Centrally-chosen versus user-selected swaps: How the selection of swapping stations impacts standby battery inventories

Swapping depleted batteries of electric vehicles promises much better driving-to-total-travel-time ratios than plug-in charging. Nonetheless, large-scale battery swapping systems have not successfully established yet. One obstacle, on top of the high infrastructure cost, is certainly the additional invest into extra standby batteries that await their swaps at stations. Existing research is focused on systems in which users decide individually where they want to swap batteries. This system requires significant standby battery inventories to protect against uncertain swapping demand. This paper evaluates another system where users must register their trips on a central platform, so that battery swaps can be coordinated based on central optimization results. To benchmark central optimization and user choice regarding their impact on standby battery inventories, we formulate the min-battery swapping problem: For a given set of vehicle trips, this optimization problem minimizes the number of standby batteries, distributes them in a given station network, and derives detailed swapping plans to feasibly power all trips. First, we present a thorough analysis of computational complexity. Then, we provide an efficient mixed-integer programming formulation that is adaptable to different swapping policies and (when fed into a default solver) solves instances with up to 200 trips to proven optimality in just a few seconds. Our computational study reveals that central optimization promises a significant reduction of standby battery inventories. This potential is shown to increase if swaps of not yet fully-charged batteries are allowed and swaps are pooled at a reduced number of swapping stations.