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CN112761757B - DPF initialization self-learning method and device - Google Patents

DPF initialization self-learning method and device Download PDF

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Publication number
CN112761757B
CN112761757B CN202110110168.8A CN202110110168A CN112761757B CN 112761757 B CN112761757 B CN 112761757B CN 202110110168 A CN202110110168 A CN 202110110168A CN 112761757 B CN112761757 B CN 112761757B
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dpf
pressure difference
mass flow
initial
initial pressure
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CN112761757A (en
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李芳�
韩虎
程欢
王梅俊
杨晓莹
郑攀
陈玉俊
白桃李
李林
张衡
周杰敏
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Dongfeng Trucks Co ltd
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Dongfeng Trucks Co ltd
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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F01—MACHINES OR ENGINES IN GENERAL; ENGINE PLANTS IN GENERAL; STEAM ENGINES
    • F01N—GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR MACHINES OR ENGINES IN GENERAL; GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR INTERNAL COMBUSTION ENGINES
    • F01N3/00—Exhaust or silencing apparatus having means for purifying, rendering innocuous, or otherwise treating exhaust
    • F01N3/02—Exhaust or silencing apparatus having means for purifying, rendering innocuous, or otherwise treating exhaust for cooling, or for removing solid constituents of, exhaust
    • F01N3/021—Exhaust or silencing apparatus having means for purifying, rendering innocuous, or otherwise treating exhaust for cooling, or for removing solid constituents of, exhaust by means of filters
    • F01N3/022—Exhaust or silencing apparatus having means for purifying, rendering innocuous, or otherwise treating exhaust for cooling, or for removing solid constituents of, exhaust by means of filters characterised by specially adapted filtering structure, e.g. honeycomb, mesh or fibrous
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F01—MACHINES OR ENGINES IN GENERAL; ENGINE PLANTS IN GENERAL; STEAM ENGINES
    • F01N—GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR MACHINES OR ENGINES IN GENERAL; GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR INTERNAL COMBUSTION ENGINES
    • F01N11/00—Monitoring or diagnostic devices for exhaust-gas treatment apparatus, e.g. for catalytic activity
    • F01N11/002—Monitoring or diagnostic devices for exhaust-gas treatment apparatus, e.g. for catalytic activity the diagnostic devices measuring or estimating temperature or pressure in, or downstream of the exhaust apparatus
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F01—MACHINES OR ENGINES IN GENERAL; ENGINE PLANTS IN GENERAL; STEAM ENGINES
    • F01N—GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR MACHINES OR ENGINES IN GENERAL; GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR INTERNAL COMBUSTION ENGINES
    • F01N13/00—Exhaust or silencing apparatus characterised by constructional features ; Exhaust or silencing apparatus, or parts thereof, having pertinent characteristics not provided for in, or of interest apart from, groups F01N1/00 - F01N5/00, F01N9/00, F01N11/00
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

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  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • General Engineering & Computer Science (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
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  • Processes For Solid Components From Exhaust (AREA)

Abstract

The application relates to a DPF initialization self-learning method and a DPF initialization self-learning device, which relate to the technical field of exhaust aftertreatment of an internal combustion engine, fitting a relation function of the obtained DPF inlet temperature, the obtained exhaust mass flow and the obtained DPF pressure difference in the preset vehicle mileage to the pressure difference and the exhaust mass flow to obtain a DPF initial pressure difference parameter, calculating according to the DPF initial pressure difference parameter to obtain a DPF initial pressure difference, because the initial pressure difference parameter of the DPF fully reflects the relationship between the pressure difference and the friction and the permeation of gas flowing through the DPF and the relationship between the pressure difference and the air compression and expansion caused by the change of the channel sectional area, therefore, the DPF initial pressure difference calculated by the DPF initial pressure difference parameter is the actual DPF pressure difference of each carrier, the deviation of flow resistance caused by the processing difference of the DPF carrier and the application of the oxidation coating material can be effectively reduced, and then improve the prediction accuracy of DPF carbon loading and effectively reduce the cost of DPF initialization.

Description

DPF initialization self-learning method and device
Technical Field
The application relates to the technical field of exhaust aftertreatment of internal combustion engines, in particular to an initialization self-learning method and device of a DPF.
Background
A DPF (Diesel Particulate Filter) is an indispensable aftertreatment device for a Diesel engine to meet the emission regulation requirements. The DPF collects PM (Particulate Matter) in the exhaust gas of the diesel engine by means of physical filtration, thereby reducing the PM emission of the diesel engine. However, as particulate matter accumulates in the DPF channels, the pressure drop across the DPF may increase, which may increase the exhaust backpressure of the engine, which may further deteriorate the fuel consumption of the engine, and in severe cases may even directly block the exhaust pipe, resulting in engine damage. Therefore, during the use of the DPF, it is generally necessary to periodically perform a regeneration operation on the DPF to oxidize and remove the soot accumulated in the DPF, so that the flow resistance of the DPF is controlled within a reasonable range, and the normal operation of the engine and the DPF is ensured.
The existing DPF carbon loading capacity prediction model generally estimates the carbon loading capacity in a DPF through a correlation relationship between the pre-calibrated DPF carbon loading capacity and the pressure difference between the front and the back of the DPF, the pressure difference between the front and the back of the DPF measured by a pressure difference sensor, and the combination of engine exhaust flow and DPF inlet temperature. However, different DPF carrier processing processes have differences, and the deviation of the flow resistance (the ratio of the pressure difference of the DPF to the volume flow of air passing through the carrier) of different carriers in the same batch is about 10%; and when the DPF carrier is coated with the oxidation coating material, the deviation can be further amplified to about 15 percent, and because the carbon loading capacity and the flow resistance of the DPF are in one-to-one correspondence, namely the change of the flow resistance can directly cause the change of the carbon loading capacity, the deviation of the flow resistance can directly cause the carbon loading capacity of the DPF to generate deviation, and further the carbon loading capacity of the DPF is inaccurate to predict.
In the related technology, when an engine is in a stop state, a fan is adopted to operate to provide constant air mass flow for a DPF, the differential pressure of a DPF carrier is measured, the flow resistance of the DPF is converted according to the air mass flow passing through the DPF carrier during measurement, the volume of the DPF carrier and the differential pressure of the DPF carrier, and the deviation value of the carbon loading capacity is calculated according to the corresponding relation table of the flow resistance and the carbon loading capacity, so that the method can solve the error caused by the processing error of the DPF carrier to the calculation of the carbon loading capacity of the DPF to a certain extent; however, since this method requires a constant air mass flow to be provided to the DPF by the fan operation when the engine is in a stopped state, it puts forward the requirement of additional equipment, increasing the cost of DPF initialization in the host plant; moreover, only components (friction and permeation when air flows through) in the DPF differential pressure, which are in a linear relation with the air mass flow, can be obtained by using a constant air mass flow, and components (air compression and expansion caused by changes in the cross-sectional area of a channel) related to the square of the air mass flow cannot be obtained, so that the influence of processing errors of the DPF carrier on calculation of the DPF carbon loading cannot be completely eliminated, and the prediction of the DPF carbon loading still has errors.
Disclosure of Invention
The embodiment of the application provides a DPF initialization self-learning method and device, and aims to solve the problems that in the related technology, the processing error of a DPF carrier influences the DPF carbon loading capacity prediction and the DPF initialization cost is high.
In a first aspect, a DPF initialization self-learning method is provided, which includes the following steps:
respectively acquiring DPF inlet temperature, exhaust mass flow and DPF pressure difference in preset vehicle mileage;
fitting a relation function of differential pressure and exhaust mass flow according to the DPF inlet temperature, the exhaust mass flow and the DPF differential pressure to obtain a DPF initial differential pressure parameter;
and calculating the DPF initial pressure difference according to the DPF initial pressure difference parameter.
In some embodiments, after said calculating DPF initial pressure difference based on said DPF initial pressure difference parameter, further comprises:
acquiring DPF actual pressure difference;
calculating to obtain carbon load capacity differential pressure according to the actual differential pressure of the DPF and the initial differential pressure of the DPF;
and estimating the carbon loading of the DPF according to the carbon loading differential pressure.
In some embodiments, the relationship function includes linear and non-linear relationships between differential pressure and exhaust mass flow.
In some embodiments, the relationship function comprises:
ΔPinit＝a·μ·Q+b·ρ·Q2
in the formula,. DELTA.PinitThe initial pressure difference of the DPF is represented by a, a is a linear DPF initial pressure difference parameter, b is a nonlinear DPF initial pressure difference parameter, mu is exhaust dynamic viscosity, rho is exhaust density, and Q is exhaust mass flow.
In some embodiments, before said obtaining the DPF inlet temperature, the exhaust mass flow rate, and the DPF differential pressure within the preset vehicle mileage respectively, the method further comprises:
arranging a temperature sensor at the inlet of the DPF, wherein the sensor is used for acquiring the inlet temperature of the DPF;
a flow sensor is arranged on an air inlet pipe of the engine and is used for collecting the exhaust mass flow;
and respectively arranging differential pressure sensors at two ends of the DPF, wherein the differential pressure sensors are used for collecting the differential pressure of the DPF.
In a second aspect, a DPF initialization self-learning apparatus is provided, comprising:
the data acquisition unit is used for respectively acquiring DPF inlet temperature, exhaust mass flow and DPF pressure difference in preset vehicle mileage;
the fitting function unit is used for fitting a relation function of differential pressure and exhaust mass flow according to the DPF inlet temperature, the exhaust mass flow and the DPF differential pressure to obtain a DPF initial differential pressure parameter;
and the pressure difference calculation unit is used for calculating the DPF initial pressure difference according to the DPF initial pressure difference parameter.
In some embodiments, the apparatus further comprises a carbon load estimation unit for:
acquiring DPF actual pressure difference;
calculating to obtain carbon load capacity differential pressure according to the actual differential pressure of the DPF and the initial differential pressure of the DPF;
and estimating the carbon loading of the DPF according to the carbon loading differential pressure.
In some embodiments, the relationship function includes linear and non-linear relationships between differential pressure and exhaust mass flow.
In some embodiments, the relationship function comprises:
ΔPinit＝a·μ·Q+b·ρ·Q2
in the formula,. DELTA.PinitThe initial pressure difference of the DPF is represented by a, a is a linear DPF initial pressure difference parameter, b is a nonlinear DPF initial pressure difference parameter, mu is exhaust dynamic viscosity, rho is exhaust density, and Q is exhaust mass flow.
In some embodiments, the apparatus further comprises a data acquisition unit comprising:
the temperature sensor is arranged at the inlet of the DPF and is used for collecting the temperature of the inlet of the DPF;
the flow sensor is arranged on an air inlet pipe of the engine and is used for collecting the exhaust mass flow;
and the two differential pressure sensors are respectively arranged at two ends of the DPF and are used for collecting the pressure difference of the DPF.
The beneficial effect that technical scheme that this application provided brought includes: the influence of the processing error of the DPF carrier on the DPF carbon loading capacity prediction is effectively avoided, and the cost of DPF initialization is reduced.
The embodiment of the application provides a DPF initialization self-learning method and a DPF initialization self-learning device, a relationship function of the DPF inlet temperature, the exhaust mass flow and the DPF pressure difference in preset vehicle mileage to the pressure difference and the exhaust mass flow is fitted to obtain a DPF initial pressure difference parameter, the DPF initial pressure difference is calculated according to the DPF initial pressure difference parameter to obtain the DPF initial pressure difference, because the initial pressure difference parameter of the DPF obtained by fitting the relation function of the pressure difference and the exhaust mass flow fully reflects the relation between the pressure difference and the friction and the permeation of gas flowing through the DPF and the relation between the pressure difference and the air compression and expansion caused by the change of the channel sectional area, therefore, the DPF initial pressure difference calculated by the DPF initial pressure difference parameter is the actual DPF pressure difference of each carrier, the flow resistance deviation caused by the processing difference of the DPF carrier and the smearing of the oxidation coating material can be effectively reduced, and the prediction accuracy of the carbon loading capacity of the DPF is further improved; and the DPF initial pressure difference parameter is calculated when the engine is in a normal running state, so that the engine does not need to be in a stop state and constant air mass flow is provided for the DPF through the running of a fan, and the cost for initializing the DPF is effectively reduced. Therefore, the method and the device effectively avoid the influence of the processing error of the DPF carrier on the DPF carbon loading capacity prediction, and reduce the cost of DPF initialization.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a DPF initialization self-learning method according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an initialization self-learning device for a DPF according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The embodiment of the application provides a DPF initialization self-learning method and device, and the problems that in the related technology, the processing error of a DPF carrier influences the DPF carbon loading capacity prediction and the DPF initialization cost is high can be solved.
FIG. 1 is a DPF initialization self-learning method provided by an embodiment of the present application, including the following steps:
s1: and respectively acquiring DPF inlet temperature, exhaust mass flow and DPF pressure difference in the preset vehicle mileage.
S2: and fitting a relation function of the pressure difference and the exhaust mass flow according to the DPF inlet temperature, the exhaust mass flow and the DPF pressure difference to obtain the DPF initial pressure difference parameter.
S3: and calculating the DPF initial pressure difference according to the DPF initial pressure difference parameter.
Fitting a relation function of pressure difference and exhaust mass flow through the obtained DPF inlet temperature, exhaust mass flow and DPF pressure difference in the preset vehicle mileage to obtain DPF initial pressure difference parameters, and calculating the DPF initial pressure difference according to the DPF initial pressure difference parameters; and the DPF initial pressure difference parameter is calculated when the engine is in a normal running state, so that the engine does not need to be in a stop state and constant air mass flow is provided for the DPF through the running of a fan, and the cost for initializing the DPF is effectively reduced. Therefore, the method and the device effectively avoid the influence of the processing error of the DPF carrier on the DPF carbon loading capacity prediction, and reduce the cost of DPF initialization.
Further, in the embodiment of the present application, after calculating the DPF initial pressure difference according to the DPF initial pressure difference parameter, the method further includes the following steps:
acquiring DPF actual pressure difference;
calculating to obtain carbon loading capacity differential pressure according to the actual differential pressure of the DPF and the initial differential pressure of the DPF;
estimating the carbon loading of the DPF according to the carbon loading differential pressure;
the specific formula is as follows:
ΔPsoot＝ΔPmeasure-ΔPinit
in the formula,. DELTA.PsootIs the carbon loading differential, Δ PmeasureIs DPF actual differential pressure, Δ PinitFor DPF initial pressure difference, the carbon loading capacity pressure difference is corrected through DPF actual pressure difference and DPF initial pressure difference, and the DPF carbon loading capacity is estimated through the corrected carbon loading capacity pressure difference, so that the accuracy of DPF carbon loading capacity estimation can be effectively improved.
Further, in the present embodiment, the relationship function includes a linear relationship and a non-linear relationship between the pressure difference and the exhaust mass flow, i.e. the DPF initial pressure difference is composed of two parts: a fraction related to friction and permeation of gases as they flow through the DPF, the fraction being proportional to exhaust mass flow and proportional to current exhaust dynamic viscosity; the other part is related to air compression expansion caused by the change of the channel sectional area, and the part is in direct proportion to the square of the exhaust mass flow and in direct proportion to the exhaust density; specifically, the relationship function includes:
ΔPinit＝a·μ·Q+b·ρ·Q2
in the formula,. DELTA.PinitThe initial pressure difference of the DPF is represented by a, a is a linear DPF initial pressure difference parameter, b is a nonlinear DPF initial pressure difference parameter, mu is exhaust dynamic viscosity, rho is exhaust density, and Q is exhaust mass flow.
Further, in this embodiment of the present application, before obtaining the DPF inlet temperature, the exhaust mass flow rate, and the DPF differential pressure within the preset vehicle mileage respectively, the method further includes:
a temperature sensor is arranged at the inlet of the DPF and used for collecting the temperature of the inlet of the DPF;
a flow sensor is arranged on an air inlet pipe of the engine and used for collecting exhaust mass flow;
and respectively arranging differential pressure sensors at two ends of the DPF, wherein the differential pressure sensors are used for collecting the differential pressure of the DPF.
Specifically, the DPF initialization self-learning method of the embodiment of the application comprises the following steps: after the DPF is initially installed, in a certain vehicle mileage (or enough sampling point number is met and cut off), under the condition that a certain sampling working condition is met (the working condition is stable, the flow sensor, the exhaust temperature sensor and the differential pressure sensor are all in a normal state, and the flow, the temperature and the differential pressure are all in the working range of the sensors), the exhaust mass flow, the DPF inlet temperature and the DPF differential pressure are recorded, the carbon loading capacity in the DPF is small at the moment, the influence on the differential pressure can be ignored, a relation function of the differential pressure and the exhaust mass flow is fitted, the DPF initial differential pressure parameters a and b can be obtained, and the initialization work of the DPF initial differential pressure parameters is completed; calculating to obtain carbon loading capacity differential pressure according to the actual differential pressure of the DPF and the initial differential pressure of the DPF; and finally, the carbon loading capacity of the DPF is estimated according to the carbon loading capacity differential pressure, so that the accuracy of DPF carbon loading capacity estimation is effectively improved.
Referring to fig. 2, an embodiment of the present application further provides an initial self-learning apparatus for DPF, which includes a data obtaining unit, a fitting function unit, and a differential pressure calculating unit, wherein,
the data acquisition unit is used for respectively acquiring DPF inlet temperature, exhaust mass flow and DPF pressure difference in preset vehicle mileage;
the fitting function unit is used for fitting a relation function of differential pressure and exhaust mass flow according to DPF inlet temperature, exhaust mass flow and DPF differential pressure to obtain DPF initial differential pressure parameters;
the pressure difference calculation unit is used for calculating the DPF initial pressure difference according to the DPF initial pressure difference parameters.
The fitting function unit fits a relation function of DPF inlet temperature, exhaust mass flow and DPF pressure difference to pressure difference and exhaust mass flow in the preset vehicle mileage acquired by the data acquisition unit to obtain a DPF initial pressure difference parameter, the pressure difference calculation unit calculates the DPF initial pressure difference according to the DPF initial pressure difference parameter, because the initial pressure difference parameter of the DPF obtained by fitting the relation function of the pressure difference and the exhaust mass flow fully reflects the relation between the pressure difference and the friction and the permeation of gas flowing through the DPF and the relation between the pressure difference and the air compression and expansion caused by the change of the channel sectional area, therefore, the DPF initial pressure difference calculated by the DPF initial pressure difference parameter is the actual DPF pressure difference of each carrier, the flow resistance deviation caused by the processing difference of the DPF carrier and the smearing of the oxidation coating material can be effectively reduced, and the prediction accuracy of the carbon loading capacity of the DPF is further improved; and the DPF initial pressure difference parameter is calculated when the engine is in a normal running state, so that the engine does not need to be in a stop state and constant air mass flow is provided for the DPF through the running of a fan, and the cost for initializing the DPF is effectively reduced. Therefore, the method and the device effectively avoid the influence of the processing error of the DPF carrier on the DPF carbon loading capacity prediction, and reduce the cost of DPF initialization.
Further, in an embodiment of the present application, the apparatus further comprises a carbon load estimation unit for:
acquiring DPF actual pressure difference;
calculating to obtain carbon loading capacity differential pressure according to the actual differential pressure of the DPF and the initial differential pressure of the DPF;
estimating the carbon loading of the DPF according to the carbon loading differential pressure;
the specific formula is as follows:
ΔPsoot＝ΔPmeasure-ΔPinit
in the formula,. DELTA.PsootIs the carbon loading differential, Δ PmeasureIs DPF actual differential pressure, Δ PinitFor DPF initial pressure difference, the carbon loading capacity pressure difference is corrected through DPF actual pressure difference and DPF initial pressure difference, and the DPF carbon loading capacity is estimated through the corrected carbon loading capacity pressure difference, so that the accuracy of DPF carbon loading capacity estimation can be effectively improved.
Further, in the present embodiment, the relationship function includes a linear relationship and a non-linear relationship between the pressure difference and the exhaust mass flow, i.e. the DPF initial pressure difference is composed of two parts: a fraction related to friction and permeation of gases as they flow through the DPF, the fraction being proportional to exhaust mass flow and proportional to current exhaust dynamic viscosity; the other part is related to air compression expansion caused by the change of the channel sectional area, and the part is in direct proportion to the square of the exhaust mass flow and in direct proportion to the exhaust density; specifically, the relationship function includes:
ΔPinit＝a·μ·Q+b·ρ·Q2
in the formula,. DELTA.PinitThe initial pressure difference of the DPF is represented by a, a is a linear DPF initial pressure difference parameter, b is a nonlinear DPF initial pressure difference parameter, mu is exhaust dynamic viscosity, rho is exhaust density, and Q is exhaust mass flow.
Furthermore, in the embodiment of the present application, the device further comprises a data acquisition unit, wherein the data acquisition unit comprises a temperature sensor, a flow sensor and two differential pressure sensors, wherein,
the temperature sensor is arranged at the inlet of the DPF and is used for collecting the temperature of the inlet of the DPF;
the flow sensor is arranged on an air inlet pipe of the engine and used for collecting exhaust mass flow;
two differential pressure sensors are respectively arranged at two ends of the DPF and are used for collecting the differential pressure of the DPF.
In the description of the present application, it should be noted that the terms "upper", "lower", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, which are only for convenience in describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and operate, and thus, should not be construed as limiting the present application. Unless expressly stated or limited otherwise, the terms "mounted," "connected," and "connected" are intended to be inclusive and mean, for example, that they may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as appropriate.
It is noted that, in the present application, relational terms such as "first" and "second", and the like, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is merely exemplary of the present application and is presented to enable those skilled in the art to understand and practice the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (8)

1. The DPF initialization self-learning method is characterized by comprising the following steps:
respectively acquiring DPF inlet temperature, exhaust mass flow and DPF pressure difference in preset vehicle mileage;
fitting a relation function of DPF pressure difference and exhaust mass flow according to the DPF inlet temperature, the exhaust mass flow and the DPF pressure difference to obtain DPF initial pressure difference parameters;
and calculating the DPF initial pressure difference according to the DPF initial pressure difference parameter.
2. The DPF initialization self-learning method of claim 1, further comprising, after said calculating DPF initial pressure difference based on said DPF initial pressure difference parameter:
acquiring DPF actual pressure difference;
calculating to obtain carbon load capacity differential pressure according to the actual differential pressure of the DPF and the initial differential pressure of the DPF;
and estimating the carbon loading of the DPF according to the carbon loading differential pressure.
3. The DPF initialization self-learning method of claim 1, wherein: the relationship function includes linear and non-linear relationships between DPF pressure differential and exhaust mass flow.
4. The DPF initialization self-learning method of claim 3, wherein the relationship function comprises:
ΔPinit＝a·μ·Q+b·ρ·Q2
in the formula,. DELTA.PinitThe initial pressure difference of the DPF is represented by a, a is a linear DPF initial pressure difference parameter, b is a nonlinear DPF initial pressure difference parameter, mu is exhaust dynamic viscosity, rho is exhaust density, and Q is exhaust mass flow.
5. An initial self-learning device for a DPF, comprising:
the data acquisition unit is used for respectively acquiring DPF inlet temperature, exhaust mass flow and DPF pressure difference in preset vehicle mileage;
the fitting function unit is used for fitting a relation function of DPF pressure difference and exhaust mass flow according to the DPF inlet temperature, the exhaust mass flow and the DPF pressure difference to obtain a DPF initial pressure difference parameter;
and the pressure difference calculation unit is used for calculating the DPF initial pressure difference according to the DPF initial pressure difference parameter.
6. The DPF initialization self-learning apparatus of claim 5, wherein the apparatus further comprises a carbon loading estimation unit for:
acquiring DPF actual pressure difference;
calculating to obtain carbon load capacity differential pressure according to the actual differential pressure of the DPF and the initial differential pressure of the DPF;
and estimating the carbon loading of the DPF according to the carbon loading differential pressure.
7. The DPF initialization self-learning apparatus as set forth in claim 5, wherein: the relationship function includes linear and non-linear relationships between DPF pressure differential and exhaust mass flow.
8. The DPF initialization self-learning apparatus of claim 6, wherein the relationship function comprises:
ΔPinit＝a·μ·Q+b·ρ·Q2
in the formula,. DELTA.PinitThe initial pressure difference of the DPF is represented by a, a is a linear DPF initial pressure difference parameter, b is a nonlinear DPF initial pressure difference parameter, mu is exhaust dynamic viscosity, rho is exhaust density, and Q is exhaust mass flow.
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