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 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 evaluation and comparison of internal cluster validity indices is a critical problem in the clustering area. The methodology used in most of the evaluations assumes that the clustering algorithms work correctly. We propose an alternative methodology that does not make this often false assumption. We compared 7 internal cluster validity indices with both methodologies and concluded that the results obtained with the proposed methodology are more representative of the actual capabilities of the compared indices.

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Certain real-world applications present serious challenges to conventional neural-network design procedures. Blindly trying to train huge networks may lead to unsatisfactory results and wrong conclusions about the type of problems that can be tackled using that technology. In this paper a modular solution to power systems alarm handling and fault diagnosis is described that overcomes the limitations of "toy" alternatives constrained to small and fixed-topology electrical networks. In contrast to monolithic diagnosis systems, the neural-network-based approach presented here accomplishes the scalability and dynamic adaptability requirements of the application. Mapping the power grid onto a set of interconnected modules that model the functional behavior of electrical equipment provides the flexibility and speed demanded by the problem. After a preliminary generation of candidate fault locations, competition among hypotheses results in a fully justified diagnosis that may include simultaneous faults. The way in which the neural system is conceived allows for a natural parallel implementation.