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Lithium-ion Battery Modeling and HIL Testing With OPALRT

Lithium-ion Battery Modeling and HIL Testing With OPALRT

引用

Industrial Electronics: Developments & applications (ICIDeA), ieee international conference on-

作者： Raksha Kulal Leah Joshi Electrical and Electronics Engineering KLE Technological University Hubballi India

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

Battery modeling plays a crucial role in understanding and enhancing the performance of lithium-ion batteries, especially for applications like electric vehicles. Such models are essential for tasks like state estimation, performance prediction, and system control, all of which contribute to safer and more efficient battery usage. This work aims to develop a reliable model of a lithium-ion battery by first estimating key parameters through the least squares method using MATLAB's parameter estimation tools. With these parameters, a detailed model is developed in MATLAB Simulink that accounts for important effects like hysteresis. The model's accuracy is then assessed by testing it at various temperatures (15°C, 25°C, and 45°C) to observe changes in performance under different thermal conditions. Finally, the hardware realization of the developed battery model is obtained using Hardware-in-the-Loop (HIL) testing on the OPAL-RT platform, which allows for real-time validation and provides a strong foundation for future research in battery management applications.

关键词： Lithium-ion batteries Accuracy Parameter estimation Battery management systems Predictive models real-time systems Reliability Vehicle dynamics Hysteresis Testing

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Exploring Traffic Signal Control: A Comprehensive Survey on Reinforcement Learning Techniques

Exploring Traffic Signal Control: A Comprehensive Survey on ...

引用

Industrial Electronics: Developments & applications (ICIDeA), ieee international conference on-

作者： K. ThamaraiSelvi Asha Rani Bohra Vishal V Pawan Sai Sunkara Balaji Sunku Bhavsar NityaJignesh Department of Information Science and Engineering New Horizon College of Engineering Bangalore India Department of Computer Science and Engineering New Horizon College of Engineering Bangalore India

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

Urban traffic congestion at intersections poses a significant challenge, leading to inefficiencies in traffic flow and increased wait times. Traditional fixed-timer traffic signal systems fail to adapt to fluctuating traffic volumes, exacerbating congestion during peak hours and leading to unnecessary delays during off-peak hours. Reinforcement Learning (RL) offers a promising solution by enabling traffic signal control systems to dynamically adjust signal timings based on real-time data. This paper surveys the current state of traffic signal control systems, highlighting the advantages of RL-based methods and presenting future directions for improvement, including the integration of Internet of Things (IoT) devices, advanced RL algorithms, and enhanced pedestrian detection systems. Through a comparative analysis of existing methods, we propose future enhancements that can further optimize urban traffic management.

关键词： Surveys Adaptation models Pedestrians Smart cities Biological system modeling Reinforcement learning real-time systems Internet of Things Sustainable development Traffic congestion

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Communications in a Trust-Triggered Cyber-Physical-Human System for Human-Robot Collaborative Manufacturing

Communications in a Trust-Triggered Cyber-Physical-Human Sys...

引用

Robotics and Technologies for Industrial Automation (ROBOTHIA), ieee international conference on

作者： S. M. Mizanoor Rahman Mechanical Engineering Pennsylvania State University Dunmore USA

ISBN: (数字)9798350356755

ISBN: (纸本)9798350356762

We proposed a human-robot bidirectional trust-triggered cyber-physical-human (CPH) system framework for human-robot collaborative assembly in flexible manufacturing. For this purpose, we developed a one human-one robot hybrid cell where a human and a robot collaborated with each other to perform the assembly operation of different manufacturing components in a flexible manufacturing setup. We configured the human-robot collaborative system in three interconnected components of a CPH system: (i) cyber system (software system), (ii) physical system (the robot, sensors, hardware accessories, and the work environment), and (iii) human system (the human co-worker and the supervisor). We divided the functions of the CPH system into three modules: (i) computing, (ii) communication, and (iii) control. We used a model to compute the human and robot's bidirectional trust in each other in real-time. We implemented the proposed trust-triggered CPH framework in the human-robot collaborative assembly setup and conducted an experiment to modulate the communication methods and strategies among the cyber, physical and human components of the CPH system. The results showed that variations in communication methods significantly impacted the performance and interactions of the CPH system in terms of human-robot interaction (HRI), and task performance (efficiency and quality). The results can transform the design, development, analysis and control of human-robot collaborative systems configuring them in the form of a CPH system and thus enhance the scope, ease and effectiveness of human-robot collaborative systems for various applications such as manufacturing, construction, etc.

关键词： Service robots Collaboration Human-robot interaction Transforms Robot sensing systems Sensor systems real-time systems System software Sensors Assembly

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Design and Conception of an IoT-Controlled UV-C Sterilization System

Design and Conception of an IoT-Controlled UV-C Sterilizatio...

引用

ieee SSD international Multi-conference on systems, Signals and Devices

作者： Souaf Manel Kortas Manel Kamel Farid Micro- optoptoctronic and nanostructures laboratory University of Monastir Tunisia SysCom Laboratory University of Tunis El Manar Tunisia 3DWave Sousse Tunisia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Due to the emergence of infectious diseases through the air in recent years, the disinfection of high-risk contamination spaces, such as hospitals and large surfaces, has become an essential task in order to ensure better health safety against bacteria and viruses. Ultraviolet (UV) light has been widely recognized for its effectiveness in eliminating pathogenic microorganisms. It has proven to be effective in various applications, including healthcare facilities, laboratories, food processing industries, and public spaces. This project focuses on the use of the UV light for the area's sterilization operation, and proposes the development of a smartphone-controlled disinfection system: from the prototype to a commercial product dedicated to spaces with high aseptic requirements. Our conception is based on a passive infrared motion sensor (PIR) HC-SR501, an ESP32 microcontroller, a TFT touch screen and a mobile application connected with a server cloud and an UV-C lamp emitting shortwavelength ultraviolet light of 254 nm. The proposed prototype has been tested in a biological laboratory, at a distance of 250 cm and over an exposure time of 20 minutes, no bacterial colonies were detected, These biological test results approves the lamp's effectiveness and confirms the use validity of this technology for disinfection in healthcare-sensitive environments.

关键词： Cloud computing Laboratories Prototypes Touch sensitive screens Biology real-time systems Motion detection Thin film transistors Mobile applications Servers

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Sign Language to Speech: the Role of Conversion Gloves in Enhancing Communication

Sign Language to Speech: the Role of Conversion Gloves in En...

引用

Smart systems for applications in Electrical Sciences (ICSSES), international conference on

作者： Nagaraja B G Sohan B Amrutha H Impana K Harshhitha G M E&CE Department Vidyavardhaka College of Engineering Mysuru Karnataka India

ISBN: (数字)9798331507671

ISBN: (纸本)9798331507688

Individuals with speech disabilities often rely on sign language for communication; however, a significant challenge arises when interacting with people who are unfamiliar with it, creating a communication barrier. This study proposes a costeffective solution to address this issue by developing smart gloves that enable speech-impaired individuals to communicate more effectively. The system utilizes gloves embedded with flex and motion sensors to detect various sign language gestures. These sensor readings are processed using an Arduino UNO, which transmits the data to an Android device via a Bluetooth module. Gesture recognition is based on pre-defined patterns corresponding to specific sign language gestures, ensuring efficient processing with minimal latency. While the current prototype focuses on American sign language (ASL), it can be adapted for other sign language variants with appropriate calibration. The system aims to bridge the communication gap by translating users' gestures into text and converting the text into speech, providing a practical and portable solution for real-world scenarios. Challenges related to gesture recognition accuracy, sign language variations, and real-time translation latency are acknowledged, with potential improvements discussed for future work.

关键词： Resistors Sign language Translation Flexible printed circuits Synthesizers Prototypes Speech enhancement Smart systems real-time systems Text to speech

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A Deep Learning Framework for Comparative Analysis in Flood Detection and Area Estimation

A Deep Learning Framework for Comparative Analysis in Flood ...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), ieee conference on

作者： Shiva Teja Pecheti Ashwaj U Uthej K Murali K Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798331521691

ISBN: (纸本)9798331521707

This research presents an innovative deep learning framework designed to be utilized for area estimation and flood detection. The most suitable architecture for real-time applications is determined using this framework by a thorough comparison of advanced architectures, including U-Net, LeNet, ResNet, and VGG16. A crucial initial phase is to classify images as flooded or non-flooded using an effective Multilayer Perceptron (MLP) classifier. Users can see areas damaged by flooding and get quick assessments with the help of a simple Streamlit interface suited to foster immediate engagement. More significantly, the results show that LeNet is the most reliable model all things considered, often estimating flooded areas with the highest accuracy. Additionally, the framework delivers essential data for rapid disaster response by estimating the intensity of floods through accurate pixel analysis. The study offers helpful techniques to improve planning and response strategies for floods in an era of growing environmental uncertainty, as well as to giving important new insights into the use of deep learning in the management of floods.

关键词： Deep learning Technological innovation Accuracy Uncertainty Estimation Streaming media real-time systems Floods Reliability Testing

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Healthcare System Using IoT and Health Monitor Website

Healthcare System Using IoT and Health Monitor Website

引用

Industrial Electronics: Developments & applications (ICIDeA), ieee international conference on-

作者： Priyanka Vijay Tandalekar Khushi Avinash Kokane Shruti Devendra Gokulpure Aditi Prashant Deshmukh Rashmi Panherkar Amruta Udapurkar Department of Electrical Engineering JSPM's Rajarshi Shahu College of Engineering Pune India

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

Technological advancements and the miniaturization of sensors have prompted initiatives to implement these innovations in diverse fields, aiming to enhance the standard of living for individuals. A notable domain that has adopted this technology is the healthcare industry. Individuals requiring healthcare services often encounter high costs, a situation that is especially prevalent in developing nations. Consequently, the project aims to address a pressing healthcare issue that societies are currently facing, with the primary goal of developing a remote healthcare system. By analyzing data via a website, healthcare professionals or guardians can monitor a patient's health status from outside the hospital environment. In this initiative, we have designed a tailored Internet of Things (IoT) framework specifically aimed at healthcare applications. The project's aim was to establish a Health Analyzing System that employs locally sourced sensors, ensuring its cost-effectiveness for potential large-scale production. The suggested model gets the sensor data via the Arduino Nano microcontroller and sends the data to the cloud for processing and analysis., thereby facilitating remote access. The feedback actions derived from the analyzed data can be viewed on the website associated with the device.

关键词： Temperature sensors Temperature measurement Cloud computing Hospitals Medical services Sensor systems real-time systems Sensors Internet of Things Monitoring

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Forest Fire Prevention and Detection System

Forest Fire Prevention and Detection System

引用

Power Electronics, Computer applications (ICPECA), ieee international conference on

作者： Lasitha Jayakody Chamathka Edirisinghe Tharush Senasinghe Shaminda Dissanayake Narmada Gamage Dinithi Pandithage Jaliya L. Wijayaraja Dept. of Computer Systems Engineering Sri Lanka Institute of Information Malabe Sri Lanka

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

Forest fires pose significant threats to both the environment and human life, necessitating the development of advanced detection and prevention systems. In this study, we propose an integrated IoT (Internet of Things)-based system for early detection and management of forest fires. The system incorporates a range of sensors including heat, gas, and thermal imaging sensors, along with IoT technology for real-time monitoring and communication. Utilizing image processing techniques and (ML) Machine Learning algorithms, the system can accurately detect fires, predict their spreading patterns, and analyze environmental conditions. Key features include the deployment of disposable heat sensors for temperature monitoring, IoT sensors for gas detection and weather monitoring, and a centralized processing node for data analysis. Alerts are sent to nearby authorities and residents, while automated firefighting devices are activated to suppress fires until backup arrives. Experimental results demonstrate the effectiveness of the proposed system in early detection and prevention of forest fires.

关键词： Temperature sensors Technological innovation Wildfires Prevention and mitigation Forestry Sensor phenomena and characterization Sensor systems real-time systems Gas detectors Resilience

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Smart Battery Swapping and Safety Management System

Smart Battery Swapping and Safety Management System

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Industrial Electronics: Developments & applications (ICIDeA), ieee international conference on-

作者： Aniket Dhanwat Aditya Sunilkumar Harsh Chandanshiv Sayali Jawale Manjusha Kanawade Dept. of Electrical Engineering JSPM's Rajarshi Shahu College of Engineering Pune India

ISBN: (数字)9798331533205

ISBN: (纸本)9798331533212

In India the demand of EVs are continuously increasing as a necessity for the future, to efficiently implement this system we require proper charging infrastructure. To reduce the charging time of existing charging system we can use battery swapping system. This paper presents the development of a smart battery swapping system which is designed for two 3.7V 4Ah batteries. The system continuously monitors the SOC, battery temperature, and potential fire hazards. Using a DHT11 sensor for temperature tracking and flame detection, the system incorporates visual and audible alarms and relay control for safety. Additionally, the system sends SMS via SIM800L if any charging slot is empty, ensuring real-time management and efficient use.

关键词： Temperature sensors Temperature measurement Visualization Safety management Fires real-time systems Batteries State of charge Usability Monitoring

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A Comprehensive Deep Learning Approach for real-time Detection and Classification of Large and Small Defects in Industrial applications

A Comprehensive Deep Learning Approach for Real-Time Detecti...

引用

international conference on Big Data and Smart computing (BIGCOMP)

作者： Joo In Kim Sung Hoon Kim Gi Nam Kwan Hee Yoo F M Fahmid Hossain Department of Computer Science Chungbuk National University Cheongju South Korea

ISBN: (数字)9798331529024

ISBN: (纸本)9798331529031

Object detection is one of the most important and continuously evolving research areas in computer vision, and as image processing technology advances, its significance is increasing across various application fields. In particular, detecting small objects is essential for identifying various defect types, but conventional defect detection methods using single AI models face limitations in achieving high accuracy across all defect types, making practical application challenging. To address this, this paper proposes a real-time method for recognizing both large and small defects in images by utilizing a deep learning approach that combines detection and classification models. The proposed structure initially integrates the Small Object Information Flow (SOIF) module into the detection model, which reduces variables related to lens conditions and enhances the accuracy of circular object detection. This helps minimize interference from complex elements in the background and image, enabling stable initial defect detection. Following this, a classification model is used to categorize specific defect types among relatively large defects. Finally, the detection model is applied once more to more precisely identify smaller defect types, creating a structure capable of comprehensively detecting defects of various sizes and shapes. This approach significantly improves overall accuracy and speed, making it a promising solution for real-world industrial settings where defects of varying sizes need to be reliably identified.

关键词： Deep learning Analytical models Accuracy Shape Computational modeling Object detection real-time systems Stability analysis Reliability Defect detection

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