PATENT CLAIM ANALYSIS

Application Number: 15960767
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2018-10
Patent Classification: ["320", "107000"]

Abstract:
The present invention relates to a method for predicting the state of health of a battery based on numerical simulation data. A method for predicting the state of health of a battery, which is performed by a battery management system, according to an embodiment of the present invention includes: a step of obtaining a verified numerical simulation database, into which solution data of the battery is extracted and stored, when a numerical analysis result is verified by an experimental result using electrical and chemical analysis of the battery; a step of counting the number of charges or discharges when a deviation between reference data read from the verified numerical simulation database and measurement data read from the battery is within a preset range and battery capacity satisfies a preset condition; and a step of predicting a state of health of the battery using the number of charges or discharges and a classifier based on a learned machine learning algorithm.

Claim (Index 13):
A method for predicting a state of health of a battery based on numerical simulation data, the method being performed by a battery management system and comprising:\n a step of obtaining a verified numerical simulation database, which solution data of the battery is extracted from and stored in, when a numerical analysis result is verified by an experimental result using electrical and chemical analysis of the battery; a step of comparing the measured data read from the battery with the reference data read from the verified numerical simulation database; a step of counting the number of charges when a charging time necessary to reach a first target voltage is within a maximum allowable time and battery capacity satisfies a first preset condition, or counting the number of discharges when a discharging time necessary to reach a second target voltage is within a minimum allowable time and the battery capacity satisfies a second preset condition; a step of predicting the state of health of the battery using the number of charges or discharges and a classifier based on a learned machine learning algorithm; and a step of emergency stopping the battery from being charged through a safety algorithm when the charging time is out of the maximum allowable time to reach the first target voltage, or emergency stopping the battery from being discharged through the safety algorithm when the discharging time is out of the minimum allowable time to reach the second target voltage.

Metadata:
- Claim Count in Document: 32.0
- Percentile: 91.0
- Lexical Diversity: 2.33333
- Patent Class: 320.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['12423922', '13269406', '15359099', '14645893', '15372836']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6986011079314222
- 35 USC 102 Novelty (BERT): 0.4799731182281532
- Combined Prediction Score: 0.6767383089610952
- Mean Citation Score: 199.59588
- Max Citation Score: 210.01872000000003
- Similarity Product: 165.33391632047656

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test