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Expansion of EV Charging Network for Long-Distance Trips


In the past decade, electric vehicles (EVs) have drawn more customers due to their lower environmental footprint, and greater financial benefit compared to conventional vehicles. Many automotive market trends indicate that the EV sales rate has increased significantly in the past few years, and is forecasted to continue to grow in the upcoming years. On the other hand, to satisfy this rising demand, the number of charging stations has grown with greater user consumption. Among the different charger types, level 3 DC fast chargers are the most practical for EV users, in order to charge their vehicles efficiently and quickly. Depending on the vehicle’s battery capacity, one can charge their car in about half an hour. This type of charger becomes handy in dense population areas (e.g., apartments and condominiums), where access to a home charger is limited, and overall demand is higher compared to suburban areas. Despite the breakthroughs and improvements in charging availability, EVs still face significant hurdles; namely, the limited driving range. These current limitations are a deterrent for new potential customers, and it’s believed that ‘EV are not suitable for long-distance trips.’ However, the combination of an extended charging network, and fast chargers, could facilitate longer trips for users.


The existing literature on EVs and charging stations mainly focuses on urban trips, and developing a charging network corresponding to inter-city areas with a limited EV driving range. Moreover, developers design charging stations by focusing on transportation networks, or power distribution networks exclusively; whereas both networks are involved in developing an integrated charging infrastructure. In a recent study by UTRAIL at the University of Utah, a framework for allocating charging stations in the state of Utah was created which tries to capture most EV traffic demand, while distributing the power load on the distribution network evenly. This recent study uses a heuristic approach to find the optimal locations for chargers using scaled GPS trajectory data. Results show that the morning and afternoon peak hours are when the demand for charging is highest. With consideration given to power network constraints, the equivalent power load of charging sessions can be normalized. Assuming a 130-mile range of driving for the sample EV, 68% of the traffic could be powered by 12 stations all over the state. Sensitivity analysis of the driving range demonstrates that, increasing the range to 200 miles, could broaden coverage up to 89%. However, most available EVs with a higher driving range (more than 200 miles) are notably pricier than vehicles with a more limited range, which is also a barrier. The findings of this study also demonstrate that the available resources for charging facilities are not sufficient for the upcoming surge of EV users; as it will only cover 18% of the demand when the EV market share reaches 10%.



The development of an expanded network could bring more customers to EVs, and a more optimal charging network for distribution and transportation networks. Yet, the enlargement of the EV user base requires a comprehensive demand management plan for more efficient utilization of the available charging stations, based on the study of EV drivers’ behavior. Users’ behavior could help planners to find the travel alternatives that offer users the most payoffs. Providing an alternate charging plan through policies for travelers could reduce the average waiting time for charging in public stations. Furthermore, it could keep the distribution network in balance, so no power shortage will be experienced, and charger posts can operate under their capacity for a fast and consistent charging session. Meanwhile, the growing EV penetration rate entails updating the demand management plan, considering the changing behavior of users. The later framework includes a sustainable planning strategy that contemplates the long-term urban infrastructure development and policies, according to users’ travel behavior. The outcome of the proposed plan could improve accessibility, and lead to perspectives that are socially supported for allocating charging points for EV users in smart and connected urban areas.


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