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 7):
The method for predicting the state of health of the battery based on numerical simulation data of  claim 6 , wherein the step of emergency stopping comprises:\n a step of reading n-th error values and (n\u22121)-th error values from an error database; a step of calculating a sum of error deviation values of deviations of the n-th error values and the (n\u22121)-th error values; a step of determining whether a preset maximum error value is less than or equal to the sum of the error deviation values calculated; a step of calculating a battery capacity being charged or discharged when the preset maximum error value is more than the sum of the error deviation values calculated; and a step of emergency stopping the battery from being charged or discharged when the preset maximum error value is less than or equal to the sum of the error deviation values calculated.

Metadata:
- Claim Count in Document: 32.0
- Percentile: 91.0
- Lexical Diversity: 2.33333
- Patent Class: 320.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['12423922', '13269406', '15359099', '14645893', '15372836']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7204020010131122
- 35 USC 102 Novelty (BERT): 0.4955217816976913
- Combined Prediction Score: 0.6979139790815702
- Mean Citation Score: 199.59588
- Max Citation Score: 210.01872000000003
- Similarity Product: 143.1901390338135

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