Browsing by Keyword "Electric vehicles"
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Item Algorithm development for night charging electric vehicles optimization in big data applications(2017) Alvaro-Hermana, Roberto; Fraile-Ardanuy, Jesús; Merino, Julia; Tecnalia Research & InnovationIn this paper a night charging method that optimizes the recharging process of electric vehicles (EVs) depending on hourly energy price in a peer to peer (P2P) energy trading system is presented. This algorithm determines how much energy should be recharged in the battery of each EV and the corresponding time slot to do it, avoiding the discontinuities in the charging process and considering the users’ personal mobility constraints.Item Business and services models for electric vehicles(Electri-City.mobi, 2012-11-21) Madina, Carlos; Coppola, Giovanni; Schumann, Detlef; Hartung, Patrice; Zabala, EduardoThis paper introduces the approach for the business models analysis for electric vehicles, as followed in the FP7 EU-funded Green eMotion project. The main goal of Green eMotion is to enable a mass deployment of electric mobility in Europe. For that purpose, Green eMotion will connect ongoing regional and national electric mobility initiatives leveraging the results and comparing different technology approaches to ensure the best solutions prevail for the European market. A virtual marketplace will be created to enable the different actors to interact and to allow for new highvalue transportation services as well as electric vehicle (EV) user convenience in billing (EU Clearing House). In addition, the Green eMotion project will demonstrate the integration of electric mobility into electricity networks and contribute to the improvement and development of new and existing standards for electric mobility interfaces. In order to facilitate large-scale EVs roll-out in terms of social acceptance, commercial viability and system/environmental impact, the most suited business models should be identified and assessed according to a methodology taking into account all economic transactions between the different participating stakeholders.Item Control of dual three-phase IPMSM drive with cascaded DC-link capacitors for third generation EV(IEEE, 2021) Sierra-Gonzalez, Andres; Pescetto, Paolo; Trancho, Elena; Ibarra, Edorta; Pellegrino, Gianmario; Alvarez-Gonzalez, Fernando; Tecnalia Research & Innovation; POWERTRAINIn this work, a dual three-phase Interior Permanent Magnet Synchronous Machine (IPMSM) drive connected to a high voltage DC/DC converter (800 V) at its input is considered for electric vehicle (EV) applications. The drive is constituted by two cascaded three-phase inverters, enabling fast charging capabilities. In this particular configuration, balancing the input voltages of the two inverters is mandatory during operation. A novel control approach that not only provides such voltage balancing but also considers the cross-coupling effects of the dual-three phase IPMSM is proposed, guaranteeing an adequate torque regulation through the whole operation range of the drive. Simulation results, generated by means of a high fidelity platform, are provided to validate the proposed approach. Additionally, preliminary experimental results are also included.Item Economic Impact of Distribution Grid Operation Scenarios for the Integration of Electric Vehicles(2014-12-03) Madina, Carlos; Zabala, Eduardo; Rodríguez-Sánchez, Raúl; Turienzo, Elena; Lopez, Jose Antonio; Tecnalia Research & InnovationElectric Vehicles (EVs) will become an important part of the transport system in Europe and can thus create a number of benefits in term of oil dependence reduction, air quality improvement and trade balance enhancement. However, they can also become a burden for distribution system operator (DSOs) if they charge in an uncontrolled way. In addition, the increasing deployment of renewable energy sources (RES) and other distributed energy resources (DER) are making the distribution grid planning more complicated than in the past, when consumers were considered to be passive elements and grid was dimensioned to meet peak demand. PlanGridEV project proposes new planning procedures, which take into account the possibility to manage consumers’ electricity demand, including the charging process of EVs, both to better integrate DER and to more efficiently plan the investments in the distribution grid. The planning rules will be validated by carrying out four test beds, which will serve as an input for assessing the economic performance of four scenarios, representing four theoretical alternatives for distribution grid planning. Different services that EVs can provide to DSOs and other actors in the e-mobility ecosystem will be analysed in each scenario. Then, a grid planning tool will be developed to help DSOs consider EVs and demand and other demand response (DR) capabilities when planning distribution grid extension.Item Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles(2019-02) Dendaluce Jahnke, Martin; Cosco, Francesco; Novickis, Rihards; Pérez Rastelli, Joshué; Gomez-Garay, Vicente; Tecnalia Research & Innovation; CCAMThe combination of machine learning and heterogeneous embedded platforms enables new potential for developing sophisticated control concepts which are applicable to the field of vehicle dynamics and ADAS. This interdisciplinary work provides enabler solutions -ultimately implementing fast predictions using neural networks (NNs) on field programmable gate arrays (FPGAs) and graphical processing units (GPUs)- while applying them to a challenging application: Torque Vectoring on a multi-electric-motor vehicle for enhanced vehicle dynamics. The foundation motivating this work is provided by discussing multiple domains of the technological context as well as the constraints related to the automotive field, which contrast with the attractiveness of exploiting the capabilities of new embedded platforms to apply advanced control algorithms for complex control problems. In this particular case we target enhanced vehicle dynamics on a multi-motor electric vehicle benefiting from the greater degrees of freedom and controllability offered by such powertrains. Considering the constraints of the application and the implications of the selected multivariable optimization challenge, we propose a NN to provide batch predictions for real-time optimization. This leads to the major contribution of this work: efficient NN implementations on two intrinsically parallel embedded platforms, a GPU and a FPGA, following an analysis of theoretical and practical implications of their different operating paradigms, in order to efficiently harness their computing potential while gaining insight into their peculiarities. The achieved results exceed the expectations and additionally provide a representative illustration of the strengths and weaknesses of each kind of platform. Consequently, having shown the applicability of the proposed solutions, this work contributes valuable enablers also for further developments following similar fundamental principles.Item An energy efficient intelligent torque vectoring approach based on fuzzy logic controller and neural network tire forces estimator(2021-01-13) Parra, Alberto; Zubizarreta, Asier; Pérez, Joshué; Tecnalia Research & Innovation; CCAMIn electric vehicles (EVs) with multiple motors, torque vectoring (TV) control can effectively enhance the cornering response and safety. Moreover, TV systems can also improve the overall efficiency through an optimal torque distribution that also considers the power consumption. For such a complex control system with multiple objectives, intelligent control techniques have demonstrated to be one of the best alternatives. However, the works proposed in the literature do not handle both vehicle dynamics behavior and energy efficiency, and generally do not consider the real-time implementability of the developed controllers. To overcome the aforementioned isues, in this work, a novel torque vectoring approach is proposed, which uses a neural network-based vertical tire forces estimator and considers the regenerative braking capabilities of EVs. Moreover, the implementability of the controller in a heterogenous (FPGA and microcontroller) automotive suitable system on chip is addressed, ensuring its real-time capabilities. For the sake of validating the proposed approach, a set of experiments have been carried out in a hardware in the loop setup. The performance of the proposed TV approach has been compared with other two TV approaches from the literature, evaluating them in several challenging manoeuvres in high and low tire-road friction coefficient scenarios. Results show that the proposed approach not only is able to enhance the vehicle dynamics behavior but also to decrease the energy consumption about 13%.Item Evolution FP7 funded project: body structure design strategies using new composite and aluminium materials and enabled technologies(InderScience, 2018-04-20) Mangino, Enrico; Alcalde, Estibaliz; Maestro, César; Di Paolo, Francesca; DeClaville Christiansen, Jesper; Sanporean, Catalina Gabriela; Deverill, John P.; Cischino, Elena; Elizetxea, Cristina; Lopez, Iratxe; Vuluga, Zina; Kirpluks, Mikelis; Cabulis, PeterisBased on Pininfarina Nido EV concept, EVolution aims to reduce the vehicle weight through new materials and process technologies, focused on five demonstrators: underbody, front crossbeam, mechanical subframe, shotgun system and door. This paper refers to body structure design strategies using new composite, Al materials and enabled technologies, focusing in particular on demonstrators design and manufacturing. The new front crossbeam geometry of the front shell is adapted starting from the Nanotough design, while the rear shell is specific for EVolution. The subframe demonstrator is redesigned to fulfil mechanical requirements of the part and manufacturing feasibility either. The EVolution door concept consists of two semistructural composite skins including a structural Al frame. The underbody is conceived through an integrated approach, optimising each element for its function. The shotgun component is designed to link parts obtained with different manufacturing technologies and several aluminium alloys in one single component: the structural node demonstrator.Item Methodology for assessing electric vehicle charging infrastructure business models(2016-02-01) Madina, Carlos; Zamora, Inmaculada; Zabala, Eduardo; POWER SYSTEMS; Tecnalia Research & InnovationThe analysis of economic implications of innovative business models in networked environments, as electro-mobility is, requires a global approach to ensure that all the involved actors obtain a benefit. Although electric vehicles (EVs) provide benefits for the society as a whole, there are a number of hurdles for their widespread adoption, mainly the high investment cost for the EV and for the infrastructure. Therefore, a sound business model must be built up for charging service operators, which allows them to recover their costs while, at the same time, offer EV users a charging price which makes electro-mobility comparable to internal combustion engine vehicles. For that purpose, three scenarios are defined, which present different EV charging alternatives, in terms of charging power and charging station ownership and accessibility. A case study is presented for each scenario and the required charging station usage to have a profitable business model is calculated. We demonstrate that private home charging is likely to be the preferred option for EV users who can charge at home, as it offers a lower total cost of ownership under certain conditions, even today. On the contrary, finding a profitable business case for fast charging requires more intensive infrastructure usage.Item Optimal coordination of electric vehicle charging and photovoltaic power curtailment in unbalanced low voltage networks: An experimental case: An experimental case(2022) Cortés Borray, Andrés Felipe; Rauma, Kalle; Torres, Esther; Tecnalia Research & Innovation; POWER SYSTEMSThis study introduces a quadratic programming-based optimisation method to coordinate electric vehicle (EV) charging and photovoltaic (PV) curtailment in unbalanced low voltage (LV) networks. The proposed model is defined as a convex model that guarantees the optimal global solution of the problem avoiding the complexity of non-linear models and surpassing the limitations of local solutions derived from meta-heuristics algorithms reported in the literature. The coordination is carried out through a centralised controller installed at the header of the LV feeder. The objective of the proposed strategy is to minimise the power curtailment of all PV systems and maximise the power delivered to all EVs by optimising at every time step a suitable setpoint for the PV units and the charging rate of each EV connected without surpassing network constraints. A new energy-boundary model is also proposed to meet the energy requirements of all EVs, which is based on a recurrent function that depends on the arrival-and-desired energy states of the vehicle to compute its charging trajectory optimally. The effectiveness of the proposed coordination strategy was successfully proven through three scenarios in a laboratory environment, making use of two commercial EVs and a PV inverter in a Power Hardware-in-the-Loop setup.Item Optimal coordination of PV active power curtailment and evs charging among aggregators(2020-10-15) Borray, Andrés Felipe Cortés; Merino, Julia; Torres, Esther; Mazón, Javier; Tecnalia Research & InnovationWith the growing adoption of electric vehicles (EVs) and residential photovoltaic (PV) systems around the world, the distribution system operators (DSOs) are facing several technical challenges on their network planning and operation, particularly on low-voltage grids. As the aggregators are intermediary actors at that system level, they are a promising figure to coordinate these devices in an aggregated manner to help to mitigate adverse effects like overloading of network assets. However, to do so, proper coordination techniques among these entities and the DSO should be developed to avoid further investments in new network assets. In this context, a centralised coordination strategy among aggregators at the DSO level is proposed. By employing a linear programming model, the optimal export limit of PV and charging profile for each aggregator is dictated by the DSO, maintaining the operational limits of the network assets. A case study on two aggregators with moderate and critical penetration levels was carried out. Results show that, by controlling the aggregated export limit of PV power and the aggregated charging rate of EVs, high penetration levels can be integrated into current networks with minor or no need for reinforcing network infrastructure.Item Optimized and enhanced grid architecture for electric vehicles in Europe(2017-02-01) Übermasser, Stefan; Rodríguez Sanchez, Raúl; Madina, Carlos; Böcker, Stefan; Glancy, Mark; O’Callaghan, Eoghan; Silvestre, Luís; Voit, Stefan; Gaul, Armin; Odena Bultó, Gemma; Hribernik, Wolfgang; Tecnalia Research & Innovation; POWER SYSTEMSFor an optimized large-scale roll-out of EVs in Europe whilst at the same time maximizing the potential of DER integration, an optimized and enhanced grid architecture for EVs in Europe has to be considered. The work in this paper is addressing this topic and summarizing the corresponding project findings. The aim of this approach is to provide a framework for the further investigation of selected use cases which allows implementing and comparing scenarios of different DSOs. Following a Smart Grid approach, the developed grid architecture implements energy grid entities and ICT components. The general framework was described including all its relevant clusters and indicating related entities. The network types used for this architecture are following the SGAM and Smart Grid Standards Map approach. A so-called “Smart Grid Connection Point”, which is a generic system interface, is used in this work to allow a more simplified graphical architecture model and increase its readability. Similar to the concept and purpose of the Smart Grid Connection Point, also the principle of an integration bus for entity clusters was introduced. From the Integration bus, the information from/to external systems passes through the Smart Grid Connection Point using one of a range of possible technological options. The position of EVs charging infrastructure within the framework is defined at the border between the domains DERs (generation) and consumption, which takes into account future V2G scenarios, where EVs may act as consumption and generation devices. EVSEs and DERs may be connected as standalone systems directly to the grid, or indirectly as part of one of the clusters at the customer premises domain which refers to the three location-wise types of charging, public, semi-public and private charging. Regarding controlled charging of EVs this optimized architecture allows a variety of different local, distributed or aggregated options which may involve different types of actors.Item PM-Assisted Synchronous Reluctance Machine Flux Weakening Control for EV and HEV Applications(2017-08-31) Trancho, Elena; Ibarra, Edorta; Arias, Antoni; Kortabarria, Inigo; Jurgens, Jonathan; Marengo, Luca; Fricasse, Antonio; Gragger, Johannes; POWERTRAINIn this manuscript, a novel robust torque control strategy for Permanent Magnet Assisted Synchronous Reluctance Machine drives applied to electric vehicles and hybrid electric vehicles is presented. Conventional control techniques can highly depend on machine electrical parameters, leading to poor regulation under electrical parameters deviations or, in more serious cases, instabilities. Additionally, machine control can be lost if field weakening is not properly controlled and, as a consequence, uncontrolled regeneration is produced. Thus, advanced control techniques are desirable to guarantee electric vehicle drive controllability in the whole speed/torque operation range and during the whole propulsion system lifetime. In order to achieve these goals, a combination of a robust second order current based Sliding Mode Control and a Look- up Table/Voltage Constraint Tracking based hybrid Field Weakening control is proposed, improving the overall control algorithm robustness under parameter deviations. The proposed strategy has been validated experimentally in a full scale automotive test bench (51 kW prototype) for being further implemented in real hybrid and electric vehicles.Item REDUCCIÓN DEL IMPACTO DE VEHÍCULOS ELÉCTRICOS A TRAVÉS DE UNA PLATAFORMA DE ECONOMÍA COLABORATIVA(Grupo Tecma Red S.L., 2016) Alvaro-Hermana, Roberto; Merino, Julia; Fraile-Ardanuy, José Jesús; Castaño, SandraEn este trabajo se presenta una nueva forma de reducir el impacto de la recarga de vehículos eléctricos (VE), basado en aplicaciones de economía colaborativa. La propuesta consiste en que VEs con excedente de energía almacenada en sus baterías puedan vender energía a aquellos VEs que requieran recargar sus baterías durante el día y que estén aparcados en la misma zona y a la misma hora. A través del mercado propuesto, es posible reducir significativamente el coste de la recarga a aquellos usuarios que necesitan recargar fuera del horario nocturno (hasta un 70% dependiendo de la situación) y reducir también el impacto de la recarga sobre la red, puesto que dicha recarga se realiza intercambiando la energía entre vehículos aparcados en la misma zona, sin necesidad de estar conectados a la red eléctrica.Item A review of the population-based and individual-based approaches for electric vehicles in network energy studies(2020-12) Cortés Borray, Andrés Felipe; Merino, Julia; Torres, Esther; Mazón, Javier; Tecnalia Research & InnovationThe growing trend of introducing electric vehicles (EVs) into power systems to reduce the environmental emissions in the transport sector is gaining significant attention among electrical power system agents for two reasons: the potential grid services the EVs can offer in an aggregated manner and the possible undesirable effects of massive integration in grid operation that can increase the requirement for investment in new assets. In this context, the aggregator is the representative entity that needs to maximise the benefits in the management of these sizeable quantities of vehicles while fulfilling the requirements of grid services requested by the distribution system operator. In this study, we review the concept of EV aggregators and their potential services to the distribution network. Several studies related to EVs aggregation modelling have been analysed and classified into three groups: individual-based, population-based, and hybrid approaches. We present the current status of EVs aggregation modelling as well as future research trends. Furthermore, we discussed the performance comparison of EVs models from several manufacturers utilised in network integration studies, likewise the most relevant databases and surveys. Finally, we arranged and annexed the most relevant mathematical expressions of the reviewed approaches, thereby simplifying the comprehension of the methods.Item Using Dynamic Neural Networks for Battery State of Charge Estimation in Electric Vehicles(2018) Jiménez-Bermejo, David; Fraile-Ardanuy, Jesús; Castaño-Solis, Sandra; Merino, Julia; Alvaro-Hermana, Roberto; Tecnalia Research & InnovationDue to urban pollution, transport electrification is being currently promoted in different countries. Electric Vehicles (EVs) sales are growing all over the world, but there are still some challenges to be solved before a mass adoption of this type of vehicles occurs. One of the main drawbacks of EVs are their limited range, for that reason an accurate estimation of the state-of-charge (SOC) is required. The main contribution of this work is the design of a Nonlinear Autoregressive with External Input (NARX) artificial neural network to estimate the SOC of an EV using real data extracted from the car during its daily trips. The network is trained using voltage, current and four different battery pack temperatures as input and SOC as output. This network has been tested using 54 different real driving cycles, obtaining highly accurate results, with a mean squared error lower than 1e-6 in all situations