Next Article in Journal
Plug-in Fuel Cell Vehicle Technology and Value Analysis
Previous Article in Journal
Aging of Lithium-Ion Batteries in Electric Vehicles: Impact of Regenerative Braking
Article Menu

Article Versions

Export Article

World Electric Vehicle Journal is published by MDPI from Volume 9 issue 1 (2018). Articles in this Issue were published by The World Electric Vehicle Association (WEVA) and its member the European Association for e-Mobility (AVERE), the Electric Drive Transportation Association (EDTA), and the Electric Vehicle Association of Asia Pacific (EVAAP). They are hosted by MDPI on mdpi.com as a courtesy and upon agreement with AVERE.
Open AccessArticle

MLS TESTING OF VRLA BATTERIES USING PSEUDO RANDOM BINARY SEQUENCES (PRBS)

1
VxI Power Ltd, Station Road, North Hykeham, Lincoln, LN6 3QY, United Kingdom
2
Electrical Machines and Drives Research Group, University of Sheffield, Mappin Street, Sheffield, S1 4DT, United Kingdom
*
Author to whom correspondence should be addressed.
World Electr. Veh. J. 2010, 4(2), 405-413; https://doi.org/10.3390/wevj4020405
Published: 25 June 2010
PDF [963 KB, uploaded 17 May 2018]

Abstract

Non-intrusive methods of establishing battery state offer distinct advantages to systems where complex charge and discharge profiles make implementation of conventional battery state reporting difficult. Furthermore, examination of equivalent circuit parameters for batteries and cells offers potential opportunities for State-of-Charge (SoC) and State-of-Health (SoH) reporting, irrespective of historic charge and discharge events. This paper expands the use of maximum length sequences as tools for parameter estimation within electrochemical cells, to seek to identify performance indicators within batteries. In order to facilitate this identification, Randles' model is used with Pseudo Random Binary Sequences (PRBS) as the excitation signal within the test system for the batteries being examined. Design of these sequences for experimental analysis is discussed, leading to application in the described test system, employing a monopolar current signal in order to apply the perturbation to the subject battery. Battery impedance is investigated using a frequency domain approach, leading to characteristic impedance spectra being produced for the test batteries. The experimental results obtained allow parameters to be established, and verification against conventional battery test methods, and a sampled data model, is carried out.
This analysis is used to present characteristics which can be subsequently used to inform the design of SoC and SoH algorithms, in order to develop online systems for evaluating these batteries.
Keywords: Batteries; PRBS; modelling; parameter estimation Batteries; PRBS; modelling; parameter estimation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Fairweather, A.; Foster, M.; Stone, D. MLS TESTING OF VRLA BATTERIES USING PSEUDO RANDOM BINARY SEQUENCES (PRBS). World Electr. Veh. J. 2010, 4, 405-413.

Show more citation formats Show less citations formats

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
World Electr. Veh. J. EISSN 2032-6653 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top