Factoring Electrochemical and Full-Lifecycle Aging Modes of Battery Participating in Energy and Transportation Systems

Shuangqi Li, Pengfei Zhao, Chenghong Gu, Yue Xiang, Siqi Bu, Edward Chung, Zhongbei Tian, Jianwei Li, Shuang Cheng

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Abstract

Transportation electrification emerges as a pivotal strategy to realize deep decarbonization for many countries, and the central part of this is battery. However, a key challenge often overlooked is the impact of battery aging on the economy and longevity of electric vehicles (EVs). To address this issue, the paper proposes a novel battery full-life degradation (FLD) model and energy management framework that substantially improves the overall economic efficiency of Battery Energy Storage Systems (BESS). In the first stage, battery electrochemical aging features are modeled by learning cell fading rate under various healthy states, capitalized on the Stanford experimental open dataset. Accordingly, a lifecycle degradation model is then developed considering various operational conditions and aging stages to quantitatively assess the effects of depth of discharge, C-rate, state of health, and state of charge. In the second stage, battery electrochemical aging features are integrated into vehicle energy management so that batteries under different fading rates can be flexibly utilized during whole lifecycles. The proposed methods are validated on a practical UK distribution network and a hybrid vehicles hardware-in-the-loop platform. With the proposed methods, EV users can make informed decisions to optimize energy usage and prolong the lifespan of vehicle BESS, thereby fostering a more sustainable and efficient transportation infrastructure.

Original languageEnglish
Number of pages14
JournalIEEE Transactions on Smart Grid
Early online date17 May 2024
DOIs
Publication statusE-pub ahead of print - 17 May 2024

Keywords

  • Aging
  • Batteries
  • battery energy storage system
  • Costs
  • Degradation
  • Electric vehicle
  • electrochemical aging model
  • energy management
  • Energy management
  • full lifecycle degradation model
  • Transportation
  • vehicle to grid
  • Vehicle-to-grid

ASJC Scopus subject areas

  • General Computer Science

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