Patent ID: 12253013

DETAILED DESCRIPTION

InFIG.1, a drivetrain of a vehicle, as can be used in the context of the invention, is shown schematically and bears the overall reference number100. The drivetrain100comprises an internal-combustion engine110, for example having six indicated cylinders, an exhaust gas system120having multiple cleaning components122,124, such as catalysts and/or particulate filters, and a computing unit130configured so as to control the internal-combustion engine110and exhaust gas system120and connected to them in a data-conducting manner. Further, in the illustrated example, the computing unit130is connected to sensors112,121,123,127in a data-conducting manner, which record operating parameters of the internal-combustion engine110and/or the exhaust gas system120. It is understood that there can be other sensors that are not shown.

In the example shown here, the computing unit130comprises a data memory132in which, for example, computational instructions and/or parameters (e.g. threshold values, characteristics of the internal-combustion engine110and/or the exhaust gas system120, or the like) can be stored.

The internal-combustion engine110drives wheels140and can also be driven by the wheels in certain operating phases (e.g. so-called coasting mode)

InFIG.2, a regulation range for an emission component as a function of time is shown, as can arise in the context of a preferred embodiment of the invention. In a diagram200, the regulation behavior for different actual values E of an emission component is plotted against time t. A regulation range as it arises in the context of the invention bears the reference number201. The regulation range201defines the range in which a respective prevailing actual value of the emission component E is to be located at a respective time point and is limited downward by a minimum value range202and upward by a maximum value range203.

The minimum value range202in turn is limited downward by a minimum value202aand upward by a minimum tolerance value202bcorresponding to a sum of a prevailing tolerance and the minimum value202a. Likewise, the maximum value range203is limited upward by a maximum value203aand downward by a maximum tolerance value203b, the difference between which also corresponds to the prevailing tolerance.

Expediently, the minimum value202ais determined by engine conditions in order to ensure combustion, and the maximum value203ais determined by statutory provisions in order to avoid high emissions.

For example, the upper tolerance value203b, Limitupper, can be calculated from the maximum value203a, Emission limitupper, and the time-based tolerance Toleffaccording to the following equation:

Limitupper=emission⁢limitupper(1+Toleff)

For example, the lower tolerance value202b, Limitlower, can be calculated from the minimum value202a, Emission limit and the time-based tolerance Toleffaccording to the following equation:
Limitlower=emission limitlower·(1+TOleff)

Beyond the limits, either compliance with the statutory limit values is no longer guaranteed, or there is an unnecessarily frequent intervention of the emissions-based regulator, leading to a deterioration of driveability and consumption, or even both at the same time.

It can be seen that, at the start of operation between a time point t=0 and a time point t=t0, the minimum value range202and maximum value range203together (or the tolerance Toleff) are so great that no regulation range exists. From the time point t=t0, at which the lower tolerance value202band the upper tolerance value203bintersect, the regulation range201is present, which then grows with time and continues increasing. The tolerance TolSpat the intersection t=t0is calculated accordingly according to the following equation:

emission⁢limitupper(1+TolSp)=emission⁢limitlower·(1+TolSp)emission⁢limitupperemission⁢limitlower=(1+TolSp)2TolSp=emission⁢limitupperemission⁢limitlower-1

The time-dependent calculation of the tolerance is based on the finding that tolerance or uncertainty of the emission determination is different at various time points in the travel cycle. This is especially true when the emissions are determined via a low tolerance sensor (which substantially corresponds to a measurement in accuracy), which is however not ready at the start of the journey. It can therefore be provided that the emission value is determined on the basis of a model for this initial phase immediately after starting the internal-combustion engine (t>0) and that a model tolerance is assumed that is usually significantly above a sensor tolerance.

How strongly a single tolerance Tol(i) (i.e. tolerance or tolerance range at step or time point “i”) influences the overall tolerance Toloverall, depends on how high the generated emission mass is within the individual tolerances in relation to the total mass. The overall tolerance Toloverallon the other hand, results from the following equation:

T⁢o⁢loverall=∑i=ki=k⁢m⁢E⁢m⁢ii·Tolim⁢E⁢m⁢io⁢v⁢e⁢r⁢a⁢l⁢l(1)

Here, mEmi(i) stands for the emission mass that was generated at the time i. The index k corresponds to the number of different tolerance ranges and, in the borderline case, the number of measurement points.

By weighting the single tolerance with the emission amount, the effect on the overall tolerance is correctly represented. A high tolerance at low mass emission flow has a significantly lower effect on the overall tolerance than in the case of a high mass flow. Therefore, the calculation is discretized over the travel path.

To assess the effective tolerance TolExpSmotng(t) at a time point t (within a shorter interval than the overall travel distance), the effective tolerance is calculated based on an exponential smoothing:

Tol⁢Exp⁢Smotng⁡(t)=α·mEmi⁡(t)·Tol⁡(t)+∑i=1t-1[(1-α)i·(mEm⁢i⁡(t-i)·Tol⁡(t-i))]α·mEmi⁡(t)+∑i=1t-1[(1-α)i·mEmi⁡(t-i)](2)

Here, a stands for the smoothing factor or present factor and i indicates how far in the past the respective time step is. This calculation allows for a lower weighting of emissions and tolerances that are further in the past, and thus the response is better to changes in the prevailing tolerance level than if all measurement points were only weighted in a mass-dependent manner, as in equation (1). However, other methods of smoothing, such as a sliding or weighted average, can also be used.

The calculation shown in equation (2) corresponds to an exponential smoothing. In so doing, the distance section emissions mEmi are multiplied by the average tolerance Tol for this path section and then integrated/summed. The respective tolerances result from the tolerance of the sensor (usually dependent on the concentration of the emission: the lower the concentration, the higher the tolerance) or from the error of the emission model used (usually dependent on the operating point, e.g. less precise in the cold engine than in the warm engine).

The individual parameters mEmi and Tol for the distance section i are calculated continuously. The further these lie in the past, the less influence they have on the prevailing tolerance after distance section t.

The smoothing serves to properly evaluate the tolerance of the prevailing (and likewise smoothed) emissions:Overall emissions require an overall toleranceSmoothed emissions require a smoothed tolerance

InFIG.3a, an exemplary progression of an emission value in any desired units is plotted against a number n of measurement points and bears the reference number301. An exponentially smoothed progression bears the reference number302.

InFIG.3b, a respective prevailing tolerance bears the reference number303, an effective overall tolerance for the entire travel path according to equation 1 bears the reference number304, and an effective tolerance based on exponential smoothing according to equation 2 bears the reference number305.

The prevailing tolerance is known for a sensor, e.g. from its technical data (e.g. 10% deviation for a measured value>100 ppm) and for a model from its verification during the model creation (e.g. it is possible for a model to have a higher tolerance in a cold engine than in a warm one).

Based on the tolerances inFIG.3b, the intervention limits inFIG.2can then be calculated, or diagnoses can be evaluated in the concrete case of application.