Simplification and efficient simulation of electrochemical model for Li-ion battery in EVs

被引:17
作者
Lin, Cheng [1 ,2 ]
Tang, Aihua [1 ,2 ,3 ]
机构
[1] Beijing Inst Technol, Sch Mech Engn, Natl Engn Lab Elect Vehicles, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Sch Mech Engn, Collaborat Innovat Ctr Elect Vehicles Beijing, Beijing 100081, Peoples R China
[3] Sichuan Univ Sci & Engn, Sch Mech Engn, Zigong 643000, Peoples R China
来源
CLEAN ENERGY FOR CLEAN CITY: CUE 2016 - APPLIED ENERGY SYMPOSIUM AND FORUM: LOW-CARBON CITIES AND URBAN ENERGY SYSTEMS | 2016年 / 104卷
关键词
electrochemical model; electric vehicles (EVs); pseudo-two-dimensional (SP2D); single particle (SP) model; Partial Differential Equations(PDEs);
D O I
10.1016/j.egypro.2016.12.013
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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. (C) 2016 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:68 / 73
页数:6
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