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Development and Validation of AEBS Anti-slip Control Model for In-wheel Motor Drive EV in AMESim Co-simulation with Matlab/Simulink 4

Development and Validation of AEBS Anti-slip Control Model f...

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2021 4th international conference on modeling, simulation and Optimization technologies and applications, MSOTA 2021

作者： Yang, Yu Liu, Yang Wang, Chao Yang, Yu School of Vehicle and Energy Yanshan University No. 438 West Hebei Avenue Hebei Province Qinhuangdao066004 China BAIC Motor Co. Ltd BAIC Motor Industry R&D Base 99 Shuanghe Avenue Renhe Town Shunyi District Beijing China

The Advanced Emergency Braking System (AEBS) is an intelligent vehicle active safety system to avoid certain sorts of collisions. Recent researches on AEBS emphasized radar, lasers and video camera technologies mostly, also controller developments were studied from Vehicle to Vehicle (V2V) to Vehicle to Pedestrian(V2P) and other aspects with different scenarios, aiming to enhance the active safety of the vehicle. However, most of the current systems focus little on braking performance of AEBS, especially for EV with distributed drive system, like in-wheel motors. In this paper, A 15 Degree of Freedom (DOF) distributed drive Electric Vehicle (EV) model was created and an Anti-slip Controller of AEBS based on the logic threshold method was built. To validate this control strategy, a co-simulation platform between Simulink and AMESim was established and vehicle braking dynamic of four in-wheel motor drive EV was evaluated. Results display that the designed controller not only enhanced the braking performance of AEBS under sudden braking on slippery surface condition, but also meet the requirement of UNECE braking regulation which has practical meanings in boosting active safety of a four in-wheel motor drive EV and development of industrialization. © Published under licence by IOP Publishing Ltd.

关键词： MATLAB

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Harnessing Bio-Inspired Optimization and Swarm Intelligence for Energy-Aware TinyML in IoT

Harnessing Bio-Inspired Optimization and Swarm Intelligence ...

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international conference on Inventive Computation technologies (ICICT)

作者： P. Kalyanakumar S. Srinivasa Pandian S. Boopalan D. Kani Jesintha R. Santhana Krishnan A. Essaki Muthu Department of Information Technology Velammal College of Engineering and Technology Madurai India Department of Computer Science and Engineering SCAD College of Engineering and Technology Cheranmahadevi India Department of Electronics and Communication Engineering SCAD College of Engineering and Technology Cheranmahadevi India

ISBN: (数字)9798350359299

ISBN: (纸本)9798350359305

This research investigates the integration of bio-inspired optimization and swarm intelligence principles with TinyML for the development of energy-aware Internet of Things (IoT) devices. A novel model algorithm, termed "BioSwarmML," is introduced and evaluated against existing algorithms through comprehensive simulation analyses employing suitable metrics. The proposed framework aims to enhance energy efficiency in IoT applications by leveraging the collective intelligence derived from bio-inspired optimization and swarm behaviors. The "BioSwarmML" algorithm is designed to draw inspiration from natural processes, incorporating bio-inspired optimization techniques such as genetic algorithms, simulated annealing, and evolutionary strategies. Concurrently, swarm intelligence principles are integrated to emulate decentralized and self-organizing behaviors observed in biological systems. This amalgamation aims to optimize the energy consumption of TinyML models on IoT devices, facilitating sustainable and adaptive learning processes. simulation analyses involve a comparative study with established algorithms, evaluating BioSwarmML based on metrics such as energy consumption, accuracy, and latency. The results demonstrate the efficacy of the proposed algorithm in achieving superior energy efficiency while maintaining competitive performance in terms of accuracy and responsiveness. The comparison sheds light on the advantages of BioSwarmML in energy-aware TinyML applications, showcasing its potential for widespread adoption in IoT ecosystems. This research contributes to the advancement of energy-efficient IoT systems by introducing a novel algorithmic paradigm that aligns with international journal standards. The proposed "BioSwarmML" model showcases a promising avenue for enhancing sustainability in TinyML-driven IoT applications, offering a valuable addition to the existing body of knowledge in the field.

关键词： Energy consumption Biological system modeling Computational modeling Ecosystems Energy efficiency Internet of Things Particle swarm optimization

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AR/VR Digital Twin for simulation and Data Collection of Robotic Environments

AR/VR Digital Twin for Simulation and Data Collection of Rob...

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IEEE international conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： João G. Martins Karle Nutonen Paulo Costa Vladimir Kuts Tauno Otto Armando Sousa Marcelo R. Petry CRIIS - Centre for Robotics in Industry and Intelligent Systems INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Faculty of Engineering University of Porto (FEUP) Porto Portugal ViruTech - Virumaa innovation center of digitalization and green technologies Taltech Virumaa College Kohtla-Jarve Estonia Department of Mechanical and Indusrial Taltech Tallinn Estonia

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

Digital twins enable real-time modeling, simulation, and monitoring of complex systems, driving advancements in automation, robotics, and industrial applications. This study presents a large-scale digital twin-testing facility for evaluating mobile robots and pilot robotic systems in a research laboratory environment. The platform integrates high-fidelity physical and environmental models, providing a controlled yet dynamic setting for analyzing robotic behavior. A key feature of the system is its comprehensive data collection framework, capturing critical parameters such as position, orientation, and velocity, which can be leveraged for machine learning, performance optimization, and decision-making. The facility also supports the simulation of discrete operational systems, using predictive modeling to bridge informational gaps when real-time data updates are unavailable. The digital twin was validated through a matrix manufacturing system simulation, with an Augmented Reality (AR) interface on the HoloLens 2 to overlay digital information onto mobile platform controllers, enhancing situational awareness. The main contributions include a digital twin framework for deploying data-driven robotic systems and three key AR/VR integration optimization methods. Demonstrated in a laboratory setting, the system is a versatile tool for research and industrial applications, fostering insights into robotic automation and digital twin scalability while reducing costs and risks associated with real-world testing.

关键词： Service robots Navigation Metaverse Databases Scalability Digital representation Real-time systems Digital twins Mobile robots Robots

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Toward Lifetime Learning-based Predictive 24

Toward Lifetime Learning-based Predictive

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24th IEEE international conference on Computer Supported Cooperative Work in Design (IEEE CSCWD)

作者： Yang, Chunsheng Guo, Yuhong Yang, Yubin Yang, Xiaohua Natl Res Council Canada Ottawa ON Canada Carleton Univ Ottawa ON Canada Nanjing Univ State Key Lab Novel Software Technol Nanjing Peoples R China Nanchang Univ Nanchang Jiangxi Peoples R China

ISBN: (纸本)9781728165974

modeling system behavior plays a vital role in controlling systems and in monitoring systems health. Recently the machine learning-enabled modeling technology has become a powerful technique and tool for developing models for explaining, predicting, and describing system behaviors. In particular, the machine learning-enabled predictive modeling methods have been widely applied to develop the data-driven models from the "big" data in different applications such as system prognostics, system control, and system health management. Over last decade, we have worked on a research program, machine learning-enabled modeling technologies, focusing on the application of machine learning to real-world problems such as control, prognostics, and fault diagnostics. The developed modeling methodologies can help building the machine lerning0vased models form large-sized operational historic data for various domain applications. This paper attempts to summarize the challenge issues facing us and the solutions for addressing these issues. On the same time, the paper also discusses some remaining challenges and future directions.

关键词： machine learning predictive modeling transfer learning lifetime learning PHM

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Reversing Voltage Topology for Multi-Level Inverters: simulation and Experimental Validation

Reversing Voltage Topology for Multi-Level Inverters: Simula...

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Sustainable Energy technologies and Computational Intelligence (SETCOM), international conference on

作者： Gaurangkumar C. Patel Ami T Patel Nikunj J. Dhimmar Electrical Department S. S. Agrawal Institute of Engineering and Technology Navsari Gujarat India Electrical Department Government Engineering College Bharuch Bharuch Gujarat India

ISBN: (数字)9798331520540

ISBN: (纸本)9798331520557

In recent years, using multi-level inverters for high power, high voltage applications has grown in popularity. Their performance is far better than standard two level inverters in terms of less harmonic distortion, decreased electromagnetic interference, and higher dc link *** might have certain drawbacks, such as a higher component count, a more difficult PWM control scheme, and a floating neutral point. This work introduces a novel architecture called Reversing Voltage (RV) to enhance the multilevel performance and compared it for different levels (up to eleven level) to show reduced % THD in output voltage at higher level. This design uses less carrier signals and switches than standard inverters, especially at higher levels. It also eliminates the need for voltage balancing. Phase disposition SPWM technology is the basis for both the topology and control mechanism. Lastly, comparisons are made between the experimental (Laboratory Proto-type Model for Single Phase Five-Level Inverter Using Reversing Voltage Topology) and simulation findings at various voltage levels. The outcomes of the experiment closely resemble those of the simulation.

关键词： Induction motor drives High-voltage techniques Computer architecture Pulse width modulation Multilevel inverters Topology Voltage control Integrated circuit reliability Integrated circuit modeling Standards

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Combat simulation to Support the Conceptual Design of Equipment for the Soldier System 10

Combat Simulation to Support the Conceptual Design of Equipm...

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10th international conference on simulation and modeling methodologies, technologies and applications (SIMULTECH)

作者： Mittal, Vikram Webb, Graham Steiner, Jackson Shriver, Luke Butcher, Sierra US Mil Acad Dept Syst Engn West Point NY 10996 USA Army Cyber Inst West Point NY USA

ISBN: (纸本)9789897584442

simulation will play an increasingly important role in designing future equipment for soldiers. The complex operational environment necessitates that the soldier be treated as a system. A soldier system can be defined as a soldier using equipment to complete a mission. Though it is often difficult to capture the mission aspect of the system, constructive combat simulation provides a technique for testing out new equipment on a soldier early in the system design lifecycle. Though combat simulations have historically been used primarily for training purposes, they can be readily modified for analysis of new military capabilities. Additionally, these simulations can be modified to reflect the changes in physical and cognitive load associated with these new capabilities. This paper outlines a methodology for using combat simulation to perform analysis of new capabilities for the soldier system. A case study is then presented to perform a trade space analysis on different tactical-cyber capabilities given to dismounted soldiers. Using the Infantry Warrior simulation (IWARS), the case study quantified changes in soldier survivability and lethality with the addition of new technologies.

关键词： Combat Modelling Cyber Capabilities Soldier Systems

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Global Sensitivity Analysis for Bridge Crane System by Surrogate modeling 6th

Global Sensitivity Analysis for Bridge Crane System by Surro...

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6th international conference on Geotechnics, Civil Engineering and Structures (CIGOS)

作者： Van-Hai Trinh Viet-Tan Nguyen Khac-Quang Pham Le Quy Don Tech Univ LQDTU Hanoi 100000 Vietnam

ISBN: (纸本)9789811671609;9789811671593

As key equipment for lifting and transporting duties, cranes are used in various industrial fields in modern productions. Thus, the dynamic problem of such crane system is commonly encountered in the design process. This paper presents a Monte Carlo-based global sensitivity analysis of the dynamic model of a bridge crane system using the surrogate model technique. To this regard, physical modeling and differential equation motion of a coupled crane system is first derived using the Lagrange equation. Then, the numerical solution is offered by using the Newmark-beta integral method for characterizing dynamic responses of the crane system involving bridge beam, trolley, and payload. In order to compute Sobol sensitivity indices, the input-output correlation is formulated by a neural network-surrogate model formed from the numerical solutions. Finally, for the considered configuration, the importance levels of input variables with the corresponding estimated values of the first and total order sensitivity functions are demonstrated.

关键词： Overhead crane Dynamic response Global sensitivity Uncertainty Monte Carlo simulation Neural network-based surrogate

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Biometric Identification using Gait Analysis: Methods, Characteristics, and Difficulties

Biometric Identification using Gait Analysis: Methods, Chara...

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Advanced Computing and Emerging technologies (ACET), international conference on

作者： Suravi Roy Sakshi Srivastava Ritwika Acharya Arya Raj Bitan Misra Nilanjan Dey Department of Computer Science and Engineering Techno International New Town Kolkata India

ISBN: (数字)9798350367720

ISBN: (纸本)9798350367737

Gait recognition is a rapidly developing field of study that applies biometrics to identify people by their distinctive walking patterns. Gait recognition primarily performs identification authentication by utilizing the unique postures of each individual. These methods aim to recognize people according to their intrinsic, visible qualities, regardless of their clothing or personal effects. While the topic suggests a long-standing challenge, the majority of solutions developed to tackle it suffer from a number of drawbacks, such as poor feature extraction and low classification rates. Deep learning-based methods, on the other hand, have lately become a powerful toolkit to tackle almost every picture and computer vision-related issue, and they also yield excellent gait identification results. With an emphasis on deep learning methodologies, we hope to highlight their advantages and expose their drawbacks to help researchers make well-informed selections about the many variables to be considered for learning gait identification. Additionally, various case studies on implication of gait recognition using different deep learning models are discussed to provide an overview of the practical applications of this technique.

关键词： Deep learning Legged locomotion Recurrent neural networks Biological system modeling Surveillance Gain measurement Performance analysis Security Gait recognition Sports

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Sensitivity Analysis of an Air Pollution Model with Using Innovative Monte Carlo Methods in Calculating Multidimensional Integrals 10th

Sensitivity Analysis of an Air Pollution Model with Using...

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10th international conference on Numerical Methods and applications, NMA 2022

作者： Ostromsky, Tzvetan Todorov, Venelin Dimov, Ivan Georgieva, Rayna Department of Parallel Algorithms Institute of Information and Communication Technologies Bulgarian Academy of Sciences Acad. G. Bonchev Str. Block 25 A Sofia1113 Bulgaria Department of Information Modeling Institute of Mathematics and Informatics Bulgarian Academy of Sciences Acad. Georgi Bonchev Str. Block 8 Sofia1113 Bulgaria

ISBN: (纸本)9783031324116

Large-scale models are mathematical models with a lot of natural uncertainties in their input data sets and parameters. Sensitivity analysis (SA) is a powerful tool for studying the impact of these uncertainties on the output results and helps to improve the reliability of these models. In this article we present some results of a global sensitivity study of the Unified Danish Eulerian Model (UNI-DEM). A large number of heavy numerical experiments must be carried out in order to collect the necessary data for such comprehensive sensitivity study. One of the largest supercomputers in Europe and the most powerful in Bulgaria, the petascale EuroHPC supercomputer Discoverer is used to perform efficiently this huge amount of computations. One of the most important features of UNI-DEM is its advanced chemical scheme, called Condensed CBM IV, which considers a large number of chemical species and all significant reactions between them. The ozone is one of the most harmful pollutants, that is why it is important for many practical applications to study it precisely. Stochastic methods based on Adaptive approach and Sobol sequences are used for computing the corresponding sensitivity measures. We show by experiments that the stochastic algorithms for calculating the multidimensional integrals under consideration are one of the best stochastic techniques for computing the small in value sensitivity indices. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Sensitivity analysis

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A novel virtual prototyping methodology for timing-accurate simulation of AMS circuits

A novel virtual prototyping methodology for timing-accurate ...

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IEEE international Symposium on Quality Electronic Design

作者： Teo Vallone Hayri Verner Hasou Ernesto Colizzi Sara Vinco Davide Zoni Politecnico di Milano Italy Infineon Technologies Pavia Italy Politecnico di Torino Italy

ISBN: (数字)9798350309270

ISBN: (纸本)9798350309287

Nowadays, analog-mixed-signal (AMS) circuits are at the core of a large variety of devices targeting automotive, medical, communication, and energy applications. Despite their ubiquity, AMS design methodologies are not automated, rely on long manual iterations, and leverage slow SPICE-level simulation as golden standard. Moreover, SPICE simulations cannot help in verifying timing checks on the digital elements of the circuit, thus allowing possible escaped bugs in the final device. In this scenario, virtual prototypes are used to abstract the modeling of the AMS circuit to boost simulation speed, favor design reuse, and allow early evaluation of the design choices at the cost of a reduced accuracy. This paper presents a novel virtual prototyping methodology for AMS circuits. Starting from the netlist of an AMS circuit and the description of the target technology library, the methodology automatically generates the SystemC models for the digital elements, extended with additional timing checks. To deliver the final timing-accurate AMS simulation, the generated SystemC models are then integrated into a co-simulation framework where the analog parts of the circuit are still simulated using SPICE. Experimental results demonstrated the validity of the proposed solution to deliver timing-accurate AMS simulations. The methodology can identify and check five timing violation classes for the digital parts of the circuit that are unchecked at SPICE level.

关键词： Power demand Circuits Prototypes Manuals SPICE Libraries Timing

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