CN112761766B - DPF carbon loading capacity estimation method and system - Google Patents

DPF carbon loading capacity estimation method and system Download PDF

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Publication number
CN112761766B
CN112761766B CN202110110161.6A CN202110110161A CN112761766B CN 112761766 B CN112761766 B CN 112761766B CN 202110110161 A CN202110110161 A CN 202110110161A CN 112761766 B CN112761766 B CN 112761766B
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dpf
flow resistance
pressure difference
resistance coefficient
self
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CN112761766A (en
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李芳�
韩虎
王梅俊
杨晓莹
郑攀
程欢
李林
白桃李
陈玉俊
周杰敏
张衡
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Dongfeng Commercial Vehicle Co Ltd
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Dongfeng Commercial Vehicle 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
    • 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
    • F01N11/00—Monitoring or diagnostic devices for exhaust-gas treatment apparatus, e.g. for catalytic activity
    • 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
    • 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

Abstract

The invention relates to the technical field of exhaust aftertreatment of internal combustion engines, in particular to a DPF carbon loading capacity estimation method and a DPF carbon loading capacity estimation system. The method comprises the following steps: acquiring the pressure difference before and after DPF when a vehicle runs; calling the initial flow resistance coefficient and the last self-learned flow resistance coefficient of the residual ash content of the DPF, and combining the pressure difference before and after the DPF when the vehicle runs to obtain the pressure drop generated by the initial flow resistance and the pressure drop generated by the residual ash content under the current pressure difference; and obtaining the pressure drop related to the carbon loading according to the pressure difference between the front and the back of the current DPF, the pressure drop generated by the initial flow resistance under the pressure difference and the pressure drop generated by the residual ash, thereby obtaining the carbon loading of the current DPF. The method and the device can solve the problem that the DPF carbon loading amount is estimated inaccurately in the prior art.

Description

DPF carbon loading capacity estimation method and system
Technical Field
The invention relates to the technical field of exhaust aftertreatment of internal combustion engines, in particular to a DPF carbon loading capacity estimation method and a DPF carbon loading capacity estimation system.
Background
Diesel particulate traps (DPFs) are the requisite aftertreatment devices for diesel engines to meet emissions legislation requirements. The DPF collects Particulate Matter (PM) in the exhaust gas of the diesel engine by means of physical filtration, and reduces the PM emission of the diesel engine. As particulate matter accumulates in the DPF channels, the pressure drop across the DPF can increase, which can increase the exhaust backpressure of the engine, deteriorate the fuel consumption of the engine, and in severe cases can even directly block the exhaust pipe, causing 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.
In the traditional regeneration opportunity control method, the main methods for judging the carbon loading amount in the DPF comprise an exhaust back pressure method, a driving time method, a soot emission amount method and a carbon loading amount estimation method based on pressure difference, wherein the judgment result is more accurate to be the carbon loading amount estimation method based on the pressure difference.
Currently, the regeneration technology of the DPF of the engine particulate trap can be divided into passive regeneration and active regeneration from the regeneration mode. Passive regeneration is the combustion of trapped particulate matter using exhaust conditions created by the high speed, high load conditions of the engine that may exist, but this approach does not eliminate DPF plugging failures because the mode in which the user uses the engine is uncertain. Active regeneration is a special system for regenerating a DPF by generating exhaust gas at a temperature higher than a temperature at which particulate matter in the DPF can ignite at any time based on a monitored operating state of the DPF.
The judgment of DPF regeneration time is an important link in DPF active regeneration control. Premature regeneration of the DPF can result in frequent DPF regeneration, which can reduce the fuel economy of the engine due to increased fuel consumption for DPF regeneration. The delayed regeneration of the DPF can cause that the temperature in the DPF is too high, the filter carrier is burnt, and the reliability and the durability of the DPF are reduced because the accumulated soot in the DPF is too much during regeneration, the soot is oxidized and burnt too violently, and the speed of releasing heat is too high. Therefore, during the DPF active regeneration control process, a prediction model of the DPF carbon loading is generally established to estimate the carbon loading in the DPF in real time. When the carbon loading in the DPF reaches a preset carbon loading, a regeneration operation is performed on the DPF.
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, when the DPF is regenerated, the ash component in the PM accumulated in the DPF cannot be removed by means of regeneration, and as the service life of the DPF increases, the ash component is accumulated in the DPF continuously and changes the correlation between the carbon loading of the DPF and the pressure difference of the DPF, so that the incorrect estimation of the carbon loading of the DPF by the carbon loading prediction model of the DPF causes the DPF to be regenerated too early or to be delayed.
Calculating the ash accumulation basic volume mass based on the fuel injection quantity and the rotating speed and performing time integration to obtain the average ash accumulation volume quantity; and correcting the volume mass of the ash content according to the total running time of the diesel engine on the DPF to obtain the volume mass of the final ash content, and calculating a carbon loading capacity correction factor of the ash content based on the volume mass of the ash content for correcting the carbon loading capacity. However, this method only considers the effect of the ash volume on the DPF carbon loading estimation and does not consider the effect of the different distribution patterns of ash within the DPF.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a DPF carbon loading capacity estimation method and a DPF carbon loading capacity estimation system, which can solve the problem that the estimation of the DPF carbon loading capacity in the prior art is inaccurate.
In order to achieve the above purposes, the technical scheme adopted by the invention is as follows:
in one aspect, the invention provides a DPF carbon loading estimation method, comprising the steps of:
acquiring the pressure difference before and after DPF when a vehicle runs;
calling the initial flow resistance coefficient and the last self-learned flow resistance coefficient of the residual ash content of the DPF, and combining the pressure difference before and after the DPF when the vehicle runs to obtain the pressure drop generated by the initial flow resistance and the pressure drop generated by the residual ash content under the current pressure difference;
and obtaining the carbon loading capacity of the DPF according to the pressure difference between the front and the back of the DPF, the pressure drop generated by the initial flow resistance under the pressure difference and the pressure drop generated by the residual ash.
In some optional embodiments, the self-learned residual ash flow resistance coefficient is obtained according to the following steps:
when the carbon loading of the DPF reaches a set threshold value, starting DPF regeneration;
when the DPF meets the condition of self-learning of the ash flow resistance coefficient, acquiring the pressure difference between the front and the back of the DPF after regeneration of the DPF, and calculating the pressure drop generated by the initial flow resistance under the current pressure difference by combining the initial flow resistance coefficient so as to obtain the pressure drop generated by residual ash after regeneration of the DPF;
according to the pressure drop generated by the regenerated residual ash of the DPF, obtaining the flow resistance coefficient of the residual ash after the regeneration of the DPF, and using the flow resistance coefficient of the residual ash after the regeneration of the DPF as a self-learned flow resistance coefficient of the residual ash to replace the last self-learned flow resistance coefficient of the residual ash;
wherein the flow resistance coefficient of the residual ash obtained by the first self-learning is a set value.
In some optional embodiments, the self-learning condition is that the vehicle travels a set mileage or that the vehicle consumes fuel to a set fuel amount after the last self-learning.
In some optional embodiments, obtaining the initial flow resistivity comprises:
acquiring the pressure difference between the front end and the rear end of the DPF during initial installation;
and calculating to obtain the initial flow resistance coefficient of the DPF during initial installation according to the pressure difference between the front end and the rear end of the DPF during initial installation.
In some alternative embodiments, the initial coefficient of flow resistance is determined by a linear function, in particular:
according to the formula Δ Pinit＝a·μ·QinitDetermining an initial flow resistance coefficient a, where μ is the dynamic viscosity of the exhaust gas, QinitTo measure delta PinitFlow rate of time, Δ PinitThe pressure difference between the front end and the rear end during the initial installation of the DPF.
In some optional embodiments, the obtaining of the self-learning flow resistance coefficient of the residual ash specifically comprises the following steps:
when DPF regeneration meets self-learning conditions, according to formula delta P(i)init＝a·μ·Q(i)And calculating to obtain the pressure drop delta P generated by the initial flow resistance of the DPF after regeneration during the ith self-learning of the DPF(i)initWherein Q is(i)The flow rate of the DPF at the ith self-learning time is obtained;
according to the formula Δ P(i)ash＝△P(i)tot-△P(i)initAnd calculating to obtain the pressure drop delta P generated by the residual ash content after the regeneration of the DPF during the ith self-learning of the DPF(i)ash，△P(i)totObtaining the pressure difference in the ith self-learning process;
according to the formula Δ a(i)＝f(△P(i)ash，Q(i)) Calculating to obtain the flow resistance coefficient delta a of the residual ash of the ith self-learning DPF(i)。
In some alternative embodiments, said initial coefficient of flow resistance is calculated by a quadratic function, in particular:
according to the formula Δ Pinit＝a·μ·Qinit+b·ρ·Qinit 2Determining initial flow resistance coefficients a and b, where μ is the dynamic viscosity of the exhaust gas, QinitTo measure delta PinitFlow rate of time, ρ is density of exhaust gas, Δ PinitThe pressure difference between the front end and the rear end during the initial installation of the DPF.
In some optional embodiments, the obtaining of the self-learning flow resistance coefficient of the residual ash specifically comprises the following steps:
according to formula P(i)init＝a·μ·Q(i)+b·ρ·Q(i) 2Calculating to obtain the pressure drop delta P generated by the initial flow resistance after DPF regeneration during the i-th self-learning of the DPF(i)initWherein Q is(i)Calculating the flow of the residual ash flow resistance coefficient after DPF regeneration in the ith self-learning process of the DPF;
according to the formula Δ P(i)ash＝△P(i)tot-△P(i)initCalculating to obtain the pressure drop delta P generated by residual ash content after DPF regeneration during the i-th self-learning of the DPF(i)ash，△P(i)totAfter regeneration for the acquired DPF at the ith self-learning timePressure difference before and after DPF;
according to the formula Δ a(i)，△b(i)＝f(△P(i)ash，Q(i)) Calculating to obtain the flow resistance coefficient delta a of the i-th self-learning residual ash of the DPF(i)，△b(i)。
In some alternative embodiments, the temperature of the DPF is obtained when the pressure difference before and after the DPF is obtained, and the kinetic viscosity μ and the density ρ of the exhaust gas are corrected by the obtained temperature and pressure.
In another aspect, the present invention also provides a DPF carbon loading estimation system comprising:
the data acquisition module is used for acquiring the pressure difference before and after the DPF when the vehicle runs;
the residual ash pressure drop calculation module is used for calling the initial flow resistance coefficient and the last self-learned residual ash flow resistance coefficient and is used for obtaining the pressure drop generated by the initial flow resistance and the pressure drop generated by the residual ash under the current pressure difference by combining the pressure difference between the front and the back of the DPF when the vehicle runs;
and the carbon loading estimation module is used for obtaining the pressure drop caused by the carbon loading in the DPF according to the pressure difference between the front and the back of the DPF, the pressure drop generated by the initial flow resistance under the pressure difference and the pressure drop generated by the residual ash, so that the carbon loading of the DPF is obtained.
Compared with the prior art, the invention has the advantages that: the method considers the ash accumulation in the DPF after each regeneration, can accurately react the pressure drop generated by the ash accumulation to the next soot carbon loading accumulation period, and can accurately react out regardless of the distribution form of the ash and whether the distribution form completely accords with the time law.
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 flow chart of a DPF carbon loading estimation method in an embodiment of the invention;
FIG. 2 is a diagram of the overall implementation steps of the DPF carbon loading estimation method in the embodiment of the invention.
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.
Embodiments of the present invention will be described in further detail below with reference to the accompanying drawings. FIG. 1 is a flow chart of a DPF carbon loading estimation method in an embodiment of the invention; FIG. 2 is a diagram of the overall implementation steps of the DPF carbon loading estimation method in the embodiment of the invention. As shown in fig. 1 and 2:
example one
The invention provides a DPF carbon loading capacity estimation method, which comprises the following steps:
s1: acquiring the pressure difference before and after DPF when a vehicle runs;
s2: calling the initial flow resistance coefficient and the last self-learned flow resistance coefficient of the residual ash, and combining the pressure difference before and after the DPF when the vehicle runs to obtain the pressure drop generated by the initial flow resistance and the pressure drop generated by the residual ash under the current pressure difference;
s3: and obtaining the carbon loading capacity of the DPF according to the pressure difference between the front and the back of the DPF, the pressure drop generated by the initial flow resistance under the pressure difference and the pressure drop generated by the residual ash.
When the DPF carbon loading capacity estimation method is used, after DPF active regeneration is completed, in the next soot accumulation period, the calculated flow resistance coefficient of the residual ash content self-learned last time of the initial flow resistance coefficient is called, and the pressure drop generated by the initial flow resistance and the ash content in the DPF is calculated, so that the pressure drop generated by soot accumulation in the period is obtained, and the corrected DPF carbon loading capacity estimation value can be obtained. The method considers the ash accumulation in the DPF after each regeneration, can accurately react the pressure drop generated by the ash accumulation to the next soot accumulation period, and can accurately react out regardless of the distribution form of the ash and whether the distribution form completely accords with the time law.
Example two
On the basis of the first embodiment, the self-learning residual ash flow resistance coefficient is obtained according to the following steps:
when the carbon loading of the DPF reaches a set threshold value, starting DPF regeneration;
when the DPF meets the condition of self-learning of the ash flow resistance coefficient, acquiring the pressure difference between the front and the back of the DPF after regeneration of the DPF, and calculating the pressure drop generated by the initial flow resistance under the current pressure difference by combining the initial flow resistance coefficient so as to obtain the pressure drop generated by residual ash after regeneration of the DPF;
according to the pressure drop generated by the regenerated residual ash of the DPF, obtaining the flow resistance coefficient of the residual ash after the regeneration of the DPF, and using the flow resistance coefficient of the residual ash after the regeneration of the DPF as a self-learned flow resistance coefficient of the residual ash to replace the last self-learned flow resistance coefficient of the residual ash;
wherein the flow resistance coefficient of the residual ash obtained by the first self-learning is a set value.
In this example, the first self-learned residual ash flow resistance coefficient is the residual ash flow resistance coefficient when the DPF is initially installed, and since it is not used at this time, the first self-learned residual ash flow resistance coefficient is set to 0.
In some optional embodiments, the self-learning condition is that the vehicle has traveled the set mileage or that the vehicle has consumed fuel to the set fuel amount after the last self-learning.
Specifically, DPF regeneration is started when the carbon loading of the DPF reaches a set threshold, but self-learning of the residual ash flow resistance coefficient is not performed if the vehicle does not travel the set mileage or the vehicle fuel reaches the set fuel amount since the last self-learning. When the set mileage is reached or the vehicle fuel reaches the set fuel amount, and self-learning of the residual ash flow resistance coefficient is needed, a section of active regeneration time length can be increased after the active regeneration is normally finished so as to ensure that carbon in the DPF is burnt out.
EXAMPLE III
On the basis of the first embodiment, the method for obtaining the initial flow resistance coefficient comprises the following steps:
acquiring the pressure difference between the front end and the rear end of the DPF during initial installation; and calculating to obtain the initial flow resistance coefficient of the DPF during initial installation according to the pressure difference between the front end and the rear end of the DPF during initial installation.
In this embodiment, when the DPF is initially installed, the initial flow resistance coefficient of the DPF during initial installation is obtained by the pressure difference between the front end and the rear end of the DPF, so that the initial flow resistance coefficient is more accurate, and the pressure drop generated by the initial flow resistance in the next accumulation period is more accurate. In some other embodiments, the initial flow resistivity may also be obtained by factory design parameters of the DPF or bench calibration.
The timing judgment of the first regeneration comprises the following steps:
after the initial flow resistance coefficient of the DPF during initial installation is obtained, when the vehicle is used, the pressure difference between the front and the back of the DPF during running of the vehicle is obtained, and the initial flow resistance coefficient and the first self-learned flow resistance coefficient of the residual ash at the moment are called. Since the first self-learned residual ash flow resistance coefficient is set to 0, the pressure drop caused by the residual ash flow resistance coefficient is 0. Obtaining the pressure drop generated by the initial flow resistance under the current pressure difference by combining the pressure difference before and after the DPF when the vehicle runs; obtaining the pressure drop related to the carbon loading capacity according to the pressure difference between the front and the back of the DPF and the pressure drop generated by the initial flow resistance under the pressure difference, thereby obtaining the carbon loading capacity of the DPF; DPF regeneration is initiated when the carbon loading of the DPF reaches a set threshold.
Example four
On the basis of the third embodiment, the initial flow resistance coefficient is calculated by a linear function, specifically:
according to the formula Δ Pinit＝a·μ·QinitDetermining an initial flow resistance coefficient a, where μ is the dynamic viscosity of the exhaust gas, QinitTo measure delta PinitFlow rate of time, Δ PinitThe pressure difference between the front end and the rear end during the initial installation of the DPF.
In some optional embodiments, the obtaining of the self-learned flow resistance coefficient of the residual ash specifically comprises the following steps:
when the DPF regeneration meets the self-learning condition, acquiring the pressure difference before and after the DPF regeneration, and calculating the pressure drop generated by the initial flow resistance under the current pressure difference by combining the initial flow resistance coefficient to obtain the pressure drop generated by the residual ash content after the DPF regeneration, specifically,
when DPF regeneration meets self-learning conditions, according to formula delta P(i)init＝a·μ·Q(i)And calculating to obtain the pressure drop delta P generated by the initial flow resistance of the DPF after regeneration during the ith self-learning of the DPF(i)initWherein Q is(i)The flow rate of the DPF at the ith self-learning time is shown.
According to the formula Δ P(i)ash＝△P(i)tot-△P(i)initAnd calculating to obtain the pressure drop delta P generated by the residual ash content after the regeneration of the DPF during the ith self-learning of the DPF(i)ash，△P(i)totThe pressure difference obtained in the ith self-learning process is used.
The flow resistance coefficient of the residual ash of the DPF regeneration residual ash is obtained according to the pressure drop generated by the DPF regeneration residual ash, and specifically,
according to the formula Δ a(i)＝f(△P(i)ash，Q(i)) Calculating to obtain the flow resistance coefficient delta a of the residual ash of the ith self-learning DPF(i)。
Residual ash flow resistance coefficient delta a of DPF due to 1 st self-learning(1)The value of i in this example is an integer greater than or equal to 2, which is a set value of 0.
A specific example of the fourth embodiment is given below:
the initial differential flow resistance of the DPF is considered to be a linear component: delta Pinit＝a·μ·Qinit
The DPF flow resistivity a may be provided by the supplier at the time of initial DPF installation, or may be determined by the pressure differential across the DPF after initial installation.
And acquiring the temperature of the DPF while acquiring the pressure difference before and after the DPF, and correcting the dynamic viscosity mu through the temperature and the pressure of the DPF.
By the function a ═ f ([ Delta ] P)init，Qinit，Tinit) Where T is used to correct mu. In the first soot accumulation period, the pressure difference DeltaP from the front end and the rear end of the DPF is neededtotSubtracting the Δ P due to initial DPF flow resistance from the measurementinitObtaining a pressure difference Δ P caused only by rootsootThen, the carbon load estimation model calculates the corresponding carbon load estimation value Msoot。
In this example, the flow resistance coefficient Δ a of the residual ash is self-learned for the first time(1)Set to 0, the residual ash flow resistivity produces a pressure drop of 0, regardless.
△Psoot＝△Ptot-△Pinit
Msoot＝f(△Psoot)
When the carbon loading is accumulated to exceed the threshold value, the active regeneration is triggered, and after the active regeneration is normally finished. And judging the current vehicle working condition and environmental factors (including the fact that the vehicle runs to reach the set mileage or the fuel consumed by the vehicle reaches the set fuel quantity), and if the set requirement is met, increasing a section of active regeneration time length to ensure that the soot in the DPF is completely burnt out, so as to solve the current residual ash flow resistance coefficient as the self-learned residual ash flow resistance coefficient. If not, the flow resistance coefficient of the residual ash at the moment is not solved.
Specifically, the flow resistance coefficient of the residual ash at this time is solved: measuring differential pressure delta P between front end and rear end of DPF(2)totThe pressure difference is the pressure drop delta P caused by the ash accumulation in the root accumulation period(2)ashPressure drop Δ P with initial DPF flow resistance(2)initAccording to the formula DeltaP(2)ash＝△P(2)tot-△P(2)initCalculating to obtain the pressure drop delta P generated by the residual ash content after DPF regeneration in the 2 nd self-learning of the DPF(2)ash，△P(2)totThe pressure difference obtained in the 2 nd self-learning is used.
The flow resistance coefficient of the residual ash of the DPF regeneration residual ash is obtained according to the pressure drop generated by the DPF regeneration residual ash, and specifically,
according to the formula Δ a(2)＝f(△P(2)ash，Q(2)) Calculating to obtain the flow resistance coefficient delta a of the residual ash of the ith self-learning DPF(2)。
In the next soot accumulation period, the pressure difference DeltaP from the front end and the rear end of the DPF is neededtotSubtracting the new flow resistance coefficient Deltaa from the measured value(2)Resulting Δ PashObtaining a pressure difference Δ P caused only by rootsootThen, the carbon load estimation model calculates the corresponding carbon load estimation value Msoot。
△Pinit+ash＝f(a，Q，T)+f(△a(2)Q, T), where T is used to correct μ. Delta Psoot＝△Ptot-△Pinit+ash
Msoot＝f(△Psoot)
And analogizing, after each self-learning condition is met and the DPF regeneration root is completely burnt out, carrying out self-learning, and updating the flow resistance coefficient delta a of the residual ash(i)For correcting the carbon load estimate in the next soot accumulation period.
EXAMPLE five
On the basis of the third embodiment, the initial flow resistance coefficient is calculated by a quadratic function, specifically:
according to the formula Δ Pinit＝a·μ·Qinit+b·ρ·Qinit 2Determining initial flow resistance coefficients a and b, where μ is the dynamic viscosity of the exhaust gas, QinitTo measure delta PinitFlow rate of time, ρ is density of exhaust gas, Δ PinitThe pressure difference between the front end and the rear end during the initial installation of the DPF.
In this example, to solve a and b in the above equations, the values of a and b can be found by fitting the measured pressure difference between the front and rear of the DPF at different air flow rates and exhaust temperatures. The smaller value a or b of the influencing factor can also be selected as a fixed value or a function change value of experimental fitting.
In this embodiment, the temperature of the DPF is acquired while acquiring the pressure difference before and after the DPF, and the kinetic viscosity μ and/or the density ρ of the exhaust gas are corrected by the acquired temperature and pressure.
Preferably, the method for obtaining the self-learning residual ash flow resistance coefficient specifically comprises the following steps:
according toFormula P(i)init＝a·μ·Q(i)+b·ρ·Q(i) 2Calculating to obtain the pressure drop delta P generated by the initial flow resistance after DPF regeneration during the i-th self-learning of the DPF(i)initWherein Q is(i)Calculating the flow of the residual ash flow resistance coefficient after DPF regeneration in the ith self-learning process of the DPF;
according to the formula Δ P(i)ash＝△P(i)tot-△P(i)initCalculating to obtain the pressure drop delta P generated by residual ash content after DPF regeneration during the i-th self-learning of the DPF(i)ash，△P(i)totObtaining the pressure difference before and after the DPF is regenerated during the ith self-learning of the DPF;
according to the formula Δ a(i)，△b(i)＝f(△P(i)ash，Q(i)) Calculating to obtain the flow resistance coefficient delta a of the i-th self-learning residual ash of the DPF(i)，△b(i)。
A specific example of the fifth embodiment is given below:
the pressure drop caused by the DPF initial flow resistance is considered to be two-part: a fraction related to the friction and permeation of the gas as it flows through the DPF, which is proportional to the exhaust mass flow Q and to the current exhaust dynamic viscosity μ; the other part is related to the air compression expansion caused by the change of the channel cross section area, and the part is proportional to the square of the exhaust mass flow Q and proportional to the exhaust density rho. Namely: delta Pinit＝a·μ·Qinit+b·ρ·Qinit 2
The DPF flow resistivity a and b may also be provided by the supplier upon initial installation of the DPF.
Or from [ a b ]]＝f(△Pinit，QinitAnd T) obtaining. Where T is used to correct μ and ρ.
In the soot accumulation period, the pressure difference DeltaP from the front end and the rear end of the DPF is requiredtotSubtracting the Δ P due to initial DPF flow resistance from the measurementinitObtaining a pressure difference Δ P caused only by rootsootThen, the carbon load estimation model calculates the corresponding carbon load estimation value Msoot. In this example, the flow resistance coefficient Δ a of the residual ash is self-learned for the first time(1)Set to 0, so residual ashThe flow resistivity results in a pressure drop of 0, regardless thereof.
△Psoot＝△Ptot-△Pinit
Msoot＝f(△Psoot)
And (3) triggering active regeneration when the carbon loading capacity is accumulated to exceed a threshold value, judging the current vehicle working condition and environmental factors (including the fact that the vehicle runs to reach a set mileage or the fuel consumed by the vehicle reaches a set fuel quantity) after the active regeneration is normally finished, and increasing a period of active regeneration time if the set requirement is met so as to ensure that the soot in the DPF is completely burnt out. The flow resistance coefficient of the residual ash at the moment is solved to be used as the flow resistance coefficient of the residual ash learned by the self-learning. If not, the flow resistance coefficient of the residual ash at the moment is not solved.
Specifically, solving the flow resistance coefficient of the residual ash at the moment, namely solving the flow resistance coefficient of the residual ash learned for the second time: measuring differential pressure delta P between front end and rear end of DPF(2)totSubtract the pressure drop Δ P caused by the DPF initial flow resistance(2)initI.e. the pressure drop DeltaP caused by the ash accumulation in the current soot accumulation period(2)ash：△P(2)ash＝(△P(2)tot-△P(2)init) (ii) a Thereby obtaining the flow resistance coefficient Delta a of the residual ash caused by the ash(2)、△b(2)：[△a(2)△b(2)]＝f(△Pash(2)，Q(2)，T (2))。
In the same way, in each root period, the initial flow resistance coefficient and the flow resistance coefficient delta a of the residual ash after the last self-learning updating are adopted(i)And Δ b(i)The carbon loading was calculated. Active regeneration is triggered until the carbon loading accumulates beyond a threshold. Judging the current vehicle working condition and environmental factors, including: and (3) when the conditions such as the vehicle driving mileage and the like are completed after the previous ash flow resistance coefficient self-learning is completed, when the learning conditions are met, the self-learning is performed after the soot is completely burnt out by DPF regeneration, and the residual ash flow resistance coefficient delta a is updated(i+1)For correcting the carbon load estimate in the next soot accumulation period.
The method also provides a method for solving the problem of updating the total flow resistance coefficient by self-learning each time and solving the carbon loading capacity by using the total flow resistance coefficient, taking a quadratic function as an example:
at the beginning,. DELTA.a(1)＝0，△b(1)And (4) the total flow resistance coefficient is the initial flow resistance coefficient as 0.
Same applies for Δ Pinit＝a1·μ·Qinit+b1·ρ·Qinit 2Determining the flow resistance coefficient a during initial installation of DPF1And b1And may also be provided by the supplier. So the first self-learning total flow resistance coefficient is a1And b1。
In the soot accumulation period, the pressure difference DeltaP from the front end and the rear end of the DPF is requiredtotThe delta P caused by DPF initial flow resistance is subtracted from the measurementinitObtaining a pressure difference Δ P caused only by rootsootI.e. formula Δ Psoot＝△Ptot-△Pinit；
Then, the carbon load estimation model calculates the corresponding carbon load estimation value MsootI.e. using the formula Msoot＝f(△Psoot)。
And (3) triggering active regeneration when the carbon loading capacity is accumulated to exceed a threshold value, judging the current vehicle working condition and environmental factors (including that the vehicle runs to reach a set mileage or the fuel consumed by the vehicle reaches a set fuel quantity) after the active regeneration is normally finished, and increasing a period of active regeneration time if the set requirement is met so as to ensure that the soot in the DPF is completely burnt out.
After DPF regeneration, the solution of the total flow resistance coefficient for the second self-learning at the moment comprises the following steps:
firstly, the flow Q of the DPF during the 2 nd self-learning calculation of the total flow resistance coefficient is obtained(2)Pressure difference delta P between front and back of DPF after DPF regeneration in 2 nd self-learning of DPF(2)tot。
According to the formula Δ P(1)＝a1·μ·Q(2)+b1·ρ·Q(2) 2Calculating to obtain the pressure drop delta P generated by the total flow resistance in the first self-learning process(1)。
According to the formula Δ P(2)ash＝△P(2)tot-△P(1)Is calculated toPressure drop DeltaP generated by increment of total flow resistance from the first self-learning to the second self-learning(2)ashI.e. the ash increment after the first self-learning to the second self-learning.
According to the formula Δ a(2)，△b(2)＝f(△P(2)ash，Q(2)) Calculating to obtain total flow resistance coefficient increment delta a caused by ash increment of 2 nd self-learning of DPF(2)，△b(2)。
According to the formula a2＝a1+△a(2)And b2＝b1+△b(2)Second self-learning updated total flow resistance coefficient a2And b2。
In the next soot accumulation period, the pressure difference DeltaP from the front end and the rear end of the DPF is neededtotSubtracting the sum DeltaP of the pressure drop caused by the initial flow resistance of the DPF and the ash content in the second self-learning from the measured value(2)Obtaining a pressure difference Δ P caused only by rootsootI.e. formula Δ Psoot＝△Ptot-△P(2)At this time, Δ P(2)＝a2·μ·Q+b2·ρ·Q2Obtaining;
then, the carbon load estimation model calculates the corresponding carbon load estimation value MsootI.e. using the formula Msoot＝f(△Psoot)。
If the third self-learning total flow resistance coefficient is solved after a certain DPF is regenerated, the following steps are carried out:
firstly, the flow Q of the DPF during the third self-learning calculation of the total flow resistance coefficient is obtained(3)And pressure difference delta P between the front and the back of the DPF after DPF regeneration in third self-learning of the DPF(3)tot。
According to the formula Δ P(2)＝a2·μ·Q(3)+b2·ρ·Q(3) 2The pressure drop delta P generated by the total flow resistance in the second self-learning process is obtained through calculation(2)。
According to the formula Δ P(3)ash＝△P(3)tot-△P(2)Calculating to obtain the pressure drop delta P generated by the increment of the total flow resistance from the second self-learning to the third self-learning(3)ashI.e. the second time fromAsh increment from after learning to the third self-learning.
According to the formula Δ a(3)，△b(3)＝f(△P(3)ash，Q(3)) Calculating to obtain total flow resistance coefficient increment delta a caused by ash increment of DPF self-learning for the third time(3)，△b(3)。
According to the formula a3＝a2+△a(3)And b3＝b2+△b(3)Third self-learning updated total flow resistance coefficient a3And b3。
In the same way, the total flow resistance coefficient a after the last self-learning updating is adopted in each root periodiAnd biThe carbon loading was calculated. When the learning condition is met every time, after the soot is completely burned out by DPF regeneration, self-learning is carried out, and the total flow resistance coefficient a is updatedi+1And bi+1To calculate the carbon load for correcting the carbon load estimate in the next soot accumulation period.
In addition, the invention also provides a DPF carbon loading estimation system, which comprises: the device comprises a data acquisition module, a residual ash pressure drop calculation module and a carbon loading estimation module.
The data acquisition module is used for acquiring the pressure difference before and after the DPF when the vehicle runs; the residual ash pressure drop calculation module is used for calling the initial flow resistance coefficient and the last self-learned residual ash flow resistance coefficient, and obtaining the pressure drop generated by the initial flow resistance and the pressure drop generated by the residual ash under the current pressure difference by combining the pressure difference between the front and the rear of the DPF when the vehicle runs; and the carbon loading estimation module is used for obtaining the carbon loading of the DPF according to the pressure difference between the front and the back of the current DPF, the pressure drop generated by the initial flow resistance under the pressure difference and the pressure drop generated by the residual ash.
The system further comprises an ash self-learning module, wherein the ash self-learning module is used for acquiring the pressure difference between the front and the back of the DPF after DPF regeneration when the DPF regeneration meets the self-learning condition, and calculating the pressure drop generated by the initial flow resistance under the current pressure difference by combining the initial flow resistance coefficient so as to obtain the pressure drop generated by the residual ash after DPF regeneration; and obtaining the flow resistance coefficient of the residual ash after DPF regeneration as a self-learning flow resistance coefficient of the residual ash according to the pressure drop generated by the residual ash after DPF regeneration.
In summary, the initial flow resistance coefficient of the DPF during initial installation is obtained by the pressure difference between the front end and the rear end of the DPF during initial installation. And in the first soot accumulation period, calculating the pressure drop generated by the initial flow resistance at the moment through the detected pressure difference before and after the DPF when the vehicle runs and the initial flow resistance coefficient. The pressure drop generated by root accumulation is calculated through the pressure difference before and after the DPF runs by a vehicle and the pressure drop generated by the initial flow resistance at the corresponding moment, the carbon loading amount is calculated according to the pressure drop, and the DPF regeneration is started when the carbon loading amount reaches a threshold value.
And judging whether to carry out self-learning of the flow resistance coefficient of the residual ash or not according to the fact that the vehicle runs for a set mileage or the vehicle fuel reaches a set fuel quantity, and directly continuing to use the vehicle when the condition is not met.
When the DPF regeneration meets the self-learning condition, acquiring the pressure difference before and after the DPF regeneration, and calculating the pressure drop generated by the initial flow resistance under the current pressure difference by combining the initial flow resistance coefficient so as to obtain the pressure drop generated by the residual ash content after the DPF regeneration; and obtaining the flow resistance coefficient of the residual ash of the DPF regeneration residual ash as a self-learning flow resistance coefficient of the residual ash according to the pressure drop generated by the DPF regeneration residual ash.
In the next soot accumulation period, the calculated flow resistance coefficient of the residual ash after the DPF regeneration is called, and the pressure drop generated by the initial flow resistance and the ash in the DPF is calculated, so that the pressure drop generated by soot accumulation in the period is obtained, and the corrected estimated value of the carbon carrying capacity of the DPF can be obtained. The method considers the ash accumulation in the DPF after each regeneration, can accurately react the pressure drop generated by the ash accumulation to the next soot accumulation period, and can accurately react out regardless of the distribution form of the ash and whether the distribution form completely accords with the time law.
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 (6)

1. A DPF carbon loading estimation method, comprising the steps of:
acquiring the pressure difference before and after DPF when a vehicle runs;
calling the initial flow resistance coefficient and the last self-learned residual ash flow resistance coefficient of the DPF, and combining the pressure difference between the front and the back of the DPF when a vehicle runs to obtain the pressure drop generated by the initial flow resistance and the pressure drop generated by the residual ash under the current pressure difference, wherein the initial flow resistance coefficient is obtained, and the method comprises the following steps: acquiring the pressure difference between the front end and the rear end of the DPF during initial installation; calculating to obtain an initial flow resistance coefficient of the DPF during initial installation according to the pressure difference between the front end and the rear end of the DPF during initial installation; the initial flow resistance coefficient is calculated by a quadratic function, specifically: according to the formula Δ Pinit＝a·μ·Qinit+b·ρ·Qinit 2Determining initial flow resistance coefficients a and b, where μ is the dynamic viscosity of the exhaust gas, QinitTo measure delta PinitFlow rate of time, ρ is density of exhaust gas, Δ PinitThe pressure difference between the front end and the rear end of the DPF during initial installation;
and obtaining the pressure drop caused by the carbon loading according to the pressure difference between the front and the back of the DPF, the pressure drop generated by the initial flow resistance under the pressure difference and the pressure drop generated by the residual ash, thereby obtaining the carbon loading of the DPF.
2. The DPF carbon loading estimation method of claim 1, wherein the self-learned residual ash flow resistance coefficient is obtained according to the steps of:
when the carbon loading of the DPF reaches a set threshold value, starting DPF regeneration;
when the DPF meets the self-learning condition of the ash flow resistance coefficient, acquiring the pressure difference between the front and the back of the DPF after regeneration of the DPF, and calculating the pressure drop generated by the initial flow resistance under the current pressure difference by combining the initial flow resistance coefficient so as to obtain the pressure drop generated by residual ash after regeneration of the DPF;
according to the pressure drop generated by the regenerated residual ash of the DPF, obtaining the flow resistance coefficient of the residual ash after the regeneration of the DPF, and using the flow resistance coefficient of the residual ash after the regeneration of the DPF as a self-learned flow resistance coefficient of the residual ash to replace the last self-learned flow resistance coefficient of the residual ash;
wherein the flow resistance coefficient of the residual ash obtained by the first self-learning is a set value.
3. The DPF carbon loading estimation method of claim 2, wherein: the self-learning condition is that the vehicle runs to reach the set mileage or the fuel consumed by the vehicle reaches the set fuel amount after the last self-learning.
4. The DPF carbon loading estimation method of claim 1, wherein obtaining a self-learned residual ash flow resistivity includes the steps of:
according to formula P(i)init＝a·μ·Q(i)+b·ρ·Q(i) 2Calculating to obtain the pressure drop delta P generated by the initial flow resistance after DPF regeneration during the i-th self-learning of the DPF(i)initWherein Q is(i)Calculating the flow of the residual ash flow resistance coefficient after DPF regeneration in the ith self-learning process of the DPF;
according to the formula Δ P(i)ash＝△P(i)tot-△P(i)initCalculating to obtain the pressure drop delta P generated by residual ash content after DPF regeneration during the i-th self-learning of the DPF(i)ash，△P(i)totObtaining the pressure difference before and after the DPF is regenerated during the ith self-learning of the DPF;
according to the formula Δ a(i)，△b(i)＝f(△P(i)ash，Q(i)) Calculating to obtain the flow resistance coefficient delta a of the i-th self-learning residual ash of the DPF(i)，△b(i)。
5. Method for DPF carbon loading estimation according to any of the claims 1 or 4, characterized in that the temperature of the DPF is obtained when obtaining the pressure difference before and after the DPF, and the kinetic viscosity μ and the density p of the exhaust gas are corrected by the obtained temperature and pressure.
6. A system for implementing the DPF carbon loading estimation method of claim 1, comprising:
the data acquisition module is used for acquiring the pressure difference before and after the DPF when the vehicle runs;
residual ash pressure drop calculation module, itThe system comprises a pressure sensor, a pressure sensor and a controller, wherein the pressure sensor is used for calling an initial flow resistance coefficient and a last self-learned residual ash flow resistance coefficient of the DPF, and is used for obtaining a pressure drop generated by the initial flow resistance and a pressure drop generated by the residual ash under the current pressure difference by combining the pressure difference between the front and the back of the DPF when a vehicle runs; and is also used for obtaining the initial flow resistance coefficient, and comprises the following steps: acquiring the pressure difference between the front end and the rear end of the DPF during initial installation; calculating to obtain an initial flow resistance coefficient of the DPF during initial installation according to the pressure difference between the front end and the rear end of the DPF during initial installation; the initial flow resistance coefficient is calculated by a quadratic function, specifically: according to the formula Δ Pinit＝a·μ·Qinit+b·ρ·Qinit 2Determining initial flow resistance coefficients a and b, where μ is the dynamic viscosity of the exhaust gas, QinitTo measure delta PinitFlow rate of time, ρ is density of exhaust gas, Δ PinitThe pressure difference between the front end and the rear end of the DPF during initial installation;
and the carbon loading estimation module is used for obtaining the pressure drop caused by the carbon loading in the DPF according to the pressure difference between the front and the back of the DPF, the pressure drop generated by the initial flow resistance under the pressure difference and the pressure drop generated by the residual ash, so that the carbon loading of the DPF is obtained.
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