Method for the model-based control and regulation of an internal combustion engine

1. A method for model-based open-loop and closed-loop control of an internal combustion engine, comprising the steps of: calculating injection system setpoint values for activating injection system control elements in a manner dependent on a setpoint torque by a combustion model; calculating gas path setpoint values for activating gas path control elements by a gas path model; adapting the combustion model during ongoing operation of the internal combustion engine; calculating a quality measure by an optimizer in a manner dependent on the injection system setpoint values and the gas path setpoint values; minimizing the quality measure by the optimizer by varying the injection system setpoint values and the gas path setpoint values within a prediction horizon; and, setting the injection system setpoint values and the gas path setpoint values by the optimizer, based on the minimized quality measure, as being definitive for setting an operating point of the internal combustion engine.

2. The method according to claim 1 , including adapting the combustion model by a first Gaussian process model for depicting a base grid and by a second Gaussian process model for depicting adaptation data points.

3. The method according to claim 2 , including assessing the quality of the second Gaussian process model based on a confidence interval.

4. The method according to claim 3 , including, in the second Gaussian process model, adopting a present adaptation data point that lies within a present confidence interval.

5. The method according to claim 3 , including, when a present adaptation data point lies outside the confidence interval, iteratively removing previously stored adaptation data points from the second Gaussian process model until a present adaptation data point lies within a new confidence interval.

6. The method according to claim 4 , including comparing a total number of the adaptation data points with a threshold value, and, when there is an overshooting of the threshold value, removing such a number of adaptation data points that a new total number is lower than the threshold value.

7. The method according to claim 6 , including readapting the first Gaussian process model for depicting a base grid by way of the second Gaussian process model.

8. The method according to claim 7 , including imprinting each data point of the first Gaussian process model with a timestamp, determining a priority based on a change of the timestamp, and estimating continued operation of the internal combustion engine dependent on the priority.