therapy, high-energy photon beams from different directions are directed at a target within the patient. Target motion can be tracked by robotic ultrasound and then compensated by synchronous beam motion. However, moving the beams may result in beams passing through the ultrasound transducer or the robot carrying it. While this can be avoided by pausing the beam delivery, the treatment time would increase. Typically, the beams are delivered in an order which minimizes the robot motion and thereby the overall treatment time. However, this order can be changed, i.e., instead of pausing beams, other feasible beam could be delivered. We address this problem of dynamically ordering the beams by applying a model checking paradigm to select feasible beams. Since breathing patterns are complex and change rapidly, any offline model would be too imprecise. Thus, model checking must be conducted online, predicting the patient’s current breathing pattern for a short amount of time and checking which beams can be delivered safely. Monitoring the treatment delivery online provides the option to reschedule beams dynamically in order to avoid pausing and hence to reduce treatment time. While human breathing patterns are complex and may change rapidly, we need a model which can be verified quickly and use approximation by a superposition of sine curves. Further, we simplify the 3D breathing motion into separate 1D models. We compensate the simplification by adding noise inside the model itself. In turn, we synchronize between the multiple models representing the different spatial directions, the treatment simulation, and corresponding verification queries. Our preliminary results show a 16.02 % to 37.21 % mean improvement on the idle time compared to a static beam schedule, depending on an additional safety margin. Note that an additional safety margin around the ultrasound robot can decrease idle times but also compromises plan quality by limiting the range of

关键词： Radiotherapy

来源：评论

学校读者我要写书评

暂无评论

Robust Counting in Overcrowded Scenes Using Batch-Free Normalized Deep ConvNet

引用

Computer systems Science & Engineering 2023年第9期46卷 2741-2754页

作者： Sana Zahir Rafi Ullah Khan Mohib Ullah Muhammad Ishaq Naqqash Dilshad Amin Ullah Mi Young Lee Institute of Computer Sciences and Information Technology(ICS/IT) The University of AgriculturePeshawar25130Khyber PakhtunkhwaPakistan Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Collaborative Robotics and Intelligent Systems(CoRIS)Institute Oregon State UniversityORUSA Department of Software Sejong UniversitySeoul05006Korea

The analysis of overcrowded areas is essential for flow monitoring,assembly control,and *** counting’s primary goal is to calculate the population in a given region,which requires real-time analysis of congested scenes for prompt reactionary *** crowd is always unexpected,and the benchmarked available datasets have a lot of variation,which limits the trained models’performance on unseen test *** this paper,we proposed an end-to-end deep neural network that takes an input image and generates a density map of a crowd *** proposed model consists of encoder and decoder networks comprising batch-free normalization layers known as evolving normalization(EvoNorm).This allows our network to be generalized for unseen data because EvoNorm is not using statistics from the training *** decoder network uses dilated 2D convolutional layers to provide large receptive fields and fewer parameters,which enables real-time processing and solves the density drift problem due to its large receptive *** benchmark datasets are used in this study to assess the proposed model,resulting in the conclusion that it outperforms conventional models.

关键词： Artificial intelligence deep learning crowd counting scene understanding

来源：评论

学校读者我要写书评

暂无评论

VisioSLR: A Vision Data-Driven Framework for Sign Language Video Recognition and Performance Evaluation on Fine-Tuned YOLO Models

引用

Procedia Computer Science 2025年 257卷 85-92页

作者： Leila Ismail Nada Shahin Henok Tesfaye Alain Hennebelle Intelligent Distributed Computing and Systems (INDUCE) Lab Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University United Arab Emirates Independent Researcher

With the emergence of AI for good, there has been an increasing interest in building computer vision data-driven deep learning inclusive AI solutions. Sign language Recognition (SLR) has gained attention recently. It is an essential component of a sign-to-text translation system to support the deaf and hard-of-hearing population. This paper presents a computer VISIOn data-driven deep learning framework for Sign Language video Recognition (VisoSLR). VisioSLR provides a precise measurement of translating signs for developing an end-to-end computational translation system. Considering the scarcity of sign language datasets, which hinders the development of an accurate recognition model, we evaluate the performance of our framework by fine-tuning the very well-known YOLO models, which are built from a signs-unrelated collection of images and videos, using a small-sized sign language dataset. Gathering a sign language dataset for signs training would involve an enormous amount of time to collect and annotate videos in different environmental setups and multiple signers, in addition to the training time of a model. Numerical evaluations of VisioSLR show that our framework recognizes signs with a mean average precision of 97.4%, 97.1%, and 95.5% and 11, 12, and 12 milliseconds of recognition time on YOLOv8m, YOLOv9m, and YOLOv11m, respectively.

关键词： Artificial intelligence Computer vision Deep learning Fine-tuning Machine translation Neural machine translation Sign language Sign language recognition Transfer learning YOLO

来源：评论

学校读者我要写书评

暂无评论

Modeling 3 Needle Steering in Uppaal

Modeling 3 Needle Steering in Uppaal

引用

5th Workshop on Models for Formal Analysis of Real systems, MARS 2022

作者： Lehmann, Sascha Rogalla, Antje Neidhardt, Maximilian Reinecke, Anton Schlaefer, Alexander Schupp, Sibylle Institute for Software Systems Hamburg University of Technology Hamburg Germany Institute of Medical Technology and Intelligent Systems Hamburg University of Technology Hamburg Germany

Medical cyber-physical systems are safety-critical, and as such, require ongoing verification of their correct behavior, as system failure during run time may cause severe (or even fatal) personal damage. However, creating a verifiable model often conflicts with other application requirements, most notably regarding data precision and model accuracy, as efficient model checking promotes discrete data (over continuous) and abstract models to reduce the state space. In this paper, we approach the task of medical needle steering in soft tissue around potential obstacles. We design a verifiable model of needle motion (implemented in Uppaal Stratego) and a framework embedding the model for online needle steering. We mitigate the conflict by imposing boundedness on both the data types, reducing from R3 to Z3 when needed, and the motion and environment models, reducing the set of allowed local actions and global paths. In experiments, we successfully apply the static model alone, as well as the dynamic framework in scenarios with varying environment complexity and both a virtual and real needle setting, where up to 100% of targets were reached depending on the scenario and needle. © S. Lehmann et al.

关键词： Needles

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：