@article{kavianipour_deploying_2023,
	title = {Deploying {Fast} {Charging} {Infrastructure} for {Electric} {Vehicles} in {Urban} {Networks}: {An} {Activity}-{Based} {Approach}},
	abstract = {This paper explores an important problem under the domain of network modeling, the optimal configuration of charging infrastructure for electric vehicles (EVs) in urban networks considering EV users’ daily activities and charging behavior. This study proposes a charging behavior simulation model considering different initial state of charges (SOC), travel distance, availability of home chargers, and the daily schedule of trips for each traveler. The proposed charging behavior simulation model examines the complete chain of trips for EV users as well as the interdependency of trips traveled by each driver. Then, the problem of finding the optimum charging configuration is formulated as a Mixed-Integer Nonlinear Programming that considers travel time and travel distance dynamics, the interdependency of trips made by each driver, limited range of EVs, remaining battery capacity for recharging, waiting time in queue, and the detour to access a charging station. This problem is solved using a metaheuristic approach for a large-scale case network. A series of examples are presented to demonstrate the model efficacy and explore the impact of energy consumption on the final SOC and the optimum charging infrastructure.},
	journal = {Transportation Research Record},
	author = {Kavianipour, Mohammadreza and Verbas, Omer and Rostami, Alireza and Soltanpour, Amirali and Gurumurthy, Krishna Murthy and Ghamami, Mehrnaz and Zockaie, Ali},
	year = {2023},
}

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The proposed charging behavior simulation model examines the complete chain of trips for EV users as well as the interdependency of trips traveled by each driver. Then, the problem of finding the optimum charging configuration is formulated as a Mixed-Integer Nonlinear Programming that considers travel time and travel distance dynamics, the interdependency of trips made by each driver, limited range of EVs, remaining battery capacity for recharging, waiting time in queue, and the detour to access a charging station. This problem is solved using a metaheuristic approach for a large-scale case network. A series of examples are presented to demonstrate the model efficacy and explore the impact of energy consumption on the final SOC and the optimum charging infrastructure.","journal":"Transportation Research Record","author":[{"propositions":[],"lastnames":["Kavianipour"],"firstnames":["Mohammadreza"],"suffixes":[]},{"propositions":[],"lastnames":["Verbas"],"firstnames":["Omer"],"suffixes":[]},{"propositions":[],"lastnames":["Rostami"],"firstnames":["Alireza"],"suffixes":[]},{"propositions":[],"lastnames":["Soltanpour"],"firstnames":["Amirali"],"suffixes":[]},{"propositions":[],"lastnames":["Gurumurthy"],"firstnames":["Krishna","Murthy"],"suffixes":[]},{"propositions":[],"lastnames":["Ghamami"],"firstnames":["Mehrnaz"],"suffixes":[]},{"propositions":[],"lastnames":["Zockaie"],"firstnames":["Ali"],"suffixes":[]}],"year":"2023","bibtex":"@article{kavianipour_deploying_2023,\n\ttitle = {Deploying {Fast} {Charging} {Infrastructure} for {Electric} {Vehicles} in {Urban} {Networks}: {An} {Activity}-{Based} {Approach}},\n\tabstract = {This paper explores an important problem under the domain of network modeling, the optimal configuration of charging infrastructure for electric vehicles (EVs) in urban networks considering EV users’ daily activities and charging behavior. This study proposes a charging behavior simulation model considering different initial state of charges (SOC), travel distance, availability of home chargers, and the daily schedule of trips for each traveler. The proposed charging behavior simulation model examines the complete chain of trips for EV users as well as the interdependency of trips traveled by each driver. Then, the problem of finding the optimum charging configuration is formulated as a Mixed-Integer Nonlinear Programming that considers travel time and travel distance dynamics, the interdependency of trips made by each driver, limited range of EVs, remaining battery capacity for recharging, waiting time in queue, and the detour to access a charging station. This problem is solved using a metaheuristic approach for a large-scale case network. A series of examples are presented to demonstrate the model efficacy and explore the impact of energy consumption on the final SOC and the optimum charging infrastructure.},\n\tjournal = {Transportation Research Record},\n\tauthor = {Kavianipour, Mohammadreza and Verbas, Omer and Rostami, Alireza and Soltanpour, Amirali and Gurumurthy, Krishna Murthy and Ghamami, Mehrnaz and Zockaie, Ali},\n\tyear = {2023},\n}\n","author_short":["Kavianipour, M.","Verbas, O.","Rostami, A.","Soltanpour, A.","Gurumurthy, K. M.","Ghamami, M.","Zockaie, A."],"key":"kavianipour_deploying_2023","id":"kavianipour_deploying_2023","bibbaseid":"kavianipour-verbas-rostami-soltanpour-gurumurthy-ghamami-zockaie-deployingfastcharginginfrastructureforelectricvehiclesinurbannetworksanactivitybasedapproach-2023","role":"author","urls":{},"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://api.zotero.org/groups/2254223/items?key=Bbol5AZSx3A5fDcmq91mfOKd&format=bibtex&limit=100","dataSources":["8NTJjnAGyZ5qTfMug"],"keywords":[],"search_terms":["deploying","fast","charging","infrastructure","electric","vehicles","urban","networks","activity","based","approach","kavianipour","verbas","rostami","soltanpour","gurumurthy","ghamami","zockaie"],"title":"Deploying Fast Charging Infrastructure for Electric Vehicles in Urban Networks: An Activity-Based Approach","year":2023}