Method for real-time, self-learning identification of fuel injectors during engine operation
View Patent ↗A system and method for real-time, self-learning characterization of fuel injector performance during engine operation. The system includes an algorithm for an engine controller which allows the controller to learn the correlation between the fuel mass and pulse width for each injector in the engine in real time while the engine is running. The controller progressively perceives those pulse widths that achieve the desired fuel mass, while it can continuously adapt what it has learned based on various input variations, such as temperature and fuel rail pressure. The controller then uses the learned actual performance of each injector to command the pulse width required to achieve the desired quantity of fuel for each cylinder on each cycle.
1. A method for learning performance characteristics of fuel injectors in an engine, said method comprising:
identifying an initial calibration curve relating fuel injection quantity to pulse width time for the fuel injectors in the engine;
defining a learned performance curve for each fuel injector in the engine as initially being equal to the initial calibration curve;
determining a desired amount of fuel;
calculating a pulse width time for each fuel injector based on the learned performance curve and the desired amount of fuel;
using the pulse width time as calculated for each fuel injector during engine operation;
measuring engine operational data;
calculating an actual amount of fuel delivered by each injector based on the engine operational data;
comparing the actual amount of fuel delivered by each injector based on the engine operational data to the desired amount of fuel corresponding to the pulse width time as calculated; and
updating the learned performance curve for each fuel injector in the engine, based on the comparison of the actual amount of fuel delivered to the desired amount of fuel, using a Markov Decision Process.
2. The method of claim 1 wherein measuring engine operational data includes using a plurality of sensors comprising an intake manifold air flow sensor and an air-fuel ratio sensor for each cylinder in the engine.
3. The method of claim 1 further comprising checking to see if termination criteria have been met.
4. The method of claim 3 wherein updating the learned performance curve continues from a time when the engine is new until the termination criteria have been met, and then the learned performance curves for all fuel injectors are stored in memory and used henceforth.
5. The method of claim 4 further comprising an adaptive scheme for optimizing fuel injector performance based on environmental variables, said adaptive scheme being used throughout the engine's life.
6. The method of claim 4 wherein updating the learned performance curve is resumed if a significant engine event is encountered.
7. The method of claim 6 wherein the significant engine event includes an engine mis-fire, or repair or replacement of certain engine components.
8. The method of claim 1 wherein the engine uses a homogeneous charge compression ignition cycle.
9. A method for learning performance characteristics of fuel injectors in an engine, said method comprising:
identifying an initial calibration curve relating fuel injection quantity to pulse width time for the fuel injectors in the engine;
defining a learned performance curve for each fuel injector in the engine as initially being equal to the initial calibration curve;
determining a desired amount of fuel;
calculating a pulse width time for each fuel injector based on the learned performance curve and the desired amount of fuel;
using the pulse width time as calculated for each fuel injector during engine operation;
measuring engine operational data with a plurality of sensors including an intake manifold air flow sensor and an air-fuel ratio sensor for each cylinder in the engine;
calculating an actual amount of fuel delivered by each injector based on the engine operational data;
comparing the actual amount of fuel delivered by each injector based on the engine operational data to the desired amount of fuel corresponding to the pulse width time as calculated;
updating the learned performance curve for each fuel injector in the engine, based on the comparison of the actual amount of fuel delivered to the desired amount of fuel, using a Markov Decision Process; and
checking to see if termination criteria have been met.
10. The method of claim 9 wherein updating the learned performance curve continues from a time when the engine is new until the termination criteria have been met, and then the learned performance curves for all fuel injectors are stored in memory and used henceforth.
11. The method of claim 10 further comprising an adaptive scheme for optimizing fuel injector performance based on environmental variables, said adaptive scheme being used throughout the engine's life.
12. The method of claim 11 wherein the engine uses a homogeneous charge compression ignition cycle.
13. A system for controlling fuel injectors in an engine, said system comprising:
an input device for prescribing a desired amount of fuel to feed to the engine;
a memory module containing an initial calibration curve for the fuel injectors in the engine;
a switch to allow either the initial calibration curve for the fuel injectors or a learned performance curve for the fuel injectors to be used;
a plurality of sensors for collecting operating data from the engine; and
a learning controller for monitoring engine operating data, computing a learned performance curve for each fuel injector relating fuel infection quantity to pulse width time, and calculating a pulse width time for each fuel injector during engine operation based on the desired amount of fuel and either the initial calibration curve or the learned performance curve for the fuel injectors, said controller being configured to compare an actual amount of fuel delivered by each injector based on the engine operating data to the desired amount of fuel corresponding to the pulse width time as calculated, said controller being further configured to update the learned performance curve for each fuel injector in the engine based on the comparison of the actual amount of fuel delivered to the desired amount of fuel using a Markov Decision Process.
14. The system of claim 13 wherein the switch selects the initial calibration curve for the fuel injectors from a time when the engine is new until sufficient data points have been gathered for the learned performance curves for each fuel injector, and thereafter the switch selects the learned performance curves.
15. The system of claim 13 wherein the learning controller continues computing a learned performance curve for each fuel injector from a time when the engine is new until a set of termination criteria have been met, and then the learned performance curves for all fuel injectors are stored in memory and used henceforth.
16. The system of claim 13 further comprising an adaptive controller for optimizing fuel injector performance based on environmental variables.
17. The system of claim 13 wherein the plurality of sensors includes an intake manifold air flow sensor and an air-fuel ratio sensor for each cylinder in the engine.
18. The system of claim 13 wherein the engine uses a homogeneous charge compression ignition cycle.