Climate change is being fought with policies and measures implemented worldwide to reduce Greenhouse Gases (GHG). One of these policies is to reduce the use of fossil fuels because they accelerate climate change and harm human health through pollution. The automotive industry is a significant player in this transition. The automotive industry is shifting from vehicles powered by a fossil energy powertrain to one that consumes clean energy. The industry is moving towards electric mobility, but this technology has a disadvantage compared to traditional mobility. Electric Vehicles (EVs) need more time to regain their range than conventional vehicles (CV) that use fossil fuels, a massive reason why users do not adopt this technology. This thesis focuses on an optimised charging process to make EVs a realistic alternative for user transport and meet the Paris Climate Accords goals. To this end, a study has been carried out analysing various points and technologies such as Electro-Mobility (e-mobility), recharging technologies, or Cloud-based systems that could optimise the charging process and have a scalable, scalable system that all EVs can use. This project has used the Internet of Things (IoT) to enable EVs to communicate with charging stations in a reliable manner with a scalable system. In addition, it has been possible to store data in the cloud, where it is processed in real-time, and mathematical equations have been developed in the python programming language. The user has access to the information through an interface that allows them to check the most optimal charging points (CPs) in different categories such as total charging time, distance from the various stations, charging total price and the CPs services. These technologies used in this thesis will contribute to optimising the charging process, leaving the door open to future developments in the e-mobility field. / <p>Universidad de Granada, Spanien och Universidad de Málaga, Spanien</p>
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-21211 |
| Date | January 2022 |
| Creators | Cortés, Jorge Lorenzo, Casero Sánchez, Alejandro |
| Publisher | Högskolan i Skövde, Institutionen för ingenjörsvetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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