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Soltanpour, Amirali (Michigan State University), Rostami, Alireza (Michigan State University), Ghafarnezhad, Behdad (Michigan State University), Ghamami, Mehrnaz (Michigan State University), Zockaie, Ali (Michigan State University), Crawford, Jessica (Michigan Department of Environment, Great Lakes, and Energy), Jackson, Robert (Michigan Department of Environment, Great Lakes, and Energy)

Charging Infrastructure Planning for Electrifying the Lake Michigan Circuit under Various Budget and Feasibility Constraints

Scheduled for presentation during the Invited Session "Large-scale Smart Mobility" (FrAT2), Friday, September 27, 2024, 11:10−11:30, Salon 5

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 8, 2024

Keywords Electric Vehicles, Infrastructure for Charging, Communication and Controls, Theory and Models for Optimization and Control

Abstract

The transportation sector poses significant environmental challenges, but the adoption of battery electric vehicles (EVs) offers a promising solution. However, barriers, such as inadequate charging infrastructure for long-distance travels, impede widespread EV use. This study explores Level-2 chargers as a viable solution, particularly for tourist destinations, considering the tradeoff between charging time and implementation costs. The focus is on potential tourist spots along the Lake Michigan coastline in Michigan. The goal is to optimize Level-2 charger placement considering the available and planned DC fast chargers. The problem is formulated as a mixed-integer linear programming (MILP) to minimize overall system costs while ensuring trip feasibility. Two solution approaches, an exact method solved with CPLEX and a heuristic algorithm are proposed. Results suggest that MILP proves superior when analyzing Level-2 requirements independently, while the heuristic approach excels in integrating the Level-2 framework with the DCFC framework due to its runtime efficiency. Sensitivity analyses reveal the impact of budget constraints and charging power on optimal solutions. Using 7 kW chargers minimizes costs compared to higher charging powers. Balancing budget and power is vital; increasing budget, with fixed power, reduces delays, while a fixed budget with increased power leads to longer delays. Strategic placement of Level-2 chargers at tourist spots enhances EV tourism, confirmed by spatial distribution.

 

 

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