My Account Log in

1 option

SOC Estimation of Battery Pack Considering Cell Inconsistency Tongji University

SAE Technical Papers (1906-current) Available online

View online
Format:
Book
Conference/Event
Author/Creator:
Yang, Yang, author.
Contributor:
Dai, Haifeng
Fang, Qiaohua
Wei, Xuezhe
Conference Name:
WCX SAE World Congress Experience (2019-04-09 : Detroit, Michigan, United States)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2019
Summary:
Range anxiety problem has always been one of the biggest concern of consumers for pure electric vehicles. Accurate driving range prediction is based on accurate lithium-ion battery pack SOC (State of Charge) estimation. In this article, a complete SOC estimation algorithm is proposed from cell level to battery pack level. To begin with, the equivalent circuit model (ECM) is applied as the model of battery cell. ECM parameters are identified every 10% SOC interval through genetic algorithm. The dual extended Kalman filtering (DEKF) algorithm is adopted for cell-level SOC and ohmic resistance R0 estimation. The estimation accuracy of cell SOC and R0 is verified under NEDC dynamic working condition. The cell-level SOC estimation error is below 1%. However, cell inconsistency can always result in inaccurate cell SOC estimation inside the battery pack. The impact of initial SOC inconsistency and internal resistance inconsistency between cells on battery pack SOC is specifically analyzed. Considering cell inconsistency, dual time-scale dual extended Kalman filtering (DTSDEKF) algorithm based on "Specific Cell and Difference Model" ("S&D model") is introduced to help accurately estimate cell SOC inside the battery pack: In the first time scale, DEKF algorithm is used to estimate current SOC and R0 of "Specific Cell". In the second time scale, the correction of the cell inconsistency is added, which involves the SOC difference between the remaining cells and the "Specific Cell", as well as R0 of all cells. Finally, the DTSDEKF algorithm based on "S&D model" is verified through NEDC dynamic working condition. The SOC estimation error of each cell inside the battery pack is below 1%
Notes:
Vendor supplied data
Publisher Number:
2019-01-1309
Access Restriction:
Restricted for use by site license

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

Find

Home Release notes

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Find catalog Using Articles+ Using your account