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The Impact of Regenerative Braking in Electric Vehicles to Energy-efficient Routing Performance

  • Xiaowen Bi
  • , Jing V. Wang
  • , Chi-Tsun Cheng
  • , Edward Chung

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

Regenerative braking has been demonstrated as an effective way in prolonging the mileages of electric vehicle (EV). In this paper, we aim to examine a generic research problem on how to better utilise the regenerative braking for energy efficiency when routing EV. To this end, we consider a Markov decision process (MDP) based model with 4 distinct reward functions to plan the paths for the EV to traverse a hilly landscape. The results show that by using net energy used as the reward function, the most energy-efficient path can be found. In addition, taking proactive detours can be an energy-efficient way to either avoid excessive energy consumption or prompt energy regeneration. © 2023 IEEE.
Original languageEnglish
Title of host publicationIEEE ISPCE-AS 2023 - IEEE International Symposium on Product Compliance Engineering-Asia 2023
PublisherIEEE
Number of pages5
ISBN (Electronic)9798350361209
ISBN (Print)9798350361216
DOIs
Publication statusPublished - 2023
Event2023 IEEE International Symposium on Product Compliance Engineering-Asia 2023 (ISPCE-ASIA 2023): Product Safety for Smart City - Shanghai, China
Duration: 3 Nov 20235 Nov 2023
https://dl2link.com/ISPCE

Publication series

NameISPCE-AS - IEEE International Symposium on Product Compliance Engineering - Asia
ISSN (Print)2831-3402
ISSN (Electronic)2831-3410

Conference

Conference2023 IEEE International Symposium on Product Compliance Engineering-Asia 2023 (ISPCE-ASIA 2023)
Abbreviated titleIEEE ISPCE-AS 2023
PlaceChina
CityShanghai
Period3/11/235/11/23
Internet address

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Research Keywords

  • electric vehicle
  • path planning
  • regenerative braking
  • road inclination
  • value iteration

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