  The transition to electric vehicles (EVs) marks a pivotal shift in personal
mobility, driven by policy incentives and automotive innovations. However, the
expansion of EVs for long-distance travel is hindered by charging time
concerns, the sparse distribution of charging stations, and the worsening
waiting times due to congestion. The main objective of this work is two-fold:
1) first, to comprehensively analyze the existing public charging station
robustness and effectively strategize for the new ones, and 2) secondly, to
select the optimal chargers for long-distance journeys, by estimating the
waiting time from current traffic congestion. This is achieved by accompanying
effective EV charging strategies, pinpointing on the congestion points from the
existing traffic, and the robustness of the current charging station
infrastructure. Utilizing a real-time transportation and charging station
dataset in Texas, we identify optimal charger placement strategies to minimize
travel time by examining the congestion and charging time trade-offs. Our
findings suggest that maximizing the constant current phase during charging
enhances efficiency, crucial for long-distance travel. On the contrary, we also
explore the negative impact of congestion on travel times and we conclude that
sometimes it might be beneficial to exceed the constant current phase to avoid
the congested charging stations.
