Multiobjective optimal operation strategy for electric vehicle battery swapping station considering battery degradation

Abstract

The study aims to analyze a futuristic view of the automobile industry conducive to the much-needed penetration of Electric Vehicles (EVs) as per the current environmental and economic scenario. The study suggests the roll-out of EVs in tandem with the supporting Charging Infrastructure, which is a prerequisite for adopting the former. Although transport electrification is a much-accentuated and researched solution to the deteriorating environment and plummeting conventional resources, the design, production, manufacturing, use, degradation, and disposal of an exponential number of lithium-ion batteries for the same have environmental, economic, and social impacts. Thus, emphasis has been made on the sustainable use of charging infrastructure that curbs unnecessary and early battery aging from fast charging technology. Battery swap requests at a Battery Swapping Station (BSS) can be served via batteries from either available battery stock or by charging previously incoming discharged batteries. The study suggests an optimal strategy for the same via a mathematical model representing the operation cost of a BSS consisting of three components, namely, cost of battery utilization, damage cost associated with different charging methods, and dynamic electricity cost. The solution to the multiobjective optimization problem gave the optimum number of batteries that should be used from the battery stock and the charging decision for incoming discharged batteries, given the possible charging options and the constraints on demand satisfaction. Finally, the results from two different optimization tools, Solver in MS Excel and Lingo software, were compared.