IEEE Canadian Journal of Electrical and Computer Engineering最新文献_第7页

An Adaptive Fault Diagnosis of Electric Vehicles: An Artificial Intelligence Blended Signal Processing Methodology 电动汽车自适应故障诊断：一种人工智能混合信号处理方法

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2023-06-19 DOI: 10.1109/ICJECE.2023.3264852

Lingli Gong;Anshuman Sharma;Mohammad Abdul Bhuiya;Hilmy Awad;Mohamed Z. Youssef

{"title":"An Adaptive Fault Diagnosis of Electric Vehicles: An Artificial Intelligence Blended Signal Processing Methodology","authors":"Lingli Gong;Anshuman Sharma;Mohammad Abdul Bhuiya;Hilmy Awad;Mohamed Z. Youssef","doi":"10.1109/ICJECE.2023.3264852","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3264852","url":null,"abstract":"This article demonstrates an innovative design of a sensorless technique to diagnose, monitor, and broadcast faults in an electric vehicle’s (EV) propulsion operating conditions. By utilizing the artificial intelligence with a signal processing mixed clustering technique, an onboard health monitoring system (HMS) has been presented. The clustering technique uses a data-mining approach to prevent future failures for predictive maintenance planning, which is novel. For example, the propulsion inverter is equipped with a diagnostic system that uses the proposed algorithm to compare the reference gate-driving signal with the actual output voltage of the voltage source inverter (VSI). This article presents different failure scenarios of the inverter and demonstrates the capability to be applied to other components, such as brakes and motors. To validate the proposed technique, the necessary algorithm calculations, simulation, and laboratory prototype results are provided. The proposed work is proven accurate with fast response in healthy and faulty conditions.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 3","pages":"196-206"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68026228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Time-Distributed Non-Convex Optimized Support Vector Machine for Vehicular Tracking Systems 车辆跟踪系统的时间分布非凸优化支持向量机

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2023-06-08 DOI: 10.1109/ICJECE.2023.3252088

R. Selvakumar;K. Venkatalakshmi

{"title":"Time-Distributed Non-Convex Optimized Support Vector Machine for Vehicular Tracking Systems","authors":"R. Selvakumar;K. Venkatalakshmi","doi":"10.1109/ICJECE.2023.3252088","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3252088","url":null,"abstract":"This article presents a non-convex optimized support vector machine (NCVX OSVM) algorithm for active steering stability of vehicles on a curved road. Initially, we considered a curved road geometrics formulation and designed a time-distributed (TD) model for NCVX OSVM to compute the steering angle 0°–180° at 10 m/s to follow active navigation at the highest curve entry speed. The proposed TD NCVX OSVM is interconnected with three modules. In the first module, formulated NCVX cost functions and Optimized SVM for smooth steering stability. The second module is based on improving faster training time (IFTT) by using the Naive Bayes probabilistic classifier (NBPC). The third module uses an optimized non-convex (NCVX) cost function to reduce the error phenomenon. The performance of these three modules is evaluated by several 100 data points from vehicle onboard sensors. Further, it is pre-processed in the curved road (start, continue, exit) conditions. The decisive of TD-NCVX OSVM design is demonstrated by using experimental learning on FPGA Zynq 7000 processor and programmed with python script. The empirical calculation shows an accuracy of 98.36%. Furthermore, the proposed design predicts an acceptable upper limit for curved steering whenever the vehicle turning speed is greater than 30 mi/h.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 2","pages":"170-178"},"PeriodicalIF":0.0,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68017010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nonlinear Dynamic States’ Estimation and Prediction Using Polynomial Predictive Modeling 基于多项式预测模型的非线性动态状态估计与预测

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2023-06-08 DOI: 10.1109/ICJECE.2023.3260830

Dileep Sivaraman;Songpol Ongwattanakul;Jackrit Suthakorn;Branesh M. Pillai

引用次数: 0

A New Electronic Tunable High-Frequency Meminductor Emulator Based on a Single VDTA 一种基于单VDTA的新型电子可调谐高频Meminductor仿真器

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2023-06-05 DOI: 10.1109/ICJECE.2023.3261886

Pankaj Kumar Sharma;Sadaf Tasneem;Rajeev Kumar Ranjan

引用次数: 0

Relay-Aided D2D MIMO Scheme (RAS) for Achieving Energy Efficiency in Satellite-Air-Ground Integrated Networks (SAGIN) Schéma D2D MIMO assisté par relais (RAS) pour atteindre l’efficacité énergétique dans les réseaux intégrés satellite-air-sol (SAGIN) 实现卫星空地一体化网络（SAGIN）能效的中继辅助 D2D MIMO 方案（RAS）

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2023-06-01 DOI: 10.1109/ICJECE.2023.3254528

Najah Abuali;Massa Ndong;Mohammad Hayajneh

{"title":"Relay-Aided D2D MIMO Scheme (RAS) for Achieving Energy Efficiency in Satellite-Air-Ground Integrated Networks (SAGIN) Schéma D2D MIMO assisté par relais (RAS) pour atteindre l’efficacité énergétique dans les réseaux intégrés satellite-air-sol (SAGIN)","authors":"Najah Abuali;Massa Ndong;Mohammad Hayajneh","doi":"10.1109/ICJECE.2023.3254528","DOIUrl":"10.1109/ICJECE.2023.3254528","url":null,"abstract":"Space-air-ground integrated network (SAGIN), as a three-tiered architecture that assimilates satellite systems, aerial, and terrestrial communication networks, has become an intensive research domain in the present era of communications. SAGIN-based communication models are developed to enhance the user’s quality of experience (QoE). Besides providing noteworthy benefits in various applications and services, SAGIN has unprecedented challenges because of its self-organized, unpredictable, and heterogeneous nature. Relaying equipment in SAGIN can be a very low-orbit satellite, a base station (BS), and an unmanned vehicle assisting a pair of mobile users’ communications. Thus, developing a robust device-to-device (D2D) direct and relaying communication model concerning channel distribution is crucial. Based on this concern, this article proposes a relay-aided D2D multiple–input and multiple–output (MIMO) scheme (RAS) for enhancing the optimal energy efficiency (EE) as a function of spectral efficiency (SE). The proposed model derives a relay-based amplify-and-forward (AF) MIMO multihop communication system for implementation. The proposed computations of optimal EE and SE for D2D MIMO show that the approximation provided by a random matrix approximation is constrained to a specific signal-to-noise ratio (SNR) range when the optimal SE and EE are derived using Gaussian quadrature and a hypergeometric function.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 4","pages":"333-341"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80418779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Inductive Transfer and Deep Neural Network Learning-Based Cross-Model Method for Short-Term Load Forecasting in Smarts Grids 基于归纳转移和深度神经网络学习的跨模型Smarts电网短期负荷预测方法

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2023-03-23 DOI: 10.1109/ICJECE.2023.3253547

Dabeeruddin Syed;Ameema Zainab;Shady S. Refaat;Haitham Abu-Rub;Othmane Bouhali;Ali Ghrayeb;Mahdi Houchati;Santiago Bañales

{"title":"Inductive Transfer and Deep Neural Network Learning-Based Cross-Model Method for Short-Term Load Forecasting in Smarts Grids","authors":"Dabeeruddin Syed;Ameema Zainab;Shady S. Refaat;Haitham Abu-Rub;Othmane Bouhali;Ali Ghrayeb;Mahdi Houchati;Santiago Bañales","doi":"10.1109/ICJECE.2023.3253547","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3253547","url":null,"abstract":"In a real-world scenario of load forecasting, it is crucial to determine the energy consumption in electrical networks. The energy consumption data exhibit high variability between historical data and newly arriving data streams. To keep the forecasting models updated with the current trends, it is important to fine-tune the models in a timely manner. This article proposes a reliable inductive transfer learning (ITL) method, to use the knowledge from existing deep learning (DL) load forecasting models, to innovatively develop highly accurate ITL models at a large number of other distribution nodes reducing model training time. The outlier-insensitive clustering-based technique is adopted to group similar distribution nodes into clusters. ITL is considered in the setting of homogeneous inductive transfer. To solve overfitting that exists with ITL, a novel weight regularized optimization approach is implemented. The proposed novel cross-model methodology is evaluated on a real-world case study of 1000 distribution nodes of an electrical grid for one-day ahead hourly forecasting. Experimental results demonstrate that overfitting and negative learning in ITL can be avoided by the dissociated weight regularization (DWR) optimizer and that the proposed methodology delivers a reduction in training time by almost 85.6% and has no noticeable accuracy losses.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 2","pages":"157-169"},"PeriodicalIF":0.0,"publicationDate":"2023-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9349829/10137376/10132308.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68016403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Application of Finite Control Set–Model Predictive Control for Servo Brake Motion in PMSM Drives 有限控制集-模型预测控制在永磁同步电机伺服制动中的应用

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2023-03-22 DOI: 10.1109/ICJECE.2022.3233029

Hiroaki Kawai;Julien Cordier;Ralph Kennel;Shinji Doki

{"title":"Application of Finite Control Set–Model Predictive Control for Servo Brake Motion in PMSM Drives","authors":"Hiroaki Kawai;Julien Cordier;Ralph Kennel;Shinji Doki","doi":"10.1109/ICJECE.2022.3233029","DOIUrl":"https://doi.org/10.1109/ICJECE.2022.3233029","url":null,"abstract":"Finite control set-model predictive control (FCS–MPC) has a simple and intuitive optimization procedure. Therefore, FCS–MPC is increasingly being applied to control strategies for electrical drive systems. This article presents a method for servo brake control of a permanent magnet synchronous motor (PMSM) based on FCS–MPC. Accordingly, we propose a reference trajectory introduced in a cost function for brake motions and an alternating procedure with speed control. Moreover, this article clarifies the problem peculiar to servo-brake control using FCS–MPC, i.e., the reduction in tracking performance near the brake position because of the low resolution of the output voltage. In addition to the conventional method, a finite number of smoothed voltages were applied as candidate voltages for FCS–MPC to improve the tracking performance near the brake position. The smoothed voltages can effectively increase the resolution of the output voltage, which results in fewer steady-state errors in angular position tracking during servo brake motion. The simulation and experimental results obtained using a PMSM drive system reveal that the proposed strategy exhibited high performance in tracking the reference target during the operation of servobrakes and the ability to seamlessly alternate between servo brake and motor operations.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 2","pages":"117-129"},"PeriodicalIF":0.0,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68014921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

IEEE Canadian Journal of Electrical and Computer Engineering IEEE加拿大电气与计算机工程杂志

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2023-03-22 DOI: 10.1109/ICJECE.2023.3251644

引用次数: 0

High-Performance RNS Modular Exponentiation by Sum-Residue Reduction 基于和残差约简的高性能RNS模块指数化

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2023-03-19 DOI: 10.1109/ICJECE.2023.3243888

Tao Wu

{"title":"High-Performance RNS Modular Exponentiation by Sum-Residue Reduction","authors":"Tao Wu","doi":"10.1109/ICJECE.2023.3243888","DOIUrl":"https://doi.org/10.1109/ICJECE.2023.3243888","url":null,"abstract":"With rapid development and application of artificial intelligence and block chain, the requirement of information and data security is also increased, in which the public-key cryptography, such as Rivest-Shamir-Adleman (RSA) cryptography, plays a significant role. Modular exponentiation is fundamental in computer arithmetic and is widely applied in cryptography, such as ElGamal cryptography, Diffie–Hellman key exchange protocol, and RSA cryptography. The implementation of modular exponentiation in a residue number system leads to high parallelism in computation and has been applied in many hardware architectures. While most residue number system (RNS)-based architectures utilize RNS Montgomery algorithm with two residue number systems, the recent modular multiplication algorithm with sum residues performs modular reduction in only one residue number system with about the same parallelism. In this work, it is shown that the high-performance modular exponentiation and RSA cryptography can be implemented in RNS. Both the algorithm and architecture are improved to achieve high performance with extra area overheads, where a 1024-bit modular exponentiation can be completed in 0.567 ms in Xilinx XC6VLX195t-3 platform, costing 26489 slices, 87357 LUTs, 363 dedicated multipilers of \u0000<inline-formula> <tex-math>$18 times 18$ </tex-math></inline-formula>\u0000 bits, and 65 block RAMs.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 2","pages":"137-143"},"PeriodicalIF":0.0,"publicationDate":"2023-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68014923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy Storage Management for Microgrids Using n-Step Bootstrapping 基于n步自举的微电网储能管理

IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2023-03-16 DOI: 10.1109/ICJECE.2022.3232213

Necati Aksoy;Istemihan Genc

{"title":"Energy Storage Management for Microgrids Using n-Step Bootstrapping","authors":"Necati Aksoy;Istemihan Genc","doi":"10.1109/ICJECE.2022.3232213","DOIUrl":"https://doi.org/10.1109/ICJECE.2022.3232213","url":null,"abstract":"Microgrids offer superiorities such as reducing energy costs and increasing the quality of energy, with the use of renewable energy sources and the effective use of energy storage unit created with innovative batteries. Furthermore, this structure, which helps to reduce the carbon footprint, will become undeniably critical to use in near future with the nanogrid and smart grid. As another development, an artificial intelligence (AI)-based control infrastructure brought to us by machine learning stands out as more beneficial than classical control methods. With this framework, which is called reinforcement learning (RL), it is promised that the system to be controlled can be more efficient. At this point, the thrifty use of energy storage unit, which is the most important tool that will increase the profitability of microgrids and enhance the proficiency of energy use, is associated with an RL-based energy control system. While this study focuses on an AI-based control infrastructure, it proposes a method utilizing an RL agent trained with a novel environmental model proposed specifically for the energy storage unit of microgrids. The advantages of this method demonstrated with the results are obtained, are shown and examined.","PeriodicalId":100619,"journal":{"name":"IEEE Canadian Journal of Electrical and Computer Engineering","volume":"46 2","pages":"107-116"},"PeriodicalIF":0.0,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68016404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0