Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

On-board electric vehicle battery charger with enhanced V2H operation mode

This paper proposes an on-board Electric Vehicle (EV) battery charger with enhanced Vehicle-to-Home (V2H) operation mode. For such purpose was adapted an on-board bidirectional battery charger prototype to allow the Grid-to-Vehicle (G2V), Vehicle-to-Grid (V2G) and V2H operation modes. Along the paper are presented the hardware topology and the control algorithms of this battery charger. The idea underlying to this paper is the operation of the on-board bidirectional battery charger as an energy backup system when occurs a power outages. For detecting the power outage were compared two strategies, one based on the half-cycle rms calculation of the power grid voltage, and another in the determination of the rms value based in a Kalman filter. The experimental results were obtained considering the on-board EV battery charger under the G2V, V2G, and V2H operation modes. The results show that the power outage detection is faster using a Kalman filter, up to 90% than the other strategy. This also enables a faster transition between operation modes when a power outage occurs.

Vehicle-to-anything application (v2anything app) for electric vehicles

This paper presents a mobile information system denominated as Vehicle-to-Anything Application (V2Anything App), and explains its conceptual aspects. This application is aimed at giving relevant information to Full Electric Vehicle (FEV) drivers, by supporting the integration of several sources of data in a mobile application, thus contributing to the deployment of the electric mobility process. The V2Anything App provides recommendations to the drivers about the FEV range autonomy, location of battery charging stations, information of the electricity market, and also a route planner taking into account public transportations and car or bike sharing systems. The main contributions of this application are related with the creation of an Information and Communication Technology (ICT) platform, recommender systems, data integration systems, driver profile, and personalized range prediction. Thus, it is possible to deliver relevant information to the FEV drivers related with the electric mobility process, electricity market, public transportation, and the FEV performance.

Smart charging management for electric vehicle battery chargers

This paper proposes a smart battery charging strategy for Electric Vehicles (EVs) targeting the future smart homes. The proposed strategy consists in regulate the EV battery charging current in function of the total home current, aiming to prevent overcurrent trips in the main switch breaker. Computational and experimental results were obtained under real-time conditions to validate the proposed strategy. For such purpose was adapted a bidirectional EV battery charger prototype to operate in accordance with the aforementioned strategy. The proposed strategy was validated through experimental results obtained both in steady and transient states. The results show the correct operation of the EV battery charger even under heavy load variations.

FPGA field oriented control of an axial flux motor-in-wheel

This paper presents the design and the prototype implementation of a three-phase power inverter developed to drive a motor-in-wheel. The control system is implemented in a FPGA (Field Programmable Gate Array) device. The paper describes the Field Oriented Control (FOC) algorithm and the Space Vector Modulation (SVM) technique that were implemented. The control platform uses a Spartan-3E FPGA board, programmed with Verilog language. Simulation and experimental results are presented to validate the developed system operation under different load conditions. Finally are presented conclusions based on the experimental results.

Field oriented control of an axial flux permanent magnet synchronous motor for traction solutions

Electric Vehicles (EVs) are increasingly used nowadays, and different powertrain solutions can be adopted. This paper describes the control system of an axial flux Permanent Magnet Synchronous Motor (PMSM) for EVs powertrain. It is described the implemented Field Oriented Control (FOC) algorithm and the Space Vector Modulation (SVM) technique. Also, the mathematical model of the PMSM is presented. Both, simulation and experimental, results with different types of mechanical load are presented. The experimental results were obtained using a laboratory test bench. The obtained results are discussed.

Comprehensive comparison of a current-source and a voltage-source converter for three-phase EV fast battery chargers

This paper presents a comprehensive comparison of a current-source converter and a voltage-source converter for three-phase electric vehicle (EV) fast battery chargers. Taking into account that the current-source converter (CSC) is a natural buck-type converter, the output voltage can assume a wide range of values, which varies between zero and the maximum instantaneous value of the power grid phase-to-phase voltage. On the other hand, taking into account that the voltage-source converter (VSC) is a natural boost-type converter, the output voltage is always greater than the maximum instantaneous value of the power grid phase-to-phase voltage, and consequently, it is necessary to use a dc-dc buck-type converter for applications as EV fast battery chargers. Along the paper is described in detail the principle of operation of both the CSC and the VSC for EV fast chargers, as well as the main equations of the power theory and current control strategies. The comparison between both converters is mainly established in terms of the total harmonic distortion of the grid current and the estimated efficiency for a range of operation between 10 kW and 50 kW.

A novel concept of unidirectional bridgeless combined boost-buck converter for EV battery chargers

This paper presents a novel concept of unidirectional bridgeless combined boost-buck converter for electric vehicles (EVs) battery chargers. The proposed converter is composed by two power stages: an ac-dc front-end converter used to interface the power grid and the dc-link, and a dc-dc back-end converter used to interface the dc-link and the batteries. The ac-dc converter is a bridgeless boost-type converter and the dc-dc converter is an interleaved buck-type converter. The proposed converter operates with sinusoidal grid current and unitary power factor for all operating power levels. Along the paper is described in detail the proposed converter for EV battery chargers: the circuit topology, the different stages describing the principle of operation, the power control theory, and the current control strategy, for both converters. Along the paper are presented several simulation results for a maximum power of 3.5 kW.

Predictive control of a current-source inverter for solar photovoltaic grid interface

Solar photovoltaic systems are an increasing option for electricity production, since they produce electrical energy from a clean renewable energy resource, and over the years, as a result of the research, their efficiency has been increasing. For the interface between the dc photovoltaic solar array and the ac electrical grid is necessary the use of an inverter (dc-ac converter), which should be optimized to extract the maximum power from the photovoltaic solar array. In this paper is presented a solution based on a current-source inverter (CSI) using continuous control set model predictive control (CCS-MPC). All the power circuits and respective control systems are described in detail along the paper and were tested and validated performing computer simulations. The paper shows the simulation results and are drawn several conclusions.

Three-phase current-source shunt active power filter with solar photovoltaic grid interface

This paper presents the proposal of a three phase current source shunt active power filter (CS-SAPF) with photovoltaic grid interface. The proposed system combines the compensation of reactive power and harmonics with the injection of energy from a solar photovoltaic array into the electrical power grid. The proposed equipment presents the advantage of giving good use to the current source inverter, even when the solar photovoltaic array is not producing energy. The paper describes the control system of the CS SAPF, the energy injection control strategy, and the current harmonics and power factor compensation strategy. Simulation results to assess the performance of the proposed system are also presented.

A taxonomy for the flexible job shop scheduling problem

This chapter aims at developing a taxonomic framework to classify the studies on the flexible job shop scheduling problem (FJSP). The FJSP is a generalization of the classical job shop scheduling problem (JSP), which is one of the oldest NP-hard problems. Although various solution methodologies have been developed to obtain good solutions in reasonable time for FSJPs with different objective functions and constraints, no study which systematically reviews the FJSP literature has been encountered. In the proposed taxonomy, the type of study, type of problem, objective, methodology, data characteristics, and benchmarking are the main categories. In order to verify the proposed taxonomy, a variety of papers from the literature are classified. Using this classification, several inferences are drawn and gaps in the FJSP literature are specified. With the proposed taxonomy, the aim is to develop a framework for a broad view of the FJSP literature and construct a basis for future studies.

Underwater acoustic modem with streaming video capabilities

Oceans have shown tremendous importance and impact on our lives. Thus the need for monitoring and protecting the oceans has grown exponentially in recent years. On the other hand, oceans have economical and industrial potential in areas such as pharmaceutical, oil, minerals and biodiversity. This demand is increasing and the need for high data rate and near real-time communications between submerged agents became of paramount importance. Among the needs for underwater communications, streaming video (e.g. for inspecting risers or hydrothermal vents) can be seen as the top challenge, which when solved will make all the other applications possible. Presently, the only reliable approach for underwater video streaming relies on wired connections or tethers (e.g. from ROVs to the surface) which presents severe operational constraints that makes acoustic links together with AUVs and sensor networks strongly appealing. Using new polymer-based acoustic transducers, which in very recent works have shown to have bandwidth and power efficiency much higher than the usual ceramics, this article proposes the development of a reprogrammable acoustic modem for operating in underwater communications with video streaming capabilities. The results have shown a maximum data-rate of 1Mbps with a simple modulation scheme such as OOK, at a distance of 20 m.

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.

Equidistribution for higher-rank Abelian actions on Heisenberg nilmanifolds

2010 Mathematics Subject Classification: Primary: 37C85, 37A17, 37A45; Secondary: 11K36, 11L07.

On the impact of overlapping access points in detecting node encounters

Data traces, consisting of logs about the use of mobile and wireless networks, have been used to study the statistics of encounters between mobile nodes, in an attempt to predict the performance of opportunistic networks. Understanding the role and potential of mobile devices as relaying nodes in message dissemination and delivery depends on the knowledge about patterns and number of encounters among nodes. Data traces about the use of WiFi networks are widely available and can be used to extract large datasets of encounters between nodes. However, these logs only capture indirect encounters between nodes, and the resulting encounters datasets might not realistically represent the spatial and temporal behaviour of nodes. This paper addresses the impact of overlapping between the coverage areas of different Access Points of WiFi networks in extracting encounters datasets from the usage logs. Simulation and real-world experimental results show that indirect encounter traces extracted directly from these logs strongly underestimate the opportunities for direct node-to- node message exchange in opportunistic networks.