Smart EV Charging to Mitigate Range Anxiety in VANET Backbone Guided by Named Data Networking and Block-Chain

Abstract

A interesting area of research for future connected car application is the development of an effective charging management system for on-the-go EVs, which is especially important given the inherent unpredictability in EV mobility. The main technological hurdles here are the necessity for intelligent decision making when choosing a CS and the related communication infrastructure for exchanging data between the grid and mobile EVs. Switching to electric vehicles has the potential to reduce pollution, vehicle maintenance expenses, and increasing gas prices (EVs). The range anxiety issue is a significant impediment to the rapid adoption of EV. Range anxiety can be alleviated by guaranteeing that a charging point will be found within the vehicle’s driving range, subject to other constraints such as waiting time, reliability, cost, and so on. In this research, we suggest building a P2P infrastructure on top of a VANET so that users may trade power with one another in a secure and reliable manner. Although the labour itself is decentralised, secure, and reliable, the associated financial transactions are not. The proposed framework for exchanging electric charge is based on the intersection of three concepts from the realm of automotive social networks: data connectivity, the bitcoin, and the anxiety of having insufficient battery power. We address reliability using an established collaborative paradigm rooted in the field of automotive social networks. Organizational verification previous to trading and encrypted parameter exchange provide safety. With the help of named data networking, reliable charging points may be located using a set of criteria. The simulation results demonstrate that the proposed technique decreases the amount of time it takes to complete an energy transaction by 17%, boosts coverage for picking charging providers by 13%, and decreases the amount of erroneous provider filtering by 18%.