# Patent

## Title
Battery management system and apparatus with anomaly reporting

## Abstract

The invention relates to the management of large stationary batteries. The invention is a comprehensive process for the management of stationary batteries that are used for backup power and are deployed in widely dispersed locations. The OMSTM (Optimization Management System) solution is comprised of Mega-Tags (preferably serialized bar-coded identification labels), a battery testing and data acquisition device, and web-based software. The OMSTM system employs algorithmic testing to determine whether a particular battery unit needs to be replaced or whether it can be advantageously redeployed. It also determines whether a particular deployment location contains anomalous readings, signifying potential problems with either the batteries themselves or possibly with other electrical equipment at the location. These components work together to provide a platform for managing a large number of perishable, expensive, and geographically dispersed assets.

## Background
CROSS REFERENCE TO RELATED APPLICATION
This application is a continuation-in-part of, and claims priority to, U.S. application Ser. No. 11/025,816, filed Dec. 29, 2004, related to U.S. application Ser. No. 11/025,305, filed Dec. 29, 2004, both applications being continuations-in-part of U.S. application Ser. No. 10/749,004, filed Dec. 30, 2003 now U.S. Pat. No. 7,003,431, all of the foregoing being incorporated herein by reference in their entirety.


BACKGROUND OF THE INVENTION
The invention relates to the management of large stationary batteries. The invention is a comprehensive system and apparatus for the management of stationary batteries that are used for backup power and are deployed in widely dispersed locations. The OMSTM (Optimization Management Solution) system is comprised of battery tags (sometimes referred to herein as “Mega-Tags,” which are preferably serialized bar-coded identification labels), a battery testing and data acquisition device, and the OMSTM web-based software. These components work together to provide a platform for managing a large number of perishable, expensive, and geographically dispersed assets.
The invention solves many of the unique problems associated with batteries. Batteries are perishable. That is, they have a limited shelf-life and a limited useful life. Stationary industrial batteries of the type that benefit from the OMSTM solution are typically sealed lead-acid batteries. These electromechanical devices typically must be installed within 6-10 months from date of manufacture or else they need to be recharged. In addition, most of these batteries are designed for a 10 year useful life, but in the field generally last only from 2-6 years. The discrepancy between design life and actual life is a major problem for users of these batteries.
Stationary batteries are also large, heavy and expensive. They are generally used in large numbers to provide the required backup power. Keeping track of these devices therefore provides an additional asset management challenge.
Batteries contain hazardous substances which are toxic to the environment. There are strict rules and regulations governing the disposal of batteries. These rules and regulations also contain documentation requirements. Users must be able to provide adequate proof of compliance or face severe penalties. Documentation is a highly manual, expensive process, and most compliance is done as an afterthought.
Batteries are generally deployed in strings of two or four 12-volt units, in strings of three 12-volt units, or in strings of six or twelve 2-volt units, in order to power 24 volt, 36 volt or 48 volt equipment. Other string configurations are also possible. This electrical combination of batteries compounds the difficulty of managing these storage devices. In sum, managing stationary batteries is difficult, and is generally not a core competency of most businesses that use these batteries.
BRIEF SUMMARY OF THE INVENTION
The OMSTM (Optimization Management Solution) system tracks batteries from cradle-to-grave. It enables companies with large deployments of stationary batteries to manage assets that are both perishable and geographically dispersed, and therefore difficult to manage. OMSTM is comprised of the following items which work together to provide this unique service: First, Mega-Tags (preferably serialized bar-coded identification labels) are affixed to every individual battery. A battery testing device (preferably the BatteryCorp BC-T2000 or BC Celtron or Ultra or similar testing device), which contains both a bar code reader and a serial port to connect to a PC, scans a Mega-Tag and then performs its test on any given battery. Batteries are usually deployed in “strings” of electrically interconnected units to increase voltage and output power. Each battery test data point is stored along with the unique identifier value associated with the individual battery unit. The user connects the BatteryCorp BC-T2000 or BC Celtron or Ultra (or similar testing device) to the serial port of a PC with the provided null-modem cable. Linking software (preferably the T2000 Link software) facilitates the transfer of data from the testing and data acquisition device to the PC internal storage. The user then logs into the proprietary website and clicks on the Upload Data icon; OMSTM then uploads the specified data file to a proprietary web server. The web server processes the data file, storing the pertinent data in the appropriate tables of the OMSTM database.
The invention provides comprehensive reporting and analysis options. This includes both operational and financial reports, as well as detailed recycling documentation. The OMSTM auto-notification feature emails reminders to customer technicians that testing is required. These emails are based upon customer-defined business rules. (Testing time period interval and escalation procedure, by business unit.)
The OMSTM solution enables users of stationary batteries to manage all aspects of their battery deployments. It is the only available tool that automates the process of uniquely identifying, testing, evaluating and reporting on the state of health of any given battery. It provides information on installation, deployment, testing, recycling and destruction. It provides information in both aggregate and detail formats, for both internal and external use.
Its advantages are many. It enables users to manage large, widely dispersed deployments of stationary batteries in an efficient and cost effective manner. It increases the reliability of the backup power plant, because the operator now has information on the performance status of the batteries. The system also facilitates the safe recycling of potentially toxic devices, while reducing the risk of non-compliance with governmental regulations.
OMSTM applies customer business rules to the uploaded test data, and automatically instructs the technician as to which specific battery or batteries, by serial number, need to be replaced. The technician no longer has to make any decisions, thus removing subjectivity from the process. OMSTM both produces reports which detail the specifics of the batteries to be replaced, and it sends automated email messages to the appropriate technician, with the relevant installation instructions.
The specific application of OMSTM that is the redeployment methodology invention is that OMSTM applies additional business rules and algorithms to the uploaded test data, and determines which batteries, if any, can be redeployed (reused) elsewhere. The viability of a battery for redeployment is based upon a number of business rules including but not limited to its age, its location, its weight, its rated useful life, its state of health as measured by its internal resistance to current flow, and its current voltage reading. OMSTM determines which batteries can be deployed, and to where. This provides significant cost savings to the user.
The OMSTM system employs algorithmic testing to determine whether a particular deployment location contains anomalous readings, signifying potential problems with either the batteries themselves or possibly with other electrical equipment at the location. In order to have visibility into the state of health of a stationary battery plant, it is necessary to periodically test the batteries. Upon testing, gross failure of the batteries is usually obvious. Less obvious are variations from accepted standards in voltage, temperature, and equipment configuration. The Anomaly Report searches large databases of stationary battery deployment data for this type of information. Lack of detection and correction of anomalies can result in the failure of the battery backup power system to perform its function in the event of a primary power outage.
Another object of the invention is to provide a battery management system easily applied to existing batteries without modification of the batteries, and that easily accommodates a varied inventory of batteries from different manufacturers.
Other objects and advantages will be more fully apparent from the following disclosure and appended claims.



BRIEF DESCRIPTION OF THE DRAWINGS
The above-mentioned and other features and objects of this invention and the manner of obtaining them will become apparent and the invention itself will be best understood by reference to the following description of an embodiment of the invention taken in conjunction with the accompanying drawings, wherein:
FIG. 1 is a representation of a tag for use with the present invention;
FIG. 2 is a perspective view of a battery unit with a tag associated with the battery;
FIG. 3 is a view of a battery testing and data acquisition device for use with the present invention;
FIG. 4 is a flow diagram illustrating the process of the present invention;
FIG. 5 is a flow diagram illustrating the battery replacement methodology;
FIG. 6 is a flow diagram illustrating a sample application of the replacement methodology;
FIG. 7 is a flow diagram illustrating the intelligent redeployment framework;
FIG. 8 is a flow diagram illustrating intelligent matching for redeployment with sample rules.



DETAILED DESCRIPTION
The invention provides and coordinates battery testing, maintenance, installation, fulfillment and disposal of batteries, and is capable of performing these functions over a wide geographical area. It seamlessly integrates these services via the BatteryCorp BC-T2000 tester and the OMSTM web based platform. This innovative solution helps companies improve their backup power systems while reducing costs.
FIG. 1 shows a preferred Mega-Tag to be associated with an individual battery. The tag is associated with a particular battery unit, so that the unique identification number embedded in the tag is consistently associated with that particular battery. Preferably to assure such continued association, the Mega-Tag is affixed to the exterior casing of the battery (5) with an adhesive, as shown in FIG. 2.
Mega-Tags are preferably bar coded labels that contain a unique identifier for the associated battery. The tag shown in FIG. 1 has, preferably, the following information: (1) the service provider name and telephone number; (2) the bar code of a unique identification number; (3) the battery model; and (d) the unique identification number in human readable form. Because of the preferred inclusion of human readable information in conjunction with the bar code identification number, the Mega-Tag is preferably affixed where it can be viewed and scanned by a human operator without dislocating the battery.
FIG. 3 shows a testing and data acquisition device for use with the present system. The device shown is a BatteryCorp BC-T2000 device. However, different testers could be used, but such testers should be able to import data from a bar code reader, and have the ability to export data files. The bar code scanner or reader is preferably in direct communication with the battery testing device for ease of use and reliable interface. This is preferably accomplished by use of a port (6) for a bar code reader and for connection to a computer. Also shown in FIG. 3 are ports for two testing probes (7), and A/C current in port (8) and an on/off switch (9). The data files can be in a number of formats, since the invention is a flexible platform with the ability to interface with data files in a number of formats.
In particular, the battery tester should be able to store test results in memory, associating each test with the pertinent unique scanned identifier. The tester also should be able to output the test results in an industry-standard file format, such as ASCII text or Excel XLS. The tester should be able to perform impedance or conductance testing (IEEE approved technologies). Many companies that utilize stationary batteries perform impedance or conductance tests.
In an alternative embodiment, the tester may operate with an infra-red thermometer, either integrated with the battery tester or otherwise in communication with the tester. The thermometer would read the temperatures of individual batteries, and the temperature associated with the unique identifier for that particular unit. Such a thermometer would provide additional information concerning the subject battery unit that would be read, uploaded and stored. Such a thermometer would obviate the need for a separate thermometer to record ambient temperature surrounding the battery units, which is stored along with the battery test data, and provide a more accurate reading of individual unit temperatures.
The testing device files preferably have the following header information. First, a Location Code is included with the file. This is a code that links the database of the invention, indicating the location of the battery. Second, the ambient temperature is stored along with the test information, because battery temperature is correlated with life expectancy. This information is also required by many battery manufacturers for warranty claims.
The testing device files preferably have the following detail information. First, there is a Unique Identifier that identifies the individual battery unit. Second, the date and time of the test are included in the file. Third, the test value, which is the individual battery unit test result, typically either an impedance value or a conductance value. It is the key indicator of the battery's health. The greater the impedance or the lower the conductance (they are inverse measurements of the same attribute) the poorer the state of health of the battery. Fourth, a strap test value, which is optional. Strap testing is a test of the interconnection between the current battery itself and the next battery in sequence (in the string). Fifth, a voltage is included, which is the voltage measurement of the battery. Voltage is another indicator for battery health and is also an indicator of the status of the device which is used to charge the battery.
Database management is another component of the present invention. Each battery test data point is stored along with the unique identifier value associated with the individual battery unit. This enables trend analysis reporting and individual battery detail reporting.
In operation, the user connects the battery testing device to the serial port of a PC with a null-modem cable, a standard computer peripheral device which is readily available. The linking software facilitates the transfer of data from the testing and data acquisition device to the PC internal storage. Typically, the user clicks the “Transfer” button displayed on the graphical user interface (GUI) of the software. The response will be “Waiting for data.” Prompts on the battery tester will guide the user to the menu option for downloading the data.
The user then logs in to the proprietary service provider website. The user will then click on the Upload Data icon displayed within the GUI. The linking software then uploads the specified data file to a proprietary web server. The web server processes the data file, storing the pertinent data in the appropriate tables of the OMSTM database.
Data elements stored include:

    
    
        a. Unique ID
        b. ID of the user who performed the test
        c. Test date and time
        d. Test type (Impedance or Conductance)
        e. Test measurement value
        f. Strap measurement value if applicable
        g. Voltage
        h. Ambient temperature
    
    


The invention then generates comprehensive reporting and analysis, including preferably the following:

    
    
        a. Battery Test History (detail by location)
        b. Battery Test Summary (overview of tests and results)
        c. Untested Batteries (verification tool)
        d. Battery Installation Aging (based upon installation date)
        e. Performance Status Report (analysis which groups batteries based upon user-defined status criteria for “pass”, “fair”, “warning” and “fail”)
        f. Replacement Forecast (analysis based upon user-defined criteria to estimate costs of upcoming replacements)
    
    


Auto-notification is another part of the present invention. This feature is based upon customer-defined business rules. These rules typically test interval and escalation procedure, automatic battery replacement intervals and escalation procedures. These business rules can be specified by customer-defined business units. Business units might be geographical areas, product line groupings, etc. This provides considerable flexibility for the user in how to utilize the automated notification process. All notifications are preferably made via email or other electronic transmission means.
FIG. 4 provides a high-level overview of the process of the present invention. The OMSTM software will send an automated email notification to the pertinent technician that various locations require battery testing. This process is called Auto Notification. The person that is informed of the required testing can be either an internal (i.e. employee of the customer company) or an outsourced (third party) technician. This Auto Notification feature is not required for functioning of the present invention, since users may utilize the OMSTM software with this feature disabled, and set up their testing schedule separately.
The technician tests the batteries with the battery tester and uploads the data via a network connection, preferably a global computer network such as the Internet, to the OMSTM proprietary database, preferably located on a server. Upon receipt of uploaded data files, the OMSTM software immediately processes the data and sends an automated report (Auto Report) back to the technician. The report will indicate whether the batteries all “Passed,” or if any “Failed” the test. The report may also provide instructions to the technician on whether or not to replace any given battery or all batteries, depending upon the business rules for that customer (Auto Replacement). If Auto Replacement is enabled, the OMSTM software will route the appropriate information to the pertinent installation technician. The OMSTM software may provide recycling documentation, so that batteries being replaced may be properly recycled.
An Auto Report is generated via the battery tester and sent via a network connection, preferably through a global computer network such as the Internet, to the OMSTM proprietary software and to the OMSTM database.
The OMSTM software platform has been built using programming tools from Microsoft. The integrated development environment (IDE) includes productivity boosting features such as automated syntax management, a powerful editor, line-by-line debugging, graphical design tools (including visual classes and subclasses), and integrated database access. The platform is fully object-oriented, offering developers the benefits of full inheritance, encapsulation and polymorphism. This dramatically reduces design, coding, and testing times, producing a highly efficient rapid application development (RAD) environment.
The methodology employed in the OMSTM platform can be referred to as business function modeling (BFM). The entire orientation of the development effort revolves around the business rules and processes. This may also be referred to as an object functional model. Each function encapsulates a particular business task, yet from a development point of view it also inherits any and all system functions necessary to perform the intended task.) For example, a purchase order object would accept the request, access the necessary data, employ all pertinent business rules, validate the posted data, update the database, and generate a response—all within a single software object. This is a major architectural advantage.
FIG. 5 shows the Replacement Methodology Framework that comprises the steps of

    Developing standards with the customer
    Converting standards into OMSTM business rules
    Acquiring data, identifying the sites and batteries
    Creating Mega-Tags for every individual jar/battery
    Testing the batteries and uploading the data to OMSTM
    Applying the business rules to the test results
    Electronic notifying of replacement with instructions to technician keyed to the battery to be replaced.


FIG. 6 also shows a set of sample rules created for the replacement determination method, together:
The general rule is to test batteries every X months, X being a value assigned in view of the particular type of batteries. The X value can be automatically scheduled by the OMS software. The sample value for X is shown as 12 months. Common values for X are 3 months, 6 months, and 12 months.
The second value X is an age value, where the business rule would be to replace the battery if it is older than X months. The sample value for X is 60 months, with the option under the rule to not replace the battery based on the battery's age.
The test results for the individual battery are uploaded into the OMS software. The preferred status options generated from an application of the business rules to the test results will be: Pass; Fair; Warn; or Fail. The test results are compared by OMSTM to a known benchmark for the pertinent battery type. Based upon the difference, in percent, between the benchmark value and the actual test value, OMSTM makes the determination as to the status. For example, if a battery tests at 1.87 milliohms and the benchmark is 1.0 milliohms, then the percentage difference is 87% and the battery would Fail; if the battery tests at 1.05 milliohms then the percentage difference is 5% and the battery would Pass. The percentage criteria for determining the status are business rule settings that are determined by the customer and input into OMSTM. This methodology is employed for both types of ohmic testing—impedance and conductance. In FIG. 6, based upon the type of battery being tested and the business rule setting for Failure, the example shows that a test result of 2.87 milliohms or higher would result in OMSTM considering the battery to have a status of Fail. In FIG. 6, the impedance value is set at 2.87 milliohms, and the system will issue a Fail message if the impedance value obtained from the test results is greater than 2.87 milliohms.
FIG. 6 also shows a business rule based on the string average variance obtained by comparing the ohmic test value (either impedance or conductance) measured for a battery in a string to the average conductance value for the battery string. In the sample, the system will generate a replacement notification signal if the conductance value for the individual battery is 25% lower than the average conductance value of the battery string.
Although the present system is fully automated within the limits of the problems faced, a visual inspection of the battery should not be overlooked. Such visual, on site examination is used to determine whether adverse conditions exist that could affect battery life, safety concerns or cause possible environmental damage. Ordinarily, a battery would be replaced if the inspection revealed leakage of electrolyte, cracking of the battery case or any other physical damage that may implicate the above concerns.
The Warn signal is a conditional message that allows the user to determine if a battery should be replaced or not replaced. One consideration is that if other batteries at the same location as the battery in Warn status are to be replaced, it may be more economical and efficient to replace the Warn status battery with the others at the same time. This concept also applies to string replacement, where an entire string of batteries should be replaced if a predetermined percentage of batteries fail, or if substantially all of the batteries in the string are of a predetermined age value. The sample shown in FIG. 6 shows an age value of 3 years based on the installation date, and a replacement message is generated if more than 40% of the batteries in a string generate a Fail message or are at least 3 years old. This business rule utilizes two settings that are determined by the customer and implemented in OMSTM: (1) the percentage of the string that is required to trigger the replacement, and (2) the age required to trigger the replacement. Common values for the percentage range from 25-50% and for the age range from 2 years to 4 years.
FIG. 7 is a flow diagram illustrating the intelligent redeployment framework. The redeployment framework begins by developing standards for the user of the batteries, and converting the standards into business rules within the OMSTM software. Data is then acquired that identifies batteries and sites. A unique identifier is created for each individual jar or battery, preferably a bar code identifier that is associated with the individual battery. The batteries are then tested and the data uploaded to the OMSTM software, which applies the generated business rules to the test results.
The notification signal generated by the OMSTM based on the application of the business rules to the test results is either a signal to recycle a spent battery or to salvage a reusable battery. If the result is a signal to recycle, the OMSTM system may supply recycling instructions and documentation to a technician for proper disposal of the spent battery unit. If the signal is to salvage the reusable battery, then the OMSTM system engages in intelligent matching of the battery units into deployable strings that will effectively extend the useful life of the battery without endangering the power supply. The signal will contain instructions to the technician in the proper replacement or redeployment of the individual battery units to achieve this objective. It will specify the serial number(s) of the batteries to be redeployed, as well as the location to which to redeploy the battery or batteries.
FIG. 8 is a flow diagram illustrating intelligent matching for redeployment with sample rules. The battery status is checked, and while the OMSTM system is in redeploy status, the battery location is also checked. The battery's float voltage is checked, the float voltage being the voltage measured when the battery is attached to a power source for recharging, also known as a power charger source. Finally, the battery age is checked to determine whether redeployment is still worthwhile.
The sample rules in FIG. 8 illustrate the method in practice. When the battery status is Pass, as shown in the replacement methodology, redeployment is considered. Once the location of the unit is determined, a decision is made as to whether or not the unit can be redeployed either in the same location or elsewhere in the same market area. If redeployment is still an option, then OMSTM determines whether or not the battery meets the float voltage specifications for redeployment. The last rule shown in FIG. 8 indicates that redeployment would proceed only if the age value of the battery is less than the specified value (36 months in the example) since redeployment is advantageous only where there is sufficient useful life left in the battery to justify the redeployment. The battery age criterion can vary from 30 months to 120 months according to the battery type.
Anomaly Reporting
The OMSTM system employs algorithmic testing to determine whether a particular deployment location contains anomalous readings, signifying potential problems with either the batteries themselves or possibly with other electrical equipment at the location.
In order to have visibility into the state of health of a stationary battery plant, it is necessary to periodically test the batteries. Upon testing, gross failure of the batteries is usually obvious. Less obvious are variations from accepted standards in voltage, temperature, and equipment configuration. The Anomaly Report searches large databases of stationary battery deployment data for this type of information. Lack of detection and correction of anomalies can result in the failure of the battery backup power system to perform its function in the event of a primary power outage.
A primary test of battery status and health is the measurement of the impedance of the unit, specifically the internal impedance of the battery as determined from the difference between the voltage without an external load and with a load, and where the voltage divided by the amperage will yield the internal impedance of the battery using the familiar formula R=E/I, where R is the resistance, E is the voltage, and I is the amperage or current. As a battery ages, the difference between its unloaded and loaded voltages becomes greater. In other words, as batteries become drained of their energy-producing capabilities, their internal impedance rises. An ideal power source would exhibit, theoretically, zero ohms of internal impedance.
Specific analysis of battery data creates Anomaly Report information of the following types:

    
    
        1) Cell Voltage. If the tested voltage exceeds the rated nominal voltage by 16.7% or more, or if the tested voltage is lower than the rated nominal voltage then it is reported as an anomaly. Low or high voltage in conjunction with a poor ohmic test result confirms that the battery is bad, but low or high voltage in conjunction with a passing ohmic test result could signify electrical problems in the charging equipment. Example: rated voltage of 12V but battery test results show voltage reading of 15.7.
        2) Equipment vs. Battery Voltage. If the specified voltage of the equipment does not match the specified voltage of the batteries then the anomaly is reported so that the false information can be corrected. Example: rated equipment voltage is 48V, and batteries are listed as 12V each, but only two batteries in the string for a total of 24V. The anomaly is reported so that the customer can determine that either the equipment is incorrectly reported as 48V and is in fact a 24V unit, or the cabinet may be missing two batteries.
        3) High Temperature. This type of anomaly could easily occur without a failing ohmic test result. High temperature is usually caused by failure in the plant's cooling system. Failure to correct high temperature conditions can lead to premature equipment and battery failure. Example: ambient temperature reading of 85° F. The ambient temperature may be calculated from a number of individual readings, where the ambient temperature may be determined as an average over a specific time period.
        4) Low Temperature. This type of anomaly could also occur without a failing ohmic test result. Low temperature is usually caused by failure in the plant's heating system. Failure to correct low temperature conditions can lead to equipment malfunction and poor battery performance. Example: ambient temperature reading of 4° C.
        5) Unknown Equipment & Batteries. This anomaly consists of battery data in the system that lacks an equipment specification. This condition precludes OMSTM or any similar software from being able to make informed decisions as to the battery state of health. Without knowing the equipment, and therefore the appropriate baseline test value, any ohmic test readings become meaningless.
    
    


The following table shows typical report details for the anomaly report. In addition to identifying particular user, the time period of the report and various site data, the report would show the string number of the unit, the unit's position within the string, the equipment type (manufacturer and model), the identification number (preferably a serial number from a bar code label affixed to the unit), the manufacturer's part number, the voltage specification, the date of manufacture of the unit, the test date, the ohmic test value, the ohmic test baseline (standard) value, the battery ohmic test status (typically pass, fair, poor or fail), the battery voltage reading, the ambient temperature, and the anomaly type.


















Equip-






String
Posi-
ment

Part
Volt-
Date of


No.
tion
Type
ID
No.
age
Mfg.







1
3
PCP
196813
TEL12-12550
12.0
Sep. 5, 2001


2
2
PCP
118192
TEL12-125
12.0
May 1, 2000

























Test
Test
Base

Test
Amb.



Date
Value
Line
Status
Voltage
Temp.
Anomaly







Aug. 2, 2005
3.130
3.000
Pass
13.525
74 F.
Low








Impedance


Aug. 3, 2004
3.130
3.000
Pass
14.111
70 F.
Cell








Voltage









Finally, the OMSTM platform contains a rich set of connectivity tools. It can easily import/export data in various formats, from plain text to delimited files to Excel to XML. In fact, the battery tester upload module accepts data in both text and XLS formats. OMSTM can also directly access any ODBC compliant data source, such as Oracle, DB2 and other databases. However, we expect that the XML classes in particular will facilitate seamless communication between OMSTM and any related systems.
The specific products utilized to build OMSTM


    
    
        Microsoft Visual FoxPro 7.0 (IDE)
        West Wind Web Connection (Base classes for web services)
        Macromedia HomeSite (HTML/JavaScript editor; any can be used)
        IDAutomation.com bar code fonts
        Adobe Acrobat 5.0

Web Connect by West Wind Technologies is a framework of base classes for building web applications. These classes perform all low-level functions for authentication, request management, session management, data formatting and output. It may be preferable to use updated versions of the above programs as they become available.

    
    


Since other modifications or changes will be apparent to those skilled in the art, there have been described above the principles of this invention in connection with specific apparatus, it is to be clearly understood that this description is made only by way of example and not as a limitation to the scope of the invention.

## Claims

1. A method for managing batteries by determining an anomaly, comprising the steps of:
creating a battery health standard, the battery health standard having a set of standard values;
creating a unique identifier for a battery;
inputting the unique identifier into a battery tester;
performing a plurality of tests on the battery with the battery tester;
generating a test value from the each test performed on the battery;
associating the test value with the unique identifier;
storing the test value in a database;
comparing the stored test value with a selected standard value of the battery health standard;
determining whether the test value meets the selected standard value;
generating an anomaly report for test values that fail to meet the standard value;
describing an anomaly in the anomaly report;
storing the anomaly report in the database.

2. The method of claim 1, further comprising the steps of:
generating a chart representing data in the anomaly report;
storing the chart in the database.

3. The method of claim 1, further comprising the steps of:
connecting the database to a computer network;
transmitting data in the anomaly report to a user of the computer network;
receiving a message with the transmitted data on a device connected to the computer network.

4. The method of claim 1, wherein the standard values comprise an impedance value, a degradation value, and an age value.

5. A method for managing batteries by determining an anomaly, comprising the steps of:
creating a plurality of battery health standards, each standard having a nominal voltage value;
creating a unique identifier for a battery;
inputting the unique identifier into a battery tester;
performing a plurality of tests on the battery with the battery tester;
generating a voltage value from rests performed on the battery;
associating the voltage value with the unique identifier;
storing the voltage value in a database;
comparing the voltage value with the nominal voltage value;
calculating a difference between the voltage and the nominal voltage value;
storing a first anomaly value in the database if the voltage exceeds the nominal value by a predetermined percentage;
storing a second anomaly value in the database if the rated nominal value exceeds rated voltage value by the predetermined percentage; and
generating an anomaly report having anomaly data.

6. The method of claim 5, further comprising the steps of:
connecting the database to computer network;
transmitting data in the anomaly report to a user of the computer network;
receiving a message with the transmitted data on a device connected to the computer network.

7. The method of claim 5, wherein said predetermined percentage is about 16.7 percent.