An algorithm has been developed to calculate the number of charging infrastructures for a particular model of an electric vehicle when traveling between two points in a particular Interstate or US-Highway. The algorithm developed is essentially a search algorithm, incorporating many constraints in its formulation, including: range anxiety, rated mileage of the electric vehicle, population of the cities near the Interstate or US-Highway, and distance between origin city and destination city. A mathematical formula is modeled which calculates the real mileage of the electric vehicle which in turn is used in the search algorithm to determine the number of charging infrastructures to be installed.

All-Electric Vehicles (EV s ), BATTERY-powered EVs (BEVs), and plug-in hybrid EVs (PHEVS) are gaining market share and increasing in popularity with the buying public because the battery range (longer) and cost (lower) have reached sweet spots, the charging infrastructure is more robust, and concern with global climate change is high. In 2013, only 100,000 EVs were sold in the United States, but by 2022, approximately 800,000 have been purchased. A similar growth is seen in EV supply equipment (EVSE), i.e., EV charging stations, with 19,742 documented EV charging station locations in the United States in 2013 to 50,054 documented EV charging station locations, with approximately 130,000 ports, by the end of 2022.

Transitioning to electric vehicles (EV) can lower emission to mitigate the effects of climate change. Labeling an EV as completely `zero emission' is incorrect, as it ignores the emissions produced by the electricity generation used to charge the vehicle. The local electricity provider's energy mix will determine the emissions of an EV, and the fuel efficiency will determine economic savings. This paper will describe the development of two indices to gauge the regional environmental and economic impact of a new EV as compared to a new conventional internal combustion engine vehicle (ICEV) and hybrid electric vehicles (HEV), which will be used to create an interface for vehicle comparison in the future.

Determining the location for electric vehicles charging stations within a particular area of interest can be a key factor for a successful deployment. In this paper, an algorithm is developed which calculates the total number of charging stations for a particular model of electric vehicle in an Interstate and US-Highway in between two point cities. The algorithm takes into account design factors such as range anxiety, rated mileage of the electric vehicle, population of the cities near the Interstate and US-Highway, and distance between start-point and end-point. Two case studies have been shown for the state of Nebraska, USA with two different models of electric vehicles, to validate the algorithm.

A key factor for the successful deployment of electrified transportation is determining locations for the electric vehicle charging infrastructures and develop a proper charging infrastructure network. In this paper, an algorithm has been developed to identify locations of charging infrastructures when driving a particular Electric Vehicle (EV) on a particular Interstate or US-Highway in a given state. The algorithm utilizes the concept of a ruler whose length is determined using constraints that include: range anxiety, driver's driving habits and EV battery's State of Health (SoH), State of Charge (SoC), and Depth of Discharge (DoD). A case study is presented to demonstrate the application of this algorithm.