PATENT CLAIM ANALYSIS

Application Number: 16035273
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2018-11
Patent Classification: ["123", "406230"]

Abstract:
A system and method for dynamically varying an amount slippage of a Torque Converter Clutch (TCC) provided between an engine and a transmission of a vehicle in response to non-powertrain factors. By varying a slippage output signal, the amount of TCC slippage between the engine and the transmission can be adjusted. Small amounts of slippage, relative to large amounts of slippage, provide (a) improved vehicle fuel economy, but (b) induce more powertrain noise and vibration in the vehicle cabin. By dynamically adjusting the slippage, a tradeoff between improved fuel economy vs. a satisfying driver experience can be realized.

Claim (Index 11):
A skip fire engine controller, comprising:\n at least one lookup table embodied in a non-transitory computer readable media, the at least one lookup table including table entries that indicate different maximum allowable cylinder loads at different vehicle operating parameters; a skip fire profile module arranged to determine an operational firing fraction suitable for delivering a requested engine output, wherein the skip fire profile module utilizes the at least one lookup table to determine the operational firing fraction and adjusts the operational firing fraction based at least in part on whether noise and vibration generated external to the engine at least partially masks noise and vibration generated by the engine; and a firing controller arranged to direct firings in a skip fire manner that delivers the operational firing fraction.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 95.0
- Lexical Diversity: 1.88333
- Patent Class: 123.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15681601', '15148826', '14638908', '14992779', '15679419']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.795007698372385
- 35 USC 102 Novelty (BERT): 0.583687487480904
- Combined Prediction Score: 0.7738756772832369
- Mean Citation Score: 424.104058
- Max Citation Score: 535.14825
- Similarity Product: 462.9819958399684

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

Dataset: test