PATENT CLAIM ANALYSIS

Application Number: 15913169
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-07
Patent Classification: ["701", "103000"]

Abstract:
A method for controlling an electronic throttle control (ETC) system, in which an electronic control unit (ECU) controls the ETC system using an air volume learning value containing information on a volume of air introduced into an engine for each opening degree of the ETC system according to carbon deposit of the ETC system, the method may include reading an air volume learning value used during a previous operation. The air volume learning value is compared to a preset learning value change reference value. Whether an operation condition of the engine satisfies a learning value change condition which is preset to change the air volume learning value, and whether the volume of air passing through the ETC system satisfies a preset learning-value-change-air-volume condition are determined. The air volume learning value used during the previous operation and stored in the ECU is substituted with a preset initial value of the air volume learning value.

Claim (Index 5):
The method of  claim 2 , wherein when the engine RPM is smaller than a preset peak RPM reference value for each start temperature of the engine, the ECU performs the step of determining whether the volume of air passing through the ETC system satisfies the preset learning-value-change-air-volume condition.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 90.0
- Lexical Diversity: 2.44776
- Patent Class: 701.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15350884', '15105953', '12659053', '10864549', '10881735']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4444148920768688
- 35 USC 102 Novelty (BERT): 0.4817438461198658
- Combined Prediction Score: 0.4481477874811685
- Mean Citation Score: 156.489722
- Max Citation Score: 172.4446
- Similarity Product: 118.55907496170998

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

Dataset: test