Multiple algorithm event discrimination method
AssigneeDelphi Technologies, Inc.
InventorsPeter Schubert, Chad Aeschliman, Benjamin Wiles
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Abstract
An event discrimination methodology executes multiple versions of the same or different event discrimination algorithms and logically or arithmetically combines their outputs to distinguish between specified events and non-events. One given algorithm is repeatedly executed with different sets of calibration data, or alternately, a number of different algorithms are executed. In cases where the algorithm results are arithmetically combined, the weights accorded to each algorithm result are dynamically adjusted based on driver input or vehicle dynamic behavior data to accord highest weight to the algorithm(s) calibrated to identify events associated with the detected driver input or vehicle dynamic behavior.
Claims10
A method of discriminating an occurrence of a specified event in a system based on measured or estimated system parameter data pertinent to said event, the method comprising the steps of:
- executing a number of event discrimination algorithms individually calibrated to detect different patterns of parameter data that are characteristic of the occurrence of said specified event, each algorithm producing an event discrimination output;
- and
- combining the event discrimination outputs produced by each of said algorithms to form a single output that discriminates the occurrence of said specified event.
Dependencies are inferred from the claim text.