System and method for adjusting a torque capacity of an engine using model predictive control
US-2015275784-A1 · Oct 1, 2015 · US
US9938908B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9938908-B2 |
| Application number | US-201615181559-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jun 14, 2016 |
| Priority date | Jun 14, 2016 |
| Publication date | Apr 10, 2018 |
| Grant date | Apr 10, 2018 |
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A system according to the principles of the present disclosure includes a pedal position prediction module and an engine actuator control module. The pedal position prediction module predicts a pedal position at a future time based on driver behavior and vehicle driving conditions. The pedal position includes at least one of an accelerator pedal position and a brake pedal position. The engine actuator control module controls an actuator of an engine based on the predicted pedal position.
Opening claim text (preview).
What is claimed is: 1. A system comprising: a pedal position prediction module that predicts a pedal position at a future time based on driver behavior, vehicle driving conditions, and the pedal position at a current time, wherein the pedal position includes at least one of an accelerator pedal position and a brake pedal position; an engine actuator control module that controls an actuator of an engine based on the predicted pedal position; and a pedal position probability module that determines P probabilities of P possible nonzero values of the pedal position at the future time based on the pedal position at the current time, the driver behavior, and the vehicle driving conditions, wherein: the pedal position prediction module sets the predicted pedal position equal to one of the P possible nonzero values of the pedal position corresponding to a highest one of the P probabilities; and P is an integer greater than one. 2. The system of claim 1 further comprising a driver identification module that identifies a driver of a vehicle, wherein the pedal position prediction module determines the driver behavior based on the driver identification. 3. The system of claim 2 further comprising a driver behavior module that transmits driver behavior data associated with the driver identification to a remote server and retrieves the driver behavior data from the remote server based on the driver identification, wherein the pedal position prediction module determines the driver behavior based on the driver identification and the driver behavior data. 4. The system of claim 1 wherein the vehicle driving conditions include at least one of a weather condition, a speed limit, a traffic condition, a road slope, and a road condition. 5. The system of claim 1 further comprising a vehicle driving conditions module that determines the vehicle driving conditions based a signal received from at least one of a vehicle sensor and a wireless communication network. 6. The system of claim 1 wherein the pedal position probability module: classifies at least one of the vehicle driving conditions into multiple categories; and determines the P probabilities of the P possible nonzero values of the pedal position based on which one of the multiple categories corresponds to actual vehicle driving conditions. 7. The system of claim 1 wherein: the engine actuator control module determines a target value for the actuator of the engine based on the predicted pedal position; and the target value includes at least one of a target throttle opening area, a target spark timing, a target exhaust gas recirculation (EGR) opening area, a target bypass valve position, a target wastegate position, and a target valve lift position. 8. The system of claim 1 further comprising a model predictive control (MPC) module that: generates a set of possible target values for the actuator of the engine; predicts an operating parameter of the engine for each of the possible target values based on the predicted pedal position; determines a cost for the set of possible target values based on the predicted operating parameter; selects the set of possible target values from multiple sets of possible target values based on the cost; and sets target values to the possible target values, wherein the engine actuator control module controls the actuator of the engine based on at least one of the target values. 9. A method comprising: predicting a pedal position at a future time based on driver behavior, vehicle driving conditions, and the pedal position at a current time, wherein the pedal position includes at least one of an accelerator pedal position and a brake pedal position; controlling an actuator of an engine based on the predicted pedal position; determining P probabilities of P possible nonzero values of the pedal position at the future time based on the pedal position at the current time, the driver behavior, and the vehicle driving conditions; and setting the predicted pedal position equal to one of the P possible nonzero values of the pedal position corresponding to a highest one of the P probabilities, wherein P is an integer greater than one. 10. The method of claim 9 further comprising: identifying a driver of a vehicle; and determining the driver behavior based on the driver identification. 11. The method of claim 10 further comprising: transmitting driver behavior data associated with the driver identification to a remote server and retrieving the driver behavior data from the remote server based on the driver identification; and determining the driver behavior based on the driver identification and the driver behavior data. 12. The method of claim 9 wherein the vehicle driving conditions include at least one of a weather condition, a speed limit, a traffic condition, a road slope, and a road condition. 13. The method of claim 9 further comprising determining the vehicle driving conditions based a signal received from at least one of a vehicle sensor and a wireless communication network. 14. The method of claim 9 further comprising: classifying at least one of the vehicle driving conditions into multiple categories; and determining the P probabilities of the P possible nonzero values of the pedal position based on which one of the multiple categories corresponds to actual vehicle driving conditions. 15. The method of claim 9 further comprising determining a target value for the actuator of the engine based on the predicted pedal position, wherein the target value includes at least one of a target throttle opening area, a target spark timing, a target exhaust gas recirculation (EGR) opening area, a target bypass valve position, a target wastegate position, and a target valve lift position. 16. The method of claim 9 further comprising: generating a set of possible target values for the actuator of the engine; predicting an operating parameter of the engine for each of the possible target values based on the predicted pedal position; determining a cost for the set of possible target values based on the predicted operating parameter; selecting the set of possible target values from multiple sets of possible target values based on the cost; setting target values to the possible target values; and controlling the actuator of the engine based on at least one of the target values. 17. The system of claim 1 wherein, if more than one of the P possible nonzero values of the pedal position corresponds to the highest one of the P probabilities, the pedal position prediction module sets the predicted pedal position equal to the one of those P possible nonzero values that is closest to the pedal position at the current time. 18. The system of claim 6 wherein the vehicle driving conditions include at least one of a weather condition, a speed limit, a traffic condition, a road slope, and a road condition. 19. The method of claim 9 further comprising, if more than one of the P possible nonzero values of the pedal position corresponds to the highest one of the P probabilities, setting the predicted pedal position equal to the one of those P possible nonzero values that is closest to the pedal position at the current time. 20. The method of claim 14 wherein the vehicle driving conditions include at least one of a weather condition, a speed limit, a traffic condition, a road slope, and a road condition.
characterised by hand, foot, or like operator controlled initiation means · CPC title
Pedal position · CPC title
Road conditions · CPC title
Information about vehicle position, e.g. from navigation system or GPS signal · CPC title
with use of a optimisation method, e.g. iteration · CPC title
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