A new hybrid approach for optimal location of charging station and ADVISOR software for energy consumption estimation of electric bus

D. M. Sumith, Sunil Nagpal, Gautam Sarkar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Energy management of electric vehicle (EV) driving distance for commercial use is the challenging factor for this era. This paper proposes a new hybrid approach which uses a combination of prim's algorithm (PA) and brute-force search (BFS) to solve the vehicle routing problem (VRP) for finding best location to build a Charging station. The 9 meters(9m) and 12 meters(12m) bus module parameters were modified in ADVISOR Software (ADVANCED VEHICLE SIMULATOR), which includes module of EV, motor module, wheel/axle module, battery module, transmission module and a driving test such as Delhi drive cycle were chosen for analyzing simulation results with respect to energy consumption estimation in kWh/km. By considering the given point charging location, the summation of distance of all the possible round trip is 48.4 km and energy consumption per loop is 37.12-47.43 kWh. By choosing the location found from new hybrid approach for installing the charging station, we can reduce the number of battery recharges and decrease the depth of discharge of EV.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Intelligent Sustainable Systems, ICISS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages251-256
Number of pages6
ISBN (Electronic)9781538677995
DOIs
Publication statusPublished - 02-2019
Externally publishedYes
Event2019 International Conference on Intelligent Sustainable Systems, ICISS 2019 - Palladam, Tamilnadu, India
Duration: 21-02-201922-02-2019

Publication series

NameProceedings of the International Conference on Intelligent Sustainable Systems, ICISS 2019

Conference

Conference2019 International Conference on Intelligent Sustainable Systems, ICISS 2019
Country/TerritoryIndia
CityPalladam, Tamilnadu
Period21-02-1922-02-19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing
  • Software

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