An overview on charging tariff schemes and incentives: the eCharge4Drivers project

Abstract This paper aims to provide an overview of the charging tariffs and e-mobility schemes adopted in different EU cities based on a survey conducted within the EU project eCharge4Drivers. The outcomes of the survey are presented and analysed in order to extract a generalised tariffication formula which allows any eMSPs or CPOs to explore different options to overcome the issues that might be affecting their current CP management strategy.

Authors: Evangelos Karfopoulos, Jaume Roca, Jaume Mata, Angel Lopez, Villy Portouli, Angelos Amditis

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Electric Vehicles Routing Including Smart-Charging Method and Energy Constraints

Abstract This paper presents an optimization-based approach for the Electric Vehicle Routing Problem considering Smart-Charging methods. The objective, based on the application of the model, is to obtain the shortest route for each of the electric vehicles that have to deliver freight to a set of customers minimizing the charging/discharging cost. Based on the Smart-Charging method, in which vehicles can charge/discharge energy from/to the grid, the power grid limits, and balancing needs are considered. In this way, both the charging points and the energy districts are prevented from exceeding the maximum allowed energy peak. A real case study in the Apulia Italian region (Italy) shows the effectiveness of the proposed optimization model.

Authors: María A. del Cacho Estil-les, Maria Pia Fanti, Agostino Marcello Mangini, Michele Roccotelli

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Small-Signal Average Switch Modeling and Dual-Loop Control of Bidirectional Integrated Converter for G2V and V2G Applications in Battery EVs

Abstract This paper proposes a small signal modeling approach of a bidirectional integrated converter configuration, which utilizes the traction inverter, motor windings and interleaved DC/DC converter for charging applications. This modeling technique represents the power electronic converters (AC/DC and DC/DC) as a transfer function that facilitates both Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) operations. During the G2V mode, the traction inverter converts into an AC/DC converter, while during the V2G mode, it operates as a DC/AC inverter, and the 3-phase interleaved DC/DC converter operates in buck and boost modes for the G2V and V2G operations, respectively. Moreover, the controller design based on the plant transfer functions is also a focal point of this paper. The inner current and outer voltage loop controllers of the DC/DC converter are designed based on the k-factor approach. For DC- link voltage control of the AC/DC converter, a dual loop control approach is adopted. Finally, the performance of both control systems has been validated via performance comparison between switch- based model and small-signal average system model in MATLAB/Simulink®.

Authors: Shahid Jaman, Sajib Chakraborty, Mohammed El Baghdadi, Thomas Geury, Omar Hegazy

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Digital Twin in Intelligent Transportation Systems

Abstract This study reviews the research works published in the last five years on Digital Twin (DT) technology for intelligent transportation systems, focusing on the use of DT in electromobility and autonomous vehicles. The review is carried out systematically, considering specific domains within intelligent transportation in which DT technology is applied in combination with Internet of Thing and 5G technologies. In addition, the paper discusses the current issues in electric vehicle services, such as tracking, monitoring, battery management systems, and connectivity, and how they can be addressed effectively through DT approaches.

Authors: Wasim Ali, Michele Roccotelli, Maria Pia Fanti

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Locating and Sizing Electric Vehicle Chargers Considering Multiple Technologies

Abstract In order to foster electric vehicle (EV) adoption rates, the availability of a pervasive and efficient charging network is a crucial requirement. In this paper, we provide a decision support tool for helping policymakers to locate and size EV charging stations. We consider a multi-year planning horizon, taking into account different charging technologies and different time periods (day and night). Accounting for these features, we propose an optimization model that minimizes total investment costs while ensuring a predetermined adequate level of demand coverage. In particular, the setup of charging stations is optimized every year, allowing for an increase in the number of chargers installed at charging stations set up in previous years. We have developed a tailored heuristic algorithm for the resulting problem. We validated our algorithm using case study instances based on the village of Gardone Val Trompia (Italy), the city of Barcelona (Spain), and the country of Luxembourg. Despite the variability in the sizes of the considered instances, our algorithm consistently provided high-quality results in short computational times, when compared to a commercial MILP solver. Produced solutions achieved optimality gaps within 7.5% in less than 90 s, often achieving computational times of less than 5 s.

Authors: Tommaso Schettini, Mauro dell’Amico, Francesca Fumero, Ola Jabali, Federico Malucelli

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An Enhanced Path Planner for Electric Vehicles Considering User-Defined Time Windows and Preferences

Abstract A number of decision support tools facilitating the use of Electric Vehicles (EVs) have been recently developed. Due to the EVs’ limited autonomy, routing and path planning are the main challenges treated in such tools. Specifically, determining at which Charging Stations (CSs) to stop, and how much the EV should charge at them is complex. This complexity is further compounded by the fact that charging times depend on the CS technology, the EV characteristics, and follow a nonlinear function. Considering these factors, we propose a path-planning methodology for EVs with user preferences, where charging is performed at public CSs. To achieve this, we introduce the Electric Vehicle Shortest Path Problem with time windows and user preferences (EVSPPWP) and propose an efficient heuristic algorithm for it. Given an origin and a destination, the algorithm prioritizes CSs close to Points of Interest (POIs) that match user inputted preferences, and user-defined time windows are considered for activities such as lunch and spending the night at hotels. The algorithm produces flexible solutions by considering clusters of charging points (CPs) as separate CSs. Furthermore, the algorithm yields resilient paths by ensuring that recommended paths have a minimum number of CSs in their vicinity. The main contributions of our methodology are the following: modeling user-defined time windows, including user-defined weights for different POI categories, creating CSs based on clusters of CPs with sufficient proximity, using resilient paths, and proposing an efficient algorithm for solving the EVSPPWP. To facilitate the use of our methodology, the algorithm was integrated into a web interface. We demonstrate the use of the web interface, giving usage examples and comparing different settings.

Authors: Maximiliano Cubillos, Mauro Dell’Amico, Ola Jabali, Federico Malucelli, Emanuele Tresoldi

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Development of Smart Charging Scheduling and Power Management Strategy of a PV-ESS based Scalable EV Charging Station

Abstract This paper describes smart power management and charging scheduling strategy for a multiple port electric vehicle (EV) charging station, connected to battery storage systems and renewable energy sources. The charging station can charge different types of EVs, like electric scooters and passenger cars at different power levels. The energy management optimizes the usage of the power sources to fulfill the charging demand by analyzing the overall load demand, the electricity tariff, and the information provided by the EV user. The station’s control system is set up to satisfy the charging demand primarily with a solar photovoltaic (PV) array and an energy storage system (ESS) as a battery. In the case of PV power generation and battery power shortage, it draws power from the grid to fulfill the charging demand. Additionally, a charging scheduling strategy is described in this paper in which the charging current setpoint for each charger is estimated by an optimization process in the local charger controller. The overall system management and charging scheduling are simulated and verified in the MATLAB/Simulink environment.

Authors: Shahid Jamana, Boud Verbruggea, Assel Zhaksylyka, Thomas Geurya, Mohamed El Baghdadia, Omar Hegazya

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Enhanced booking services for electric mobility
Abstract The transition from conventional vehicles to electric vehicles dictates the design and development of user-centric charging solutions aiming to facilitate the accessibility to as well as the usability of the charging network and improve the user’s charging experience. This paper presents the design of booking services to facilitate electric vehicle users to reserve a charging solution based on their charging preferences and needs. The objective is to develop interoperable booking services for static and mobile charging stations and battery swapping ones which will enhance the communication of user’s reservation requests to the Charging Point Operator, reduce the time wasted by EV users searching unoccupied charging stations and, consequently, improve EV user’s charging experience.

Authors: Maria Pia Fanti, Michele Roccotelli, Alessandro Rinaldi, Daniele Pagano, Raol Buqi, Stefano Persi, Montserrat Anglès, Evangelos Karfopoulos, Angelos Amditis

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Smart charging solutions for electric mobility

Abstract Transport electrification is an accelerating reality which should be complemented by the respective charging technologies and services for its successful deployment. While the electric vehicle (EV) market is now fully developed, users still have concerns about key areas of the electric vehicle charging infrastructure. The transition from conventional vehicles to electric ones dictates the design and development of user-centric charging solutions aiming to facilitate the accessibility to as well as the usability of the charging network and improve the user’s charging experience. This paper aims to highlight the critical issues of the electric mobility sector and analyse smart charging approaches supporting the large-scale implementation of electric cars.

Authors: Alessandro Rinaldi, Maria Pia Fanti, Michele Roccotelli, Evangelos Karfopoulos, Angelos Amditis, Villy Portouli

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Development and Validation of V2G Technology for Electric Vehicle Chargers Using Combo CCS Type 2 Connector Standards

Abstract Vehicle-to-Grid (V2G) technology is viewed as a viable solution to offer auxiliary power system services. Currently, V2G operation is only possible through DC chargers using the CHAdeMO connector with the necessary communication protocol. However, in Europe, for high-power DC charging (>50 kW), the Combined Charging Service (CCS) Type 2 is preferred over CHAdeMO. Therefore, this work presents the development of a V2G testing system with a Combo CCSType 2 charger including communication via the ISO 15118-2 protocol. The BOSCH passenger car with a 400 V battery pack is used to test and validate the technical feasibility of V2G charging via a Combo CCS Type 2 connector standard. The V2G feature is characterized in terms of efficiency, signal delay, response proportionality, magnitude accuracy and noise precision. A data driven V2G charger simulation model based on the real-time data is also developed in MATLAB/Simulink. The performance under various operating settings is presented in the outcomes, emphasizing the need for appropriate hardware calibration, and understanding while delivering standard-compliant grid control services using V2G technology. Finally, the results of the simulation model are compared with the real hardware results in terms of error, noise level and data magnitude accuracy.

Authors: Shahid Jaman, Boud Verbrugge, Oscar Hernandez Garcia, Mohamed Abdel-Monem, Blum Oliver, Thomas Geury, Omar Hegazy

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