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24th European Conference on Power Electronics and Applications (EPE ECCE Europe)

作者： Bacheti, Gabriel Gaburro Camargo, Renner Sartorio Bueno, Emilio Jose Liserre, Marco Encarnacao, Lucas Frizera Fed Univ Espirito Santo UFES Dept Elect Engn Ave Fernando Ferrari 514 BR-29075910 Vitoria Brazil Fed Inst Espirito Santo IFES Dept Control & Automat Engn Rod ES010 BR-29173087 Serra Brazil Alcala Univ UAH Dept Elect Pl San Diego Madrid 28801 Spain Univ Kiel Chair Power Elect Kaiserstr 2 Kiel Germany

ISBN: (纸本)9789075815399

This work proposes a sectorized optimization with Graph Theory applied in cascaded multilevel transformerless SST. The sectorized optimization can reduce the FCS-MPC combinational explosion due to the multiple cascaded H-bridges cells, while the proposed control is capable to avoid the prohibitive states maintaining the converter controllability and power quality.

关键词： Multi-level converters Model predictive control High voltage power converters SolidState Transformer optimization algorithm

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Enhanced Meta-Heuristic Approach for Echo Suppression in Synthetic Aperture Radar Using Non-Periodic Interrupted Sampling

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TRAITEMENT DU SIGNAL 2025年第2期42卷 1097-1110页

作者： Chukka, Anoosha Battula, Tirumala Krishna Anil Neerukonda Inst Technol & Sci Dept ECE Visakhapatnam 531162 India Jawaharlal Nehru Technol Univ Kakinada Dept ECE Kakinada 533003 India

Echo cancellation is a deception jamming technique designed to nullify the target's echo and prevent its detection by enemy radar. Traditional methods rely on time-domain synchronization, but they struggle to fully suppress echoes when there is an amplitude mismatch. This limitation often leaves the target partially visible in synthetic aperture radar (SAR) images, reducing the effectiveness of the jamming technique. Non-periodic interrupted sampling modulation (NP-ISM) is applied as it produces a continuous jamming strip instead of discrete false targets whereas in Periodic sampling multiple false targets emerge even the real target echo is canceled which makes it easy to be countered by enemy radar. The improved henry gas solubility optimization algorithm (IHGSOA) is applied in the echo cancellation model to optimize the random rectangular envelope pulse train in the NP-ISM which enhances signal cancellation. This significantly reduces the Peak to Average Ratio (PAR), enabling more effective target echo suppression. A polynomial non-linear frequency modulation (PNLFM) is employed to reduce the PAR leading to significant improvement in signal-to-noise ratio (SNR), enabling more effective target echo cancellation. The proposed IHGSOA-based echo cancellation model effectively aligns the cancellation and echo signals through time-delay synchronization, minimizing errors even in the presence of a mismatch. The simulation results show that using the above cancelling system the desired target echo amplitude drops to 50% and 40% of its original target echo, hence the system has a very high cancellation effect. Thus, the effectiveness of the IHGSOA is evaluated by comparing its performance with other conventional algorithms.

关键词： echo cancellation synthetic aperture radar (SAR) non-periodic interrupted sampling modulation improved henry gas solubility optimization algorithm peak to average ratio polynomial non-linear frequency modulation (PNLFM) NLFM

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Optimizing Urban Electric Vehicle Charging Infrastructure Selection: An Approach Integrating GPS Data, Battery Levels, and Energy Availability

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IFAC-PapersOnLine 2024年第13期58卷 392-397页

作者： Meriem Belaid Said El Beid Anas Hatim CISIEV Team Cadi Ayyad University Marrakech 40160 Morocco TIM team Cadi Ayyad University Marrakech 40160 Morocco

This research paper offers a comprehensive exploration of how to enhance the charging infrastructure for Electric Vehicles (EVs) in urban settings. The analysis assesses three hypothetical charging infrastructures in a city, each with generators connected to the national grid and strategically placed AC and DC chargers. The proposed method employs GPS data, EV battery levels, and energy availability across the charging infrastructures. Using an optimization algorithm implemented via the Pandapower Python library, the most appropriate charging infrastructure is identified for individual drivers. The algorithm considers factors such as GPS data and energy availability to suggest the optimal charging station for each EV’s battery level. This pioneering solution aims to streamline the charging process, enhance user experience, and encourage efficient use of urban charging infrastructure for electric vehicles.

关键词： Electric Vehicle (EV) Charging Infrastructure Urban Environments AC Chargers DC Chargers GPS Data Battery Levels optimization algorithm Pandapower Python Library Sustainable Transportation User Experience

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Optimal Design of Interior Permanent Magnet Synchronous Motor for Eco-friendly ship using Hybrid ABC-SVM algorithm 20

Optimal Design of Interior Permanent Magnet Synchronous Moto...

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20th Biennial IEEE Conference on Electromagnetic Field Computation (CEFC)

作者： Park, Jong-Woon Lim, Dong-Kuk Univ Ulsan Dept Elect Elect & Comp Engn Ulsan South Korea

ISBN: (数字)9781665468336

ISBN: (纸本)9781665468336

This paper investigates the best design of IPMSM for eco-friendly ships using a hybrid ABC-SVM algorithm (HAS). HAS is a multimodal optimization method capable of exploring several optimal solutions. HAS enhances navigation capability by combining the existing Artificial Bee Colony algorithm (ABC) with Support Vector Machine (SVM). In addition, hybridization with Simplex enables accurate and quick convergence on neighbor optimization at pointers discovered in ABC. In two test functions, the higher performance of the proposed algorithm is tested with conventional ABC, and the algorithm is applied to the optimal design of the IPMSM for the eco-friendly ship.

关键词： Electromagnetic analysis Eco-friendly ship Motor optimization optimization algorithm Permanent magnet motors

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Visual scripting approach for structural safety assessment of masonry walls

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CURVED AND LAYERED STRUCTURES 2025年第1期12卷

作者： Lasorella, Mariaceleste Percolla, Giulia Pisano, Aurora Angela Fuschi, Paolo Univ Mediterranea Reggio Calabria Dept dAeD Via Univ 25 I-89124 Reggio Di Calabria Italy

A visual scripting approach for limit analysis of masonry walls subjected to out-of-plane loads is proposed. To this aim, within a visual scripting framework, an interactive CAD representation of the structure and of the acting loads, boundary conditions, and restraints is coupled with an optimization algorithm to calculate the collapse load multiplier and visualize the related predicted collapse mechanism. The proposed approach can be useful for practical purposes, indeed it allows us to quickly identify the key factors that influence the structural response and, through the tuning of some input data, can furnish some hints for design purposes. The effectiveness of the promoted tool is verified by application to eight well-known benchmark cases.

关键词： visual scripting optimization algorithm Masonry macro-blocks limit analysis

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Aeroacoustic and aerodynamic optimization of propeller blades

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Chinese Journal of Aeronautics 2020年第3期33卷 826-839页

作者： Peixun YU Jiahui PENG Junqiang BAI Xiao HAN Xiang SONG School of Aeronautics Northwestern Polytechnical UniversityXi’an 710072China Unmanned System Research Institute Northwestern Polytechnical UniversityXi’an 710072China

It is of great significance to develop a high-efficiency and low-noise propeller optimization method for new-generation propeller aircraft *** with free form deformation method,dynamic mesh interpolation technology,optimization algorithm,surrogate model,aerodynamic calculation and aeroacoustic prediction model module,the integrated aerodynamic and aeroacoustic design method of propeller is *** optimization design for the six-blade propeller is carried *** non-reduction in efficiency,thrust coefficient and the minimum of aerodynamic noise is treated as the optimization design *** spatial vorticity distribution of the propeller before and after the design is also analyzed by using unsteady computational fluid dynamics *** results show that the optimized propeller can effectively reduce the aerodynamic noise *** maximum total sound pressure level can be reduced by 5 dB without reducing its aerodynamic *** developed method has good application potential in low-noise optimization design of propeller and other rotating machinery.

关键词： Aeroacoustic Aerodynamic Dynamic mesh interpolation technology Free form deformation method optimization algorithm Propeller Sound pressure level Surrogate model

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Comparison of Electrified Aircraft Propulsion Drive Systems with Different Electric Motor Topologies

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JOURNAL OF PROPULSION AND POWER 2021年第5期37卷 733-747页

作者： Sirimanna, Samith Thanatheepan, Balachandran Lee, Dongsu Agrawal, Shivang Yu, Yangxue Wang, Yuyao Anderson, Aaron Banerjee, Arijit Haran, Kiruba Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA Univ Illinois Urbana IL 61801 USA Hitet LLC Champaign IL USA

Y Electric aircraft propulsion is a growing research area that looks into achieving propulsion through fully electric or hybrid electric systems while achieving low CO2 emissions. The system-level benefit gained by different electric and hybrid-electric propulsion schemes depends heavily on the performance of system-level components in the electric drive-train, including the electric motor, gear box, motor drive, protection systems, as well as the thermal management system. When comparing motor topologies, it is important to understand performance measures such as efficiency and specific power on a drive system level. Many different motor types have been qualitatively compared and can be found in the literature. To guide appropriate component selection, this paper presents details of a quantitative study for a given electric propulsion drive system. A Pareto optimal front for a notional drive system of a 1.5 MW electrical propulsor with different motor types is generated and compared. An optimization algorithm coupled with an electromagnetic finite element analysis software tool was used to optimize the induction motor, switched reluctance motor, wound rotor synchronous motor, permanent magnet synchronous motor (PMSM), slotless PMSM, permanent-magnet-assisted synchronous reluctance motor, brushless DC motor, and brushless doubly fed reluctance motor types for efficiency and specific power. Overall advantages considering system-level efficiency, specific power, and a few other key metrics such as origin of losses, cooling complexity, manufacturing tolerance, and fault tolerance are discussed. This gives an indication of the relative performance of different motor types and confirms the overall advantage of PM motor topologies in aircraft propulsion.

关键词： Aircraft Propulsion System Switched Reluctance Motor Finite Element Analysis Electric Propulsion optimization algorithm Thermal Management System Fault Tolerance Software Tool Hybrid Electric Aircraft Torque Ripple

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Brain tumor grade identification using deep Elman neural network with adaptive fuzzy clustering-based segmentation approach

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MULTIMEDIA TOOLS AND APPLICATIONS 2021年第16期80卷 25139-25169页

作者： Sankaran, K. Sakthidasan Thangapandian, M. Vasudevan, N. Hindustan Inst Technol & Sci Dept Elect & Commun Engn Chennai Tamil Nadu India

A brain tumor is a collection of anomalous evolution of harmful and unnecessary nerve cells in the brain. For advanced treatment, it is essential to categorize the tumors from the MRI (magnetic resonance imaging). In this paper, develop the adaptive fuzzy Tsallis entropy (FTE) clustering with the improved cuckoo search optimization (ICS) procedure, and the effective feature selection mechanism is proposed in this paper. Initially, the input MRI is pre-processed using the anisotropic diffusion filter and non-parametric region-based techniques to eliminate noise removal and skull stripping. After that, the tumor regions are segmented using the adaptive FTE clustering method with the ICS algorithm. The robust features are attained using the first-order statistical, discrete wavelet transform (DWT), the histogram of oriented gradients (HOG), and intensity histogram. After that, the set of optimal features are selected from the mined features using the black widow optimization (BWO) algorithm in the feature selection (FS) process. Finally, a deep Elman neural network (DENN) structure is utilized to categorize the grade of brain tumor. The suggested approach is simulated using the Matlab environment using the BRATS 2012, BRATS 2019 and BRATS 2020 datasets. The different performances are evaluated, and it is related to other existing classifiers and other approaches. The simulation results verified that the accuracy of developed approach is 99.8% for BRATS 2012, 98.7% for BRATS 2019 and 98% for BRATS 2020 as compared to other classifiers and other existing approaches.

关键词： Segmentation Feature selection Brain tumor identification MRI Classifiers optimization algorithm Classification

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Landing Gear Mechanical Network Synthesis for Improving Comfort at Landing Considering Aircraft Flexibility

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JOURNAL OF AIRCRAFT 2021年第6期58卷 1242-1253页

作者： Stachiw, Terrin Khouli, Fidel Langlois, Robert G. Afagh, Fred F. Carleton Univ Mech & Aerosp Engn Ottawa ON K1S 5B6 Canada

The landing impact that occurs during aircraft touchdown results in the development of significant loads and accelerations within the airframe. Accurate knowledge of the landing loads is necessary not only for predicting the resulting stresses for design of the airframe, but also for designing strategies to mitigate the vibratory loads and improve the ride quality. Perceived passenger comfort is dependent both on the magnitude of the acceleration experienced by the passengers and on the frequency content of the vibrations. Using a flexible airframe model to better capture the loading regime and frequency response at landing impact, this study optimizes various single-port (two-terminal) passive mechanical networks that consist of an arrangement of springs, dampers, and inerters to minimize passenger discomfort and peak forces applied to the aircraft. The performance is compared with a baseline oleo-pneumatic shock absorber. First, the candidate layouts are optimized, and then the observations from this exercise are used to synthesize a mechanical network with a desired frequency response. All considered mechanical networks demonstrated the ability to control the frequency content of the input loading, thus resulting in a reduction in accelerations and an improvement in all comfort parameters used in this study over the oleo-pneumatic baseline.

关键词： Model Aircraft Aircraft Structures Frequency Response Functions Maximum Landing Weight Aircraft Operations Finite Element Modeling Federal Aviation Regulation optimization algorithm Damping Coefficient Recurrent Neural Network

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Review on optimization algorithms for plug in hybrid electric vehicle 19

Review on optimization algorithms for plug in hybrid electri...

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19th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)

作者： Ben Ali, Marwa Elloumi, Mariem Boukettaya, Ghada Univ Sfax Natl Sch Engn Dept Elect Engn Sfax 3038 Tunisia

ISBN: (纸本)9781728112923

In this study, Vehicle to grid (V2G) application is considered as an important solution to minimize the CO2 emission, as well as its ability to involve the utilization of renewable energy and recovers the limitation of fossil energy. In this context, the plug in hybrid electric vehicle (PHEV) have attracted the attention of researchers and industries due to its various advantages especially it's utilization as a good interface on the V2G application all over the world. This paper includes an introduction of various vehicle architecture and the formulation of total cost of ownership (TCO) presented during the owning period of the vehicle. We are also interested on the different approaches and algorithms used for optimal design of PHEV in literature to optimize the TCO.

关键词： V2G application Plug in hybrid electric vehicle optimization algorithm Total cost of ownership

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