GB2504714A - Evaluating a pressure drop across a particulate filter in an exhaust system of an automotive internal combustion engine - Google Patents

Abstract

A method of evaluating a pressure drop across a particulate filter disposed in an exhaust system of an automotive internal combustion engine comprises: calculating a flow resistance of the filter and a clean pressure drop across the filter; and subsequently calculating an actual pressure drop across the filter by adding 26 the calculated clean pressure drop across the filter to the product 25 of the flow resistance of the filter and an exhaust volumetric flow rate of the exhaust system. The clean pressure drop may be calculated using a clean pressure drop map 20 representative of the pressure drop across the filter for a given exhaust volumetric flow rate and filter inlet temperature when the filter is free of soot. The flow resistance may be calculated using an inverse soot loading map 24 representative of the flow resistance of the filter for given soot loading levels and exhaust volumetric flow rates. The filter may be a diesel particulate filter (DPF). The method may be used to replace or diagnose a conventional exhaust gas pressure (EGP) sensor of a DPF.

Description

METHOD OF OPTiMIZING THE CONTROL OF A PARTICULATE FIL TEA

TECHNICAL FIELD

The present disclosure relates to a method of optimizing the CONTROL of a particulate filter in an exhaust system of an internal combustion engine, such method being particularly useful for modern Diesel engine adopting said particulate filter as aftertreatment device.

BAC KGRO U ND

It is known that the exhaust system of an internal combustion engine can be provided with one or more exhaust aftertreatment devices. The aftertreatment devices may be any device configured to change the composition of the exhaust gases. Some examples of aftertreatrnent devices include, but are not limited to, catalytic converters (two and three way), oxidation catalysts, lean NOx traps, hydrocarbon adsorbers, selective catalytic reduction (SCR) systems, particulate filters (DPF).

In particular, a typical configuration of an after-treatment system of a Diesel engine comprises a Diesel Oxidation Catalyst (DOC) and a diesel particulate filter (DPF), the former device being particular useful to oxides carbon monoxide (CO) and unburned hydrocarbons (HC), the latter to trap the diesel particulate.

The diesel particulate filter, operating as a filter, collects liquid and solid particles in a porous substrate structure while allowing exhaust gases to flow through. As it reaches its nominal storage capacity, it needs to be cleaned by a process called regeneration.

during which the exhaust gas temperature is increased substantially to create a condition whereby the soot contained in the DPF is burned (oxidized). In particular, hydrocarbon based reagents (HC), like the same diesel fuel used for fuelling the engine, are injected by means of late injections (in order not to create additional engine torque) in the cylinder and/or in the exhaust line, in order to promote the regeneration of the DPF with the burning of the particulate accumulated therein.

In order to optimize the DPF control and in particular its regeneration frequency, engine management systems use specific models to manage this device. The models need several input, among them an accurate soot loading estimation has to be provided.

Different strategies can be identified for this purpose: a DPF physical model is part of this and it is based on differential pressure signal read across the DPF by an Exhaust Gas Pressure (EGP) sensor.

Unfortunately, the EGP sensor diagnostic has limited capability due to lack of EGP models. Moreover, in case of fault of the EGP sensor, pressure information is no longer available also for other controls functions (e.g. 1-ICI low-level compensation, air/fuel ratio sensor compensation, turbine protection from high backpressure).

Therefore a need exists for a method that estimate the differential pressure across the DPF, independent on the signal coming from the EGP sensor, thus improving the control and in particular the regeneration frequency of the diesel particulate filter.

An object of this invention is to provide a method which optimizes the control of a particulate filter, without any need of further components in the Engine Management System (EMS). This method, based on a model which estimates the differential pressure across the DPF, could be very useful either to replace a faulty EGP sensor or to perform a diagnosis of the sensor itself. Of course the method can also be adopted in case other needs recommend to avoid any EGP sensor in the aftertreatment system.

Another object is to provide an apparatus which allows to perform the above method.

These objects are achieved by a method, by an apparatus, by an engine, by a computer program and computer program product, and by an electromagnetic signal having the features recited in the independent claims.

The dependent claims delineate preferred and/or especially advantageous aspects.

SUMMARY

An embodiment of the disclosure, provides a method of evaluating the pressure drop across a particulate filter in an exhaust system of an internal combustion engine of an automotive system, the method comprising: -calculating a flow resistance and a clean pressure drop across the particulate filter, -calculating a pressure drop across the particulate filter by adding to said clean pressure drop the product between said flow resistance and an exhaust volumetric flowrate.

Consequently, an apparatus is disclosed for evaluating the pressure drop across a particulate filter in an exhaust system of an internal combustion engine of an automotive system, the apparatus comprising: -means for calculating a flow resistance and a clean pressure drop across the particulate filter, -means for calculating a pressure drop across the particulate filter by adding to said clean pressure drop the product between said flow resistance and an exhaust volumetric flowrate.

An advantage of this embodiment is that it provides an effective way to diagnose an EGP sensor fault and to provide a consistent value for further Engine Management System functions.

According to another embodiment of the invention, said flow resistance is the output of an inverse soot loading map, having as input a soot loading level and the exhaust volumetric flowrate.

An advantage of this embodiment is that it can be used for both the DFF loading and unloading phases, being not related to the physical pressure drop signal.

According to a further embodiment, said inverse soot loading map is based either on a statistical soot model or on a physical soot model, disclalming a physical pressure based model.

An advantage of this embodiment is that it is independent on the chosen soot model. In fact, it can be based on whatever available soot model, either statistical or physical (but not related to measured pressure drop). Only required condition is the reliability of the soot model.

According to a still further embodiment, said clean pressure drop across the particulate filter is the output of a pressure drop clean map, having as input the exhaust volumetric flowrate and a temperature at a DPF inlet.

An advantage of this embodiment is that the modeled pressure drop across the particulate filter, takes into account the* real catalyst structure, thus improving the accuracy of the whole method.

The method according to one of its aspects can be carried out with the help of a computer program comprising a program-code for carrying out all the steps of the method described above, and in the form of computer program product comprising the computer program.

The computer program product can be embodied as a control apparatus for an internal combustion engine, comprising an Electronic Control Unit (ECU), a data carrier associated to the ECU, and the computer program stored in a data carrier, so that the control apparatus defines the embodiments described in the same way as the method. In this case, when the control apparatus executes the computer program all the steps of the method described above are carried out.

The method according to a further aspect can be also embodied as an electromagnetic signal, said signal being modulated to carry a sequence of data bits which represents a computer program to carry out all steps of the method.

A still further aspect of the disclosure provides an internal combustion engine specially arranged for carrying out the method claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The various embodiments will now be described, by way of example, with reference to the accompanying drawings, in which: Figure 1 shows an automotive system.

Figure 2 is a section of an internal combustion engine belonging to the automotive system of figure 1.

Figure 3 is a schematic view of the after-treatment system according to the invention.

Figure 4 is an algorithm showing a known model for estimating the soot loading in particular filter.

Figure 5 is an algorithm showing a model for estimating the differential pressure across a particulate filter, according to an embodiment of the invention.

Figure 6 is a flowchart of a method for estimating the differential pressure across a particulate filter, according to an embodiment of the invention.

DETAILED DESCRIPTION OF THE DRAWINGS

Some embodiments may include an automotive system 100, as shown in Figures land 2, that includes an internal combustion engine (ICE) 110 having an engine block 120 defining at least one cylinder 125 having a piston 140 coupled to rotate a crankshaft 145.

A cylinder head 130 cooperates with the piston 140 to define a combustion chamber 150.

A fuel and air mixture (not shown) is disposed in the combustion chamber 150 and ignited, resulting in hot expanding exhaust gasses causing reciprocal movement of the piston 140. The fuel is provided by at least one fuel injector 160 and the air through at least one intake port 210. The fuel is provided at high pressure to the fuel injector 160 from a fuel rail 170 in fluid communication with a high pressure fuel pump 180 that increase the pressure of the fuel received a fuel source 190. Each of the cylinders 125 has at least two valves 215, actuated by a camshaft 135 rotating in time with the crankshaft 145. The valves 215 selectively allow air into the combustion chamber 150 from the port 210 and alternately allow exhaust gases to exit through a port 220. In some examples, a cam phaser 155 may selectively vary the timing between the camshaft 135 and the crankshaft 145.

The air may be distributed to the air intake port(s) 210 through an intake manifold 200.

An air intake duct 205 may provide air from the ambient environment to the intake manifold 200. In other embodiments, a throttle body 330 may be provided to regulate the flow of air into the manifold 200. In still other embodiments, a forced air system such as a turbocharger 230, having a compressor 240 rotationally coupled to a turbine 250, may be provided. Rotation of the compressor 240 increases the pressure and temperature of the air in the duct 205 and manifold 200. An intercooler 260 disposed in the duct 205 may reduce the temperature of the air. The turbine 250 rotates by receiving exhaust gases from an exhaust manifold 225 that directs exhaust gases from the exhaust pals 220 and through a series of vanes prior to expansion through the turbine 250: The exhaust gases exit the turbine 250 and are directed into an exhaust system 270. This example shows a variable geometry turbine (VGT) with a VGT actuator 290 arranged to move the vanes to alter the flow of the exhaust gases through the turbine 250. In other embodiments! the turbocharger 230 may be fixed geometry and/or include a waste gate.

The exhaust system 270 may include an exhaust pipe 275 having one or more exhaust aftertreatment devices 280. The aftertreatment devices may be any device configured to change the composition of the exhaust gases. Some examples of aftertreatment devices 280 include, but are not limited to, catalytic converters (two and three way), oxidation catalysts 281, lean NOx traps, hydrocarbon adsorbers, selective catalytic reduction (SCR) systems, particulate filters (DPF) 282. Other embodiments may include an exhaust gas recirculation (EGR) system 300 coupled between the exhaust manifold 225 and the intake manifold 200. The EGR system 300 may include an EGR cooler 310 to reduce the temperature of the exhaust gases in the EGR system 300. An EGR valve 320 regulates a flow of exhaust gases in the EGR system 300.

The automotive system 100 may further include an electronic control unit (ECU) 450 in communication with one or more sensors and/or devices associated with the ICE 110 and equipped with a data carrier 40. The ECU 450 may receive input signals from various sensors configured to generate the signals in proportion to various physical parameters associated with the ICE 110. The sensors include, but are not limited to, a mass airflow and temperature sensor 340, a manifold pressure and temperature sensor 350, a combustion pressure. sensor 360, coolant and oil temperature and level sensors 380, a fuel rail pressure sensor 400, a cam position sensor 410, a crank position sensor 420, exhaust pressure and temperature sensors 430, an EGR temperature sensor 440, and an accelerator pedal position sensor 445. Furthermore, the ECU 450 may generate output signals to various control devices that are arranged to control the operation of the ICE 110, including, but not limited to, the fuel injectors 160, the throttle body 330, the EGR Valve 320, the VOT actuator 290, and the cam phaser 155. Note1 dashed lines are used to indicate communication between the ECU 450 and the various sensors and devices, but some are omitted for clarity.

Turning now to the ECU 450, this apparatus may include a digital central processing unit (CPU) in communication with a memory system and an interface bus. The CPU is configured to execute instructions stored as a program in the memory system, and send and receive signals to/from the interface bus. The memory system may include various storage types including optical storage, magnetic storage, solid state storage, and other non-volatile memory. The interface bus may be configured to send, receive, and modulate analog and/or digital signals to/from the various sensors and control devices.

The program may embody the methods disclosed herein, allowing the CPU to carryout out the steps of such methods and control the ICE 110.

Turning back to exhaust system 270, the purpose of this invention is to obtain an estimation of the DPF 282 pressure signal relying on soot evaluation models independent on exhaust gas pressure measurements, and applying the inverse structure of what is currently done by the OPE physical model, based on an Exhaust Gas Pressure 283 signal.

In Fig.3 an exemplifying configuration of an aftertreatment system for a Diesel engine is shown. It comprises a Diesel Oxidation Catalyst 281 and a diesel particulate filter 262.

As known, an oxidation catalyst is used to oxides carbon monoxide (CO) and unburned hydrocarbons (NC), while a particulate filter is used to trap the soot and more in general all particulate matter, which is produced during the engine combustion phase.

The diesel particulate filter, operating as a filter, collects liquid and solid particles in a porous substrate structure while allowing exhaust gases to flow through As it reaches its nominal storage capacity, it needs to be cleaned by a process called regeneration, during which the exhaust gas temperature is increased substantially to create a condition whereby the soot contained in the DPF is burned (oxidized). In particular, hydrocarbon based reagents (NC), like the same diesel fuel used for fuelling the engine, are injected by means of late injections (in order not to create additional engine torque) in the cylinder and/or in the exhaust line, in order to promote the regeneration of the DPF with the burning of the particulate accumulated therein.

In order to optimize the DPF control and, in particular, its regeneration frequency, engine management systems use specific models to manage this device. The models need several input, among them an accurate soot loading estimation has to be provided.

Different strategies can be identified for this purpose: a DPF physical model is part of this and it is based on differential pressure signal read across the DPF 282 by an Exhaust Gas Pressure (EGP) sensor 2B3.

In fad, as shown in Fig. 4, a known DPF physical model evaluates the soot loading into the DPF 282 starting from OPE-physically related input, namely the pressure drop across the filter, the exhaust volumetric flowrate and the exhaust gas temperature at the DPF inlet. For given exhaust volumetric flowrate and temperature, the delta pressure will increase as soot is accumulated on the DPF, The base information for the model behavior is the pressure drop across a clean DPF at all operating conditions. This clean pressure drop map 20 is1 therefore, function of temperature at OFF inlet and exhaust volumetric flowrate. Subtracting 21 this map from the measured pressure drop, the real pressure drop due to the soot accumulation is obtained. Then, dividing 22 the latter pressure drop by the exhaust volumetric flowrate, a flow resistance can be obtained. This flow resistance and the exhaust volumetric fiowrate are the input for the final soot map 24.

As already mentioned, the main drawback of this known strategy is that it is related on a physical signal coming from the EGP sensor 283. In case of fault of this sensor1 no backup solution has been provided up to now. Even if soot models can also be available in different way (e.g. statistically based soot model), the fault of the EGP sensor, or its absence, would badly influence other Engine Management System (EMS) functions.

Therefore, the idea of the present new method is to estimate the pressure drop across the OFF, independently on an EGP signal1 but using, as main input, the information coming from the best available soot evaluation model.

In fact, being a direct relationship between the pressure drop signal and the evaluation of soot trapped in the filter, the same direct relationship can be found on the opposite, among soot and exhaust pressure drop signal. Basic elements for the estimation here proposed are (see Fig. 5): -the inverse of the soot map 24, which provides the relationship between the soot loading and the flow resistance; -such flow resistance multiplied 25 per the exhaust volumetric flowrate gives the pressure drop across the filter, due to the effective soot loading; -the clean map 20 to be added 26 to said pressure drop, in order to take into account the empty IJPF pressure contribution.

The soot loading model to be used can be either a simulated one (any of the statistical calculations available) or a physical one (but not tied with the EGP sensor information.

As an example of physical soot model, the information about the soot which is trapped in the DPF can be returned by means of a map-based soot model, in which basic inputs to calculate the soot flow in the DPF are the engine operating point and other parameters.

The after are strictly related to the vehicle driving profile (gear, vehicle speed, exhaust temperature), with a further multiplicative correction dependent on environmental conditions (barometric pressure, air temperature) to take into account different outside conditions (e.g. cold compensations).

Of course, in order to avoid a wrong pressure drop estimation caused by wrong soot loading estimation, the reliability of all soot loading models has to be previously verified by means of specific plausibility checks among all soot evaluation models in ECU.

A plausibility check might be simply performed by comparing the soot evaluation coming from the chosen model with the soot evaluation coming from other models running in parallel and rated as reliable in that given condition. In case of deviation higher than a calibratable threshold the chosen model shall not be used as an input for EGP estimation.

A simple flowchart of the proposed method is shown in Fig. 6: starting from the availability of a reliable soot model 27, the information needed 28 are the current soot level, the exhaust volumetric flowrate and the inlet DPF temperature; then by using the inverse soot map 24, the flow resistance can be calculated 29 and by using the pressure drop clean map 20, the clean pressure drop can be calculated 29 as well; finally, the product of the flow resistance per the exhaust volumetric flowrate, added to the clean pressure drop, will provide 30 the modeled pressure drop across the DPF. This model can be used 31 to replace the signal coming from a fault (or missing) EGP sensor 283, or to perform a diagnosis of the sensor itself It can be also used for other EMS functions calculation.

The proposed method is able to work properly during both the DPF loading and unloading phase (in other words, normal and regeneration mode), since loading and unloading models will not be based on EGP sensor information. For both loading and unloading phase, the same soot model can be chosen.

Moreover, the method is based on any reliable soot model, either statistical or physical.

Furthermore, the method also takes into account the real catalyst structure, by using the clean pressure drop map 20.

Preliminary tests show that, during the DPF Loading phase the model trend fits very well with the real signal behavior, and the average error does not overcome the range +1-lkPa even with higher pressure values. In the same way, during the DPF unloading phase, the model trend fits very well with the real signal behavior and the average error is kept in the range ÷/-2kPa even with higher pressure values.

Summarizing, the advantages of the proposed invention are the estimation of the pressure drop across the DPF, in both the DPF loading and unloading phases; moreover the method is able to meet the real pressure signal behavior, keeping the error inside a small window, thus allowing the pressure estimation to be used for different purposes, including (but not limited to): -EGP sensor plausibility diagnosis -Ensure the following EMS functions, even with faulty or lacking EGP sensor, such as (but not limited to): * turbine protection from elevate backpressure * Air/fuel ratio sensor compensation function * HCI low-level compensation function While at least one exemplary embodiment has been presented in the foregoing summary and detailed description, it should be appreciated that a vast number of variations exist. It should also be appreciated that the exemplary embodiment or exemplary embodiments are only examples, and are not intended to limit the scope, applicability, or configuration in any way. Rather, the foregoing summary and detailed description will provide those skilled in the art with a convenient road map for implementing at least one exemplary embodiment, it being understood that various changes may be made in the function and arrangement of elements described in an exemplary embodiment without departing from the scope as set forth in the appended claims and their legal equivalents.

REFERENCE NUMBERS block

21 block 22 block 23 block 24 block block 26 block 27 block 28 block 29 block block 31 block data carrier 100 automotive system internal combustion engine engine block cylinder cylinder head 135 camshaft piston crankshaft combustion chamber cam phaser 160 fuel injector fuel rail fuel pump fuel source intake manifold 205 air intake pipe 210 intake port 215 valves 220 exhaust port 225 exhaust manifold 230 turbocharger 240 compressor 245 turbocharger shaft 250 turbine 260 intercooler 270 exhaust system 275 exhaust pipe 280 aftertreatment devices 281 diesel oxidation catalyst (DOC) 282 diesel particulate filters (DPF) 283 Exhaust gas pressure (EGP) sensor 290 VGT actuator 300 exhaust gas recirculation system 310 EGR cooler 320 EGR valve 330 throttle body 340 mass airflow and temperature sensor 350 manifold pressure and temperature sensor 360 combustion pressure sensor 380 coolant temperature and level sensors 385 lubricating oil temperature and level sensor 390 metal temperature sensor 400 fuel rail pressure sensor 410 cam position sensor 420 crank position sensor 430 exhaust pressure and temperature sensors 440 EGR temperature sensor 445 accelerator position sensor 446 accelerator pedal 450 ECU

Claims (9)

1. CLAIMS1. Method of evaluating the pressure drop across a particulate filter (282) in an exhaust system (270) of an internal combustion engine (110) of an automotive system (100), the method comprising: -calculating (29) a flow resistance and a clean pressure drop across the particulate filter (282), -calculating (21) a pressure drop across the particulate filter by adding (26) to said clean pressure drop the product (25) between said flow resistance and an exhaust volumetric ulowrate.
2. 2. Method according to claim 1, wherein said flow resistance is the output of an inverse soot loading map (24), having as input a soot loading level and said exhaust volumetric flowrate.
3. 3. Method according to claim 2, wherein said inverse soot loading map is based either on a statistical soot model or on a physical soot model1 disclaiming a physical pressure based model.
4. 4. Method according to one of the previous claims, wherein said clean pressure drop across the particulate filter (282) is the output of a pressure drop clean map (20), having as input the exhaust volumetric flowrate and a temperature at a DPF inlet.
5. 5. Internal combustion engine (110) of an automotive system (100) equipped with an exhaust system (270), comprising at least a particulate filter (282), the automotive system (100) comprising an electronic control unit (450) configured for carrying out the method according to claims 1-4.
6. 6. A computer program comprising a computer-code suitable for performing the method according to any of the claims 1-4.
7. 7. Computer program product on which the computer program according to claim 6 is stored.
8. 8. Control apparatus for an internal combustion engine, comprising an Electronic Control Unit (450) a data carrier (40) associated to the Electronic Control Unit (450) and a computer program according to claim 6 stored in the data carrier (40).
9. 9. An electromagnetic signal modulated as a carrier for a sequence of data bits representing the computer program according to claim 6.