CN113944535A - Real-time monitoring system for tail gas aftertreatment - Google Patents
Real-time monitoring system for tail gas aftertreatment Download PDFInfo
- Publication number
- CN113944535A CN113944535A CN202111157673.4A CN202111157673A CN113944535A CN 113944535 A CN113944535 A CN 113944535A CN 202111157673 A CN202111157673 A CN 202111157673A CN 113944535 A CN113944535 A CN 113944535A
- Authority
- CN
- China
- Prior art keywords
- layer
- dpf
- real
- sensor
- strategy
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 28
- 238000004891 communication Methods 0.000 claims abstract description 41
- 238000012545 processing Methods 0.000 claims abstract description 30
- 238000000034 method Methods 0.000 claims abstract description 10
- 238000012805 post-processing Methods 0.000 claims abstract description 10
- 230000002159 abnormal effect Effects 0.000 claims abstract description 5
- 230000008054 signal transmission Effects 0.000 claims abstract description 4
- 239000003054 catalyst Substances 0.000 claims description 53
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 38
- 229910052799 carbon Inorganic materials 0.000 claims description 38
- 238000003745 diagnosis Methods 0.000 claims description 37
- XSQUKJJJFZCRTK-UHFFFAOYSA-N Urea Chemical compound NC(N)=O XSQUKJJJFZCRTK-UHFFFAOYSA-N 0.000 claims description 34
- 239000004202 carbamide Substances 0.000 claims description 34
- 238000011069 regeneration method Methods 0.000 claims description 34
- 230000008929 regeneration Effects 0.000 claims description 33
- 230000032683 aging Effects 0.000 claims description 22
- 230000009467 reduction Effects 0.000 claims description 10
- 230000000903 blocking effect Effects 0.000 claims description 5
- 238000011217 control strategy Methods 0.000 claims description 4
- 239000007788 liquid Substances 0.000 claims description 2
- 230000035945 sensitivity Effects 0.000 claims description 2
- UCQFCFPECQILOL-UHFFFAOYSA-N diethyl hydrogen phosphate Chemical compound CCOP(O)(=O)OCC UCQFCFPECQILOL-UHFFFAOYSA-N 0.000 claims 12
- 238000012423 maintenance Methods 0.000 abstract description 2
- 101100170991 Caenorhabditis elegans dpf-6 gene Proteins 0.000 description 61
- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical compound N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 description 44
- 229910021529 ammonia Inorganic materials 0.000 description 20
- 238000002347 injection Methods 0.000 description 18
- 239000007924 injection Substances 0.000 description 18
- 238000011144 upstream manufacturing Methods 0.000 description 13
- 238000006722 reduction reaction Methods 0.000 description 9
- 238000006243 chemical reaction Methods 0.000 description 8
- 230000006378 damage Effects 0.000 description 7
- 239000000243 solution Substances 0.000 description 7
- 239000013618 particulate matter Substances 0.000 description 6
- 230000008859 change Effects 0.000 description 5
- 239000002245 particle Substances 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 3
- 230000003197 catalytic effect Effects 0.000 description 3
- 238000012937 correction Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000003647 oxidation Effects 0.000 description 3
- 238000007254 oxidation reaction Methods 0.000 description 3
- 230000004044 response Effects 0.000 description 3
- 230000007423 decrease Effects 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 230000007257 malfunction Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 229910000069 nitrogen hydride Inorganic materials 0.000 description 2
- 230000035939 shock Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010531 catalytic reduction reaction Methods 0.000 description 1
- 238000002485 combustion reaction Methods 0.000 description 1
- 150000001875 compounds Chemical class 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- WWHFPJVBJUJTEA-UHFFFAOYSA-N n'-[3-chloro-4,5-bis(prop-2-ynoxy)phenyl]-n-methoxymethanimidamide Chemical compound CONC=NC1=CC(Cl)=C(OCC#C)C(OCC#C)=C1 WWHFPJVBJUJTEA-UHFFFAOYSA-N 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 239000004071 soot Substances 0.000 description 1
- 239000007921 spray Substances 0.000 description 1
- 230000008646 thermal stress Effects 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Images
Classifications
-
- 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
- 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
- F01N9/00—Electrical control of exhaust gas treating 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
- F01N2900/00—Details of electrical control or of the monitoring of the exhaust gas treating apparatus
- F01N2900/04—Methods of control or diagnosing
-
- 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
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
- Y02A50/20—Air quality improvement or preservation, e.g. vehicle emission control or emission reduction by using catalytic converters
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Exhaust Gas After Treatment (AREA)
Abstract
The invention relates to a real-time monitoring system for tail gas aftertreatment, which comprises: a sensor layer: the system is responsible for collecting sensor signals and used as a decision basis of a strategy layer; a driving layer: the device is used for ensuring the stable transmission of signals in a hardware layer; a signal processing layer: processing the digital signal and the analog signal for the strategy layer to use; a CAN communication layer: ensuring that the signals are stably transmitted and received on the CAN bus; and (4) a strategy layer: the DOC, DPF and SCR decision modules adopt a model-based method to realize the recognition, feedback and decision of the state of the post-processing system according to the signals of the sensor layer and the signals processed by the signal processing layer; the wireless display screen: displaying real-time information and giving an alarm for abnormal information; and a ZigBee communication protocol. The vehicle post-processing system can prompt the state of the vehicle post-processing system in real time, such as the occurrence of a fault, and prompt a driver to perform maintenance, replacement and other processing in time aiming at the post-processing modified vehicle, particularly a vehicle without an OBD system in the third country.
Description
Technical Field
The invention relates to the field of diesel vehicle post-processing information systems, in particular to a real-time monitoring system for tail gas post-processing.
Background
The diesel engine has the characteristics of high thermal efficiency, good fuel economy, wide power coverage range, good durability and the like, can be widely applied to the fields of transportation, engineering machinery, agricultural machinery, ships and the like, is a main contributor to the emission of mobile NOx and Particulate Matters (PM), becomes one of main factors restricting the development of the diesel engine, and needs to be mainly solved.
Oxidation Catalyst (DOC), catalytic type particulate matter trap (CDPF) and Selective Catalytic Reduction (SCR) have obtained extensive application in diesel engine exhaust aftertreatment, in order to prevent that aftertreatment system from appearing blockking up in the use, damage, a series of problems such as urea sprays are abnormal, need carry out real-time supervision to aftertreatment system's performance and state, especially to present transformation vehicle, a lot of vehicles do not have the OBD system itself, the driver lacks the grasp to real-time aftertreatment information, can not in time solve the problem that processing system appears, lead to aftertreatment system to produce more serious problem, until thoroughly damaging, still can influence driving safety.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a real-time monitoring system for tail gas aftertreatment.
The purpose of the invention can be realized by the following technical scheme: an exhaust aftertreatment real-time monitoring system comprising: a sensor layer: the system is responsible for collecting sensor signals and used as a decision basis of a strategy layer;
a driving layer: the device is used for ensuring the stable transmission of signals in a hardware layer;
a signal processing layer: processing the digital signal and the analog signal for the strategy layer to use;
a CAN communication layer: ensuring that the signals are stably transmitted and received on the CAN bus;
and (4) a strategy layer: each DOC, DPF and SCR decision module realizes the identification, feedback and decision of the post-processing system state by adopting a model-based method according to the signal of the sensor layer and the signal processed by the signal processing layer;
the wireless display screen: displaying real-time information and giving an alarm for abnormal information;
and a ZigBee communication protocol.
Further, the sensors include, but are not limited to, a first NOx sensor, a first temperature sensor disposed at the exhaust pipe inlet; the second temperature sensor is arranged at the outlet of the DOC, and the differential pressure sensor is arranged at two ends of the DOC; a second NOx sensor, a third temperature sensor disposed at the SCR inlet; a third NOx sensor, NH, arranged at the SCR outlet3A sensor, a fifth temperature sensor; a liquid level sensor and a fourth temperature sensor.
Further, the driver layer includes, but is not limited to, an MCU driver, an EEPROM driver, a communication driver, and an I/O driver.
Furthermore, the signal processing layer comprises an internal signal processing module for processing signals collected by the sensor and an external signal processing module for processing signals of the CAN bus.
Further, the CAN communication layer comprises a system service communication layer, a memory service communication layer and a communication service communication layer.
Further, the strategy layer comprises a DOC strategy, a DPF strategy and an SCR strategy.
Furthermore, the DOC strategy is to provide a fault diagnosis parameter K based on the sensitivity of the differential pressure parameter to the fault, and can judge the fault degree and the fault types of breakage and blockage.
The pressure difference across the DOC increases with the degree of DOC damage, the DOC's resistance to exhaust decreases, so the pressure difference across gradually decreases.
The pressure difference at the two ends of the DOC is increased along with the DOC blockage degree, the flow area of the DOC is gradually reduced, the blocking effect on exhaust is enhanced, and the pressure difference at the two ends is increased.
Therefore, the differential pressure across the DOC is basically linearly related to the exhaust volume flow, and the differential pressure increases along with the increase of the exhaust volume flow, so that a parameter K for fault diagnosis is provided, and the calculation formula of the parameter is as follows:
in the formula: p is the pressure difference across the DOC; v is the volumetric flow through the DOC; t is the temperature of the gas.
Furthermore, the fault diagnosis parameter K draws a K value smooth curve according to the acquired temperature and pressure difference at two ends of the DOC under different operation conditions and the engine exhaust flow data, and analyzes and judges the fault type and the fault degree by utilizing the offset direction and the offset between the DOC fault characteristic parameter K of unknown different fault types and the DOC parameter K in a normal state. The deviation direction represents different fault types, the parameter K deviates upwards to indicate that a blocking fault occurs, the parameter K deviates downwards to indicate that a breakage fault occurs, the deviation amount represents the fault degree, and the larger the deviation amount is, the deeper the fault degree is.
Further, the DPF strategy carries out fault diagnosis and identification through a carbon load calculation model, wherein the fault diagnosis comprises DPF removal diagnosis, DPF overload diagnosis, DPF collection efficiency reduction diagnosis, DPF leakage fault diagnosis, DPF blocking fault diagnosis, DPF physical aging diagnosis, DPF incomplete regeneration diagnosis and DPF frequent regeneration diagnosis.
The carbon load calculation model carries out discretization summation by utilizing the loading process of the DPF, and then
As the unit time, the time period of the unit time,
the working condition of the internal engine is regarded as unchanged, the working condition, the oil consumption and the exhaust flow of the engine at the moment t are read, and the working condition, the oil consumption and the exhaust flow of the engine are determined according to the emission universal characteristic curve
The original discharge amount of particulate matter of the engine in time according toFront and back exhaust temperature and carrier basic parameters of DOC and DPF are determined2、NO2The oxidation amount of the particulate matter was determined
And finally, obtaining the carbon loading of the DPF by integrating the time according to the variation of the carbon loading of the time.
And in the DPF removal diagnosis, the change rule of the differential pressure of the pressure sensors at the front and rear positions of the trap is analyzed by reading the differential pressure of the pressure sensors arranged at the upstream and the downstream of the DPF, the differential pressure is compared, and then the obtained result is used as the diagnosis basis to diagnose whether the catalyst is removed or not.
And (3) DPF overload diagnosis, namely considering the damage of soot loading to the DPF and the bearing capacity of the DPF to thermal stress and thermal shock, evaluating the carbon loading of the DPF based on a carbon loading model of flow resistance and a carbon loading theoretical calculation model, comparing the carbon loading with a carbon loading threshold value, judging whether the DPF is overloaded or not, and determining a corresponding response measure aiming at an overload state.
And (3) diagnosing the reduction of the trapping efficiency of the DPF, wherein after the trapping efficiency of the DPF is reduced, the quantity and the quality of carbon particles are increased, the PM emission exceeds the standard, the environmental pollution is caused, the carbon loading capacity actually captured is reflected through the differential pressure change of the differential pressure sensor in a certain time under the condition of meeting the diagnosis working condition, and the carbon loading capacity generated through calculation of the carbon loading capacity model is compared to determine whether the trapping efficiency of the DPF6 is reduced.
The DPF leakage fault diagnosis method has the advantages that the DPF is easy to burn and break due to frequent factors such as thermal shock and mechanical impact in the driving process of the DPF, so that exhaust gas leaks when passing through the trap, the trapping efficiency is reduced by a certain range or even loses efficacy, and the emission is deteriorated. When the DPF leaks, the carbon loading M1 obtained based on the carbon loading calculation model is larger than the carbon loading M2 obtained based on the back check of the exhaust flow of the pressure drop before and after the DPF. Taking M2 as the actual amount of particulate matter collected, M1 is the mass that should theoretically be collected, and if (M1-M2)/M2 is greater than the threshold value, it is confirmed that a leak failure has occurred.
DPF blockage fault diagnosis, when severe blockage occurs to DPF, exhaust back pressure is too high, and combustion is badThe engine can not be started after flameout, so that the catcher and even the engine are damaged in severe cases, and the service life of the engine is influenced. By measuring the differential pressure of the differential pressure sensor 5 in real time
And from the volume flow QvPressure difference inversely checked with carbon loading M1 obtained by theoretical calculation model of carbon loading
Make a comparison of
A fault limit value coefficient is set and,
greater than 1.2
And determining whether the DPF is blocked, wherein the measured value of the pressure difference exceeds a set pressure difference high limit value, and a fault indicator lamp needs to be lightened when the measured value of the pressure difference exceeds the set pressure difference high limit value, which indicates that the DPF is blocked.
DPF physical aging diagnosis, DPF's normal aging can not lead to the filtration efficiency to reduce, can lead to DPF flow resistance grow, consequently regards the flow resistance as an ageing judgement basis, can clear away the ash content after, compares DPF's flow resistance and the exhaust resistance of original filter body, and analysis DPF ageing degree exceeds certain restriction then DPF ages seriously and needs to change.
And (3) diagnosing incomplete regeneration of the DPF, wherein the regeneration time is long or the regeneration is incomplete due to improper working conditions and temperature in the DPF regeneration stage, and after the trap is incompletely regenerated, a certain amount of residual particles exist in the trap, and the flow resistance of the residual particles is larger than that of a fresh trap which is successfully regenerated. Therefore, incomplete regeneration of the DPF can be failure diagnosed by flow resistance. Monitoring the temperature behind the DPF, judging whether the regeneration is finished or not, and reading the flow Q at the moment after the regeneration is finishedvAnd back pressure
After temperature correction, calculating the corresponding flow resistance R of the DPF after temperature correction and the maximum threshold R of the flow resistance of the DPF after complete regenerationmaxAnd comparing to judge whether the DPF has an incomplete regeneration fault.
Frequent regeneration diagnosis of the DPF is realized, and when the DPF is regenerated, incomplete regeneration occurs frequently, so that the regeneration is frequent and the oil consumption is increased rapidly. The diagnosis method is to read the oil consumption of the engine in a certain period of time, estimate the carbon load amount, and calculate the regeneration times required by theory. And comparing the read actual regeneration times in the period of time with a theoretical value to judge whether frequent regeneration occurs.
Further, the SCR strategy monitors the faults of the third temperature sensor, the fourth temperature sensor and the fifth temperature sensor, the faults of the first NOx sensor, the second NOx sensor and the third NOx sensor, the ageing of the SCR catalyst and the blockage of the urea nozzle in real time through a closed-loop control strategy of PID.
The PID closed-loop control principle is as follows:
in the formula (I), the compound is shown in the specification,
is a coefficient of proportionality that is,
in order to be the integral coefficient of the light,
is a differential coefficient.
And diagnosing the fault of the third temperature sensor, wherein when the absolute value of the difference value between the measured value of the third temperature sensor and the measured value of the fifth temperature sensor is greater than the threshold value of the difference value between the front temperature and the rear temperature of the SCR catalyst, and the absolute value of the estimated residual error of the upstream temperature of the SCR catalyst is greater than the threshold value of the estimated residual error of the upstream temperature of the SCR catalyst, the fault of the third temperature sensor is diagnosed.
And diagnosing the fault of the fifth temperature sensor, wherein when the absolute value of the difference value between the measured value of the third temperature sensor and the measured value of the fifth temperature sensor is greater than the threshold value of the difference value between the front temperature and the rear temperature of the SCR catalyst, and the absolute value of the estimated residual error of the downstream temperature of the SCR catalyst is greater than the threshold value of the estimated residual error of the downstream temperature of the SCR catalyst, the fault of the fifth temperature sensor is diagnosed.
And diagnosing a malfunction of the second NOx sensor when an absolute value of an estimated residual of the NOx concentration upstream of the SCR catalyst is greater than an estimated residual threshold of the NOx sensor upstream of the SCR catalyst.
And diagnosing a fault of the third NOx sensor when the absolute value of the estimated residual error of the NOx concentration at the downstream of the SCR catalyst is larger than the threshold value of the estimated residual error of the NOx sensor at the downstream of the SCR catalyst.
And when the upper limit of the ammonia leakage amount at the downstream of the SCR catalyst estimated by the model is less than or equal to the threshold of the ammonia leakage amount at the downstream of the SCR catalyst, the upper limit of the NOx conversion efficiency of the SCR system is less than or equal to the threshold of the NOx conversion efficiency of the SCR system, and the upper limit of the section coefficient of the urea nozzle is less than or equal to the threshold of the section coefficient of the urea nozzle, diagnosing that the urea injection amount is greatly reduced.
And when the lower boundary of the ammonia leakage amount of the downstream of the SCR catalyst estimated by the model is larger than or equal to the threshold of the ammonia leakage amount of the downstream of the SCR catalyst and the lower boundary of the ammonia coverage of the SCR catalyst is larger than or equal to the threshold of the ammonia coverage of the SCR catalyst, diagnosing that the urea injection amount is greatly increased.
And when the absolute value of the ratio of the difference value of the actual average consumption of the urea solution and the theoretical average consumption of the urea solution to the theoretical average consumption of the urea solution is more than or equal to 0.5, diagnosing that the urea injection quantity is seriously inconsistent with the fault.
And (4) aging the SCR catalyst, and diagnosing an aging fault of the SCR catalyst when the lower boundary of the ammonia leakage amount of the downstream of the SCR catalyst estimated by the model is larger than or equal to the threshold of the ammonia leakage amount of the downstream of the SCR catalyst, the upper boundary of the ammonia coverage of the SCR catalyst is smaller than or equal to the threshold of the ammonia coverage of the SCR catalyst, and the upper boundary of the NOx conversion efficiency of the SCR system is smaller than or equal to the threshold of the NOx conversion efficiency of the SCR system.
Furthermore, the wireless display screen simultaneously displays the real-time information of the DOC, the DPF and the SCR, and has an information prompt warning sound besides the display function.
When a fault occurs, the alarm sound can be sounded in time, and the alarm device is small in size, can be mounted on an instrument desk and is convenient for a driver to observe.
The ZigBee communication protocol belongs to a high-level communication protocol, and is an 802 protocol formulated based on the IEEE association in the world, the ZigBee communication protocol has the advantages of low power consumption, low cost, high capacity, high safety and the like, the ZigBee works at the rate of 20-250 kbps, the data transmission rate of a post-processing maintenance information prompting system is completely met, the transmission range is generally between 10-100 m, the transmission distance covers the length of a vehicle, the response speed of the ZigBee is high, generally, only 15ms is needed for switching from sleep to working state, only 30ms is needed for connecting nodes to enter a network, the electric energy is further saved, the ZigBee provides a three-level safety mode, and the three-level safety mode comprises safety setting, access control list prevention of illegal data acquisition and adoption of a symmetric password of a high-level encryption standard, so that the safety attribute of the ZigBee is flexibly determined.
Compared with the prior art, the invention has the following beneficial effects:
(1) the monitoring strategies comprise a DOC strategy, a DPF strategy and an SCR11 strategy, the running state and fault monitoring of the whole aftertreatment system are covered, the practicability is high, and comprehensive information prompt can be provided.
(2) The detection device based on ZigBee wireless communication has the advantages of low cost, convenience in installation and large market potential after modification.
Drawings
FIG. 1 is a diagram of an exhaust aftertreatment real-time monitoring system architecture;
FIG. 2 is a schematic view of a tail gas aftertreatment system;
FIG. 3 is a graph showing the variation trend of differential pressure across a DOC with exhaust volume flow;
FIG. 4 is a schematic diagram of DPF carbon loading calculation strategy;
fig. 5 is a schematic diagram of an SCR closed loop feedback control strategy.
Reference numerals: 1. a first NOx sensor, 2, a first temperature sensor, 3, DOC, 4, a second temperature sensor, 5, a differential pressure sensor, 6, DPF, 7, a second NOx sensor, 8, a third temperature sensor, 9, a urea pump nozzle, 10, a mixer, 11, SCR, 12, a third NOx sensor, 13, NH3 sensor, 14, a level sensor, 15, a urea tank, 16, a fourth temperature sensor, 17, a urea pump, 18, a fifth temperature sensor.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
In the drawings, structurally identical elements are represented by like reference numerals, and structurally or functionally similar elements are represented by like reference numerals throughout the several views. The size and thickness of each component shown in the drawings are arbitrarily illustrated, and the present invention is not limited to the size and thickness of each component. Parts are exaggerated in the drawing where appropriate for clarity of illustration.
Example 1:
as shown in fig. 1 and 2, an exhaust aftertreatment real-time monitoring system includes: a sensor layer: the system is responsible for collecting sensor signals and used as a decision basis of a strategy layer;
a driving layer: the device is used for ensuring the stable transmission of signals in a hardware layer;
a signal processing layer: processing the digital signal and the analog signal for the strategy layer to use;
a CAN communication layer: ensuring that the signals are stably transmitted and received on the CAN bus;
and (4) a strategy layer: each decision module of DOC3, DPF6 and SCR11 realizes the identification, feedback and decision of the post-processing system state by adopting a model-based method according to the signal of the sensor layer and the signal processed by the signal processing layer;
the wireless display screen: displaying real-time information and giving an alarm for abnormal information;
and a ZigBee communication protocol.
Preferably, the sensors include, but are not limited to, a first NOx sensor 1, a first temperature sensor 2 disposed at the inlet of the exhaust pipe; a second temperature sensor 4 disposed at the outlet of the DOC3, a differential pressure sensor 5 disposed across the DOC 3; a second NOx sensor 7, a third temperature sensor 8 arranged at the inlet of the SCR 11; a third NOx sensor 12, an NH3 sensor 13, a fifth temperature sensor 18 arranged at the outlet of the SCR 11; a level sensor 14, a fourth temperature sensor 16.
Preferably, the driver layer includes, but is not limited to, an MCU driver, an EEPROM driver, a communication driver, and an I/O driver.
Preferably, the signal processing layer comprises an internal signal processing module for processing signals collected by the sensor and an external signal processing module for processing signals of the CAN bus.
Preferably, the CAN communication layer includes a system service communication layer, a memory service communication layer and a communication service communication layer.
Preferably, the strategy layers include DOC3 strategy, DPF6 strategy and SCR11 strategy.
The CAN communication layer ensures that data of the signal processing layer CAN be stably and safely transmitted to the strategy layer, based on a CAN communication basic principle and a communication framework, the communication module stably transmits related signal data for strategy formulation to a previous layer, the system service module provides a diagnosis function for the whole system and is used for diagnosing current and historical faults occurring in the system, the memory service backs up and stores important data, and the backed-up data CAN be used when the data is lost.
As shown in fig. 3, in the present embodiment, only the fault related to the DOC3 is diagnosed, and since the differential pressure across the DOC3 is substantially linearly related to the exhaust gas volume flow rate, and the differential pressure increases with the increase of the exhaust gas volume flow rate, a calculation formula (1) of a parameter K for fault diagnosis is proposed:
in the formula: p is the pressure differential across DOC 3; v is the volumetric flow through DOC 3; t is the temperature of the gas.
According to the collected temperature and pressure difference at two ends of the DOC3 under different operating conditions and engine exhaust flow data, a K value smooth curve is drawn, and the fault type and the fault degree are analyzed and judged by utilizing the offset direction and the offset between the DOC3 fault characteristic parameter K of different unknown fault types and the DOC3 parameter K in a normal state. The deviation direction represents different fault types, the parameter K deviates upwards to indicate that a blocking fault occurs, the parameter K deviates downwards to indicate that a breakage fault occurs, the deviation amount represents the fault degree, and the larger the deviation amount is, the deeper the fault degree is.
The DOC3 diagnoses the fault degree and the fault types such as damage, blockage and the like, and wirelessly transmits the fault types to the display end through the ZigBee communication protocol, and the wireless display screen displays real-time information and is accompanied with a prompt warning sound to prompt a driver of the monitoring information of the current DOC3 system.
Example 2:
as shown in fig. 4, in this embodiment, only the fault related to the DPF6 is diagnosed, and the loading process of the DPF6 is discretized and summed based on the carbon loading calculation model, so as to obtain the result
As the unit time, the time period of the unit time,
the working condition of the internal engine is regarded as unchanged, the T moment, the working condition, the oil consumption and the exhaust flow of the engine are read, and the working condition, the oil consumption and the exhaust flow of the engine are determined according to the emission universal characteristic curve
Determining the original discharge amount of the particles of the engine in time according to the temperature difference between the first temperature sensor 2 and the second temperature sensor 4, the temperature difference between the third temperature sensor 8 and the fifth temperature sensor 18 and the basic parameters of the carrier2、NO2The oxidation amount of the particulate matter was determined
And finally, obtaining the carbon loading of the DPF by integrating the time according to the variation of the carbon loading of the time.
By reading the differential pressure between the differential pressure sensor 5 arranged upstream and downstream of the DPF6, the change law of the differential pressure between the pressure sensors at the positions before and after the trap is analyzed and compared, and then the result is used as the basis for diagnosis to determine whether the catalyst is removed.
And evaluating the carbon loading of the DPF6 based on the carbon loading model of the flow resistance and the carbon loading calculation model, comparing the carbon loading with a carbon loading threshold value, judging whether the DPF6 is overloaded or not, and determining a corresponding response measure according to the overload state.
And under the condition of meeting the diagnosis working condition, reflecting the actually captured carbon loading amount through the differential pressure change of the differential pressure sensor within a certain time, and comparing the carbon loading amounts calculated and generated through the carbon loading amount model to determine whether the trapping efficiency of the DPF6 is reduced or not.
When the DPF6 leaks, the carbon loading M1 obtained based on the carbon loading calculation model is larger than the carbon loading M2 obtained based on the back check of the exhaust flow of the pressure drop before and after the DPF 6. Taking M2 as the actual amount of particulate matter collected, M1 is the mass that should theoretically be collected, and if (M1-M2)/M2 is greater than the threshold value, it is confirmed that a leak failure has occurred.
Differential pressure measured in real time by differential pressure sensor
And from the volume flow QvPressure difference inversely checked with carbon loading M1 obtained by theoretical calculation model of carbon loading
Make a comparison of
A fault limit value coefficient is set and,
greater than 1.2
And determining whether the DPF6 is blocked, wherein the measured value of the pressure difference exceeds a set pressure difference high limit value, which indicates that the DPF6 is blocked and a fault indicator lamp needs to be lightened.
The flow resistance is used as an aging judgment basis, the flow resistance of the DPF6 can be compared with the exhaust resistance of an original filter body after ash is removed, the aging degree of the DPF6 is analyzed, and if the aging degree exceeds a certain limit, the DPF6 is seriously aged and needs to be replaced.
Monitoring the temperature of the third temperature sensor 8, judging whether the regeneration is finished or not, and reading the flow Q at the moment after the regeneration is finishedvAnd back pressure
After temperature correction, the corresponding flow resistance R and the maximum threshold R of the flow resistance of the DPF6 after complete regeneration are calculatedmaxThe comparison is made to determine whether an incomplete regeneration failure has occurred in DPF 6.
And reading the oil consumption of the engine in a certain time period, estimating the carbon loading capacity, and calculating the regeneration times required by theory. And comparing the read actual regeneration times in the period of time with a theoretical value to judge whether frequent regeneration occurs.
Faults diagnosed by the DPF6, such as DPF6 removal, DPF6 overload, DPF6 trapping efficiency reduction, DPF6 leakage, DPF6 blockage, DPF6 physical aging, DPF6 incomplete regeneration and DPF6 frequent regeneration, are wirelessly transmitted to a display end through a ZigBee communication protocol, and a wireless display screen displays real-time information and is accompanied with a prompt warning sound to prompt a driver of monitoring information of a current DPF6 system.
The rest of this example is the same as example 1.
Example 3:
as shown in fig. 5, in this embodiment, only the fault related to urea tank 15 is diagnosed, and the control principle is as follows (2) based on the closed-loop control strategy of PID:
in the formula，
Is a coefficient of proportionality that is,
in order to be the integral coefficient of the light,
is a differential coefficient.
And when the absolute value of the difference between the measured value of the third temperature sensor 8 and the measured value of the fifth temperature sensor 18 is larger than the threshold value of the temperature difference between the front and the rear of the SCR11 catalyst, and the absolute value of the estimated residual error of the temperature of the upstream of the SCR11 catalyst is larger than the threshold value of the estimated residual error of the temperature of the upstream of the SCR11 catalyst, diagnosing that the third temperature sensor 8 at the upstream of the SCR11 catalyst is in failure.
And when the absolute value of the difference value between the measured value of the third temperature sensor 8 at the upstream of the SCR11 catalyst and the measured value of the downstream temperature sensor is larger than the threshold value of the temperature difference value before and after the SCR11 catalyst, and the absolute value of the estimated residual error of the downstream temperature of the SCR11 catalyst is larger than the threshold value of the estimated residual error of the downstream temperature of the SCR11 catalyst, the fifth temperature sensor 18 of the SCR11 catalyst is diagnosed to be in fault.
When the absolute value of the estimated residual of the SCR11 catalyst upstream NOx concentration is greater than the threshold value of the estimated residual of the SCR11 catalyst upstream second NOx sensor 7, it is diagnosed that the SCR11 catalyst upstream second NOx sensor 7 is malfunctioning.
When the absolute value of the estimated residual of the SCR11 catalyst downstream NOx concentration is greater than the estimated residual threshold of the third NOx sensor 12, it is diagnosed that the third NOx sensor 12 is malfunctioning.
When the upper limit of the ammonia leakage amount of the downstream of the SCR11 catalyst estimated by the model is smaller than or equal to the threshold of the ammonia leakage amount of the downstream of the SCR11 catalyst, the upper limit of the NOx conversion efficiency of the SCR system is smaller than or equal to the threshold of the NOx conversion efficiency of the SCR11 system, and the upper limit of the section coefficient of the urea nozzle is smaller than or equal to the threshold of the section coefficient of the urea nozzle, the fault that the urea injection amount is greatly reduced is diagnosed.
When the lower boundary of the ammonia leakage amount estimated by the model and downstream of the SCR11 catalyst is larger than or equal to the threshold value of the ammonia leakage amount of the SCR11 catalyst, and the lower boundary of the ammonia coverage of the SCR11 catalyst is larger than or equal to the threshold value of the ammonia coverage of the SCR11 catalyst, a fault that the urea injection amount is greatly increased is diagnosed.
And when the absolute value of the ratio of the difference value of the actual average consumption of the urea solution to the theoretical average consumption of the urea solution is more than or equal to 0.5, diagnosing that the urea injection quantity is seriously inconsistent with the fault.
And diagnosing the aging fault of the SCR11 catalyst when the lower boundary of the ammonia leakage amount of the downstream of the SCR11 catalyst estimated by the model is larger than or equal to the threshold of the ammonia leakage amount of the downstream of the SCR11 catalyst, the upper boundary of the ammonia coverage of the SCR11 catalyst is smaller than or equal to the threshold of the ammonia coverage of the SCR11 catalyst, and the upper boundary of the NOx conversion efficiency of the SCR11 system is smaller than or equal to the threshold of the NOx conversion efficiency of the SCR11 system.
Faults of failure of the third temperature sensor 8, the fifth temperature sensor 18, the second NOx sensor 7 and the third NOx sensor 12 diagnosed by the SCR11, large reduction of urea injection quantity, large increase of urea injection quantity, serious inconsistency of urea injection quantity and aging of the SCR11 catalytic converter are wirelessly transmitted to a display end through a ZigBee communication protocol, and a wireless display screen displays real-time information and is accompanied with a prompt warning sound to prompt a driver of monitoring information of the current SCR11 system.
The rest of this example is the same as example 1.
Example 4:
as shown in fig. 3 and 4, in the present embodiment, the DOC3 and the DPF6 are diagnosed with respect to a failure.
The DOC3 diagnoses faults such as fault degree, damage, blockage and the like, the faults such as DPF6 removal, DPF6 overload, DPF6 capture efficiency reduction, DPF6 leakage, DPF6 blockage, DPF6 physical aging, DPF6 incomplete regeneration and DPF6 frequent regeneration and the like diagnosed by the DPF6 wirelessly transmit to a display end through a ZigBee communication protocol, and a wireless display screen displays real-time information and is accompanied with a prompt warning sound to prompt a driver of monitoring information of the current DOC3 and DPF6 systems.
The rest of this example is the same as examples 1 and 2.
Example 5:
as shown in fig. 3 and 5, in the present embodiment, the DOC3 and SCR11 related faults are diagnosed.
The DOC3 diagnoses the fault degree, damage, blockage and other faults, the third temperature sensor 8, the fifth temperature sensor 18, the second NOx sensor 7 and the third NOx sensor 12 diagnosed by the SCR11 fail, the urea injection quantity is greatly reduced, the urea injection quantity is greatly increased, the urea injection quantity is seriously inconsistent with the aging of the SCR11 catalytic converter, the faults are wirelessly transmitted to a display end through a ZigBee communication protocol, and the wireless display screen displays real-time information and is accompanied with a prompt warning sound to prompt a driver of monitoring information of the current DOC3 and SCR11 systems.
The rest of this example is the same as examples 1 and 3.
Example 6:
as shown in fig. 4 and 5, in the present embodiment, the diagnosis of the malfunction relating to the DPF6 and the SCR11 is performed.
The faults of DPF6 removal, DPF6 overload, DPF6 collection efficiency reduction, DPF6 leakage, DPF6 blockage, DPF6 physical aging, DPF6 incomplete regeneration, DPF6 frequent regeneration and the like diagnosed by the DPF6, faults of failure of the third temperature sensor 8, the fifth temperature sensor 18, the second NOx sensor 7 and the third NOx sensor 12 diagnosed by the SCR11, urea injection quantity reduction, urea injection quantity increase, serious urea injection quantity inconsistency, SCR11 catalyst aging and the like are wirelessly transmitted to a display end through a ZigBee communication protocol, and a wireless display screen displays real-time information and is accompanied with warning sounds to prompt a driver of monitoring information of the current DPF6 and SCR11 systems.
The rest of this example is the same as examples 2 and 3.
Example 7:
as shown in fig. 3, 4 and 5, in the present embodiment, the DOC3, DPF6 and SCR11 related failures are diagnosed.
The fault degree, damage, blockage and other faults diagnosed by the DOC3, faults diagnosed by the DPF6, such as DPF6 removal, DPF6 overload, DPF6 collection efficiency reduction, DPF6 leakage, DPF6 blockage, DPF6 physical aging, DPF6 incomplete regeneration and DPF6 frequent regeneration, faults diagnosed by the SCR11, such as the failure of the third temperature sensor 8, the fifth temperature sensor 18, the second NOx sensor 7 and the third NOx sensor 12, the great reduction of urea injection amount, the great increase of urea injection amount, the serious inconsistency of urea injection amount and SCR11 catalyst aging, are wirelessly transmitted to a display end through a ZigBee communication protocol, and the wireless display screen displays real-time information and prompts warning sounds to prompt a driver to monitor information of the current DOC3, DPF6 and SCR11 systems.
The remainder of this example is the same as examples 1, 2 and 3.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (10)
1. An exhaust aftertreatment real-time monitoring system, comprising:
a sensor layer: the system is responsible for collecting sensor signals and used as a decision basis of a strategy layer;
a driving layer: the device is used for ensuring the stable transmission of signals in a hardware layer;
a signal processing layer: processing the digital signal and the analog signal for the strategy layer to use;
a CAN communication layer: ensuring that the signals are stably transmitted and received on the CAN bus;
and (4) a strategy layer: each decision module of the DOC (3), the DPF (6) and the SCR (11) realizes the identification, feedback and decision of the post-processing system state by adopting a model-based method according to the signal of the sensor layer and the signal processed by the signal processing layer;
the wireless display screen: displaying real-time information and giving an alarm for abnormal information;
and a ZigBee communication protocol.
2. An exhaust aftertreatment real-time monitoring system according to claim 1, characterized in that the sensors include but are not limited to a first NOx sensor (1), a first temperature sensor (2) arranged at the exhaust pipe inlet; a second temperature sensor (4) arranged at the outlet of the DOC (3), and a differential pressure sensor (5) arranged at two ends of the DOC (3); a second NOx sensor (7), a third temperature sensor (8) arranged at the inlet of the SCR (11); a third NOx sensor (12), NH arranged at the outlet of the SCR (11)3A sensor (13), a fifth temperature sensor (18); a liquid level sensor (14) and a fourth temperature sensor (16).
3. The real-time exhaust aftertreatment monitoring system according to claim 1, wherein the driver layer includes but is not limited to MCU driver, EEPROM driver, communication driver and I/O driver.
4. The real-time monitoring system for exhaust gas aftertreatment according to claim 1, wherein the signal processing layer comprises an internal signal processing module for processing signals collected by the sensor and an external signal processing module for processing signals of the CAN bus.
5. The real-time monitoring system for exhaust gas aftertreatment according to claim 1, wherein the CAN communication layer comprises a system service communication layer, a memory service communication layer and a communication service communication layer.
6. An exhaust aftertreatment real-time monitoring system according to claim 1, characterized in that the strategy layer comprises a DOC (3) strategy, a DPF (6) strategy and a SCR (11) strategy.
7. The exhaust aftertreatment real-time monitoring system according to claim 6, wherein the DOC (3) strategy provides a fault diagnosis parameter K based on the sensitivity of the differential pressure parameter to the fault, and can judge the fault degree and the fault type of breakage and blockage.
8. The real-time exhaust gas aftertreatment monitoring system according to claim 6, wherein the DPF (6) strategy performs fault diagnosis and identification through a carbon load calculation model, and comprises DPF (6) removal diagnosis, DPF (6) overload diagnosis, DPF (6) trapping efficiency reduction diagnosis, DPF (6) leakage fault diagnosis, DPF (6) blocking fault diagnosis, DPF (6) physical aging diagnosis, DPF (6) incomplete regeneration diagnosis and DPF (6) frequent regeneration diagnosis.
9. An exhaust gas aftertreatment real-time monitoring system according to claim 6, characterized in that the SCR (11) strategy monitors in real time the failure of the third temperature sensor (8), the fourth temperature sensor (16), the fifth temperature sensor (18), the failure of the first NOx sensor, the second NOx sensor (7), the third NOx sensor (12), the aging of the SCR (11) catalyst and the blockage of the urea nozzle (9) by means of a closed loop control strategy of PID.
10. The system for monitoring the real-time after-treatment of the tail gas as claimed in claim 1, wherein the wireless display screen simultaneously displays the real-time information of the DOC (3), the DPF (6) and the SCR (11) and is provided with an information prompt warning sound.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111157673.4A CN113944535A (en) | 2021-09-30 | 2021-09-30 | Real-time monitoring system for tail gas aftertreatment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111157673.4A CN113944535A (en) | 2021-09-30 | 2021-09-30 | Real-time monitoring system for tail gas aftertreatment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113944535A true CN113944535A (en) | 2022-01-18 |
Family
ID=79329082
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111157673.4A Pending CN113944535A (en) | 2021-09-30 | 2021-09-30 | Real-time monitoring system for tail gas aftertreatment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113944535A (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20070095857A (en) * | 2007-09-06 | 2007-10-01 | (주)지맥 | System and method for diagnosing trouble of diesel particulate filter |
| JP2012189007A (en) * | 2011-03-10 | 2012-10-04 | Honda Motor Co Ltd | Exhaust emission control system for internal combustion engine |
| CN106812577A (en) * | 2017-03-30 | 2017-06-09 | 无锡威孚力达催化净化器有限责任公司 | Scr system control device |
| CN207261081U (en) * | 2017-09-21 | 2018-04-20 | 中国汽车技术研究中心 | The on-line automatic warning system of grain catcher failure |
| KR101865915B1 (en) * | 2016-12-07 | 2018-06-11 | 현대오트론 주식회사 | Diagnosis method of catalyst and estimation method of incorrect urea for scr system |
| CN108425730A (en) * | 2018-02-27 | 2018-08-21 | 西南交通大学 | The OBD of diesel SCR after-treatment system is diagnosed and processing method |
| CN110206623A (en) * | 2019-06-25 | 2019-09-06 | 三河市科达科技有限公司 | A kind of motor exhaust post-processing control system and control method |
| CN110617129A (en) * | 2019-09-20 | 2019-12-27 | 深圳市劲力超科技有限公司 | Fixed source steamer waste gas purification monitored control system |
| CN112727617A (en) * | 2019-10-14 | 2021-04-30 | 康明斯有限公司 | System and method for predictive control of an exhaust aftertreatment system |
| CN113417725A (en) * | 2021-07-23 | 2021-09-21 | 保蓝行(福建)环保技术研究院有限责任公司 | Tail gas emission control system |
-
2021
- 2021-09-30 CN CN202111157673.4A patent/CN113944535A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20070095857A (en) * | 2007-09-06 | 2007-10-01 | (주)지맥 | System and method for diagnosing trouble of diesel particulate filter |
| JP2012189007A (en) * | 2011-03-10 | 2012-10-04 | Honda Motor Co Ltd | Exhaust emission control system for internal combustion engine |
| KR101865915B1 (en) * | 2016-12-07 | 2018-06-11 | 현대오트론 주식회사 | Diagnosis method of catalyst and estimation method of incorrect urea for scr system |
| CN106812577A (en) * | 2017-03-30 | 2017-06-09 | 无锡威孚力达催化净化器有限责任公司 | Scr system control device |
| CN207261081U (en) * | 2017-09-21 | 2018-04-20 | 中国汽车技术研究中心 | The on-line automatic warning system of grain catcher failure |
| CN108425730A (en) * | 2018-02-27 | 2018-08-21 | 西南交通大学 | The OBD of diesel SCR after-treatment system is diagnosed and processing method |
| CN110206623A (en) * | 2019-06-25 | 2019-09-06 | 三河市科达科技有限公司 | A kind of motor exhaust post-processing control system and control method |
| CN110617129A (en) * | 2019-09-20 | 2019-12-27 | 深圳市劲力超科技有限公司 | Fixed source steamer waste gas purification monitored control system |
| CN112727617A (en) * | 2019-10-14 | 2021-04-30 | 康明斯有限公司 | System and method for predictive control of an exhaust aftertreatment system |
| CN113417725A (en) * | 2021-07-23 | 2021-09-21 | 保蓝行(福建)环保技术研究院有限责任公司 | Tail gas emission control system |
Non-Patent Citations (2)
| Title |
|---|
| 章慧敏: "重型柴油机DPF的OBD故障诊断策略研究", 中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑, no. 2017, 15 September 2017 (2017-09-15), pages 22 - 44 * |
| 荀启峰: "基于ZigBee的车载尾气实时监测系统设计", 软件工程, no. 2013, 31 October 2013 (2013-10-31), pages 17 - 19 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP3433476B1 (en) | Radio frequency process sensing, control, and particulate matter diagnostics system | |
| US9273587B2 (en) | Method, system, and apparatus for diagnosing an exhaust aftertreatment component | |
| US10799826B2 (en) | Radio frequency process sensing, control, and diagnostics network and system | |
| CN102667090B (en) | Apparatus, system, and method for estimating deterioration of a NOX sensor response rate | |
| WO2011118250A1 (en) | Reproduction control device, reproduction control method, and reproduction support system for dpf | |
| CN113790094B (en) | Method, device, vehicle and medium for determining sulfur poisoning of aftertreatment system | |
| CN110863890A (en) | Method for remotely diagnosing reasonability of urea consumption of diesel vehicle SCR system | |
| EP3222832B1 (en) | Device for diagnosing failure in exhaust pipe fuel injector | |
| CN114087058B (en) | Method and system for detecting DPF overload | |
| Dadam et al. | A Unique Application of Gasoline Particulate Filter Pressure Sensing Diagnostics | |
| JP6148553B2 (en) | Exhaust brake failure diagnosis device | |
| US20240318585A1 (en) | Systems and methods for diagnosing component failure | |
| CN110671178B (en) | Exhaust temperature sensor diagnosis method based on exhaust temperature characteristics of different torque sections | |
| US12055114B2 (en) | Systems and methods for selective catalytic reduction (scr) multipoint diagnosis | |
| CN113514169B (en) | Credibility fault diagnosis method for downstream temperature sensor of SCR (selective catalytic reduction) system | |
| CN113944535A (en) | Real-time monitoring system for tail gas aftertreatment | |
| CN111706424A (en) | Method for diagnosing faults of post-processing structure and post-processing structure | |
| CN111764991A (en) | Diagnostic device and diagnostic method for removing fault of particulate matter trap | |
| CN112012818B (en) | Exhaust system, power system, and failure diagnosis method | |
| KR20230030091A (en) | Emission Reduction System for Operating Vehicles | |
| KR101551083B1 (en) | Mehtod for monitoring fail of DPF system | |
| US11053835B2 (en) | Method and system for assessing engine faults | |
| CN114810303B (en) | Method and system for detecting air leakage of rear air intake pipe of DPF pressure difference sensor | |
| CN114893279B (en) | SDPF ash load detection method and equipment, SDPF ash load monitoring method and device and vehicle | |
| CN118167464A (en) | DPF fault detection method, device and engine |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |