Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Electrical signal parameter measurement system
Reexamination Certificate
2001-05-02
2003-09-09
Hoff, Marc S. (Department: 2857)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Electrical signal parameter measurement system
C702S031000, C702S063000, C702S085000, C702S182000, C320S127000, C320S130000, C320S136000, C324S426000, C324S430000, C324S433000, C700S052000, C700S089000, C700S108000, C307S018000, C307S024000, C307S046000
Reexamination Certificate
active
06618681
ABSTRACT:
FIELD OF THE INVENTION
The invention relates to a method and apparatus for predicting the available energy of a battery and the available run time for such a battery at any state of charge by use of a non-invasive test procedure.
BACKGROUND OF THE INVENTION
It is often desired to determine the actual capacity of a battery, usually measured in amp hours (Ah), and particularly a lead-acid storage type. Conventional methods for determining the capacity of a lead-acid storage battery involve fully charging the battery to 100% state of charge (SOC) and then fully discharging the battery at a constant current (amperes) value. The battery capacity is determined by multiplying the discharge current value (in amperes) times the discharge time (in hours) needed to fully discharge the battery.
Following the discharge to determine its capacity, the battery must be fully charged again to be ready for use. As seen, this method involves a significant amount of charging and discharging and is time consuming since it takes a relatively long time for each of the charge and discharge cycles. The cycling method also may be destructive of the battery health. For example, in a lead-acid storage battery, gassing may occur in overcharging the battery, and cause damage. Also, there is wear of the battery due to the charge/discharge cycling.
The foregoing test basically provides an analysis of the static condition of a battery and is not a measure of its future performance. It also is often important to be able to predict the available energy that a battery can deliver when at a given condition of charge, e.g., when fully charged (100% SOC) or at less than 100% SOC. The available energy of a battery is different from its rated capacity. Battery capacity is the maximum amount of energy that can be stored and retrieved from the battery. Available energy is a function of the battery SOC. That is, the battery capacity is assumed to be that as rated by the manufacturer or the value determined most recently by actual discharge testing as described above. Battery rated capacity is the same at all states of charge. But a battery can be at various states of charge (SOC) from 0% to 100%. The battery rated capacity (Ah) times the state of charge (SOC) determines the available energy that can be delivered by the battery. Thus, it is apparent that actual available energy decreases with decreasing states of charge.
Being able to predict the available energy can be important, for example, in a mission critical application, such as an uninterruptible power source (UPS), since this determines the time that the source battery can perform its function. This is sometimes called battery “run time”, which is the time that the battery can operate in its application at a given current drain based on the available energy until full discharge. This is calculated based on the available energy of the battery at its present SOC and the discharge current of the application.
As should be apparent, maintenance personnel and time are required to test a battery using the prior art charge/discharge cycling method described above for determining battery actual capacity. Also, to do this, a battery has to be taken off line for testing, during which time the battery is not available for its designated application, such as in an UPS.
Another method for determining battery capacity has been developed by the assignee of this application, as described in U.S. Pat. No. 5,049,803. That method determines battery actual capacity through active testing of a fully charged (100% SOC) battery without requiring that the battery be discharged. This test is significantly faster than the conventional discharge-charge cycling described above, and has no harmful effect on the battery and its performance. If the battery actual capacity, i.e., available energy, is known, the run time can be calculated if the rate of current discharge of the application is known. However, the method described in this patent is limited in application to batteries in a fully charged state, i.e., 100% SOC.
Accordingly, a need exists for predicting the available energy of a battery over a range of SOC values without having to perform the charge/discharge cycling or to fully charge the battery. If the available energy is known, the run time of the battery, that is, the time that the battery can successfully operate in its application, can be computed.
BRIEF DESCRIPTION OF THE INVENTION
The present invention is directed to a method for predicting the available energy of a battery independent of its state of charge (SOC) without having to discharge the battery and from this to determine run time. In a preferred embodiment of the invention, the system includes a programmable computer that controls the testing.
In accordance with the invention, a prediction algorithm in equation form is first developed by testing a battery to acquire data of various battery parameters such as its internal resistance (IR), operating temperature (T), open circuit voltage (OCV) and gas point voltage responses to both a charging and a discharging current. The values of these parameters are subjected to mathematical analysis to develop the algorithm equation that has various numerical weighting factors for the parameters. The equation also can include a numerical offset value.
To predict the available energy of a battery being tested, the battery is tested to acquire data of the parameters. To obtain the value of IR, a charging current pulse is applied and battery internal resistance (IR) is determined based on the voltage response. The OCV and T are measured directly. A ramp current is applied to the battery and the voltage response to the ramp is monitored, and from this data the parameters of the gas points of battery charge and discharge are determined. The values of the acquired parameters of the battery are applied to the equation and the solution is the predicted available energy. All of the acquisition of the parameter data values and prediction of the available energy is accomplished under control of a computer and is done on a non-invasive basis, i.e., there is no need to access the battery structure such as to measure the electrolyte. Also, the testing and prediction are accomplished in a rapid manner.
Available energy of the battery can be predicted at various states of charge (SOC) and is not dependent on whether the battery is fully charged. The invention has been successfully developed and tested for lead-acid batteries having capacities over the range of 2 Ah to 25 Ah and is applicable to batteries of various ranges of capacities.
OBJECTS OF THE INVENTION
It is therefore an object of the invention to provide a method to predict the available energy of a battery.
Another object is to provide a method to predict the available energy of a battery over a range of battery SOC without having to discharge the battery or perform invasive testing.
Yet a further object is to provide a method to predict the available energy of a lead-acid storage battery by subjecting it to pulse and ramp type current testing and measuring various parameters.
Another object of the invention is to provide a method to predict the available energy of a battery by non-invasive testing.
REFERENCES:
patent: 4745349 (1986-10-01), Palanisamy et al.
patent: 6411911 (1992-06-01), Hirsch et al.
patent: 5281919 (1994-01-01), Palanisamy
patent: 5642100 (1995-09-01), Farmer
patent: 6137292 (1999-05-01), Hirsch et al.
patent: 6215312 (2001-04-01), Hoening et al.
Eagan Margaret
Hoenig Steven
Palanisamy Thirumalai G.
Singh Harmohan
Desta Elias
Hoff Marc S.
Honeywell International , Inc.
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