## 2 Related Works
### EV Charging Stations  
The paper [8] talks about the various charging connector types and presents the comparison between the American and European standards. In addition, the paper discusses the various energy storage systems and how to incorporate them with charging stations. A useful ESS for linking fast EV charging stations might be considered a system that includes batteries and ultra-capacitors: the first for their high energy densities and the second for their high power density. The paper [9] presents a novel design strategy for rapid EV charging stations on a round motorway that takes into account spatial and temporal mobility habits. The planning approach is divided into three parts: an EV charging point spatial-temporal model, a placement determination model, and a capacity determination model. The established planning approach not only precisely determines the most ideal sites for EV charging stations while taking into account the travel convenience of EV users, but also minimizes the total cost. The paper [10] presents a data-driven robust EV charging infrastructure design strategy for residential car parks that takes into account the uncertainty of future EV charging behavior. For more realistic modeling of individual billing behavior, the suggested data-driven system makes use of real-world identity unit data and a queuing mechanism. The non-parametric estimation of charging power probability density may be derived by aggregating EV individuals. Following that, a distributionally robust optimization strategy for planning EV infrastructure under stochastic charging demand and maximum queue time is devised. The paper [11] proposes a business case for a battery switching station as well as an optimization model. Customers' complaints about long charging periods and range anxiety can be alleviated with the BSS. The BSS not only benefits users financially, but it also benefits the electrical system by participating in electricity markets and avoiding or postponing costly infrastructure changes. To be profitable, the BSS must ensure that the fees it collects, the risk it takes of failing to satisfy its clients, and the discounts it offers are all correctly constructed. The author of the paper [12] implements a periodic fluid model to represent charging operations at a BSS with time-varying demand for battery swap and time-varying prices for charging empty batteries, with the goal of determining the best battery purchasing and charging policy that best trades off battery investment cost and operating cost, including charging cost and customer waiting for cost. The authors of the [13] focus on a design concept and methodology for promoting EV adoption by automated battery pack switching at battery sharing stations as part of a battery sharing network, which would become an integral element of the smart grid. In addition, the advantages and disadvantages of traditional battery swapping were also discussed. The authors in [14] focus to address the issue of optimally locating charging stations in metropolitan environments. There are two optimization criteria used: maximization of reachable households and minimization of overall e-transportation energy cost. Mixed integer programming with linear and nonlinear energy-aware constraints is utilized to make decisions in both scenarios. A multi-objective optimization model is also offered, which addresses both criteria (number of reachable homes and transportation energy) at the same time. The author of the paper [15] describes the development of a universal inductive charger (UIC) for electric vehicles. The suggested UIC can provide a constant or regulated charging voltage to various EVs thanks to a wide range of magnetic coupling between the transmitting and receiving coils. Zero-voltage switching of the primary dc-ac inverter is universally realized in every charging cycle with a series-connected LC circuit.