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Integration of a relaxation voltage prediction function into a PI-based observer to improve the SOC estimation of battery packs in renewable energy applications 13

Integration of a relaxation voltage prediction function into...

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13th international ELEKTRO conference (ELEKTRO)

作者： Nobile, Giovanni Vasta, Ester Cacciato, Mario Scarcella, Giuseppe Scelba, Giacomo Federica Di Stefano, Agnese Giuseppa Leotta, Giuseppe Pugliatti, Paola Maria Bizzarri, Fabrizio Univ Catania Dept Elect Elect Engn & Comp Sci Catania Italy Enel Green Power SpA Catania Italy

ISBN: (纸本)9781728175423

the integration of energy storage systems (ESSs) and specially of battery ESSs (BESSs) with renewable energy sources represents an efficient solution due to their ability to provide energy time shifting, peak shaving and so on. Considering the above, deepening all aspects related to the precise estimation of the state of charge (SOC) of a battery becomes extremely important. In this work, a real-time estimation algorithm including a PI-based observer and an equivalent circuit model (ECM), is improved exploiting the SOC dependence on the open circuit voltage (OCV). Particularly, it is described how the SOC can be reliably deduced from relaxation voltage in a short time thanks to a prediction function. the integration of such function into the PI-based observer allows to get a good trade-off between accuracy and complexity.

关键词： Energy storage Batteries State estimation Prediction algorithms Observers

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Emulation and Testing for Automotive Propulsion Drive Using Two Cascaded Inverters

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ieee TRANSACTIONS ON INDUSTRY applications 2020年第2期56卷 1766-1783页

作者： Boukadida, Yassine Marignetti, Fabrizio Casolino, Giovanni Mercurio Masmoudi, Ahmed Andreoli, Alessandro Albanesi, Mariano Univ Sfax Sfax 3029 Tunisia Univ Cassino & South Lazio I-03043 Cassino Italy Loccioni Grp I-60030 Angeli Italy

Assessing the operation of electric drives under standard operating cycles is mandatory in production lines of electric vehicles drivetrains. this article presents a technique dedicated to the performance assessment of electric powertrains for automotive applications. A numerically controlled experimental setting is developed, including a power system made up of two dc-ac converters with their ac sides connected through chokes and a control system implemented in a national instrument PCI eXtensions for instrumentation (NI PXI) hardware-in-the-loop testing system. this system emulates the dynamic behavior of the electric vehicle and of its powertrain. System analysis is used to assess the stability conditions and to calculate the current ripple and the optimal values of the chokes. the experimental emulation of automotive driving cycles in two case studies highlights the effectiveness of the developed automotive testing system. the power flow is analyzed during the motoring and the regenerative braking phases.

关键词： Acceleration automotive drive test braking emulation Hardware-In-the-Loop (HIL) real-time (RT) systems road vehicle electric propulsion testing

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Overcoming Memory Constraint for Improved Target Classification Performance on embedded Deep Learning systems 22

Overcoming Memory Constraint for Improved Target Classificat...

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22nd ieee international conference on High Performance computing and Communications, 18th ieee international conference on Smart City and 6th ieee international conference on Data Science and systems, HPCC-SmartCity-DSS 2020

作者： Wu, Fan Liu, Huanghe Zhu, Zongwei Ji, Cheng Xue, Chun Jason Suzhou Institute for Advanced Study University of Science and Technology of China China Nanjing University of Science and Technology China City University of Hong Kong Hong Kong

ISBN: (纸本)9781728176499

Pattern recognition applications such as face recognition, detection of broken eggs, and classification of agricultural products are all using image classification in deep neural networks to improve the quality of services. However, traditional cloud inference models suffer from several problems such as network delay fluctuations and privacy leakage. In this regard, most real-time applications currently need to be deployed on edge computing devices. Constrained by the computing power and memory limitations of edge devices, the use of an efficient memory manager for model reasoning is the key to improving the quality of service. this study firstly explored the incremental loading strategy of model weights for the model reasoning. Next, the memory space at runtime is optimized through data layout reorganization from the spatial dimension. In particular, our proposed schemes are orthogonal and transparent to the model. Experimental results demonstrate that the proposed approach reduced the memory consumption by 43.74% on average without additional reasoning time overhead. © 2020 ieee.

关键词： Quality of service

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A CNN-based Audio Sensor for Rainfall Estimation: Implementation on embedded Board

A CNN-based Audio Sensor for Rainfall Estimation: Implementa...

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ieee international Workshop on Intelligent Data Acquisition and Advanced computing systems: Technology and applications

作者： Michele Russo Valerio Francesco Puglisi Roberta Avanzato Francesco Beritelli VICOSYSTEMS S.R.L. Viale Odorico da Pordenone Catania Italy DMI - University of Catania Catania Italy DIEEI - University of Catania Catania Italy

ISBN: (纸本)9781665426060

At present, one of the main issues of interest is climate change. It triggers calamitous phenomena (fires, hydrogeological instability and many others) that put crops, vegetation and even human beings at risk. Considering the phenomenon of hydrogeological instability, there is a wide range of smart application contexts (for example, smart city, smart road and smart agriculture), which require a real-time rainfall level monitoring, recognition and classification system. this system is supposed to provide accurate and real-time estimates of rain intensity and alert those in charge in order to reduce the risks associated with the various application contexts. thus, the present paper proposes an audio sensor enabled real-time audio rainfall classification, based on 1-D convolutional neural network (CNN) which offers 95% classification accuracy in five rainfall intensity classes.

关键词： Rain Smart cities Roads Estimation Vegetation mapping real-time systems Sensor systems

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Electromagnetic Simulation of Periodic Structures Using Memory Efficient DGTD Method 6

Electromagnetic Simulation of Periodic Structures Using Memo...

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ieee international conference on Computational Electromagnetics (ICCEM)

作者： Wen, Pengfei Ren, Qiang Chen, Aixin Zhang, Yan Chen, Jiefu Beihang Univ Sch Elect & Informat Engn Beijing Peoples R China Univ Houston Dept Elect & Comp Engn Houston TX USA

ISBN: (纸本)9781728134482

this paper analyzed the periodic structures with quasi-periodic and multi-scale features based on memory efficient discontinuous Galerkin finite-element time-domain (DGTD) method that can reduce computing resource overhead significantly by employing matrix reuse technique. the memory efficient DGTD method is improved in two ways. Firstly, multiple types of cells are allowed to be mixed, which solved the problem that there are multiple periodic elements in the structure. Secondly, one lattice can he inserted into another lattice using non-conformed mesh which can solve multiscale structures. the numerical example is presented to validate the versatility, validity. and potential applications of the improved method in electromagnetic problems.

关键词： memory efficient discontinuous Galerkin finite-element time-domain (DGTD) quasi-periodic structures embedded structures memory consumption

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Adaptive Data Replication in real-time Reliable Edge computing for Internet of things

Adaptive Data Replication in Real-Time Reliable Edge Computi...

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5th ieee/ACM international conference on Internet-of-things Design and Implementation (ACM/ieee IoTDI)

作者： Wang, Chao Gill, Christopher Lu, Chenyang Natl Taiwan Normal Univ Dept Comp Sci & Informat Engn Taipei Taiwan Washington Univ Dept Comp Sci & Engn St Louis MO 63110 USA

ISBN: (纸本)9781728166025

Many Internet-of-things (IoT) applications rely on timely and reliable processing of data collected from embedded sensing devices. To achieve timely response, computing tasks are executed on IoT gateways at the edge of clouds, and for fault tolerance, the gateways perform data replication to backup gateways. In this paper, we report our study of data replication strategies and a real-time and fault-tolerant edge computing architecture for IoT applications. We first analyze how both embedded devices' storage constraints and data replication frequency may impose timing constraints on data replication tasks, and we investigate correlations between execution of data replication tasks and execution of edge computing tasks. Accordingly, we propose adaptive data replication strategies and introduce a framework for real-time reliable edge computing to meet the needed levels of data loss tolerance and timeliness. We have implemented our framework and empirically evaluated the proposed strategies with baseline approaches. We set up experiments using Industrial IoT traffic configurations that have requirements on data loss and timeliness, and our experimental results show that the proposed data replication strategies and framework can ensure needed levels of data loss tolerance, save network bandwidth consumption, while maintaining the latency performance.

关键词： real time systems

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Parallel Implementation of H.265 Intra-Frame Coding Based on FPGA Heterogeneous Platform 22

Parallel Implementation of H.265 Intra-Frame Coding Based on...

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作者： Chen, Wenjie He, Qunfang Li, Shen Xiao, Bo Chen, Mingsong Chai, Zhilei East China Normal University National Trusted Embedded Software Engineering Technology Research Center Shanghai China East China Normal University MoE Engineering Research Center for Software/Hardware Co-design Technology Shanghai China Jiangnan University School of IoT Engineering Wuxi China

ISBN: (纸本)9781728176499

the new video coding algorithm H.265 achieved twice compression rate than the prevailing H.264, but the encoding speed is reduced several times, making it difficult for the real-time applications such as video surveillance and remote meeting. In this paper, we design a parallel intra-frame mode decision architecture based on FPGA to accelerate the coding. We prove that the mode decision problem of multi-level large coding unit of H.265 can be transformed into the accumulation of multiple single-level small coding unit mode decision. Furthermore, we design how mode decision is accelerated by fine-grained parallelism within coding unit, and pipelining among coding units, then implement them on FPGA. the experimental results show that the proposed architecture achieves maximum 93.6\times acceleration compare with the ARM A53 platform, with an insignificant loss of video quality. © 2020 ieee.

关键词： Field programmable gate arrays (FPGA)

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Formal Modeling and Verification of EDCA Based on Probabilistic Model Checking 22

Formal Modeling and Verification of EDCA Based on Probabilis...

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作者： Zan, Yixuan Li, Xiaojuan Guan, Yong Wang, Rui Zhang, Jie Capital Normal University College of Information Engineering Beijing China Capital Normal University Beijing Engineering Research Center of High Reliability Embedded System Beijing China Capital Normal University Beijing Advanced Innovation Center for Imaging Theory and Technology Beijing China Capital Normal University Beijing Key Laboratory of Light Industrial Robots and Safety Verification Beijing China Beijing University of Chemical Technology College of Information Science and Technology Beijing China

ISBN: (纸本)9781728176499

Enhanced Distributed Channel Access (EDCA) is a distributed control protocol to guarantee the network quality of service (QoS). It extends the access mode based on the traditional ieee 802.11, and becomes an effective means to provide highly reliable transmission of real-time applications. the four access categories of it show the ability to guarantee various priority queues when the network load varies frequently, and multimedia data transmission has the characteristics of high real-time and concurrency. therefore, it is necessary to analyse and verify the high reliability of the protocol according to requirements. In this paper, we formalize the EDCA protocol and design three transmission modes respectively. then we verify the probability accessibility and feasibility of EDCA, and find that the higher priority queue with lower parameter value will affect the sending of low priority. More importantly, we compare the performance of Distributed Coordination Function (DCF) in collision probability and transmission probability. Finally, we demonstrate the reliability and practicability of EDCA via detailed properties studies in different network conditions, and propose innovative ideas for existing problems, which provide guidance reference for implementation and improvement. © 2020 ieee.

关键词： ieee Standards

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A content-based intelligent mobile video censoring system 7

A content-based intelligent mobile video censoring system

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7th ieee international conference on Progress in Informatics and computing, PIC 2020

作者： Wang, Jing Yuan, Chenyu Liu, Yao Lin, Yuxuan Liang, Jian City College of Huizhou School of Mechatronics Huizhou China Hohai University College of Computer and Information Nanjing China

ISBN: (纸本)9781728170862

With the development of information technology, mobile video on-demand and live streaming prevails in the young population. But the content of mobile video may contain some bloody and violent scenes. Teenagers, among all consumers, are more susceptible the negative influence of violence in videos. the censorship targeting at the online contents including images and video is an important yet arduous task. the adoption of AI-based censoring technique can help lower the operation cost for Internet content providers and save the work labor in censorship while preventing video consumers from being affected by unhealthy information. this paper presents an embedded system for content-based video censoring based on the deep learning technique. the proposed system is capable of filtering video content automatically, where an algorithm is developed that utilizes the power of Intel IoT development suite and the Intel Neural compute stick. Efforts has been made to optimize the real-time content censoring of the system. Experimental results show that, when applied to the video-on-demand IoT applications, the proposed system can speed up the video processing significantly and it can be effective in shielding young audience from violent videos at mobile devices in a real-time manner. © 2020 ieee.

关键词： embedded systems

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Graph transformations and derivation of scheduling constraints applied to the mapping of real-time distributed applications 13

Graph transformations and derivation of scheduling constrain...

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ieee 13th international Symposium on embedded Multicore/Many-Core systems-on-Chip (MCSoC)

作者： Louise, Stephane CEA LIST PC172Bat 862 F-91191 Gif Sur Yvette France

ISBN: (纸本)9781728148823

Synchronous Data-Flow as a deterministic variation of Khan Process Networks is a good model for distributed applications that allows for verification of the properties of the applications both at the design level and at run-time. real-time extensions exist which allow to specify real-time clocks for some of the processes in the graph. With the addition of real-time clocks, the behavior of the complete system can be easily differentiated from a nominal real-time mode where all the required data for processing is available when a clock tick occurs, and an error mode can be triggered when the condition is not met. Our contribution in this paper is -first- to show a set of graph transformations that allow to account for the execution and communication time on a real platform while at the same time maximizing the parallelism of execution and -second-on top of these transformations to provide the execution constraints as a linear program that must be met at run-time to guarantee the real-time requirements. It is illustrated on a subset of a real-life automotive example.

关键词： Distributed and Heterogeneous systems Synchronous Data-Flow Graph Transformations

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