arrow
Return

Battery algorithm verification and development using hardware-in-the-loop testing

delete2010-05-01
delete54
PRE
AI
Y
Yongsheng He *
W
Wei Liu
B
Brain J. Koch
DOI:10.1016/j.jpowsour.2009.11.036delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Battery algorithms play a vital role in hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), extended-range electric vehicles (EREVs), and electric vehicles (EVs). The energy management of hybrid and electric propulsion systems needs to rely on accurate information on the state of the battery in order to determine the optimal electric drive without abusing the battery. In this study, a cell-level hardware-in-the-loop (HIL) system is used to verify and develop state of charge (SOC) and power capability predictions of embedded battery algorithms for various vehicle applications. Two different batteries were selected as representative examples to illustrate the battery algorithm verification and development procedure. One is a lithium-ion battery with a conventional metal oxide cathode, which is a power battery for HEV applications. The other is a lithium-ion battery with an iron phosphate (LiFePO4) cathode, which is an energy battery for applications in PHEVs, EREVs, and EVs. The battery cell HIL testing provided valuable data and critical guidance to evaluate the accuracy of the developed battery algorithms, to accelerate battery algorithm future development and improvement, and to reduce hybrid/electric vehicle system development time and costs. (c) 2009 Elsevier B.V. All rights reserved.
Keywords:
Battery algorithm
Hardware-in-the-loop
State of charge
Power capability
Lithium-ion battery
Lithium iron phosphate battery
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Journal of Power Sources cover
Journal of Power Sources
IF:
7.9
Papers:
3.7W
Citations:
15.0W

Organization

G
General Motors
Scholars:
1.4K
Papers: 1.8K
Citations: 10