Márcio Duarte Zanconato
Enerbrax Industry, Brazil
E-mail: zanconato.marcio@gmail.com
Beatriz Braido de Rossi
University of Sagrado Coração, Brazil
E-mail: beatriz.rossi@hotmail.com
Herbert Duchatsch Johansen
University of Sagrado Coração, Brazil
E-mail: hdjohansen@gmail.com
Márcia Rodrigues de Morais Chaves
University of Sagrado Coração, Brazil
E-mail: marcia.chaves@usc.br
Beatriz Antoniassi
University of Sagrado Coração, Brazil
E-mail: beatriz.tavares@usc.br
Submission: 17/06/2016
Revision: 03/07/2016
Accept: 04/08/2016
ABSTRACT
In this work, the automated formation
process of lead-acid battery and its industrial positive impact on the battery
efficiency are evaluated toward the manual process. The problems in the
lead-acid batteries formation are related to the α-PbO2 and β-PbO2
production during the first electric charge. The lead-acid battery formation
problems frequently occur when electrical current sources with manual control
are used. The main drawback of the manual method is addressed to the electric
current interruptions between the plates during the battery charging. Thus, the
lead oxides phases in the plates were used as parameter to correlate the
chemical composition to the failure on the batteries formation process. X-ray
powder diffraction technique was used to identify the lead phases. Results
showed that the use of automated electric power supply has higher efficiency
than the manual one. The benefits of automation include the increased productivity,
reduction on the production costs, and lower consumption of natural resources.
Keywords: lead-acid
battery; automated formation; XRPD, PbO2.
1. INTRODUCTION
The electricity discovery has prompted the
technological development in various sectors of society, such as lighting,
telecommunication system, the ignition for the transport vehicles, among
others. Since then, the human being has become dependent on electricity to meet
their consumption needs. However, current environmental concerns demand for using
alternative energy sources, cleaner and more efficient. It is especially
considered when remote areas suffer from a lack of power supply (GUERRA et al.
2015; UGURLU; OZTUNA, 2015; KONOVALOV et al. 2015; SOLOVEICHIK, 2014; GROOS,
2012). Thus, the development of energy storage systems is a key part for this
breakthrough to become efficient and feasible (SUBERO et al. 2014; RADUCAN;
MORARU, 2011). Among the different types of energy storage systems available,
the battery is the most used (JANNATI et al. 2016; TAN et al. 2016; CHO et al.
2015; ZHOU et al. 2013; KEAR et al. 2012).
Lead-acid batteries are the preferred consumed battery
systems, by being able to supply power stably and continuously controlled
quality when subjected to good maintenance procedures (HIREMATH et al. 2015;
MCKENNA et al. 2013). In addition, these types of batteries are manufactured at
low cost, with robust recycling production system, and have easy maintenance
when compared with other power storage systems (MATTESON; WILLIAMS, 2015;
GONZÁLEZ et al. 2012). Its main applications are as a power source for
starting, ignition and lighting vehicles, the traction electric vehicles,
no-break systems, in alarm systems and emergency lighting, telephone exchanges
and electrical substations, featuring applications known as start-up,
tractionary and stationary, respectively (MCKEON, 2014; MACLEAN; LAVE, 2003).
Due to their economic and technological importance,
the electrochemical system of lead-acid batteries has been the subject of several
researches, scientific studies and technical assessments (PITATOWICZ et al.
2015; FERG et al. 2013; SAUER; WENZ, 2008). In Brazil, the product quality
control occurs through the certification by the National Institute of
Metrology, Quality and Technology (INMETRO). This product requires reliability;
therefore, is essential the control and track of the entire production process
of lead-acid battery (BRAZIL, 2015, 2012, 2011).
The battery formation is one of the most important
phases in the production processes of lead-acid batteries. During this process,
the precursor material of battery (formed mainly by basic lead oxide and sulfate
paste, which is adhered to the grid) is transformed into active material by the
passage of electric current. The battery formation step is critical for it
works in accordance with what has been dimensioned in its production process (ZENG
et al. 2015; GOU et al. 2014; GRUGEON-DEWAELE et al. 1997; CHEN et al. 1996;
PROUT, 1993).
The manual process is the main procedure used for the
lead-acid battery formation in the most industries in Brazil. Despite of this,
some industries are starting the use of the automated process to form lead-acid
batteries. To contribute to this field, this work evaluated the automated
process of lead-acid battery formation, in attempt to elucidate the effect of
electric source control on the battery efficiency.
2. RESEARCH METHODOLOGY
The industrial process of the lead-acid battery
formation using manual or automated power source is described as following, as
well as all the other methodology used in this study.
This study was performed in a production of lead-acid
VRLA industry (Valve Regulated Lead-Acid) for motorcycles and jet skis, located
in the city of Bauru, SP, Brazil (RAND et al. 2004). The company has quality
integrated management system and environmental certificates based on standards
of the International Organization for Standardization (ISO) and National
Standards (NBR) under responsibility of the Brazilian Association of Technical
Standards (ABNT) (ABNT, 2008, 2004).
The battery formation starts with the introduction of
a sulfuric acid solution, density 1.25 g/cm3, in the boxes of the
batteries containing the positive and negative plates. This step is performed
with a filling device aid (Figure 1), and stops when the electrolyte
transshipment occur (CHEN et al. 1996; PROUT,
1993; KIESSLING, 1992).
Figure 1: Initial step of the formation process:
filling.
After filling, the batteries are allowed to stand in
the electrolyte for a period of 2 hours. This resting step is called soaking
which corresponds to the chemical reaction between sulfuric acid solution with
the oxide and basic lead sulfates resulting in the formation of surface layers
of lead sulfate (PbSO4) in the plate surfaces and the inner surfaces
of their macropores. These layers PbSO4 contribute to
electrochemical and thermal balances involved in this stage, increasing the
process efficiency (LAWRENCE et al. 2002; LAM et al. 1994). For the production
of VRLA batteries, the soaking step coincides with the suitable time for the
electrolyte absorption by the tabs (ZENG et al. 2015). After
the soaking process, the electrical connections are made in series, every 15
batteries, to be connected to sources of electrical current required to the
forming step.
It
was conducted a comparative study of the battery formation quality using manual
source of electric current (conventional) and an automated source of electric
current. In the manual source, the operator controls the time and adjusts the
desirable electrical current values; it tends to vary during the charging
process. The variation on the electric current is a result of chemical
transformations of the precursor materials (of low electric conductivity), to
chemical compounds, known as active materials, which are good electrical
conductors. When the contact between the electrical conductors is poor, due to
oxidation of the terminals and electrical ligaments present between the
batteries, it is possible to achieve zero electric current. Figure 2 shows the
image of a manual power supply control devices. It can be
observed that this type of controller is very old, and the high precision in
the battery formation process control is not possible to be achieved.
Figure 2: Manual power supply control devices.
The automated equipment incorporates a controller of internal
circuit switches, in which the current turns on and off in order to maintain
the constant output voltage, that is, one obtains a source of steady electric
current. These devices are controlled by software that allows choosing electric
current values and application times more accurately than when used analog
equipment. Table 1 shows the programming interface of the formation plan of a
lead-acid battery.
Table 1: Plan for lead-acid battery formation process.
Time is related to the battery permanency under electric charge, break,
discharge or recharge.
|
Current (A) |
Time (Hour) |
1st Charge |
0.6 |
1 |
2nd Charge |
0.6 |
2 |
3rd Charge |
1.5 |
23 |
1st break |
0.0 |
0.25 |
4th Charge |
3.0 |
2 |
2nd break |
0.0 |
0.25 |
Discharge |
2.0 |
2 |
Recharge |
1.5 |
8 |
The
battery forming process uses a water cooling system placed beneath the stand,
as shown in Figure 3. This process is necessary due to dissipate large
quantities of heat, and the temperature increases dramatically. High
temperature can negatively affect the electrochemical conversion of the active
materials precursors (RAND et al., 2004). Figure 3 shows the structure of the
stands where the batteries are formed using either manual or automatic current
source.
Figure 3: Batteries
positioned and ready to connect the source of electric current.
When using the automated source, throughout the
process, the software monitors and controls the electrical current and the time
for each step of the forming cycle. The high control of formation parameters
during the second charge of 10 batteries can be seen in the Table 2. The
average voltage is 178.1 ± 0.24 V, and the current average is 1.60 ± 0.02 A.
This fine control is considered impossible to be obtained by manual power source.
The temperature is controlled independently of the software, the entire process
is kept between 35°C <T <55°C.
Table 2: Software screen controller entire
forming system using the automated source of electric current.
Stand |
Charger |
Step |
Voltage (V) |
Current (A) |
Total Time (hour) |
Ampere Hour (AH) |
Status |
001 |
1 |
2nd Charge |
178.3 |
1.58 |
03:23:09 |
3.65 |
Running |
001 |
2 |
2nd Charge |
179.0 |
1.59 |
03:22:51 |
2.58 |
Running |
001 |
3 |
2nd Charge |
179.3 |
1.64 |
03:22:37 |
2.57 |
Running |
001 |
4 |
2nd Charge |
179.5 |
1.64 |
03:22:33 |
2.57 |
Running |
001 |
5 |
2nd Charge |
175.3 |
1.61 |
03:21:38 |
2.55 |
Running |
001 |
6 |
2nd Charge |
176.9 |
1.58 |
03:21:17 |
2.52 |
Running |
001 |
7 |
2nd Charge |
176.4 |
1.61 |
03:20:57 |
2.53 |
Running |
001 |
8 |
2nd Charge |
175.5 |
1.60 |
03:20:35 |
2.53 |
Running |
001 |
9 |
2nd Charge |
177.8 |
1.58 |
03:20:12 |
2.51 |
Running |
001 |
10 |
2nd Charge |
183.4 |
1.61 |
03:19:57 |
2.50 |
Running |
The parameters of battery formation are easy to be
monitored by the industry operators, once all of them are displayed in the
power source control screen (Figure 4). This kind of control is important because
during the formation process it is possible, for example, reset electrolyte in
the batteries in the case of excessive losses due to parallel reactions of
water decomposition.
Figure 4: Display
indicator of process variables (written in Portuguese).
At the end of this process, in open circuit, the
batteries are allowed to cool to 30ºC, so the electrolyte excess is drained,
and the forming process is finished.
In an attempt to obtain an indicative about the
efficiency of the formation process, the visual analysis was performed in the
positive plate of the battery samples. Samples of new batteries, obtained by
automated formation process, as well as samples of returned batteries, obtained
by manual formation process, were analyzed. This kind of test is destructive
and requires opening the battery to positive plate removal.
The method consisted in visually observing the color
throughout the positive plates, as the precursor material initially, basic lead
sulfate and lead oxide, have a white or yellow color. The final active material
(PbO2) is dark brown or black when in the presence of water. The
heterogeneous distribution of these colors indicates a low efficiency of the
electrochemical formation process, while the uniform distribution of black
color indicates a high possibility of a complete formation (PAVLOV, 1984; PAVLOV
et al.1972).
X-ray powder diffraction technique (XRPD) was used to
find the predominant chemical composition of the precursor material formed in
the positive plate (Watson 1945). The samples obtained to the visual inspection
were used to the XRPD analysis (manual and automated formation process), as
well as the material of the positive plate before the formation process.
The XRPD patterns of the samples were obtained on a
Rigaku equipment Gergenfex RINT2000 using radiation Cu-Kα1
(1.5818 Å) at 40 kV, 20 mA, between 20º≤ θ ≤ 80º with a scan speed 0.02º/min. The data
interpretation was based on the Powder Diffraction File (PDF) number 44-0872,
45-1416 e 72-2440 (JENKINS, 1986).
3. RESULTS AND DISCUSSION
The results of the visual, chemical, and electrical
characterization are presented in this section. It is important to explain that
all steps in the battery industrial process are checked, but the formation
process. Thus, if some problem occurs with the battery after sale, it is attributed
to failure on the formation process. The final test to ensure the quality
control of battery is done by sampling 10% of the lot. Consequently, some
batteries that do not achieve the quality standard, were not checked in the
final quality control, and were sold to batteries stores (auto parts and other
representatives), are received back by the industry and reprocessed.
To verify the influence on the use of automated sources
in replacing the manual ones in the battery formation process, a plan for the
54.3 Ah battery model (Ah) was applied. This plan can be seen in Figure 5,
wherein the programmed current value is given by the red line. The blue line
representing the self-correction of the electric current due to the large
variation tendency of the internal electrical resistance of the battery during
the formation process.
Figure 5: Data of formation of
the automated current source.
In terms of current load, the automated source
supplied 54.2 Ah to the battery, with only a difference of 0.18% in relation to
the planned deviation, considered negligible. In the process using the manual
source, this behavior was not possible to be reproduced, being the control of
these parameters infeasible and of low productivity.
Visual analysis of the positive plates was carried out
and the results presented. Figure 6 shows the positive battery plates when the
formation process was used: (a) manual source and (b) automated source.
Figure 6: Positive plates
of lead-acid battery: (a) formation manual process and (b) automated formation
process.
The visual inspection shows clearly the difference on
the quality of positive plate formed in the automated process. In Figure 6a,
the yellowish color indicates that the precursor materials (basic lead sulfates
and lead oxide) were not completely converted to PbO2 during the
formation process. The higher the amount of active material, better the battery
efficiency. Consequently, if the plate presents regions in which the precursor
materials were not converted to active material, its effectiveness will be
diminished.
The homogeneously distributed brownish black staining
on the positive plate, formed in automated process, can be observed in the
Figure 6b. It indicates that the PbSO4 has been completely oxidized
to lead oxide.
The current density in the formation of lead-acid
battery is critical to the growth PbO2 (PAVLOV, 2003). Thus, it is
very important that the current source feeds the positive plate with a constant
current density. Based on the visual analysis, it is possible to verify that
the automated source ensures a formation process of the lead-acid battery with
higher quality than the manual one.
The process of lead-acid battery formation occurs by
chemical conversion of precursor materials to the active α-PbO2 and β-PbO2
phases. The greater efficiency of the battery formation process, the greater
the amount of these phases in the positive plate. The α-PbO2 shows a
higher life-time and mechanical strength, being preferable to be formed in
positive plate of stationary batteries. Meanwhile, the β-PbO2 phase preferably
occurs in acidic medium because it is more stable electrochemically and offers
better performance, being interesting for starter batteries (BODE, 1977).
To build up the positive plate, pure lead is grinded
in a ball mill. This process results in a powder containing 25 to 30% wt of
free lead and 70 to 75% wt of lead oxide in its most stable structurally, the α-PbO
tetragonal. To this powder is added lead sulfate and additives, and then, this
sludge is applied on the lead grid. The resulting plate is transferred to the
oven at 60-80oC during 72 h, for curing process; after then, is
conducted to the formation process.
Figure 7 shows the XRPD patterns of the positive plate
material before and after manual or automated formation process. It was
identified the predominance of α-PbO phase in the sludge sample. This is very
interesting because this phase is preferably converted during the formation
process in β-PbO2 phase. However, the β-PbO
phase was also identified, what explain the presence of the α-PbO2
phase in the manual and automated sources samples.
The XRPD pattern of automated process shows only the
presence of β-PbO2 and α-PbO2
phases, what is quite desirable. In contrast, the XRPD pattern of manual
process shows the presence of α-PbO and β-PbO phases. These results revealed that the main
cause of battery failure is associated to the deficiency in the oxidation of
the precursor materials into the active material during the formation process.
Thus, the automated control of the formation process is more suitable to
achieve high quality of the battery performance. The lead oxide phase evolution
from α-PbO
to β-PbO2
phase was also identified in the studies of Palmer (2008) and Pavlov (2011).
Figure 7: XRPD pattern of
the positive plate before and after formation process using manual and
automated source.
The batteries produced using both manual and automated
formation processes were evaluated by electrical tests. They were conducted
using the methodology adopted by Inmetro, and described in the NBR 15941:2012
(ABNT 2012). The test of nominal capacity was performed at 25º ± 2ºC in 10-hour
discharge rate (C10), because of the batteries studied in this work are
used in motorcycles. If the battery were produced for use in car, testing is
performed in 20-hour system (C20).
The battery is considered approved if the value of the
capacity measure (C20 or C10) is greater than or equal to
95% of the rated capacity specified on the label for new batteries, collected
from the manufacturer or trade up to 90 days after its manufacture. Table 3
shows the results for the electrical testing C10.
Table
3: Results of the electrical tests - C10 capacity.
Battery |
Capacity
C10 (Ah) |
Capacity
C10 Minimum standard |
Result |
Automated |
6.13 |
5.0
Ah |
OK |
Manual |
4.72 |
5.0
Ah |
NOK |
OK: passed on the test
NOK: not passed on the test
It was observed that the battery formed using
automated source achieved a C10 current capacity 22.6% higher than
the minimum required. Already the battery formed using manual source did not
achieve the standard value (NOK) for this test, reaching a current capacity
5.6% lower.
To support the electrical C10 tests,
electrical tests of cold start current - “Cold Crank Ampère” or “Cold Cranking
Amps” (CCA) - were performed. This assay was performed at 10ºC, and the time (seconds)
required reaching the 6 volts voltage in the case of motorcycles batteries.
In test CCA for the motorcycles batteries are
considered approved if the time measured in discharge up to 6 V is greater than
or equal to that specified on the product label (BRAZIL, 2012). Results of the
CCA test are presented in the Table 4.
Table
4: Results of the electrical testing of cold start current: CCA.
Battery formation |
CCA 40A (s) |
CCA 40A Minimum |
Result |
Automated |
151 |
144 s |
OK |
Manual |
84 |
144 s |
NOK |
OK: passed on the test
NOK: not passed on the test
It was observed that the battery using automated
formation process also surpassed the standard value in 4.9% of the time for
supplying a constant electric current of 40 A. The tests of the batteries using
the manual formation process revealed that these ones also did not reach the
required by the standard for this test (NOK), reaching only 58.3% of the
standard value.
The economic evaluation for the automated formation
process line in the industrial production of lead-acid VLRA batteries for
motorcycles was carried out. It was taken in account the fact of 580,000
batteries/year were processed in the studied industry in the base year of
2014-2015. Since then, 33,000 batteries (5.69%) were reprocessed by deficiency
in the formation process. This number is related only to those batteries
returned to the industry after failure detection by the users.
The batteries are composed by electrical association
of 15 elements connected in series, resulting in 2,200 circuits to be reworked
of the total batteries with defect. It is needed to, approximately, 10 hours of
operation with electric current of 1.2 A, and a consumption electricity of 3.6
kilowatt-hour (kWh). Thus, it is estimated that over a period equivalent to one
year, the electricity consumption is about 7,920 kWh. In using the automated
formation process of the batteries, this energy consumption could be avoided,
since the process is more efficient.
At first, it appears that this economy (by not re-processing
of batteries) will not result in significant amounts, ie annual US$ 16,584.48,
considering the average cost as US$ 0.60 per kWh for the industrial electricity
(CPFL, 2015). However, it is feasible for the environmental aspects,
considering that the energy matrix in Brazil is based on hydroelectric power
plants. According to Machado (2015) 3,600 liters of water are needed to produce
1 kWh in a hydroelectric. So, the using of automated source is able to save
approximately 28,512 m3 of water annually.
One stand in the industrial line is exclusive to the
battery rework. Thus, when the production of NOK battery is avoided, this stand
is available for producing about 41,250 new batteries by year.
The cost to replace manual to the automated source is
estimated at US$ 523,000.00 (500 unities at US$ 1,046.00), once only the source
are object of replacing; all the other dispositive are the same used in manual
source control. As the industrial price average sale is US$ 15.00 per battery,
automation will result about US$ 618,750.00 on the annual revenue of the
industry, only considering the 41,250 new batteries produced by using of the
free stand in the production line. Thus, the investment can be paid in one
year. After that, the automation of the formation process will represent an
additional turnover of about US $ 618,750.00 a year.
4. CONCLUSION
This study showed the advantages of automating the
formation process of the lead-acid battery production. The visual analysis, as
well as, the XRPD analysis demonstrated that the manual process is not able to
convert the precursor materials to the active α-PbO2 and β-PbO2
phases. This indicated that a constant and stable control of the current
density in the formation process is essential to achieve the high efficiency of
the batteries. Thus, the replacement of manual source for automated is
relevant, since it increases the battery quality; consequently, it saves energy
and water resources, improves the use of lead source, decreases pollution
footprint associated for battery manufacture (rework), and is cost-effective.
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