Open Access System for Information Sharing

Login Library

 

Article
Cited 23 time in webofscience Cited 23 time in scopus
Metadata Downloads

A Degradation-Informed Battery-Swapping Policy for Fleets of Electric or Hybrid-Electric Vehicles SCIE SSCI SCOPUS

Title
A Degradation-Informed Battery-Swapping Policy for Fleets of Electric or Hybrid-Electric Vehicles
Authors
LEE, SEUNG CHUL
Date Issued
2014-11
Publisher
INFORMS
Abstract
Motivated by high oil prices, several large fleet companies initiated future plans to hybridize their fleets to establish immunity of their optimized business models against severe oil price fluctuations, and adhere to increasing awareness of environmentally friendly solutions. The hybridization projects increased maintenance costs especially for costly and degradable components such as Li-ion batteries. This paper introduces a degradation-based resource allocation policy to optimally utilize batteries on fleet level. The policy, denoted as degradation-based swapping optimization, incorporates optimal implementation of swapping and substitution actions throughout a plan of finite-time horizon to minimize projected maintenance costs. The swapping action refers to the interchange in the placement of two batteries within a fleet. The substitution action refers to the replacement of degraded batteries with new ones. The policy takes advantage of the different degradation rates of the state of health of the batteries because of different loading conditions, achieving optimal placement at different time intervals throughout the plan horizon. A mathematical model for the policy is provided. The optimization of the generated model is studied through several algorithms. Numerical results for sample problems are obtained to illustrate the capability of the proposed policy in establishing substantial savings in the projected maintenance costs compared to other policies.
Keywords
intelligent maintenance; swapping policy; resource allocation policy; fleet electrification and hybridization; electric delivery vehicles (EDV); genetic algorithm; simulated annealing; branch and bound
URI
https://oasis.postech.ac.kr/handle/2014.oak/41134
DOI
10.1287/trsc.2013.0494
ISSN
0041-1655
Article Type
Article
Citation
TRANSPORTATION SCIENCE, vol. 48, no. 4, page. 609 - 618, 2014-11
Files in This Item:
There are no files associated with this item.

qr_code

  • mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher

이승철LEE, SEUNGCHUL
Dept of Mechanical Enginrg
Read more

Views & Downloads

Browse