CN111810280A - System for DPF carbon loading capacity early warning - Google Patents
System for DPF carbon loading capacity early warning Download PDFInfo
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- CN111810280A CN111810280A CN202010340291.4A CN202010340291A CN111810280A CN 111810280 A CN111810280 A CN 111810280A CN 202010340291 A CN202010340291 A CN 202010340291A CN 111810280 A CN111810280 A CN 111810280A
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- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 title claims abstract description 142
- 229910052799 carbon Inorganic materials 0.000 title claims abstract description 142
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims abstract description 10
- 229910052760 oxygen Inorganic materials 0.000 claims abstract description 10
- 239000001301 oxygen Substances 0.000 claims abstract description 10
- 230000008929 regeneration Effects 0.000 claims description 20
- 238000011069 regeneration method Methods 0.000 claims description 20
- 238000004088 simulation Methods 0.000 claims description 16
- 238000004364 calculation method Methods 0.000 claims description 14
- 230000004913 activation Effects 0.000 claims description 5
- 238000012423 maintenance Methods 0.000 claims description 5
- 239000007789 gas Substances 0.000 claims description 4
- 230000000694 effects Effects 0.000 claims description 2
- 238000012821 model calculation Methods 0.000 claims description 2
- 230000007547 defect Effects 0.000 abstract description 3
- 238000000034 method Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
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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
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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
- F01N13/00—Exhaust or silencing apparatus characterised by constructional features ; Exhaust or silencing apparatus, or parts thereof, having pertinent characteristics not provided for in, or of interest apart from, groups F01N1/00 - F01N5/00, F01N9/00, F01N11/00
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F01—MACHINES OR ENGINES IN GENERAL; ENGINE PLANTS IN GENERAL; STEAM ENGINES
- F01N—GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR MACHINES OR ENGINES IN GENERAL; GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR INTERNAL COMBUSTION ENGINES
- F01N3/00—Exhaust or silencing apparatus having means for purifying, rendering innocuous, or otherwise treating exhaust
- F01N3/02—Exhaust or silencing apparatus having means for purifying, rendering innocuous, or otherwise treating exhaust for cooling, or for removing solid constituents of, exhaust
- F01N3/021—Exhaust or silencing apparatus having means for purifying, rendering innocuous, or otherwise treating exhaust for cooling, or for removing solid constituents of, exhaust by means of filters
- F01N3/022—Exhaust or silencing apparatus having means for purifying, rendering innocuous, or otherwise treating exhaust for cooling, or for removing solid constituents of, exhaust by means of filters characterised by specially adapted filtering structure, e.g. honeycomb, mesh or fibrous
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F01—MACHINES OR ENGINES IN GENERAL; ENGINE PLANTS IN GENERAL; STEAM ENGINES
- F01N—GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR MACHINES OR ENGINES IN GENERAL; GAS-FLOW SILENCERS OR EXHAUST APPARATUS FOR INTERNAL COMBUSTION ENGINES
- F01N3/00—Exhaust or silencing apparatus having means for purifying, rendering innocuous, or otherwise treating exhaust
- F01N3/02—Exhaust or silencing apparatus having means for purifying, rendering innocuous, or otherwise treating exhaust for cooling, or for removing solid constituents of, exhaust
- F01N3/021—Exhaust or silencing apparatus having means for purifying, rendering innocuous, or otherwise treating exhaust for cooling, or for removing solid constituents of, exhaust by means of filters
- F01N3/023—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 using means for regenerating the filters, e.g. by burning trapped particles
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
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- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Combined Controls Of Internal Combustion Engines (AREA)
Abstract
The invention provides a DPF carbon loading capacity early warning system which is characterized by comprising a controller, a vehicle-mounted T-BOX, a cloud platform and a mobile phone APP, wherein the controller and the vehicle-mounted T-BOX are installed on a vehicle; the controller collects the state information of the vehicle in real time, wherein the state information comprises the rotating speed, the torque, the oil consumption, the DPF temperature, the carbon emission of the original machine, the carbon loading capacity of the DPF, the NOx emission of the original machine and the exhaust oxygen concentration; the controller sends the acquired state information of the vehicle to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the state information of the vehicle to the cloud platform, the cloud platform predicts according to the collected state information of the vehicle, analyzes and calculates the time required by the carbon loading capacity of the DPF to reach a set early warning value, and sends the time to the mobile phone APP. The invention aims to provide a DPF carbon loading capacity early warning system aiming at the defects of the prior art, which can predict the level of future carbon loading capacity and carry out early warning on overlarge carbon loading capacity.
Description
Technical Field
The invention relates to the field of particle trapping (DPF) systems of exhaust aftertreatment systems, in particular to a DPF carbon loading amount early warning system.
Background
With increasingly stringent emission regulations, particulate emission limits are becoming lower and lower, and therefore aftertreatment systems require the addition of a DPF to reduce particulate emissions in the exhaust, the particulates being trapped by the DPF and remaining on the DPF walls. When a large carbon loading is accumulated on the DPF surface, this can result in increased exhaust backpressure, affecting economy and dynamics. When the carbon loading in the DPF is too high, the safety risk during DPF regeneration is larger, so that the carbon loading in the DPF needs to be strictly monitored, and the carbon loading is prevented from being too high through real-time early warning.
The carbon loading of the DPF is divided into three grades L1, L2 and L3, and if the carbon loading is below L1, the vehicle is indicated to be in normal running without other operations; when the carbon loading is L1-L2, the carbon loading is large, and the carbon loading needs to be regenerated to burn off; when the carbon loading is L2-L3, the carbon loading is too large, and the regeneration needs to be carried out immediately, otherwise, the speed limit of the vehicle is limited. The defects of the prior art are as follows: the carbon loading capacity of the current working condition point can be calculated only in real time, the future carbon loading capacity level cannot be predicted, and the vehicle cannot be early warned in advance to avoid speed limit and torque limit.
Disclosure of Invention
The invention aims to provide a DPF carbon loading capacity early warning system aiming at the defects of the prior art, which can predict the level of future carbon loading capacity and carry out early warning on overlarge carbon loading capacity.
The invention provides a DPF carbon loading capacity early warning system which is characterized by comprising a controller, a vehicle-mounted T-BOX, a cloud platform and a mobile phone APP, wherein the controller and the vehicle-mounted T-BOX are installed on a vehicle; the controller collects the state information of the vehicle in real time, wherein the state information comprises the rotating speed, the torque, the oil consumption, the DPF temperature, the carbon emission of the original machine, the carbon loading capacity of the DPF, the NOx emission of the original machine and the exhaust oxygen concentration; the controller sends the acquired state information of the vehicle to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the state information of the vehicle to the cloud platform, the cloud platform predicts according to the collected state information of the vehicle, analyzes and calculates the time required by the carbon loading capacity of the DPF to reach a set early warning value, and sends the time to the mobile phone APP.
In the technical scheme, the cloud platform sets the carbon loading capacity of the DPF into three levels from small to large, namely L1, L2 and L3, wherein L2 and L3 are set early warning values; when the carbon loading of the DPF is judged to be below L1, the vehicle is indicated to be running normally, and other operations are not needed; when the carbon loading capacity of the DPF is judged to be L1-L2, sending information of 'the existence of DPF regeneration requirement' to a mobile phone APP; when the carbon loading capacity of the DPF is judged to be L2-L3, sending information of 'immediately starting DPF regeneration function' to a mobile phone APP; and when the carbon loading capacity of the DPF is judged to be larger than L3, sending information of 'needing to enter a service station for maintenance, limiting the speed and the torque of the vehicle' to the mobile phone APP.
In the technical scheme, when the time required by the DPF carbon loading capacity reaching the set early warning value is less than the target time, the cloud platform calls the user through the automatic dialing system to inform the user that the regeneration is required.
In the technical scheme, the cloud platform calculates the time A required for the carbon loading capacity of the DPF to reach L2 and the time B required for the carbon loading capacity of the DPF to reach L3 by adopting the state information of the vehicle collected within a period of time t1 and obtaining a carbon loading capacity change curve through fitting a curve; where the DPF carbon loading at the start of the data for the t period is greater than L1.
In the technical scheme, the cloud platform adopts the state information of the vehicle collected within a period of time t to construct a simulation model, and calculates the time C required for the carbon loading capacity of the DPF to reach L2 and the time D required for the carbon loading capacity of the DPF to reach L3 through the simulation model; assuming that the working condition of the future operation of the vehicle is the same as the working condition in the time t, the DPF carbon loading simulation model comprises the following steps:
M＝M1+f(m1)-f(m2,m3,T)
f(m1)＝m1*Δt
f(m2,m3,T)＝k1*m2*e-E1/RT+k2*m3*e-E2/RT
m is the carbon loading capacity of the current working condition, M1 is the carbon loading capacity of the previous moment, M1 is the carbon emission of the original engine, delta T is the time difference between the two calculation moments, k1 and k2 are proportionality constants, M2 is the concentration of NOx of the original engine, E1 is the activation energy of the reaction of NOx and carbon, M3 is the oxygen concentration of exhaust gas, E2 is the activation energy of the reaction of oxygen and carbon, and T is the temperature of the DPF; r is a gas constant, 8.31J/(mol. K);
where the DPF carbon loading at the start of the data for the t period is greater than L1.
In the technical scheme, the required time obtained by fitting the curve and the required time obtained by calculating the simulation model are weighted to obtain final time E and final time F;
E＝w1*A+w2*C；F＝w1*B+w2*D；
wherein w1 and w2 are weight coefficients and are time comprehensive effects of the fitting and model calculation of the Aureobasi reference curve; e is the time required for the DFP carbon loading to reach L2; f is the time required for the DFP carbon loading to reach L3.
In the technical scheme, the cloud platform feeds back the time A and the time B to the mobile phone APP as the final calculation result of the time required by the DPF carbon loading amount to reach the set early warning value.
In the technical scheme, the cloud platform feeds back the time C and the time D to the mobile phone APP as the final calculation result of the time required by the DPF carbon loading amount to reach the set early warning value.
In the technical scheme, the cloud platform feeds back the time E and the time F to the mobile phone APP as the final calculation result of the time required by the DPF carbon loading amount to reach the set early warning value.
In the above technical solution, L1, L2, and L3 are set to corresponding values as required.
The method can predict the level of the future carbon loading amount based on the carbon loading amount of the current DPF and the working condition of the next period of time, pre-warns the excessive carbon loading amount, informs a driver when the carbon loading amount reaches the warning level, reminds the driver to select proper time and place for parking regeneration before warning, and avoids the situation that the vehicle speed limit is limited due to the excessive carbon loading amount. If the time is less than the target value, the cloud platform calls the driver through the automatic dialing system to inform the driver that the regeneration is needed. The invention generates the prompt of whether to start regeneration or whether to need maintenance according to the carbon loading of the current DPF, thereby further ensuring the vehicle using safety of users.
Drawings
FIG. 1 is a schematic block diagram of the present invention;
FIG. 2 is a carbon loading variation curve using a non-linear fit;
fig. 3 is a carbon loading variation curve calculated using a simulation model.
Detailed Description
The invention will be further described in detail with reference to the following drawings and specific examples, which are not intended to limit the invention, but are for clear understanding.
As shown in figure 1, the DPF carbon loading capacity early warning system at least comprises a controller, a vehicle-mounted T-BOX, a cloud platform and a mobile phone APP, wherein the controller and the vehicle-mounted T-BOX are both installed on a vehicle, the cloud platform is a data network platform, and the mobile phone APP is required to be installed on a mobile phone of a driver. The controller collects the rotating speed, torque, oil consumption, DPF temperature, original machine carbon emission, DPF carbon loading capacity, original machine NOx emission and exhaust oxygen concentration of the vehicle in real time. The controller sends the acquired signals to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the signals to the cloud platform, and the cloud platform can predict the carbon loading capacity of the DPF according to the collected signals.
The cloud platform sets the DPF carbon loading to three levels L1, L2, and L3, which may be manually set as a practical matter. When the carbon loading is below L1, the vehicle is indicated to be running normally, and other operations are not needed; when the carbon loading is L1-L2, the carbon loading is large, the carbon loading needs to be regenerated to burn off, and the cloud platform sends information of 'the existence of DPF regeneration requirement' to the mobile phone APP; when the carbon loading is L2-L3, the carbon loading is too large, regeneration needs to be carried out immediately, otherwise, the speed limit of the vehicle is limited, and the cloud platform sends information of 'starting DPF regeneration function immediately' to the mobile phone APP; when the carbon loading capacity is larger than L3, the carbon loading capacity is very large, regeneration can not be carried out any more, maintenance needs to be carried out when a vehicle enters a service station, the speed limit and the turn limit of the vehicle are already carried out, and the cloud platform sends information of 'maintenance needs to enter the service station and speed limit and turn limit of the vehicle' to the mobile phone APP.
The cloud platform judges that DPF carbon loading reaches the time that L2 and L3 required to send this time to cell-phone APP to remind the driver to select suitable time and place and carry out DPF regeneration, ensure not to influence the normal operating of vehicle. And when the time is less than the target value, calling the driver through an automatic dialing system of the cloud platform to inform the driver that regeneration is needed.
When the DPF carbon loading is less than L1, the cloud platform does not perform any calculations.
When the DPF carbon loading is greater than L1, the cloud platform begins to predict DPF carbon loading, with three prediction methods.
The method comprises the following steps: by utilizing data uploaded by the vehicle-mounted T-BOX, the cloud platform obtains a carbon loading change curve by fitting the data of a period of time T1, and then calculates the time A when the carbon loading reaches L2 and the time B when the carbon loading reaches L3. And informing the driver of the calculated time A and time B through a mobile phone APP, and calling the driver through an automatic dialing system of the cloud platform to inform the driver of the need of regeneration when the time A and the time B are smaller than a target value.
Fig. 2 is a graph of carbon loading variation using a non-linear fit so that time a and time B can be accurately calculated. The L1, L2 and L3 can be set to corresponding numerical values according to needs, the fitting curve can also be set to other linear and nonlinear functions, the starting point of the data of the section t1 can be selected at will, as long as the carbon loading of the DPF is larger than that of the L1, and the end point of the data of the end t1 can be selected at will.
The method 2 comprises the following steps: and (3) building a DPF carbon loading capacity simulation model on the cloud platform, calculating the carbon loading capacity in real time, calculating the carbon loading capacity through simulation by the cloud platform by adopting data of a period of time t2, and further calculating the time C when the carbon loading capacity reaches L2 and the time D when the carbon loading capacity reaches L3. And informing the driver of the calculated time C and time D through a mobile phone APP, and calling the driver through an automatic dialing system of the cloud platform to inform the driver of the need of regeneration when the time C and the time D are less than a target value.
Assuming that the working condition of the future operation of the vehicle is the same as the working condition in the time T2, the cloud platform simulates and calculates the carbon load according to T2 data uploaded by the vehicle-mounted T-BOX, and the simulation method is as follows
M＝M1+f(m1)-f(m2,m3,T)
f(m1)＝m1*Δt
f(m2,m3,T)＝k1*m2*e-E1/RT+k2*m3*e-E2/RT
M is the carbon load of the current working condition, M1 is the carbon load of the last moment, M1 is the carbon emission of the original engine, delta t is the time difference between the two calculation moments, k1 and k2 are proportionality constants, M2 is the NOx concentration of the original engine, E1Activation energy for NOx to carbon reaction, m3 exhaust oxygen concentration, E2Is the activation energy for the reaction of oxygen with carbon and T is the DPF temperature.
Fig. 3 is a graph of carbon loading variation calculated using simulation so that the time C and the time D can be accurately calculated. The L1, L2 and L3 can be set to corresponding numerical values according to needs, the fitting curve can also be set to other linear and nonlinear functions, the starting point of the data in the t2 segment can be freely selected, and the end point of the data in the t2 segment can be freely selected as long as the carbon loading of the DPF is larger than that of the L1.
The method 3 comprises the following steps: by utilizing data uploaded by the vehicle-mounted T-BOX, the cloud platform obtains a carbon load change curve by fitting the data of a period of time T3, and then calculates the time A1 when the carbon load reaches L2 and calculates the time B1 when the carbon load reaches L3. And (3) building a DPF carbon loading capacity simulation model on the cloud platform, calculating the carbon loading capacity in real time, calculating the carbon loading capacity by the cloud platform through simulation by adopting data of t3 section, further calculating the time C1 when the carbon loading capacity reaches L2, and calculating the time D1 when the carbon loading capacity reaches L3. And (4) carrying out weighting calculation on the time obtained by fitting the curve and the time obtained by simulation calculation to obtain final time E and final time F. E ═ w1 a1+ w 2C 1; f ═ w1 × B1+ w2 × D1; w1+ w2 is 1.
And informing the driver of the calculated time E and time F through a mobile phone APP, and calling the driver through an automatic dialing system of the cloud platform to inform the driver of the need of regeneration when the time E and the time F are smaller than a target value.
Details not described in this specification are within the skill of the art that are well known to those skilled in the art.
Claims (10)
1. A DPF carbon loading capacity early warning system is characterized by comprising a controller, a vehicle-mounted T-BOX, a cloud platform and a mobile phone APP, wherein the controller and the vehicle-mounted T-BOX are installed on a vehicle; the controller collects the state information of the vehicle in real time, wherein the state information comprises the rotating speed, the torque, the oil consumption, the DPF temperature, the carbon emission of the original machine, the carbon loading capacity of the DPF, the NOx emission of the original machine and the exhaust oxygen concentration; the controller sends the acquired state information of the vehicle to the vehicle-mounted T-BOX, the vehicle-mounted T-BOX sends the state information of the vehicle to the cloud platform, the cloud platform predicts according to the collected state information of the vehicle, analyzes and calculates the time required by the carbon loading capacity of the DPF to reach a set early warning value, and sends the time to the mobile phone APP.
2. The DPF carbon load warning system of claim 1, wherein the cloud platform sets DPF carbon load to three levels from small to large L1, L2 and L3, L2 and L3 being set warning values; when the carbon loading of the DPF is judged to be below L1, the vehicle is indicated to be running normally, and other operations are not needed; when the carbon loading capacity of the DPF is judged to be L1-L2, sending information of 'the existence of DPF regeneration requirement' to a mobile phone APP; when the carbon loading capacity of the DPF is judged to be L2-L3, sending information of 'immediately starting DPF regeneration function' to a mobile phone APP; and when the carbon loading capacity of the DPF is judged to be larger than L3, sending information of 'needing to enter a service station for maintenance, limiting the speed and the torque of the vehicle' to the mobile phone APP.
3. The DPF carbon loading pre-warning system of claim 2, wherein when the time required for the DPF carbon loading to reach the pre-warning value is less than the target time, the cloud platform calls a user through the automatic dialing system to inform the user that regeneration is required.
4. The DPF carbon loading early warning system according to claim 3, wherein the cloud platform calculates the time A required for the DPF carbon loading to reach L2 and the time B required for the DPF carbon loading to reach L3 by using the vehicle state information collected in a period of time t1 and obtaining a carbon loading change curve through fitting the curve; where the DPF carbon loading at the start of the data for the t period is greater than L1.
5. The DPF carbon loading early warning system according to claim 3 or 4, wherein the cloud platform adopts the collected vehicle state information in a period of time t to construct a simulation model, and calculates the time C required for the DPF carbon loading to reach L2 and the time D required for the DPF carbon loading to reach L3 through the simulation model; assuming that the working condition of the future operation of the vehicle is the same as the working condition in the time t, the DPF carbon loading simulation model comprises the following steps:
M＝M1+f(m1)-f(m2,m3,T)
f(m1)＝m1*Δt
f(m2,m3,T)＝k1*m2*e-E1/RT+k2*m3*e-E2/RT
m is the carbon loading capacity of the current working condition, M1 is the carbon loading capacity of the previous moment, M1 is the carbon emission of the original engine, delta T is the time difference between the two calculation moments, k1 and k2 are proportionality constants, M2 is the concentration of NOx of the original engine, E1 is the activation energy of the reaction of NOx and carbon, M3 is the oxygen concentration of exhaust gas, E2 is the activation energy of the reaction of oxygen and carbon, and T is the temperature of the DPF; r is a gas constant, 8.31J/(mol. K);
where the DPF carbon loading at the start of the data for the t period is greater than L1.
6. The DPF carbon loading early warning system as claimed in claim 5, wherein the final time E and F are obtained by weighting calculation of the required time obtained by fitting a curve and the required time obtained by calculation of a simulation model;
E＝w1*A+w2*C；F＝w1*B+w2*D；
wherein w1 and w2 are weight coefficients and are time comprehensive effects of the fitting and model calculation of the Aureobasi reference curve; e is the time required for the DFP carbon loading to reach L2; f is the time required for the DFP carbon loading to reach L3.
7. The DPF carbon loading early warning system as claimed in claim 4, wherein the cloud platform feeds back time A and time B to the mobile phone APP as the final calculation result of the time required for the DPF carbon loading to reach the set early warning value.
8. The DPF carbon loading early warning system as claimed in claim 5, wherein the cloud platform feeds back time C and time D to the mobile phone APP as the final calculation result of the time required for the DPF carbon loading to reach the set early warning value.
9. The DPF carbon loading early warning system as claimed in claim 6, wherein the cloud platform feeds back time E and time F to the mobile phone APP as the final calculation result of the time required for the DPF carbon loading to reach the set early warning value.
10. The DPF carbon load warning system of claim 6, wherein L1, L2, L3 are set to corresponding values as needed.
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| CN114658520A (en) * | 2020-12-23 | 2022-06-24 | 北汽福田汽车股份有限公司 | Vehicle exhaust aftertreatment method, system, storage medium and electronic equipment |
| CN114658520B (en) * | 2020-12-23 | 2023-01-13 | 北汽福田汽车股份有限公司 | Vehicle exhaust aftertreatment method, system, storage medium and electronic equipment |
| CN113741196A (en) * | 2021-09-14 | 2021-12-03 | 江苏海平面数据科技有限公司 | DPF regeneration period control optimization method based on Internet of vehicles big data |
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Application publication date: 20201023 |