Annisaaulkarimah, Fitri (2020) Developing an Application of Inventory Routing Problem for Managing Battery Swap Stations. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
The trend of electric vehicle keeps increasing annually, especially due to a campaign of “EV 30@30”. This campaign has a target of minimum 30 % of deployment of electric vehicles (EVs) in the world by 2030. Currently, EV is refueled with charging scheme by plugging the EV into a charging outlet. A study found that availability of charging infrastructure and charging time became one of the reasons for people to not buying electric vehicle. However, this issue could be overcome by using battery swapping concept. Battery swapping concept is a system where fully charged battery could be obtained by exchanging it with the depleted battery in a Battery Swap Station (BSS). To maintain the availability of fully charged batteries in the BSSs, each BSS is completed with centralized charging platform. Besides, a fleet of vehicles could be operated to distribute fully charged batteries from Center Battery Station (CBS) to replace the depleted batteries in BSSs. CBS should know the inventory level of BSS in order to determine the appropriate delivery quantity. This research develops an Inventory Routing Problem (IRP) model to create distribution plan that minimizes stock-out in BSSs with decision over time only. The IRP model is developed by considering stochastic demand and state of charge (SoC) of each battery in each BSS. To determine the appropriate amount of replenishment unit to each BSS, a minimum acceptable SoC (α) value is required. The model is developed heuristically in Microsoft Excel 2016 using Visual Basic for Application (VBA). Besides developing the IRP model, two numerical experiments are also conducted in respect of total cost and total lost sales.
Item Type: | Thesis (Other) |
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Uncontrolled Keywords: | Inventory Routing Problem (IRP), Battery Swap Station (BSS), State of Charge (SoC) |
Subjects: | T Technology > T Technology (General) > T57.84 Heuristic algorithms. |
Divisions: | Faculty of Industrial Technology > Industrial Engineering > 26201-(S1) Undergraduate Thesis |
Depositing User: | Fitri Annisaaulkarimah |
Date Deposited: | 19 Aug 2020 05:39 |
Last Modified: | 19 Jul 2023 15:17 |
URI: | http://repository.its.ac.id/id/eprint/79164 |
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