Varying closed loop gain control to constrain ramp rate of oxygen sensors in exhaust systems

    公开(公告)号:US10975746B1

    公开(公告)日:2021-04-13

    申请号:US16711637

    申请日:2019-12-12

    Abstract: A driver circuit drives a heater associated with a sensor in an exhaust system of a vehicle at a duty cycle. A feedback circuit generates a feedback signal indicating a temperature of the sensor. A ramp circuit outputs a first ramping set point indicating a first rate at which the temperature of the sensor is to be changed over a first time period after an engine of the vehicle is turned on, and a second ramping set point indicating a second rate at which the temperature of the sensor is to be changed after the first time period until the temperature of the sensor reaches a predetermined temperature. An error circuit generates first and second error signals based on the feedback signal and the first and second ramping set points. A controller controls the duty cycle of the driver circuit to drive the heater based on one or more gains.

    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.

    VEHICLE STOP PREDICTION
    4.
    发明申请

    公开(公告)号:US20200149484A1

    公开(公告)日:2020-05-14

    申请号:US16185533

    申请日:2018-11-09

    Abstract: Methods and systems for predicting a vehicle stop event and/or operating a purge pump for a vehicle are disclosed. An example method includes providing a fuel vapor canister in fluid communication with a fuel tank of the vehicle, the fuel vapor canister configured to absorb fuel vapors from the fuel tank, and placing a purge pump in fluid communication with the fuel vapor canister, with the purge pump being configured to pump an external airflow into the canister. Some methods and systems may be directed to predicting a vehicle stop while the vehicle is moving based upon at least a model of vehicle speed, and initiating a vehicle response based upon the prediction. In some examples, a vehicle response includes reducing ambient noise emitted by the purge pump.

    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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