Stationary Lead-Acid Batteries Maintenance Management System

M. Fátima N.C. Rosolem** Gilcinea Rangel Pessenti * Luiz Eduardo F. D. Júnior**

CPqD Light CPqD mfatima@cpqd.com.br gilcinea.pessenti@light.com.br ljunior@cpqd.com.br

Glauco Ribeiro dos Santos** Pamela Tobias Frare** Raul Fernando Beck**

CPqD CPqD CPqD glauco@cpqd.com.br pamela@cpqd.com.br raul@cpqd.com.br

Vitor Torquato Arioli** Paulo Henrique O. Lopes**

CPqD CPqD vitor@cpqd.com.br pauloh@cpqd.com.br

*Light Centrais Elétricas S. A

Av. Marechal Floriano, 168 - 4º andar - Centro - CEP 20080-002

Rio de Janeiro – RJ, Brazil

**CPqD Foundation - Telecommunications Research and Development Center Rod. Campinas - Mogi-Mirim km 118.5 - CEP: 13086-902

Campinas - SP, Brazil

Abstract – This work describes a study to obtain premature failures diagnoses in stationary lead acid batteries (flooded and valve regulated) by measurements of its internal resistance. The main goal was to obtain a methodology to estimate the future conditions of the batteries and replace then before failures. To achieve this goal we planned and executed some accelerated aging tests in different models of flooded and VRLA batteries used by LIGHT in CPqD’s Batteries Laboratory. By analyze of the records, was developed a mathematical algorithm to predict the state of degradation of 2 V lead acid flooded and VRLA batteries for the next 24 months. From this prediction algorithm, based on conductance and/or impedance measurements, was developed a software implemented in WEB, JAVA language and SQL Server Database.

1 INTRODUCTION

Batteries are the most important element in electric power substations when occur grid outages. In order to keep the auxiliary services (electronics controls, fire protection system, etc) in operation, the lead-acid battery invented by Plante in 1860 remains the dominant solution in stationary applications.

Until the beginning of the 90's the Brazilian batteries market share was dominated exclusively by flooded lead-acid batteries. Between 1995 and 1998 the valve regulated lead-

acid battery (VRLA) was introduced in some electric companies. This product became popular quickly and today it is estimated that about fifty percent of the batteries installed are VRLA.

Now, in Brazil, with the introduction of the datacenters services, internet, mobile phone, etc, critical backup systems has became a imperative needs for this companies. Therefore, it is necessary to development reliable methods to evaluate the actual state of degradation of the lead acid battery.

Recently in Brazil, the technique of measuring internal ohmic is an alternative methodology applied to assess the degradation state of these batteries. Because this, currently in the market, there are several options of portable instruments for this purpose but, when this technique is applied, is necessary a correct analysis of the acquired database. It can be problematic because is necessary to set a baseline reference (which is not often available), the possibility to generate a huge amounts of data (not even correctly analyzed) and the lack of an operator to perform these measurements.

Because these problems, since 2001, LIGHT (Electric Generation and Distribution Company of Rio de Janeiro - Brazil) and CPqD (Research and Development Center in

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978-1-4244-3384-1/10/$25.00 ©2010 IEEE

Telecommunications - Brazil) have necessary researches projects to enhance and implement the internal ohmic measurement methodology as a tool for predictive and corrective maintenance of LIGHT´s stationary lead acid batteries. In 2006 and 2007 LIGHT and CPqD became this tool a mature technology in development project management maintenance system for LIGHT´s stationary lead acid (VRLA) batteries. The main goal of this research was to obtain premature failures diagnoses of all batteries in operation in the LIGHT´s electrical substations by measurements of internal resistance and with the methodology, to estimate the future replacement of these batteries as well. To achieve this goal were planned and executed a set of accelerated aging tests in different models of flooded and VRLA batteries used by LIGHT, in the CPqD’s Batteries Laboratory.

Analyzing the results of accelerated laboratory tests was developed a mathematical algorithm to predict the state of degradation of 2 V lead acid flooded and VRLA batteries for the next 24 months. From this prediction algorithm, based on conductance and/or impedance measurements, the project resulted in a software implemented in WEB, JAVA language and SQL Server Database.

The objective of this software is to provide an efficient tool to assist in the management of the batteries strings. It was organizing a database (independently of the electrical company or outsourcing maintenance team) acquired in the field, with the input of historical measurements and performance records of the batteries. The algorithm make a skeptical analyze, providing premature diagnosis of the state of degradation of each cell or battery, before the service stopped. The software also makes possible the previous planning of corrective and preventive maintenance, and provide a powerful decision tool to compare batteries from different models and manufacturers.

2 ALGORITHM

To make the tests, were acquired 64 cells from Brazilian current batteries suppliers. It was necessary to keep the appropriate representation of the domestic market share. The set of samples was bought from four different manufacturers (2V, flooded and VRLA) with these follow requirements: four flooded (three with antimony alloy and one with calcium alloy) and four VRLA (two Gel and two AGM). These cells were subdivided in eight sets of samples that were submitted to different accelerate tests, nominally: charge and discharge cycling, storage at 35ºC and floating at elevated temperature. The tests were conducted during 12 months or until the cells capacities achieve value lower than 80% of the nominal capacity. During the tests, the batteries degradation was verified through capacity tests and voltage, conductance and impedance measurements. These measurements were carried out monthly.

The Table 1 shows the measurements of Conductance, Impedance and Capacity Percentages at the end of accelerated tests. The result shows that any battery model has a best or worst performance in all tests, that is, there isn’t a specified model of battery that has a better performance in all accelerate tests. Regarding the correlation between measurements of capacity, conductance and impedance, it was observed that measurements of conductance and impedance are not directly proportional to capacity, but there is a correlation between the decrease of the conductance, the increase of impedance and the decrease of capacity. In general the samples showed conductance values lower than 80% compared to the reference value, impedances values higher than 125% compared to the reference value and capacities lower than 80% compared to the nominal capacity. During the accelerating tests, it was developed periodic measurements of conductance, voltage and impedance and capacity tests as well. The mathematical model was made with selected records from samples (from accelerated tests) that showed the best correlation between capacity, impedance and conductance. The mathematical model was also developed from the curves of conductance and impedance when the tests was running. The trend of degradation was taken account in these measurements during accelerated tests, that is, there was a correlation between tests duration and the batteries life time, taking as a reference the design of the batteries. It was adopted a projected life of 12 years for the flooded battery and 7 years for VRLA From the range of measurements acquired it was possible to estimate the actual state of the battery health (in years of life time) and to project conductance and impedance values according to the projected life time of each battery type. The Figure 1 shows the conductance degradation curve to VRLA concerning the time of its projected life. A mathematical model that represents the battery degradation as a function of its projected time life was elaborated for each type of battery (flooded and VRLA) These algorithms was implemented in the Batteries Software Management, which were used to project future degradation of batteries based on measurements of conductance or impedance. Estimates were made for the next 24 months counted from the last measurement

3 SOFTWARE OF BATTERIES MANAGEMENT (GEBAT)

The Batteries Software Management (GEBAT) was developed in a WEB environment, JAVA language and SQL Server Database. The GEBAT following the evolution of the density, voltage, impedance and/or conductance measurements, besides predict the state of degradation of the battery for the next 24 months.

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The GEBAT has the following features in the Main Menu bar (Figure 2):

o Import data o Measurements o Maintenance o Reports o Registration o Configuration o Security

On the left side of the entries main screen also appears all substations registered in SW. Through this menu is possible access all reports relating to selected substation.

A more detailed description and characteristics of these features found in the Main Menu is given bellow.

3.1 Import Data

The import functionality is essential for this software, it allows to transfer (uploading) the conductance and impedance measurements records to GEBAT. It is possible to import three different types of information, which are described below.

3.1.1 Impedance

The impedance records are import to GEBAT in files with the .TXT extension. The procedure to obtain the TXT file is downloading the database file from the impedance equipment collector (Interrogator® from WELL) to the PC and converts it into TXT file readable by the SW.

3.1.2 Conductance

The conductance database is imported to GEBAT through two different ways: by files (.TXT or .C60 extension, using the same procedure to impedance database) or downloading the database directly from the serial port of the conductance equipment collector (Midtronics®).

3.2 Measures

The software is able to analyze others measurements too, as electrolyte density, floating voltage and information come from the capacity tests. These databases have to be inserted manually, that is, these records can not be imported from database equipment collector.

The software also offers the possibility of the user to access an overview of the batteries conditions. It is possible to select the battery site for each different measurement, i.e., conductance, impedance, voltage, electrolyte density and capacity test.

In general the summary presents the following information:

o measurement date o reference values o temperature o average measurements o identification of the cell or string that has been

showing higher value o identification of the cell or string that has been

showing smaller value o total voltage of battery

These informations are showed in table format (Figure 3).

Further in this information on the left side of the table, there is a visual sign indicating the condition of battery degradation (this information is based on the conductance or impedance measures). The green signal indicates that the batteries is good, (i.e., the battery has a good health), yellow sign indicates that the battery is in alert condition (i.e. the battery health is getting worse) and the red sign indicates that the battery health is bad.

3.3 Maintenance Management

This feature is applied when the battery (or the battery string) is reallocated or removed. The reallocation occurs when the battery is taken from one site and it is installed in another site. In this situation, all the measurements made in this location is remove for the a new location. The exclusion is used when a bank of batteries is scrapped, or is taken from one location and is no longer used. In this case the user has the option of stores or not the data of the battery scrapped.

3.4 Reports

The reports created by the software are an important tool for a better view of the batteries health. The reports show information as measurements values (imported or inserted), further degradation state and battery inventory. This menu has the follow features:

o Reports in graphs or in tables show the conductance, impedance, floating voltage, density and capacity tests information.

o Specific reports for battery, for one specific cell or string.

o All the tables and graphs reports are able to generate a summary that show an assessment of measurements.

o Reports generate for a single or several kinds of measurements acquired at different time (Figure 4).

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o Reports with monthly variation in the measurements of conductance and/or impedance for cell or string.

o Projected degradation reports (degradation state for the next 24 months (Figure 5).

o Comparative reports about different manufacturers, batteries and models.

All the reports can be printed or salved. A simple view on the computer screen is also possible.

3.5 Registration

There are these follow fields on the software to be filled:

o Manufacturer: information of battery manufacturers, such as name, address, phone, e-mail and contact;

o Battery type: VRLA Battery (gel and AGM), or flooded type (lead-antimony and lead-calcium);

o Battery Model: Each manufacturer has different models of batteries. In order to make a right comparative the user have to insert these information: model name, technology type, projected life time, nominal capacity, cell or battery voltage, floating voltage and conductance and impedance reference values;

o Site: site where one or more batteries are installed. It is necessary complete the following information: identification of site (it depends on the user), address and amount of battery;

o Batteries: This field has to be filled with information about the characteristics of installed batteries per site. The information about manufacturer, model and location are already provided records. The new information inserted in this field are: battery identification, total number of cell or strings and installation time.

3.6 Configuration

This function allows inserting parameters that will be used in analysis of the measurements (conductance, impedance, electrolyte density and capacity voltage). These parameters are analyzed to indicate if the measures are at the desired threshold and they are also used in the projection algorithm of the degradation. These parameters are settable, i.e., can be adjusted according the user needs.

3.7 Security

To login and operate the GEBAT, the User must be registered in the system. The User has a login, password and profile. Its profile is settable to limit the software features and in accordance with the tasks assigned, each user create a different profile.

4 CONCLUSION

The GEBAT it is a tool that will provide to the users the following benefits:

o Trend of the degradation state of the battery for the next 24 months from the last measurement of conductance and / or impedance.

o Early diagnosis of battery failures that can lead to disruption on its operation.

o Automatic technical reports generation and management.

o Continuous monitoring of battery performance. o Advanced planning of corrective and predictive

actions. o Effective way to ensure that the maintenance and

operation of the battery have been performed correctly.

o Agility to support decisions making. o Centralization and automation of the maintenance

data analysis of battery. o All database of maintenance and operation of the

battery are stored electronically. o The database is not lost over time or with the

maintenance team change. o Allowing to apply the manufacturer's warranty to

apply for full or pro-rata. o Generating Alarms. o Better batteries planning replacement. o Capable to make an easy comparative between the

performance of batteries of different models and manufacturers.

5 REFERENCES [1] BERNDT, D. - "Maintenance-Free Batteries" - A Handbook of Battery Technology, 3rd edition, 2001. [2] NBR 14204 - Requirements of Stationary Valve Regulated Lead Acid Battery - edition 2002. [3] ROSOLEM, Maria.F.N.C.; BECK, Raul.F. & JÚNIOR, Martos.G.R. - “Evaluation Tools for Batteries Employed in Oudooor Cabinets - An Experience of a Brazilian Telecom Company”; INTELEC 2000 - Phoenix/EUA. [4] ROSOLEM, Maria.F.N.C.; BECK, Raul .F & SOARES, Luiz A. - “Failure Detection of Stationary Lead-acid Batteries in Service in Various Regions of Brazil”, INTELEC 2002 - Montreal/Canadá. [5] ROSOLEM, Maria, F.N.C.; BECK, Raul F.; CARDOSO, Paulo E.; SOARES, Luiz A & YAMAGUTI, Francisco - Stationary VRLA Battery Evaluations: Internal Measurements and Capacity Test - an the Claro Celular Mobile Company; BATTCON 2004 - Florida, USA.

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[6] ROSOLEM, Maria.F.N.C.; BECK, Raul F.; CARDOSO, Paulo.E; SOARES, Luiz.A. - Evaluation of the Relationship Between Conductance and Capacity Measurements of VRLA Batteries in Brazil; INTELEC 2004 - Chicago, USA. [7] PINHEL, A. S., ROSOLEM, M.F.N.C.; .; BECK, R.F.; SOARES, L.A.; RIBEIRO, G.S.; ARIOLI, V.T.; FRARE, P.T. “Impacto da Estocagem na Vida Útil de BateriasChumbo-ácidas Reguladas por Válvula – (VRLA)”, 23º Congresso Brasileiro de Manutenção, Santos-SP, Brasil, 2008 [8]Melo, A. M, ROSOLEM, M.F.N.C.; BECK, R.F.; SOARES, L. A. e CARDOSO, P.E. R., Revista Eletrecidade Moderna, Ano XXXVII nº417, dezembro 2008. [9] ROSOLEM, M.F.N.C.; . BECK, R.F.; SOARES, L.A.; RIBEIRO, G.S.; ARIOLI, V.T.; FRARE, P.T, FONSECA, J. C. – “The Batterie’s Regulatory Process in Brazilian Telecommunications Industry, Telescon 2009 – Viena/Austria.

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Table 1: Results of Accelerated Tests

Manufacture/ Battery Type Samples

Accelereted Tests Storage Charge/Discharge Cycling Floating Elevated Temp

Cap Cond Imp Cap Cond Imp Cap Cond Imp

1- Bat 1 VRLA

1 77,96 59,15 174,09 94,19 87,38 112,58 97,11 78,92 126,52

2 89,75 81,38 129,39 93,39 88,92 109,09 96,33 81,77 125,30

1- Bat 2 Vented

1 63,16 72,40 146,50 87,16 103,50 92,88 94,93 104,10 88,25

2 72,59 72,10 152,50 78,16 91,00 110,50 95,50 106,90 95,13

1- Bat 3 Vented

1 81,84 81,15 125,53 -- 67,20 162,89 113,22 118,90 93,68

2 101,90 89,60 113,68 -- 6,30 1757,37 111,01 118,00 94,21

2- Bat 1 VRLA

1 76,07 98,59 87,07 28,21 76,06 115,00 57,19 60,12 145,69

2 73,89 89,65 96,90 31,68 89,41 98,97 32,30 60,18 147,41

3- Bat 1 VRLA

1 43,94 76,90 124,12 95,39 107,86 91,32 95,73 86,98 97,06

2 69,03 88,89 110,29 94,35 107,30 92,06 106,25 108,89 93,82

3- Bat 2 Vented

1 86,13 95,25 104,52 -- 96,24 102,58 103,81 98,65 101,45

2 85,29 95,60 107,90 -- 98,58 102,42 100,41 95,60 102,58

4- Bat 1 VRLA

1 62,96 66,43 152,17 52,96 32,07 294,33 31,50 51,86 204,00

2 75,56 75,14 135,17 59,55 33,36 292,33 20,10 43,93 243,33

4- Bat 2 Vented

1 36,40 66,85 136,15 86,75 89,46 96,92 101,45 107,62 90,92

2 55,47 78,00 120,15 94,40 96,69 94,15 97,34 101,15 95,23

50,0

60,0

70,0

80,0

90,0

100,0

110,0

0,0 1,0 2,0 3,0 4,0 5,0 6,0 7,0 8,0Time (years)

Con

duct

ance

(%)

Figure 1: Conductance degradation curve as a function of designed life time - VRLA Battery

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Figure 2: Main Menu GEBAT

Figure 3: Measurements Resume

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Figure 4: Graphic of Conductance Measurements

Figure 5: Degradation Conductance Curve

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