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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Bose, Anubhav Bali, Arjit Haran, Kiruba Stillwell, Andrew University of Illinois Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL United States

ISBN: (纸本)9798350376067

Slotless machines have been shown to have exceptional power density and suitability for aerospace propulsion applications. Their low inductance places specific considerations on the drive requirements and design. Multilevel interleaved converters have been frequently proposed as a solution, but have not been specifically optimized for this application. This paper proposes an analysis and motor-drive codesign framework to maximize system-level power density and efficiency for these class of drives. Inverter output spectrum estimation is coupled with motor loss analysis to iteratively arrive at the optimal drive design. The proposed co-design and optimization framework shows that multi-level inverter based motor-drives can achieve significantly higher system power density and efficiency than conventional 2-level drives. © 2024 IEEE.

关键词： Permanent magnets

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Advanced Control of SVCs for Improved Voltage Stability and Power Quality in PV-Integrated Power Grids 4

Advanced Control of SVCs for Improved Voltage Stability and ...

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4th International Conference on Embedded and Distributed Systems, EDiS 2024

作者： Saihi, Lakhdar Berbaoui, Brahim Ferroudji, Fateh Adrar Algeria University of Draia Ahemed Adrar Department of Electrical and Computer Engineering Adrar Algeria

ISBN: (纸本)9798331519872

This work proposes the integration of photovoltaic (PV) solar systems into existing power grids, which poses significant technical challenges due to the intermittent nature of solar energy and the resulting fluctuations in power output. These fluctuations can lead to voltage instability, power quality degradation, and overall grid reliability issues. Additionally, non-linear loads introduce harmonics, further complicating power quality. To address these challenges, we propose the use of Static Var Compensators (SVC) to enhance grid stability and power quality. This study focuses on SVCs, which provide fast-acting reactive power compensation to stabilize voltage levels during transient conditions. By integrating advanced control techniques, this paper introduces a novel approach for SVCs using a neural network with PWM control, validated through extensive simulations in the MATLAB/SPS environment. The results demonstrate the efficacy of the proposed system in maintaining voltage stability, reducing harmonics, and improving overall power quality, thereby addressing the complexities of modern power grids with renewable energy integration. © 2024 IEEE.

关键词： Solar power generation

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Electro-Thermal Design Characterization of a High Power SiC based ANPC Inverter for EV / Aerospace Applications

Electro-Thermal Design Characterization of a High Power SiC ...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Deshpande, Ankit Vivek Pool-Mazun, Erick I. Garza-Arias, Enrique Wang, Shaozhe Sandoval, Rolando Malone, Nathan Enjeti, Prasad Felts, Jonathan Texas A&m University Department of Electrical and Computer Engineering College Station United States

ISBN: (纸本)9798350376067

This paper presents a detailed design of a 1000V, 250 kW Silicon Carbide (SiC) based Active Neutral Point Clamped (ANPC) inverter, adhering to the specifications set forth by the Aviation-Class Synergistically Cooled Electric-motors with Integrated Drives (ASCEND) project, an initiative under the Advanced Research Projects Agency-Energy (ARPA-E).The ANPC inverter utilizes a hybrid combination of high and low thermal resistance commercial off-the-shelf (COTS) SiC modules along with a Hybrid PWM strategy.A thermo-electric evaluation of such an all-SiC hybrid ANPC inverter is discussed in detail. The design methodology integrates PLECS electro-thermal simulation and Finite Element Analysis (FEA) using ANSYS SIWave and *** experimental inverter prototype was built in which the SiC modules where cooled by a liquid cooling system. Experimental validation was conducted using a pump-back test arrangement of two single-phase ANPC inverter legs with 15.2kVA apparent power and 13.11 kW of active power being circulated between the converters. This represents the equivalent cruise power per phase for the ASCEND flight ***, a procedure was established to estimate the junction temperature of a COTS SiC module. © 2024 IEEE.

关键词： Cooling systems

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R Age-k: Communication-Efficient Federated Learning Using Age Factor 58

R Age-k: Communication-Efficient Federated Learning Using Ag...

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58th Asilomar Conference on Signals, Systems and computers, ACSSC 2024

作者： Mortaheb, Matin Kaswan, Priyanka Ulukus, Sennur University of Maryland Department of Electrical and Computer Engineering College ParkMD20742 United States

ISBN: (纸本)9798350354058

Federated learning (FL) is a collaborative approach where multiple clients, coordinated by a parameter server (PS), train a unified machine-learning model. The approach, however, suffers from two key challenges: data heterogeneity and communication overhead. Data heterogeneity refers to inconsistencies in model training arising from heterogeneous data at different clients. Communication overhead arises from the large volumes of parameter updates exchanged between the PS and clients. Existing solutions typically address these challenges separately. This paper introduces a new communication-efficient algorithm that uses the age of information metric to simultaneously tackle both limitations of FL. We introduce age vectors at the PS, which keep track of how often the different model parameters are updated from the clients. The PS uses this to selectively request updates for specific gradient indices from each client. Further, the PS employs age vectors to identify clients with statistically similar data and group them into clusters. The PS combines the age vectors of the clustered clients to efficiently coordinate gradient index updates among clients within a cluster. We evaluate our approach using the MNIST and CIFAR10 datasets in highly non-i.i.d. settings. The experimental results show that our proposed method can expedite training, surpassing other communication-efficient strategies in efficiency. © 2024 IEEE.

关键词： Federated learning

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A learning artificial visual system for motion direction detection

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Neural Computing and Applications 2024年第27期36卷 17181-17197页

作者： Chen, Tianqi Kobayashi, Yuki Todo, Yuki Tang, Zheng Faculty of Electrical and Computer Engineering Kanazawa University Kakuma Ishikawa Kanazawa9201162 Japan Department of Intelligence Information Systems University of Toyama Toyama9308555 Japan

Research on the visual system and its development is not only crucial for understanding how we see and interpret the environment from basic visual processing to complex perception but also aids in the development of technologies like virtual reality, augmented reality, and computer vision. In our previous paper, we have proposed a novel biological motion direction detection mechanism. Based on this mechanism, the authors of this paper proposed a learning artificial visual system (AVS) and use it to achieve motion direction detection. The learning AVS consists of two layers: the local visual feature detective neuron layer and the global feature detective neuron layer. For local motion direction detection, we use dendritic neurons to implement local motion direction-detective neurons and use them to extract local motion direction information. Global feature detective neurons are simply implemented by summing the local motion direction-detective neurons in each direction of possible motion. We trained the learning AVS by eliminating unnecessary branches or synapses and keeping only those that are strongly connected to the function of motion direction detection. computer simulations demonstrate that AVS can learn the correct motion direction of objects with different shapes, size and positions. We compare the performance of AVS with support vector machine (SVM) and traditional convolutional neural networks (CNNs)—LeNet-5 and EfficientNet-B0 (EfN)—in motion direction detection and find that our learning AVS has better recognition accuracy, noise immunity and less demands on size of dataset and learning costs. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Neurons

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Doubly Salient Parallel Path Magnetic Motor: A novel doubly salient stator permanent magnet machine

Doubly Salient Parallel Path Magnetic Motor: A novel doubly ...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Salehi, Maryam Manjrekar, Madhav University of North Carolina at Charlotte Department of Electrical and Computer Engineering CharlotteNC United States

ISBN: (纸本)9798350376067

It has been reported that Parallel Path Magnetic Technology (PPMT) enables control of a given magnetic flux level in an electric machine with a lower energy input. This paper presents a novel Doubly Salient Parallel Path Magnetic Motor (DS-PPMM) based on the PPMT principle. The topology and operating principle of the proposed machine are presented. It is shown that the flux linkages and back-EMFs are near-sinusoidal, enabling a three-phase sinusoidal excitation current for motoring operation. It is interesting to note that, these back-EMFs are near-sinusoidal even when the structure is doubly salient and concentrated stator windings are employed. It is shown that the proposed DS-PPMM has low cogging torque, high torque density, and offers nearly identical d-q axis inductances. © 2024 IEEE.

关键词： Stators

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Comprehensive Study of Hydrogen Gas Sensing Performance of an Amorphous In-Al-Zn-O (a-IAZO) Thin Film Synthesized With Pd Nanoparticles

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IEEE Transactions on Electron Devices 2023年第9期70卷 4837-4842页

作者： Niu, Jing-Shiuan Peng, Ren-You Chiu, Chao-Chun Tsai, Jung-Hui Hsu, Wei-Chou Lin, Kun-Wei Liu, Wen-Chau National Cheng-Kung University Institute of Microelectronics Department of Electrical Engineering Tainan70101 Taiwan National Kaohsiung Normal University Department of Electronic Engineering Kaohsiung802 Taiwan Academy of Innovative Semiconductor and Sustainable Manufacturing Institute of Microelectronics Department of Electrical Engineering Tainan70101 Taiwan Chaoyang University of Technology Department of Computer Science and Information Engineering Taichung41349 Taiwan

A novel hydrogen (H2) sensor produced by the combination of an amorphous indium-aluminum-zinc-oxide (a-IAZO) thin film and palladium (Pd) nanoparticles (NPs) is demonstrated and studied herein. Elemental and morphological analyses are employed to investigate the designed device structure. The use of Pd NPs effectively increase the specific surface area, spillover effect, and catalytic activity which substantially enhances the related H2 gas sensing performance. Excellent hydrogen sensing properties, including an ultrahigh sensing response of 9.6 × 105 accompanied by a short recovery time of 10 s under 1% H2/air gas and a lower sensing concentration of 1 ppm H2/air at 250 °C are obtained. Also, the produced device shows excellent selectivity and long-term stability in relation to H2 gas. The studied Pd NP/a-IAZO sensor also reveals merits including a simple device structure and relatively easy production process. © 1963-2012 IEEE.

关键词： Zinc oxide

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Measuring Impact of Lean Manufacturing Tools for Continuous Improvement on Economic Sustainability

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Journal of Systems Science and Systems engineering 2024年第4期33卷 452-474页

作者： Luis Javier Márquez Figueroa Jorge Luis García-Alcaraz Ahmed I.Osman Alfonso Jesús Gil López Yashar Aryanfar Mika Sillanpää Mamdouh El Haj Assad Department of Electrical Engineering and Computer Science Universidad Autónoma de Ciudad JuárezCiudad JuárezChihuahuaMéxico Department of Industrial Engineering and Manufacturing Universidad Autónoma de Ciudad JuárezCiudad JuárezChihuahuaMéxico School of Chemistry and Chemical Engineering Queens UniversityBelfastNorthern IrelandUK Department of Economic and Managerial Sciences University of La RiojaLa RiojaSpain Department of Chemical Engineering University of JohannesburgJohannesburgSouth Africa Department of Sustainable and Renewable Energy Engineering University of SharjahSharjahUAE

Using Lean Manufacturing(LM)tools in production processes is crucial for companies’economic,environmental,and social sustainability *** study shows a structural equation model(SEM)that shows the relationship between LM Tools like Kaizen(KAI),Gemba(GEM),Value Stream Mapping(VSM)and Key Performance Indicator(KPI)with Economic Sustainability(ECS).Seven hypotheses were evaluated with data from 179 responses to a questionnaire about the Mexican maquiladora industry,showing that these variables are *** a 95%confidence level,the model was evaluated using the partial least squares *** findings indicate that the relationships between KAI and GEM and KAI and VSM have the strongest relationship,followed by VSM and ECS;however,VSM has the strongest effect on *** on these findings,it is recommended that managers adopt a continuous improvement(KAI)approach based on working directly on the shop floor(GEM and VSM)to support their decisions regarding economic growth(ECS).

关键词： Lean manufacturing economic sustainability structural equation model quality improvement

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Self-Powered Wearable Devices Integrated with Virtual Reality Simulation Clinics: A Novel Approach to Healthcare Modernization

Self-Powered Wearable Devices Integrated with Virtual Realit...

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2024 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2024

作者： Martinez, Benjamin Velazquez, Adrian Vital, Dieff Department of Electrical and Computer Engineering University of Illinois Chicago ChicagoIL60607 United States

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Optimizing Hysteresis-Based Reinforcement Learning to Improve Collision Avoidance for Self-Driving Vehicles

Optimizing Hysteresis-Based Reinforcement Learning to Improv...

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2024 Systems and Information engineering Design Symposium, SIEDS 2024

作者： Wunderlich, Erwin J. Korman, E. George Washington University Department of Electrical and Computer Engineering WashingtonDC20052 United States

ISBN: (纸本)9798350385144

This paper considers an optimization for fully automated driving systems. We analyze and optimize the performance of two different types of hysteresis-based feedback mechanisms based on noisy sensor inputs. We show how hysteresis can be used in conjunction with Reinforcement Learning (RL) algorithms to make them more resilient to noise. Our results show that by using hysteresis-based RL, we reduce the likelihood of collisions by over 50% in comparison to non-hysteresis-based RL. © 2024 IEEE.

关键词： Hysteresis

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