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Improving Sensor-less Vector Controller for a Synchronous Reluctance Motor by Upgrading the Inverter Used

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Improving Sensor-less Vector Controller for a Synchronous Re...

International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM

作者： Alireza Souri Alireza Siadatan Mohammad Mansour Riahi Kashani dept. Electrical and Computer Engineering Islamic Azad University of Tehran North Branch-Tehran IRAN Energy Systems Group The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto Toronto ON Canada

ISBN: (数字)9781728170190

ISBN: (纸本)9781728170206

Increasing importance of energy, equipment, and consumables is the main motivation for many researches. One of the most efficient and, of course, very old equipment is the reluctance synchronous motor, which has not received much attention until now due to the problems of analog controllers. However, in the years to come, thanks to the remarkable development of control equipment and digital equipment, these motors can be controlled with great flexibility and stability. Therefore, in this research, we have tried to design an optimum drive for these motors, while controlling these motors with the least dependence on different operating conditions and load changes with minimum losses and, of course, unwanted harmonics. They are also a good alternative to induction motors with about 60% less loss and, of course, for permanent magnet synchronous motors because of the lower construction cost and no dependency on the permanent magnet. And, of course, due to the smooth operation and the lack of a ripple in torque, they can replace with switch reluctance motors.

关键词： Inverters Reluctance motors Torque Permanent magnet motors Rotors

Optimization-Based Control Allocation for Driving/Braking Torque Vectoring in a Race Car

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Optimization-Based Control Allocation for Driving/Braking To...

American Control Conference

作者： Moad Kissai Bruno Monsuez Xavier Mouton Adriana Tapus Department of Computer and System Engineering (U2IS) Institut Polytechnique de Paris ENSTA Paris Autonomous Systems and Robotics Lab Palaiseau France Chassis Systems Department Group Renault Guyancourt France

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

Most of recent researches on the automotive field focus on autonomous vehicles. These vehicles are equipped with conventional chassis systems. The goal is to control the vehicle's traction, brakes, and front steering. This paper discusses the importance of advanced chassis systems, as driving/braking torque vectoring, for both autonomous and non-autonomous vehicles, especially in a race mode. Reliable co-simulation results show that expanding the vehicle's potential leads to high performances and safety with respect to severe situations when optimal control allocation is ensured. Therefore, future passenger cars shall not only be equipped with additional sensors, but also by advanced systems along with adequate control algorithms.

关键词： Tires Torque Mathematical model Force Automobiles Wheels Resource management

Load balancing policies without feedback using timed replicas

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arXiv 2020年

作者： Jinan, Rooji Badita, Ajay Bodas, Tejas Parag, Parimal Department of Cyber-physical Systems IISc KA Bangalore560012 India Department of Electrical Communication Engineering IISc KA Bangalore560012 India Computer Systems Group at IIIT TS Hyderabad500032 India

Dispatching policies such as the join shortest queue (JSQ), join smallest work (JSW) and their power of two variants are used in load balancing systems where the instantaneous queue length or workload information at all queues or a subset of them can be queried. In situations where the dispatcher has an associated memory, one can minimize this query overhead by maintaining a list of idle servers to which jobs can be dispatched. Recent alternative approaches that do not require querying such information include the cancel on start and cancel on complete based replication policies. The downside of such policies however is that the servers must communicate the start or completion of each service to the dispatcher and must allow cancellation of redundant copies. In practice, the requirements of query messaging, memory, and replica cancellation pose challenges in their implementation and their advantages are not clear. In this work, we consider load balancing policies that do not query load information, do not have a memory, and do not cancel replicas. Surprisingly, we were able to identify operating regimes where such policies have better performance when compared to some of the popular policies that utilize server feedback information. Our policies allow the dispatcher to append a timer to each job or its replica. A job or a replica is discarded if its timer expires before it starts receiving service. We analyze several variants of this policy which are novel, simple to implement, and also have remarkably good performance in some operating regimes, despite no feedback from servers to the dispatcher. Copyright © 2020, The Authors. All rights reserved.

关键词： Queueing theory

Fully three-dimensional sound speed-corrected multi-wavelength photoacoustic breast tomography

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arXiv 2023年

作者： Dantuma, M. Lucka, F. Kruitwagen, S.C. Javaherian, A. Alink, L. Pompe van Meerdervoort, R.P. Nanninga, M. Op't Root, T.J.P.M. De Santi, B. Budisky, J. Bordovsky, G. Coffy, E. Wilm, M. Kasponas, T. Aarnink, S.H. de Geus-Oei, L.F. Brochin, F. Martinez, T. Michailovas, A. Muller Kobold, W. Jaros, J. Veltman, J. Cox, B. Manohar, S. Multi-Modality Medical Imaging group TechMed Centre University of Twente Enschede Netherlands Computational Imaging Centrum Wiskunde & Informatica Amsterdam Netherlands Department of Computer Science University College London London United Kingdom Medisch Spectrum Twente Hospital Enschede Netherlands Department of Medical Physics and Biomedical Engineering University College London London United Kingdom P.A. Imaging R&D B.V. Enschede Netherlands Department of Computer Systems Faculty of Information Technology Brno University of Technology Brno Czech Republic Imasonic SAS Voray-sur-l'Orgnon France Ekspla UAB Vilnius Lithuania Biomedical Photonic Imaging group University of Twente Enschede Netherlands Department of Radiology Leiden University Medical Center Leiden Netherlands Center for Physical Science and Technology Vilnius Lithuania Department of Radiology Ziekenhuisgroep Twente Hengelo Netherlands

Photoacoustic tomography is a contrast agent-free imaging technique capable of visualizing blood vessels and tumor-associated vascularization in breast tissue. While sophisticated breast imaging systems have been recently developed, there is yet much to be gained in imaging depth, image quality and tissue characterization capability before clinical translation is possible. In response, we have developed a hybrid photoacoustic and ultrasound-transmission tomographic system (PAM3). The photoacoustic component has for the first time three-dimensional multi-wavelength imaging capability, and implements substantial technical advancements in critical hardware and software subsystems. The ultrasound component enables for the first time, a three-dimensional sound speed map of the breast to be incorporated in photoacoustic reconstruction to correct for inhomogeneities, enabling accurate target recovery. The results demonstrate the deepest photoacoustic breast imaging to date (48 mm),with a more uniform field of view than hitherto, and an isotropic spatial resolution that rivals that of Magnetic Resonance Imaging. The in vivo performance achieved, and the diagnostic value of interrogating angiogenesis-driven optical contrast as well as tumor mass sound speed contrast, gives confidence in the system's clinical potential. © 2023, CC BY.

关键词： Photoacoustic effect

Anti-Collision System for Accident Prevention in Underground Mines using computer Vision 22

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Anti-Collision System for Accident Prevention in Underground...

Proceedings of the 6th International Conference on Advances in Artificial Intelligence

作者： Mohamed Imam Karim Baïna Youness Tabii Intissar Benzakour Youssef Adlaoui El Mostafa Ressami El Hassan Abdelwahed Alqualsadi Research Team Rabat IT Center ENSIAS Mohammed V University in Rabat ENSIAS Morocco and Digitalization & Microelectronic Smart Devices - MAScIR Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Morocco Alqualsadi Research Team Rabat IT Center ENSIAS Mohammed V University in Rabat ENSIAS Morocco Information Retrieval and Data Analytics (IRDA) Research Team Rabat IT Center ENSIAS ENSIAS Morocco Reminex Research and Engineering center MANAGEM Group REMINEX Morocco Digitalization & Microelectronic Smart Devices - MAScIR Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Morocco Laboratory of Computer Systems Engineering (LISI) FSSM Cadi Ayyad University FSSM Morocco

ISBN: (纸本)9781450396943

Underground prospecting operations are often characterized by critical safety issues mainly due to poor visibility and blind spots around large vehicles and equipment. This can result in vehicle-to-vehicle collisions, as well as vehicle-to-pedestrian or structural-element collisions, resulting in accidents. In this article, we discuss an anti-collision system for pedestrian identification in deep mines under the premise that we are looking to prevent collisions with moving machinery. This study presents the findings from testing an image processing module and sensory system based on deep learnig in the context of "smart connected mine" project.

关键词： Yolov5 Pedestrian detection Deep Learning Underground mining

The Bankable Economic Potential of Utility-Scale Solar Pv: A Novel Gis-Based Framework with Application to Indonesia

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SSRN

SSRN 2023年

作者： Langer, Jannis Ashqar, Ziad Zhou, Yilong Isabella, Olindo Praktiknjo, Aaron Quist, Jaco Kwee, Zenlin Blok, Kornelis Delft University of Technology Faculty of Technology Policy and Management Department of Engineering Systems and Services Jaffalaan 5 Delft2628 BX Netherlands Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Department of Electrical Sustainable Energy Photovoltaic Materials and Devices group Mekelweg 4 Delft2628 CD Netherlands RWTH Aachen University Energy System Economics Institute for Future Energy Consumer Needs and Behavior E.ON Energy Research Center Mathieustraße 10 Aachen52074 Germany Delft University of Technology Faculty of Technology Policy and Management Department of Values Technology and Innovation Jaffalaan 5 Delft2628 BX Netherlands

Geospatial analysis is useful to calculate and map solar photovoltaic’s (PV) economic potential. However, recent studies do not address PV’s bankable potential for practical implementation and show limitations in (1) potential and input reporting, (2) studied metrics, (3) uncertainty analysis, and (4) policy analysis. To tackle these limitations, we propose a novel framework for utility-scale PV’s bankable potential, which combines geospatial analysis and project finance. The framework involves 20 years of hourly solar electricity production, a debt sizing and cash flow analysis model, and Monte Carlo simulation. We report a conservative technical potential of 9.3 TWpeak and 12.1 PWh/year in Indonesia. Considering expected 2030 demand, PV’s bankable potential is up to 40.8 TWh/year mostly situated in East Indonesia where population and demand are low. PV’s bankability is currently limited by strict loan maturities and low electricity tariffs, and could be improved to up to 232 TWh/year (52% of 2030 demand) via a feed-in tariff of 11.5 US¢(2021)/kWh and a temporary lift of local content for solar panels. Despite their effectiveness, policymakers should be aware of possible side effects of PV policies, e.g. for local coal-based industries and rural communities with limited electricity access. © 2023, The Authors. All rights reserved.

关键词： Economic analysis

Resource-efficient speech mask estimation for Multi-channel speech enhancement

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arXiv 2020年

作者： Pfeifenberger, Lukas Zöhrer, Matthias Schindler, Günther Roth, Wolfgang Fröning, Holger Pernkopf, Franz Intelligent Systems Group at the Signal Processing and Speech Communication Laboratory Graz University of Technology Graz Austria Institute of Computer Engineering Ruperts Karls University Heidelberg Germany

While machine learning techniques are traditionally resource intensive, we are currently witnessing an increased interest in hardware and energy efficient approaches. This need for resource-efficient machine learning is primarily driven by the demand for embedded systems and their usage in ubiquitous computing and IoT applications. In this article, we provide a resource-efficient approach for multi-channel speech enhancement based on Deep Neural Networks (DNNs). In particular, we use reduced-precision DNNs for estimating a speech mask from noisy, multi-channel microphone observations. This speech mask is used to obtain either the Minimum Variance Distortionless Response (MVDR) or Generalized Eigenvalue (GEV) beamformer. In the extreme case of binary weights and reduced precision activations, a significant reduction of execution time and memory footprint is possible while still obtaining an audio quality almost on par to single-precision DNNs and a slightly larger Word Error Rate (WER) for single speaker scenarios using the WSJ0 speech corpus. Copyright © 2020, The Authors. All rights reserved.

关键词： Speech enhancement

A Compact Low-Power Data Retention Flip-Flop with Easy-Sleep Mode

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A Compact Low-Power Data Retention Flip-Flop with Easy-Sleep...

IEEE International Symposium on Circuits and systems (ISCAS)

作者： Hailong Jiao Zhanliang Zhang VLSI Lab School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen China Electronic Systems group Eindhoven University of Technology Eindhoven The Netherlands

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

A new data retention flip-flop, DRFF-Lite, which is designed based on the conventional master-slave flip-flop is proposed in this paper. No additional data retention circuitry is required by DRFF-Lite to implement the low-leakage data retention sleep mode, thereby providing easy and energy-efficient mode transitions. Due to the simplified topology, DRFF-Lite achieves up to 40% layout area savings as compared to the state-of-the-art data retention flip-flops in a 40-nm CMOS technology. Furthermore, DRFF-Lite reduces the sleep mode leakage power consumption, active mode leakage power consumption, active power consumption, and mode transition energy consumption by up to 31.5%, 60%, 18.5%, and 85.9%, respectively, under the impact of process parameter variations, while providing similar critical path propagation delay as compared to the state-of-the-art data retention flip-flops.

关键词： Flip-flops Transistors Latches Logic gates Switching circuits Leakage currents Power demand

A data-centric weak supervised learning for highway traffic incident detection

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arXiv 2021年

作者： Sun, Yixuan Mallick, Tanwi Balaprakash, Prasanna Macfarlane, Jane School of Mechanical Engineering Purdue University West LafayetteIN United States Mathematics and Computer Science Division Argonne National Laboratory LemontIL United States Mathematics and Computer Science Division & Argonne Leadership Computing Facility Argonne National Laboratory LemontIL United States Sustainable Energy Systems Group Lawrence Berkeley National Laboratory BerkeleyCA United States

Using the data from loop detector sensors for near-real-time detection of traffic incidents in highways is crucial to averting major traffic congestion. While recent supervised machine learning methods offer solutions to incident detection by leveraging human-labeled incident data, the false alarm rate is often too high to be used in practice. Specifically, the inconsistency in the human labeling of the incidents significantly affects the performance of supervised learning models. To that end, we focus on a data-centric approach to improve the accuracy and reduce the false alarm rate of the traffic incident detection on highways. We develop a weak supervised learning workflow to generate high-quality training labels for the incident data without the ground truth labels, and we use those generated labels in the supervised learning setup for final detection. This approach comprises three stages. First, we introduce a data preprocessing and curation pipeline that processes traffic sensor data to generate high-quality training data through leveraging labeling functions, which can be domain knowledge related or simple heuristic rules. Second, we evaluate the training data generated by weak supervision using three supervised learning models—random forest, k-nearest neighbors, and a support vector machine ensemble—and long short-term memory classifiers. The results show that the accuracy of all of the models improves significantly after using the training data generated by weak supervision. Third, we develop an online real-time incident detection approach that leverages the model ensemble and the uncertainty quantification while detecting incidents. Overall, we show that our proposed weak supervised learning workflow achieves a high incident detection rate (0.90) and low false alarm rate (0.08). © 2021, CC BY.

关键词： Decision trees