Wind Energy Harnessing in a Railway Infrastructure: Converter Topology and Control Proposal

Long distances in the vicinities of railways are not exploited in terms of wind energy. This paper presents a scalable power electronics approach, aimed to harness the wind potential in a railway infrastructure. The key aspect of this proposal relies on both using the wind energy in the location, and the displaced air mass during the movement of a train along the railway, in order to produce electrical energy. Vertical Axis Wind Turbines (VAWT) are used in order to take advantage of the wind power, and widely used and well-known power converter techniques to accomplish the goal, showing MPPT techniques, parallelization of converters and power delivery with a Solid State Transformer (SST). Results are shown according simulations of the whole system, with and without train activity, resulting that 30.6 MWh of the energy could be generated without the train, and the energy generated with the assistance of the train could reach 32.3 MWh a year. Concluding that almost the 10% of the energy could be provided by the assistance of the train.The authors thank the support from the Basque Government (project ELKARTEK Twin KK-2020/00050, GISEL Research Group IT1191-19 and PIBA_2019_1_0098), as well as from the University of the Basque Country UPV/EHU (COLAB19/02, under Grant PES16/31)

Empirical calendar ageing model for electric vehicles and energy storage systems batteries

Transport electrification and energy storage are considered part of the solution to decrease CO2 emissions from the energy and transport sectors. In this context, batteries can be a promising technology, since advances in the last few years have ensured a larger lifetime and better performance. Depending on actual use of the batteries, calendar ageing can be considered as the main origin of degradation in both transport electrification and energy storage since electric vehicles are parked 96 % of the time and battery energy storage stations (BESSs) can remain at a high State of Charge (SoC) for a long time along their lifetime. Therefore, a lifetime model or a degradation model of batteries is necessary to optimally develop an application of these in every sector. In this sense, this paper presents a calendar ageing model of a nickel-manganese-cobalt (NMC) battery, which is used in commercialised electric vehicles. The degradation model presented here is based on the Hermite Cubic Interpolation Polynomial (PCHIP) over an experimental results data set in combination with a power law for modeling the influence of the storing time. In this context, four fitting equations have been compared in search of the most appropriate time depending rate, and the accuracy of the most commonly used model was improved. The storing temperature and SoC have been found to be the most harmful factors in the degradation of these batteries by calendar ageing. The degradation model developed yields of an average root-mean-square error (RMSE) of 0.8 % in capacity fade (CF), while in power fade (PF), the average RMSE has been 2.3 %.The authors thank the Basque Government (project PIBA_2019_1_0098, KK-2022/00100 and GISEL research group IT1522-22) and the University of the Basque Country UPV/EHU (project COLAB19 and PES16/31) for their support

Optimización de la recarga del vehículo eléctrico considerando la degradación de baterías

239 p.La presente Tesis Doctoral propone una nueva metodología para integrar los vehículos eléctricos enchufables en las redes de baja tensión. La carga de vehículos eléctricos produce un impacto en la red de baja tensión como puede ser el aumento de pérdidas, la sobrecarga de líneas y transformadores, caídas de tensión, desequilibrios de tensión, etc., pero sobre todo produce una degradación en las baterías que equipan. Este último impacto dependerá enormemente del control de la carga empleado y será determinante en la cuantificación del coste de la misma.En este contexto, la presente tesis propone una nueva metodología óptima para evaluar y reducir al mínimo el coste económico de cada recarga, maximizando la vida útil de las baterías, y respetando siempre las limitaciones técnicas de la red a la que se conecta, sin renunciar a las necesidades del usuario.Para ello, se desarrolla un modelo de degradación basado en datos experimentales de una batería de vehículo eléctrico comercial. Dicho modelo considera diferentes variables, entre ellas la profundidad de descarga, el número de ciclos, la corriente media, el estado de carga de almacenamiento y la temperatura; las dos fuentes principales de degradación, como son el calendar aging y el cycle aging; y los dos principales efectos, a saber, el capaciy fade y el power fade. Este modelo es de gran utilidad en el desarrollo de diferentes herramientas para la evaluación de la rentabilidad de una batería en función del uso requerido (patrones de conducción, de recarga, etc.).Teniendo en cuenta todas estas consideraciones, la metodología propuesta propicia la integración de los vehículos eléctricos enchufables en las redes de distribución de baja tensión

Optimización de la recarga del vehículo eléctrico considerando la degradación de baterías

239 p.La presente Tesis Doctoral propone una nueva metodología para integrar los vehículos eléctricos enchufables en las redes de baja tensión. La carga de vehículos eléctricos produce un impacto en la red de baja tensión como puede ser el aumento de pérdidas, la sobrecarga de líneas y transformadores, caídas de tensión, desequilibrios de tensión, etc., pero sobre todo produce una degradación en las baterías que equipan. Este último impacto dependerá enormemente del control de la carga empleado y será determinante en la cuantificación del coste de la misma.En este contexto, la presente tesis propone una nueva metodología óptima para evaluar y reducir al mínimo el coste económico de cada recarga, maximizando la vida útil de las baterías, y respetando siempre las limitaciones técnicas de la red a la que se conecta, sin renunciar a las necesidades del usuario.Para ello, se desarrolla un modelo de degradación basado en datos experimentales de una batería de vehículo eléctrico comercial. Dicho modelo considera diferentes variables, entre ellas la profundidad de descarga, el número de ciclos, la corriente media, el estado de carga de almacenamiento y la temperatura; las dos fuentes principales de degradación, como son el calendar aging y el cycle aging; y los dos principales efectos, a saber, el capaciy fade y el power fade. Este modelo es de gran utilidad en el desarrollo de diferentes herramientas para la evaluación de la rentabilidad de una batería en función del uso requerido (patrones de conducción, de recarga, etc.).Teniendo en cuenta todas estas consideraciones, la metodología propuesta propicia la integración de los vehículos eléctricos enchufables en las redes de distribución de baja tensión

Electric Vehicle into the Grid: Charging Methodologies Aimed at Providing Ancillary Services Considering Battery Degradation

The necessity of transport electrification is already undeniable due to, among other facts, global Greenhouse Gas (GHG) emissions and fossil-fuel dependency. In this context, electric vehicles (EVs) play a fundamental role. Such vehicles are usually seen by the network as simple loads whose needs have to be supplied. However, they can contribute to the correct operation of the network or a microgrid and the provision of ancillary services and delay the need to reinforce the power lines. These concepts are referred to as Vehicle-to-Grid (V2G), Vehicle-to-Building (V2B) and Vehicle-to-Home (V2H). In paper, a deep classification and analysis of published charging strategies is provided. In addition, optimal charging strategies must minimise the degradation of the batteries to increase their lifetime, since it is considered that the life of a battery ends when its capacity is reduced by 20% with respect to its nominal capacity. Therefore, an optimal integration of EVs must consider both grid and batteries impact. Finally, some guidelines are proposed for further research considering the current limitations of electric vehicle technology. Thus, these proposed guidelines are focused on V2G optimal management, enabling new business models while keeping economic viability for all parts involved.The authors acknowledge the support from the Provincial Council of Gipuzkoa (project Etorkizuna Eraikiz 2019 DGE19/03), the Basque Government (GISEL Research Group IT1083-16), and the University of the Basque Country UPV/EHU (PES16/31 and PES17/08)

Analysis of the Current Electric Battery Models for Electric Vehicle Simulation

This article belongs to the Section Electric Vehicles.Electric vehicles (EVs) are a promising technology to reduce emissions, but its development enormously depends on the technology used in batteries. Nowadays, batteries based on lithium-ion (Li-Ion) seems to be the most suitable for traction, especially nickel-manganese-cobalt (NMC) and nickel-cobalt-aluminum (NCA). An appropriate model of these batteries is fundamental for the simulation of several processes inside an EV, such as the state of charge (SoC) estimation, capacity and power fade analysis, lifetime calculus, or for developing control and optimization strategies. There are different models in the current literature, among which the electric equivalent circuits stand out, being the most appropriate model when performing real-time simulations. However, impedance models for battery diagnosis are considered very attractive. In this context, this paper compares and contrasts the different electrical equivalent circuit models, impedance models, and runtime models for battery-based EV applications, addressing their characteristics, advantages, disadvantages, and usual applications in the field of electromobility. In this sense, this paper serves as a reference for the scientific community focused on the development of control and optimization strategies in the field of electric vehicles, since it facilitates the choice of the model that best suits the needs required.The authors thank the support from the Gipuzkoa Provincial Council (project Etorkizuna Eraikiz 2019 DGE19/03), the Basque Government (GISEL research group IT1083-16), as well as from the University of the Basque Country UPV/EHU (PES16/31 and PES17/08)