Operation modes of battery chargers for electric vehicles in the future smart grids

This paper presents an on-board bidirectional battery charger for Electric Vehicles (EVs), which operates in three different modes: Grid-to- Vehicle (G2V), Vehicle-to-Grid (V2G), and Vehicle-to-Home (V2H). Through these three operation modes, using bidirectional communications based on Information and Communication Technologies (ICT), it will be possible to exchange data between the EV driver and the future smart grids. This collaboration with the smart grids will strengthen the collective awareness systems, contributing to solve and organize issues related with energy resources and power grids. This paper presents the preliminary studies that results from a PhD work related with bidirectional battery chargers for EVs. Thus, in this paper is described the topology of the on-board bidirectional battery charger and the control algorithms for the three operation modes. To validate the topology it was developed a laboratory prototype, and were obtained experimental results for the three operation modes.

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.

Multifunctional converter to interface renewable energy sources and electric vehicles with the power grid in smart grids context

This paper proposes a multifunctional converter to interface renewable energy sources (e.g., solar photovoltaic panels) and electric vehicles (EVs) with the power grid in smart grids context. This multifunctional converter allows deliver energy from the solar photovoltaic panels to an EV or to the power grid, and exchange energy in bidirectional mode between the EV and the power grid. Using this multifunctional converter are not required multiple conversion stages, as occurs with the traditional solutions, where are necessary two power converters to integrate the solar photovoltaic system in the power grid and also two power converters to integrate an off-board EV battery charger in the power grid (dc-dc and dc-ac power converters in both cases). Taking into account that the energy provided (or delivered) from the power grid in each moment is function of the EV operation mode and also of the energy produced from the solar photovoltaic system, it is possible to define operation strategies and control algorithms in order to increase the energy efficiency of the global system and to improve the power quality of the electrical system. The proposed multifunctional converter allows the operation in four distinct cases: (a) Transfer of energy from the solar photovoltaic system to the power grid; (b) Transfer of energy from the solar photovoltaic system and from the EV to the power grid; (c) Transfer of energy from the solar photovoltaic system to the EV or to the power grid; (d) Transfer of energy between the EV and the power grid. Along the paper are described the system architecture and the control algorithms, and are also presented some computational simulation results for the four aforementioned cases. It is also presented a comparative analysis between the traditional and the proposed solution in terms of operation efficiency and estimated cost of implementation.

Towards automated test and validation of SIP solutions

IP networks are currently the major communication infrastructure used by an increasing number of applications and heterogeneous services, including voice services. In this context, the Session Initiation Protocol (SIP) is a signaling protocol widely used for controlling multimedia communication sessions such as voice or video calls over IP networks, thus performing vital functions in an extensive set of public and enter- prise solutions. However, the SIP protocol dissemination also entails some challenges, such as the complexity associated with the testing/validation processes of IMS/SIP networks. As a consequence, manual IMS/SIP testing solutions are inherently costly and time consuming tasks, being crucial to develop automated approaches in this specific area. In this perspective, this article presents an experimental approach for automated testing/validation of SIP scenarios in IMS networks. For that purpose, an automation framework is proposed allowing to replicate the configuration of SIP equipment from the pro- duction network and submit such equipment to a battery of tests in the testing network. The proposed solution allows to drastically reduce the test and validation times when compared with traditional manual approaches, also allowing to enhance testing reliability and coverage. The automation framework comprises of some freely available tools which are conveniently integrated with other specific modules implemented within the context of this work. In order to illustrate the advantages of the proposed automated framework, a real case study taken from a PT Inovação customer is presented comparing the time required to perform a manual SIP testing approach with the one time required when using the proposed auto- mated framework. The presented results clearly corroborate the advantages of using the presented framework.

An automated framework for the management of P2P traffic in ISP infrastructures

Peer-to-Peer (P2P) is nowadays a widely used paradigm underpinning the deployment of several Internet services and applications. However, the management of P2P traffic aggregates is not an easy task for Internet Service Providers (ISPs). In this perspective, and considering an expectable proliferation in the use of such ap- plications, future networks require the development of smart mechanisms fostering an easier coexistence between P2P applications and ISP infrastructures. This paper aims to contribute for such research efforts presenting a framework incorporating useful mechanisms to be activated by network administrators, being also able to operate as an automated management tool dealing with P2P traffic aggregates.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

OnBoard reconfigurable battery charger for electric vehicles with traction-to-auxiliary mode

This paper proposes a single-phase reconfigurable battery charger for Electric Vehicle (EV) that operates in three different modes: Grid-to-Vehicle (G2V) mode, in which the traction batteries are charged from the power grid; Vehicle-to-Grid (V2G) mode, in which the traction batteries deliver part of the stored energy back to the power grid; and in Traction-to-Auxiliary (T2A) mode, in which the auxiliary battery is charged from the traction batteries. When connected to the power grid, the battery charger works with sinusoidal current in the AC side, for both G2V and V2G modes, and also regulates the reactive power. When the EV is disconnected from the power grid, the control algorithms are modified and the full-bridge AC-DC bidirectional converter works as a full-bridge isolated DC-DC converter that is used to charge the auxiliary battery of the EV, avoiding the use of an additional charger to accomplish this task. To assess the behavior of the proposed reconfigurable battery charger under different operation scenarios, a 3.6 kW laboratory prototype has been developed and experimental results are presented.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational intelligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two illustrative Traffic Engineering methods are described, allowing to attain routing configurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.