With the continuous development of society and the economy and the popularization of the environmental protection concept, more and more people have begun to turn to electric vehicles. The application of electric vehicles can effectively avoid the damage caused by automobile fuel emissions to the surrounding environment and promote the development and utilization of new energy. However, the development of the electric vehicle industry has led to frequent accidents related to charging safety. In order to prevent accidents related to the charging safety of electric vehicles and ensure proper safety of passengers and people, the charging safety and charging safety protection methods of electric vehicles have become the research priorities for scholars. This paper reviewed the existing research results on the charging safety of electric vehicles, analyzed the influencing factors of the charging safety of electric vehicles, summarized the charging safety protection methods, and forecast the future research direction of charging safety, which has reference value and reference significance for the charging safety research of electric vehicles.

With the development of electric vehicles in China, the fault monitoring and warning systems for the charging process of electric vehicles have received the industry’s attention. A method for the monitoring and warning of electric vehicle charging faults based on a battery model is proposed in this paper. Through online estimation of the state of charge of the power battery model and battery electromotive force, parameters such as battery state of charge, voltage, and temperature can be adjusted in real time to simulate the charging response of the power battery, which can simulate power batteries of different types, specifications, and parameters. During the charging process, CAN (Controller Area Network) bus monitoring technology is used to receive and analyze the charging information of the charger, as well as the battery charging information and battery charging demand information. The charging response information simulated by the battery model is compared with the battery charging state information, and the charging state information of the charger is compared with the battery charging demand information to determine whether the charging process is normal. When it is judged that a charging fault occurs, a fault warning signal is sent. This method can identify more than 10 types of faults, including the failure of the BMS (Battery Management System) function. The comparison and analysis of actual charging accident data and power battery model data verifies the feasibility of the charging fault monitoring method proposed in this paper.

In February 2017, various new energy power generation enterprises and power users have attracted wide attention, after the issuance of the green power certificate and the issuance of the trial notice of voluntary subscription system. This paper makes a detailed investigation and analysis of the research status of green energy certificate trading at home and abroad. Then, based on the status quo of the company’s Internet of vehicles platform, green certificate generation and transaction architecture, transaction subject and transaction process are designed. Finally, based on the above basis, five green certificate trading business models, namely, trading platform mode, energy storage system mode, demand side management service mode, new business mode of electric vehicles and energy big data information service mode, are designed and analyzed.

Considering the time-space uncertainty of electric vehicle charging and changing demand, the uneven distribution and random diversity of charging stations, the big data cloud network is used to realize the real-time information interaction between charging and changing power station and electric vehicle. Based on the user demand orientation, an intelligent charging and changing optimization control strategy of “Vehicle-Road-Grid” integrating cloud vehicle operation data is proposed. Under the discrete electric vehicle charging demand, this strategy quickly organizes the supply information around the discrete point. On the basis of the minimum energy consumption between the electric vehicle charging request point and the supply point, considering the multi-dimensional factors such as the optimal interests of the electric vehicle users, the shortest waiting time for charging and changing, and the shortest driving distance for charging and changing, the multi-objective optimal configuration strategy is realized. The simulation results show that the strategy can stably select the charging and swapping scheme that best meets the actual needs of users, effectively improve the charging and swapping service experience of users, and enhance the adhesion and participation of users.