METHODS, SYSTEMS, AND APPARATUSES OF PURGE CONTENT ESTIMATION LOGIC FOR IMPROVED FUEL CONTROL

    公开(公告)号:US20220100167A1

    公开(公告)日:2022-03-31

    申请号:US17038615

    申请日:2020-09-30

    Abstract: In various embodiments, methods, systems, and vehicle apparatuses are provided. In one exemplary embodiment, a method is provided that includes obtaining a set of inputs, by a processor, pertaining to one or more features that are used to predict the purge flow of a purge canister system of an intake system of a vehicle; obtaining data, by the processor, from sensors about the vehicle's intake system for use by a neural network to enable the processor to classify the set of inputs including the one or more features for purge flow control for use in predicting a presence of purge content in the vehicle's intake system; and obtaining, by the processor, an output from the neural network wherein the output is configured as a binary or continuous output to instruct a vehicle controller to execute an action to fueling control by letting fueling controller choose different gain sets and adaption strategy based on the binary output flag in a case of the binary-output model, or apply an adjustment factor to fueling command in case of a continuous model.

    Methods, systems, and apparatuses of purge content estimation logic for improved fuel control

    公开(公告)号:US11815875B2

    公开(公告)日:2023-11-14

    申请号:US17038615

    申请日:2020-09-30

    CPC classification number: G05B19/408 G06N3/08 G05B2219/45076

    Abstract: In various embodiments, methods, systems, and vehicle apparatuses are provided. In one exemplary embodiment, a method is provided that includes obtaining a set of inputs, by a processor, pertaining to one or more features that are used to predict the purge flow of a purge canister system of an intake system of a vehicle; obtaining data, by the processor, from sensors about the vehicle's intake system for use by a neural network to enable the processor to classify the set of inputs including the one or more features for purge flow control for use in predicting a presence of purge content in the vehicle's intake system; and obtaining, by the processor, an output from the neural network wherein the output is configured as a binary or continuous output to instruct a vehicle controller to execute an action to fueling control by letting fueling controller choose different gain sets and adaption strategy based on the binary output flag in a case of the binary-output model, or apply an adjustment factor to fueling command in case of a continuous model.

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