Optimal charging guidance strategy for electric vehicles based of mixed integer linear programming

As the global transition towards sustainable energy gains momentum, electric vehicles (EVs) are progressively replacing conventional fuel vehicles due to their utilization of clean energy. However, the rapid proliferation of EVs has led to a significant disparity between the number of vehicles and the availability of charging infrastructure, resulting in strain on the fast charging demands of EVusers. This research presents a novel EVcharging guidance strategy based on a mixed integer linear programming (MILP) model. The strategy establishes a time optimization modelfor EVs and charging piles, ensuring accurate and reliable data through meticulous cleaning and processing. Specific constraint conditions are defined for both EVs and charging piles, providing a structured framework for the guidance strategy. A simulation experiment is conducted in a designated area in Shanghai to evaluate the feasibility and practicality of the proposed approach. The objective of this study is to optimize the charging process, improve efficiency, and enhance user satisfaction.