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The topics of interest in this book include significant challenges in the BMS design of EV/HEV. The equivalent models developed for several types of integrated Li-ion batteries consider the environmental temperature and ageing effects. Different current profiles for testing the robustness of the Kalman filter type estimators of the battery state of charge are used in this book. Additionally, the BMS can integrate a real-time model-based sensor Fault Detection and Isolation (FDI) scheme for a Li-ion cell undergoing degradation, which uses the recursive least squares (RLS) method to estimate the equivalent circuit model (ECM) parameters. This book will fully meet the demands of a large community of readers and specialists working in the field due to its attractiveness and scientific content with a great openness to the side of practical applicability. This covers various interesting aspects, especially related to the characterization of commercial batteries, diagnosis and optimization of their performance, experimental testing and statistical analysis, thermal modelling, and implementation of the most suitable Kalman filter type estimators of high accuracy to estimate the state of charge

Technology: general issues --- arrayed waveguide grating (AWG) --- CMOS sensor --- direct laser lithography --- fiber Bragg grating (FBG) --- lithium-ion battery --- fault detection and isolation --- sensor fault --- battery model --- battery management systems --- battery degradation --- electric vehicles --- online parameter estimation --- recursive least squares --- parallel-connected cells --- measuring test bench --- current distribution --- tab contact resistance --- battery --- ultracapacitor --- supercapacitor --- electric mobility --- electric bus --- SAFT lithium-ion battery --- Simscape model --- 3RC ECM Li-ion battery model --- state of charge --- adaptive EKF SOC estimator --- adaptive UKF SOC estimator --- particle filter SOC estimator --- ADVISOR estimate

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Application of multi-sensor fusion technology has drawn a lot of industrial and academic interest in recent years. The multi-sensor fusion methods are widely used in many applications, such as autonomous systems, remote sensing, video surveillance, and the military. These methods can obtain the complementary properties of targets by considering multiple sensors. On the other hand, they can achieve a detailed environment description and accurate detection of interest targets based on the information from different sensors.This book collects novel developments in the field of multi-sensor, multi-source, and multi-process information fusion. Articles are expected to emphasize one or more of the three facets: architectures, algorithms, and applications. Published papers dealing with fundamental theoretical analyses, as well as those demonstrating their application to real-world problems.

target detection --- multi-platform imaging --- spectral matching --- terrestrial-hyperspectral imagery --- automated image analysis --- spectral library --- multi-sensor fusion --- object detection --- deep learning --- convolutional neural networks --- autonomous vehicles --- marine environment --- co-operative --- autonomous --- multi-robot --- USV --- AUV --- semantic SLAM --- YOLOv3 --- object based map --- EKF --- specular reflection detection --- specular reflection inpainting --- transparent object --- multispectral polarimetric imagery --- light field --- maritime vessel dataset --- ship detection --- convolutional neural network --- autonomous marine navigation --- machine learning --- inversion --- ocean colour --- phytoplankton --- pigment vertical profile --- deep chlorophyll maximum --- Tara Oceans --- MAREDAT --- pigments --- ITCOMP-SOM --- Self Organizing Maps

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Application of multi-sensor fusion technology has drawn a lot of industrial and academic interest in recent years. The multi-sensor fusion methods are widely used in many applications, such as autonomous systems, remote sensing, video surveillance, and the military. These methods can obtain the complementary properties of targets by considering multiple sensors. On the other hand, they can achieve a detailed environment description and accurate detection of interest targets based on the information from different sensors.This book collects novel developments in the field of multi-sensor, multi-source, and multi-process information fusion. Articles are expected to emphasize one or more of the three facets: architectures, algorithms, and applications. Published papers dealing with fundamental theoretical analyses, as well as those demonstrating their application to real-world problems.

Information technology industries --- target detection --- multi-platform imaging --- spectral matching --- terrestrial-hyperspectral imagery --- automated image analysis --- spectral library --- multi-sensor fusion --- object detection --- deep learning --- convolutional neural networks --- autonomous vehicles --- marine environment --- co-operative --- autonomous --- multi-robot --- USV --- AUV --- semantic SLAM --- YOLOv3 --- object based map --- EKF --- specular reflection detection --- specular reflection inpainting --- transparent object --- multispectral polarimetric imagery --- light field --- maritime vessel dataset --- ship detection --- convolutional neural network --- autonomous marine navigation --- machine learning --- inversion --- ocean colour --- phytoplankton --- pigment vertical profile --- deep chlorophyll maximum --- Tara Oceans --- MAREDAT --- pigments --- ITCOMP-SOM --- Self Organizing Maps --- target detection --- multi-platform imaging --- spectral matching --- terrestrial-hyperspectral imagery --- automated image analysis --- spectral library --- multi-sensor fusion --- object detection --- deep learning --- convolutional neural networks --- autonomous vehicles --- marine environment --- co-operative --- autonomous --- multi-robot --- USV --- AUV --- semantic SLAM --- YOLOv3 --- object based map --- EKF --- specular reflection detection --- specular reflection inpainting --- transparent object --- multispectral polarimetric imagery --- light field --- maritime vessel dataset --- ship detection --- convolutional neural network --- autonomous marine navigation --- machine learning --- inversion --- ocean colour --- phytoplankton --- pigment vertical profile --- deep chlorophyll maximum --- Tara Oceans --- MAREDAT --- pigments --- ITCOMP-SOM --- Self Organizing Maps

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This reprint presents various aspects of the future grid, which is the next generation of the electrical grid and will enable the smart integration of conventional, renewable, and distributed power generation, energy storage, transmission and distribution, and demand management. Renewable energy is crucial in transitioning to a less carbon-intensive economy and a more sustainable energy system. The high penetration and uncertain power outputs of renewable energy pose great challenges to the stable operation of energy systems. The deployment of the smart grid is revolutionary, and also imperative around the world. It involves and deals with multidisciplinary fields such as energy sources, control systems, communications, computational generation, transmission, distribution, customer operations, markets, and service providers. Smart grids are emerging in both developed and developing countries, with the aim of achieving a reliable and secure electricity supply. Smart grids will eventually require standards, policy, and a regulatory framework for successful implementation. This reprint addresses the emerging and advanced green energy technologies for a sustainable and resilient future grid, and provides a platform to enhance interdisciplinary research and share the most recent ideas.

Technology: general issues --- History of engineering & technology --- islanded mode --- microgrid --- decentralized control --- robust tracking --- invariant set --- thermal energy storage --- parabolic dish --- latent heat --- phase change material --- heat transfer fluid --- bio-inspired algorithms --- wireless sensor network --- genetic algorithm --- particle swarm optimization --- advanced metering infrastructure --- blockchain --- Ethereum --- isolated DC–DC converter --- photovoltaics --- LLC resonant converter --- dual-bridge --- wide voltage range --- power optimizer --- coordinated control --- vehicle-to-grid --- primary frequency control --- secondary frequency control --- state of charge --- decentralized --- Simulink model --- dimensionality reduction --- simple linear regression --- multiple linear regression --- polynomial regression --- load forecasting --- VSC (voltage source converter) --- PLL (Phase-Locked Loop) --- weak grid --- small signal stability --- eigenvalues --- demand-side management --- low-power consumer electronic appliances --- low-voltage distribution system --- non-intrusive identification of appliance usage patterns --- power quality --- smart home --- true power factor --- total harmonic distortion --- renewable energy sources --- energy management system --- communication technologies --- microgrid standards --- third-order sliding mode control --- asynchronous generators --- variable speed dual-rotor wind turbine --- direct field-oriented control --- integral-proportional --- transformer --- internal fault currents --- magnetic inrush currents --- extended Kalman filter (EKF) algorithm --- harmonic estimation --- DC microgrid --- fault --- cluster --- DC/DC converter --- fault current limiter (FCL) --- multi-objective --- renewable energy --- profit-based scheduling --- Equilibrium Optimizer --- smart grid --- campus microgrid --- batteries --- prosumer market --- distributed generation --- renewable energy resources --- energy storage system --- distributed energy resources --- demand response --- load clustering techniques --- sizing methodologies --- digital signal processing --- green buildings --- spectral analysis --- spectral kurtosis --- life-cycle cost --- optimal scheduling --- reinforcement learning --- enabling technologies --- energy community --- smart meter --- nanogrid --- platform --- power cloud --- n/a --- isolated DC-DC converter

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Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITS) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include: road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas. The efficient operation of these complex systems requires: i) efficient solutions to the issues of sensors/actuators used to capture and control the physical parameters of these systems, as well as the quality of data collected from these systems; ii) tackling complexities using simulations and analytical modelling techniques; and iii) applying optimization techniques to improve the performance of these systems. It includes twenty-four papers, which cover scientific concepts, frameworks, architectures and various other ideas on analytics, trends and applications of transportation-related data.

Technology: general issues --- image dehazing --- traffic video dehazing --- dark channel prior --- spatial-temporal correlation --- contrast enhancement --- traffic signal control --- game theory --- decentralized control --- large-scale network control --- railway intrusion detection --- scene segmentation --- scene recognition --- adaptive feature extractor --- convolutional neural networks --- in-cylinder pressure identification --- speed iteration model --- EKF --- frequency modulation --- amplitude modulation --- sensor synchronization --- microscopic traffic data --- trajectory reconstruction --- expectation maximization --- vehicle matching --- artificial neural networks --- metro --- transportation --- user flow forecast --- matrix inversion --- time-varying matrix --- noise problem in time-varying matrix inversion --- recurrent neural network (RNN) --- RNN-based solver --- real-time fast computing --- real-time estimation --- probe vehicle --- traffic density --- neural network --- level of market penetration rate --- deep neural network --- neural artistic extraction --- objectification --- ride comfort --- subjective evaluation --- road surface recognition --- Gaussian background model --- abnormal road surface --- acceleration sensor --- traffic state prediction --- spatio-temporal traffic modeling --- simulation --- machine learning --- hyper parameter optimization --- ITS --- crash risk modeling --- hazardous materials --- highway safety --- operations research --- prescriptive analytics --- shortest path problem --- trucking --- vehicle routing problem --- data visualization --- descriptive analytics --- predictive analytics --- urban rail transit interior noise --- smartphone sensing --- XGBoost classifier --- railway maintenance --- vehicle trajectory prediction --- license plate data --- trip chain --- turning state transit --- route choice behavior --- real world experiment --- Intelligent Transportation Systems (ITS) --- advanced traveler information systems (ATIS) --- connected vehicles --- particle filter --- Kalman filter --- road safety --- travel time information system --- safety performance function --- bicycle sharing systems --- public transport systems --- data-driven classification of trips --- BSS underlying network --- trip index --- automatic rail-surface-scratch recognition and computation --- triangulation algorithm --- complete closed mesh model --- online rail-repair --- autonomous vehicle --- obstacle avoidance --- artificial potential field --- model predictive control --- human-like --- variable speed limits --- intelligent transportation systems --- ITS services --- driving simulator studies --- traffic modelling --- surrogate safety measures --- driving safety --- driving emotions --- driving stress --- lifestyle --- sensors --- heart rate --- plate scanning --- low-cost sensor --- sensor location problem --- traffic flow estimation --- image dehazing --- traffic video dehazing --- dark channel prior --- spatial-temporal correlation --- contrast enhancement --- traffic signal control --- game theory --- decentralized control --- large-scale network control --- railway intrusion detection --- scene segmentation --- scene recognition --- adaptive feature extractor --- convolutional neural networks --- in-cylinder pressure identification --- speed iteration model --- EKF --- frequency modulation --- amplitude modulation --- sensor synchronization --- microscopic traffic data --- trajectory reconstruction --- expectation maximization --- vehicle matching --- artificial neural networks --- metro --- transportation --- user flow forecast --- matrix inversion --- time-varying matrix --- noise problem in time-varying matrix inversion --- recurrent neural network (RNN) --- RNN-based solver --- real-time fast computing --- real-time estimation --- probe vehicle --- traffic density --- neural network --- level of market penetration rate --- deep neural network --- neural artistic extraction --- objectification --- ride comfort --- subjective evaluation --- road surface recognition --- Gaussian background model --- abnormal road surface --- acceleration sensor --- traffic state prediction --- spatio-temporal traffic modeling --- simulation --- machine learning --- hyper parameter optimization --- ITS --- crash risk modeling --- hazardous materials --- highway safety --- operations research --- prescriptive analytics --- shortest path problem --- trucking --- vehicle routing problem --- data visualization --- descriptive analytics --- predictive analytics --- urban rail transit interior noise --- smartphone sensing --- XGBoost classifier --- railway maintenance --- vehicle trajectory prediction --- license plate data --- trip chain --- turning state transit --- route choice behavior --- real world experiment --- Intelligent Transportation Systems (ITS) --- advanced traveler information systems (ATIS) --- connected vehicles --- particle filter --- Kalman filter --- road safety --- travel time information system --- safety performance function --- bicycle sharing systems --- public transport systems --- data-driven classification of trips --- BSS underlying network --- trip index --- automatic rail-surface-scratch recognition and computation --- triangulation algorithm --- complete closed mesh model --- online rail-repair --- autonomous vehicle --- obstacle avoidance --- artificial potential field --- model predictive control --- human-like --- variable speed limits --- intelligent transportation systems --- ITS services --- driving simulator studies --- traffic modelling --- surrogate safety measures --- driving safety --- driving emotions --- driving stress --- lifestyle --- sensors --- heart rate --- plate scanning --- low-cost sensor --- sensor location problem --- traffic flow estimation