Son yıllarda, içten yanmalı motorlu araçların neden olduğu çevresel sorunların oldukça artması nedeniyle elektrikli araç teknolojisindeki gelişmeler hız kazanmıştır. Ancak elektrikli araçlar henüz içten yanmalı motorlu araçların yerini tam olarak alamamıştır. Çünkü elektrikli araçların menzil ve şarj süresi sorunları bulunmaktadır. Bu iki sorun batarya parametresi ile ilgilidir. Bu yüzden elektrikli araçlarla ilgili çalışmalar batarya gruplarına yoğunlaşmıştır. Bu çalışmada elektrikli araçlar ve batarya sistemleri incelenmiştir. Ayrıca MATLAB/Simulink ortamında bir elektrikli araç için lityum iyon batarya paketi modellemesi yapılmıştır.

The noticeable dynamic development of electromobility poses new challenges for the energy industry and users of electric vehicles. One of these challenges is coping with the change in the way we refuel. In the case of electric vehicles, the batteries can also be charged via home electrical installations. The presence of a new, non-linear load with significant power may affect the quality parameters of electricity in this installation and therefore indirectly affect the operation of other loads. In order to investigate the possible impact of the electric vehicle charging process on these parameters, a number of measurements were carried out. This paper presents the results of observing voltage distortions in the installation as a result of the harmonics of the current supplying the AC/DC converter in the vehicle. The test results confirm the compliance of the voltage with the requirements of the standards; however, the large share of current harmonics requires the analysis of the anti-shock protections existing in the installation to ensure that they are effective when currents at higher frequencies flow. The research results may be a guide for designers and users of home electrical installations.

In today's world, internal combustion engine vehicles are widely used. These vehicles cause harmful emissions as they use fossil fuels for engine propulsion and vehicle movement. To address this issue, electric vehicles have been considered as a solution. In electric vehicles, electric motors are used instead of traditional internal combustion engines and the necessary electrical energy is supplied from battery packs. In this way, electric vehicles do not cause harmful emissions to the environment. If the energy required for electric vehicle charging stations is obtained from renewable energy systems, electric vehicles will be zero-emission vehicles. Battery packs, that provide energy for electric vehicles, typically consist of rechargeable Lithium-ion battery groups and they can be charged using fast charging technology. In this study, the future of transportation, electric vehicles and the standards and technologies used in electric vehicle charging stations have been examined. Additionally, an electric vehicle system has been designed using MATLAB/Simscape.

The widespread use of electric vehicles contributes significantly to environmental sustainability by reducing the use of fossil fuels. However, the increasing number of electric vehicles and the intense charging demand may cause negative impacts such as overloading, voltage fluctuations and energy supply-demand imbalances in electricity grids. In this paper, artificial intelligence-based methods applied for the management of the negative impacts of electric vehicles on the grid are discussed comprehensively and artificial intelligence approaches in the literature used to manage electric vehicle charging load are analysed. Among these approaches, energy management strategies based on charging demand forecasting, dynamic pricing, routing, charging scheduling and smart grid integration are analysed in detail. This paper summarises the latest innovative AI-based solutions developed to manage the charging load of electric vehicles, improve grid stability, increase charging service price prediction accuracies, maximise grid and user satisfaction, ensure load balance, reduce charging and operating costs, reduce energy consumption and optimise power flow. This paper contains comprehensive and qualified information about the bilateral (grid and user perspective) management algorithms of the charging load of electric vehicles.