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Machine Learning-driven optimization of MTPA in IPMSM Drives for Electric Vehicles

Machine Learning-Driven Optimization of MTPA in IPMSM Drives...

引用

Aerospace Electrical Engineering and Informatics (ICAAEEI), International conference of Adisutjipto on

作者： Ravi Kumar Jujjuvarapu Amaleswari Rajulapati Subject Matter Expert Faculty of Engineering Beacon Red EDGE Group Abu Dhabi United Arab Emirates Electrical and Electronics Engineering Department NS Raju Institute of Technology Vishakapatnam India

ISBN: (数字)9798331507930

ISBN: (纸本)9798331507947

This research presented in this paper outlines a pioneering optimization framework concentrated on perfecting the Maximum Torque per Ampere (MTPA) control mechanism in Interior Permanent Magnet Synchronous Motor (IPMSM) drives for the realm of electric vehicles (EVs). Through the integration of supervised learning methodologies for parameter forecasting alongside reinforcement learning (RL) techniques for real-time adaptive regulation, the proposed methodology dynamically enhances torque output and energy efficiency across fluctuating driving conditions. The framework employs a Deep Q-Network (DQN) agent to perpetually recalibrate the direct-axis and quadrature-axis currents, establishing an equilibrium between torque production and energy expenditure in a real-time context. The simulation data reveals a potential rise of up to 15% in torque efficiency, a 10% lessening in energy expended, and a 15% prolongation in battery life when juxtaposed with traditional fixed-parameter approaches. This technique surpasses traditional motor control methodologies by prioritizing real-time adaptability and resilience, thus presenting itself as a viable solution for the forthcoming generation of EVs. Subsequent research will investigate the practical application of the proposed framework in real-world scenarios and its adaptability to more intricate operating conditions.

关键词： Motor drives Torque Supervised learning Reinforcement learning Electric vehicles Permanent magnet motors Real-time systems Batteries optimization Load modeling

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Evaluation of Participants' Reaction and Learning in a Taught Analytics and Modelling Academy Program in UK's National Health Service 10

Evaluation of Participants' Reaction and Learning in a Taugh...

引用

10th IEEE International conference on Healthcare Informatics (IEEE ICHI)

作者： Gartner, Daniel Spernaes, Izabela England, Tracey J. Behrens, Doris A. Buchanan, Joanne Harper, Paul R. Cardiff Univ Sch Math Cardiff Wales Natl Hlth Serv Cardiff Wales Univ Southampton Sch Heath Sci Southampton Hants England Danube Univ Krems Dept Econ & Hlth Krems Austria Natl Hlth Serv Math Modelling Unit Aneurin Bevan Univ Hlth Board Newport Gwent Wales

ISBN: (数字)9781665468459

ISBN: (纸本)9781665468459

Recent research has highlighted the need to invest in the development of healthcare analytics capability. However, the contents of such programs and how they should be delivered to maximize the learning outcome are unclear. In this paper, we provide insights into the learning within the first two cohorts of modelling fellows successfully trained in an analytics and modelling academy run within the National Health Service (NHS) Wales, U.K. The participants followed a taught healthcare analytics and mathematical modelling program tailored for senior staff members including managers and clinicians. We build our learning evaluation framework on Kirkpatrick's training evaluation model and participants filled in questionnaires with respect to their level 1 (reaction) and level 2 (learning) experience after each module. In addition, we asked the participants about their self-assessments during three time points in the program. The qualitative feedback results revealed that the participants appreciate the learning and reflect where they could use the new developed skills in practice. They also provided useful suggestions for improving the program. The participants' aggregated quantitative self-assessments show a statistically significant increase in competence. In conclusion, this may lead to a behavior change in applying the methods on the job (level 3) and, ultimately, improve level 4 outcomes through analytics-driven healthcare improvement.

关键词： computer and information science education queuing theory simulation modeling methodologies modeling and prediction healthcare optimization of service systems

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Edge Computing Resource Optimal Dispatch in Distribution Network Considering the Power Tasks Uncertainty

Edge Computing Resource Optimal Dispatch in Distribution Net...

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Energy, Power and Electrical Technology (ICEPET), International conference on

作者： Tiantian Cai Junjian Chen Junye Li Xuran Liang Xiaohua Li Zexiang Cai Ming Hu Bin Yang Technology R&D Center China Southern Power Grid Digital Power Grid Research Institute Co. Ltd. Guangzhou China School of Electric Power Engineering South China University of Technology Guangzhou China

ISBN: (数字)9798350352658

ISBN: (纸本)9798350352665

With the increasing penetration rate of new energy in the power grid, the tasks scenarios faced by the power system are becoming increasingly complex. This complexity leads to the spatiotemporal uncertainty about resource requirements of terminal task for edge computing. Traditional resource scheduling schemes are configured with constant values or over-provisioned in each power business scenario, resulting in low resource utilization. A data-driven model to optimize scheduling resources, which can be for edge computing terminals in distribution network, is proposed to meet the uncertain resource requirements. Firstly, a power tasks resource demand model considering source-load uncertainty is established, and the boundary conditions of adjustable resources are established by utilizing the adjustability of power tasks with different delay and priority requirements. Secondly, considering the multiple costs consumed in the process of power tasks scheduling, a two-stage optimization model is established with the comprehensive computing resource balance and operation cost as the objective function. Finally, the simulation results show that the proposed model has a positive effect on improving the balance and economy of distribution network edge computing resources compared with the traditional optimization model.

关键词： Uncertainty Costs Processor scheduling Computational modeling optimization models Distribution networks Power grids

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User-Centered Configuration of Soft Hip Flexion Exosuit Designs to Assist Individuals with Multiple Sclerosis Through Simulated Human-in-the-Loop optimization

User-Centered Configuration of Soft Hip Flexion Exosuit Desi...

引用

IEEE International conference on Rehabilitation Robotics (ICORR)

作者： Ross M. Neuman Nicholas P. Fey Walker Department of Mechanical Engineering University of Texas at Austin Austin TX USA

Soft exosuits hold promise as assistive technology for people with gait deficits owing to a variety of causes. A key aspect of providing useful assistance is to keep the human user at the center of all considerations made in the design, configuration, and prescribed use of an assistive device. This work details a method for informing the configuration of a soft hip flexion exosuit by 1) modeling the user's shape and movements in order to simulate the mechanical interaction of the exosuit and user, 2) incorporating the mechanical effects of the exosuit into a muscle-driven musculoskeletal gait simulation, and 3) using the results of these simulations to define a cost function that is minimized via Bayesian optimization. This process is carried out for models of four different people with multiple sclerosis, and the final optimized configurations for each subject are compared. For all users, the estimated metabolic cost of transport was reduced below baseline, no-device levels. This work represents a step toward more individualized, user-centric modeling of assistive devices, and demonstrates a system for informing the physical configuration of an exosuit on a case-by-case basis using real patient data.

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43rd IBIMA conference on Artificial intelligence and Machine Learning, IBIMA-AI 2024

43rd IBIMA Conference on Artificial intelligence and Machine...

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43rd IBIMA conference on Artificial intelligence and Machine Learning, IBIMA-AI 2024

ISBN: (纸本)9783031774928

The proceedings contain 62 papers. The special focus in this conference is on Artificial intelligence and Machine Learning. The topics include: Comprehensive Analysis of Football Player Performance with WorldfootballR: Data Insights and Key Variables;Decision Making Process for a Sustainable Horticulture Using AI;drug Delivery System – The Construction and Use of the Graphical Interface in modeling the Controlled Release of Drugs in the Human Body;Enabling German SMEs and Crafts Through Data-driven Innovation: Developing a Scoring Model and Chronological Framework for Enhanced Decision-Makin;Exploring the Impact of AI-driven Gamification on Visitor Engagement in Museums: A Critical Review;framework for Automating Bank Transactions and Invoice Mapping Using Multi-criteria optimization and Neural Networks;measurements of Clothing Circumference Using Vision Methods;mechatronic Mannequin as A Way to Reduce the Number of Returns in Fashion E-Commerce;ontological modeling of the Financial Intermediation Models for Creating a System of Texts’ Semantic Analysis;optimizing Delivery Routes with Spatially Distributed Orders;review of Artificial Intelligence Models for Constructing a Sales Forecasting Module to Enhance Decision-Making;Stock Price Prediction Using Sentiment Analysis and LSTM Networks;unveiling Online Shopping Quality: Taxonomy-Based Multi-label Classification of Shopping App Reviews;unveiling the Dynamics in Shopping Behaviors: A Review;control of Technical Parameters of Industrial Products Through Machine Vision;automatic Coffee Roasting Process Assistance System Based on Fuzzy Logic Techniques;a simulation Study on the Influence of Prioritized Multicast Connections on Traffic Effectiveness Network Nodes;Advantages of Introducing the DVB-T2 Standard in Terrestrial Television;consensus Mechanisms in Blockchain Networks;Self-optimizing SD-WAN.

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43rd IBIMA conference on Artificial intelligence and Machine Learning, IBIMA-AI 2024

43rd IBIMA Conference on Artificial intelligence and Machine...

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43rd IBIMA conference on Artificial intelligence and Machine Learning, IBIMA-AI 2024

ISBN: (纸本)9783031790850

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Bayesian Constrained optimization of IEEE 802.11 VANET for Safety Applications

Bayesian Constrained Optimization of IEEE 802.11 VANET for S...

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International conference on Advanced Communication Technology (ICACT)

作者： Shengli Ding Xiaomin Ma School of Engineering Oral Roberts University Tulsa OK USA

IEEE 801.11p/bd based Vehicular Ad Hoc Networks (VANETs) have been introduced to improve road safety that involves message broadcasts with low transmission latency and high reliability. Different safety-critical applications of VANETs have different quality of service (QoS) requirements under dynamic vehicular environments. A set of dynamically adaptive parameters for the communication networks is essential to obtain the best channel efficacy constrained on that the QoS requirements are satisfied. However, the complexity and high computation consumption of simulation models for safety applications make direct parameter optimization inaccessible. This paper proposes a real-time optimization scheme for VANET safety applications based on a Bayesian constrained optimization algorithm. The scheme consists of a Bayesian optimization algorithm and an analytical model for IEEE 802.11 VANET channel access. The Bayesian optimization generates surrogate functions with lower computational costs based on the sampling points obtained from the analytical model or measurement observations, incorporates QoS requirements as the optimization constraints, and iterates to find the optimal parameters for the best channel usage. Experiments results on Python demonstrate that compared with other non-gradient optimization algorithms, Bayesian optimization can converge to the optimal parameters solutions for IEEE 802.11 driven VANETs efficiently and accurately.

关键词： Analytical models Computational modeling Vehicular ad hoc networks Quality of service Real-time systems Bayes methods Safety

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simulation and Performance Analysis of Electric Vehicle

Simulation and Performance Analysis of Electric Vehicle

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IEEE International conference on Intelligent Techniques in Control, optimization and Signal Processing (INCOS)

作者： Jean Dickson D Devaraj Departmnt of Electrical and Electronics Engineering Kalasalingam Academy of Research and Education Krishnankoil Tamilnadu India Department of Electrical and Electronics Engineering Kalasalingam Academy of Research and Education Krishnankoil Tamilnadu

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361193

Reducing greenhouse gas emissions and pollution in our environment can be achieved with electric automobiles. Electric Vehicle is highly required to replace the impact of IC engines. The goals include enhancing fuel efficiency, cutting emissions, guaranteeing drivability, and preserving the energy storage system's longevity and current state of charge while taking constraints into account. Power train that is driven by fuel cells, batteries, and super capacitors can offer an economical transportation solution. An effective Energy Management System (EMS) is highly required to distribute power across the power train's components by choosing the right operating modes. This article has discussed the electric vehicle's modeling. An optimized model has been created by taking into account real key parameters. This study compares the actual speed of the vehicle with the input drive speed to determine the optimal performance of an electric car. The initial and final charge of the battery is used to compare the energy consumption value of the electric vehicle. Examined has been the impact of many characteristics on the energy consumption and performance of vehicles.

关键词： Energy consumption System performance Fuel cells Transportation Supercapacitors Electric vehicles Stability analysis

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An Optimal Technique for Computation-intensive Task Allocation at Virtual Machines

An Optimal Technique for Computation-intensive Task Allocati...

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International conference on Electrical, Computer and Communication Engineering (ECCE)

作者： Akil Uddin Chowdhury Md Sazzad Hossen M. Ishtiaque A. Zahed School of Science Engineering and Technology East Delta University Chattogram Bangladesh

Currently, the world is moving towards data-driven cloud-based services for diverse applications. In such applications, the user is more willing to request space and computational resources from a virtual machine (VM) rather than investing in building more costly and space-consuming physical machines. This ever-increasing demand for VMs introduces a growing need for optimal task allocations. The goal of this study is to develop a model to allocate user requests for tasks into the least possible number of available VMs. The problem is designed as an integer linear programming (ILP) optimization problem. To solve the problem in a practical time span, a heuristic algorithm is also designed. The simulation results show that the heuristic approach achieves a near-optimal solution for task allocation and eventually leads to reduced setup and operational costs for the service providers.

关键词： Cloud computing Costs Heuristic algorithms Computational modeling simulation Virtual machining Resource management

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Slip modeling and simulation of Spiral Zipper Friction-driven Prismatic Actuator

Slip Modeling and Simulation of Spiral Zipper Friction-Drive...

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IEEE/RSJ International conference on Intelligent Robots and Systems (IROS)

作者： Lee, Seohyeon Ahn, Sahoon Carroll, Devin Yim, Mark Seo, TaeWon Hanyang Univ Dept Mech Convergence Engn Seoul 04763 South Korea Univ Penn Dept Mech Engn & Appl Mech Philadelphia PA 19146 USA

ISBN: (纸本)9781665417143

In this study, based on an analysis of experimental results, we propose a method for slip modeling of Spiral Zipper. The Spiral Zipper is a prismatic actuator that extracts a length-changeable cylindrical tube from a flexible ABS band. The band tube is driven by a friction wheel;the slip results due to the lack of synchronization between the motion of the band and that of the friction wheel. Through experiments, we verify that the flexibility of the band causes an impact force between the band and the friction wheel. Additionally, we verify that the tube extraction process causes resistance, which contributes to the increase in the relative angular velocity. Considering the factors mentioned above, we develop a slip model by employing different numbers of contact patches that express the flexibility of the band. Subsequently, we validate the model's performance through simulations. In addition, we propose a coefficients standardization method for obtaining similar results with different number of contact patches We expect that this study will be a basis for design optimization and control system development of the Spiral Zipper.

关键词： Damping Actuators Spirals Friction Force Wheels Control systems

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