A Coordinated Battery Swapping Service Management Scheme Based on Battery Heterogeneity

The service management based on battery heterogeneity has become an increasingly important research problem in battery swapping technology. In this article, with the method of bipartite matching, we first theoretically analyze the offline optimization problem of battery swapping service under battery heterogeneity. Nevertheless, the information of global view used in offline optimization solutions cannot be known in advance during real-time operation. To address the disadvantage, an online framework comprising several subprocedures is proposed for heterogeneous battery implementation. First, by incorporating battery swapping station (BSS) local status such as charging and waiting queue of heterogeneous batteries, a charging slot allocation mechanism is designed. Utilizing the proposed allocation method, the charging priority is determined by the proportion of heterogeneous batteries demand, so as to guarantee charging fairness. Second, with the help of reservation information, the proposed allocation method can further be improved by predicting the future arrival distribution of heterogeneous types of electric vehicles. Third, according to the service demand prediction based on long short-term memory neural network, joint optimization of BSS-selection and charging cost can be achieved by charging power adjustment. Simulation results indicate the desirable performance of the proposed scheme in balancing the demands of multiparty participators.