APPARATUS AND METHOD FOR TESTING STATE OF CHARGE IN BATTERY
First Claim
1. An apparatus for estimating a state of charge (SOC) in a battery, the apparatus comprising:
- a detector unit including a current detector for detecting current from a battery cell, a voltage detector for detecting voltage from the battery cell, and a temperature detector for detecting temperature from the battery cell;
a soft computing unit for calculating and outputting a battery SOC estimation value by processing the current, the voltage and the temperature detected by the detector unit using a first computing algorithm, which is a combination of a neural network algorithm and a second computing algorithm which adaptively updates parameters, the soft computing unit storing the battery SOC estimation value in a memory; and
a comparator operably coupled to the soft computing unit and a charger-discharger, the charger-discharger being further operably coupled to the battery cell, the comparator comparing the battery SOC estimation value with a predetermined target value that varies with charging or discharging of the battery, the comparator further providing an algorithm update signal to the soft computing unit to update the first computing algorithm based on a learning algorithm when a difference between the battery SOC estimation value and the predetermined target value is outside of critical range.
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Abstract
Disclosed is an apparatus and method for estimating a state of charge (SOC) in a battery, in which the battery SOC is estimated using a fusion type soft computing algorithm, thereby accurately estimating the battery SOC in a high C-rate environment. The apparatus includes a detector unit for detecting current, voltage and temperature of a battery cell; and soft computing unit for outputting a battery SOC estimation value of processing the current, the voltage and the temperature detected by the detector unit using a radial function based on a neural network algorithm. Especially, the soft computing unit combines the neural network algorithm with any one of a fuzzy algorithm, a genetic algorithm (GA), a cellular automata (CA) algorithm, an immune system algorithm, and a rough-set algorithm, and thereby adaptively updates the parameters of the neural network algorithm.
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Citations
16 Claims
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1. An apparatus for estimating a state of charge (SOC) in a battery, the apparatus comprising:
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a detector unit including a current detector for detecting current from a battery cell, a voltage detector for detecting voltage from the battery cell, and a temperature detector for detecting temperature from the battery cell; a soft computing unit for calculating and outputting a battery SOC estimation value by processing the current, the voltage and the temperature detected by the detector unit using a first computing algorithm, which is a combination of a neural network algorithm and a second computing algorithm which adaptively updates parameters, the soft computing unit storing the battery SOC estimation value in a memory; and a comparator operably coupled to the soft computing unit and a charger-discharger, the charger-discharger being further operably coupled to the battery cell, the comparator comparing the battery SOC estimation value with a predetermined target value that varies with charging or discharging of the battery, the comparator further providing an algorithm update signal to the soft computing unit to update the first computing algorithm based on a learning algorithm when a difference between the battery SOC estimation value and the predetermined target value is outside of critical range. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A method for estimating a state of charge (SOC) in a battery, the method comprising the steps of:
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detecting current, voltage and temperature from a battery cell, utilizing a current detector, a voltage detector, and a temperature detector, respectively; calculating a battery SOC estimation value by processing the detected current, voltage and temperature using a first computing algorithm, which is a combination of a neural network algorithm and a second computing algorithm which adaptively updates parameters, utilizing a soft computing unit; storing the battery SOC estimation value in a memory utilizing the soft computing unit; calculating a difference value between the calculated battery SOC estimation value and a predetermined target value varying with charging or discharging of the battery utilizing a comparator operably coupled to the soft computing unit and a charger-discharger; sending an algorithm update signal from the comparator to the soft computing unit when a difference between the battery SOC estimation value and the predetermined target value is outside of a critical range; and updating the first computing algorithm based on a learning algorithm utilizing the soft computing unit in response to the algorithm update signal. - View Dependent Claims (10, 11, 12, 13, 14, 15, 16)
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Specification