Simplification and Efficient Simulation of Electrochemical Model for Li-ion Battery in EVs

Cheng Lin, Aihua Tang*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

19 Citations (Scopus)

Abstract

At present, lithium-ion (Li-ion) cells are the core of electric vehicles (EVs). The complexity of electrochemical model makes on-line simulation difficult in electric vehicles. Thence, it is necessary to obtain a simplified model instantaneously under all operating conditions of the batteries. In this paper, simplification of electrochemical models of Li-ion battery to improve simulation and computational efficiency in EVs will be proposed. An isothermal pseudo-two-dimensional (P2D) model based on spatiotemporal dynamics of li-ion concentration, electrode potential in each phase, and the Butler-Volmer kinetics is developed. Since using traditional approaches to simulate the P2D model is computationally expensive, it has limited its use in EV's applications. Some methods can be used to decrease the number of Partial Differential Equations (PDEs) that must be solved simultaneously and enable faster computation while using limited resources. Moreover, an averaged electrode (AE) model and single particle (SP) model which derive from P2D model embodies high precision and fast simulation of battery performance for a range of working conditions. Finally, the simulation results of the AE and SP model are compared with Doyle-Fuller Newman (DFN) model and show that the SP model can reduce computational amount significantly while still retaining the accuracy.

Original languageEnglish
Pages (from-to)68-73
Number of pages6
JournalEnergy Procedia
Volume104
DOIs
Publication statusPublished - 2016
EventApplied Energy Symposium and Forum: Low - Carbon Cities and Urban Energy Systems, CUE 2016 - Jinan, China
Duration: 13 Jun 201615 Jun 2016

Keywords

  • Partial Differential Equations(PDEs)
  • electric vehicles (EVs)
  • electrochemical model
  • pseudo-two-dimensional (SP2D)
  • single particle (SP) model

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