Carbon loading capacity detection method and device of particle catcher, electronic equipment and medium
By performing deep regeneration and ash coefficient calculation on DPF, using zero ash and full ash model interpolation, the problem of impossible to accurately estimate the carbon load of DPF in the prior art is solved, and accurate detection and precise regeneration in any ash state is achieved .
Patent Information
- Application Number
- CN202411494918.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-24
- Publication Date
- 2025-01-07
AI Technical Summary
The prior art cannot accurately estimate the carbon load of the particle trap (DPF), especially the impact of ash on the carbon load pressure difference, resulting in a large deviation during regeneration.
By performing deep regeneration of DPF, the current pressure difference is obtained using a differential pressure sensor, and the ash coefficient is determined based on the interpolation calculation in the zero ash and all ash carbon load model, so as to accurately detect the carbon load of DPF.
It realizes accurate detection of DPF carbon load under any ash content state, provides accurate regeneration triggering basis, and reduces the deviation between regeneration and ash cleaning.
Smart Images
Figure CN119266972A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of carbon load detection of a particle trap, and in particular to a method, device, electronic equipment and medium for detecting carbon load of a particle trap. Background Art
[0002] After a long period of use, the increase in the number of particulate matter in the Diesel Particulate Filter (DPF) will lead to an increase in carrier resistance, affecting engine performance and accompanied by the risk of clogging. Therefore, the DPF needs to be cleaned in a timely manner. Combustible particulate matter can be treated by DPF regeneration, while non-combustible ash needs to be disassembled and cleaned. DPF ash is usually composed of inorganic salts, which will not oxidize at temperatures below 750 degrees Celsius. The ash is formed during the active regeneration or passive oxidation of soot in the DPF. Its components come from oil additive elements, coolant additive elements, metal oxides produced by engine wear, and corrosion (iron) oxides). Over time, the accumulation of ash in the DPF will affect the accuracy of the carbon load model's estimation of the carbon load in the DPF. Therefore, how to accurately estimate the carbon load of the DPF and accurately trigger the regeneration of the DPF has become an urgent problem to be solved.
[0003] At present, there are some inventions or methods (for diesel engine DPF ash warning, pressure differential carbon load detection, DPF regeneration, etc.) to obtain the vehicle's operating conditions based on big data, and combine the oil consumption under the universal curve obtained by bench test to determine the vehicle's oil consumption, and then further combine the ash ratio in the oil and the DPF ash accumulation rate obtained by the bench rapid ash accumulation test to obtain the vehicle's ash accumulation at this time. When the ash accumulation reaches the threshold, the user is reminded to choose an appropriate time for cleaning. Based on pressure differential carbon load detection, the influence of carbon soot is considered alone, and the influence of ash on carbon load pressure difference is not considered. This similar method is mostly open-loop ash detection, which is affected by the consistency of the engine (different engines have different fuel / oil consumption), and different carbon soot and ash forms under different working conditions, resulting in different back pressures formed by ash inside the DPF. Using a unified ash detection method, the regeneration needs and the improvement of cleaning mileage have large deviations. In addition, there is currently no clear control method for the influence and adjustment of ash on carbon load. Summary of the invention
[0004] The present invention provides a method, device, electronic device and medium for detecting the carbon load of a particle trap, so as to solve the defect in the prior art that the carbon load of a DPF cannot be accurately estimated without considering the influence of ash content, and realize accurate detection of the DPF carbon load under any ash content state, thereby providing a basis for accurately triggering the regeneration of the DPF.
[0005] The present invention provides a method for detecting the carbon load of a particle trap, comprising: Performing deep regeneration of the target particle trap to be detected to meet preset regeneration conditions; acquiring a current differential pressure of the target particulate trap after deep regeneration based on a differential pressure sensor disposed on the target particulate trap; Determining an ash coefficient of the target particle trap based on the current pressure difference and a pre-generated zero-ash carbon loading model and a full-ash carbon loading model; The target carbon loading of the target particle trap is obtained by interpolating the pre-generated zero-ash carbon loading model and the full-ash carbon loading model based on the ash coefficient.
[0006] In a possible implementation, the method further includes: A carbon loading test is conducted on the zero-ash first particle catcher, and a corresponding zero-ash carbon loading model is generated by performing flow scans at different carbon loadings; A carbon loading test is conducted on the prefabricated second particulate filter fully loaded with ash, and a corresponding full ash carbon loading model is generated by performing flow scans at different carbon loadings; The first particle trap, the second particle trap and the target particle trap are of the same model.
[0007] In a possible implementation, the method further includes: Querying the corresponding target pressure difference in the zero-ash carbon loading model and the full-ash carbon loading model based on the current pressure difference; The ash coefficient of the target particle trap is determined based on the position of the target pressure difference in the zero ash carbon loading model and the full ash carbon loading model.
[0008] In a possible implementation, the method further includes: Based on the current pressure difference, obtaining a first carbon load and a second carbon load corresponding to the current pressure difference in a pre-generated zero-ash carbon load model and a full-ash carbon load model; The sum of the products of the ash coefficient, the first carbon load and the second carbon load is used as the target carbon load of the target particle trap.
[0009] In a possible implementation, the method further includes: After the target carbon load reaches a preset regeneration standard, the regeneration operation of the target particle trap is triggered, and the carbon load of the target particle trap is continuously detected.
[0010] In a possible implementation, the method further includes: When the current pressure difference of the target particle trap is the same as the maximum pressure difference in the full ash carbon loading model, determining that the target particle trap is in a full ash state; The target particle trap in the full ash state is cleaned.
[0011] The present invention also provides a carbon load detection device for a particle trap, comprising: A regeneration module, used to perform deep regeneration of the target particle trap to be detected to meet preset regeneration conditions; an acquisition module, configured to acquire a current differential pressure of the target particle trap after deep regeneration based on a differential pressure sensor disposed on the target particle trap; A determination module, configured to determine an ash coefficient of the target particle trap based on the current pressure difference and a pre-generated zero ash carbon loading model and a full ash carbon loading model; A determination module is used to interpolate the target carbon loading of the target particle trap in the pre-generated zero-ash carbon loading model and the full-ash carbon loading model based on the ash coefficient.
[0012] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the carbon load detection method for a particle trap as described above are implemented.
[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any of the above-mentioned methods for detecting the carbon load of a particle trap.
[0014] The carbon load detection method, device, electronic device and medium of the particle trap provided by the present invention perform deep regeneration of the target particle trap to be detected to meet preset regeneration conditions; obtain the current pressure difference of the target particle trap after deep regeneration based on the pressure difference sensor set on the target particle trap; determine the ash coefficient of the target particle trap based on the current pressure difference and the pre-generated zero ash carbon load model and full ash carbon load model; interpolate the pre-generated zero ash carbon load model and full ash carbon load model based on the ash coefficient to obtain the target carbon load of the target particle trap. Compared with the problem that the carbon load of DPF cannot be accurately estimated without considering the influence of ash in the prior art, this solution can accurately detect the carbon load of DPF under any ash content state by generating a zero ash carbon load model and a full ash carbon load model and the current ash coefficient corrected carbon load prediction result, providing a basis for accurately triggering DPF regeneration. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0016] Figure 1 This is one of the flow diagrams of the carbon load detection method of the particle trap provided by the present invention.
[0017] Figure 2 This is the second flow chart of the carbon load detection method of the particle trap provided by the present invention.
[0018] Figure 3 It is a schematic diagram of the preset regeneration conditions provided by the present invention.
[0019] Figure 4 It is a schematic diagram of the zero ash and full ash carbon loading models provided by the present invention.
[0020] Figure 5 It is a structural schematic diagram of the carbon load detection device of the particle trap provided by the present invention.
[0021] Figure 6 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION
[0022] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0023] To facilitate understanding of the embodiments of the present invention, specific embodiments will be further explained below in conjunction with the accompanying drawings. The embodiments do not constitute a limitation on the embodiments of the present invention.
[0024] Figure 1 FIG. 1 is one of the flow diagrams of the carbon load detection method of the particle trap provided by the present invention, such as Figure 1 As shown, the method specifically includes: S11 . Performing deep regeneration on the target particle trap to be detected currently so as to meet preset regeneration conditions.
[0025] The embodiment of the present invention is applied to the carbon load detection of the particle trap of the vehicle. First, the target particle trap (Diesel Particulate Filter, DPF) to be detected is deeply regenerated to meet the preset regeneration conditions. DPF deep regeneration is added on the basis of DPF conventional regeneration, wherein the regeneration method may include methods based on time, mileage, carbon load, desulfurization, etc. Generally, for example, the conditions for conventional regeneration are an interval of 100h, a regeneration temperature>500℃, and a regeneration time of at least 20min; the conditions for deep regeneration are an interval of 200h, a regeneration temperature>525℃, and a regeneration time of at least 40min. DPF deep regeneration is intended to determine the ash coefficient of the current DPF.
[0026] The idea of DPF deep regeneration is essentially to deep clean the DPF to be soot-free or nearly soot-free, so that the pressure drop from DPF soot can be ignored. At this time, the DPF pressure drop is measured and the measured value is regarded as caused by ash or DPF deviation. The back pressure deviation adjustment after deep regeneration will be used in the DPF carbon loading model calculation.
[0027] Further, such as Figure 3 As shown, deep regeneration completion can be determined when multiple conditions are met, including that the total time to reach the target deep regeneration temperature meets a threshold, the percentage of time to reach the target regeneration temperature is greater than a threshold, the standard deviation of the carbon loading based on the pressure difference is stable, and the carbon loading slope change is zero.
[0028] S12: Acquire a current differential pressure of the target particulate trap after deep regeneration based on a differential pressure sensor disposed on the target particulate trap.
[0029] In order to obtain the current pressure difference of the target particle trap, a pressure difference sensor can be set on the target particle trap to directly obtain the current pressure difference of the target particle trap after deep regeneration through the pressure difference sensor. The sensor will collect data in real time and transmit the data to the vehicle's control unit (such as ECU).
[0030] S13. Determine the ash coefficient of the target particle trap based on the current pressure difference and a pre-generated zero ash carbon loading model and a full ash carbon loading model.
[0031] In the embodiment of the present invention, a carbon loading test is performed on the first particle trap with zero ash in advance, and a corresponding zero ash carbon loading model is generated by performing flow scans at different carbon loadings; a carbon loading test is performed on the pre-fabricated second particle trap with full ash load, and a corresponding full ash carbon loading model is generated by performing flow scans at different carbon loadings, such as Figure 4 As shown, different carbon loads correspond to pressure difference values. The first particle trap and the second particle trap are of the same model as the target particle trap.
[0032] Furthermore, the ash coefficient of the target particle trap may be determined based on the target pressure difference corresponding to the current pressure difference in the zero ash carbon loading model and the full ash carbon loading model.
[0033] For example, the pressure difference of the zero ash carbon loading model is 1, the pressure difference of the full ash carbon loading model is 10, and the current pressure difference is 5, then the ash coefficient is 0.5.
[0034] S14. Based on the ash coefficient, interpolate the target carbon loading of the target particle trap in the pre-generated zero-ash carbon loading model and the full-ash carbon loading model.
[0035] The first carbon loading corresponding to the zero ash carbon loading model is queried according to the current pressure difference, and the second carbon loading corresponding to the full ash carbon loading model is determined according to the current pressure difference.
[0036] Furthermore, the sum of the product of the ash coefficient and the first carbon loading and the second carbon loading is taken as the target carbon loading of the target particle trap.
[0037] For example, if the ash coefficient is 0.5, the first carbon loading is 12, and the second carbon loading is 4, then the target carbon loading is equal to the first carbon loading multiplied by the ash coefficient plus the second carbon loading multiplied by the ash coefficient, and the target carbon loading is 8.
[0038] Optionally, the current engine flow rate can also be obtained, and the target carbon load of the target particulate filter can be determined based on the engine flow rate. Engine flow rate generally refers to the amount of gas or fuel inhaled or ejected by the engine per unit time. During vehicle operation, this flow rate will be dynamically adjusted according to the engine operating conditions (such as speed, load, etc.). To determine the current engine flow rate, it is first necessary to obtain the current operating parameters of the target vehicle. These parameters include but are not limited to: Engine Speed: The number of times the engine rotates per minute, usually measured in rpm (revolutions per minute).
[0039] Throttle opening: The degree of opening of the device that controls the amount of air entering the engine.
[0040] Intake Pressure: The pressure of gas in the engine's intake manifold.
[0041] Intake Air Temperature: The temperature of gases in the engine's intake manifold.
[0042] Coolant Temperature: The temperature of the engine cooling system.
[0043] Fuel injection amount: The amount of fuel injected into the engine each time.
[0044] In order to obtain the above parameters, vehicles are usually equipped with various sensors, such as speed sensor, throttle position sensor, intake pressure sensor, intake temperature sensor, coolant temperature sensor, fuel injection amount sensor, etc. These sensors will collect data in real time and transmit the data to the vehicle's control unit (such as ECU).
[0045] After obtaining the current operating parameters, the vehicle's control unit will perform a series of calculations to determine the current engine flow.
[0046] Furthermore, the first carbon load and the second carbon load are determined in the zero ash carbon load model and the full ash carbon load model respectively according to the current engine flow, and then the target carbon load of the target particulate trap is calculated according to the ash coefficient.
[0047] The carbon load detection method of the particle trap provided by the present invention performs deep regeneration of the target particle trap to be detected to meet preset regeneration conditions; obtains the current pressure difference of the target particle trap after deep regeneration based on the pressure difference sensor set on the target particle trap; determines the ash coefficient of the target particle trap based on the current pressure difference and the pre-generated zero ash carbon load model and full ash carbon load model; and interpolates the pre-generated zero ash carbon load model and full ash carbon load model based on the ash coefficient to obtain the target carbon load of the target particle trap. Compared with the problem in the prior art that the carbon load of DPF cannot be accurately estimated without considering the influence of ash, this method, by generating a zero ash carbon load model and a full ash carbon load model and the current ash coefficient corrected carbon load prediction result, can accurately detect the DPF carbon load under any ash content state, providing a basis for accurately triggering DPF regeneration.
[0048] Figure 2 FIG. 2 is a flow chart of the carbon load detection method of the particle trap provided by the present invention. Figure 2 As shown, the method specifically includes: S21. Perform a carbon loading test on the first particle trap with zero ash content, and generate a corresponding zero ash carbon loading model by performing flow scans at different carbon loadings.
[0049] Based on the fresh DPF (zero ash first particle trap), a carbon loading test was performed, such as 0g / l, 2g / l, 5 g / l, 7 g / l, etc. The zero ash DPF carbon loading model was obtained by performing flow scans at different carbon loadings.
[0050] The specific test process includes: In the first step, the dry weight of the fresh DPF (without ash) is obtained. The engine is run at the rated point for 2 h and the DPF is weighed.
[0051] The second step is carbon loading under typical working conditions (high smoke density calibration, loading rate 1g / L / h, actual carbon loading 0, 2, 3, 5.5, 8, 9g / l, etc.).
[0052] The third step is to weigh the DPF (the recommended temperature for weighing the DPF is 160°C, and it is recommended to weigh it three times to get the average weight).
[0053] The fourth step is flow rate scanning at different carbon loading levels.
[0054] Step 5: Generate a zero-ash carbon loading model.
[0055] S22. Perform a carbon loading test on the prefabricated second particle trap fully loaded with ash, and generate a corresponding full ash carbon loading model by performing flow scans at different carbon loadings.
[0056] In the embodiment of the present invention, the step of first preparing a sample fully loaded with ash includes: In the first step, the dry weight of the fresh DPF (without ash) is obtained. The engine is run at the rated point for 2 h and the DPF is weighed.
[0057] The second step is to add fine sand to the DPF (calculated based on the density and mass of the fine sand, add approximately 100g~200g for each test).
[0058] The third step is to add POP glue into the DPF (70~80g POP glue into the DPF).
[0059] Step 4. Add some water into the DPF (water removes the POP glue in the DPF holes, add 1L of water into the DPF).
[0060] Step 5: Leave it for 24 to 48 hours and measure the ash depth.
[0061] Step 6: Trigger active regeneration (regeneration conditions are 575°C, 1~2h).
[0062] Step 7: Flow scan and weigh the DPF.
[0063] Repeat the above steps until the fine sand covers the target depth.
[0064] Among them, the mass of 500ml of sand is about 811g, so the density of sand is about 1.62g / ml. The required sand can be obtained according to the following formula.
[0065]
[0066] Where V is the volume of sand, h is the ash depth, 0.477 is the open cross-sectional area in a single module DPF, and d is the diameter of the DPF.
[0067] Furthermore, a carbon loading test is performed on the prefabricated particle collector fully loaded with ash, and the specific steps include: The first step is to obtain the basis weight of the full ash DPF (without soot), run the engine at the rated point for 2 hours, and weigh the DPF.
[0068] In the second step, the ash coefficient of the full-ash DPF is obtained by flow scanning.
[0069] The third step is carbon loading under typical working conditions (high smoke density calibration, loading rate 1g / L / h, actual carbon loading, 3, 5.5, 8, 9g / L, etc.)
[0070] Step 4: weigh the DPF (the recommended temperature for weighing the DPF is 160°C, and it is recommended to weigh it three times to get the average weight).
[0071] Step 5: Flow rate scanning at different carbon loadings.
[0072] The sixth step is to generate the carbon loading model of total ash.
[0073] S23, performing deep regeneration on the target particle trap to be detected currently so as to meet preset regeneration conditions.
[0074] The target particle trap (Diesel Particulate Filter, DPF) to be tested is deeply regenerated to meet the preset regeneration conditions. DPF deep regeneration is added on the basis of DPF regular regeneration, wherein the regeneration method may include methods based on time, mileage, carbon load, desulfurization, etc. Generally, for example, the conditions for regular regeneration are an interval of 100h, a regeneration temperature>500℃, and a regeneration time of at least 20min; the conditions for deep regeneration are an interval of 200h, a regeneration temperature>525℃, and a regeneration time of at least 40min. DPF deep regeneration is intended to determine the ash coefficient of the current DPF.
[0075] The idea of DPF deep regeneration is essentially to deep clean the DPF to be soot-free or nearly soot-free, so that the pressure drop from DPF soot can be ignored. At this time, the DPF pressure drop is measured and the measured value is regarded as caused by ash or DPF deviation. The back pressure deviation adjustment after deep regeneration will be used in the DPF carbon loading model calculation.
[0076] Further, such as Figure 3 As shown, deep regeneration completion can be determined when multiple conditions are met, including that the total time to reach the target deep regeneration temperature meets a threshold, the percentage of time to reach the target regeneration temperature is greater than a threshold, the standard deviation of the carbon loading based on the pressure difference is stable, and the carbon loading slope change is zero.
[0077] S24: Acquire a current differential pressure of the target particulate trap after deep regeneration based on a differential pressure sensor disposed on the target particulate trap.
[0078] In order to obtain the current pressure difference of the target particle trap, a pressure difference sensor can be set on the target particle trap to directly obtain the current pressure difference of the target particle trap after deep regeneration through the pressure difference sensor. The sensor will collect data in real time and transmit the data to the vehicle's control unit (such as ECU).
[0079] S25. Query the corresponding target pressure difference in the zero-ash carbon loading model and the full-ash carbon loading model based on the current pressure difference.
[0080] In the embodiment of the present invention, different carbon loads in the above zero ash carbon load model and the full ash carbon load model correspond to pressure difference values. According to the pressure difference value, the target pressure difference corresponding to the current pressure difference in the zero ash carbon load model and the full ash carbon load model can be queried.
[0081] S26. Determine the ash coefficient of the target particle trap based on the position of the target pressure difference in the zero ash carbon loading model and the full ash carbon loading model.
[0082] Furthermore, the ash coefficient of the target particle trap may be determined based on the target pressure difference corresponding to the current pressure difference in the zero ash carbon loading model and the full ash carbon loading model.
[0083] For example, the pressure difference of the zero ash carbon loading model is 1, the pressure difference of the full ash carbon loading model is 10, and the current pressure difference is 5, then the ash coefficient is 0.5.
[0084] S27. Based on the current pressure difference, obtain a first carbon loading and a second carbon loading corresponding to the current pressure difference in a pre-generated zero-ash carbon loading model and a full-ash carbon loading model.
[0085] In an embodiment of the present invention, different carbon loadings in the above-mentioned zero ash carbon loading model and the full ash carbon loading model correspond to pressure difference values. Based on the current pressure difference, the corresponding first carbon loading and second carbon loading can be determined in the zero ash carbon loading model and the full ash carbon loading model, respectively.
[0086] The difference between the first carbon loading and the second carbon loading may be considered as the current ash content of the target particle trap.
[0087] S28. The sum of the products of the ash coefficient, the first carbon load and the second carbon load is taken as the target carbon load of the target particle trap.
[0088] The first carbon loading corresponding to the zero ash carbon loading model is queried according to the current pressure difference, and the second carbon loading corresponding to the full ash carbon loading model is determined according to the current pressure difference.
[0089] Furthermore, the sum of the product of the ash coefficient and the first carbon loading and the second carbon loading is taken as the target carbon loading of the target particle trap.
[0090] For example, if the ash coefficient is 0.5, the first carbon loading is 12, and the second carbon loading is 4, then the target carbon loading is equal to the first carbon loading multiplied by the ash coefficient plus the second carbon loading multiplied by the ash coefficient, and the target carbon loading is 8.
[0091] Optionally, the current engine flow rate can also be obtained, and the target carbon load of the target particulate filter can be determined based on the engine flow rate. Engine flow rate generally refers to the amount of gas or fuel inhaled or ejected by the engine per unit time. During vehicle operation, this flow rate will be dynamically adjusted according to the engine operating conditions (such as speed, load, etc.). To determine the current engine flow rate, it is first necessary to obtain the current operating parameters of the target vehicle. These parameters include but are not limited to: Engine Speed: The number of times the engine rotates per minute, usually measured in rpm (revolutions per minute).
[0092] Throttle opening: The degree of opening of the device that controls the amount of air entering the engine.
[0093] Intake Pressure: The pressure of gas in the engine's intake manifold.
[0094] Intake Air Temperature: The temperature of gases in the engine's intake manifold.
[0095] Coolant Temperature: The temperature of the engine cooling system.
[0096] Fuel injection amount: The amount of fuel injected into the engine each time.
[0097] In order to obtain the above parameters, vehicles are usually equipped with various sensors, such as speed sensor, throttle position sensor, intake pressure sensor, intake temperature sensor, coolant temperature sensor, fuel injection amount sensor, etc. These sensors will collect data in real time and transmit the data to the vehicle's control unit (such as ECU).
[0098] After obtaining the current operating parameters, the vehicle's control unit will perform a series of calculations to determine the current engine flow.
[0099] Furthermore, the first carbon load and the second carbon load are determined in the zero ash carbon load model and the full ash carbon load model respectively according to the current engine flow, and then the target carbon load of the target particulate trap is calculated according to the ash coefficient.
[0100] As time goes by, ash accumulation in the DPF will affect the accuracy of the carbon loading model. In the embodiment of the present invention, DPF deep regeneration is added on the basis of conventional DPF regeneration (time, mileage, carbon loading, desulfurization, etc.). The DPF deep regeneration is intended to determine the current DPF ash coefficient. After deep regeneration, the current ash-corrected carbon loading is interpolated in the zero ash carbon loading and full ash carbon loading models based on the current ash coefficient.
[0101] Another benefit of ash adjustment is to compensate for the consistency deviation between DPF parts. The carbon load model calibration is based on the median level. The actual DPF back pressure has a certain deviation distribution. In order to obtain a more accurate carbon load, the model curve needs to be adjusted according to each specific system.
[0102] S29: After the target carbon load reaches a preset regeneration standard, trigger the regeneration operation of the target particle trap and continue to detect the carbon load of the target particle trap.
[0103] In an embodiment of the present invention, a regeneration standard for a target particle trap may be preset (for example, regeneration is triggered when the carbon load reaches a preset threshold), and then after the target carbon load is accurately determined as described above, it is determined whether the target carbon load reaches the preset regeneration standard. If so, the regeneration operation of the target particle trap is triggered, and the carbon load of the target particle trap continues to be detected while the vehicle continues to work.
[0104] The carbon load detection method of the particle trap provided by the present invention performs deep regeneration of the target particle trap to be detected to meet preset regeneration conditions; obtains the current pressure difference of the target particle trap after deep regeneration based on the pressure difference sensor set on the target particle trap; determines the ash coefficient of the target particle trap based on the current pressure difference and the pre-generated zero ash carbon load model and full ash carbon load model; and interpolates the pre-generated zero ash carbon load model and full ash carbon load model based on the ash coefficient to obtain the target carbon load of the target particle trap. According to this method, by generating a zero ash carbon load model and a full ash carbon load model and the current ash coefficient corrected carbon load prediction result, it is possible to accurately detect the DPF carbon load under any ash content state, providing a basis for accurately triggering DPF regeneration.
[0105] The carbon loading detection device for the particle trap provided by the present invention is described below. The carbon loading detection device for the particle trap described below and the carbon loading detection method for the particle trap described above can be referred to each other.
[0106] Figure 5 : is a structural schematic diagram of a carbon load detection device for a particle trap provided by the present invention, which specifically comprises: The regeneration module 501 is used to perform deep regeneration on the target particle trap to be detected to meet the preset regeneration conditions. For detailed description, please refer to the relevant description of the above method embodiment, which will not be repeated here.
[0107] The acquisition module 502 is used to acquire the current differential pressure of the target particle trap after deep regeneration based on the differential pressure sensor arranged on the target particle trap. For detailed description, please refer to the relevant description corresponding to the above method embodiment, which will not be repeated here.
[0108] The determination module 503 is used to determine the ash coefficient of the target particle trap based on the current pressure difference and the pre-generated zero ash carbon loading model and full ash carbon loading model. For detailed description, please refer to the relevant description corresponding to the above method embodiment, which will not be repeated here.
[0109] The determination module 503 is used to interpolate the target carbon load of the target particle trap in the pre-generated zero ash carbon load model and full ash carbon load model based on the ash coefficient. For detailed description, please refer to the relevant description corresponding to the above method embodiment, which will not be repeated here.
[0110] Figure 6 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 6 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication interface 820 and the memory 830 communicate with each other through the communication bus 840. The processor 810 may call the logic instructions in the memory 830 to execute the carbon load detection method of the particle trap, the method comprising: performing a deep regeneration of the target particle trap to be detected that meets the preset regeneration conditions; obtaining the current pressure difference of the target particle trap after deep regeneration based on the pressure difference sensor set on the target particle trap; determining the ash coefficient of the target particle trap based on the current pressure difference and the pre-generated zero ash carbon load model and the full ash carbon load model; interpolating the target carbon load of the target particle trap in the pre-generated zero ash carbon load model and the full ash carbon load model based on the ash coefficient.
[0111] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.
[0112] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the carbon loading detection method of the particle trap provided by the above-mentioned methods, the method including: performing deep regeneration on the target particle trap to be detected to meet preset regeneration conditions; obtaining the current pressure difference of the target particle trap after deep regeneration based on a pressure difference sensor provided on the target particle trap; determining the ash coefficient of the target particle trap based on the current pressure difference and a pre-generated zero ash carbon loading model and a full ash carbon loading model; and interpolating the target carbon loading of the target particle trap in the pre-generated zero ash carbon loading model and the full ash carbon loading model based on the ash coefficient.
[0113] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the above-mentioned carbon loading detection method for the particle trap provided, the method comprising: performing deep regeneration on the target particle trap to be detected to meet preset regeneration conditions; obtaining the current pressure difference of the target particle trap after deep regeneration based on a pressure difference sensor provided on the target particle trap; determining the ash coefficient of the target particle trap based on the current pressure difference and a pre-generated zero ash carbon loading model and a full ash carbon loading model; and interpolating the target carbon loading of the target particle trap in the pre-generated zero ash carbon loading model and the full ash carbon loading model based on the ash coefficient.
[0114] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.
[0115] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.
[0116] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A method for detecting carbon loading of a particle trap, characterized in that: include: Performing deep regeneration of the target particle trap to be detected to meet preset regeneration conditions; acquiring a current differential pressure of the target particulate trap after deep regeneration based on a differential pressure sensor disposed on the target particulate trap; Determining an ash coefficient of the target particle trap based on the current pressure difference and a pre-generated zero-ash carbon loading model and a full-ash carbon loading model; The target carbon loading of the target particle trap is obtained by interpolating the pre-generated zero-ash carbon loading model and the full-ash carbon loading model based on the ash coefficient.
2. The method according to claim 1, characterized in that The method further comprises: A carbon loading test is conducted on the zero-ash first particle catcher, and a corresponding zero-ash carbon loading model is generated by performing flow scans at different carbon loadings; A carbon loading test is conducted on the prefabricated second particulate filter fully loaded with ash, and a corresponding full ash carbon loading model is generated by performing flow scans at different carbon loadings; The first particle trap, the second particle trap and the target particle trap are of the same model.
3. The method according to claim 2, characterized in that The determining the ash coefficient of the target particle trap based on the current pressure difference and a pre-generated zero ash carbon loading model and a full ash carbon loading model includes: Querying the corresponding target pressure difference in the zero-ash carbon loading model and the full-ash carbon loading model based on the current pressure difference; The ash coefficient of the target particle trap is determined based on the position of the target pressure difference in the zero ash carbon loading model and the full ash carbon loading model.
4. The method according to claim 3, characterized in that The interpolating the target carbon load of the target particle trap in the pre-generated zero ash carbon load model and the full ash carbon load model based on the ash coefficient includes: Based on the current pressure difference, obtaining a first carbon load and a second carbon load corresponding to the current pressure difference in a pre-generated zero-ash carbon load model and a full-ash carbon load model; The sum of the products of the ash coefficient, the first carbon load and the second carbon load is used as the target carbon load of the target particle trap.
5. The method according to claim 4, characterized in that The method further comprises: After the target carbon load reaches a preset regeneration standard, the regeneration operation of the target particle trap is triggered, and the carbon load of the target particle trap is continuously detected.
6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: When the current pressure difference of the target particle trap is the same as the maximum pressure difference in the full ash carbon loading model, determining that the target particle trap is in a full ash state; The target particle trap in the full ash state is cleaned.
7. A carbon load detection device for a particle trap, characterized in that: include: A regeneration module, used to perform deep regeneration of the target particle trap to be detected to meet preset regeneration conditions; an acquisition module, configured to acquire a current differential pressure of the target particle trap after deep regeneration based on a differential pressure sensor disposed on the target particle trap; A determination module, configured to determine an ash coefficient of the target particle trap based on the current pressure difference and a pre-generated zero ash carbon loading model and a full ash carbon loading model; A determination module is used to interpolate the target carbon loading of the target particle trap in the pre-generated zero-ash carbon loading model and the full-ash carbon loading model based on the ash coefficient.
8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method for detecting the carbon load of the particulate trap according to any one of claims 1 to 6 are implemented.
9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for detecting the carbon load of a particulate trap according to any one of claims 1 to 6 are implemented.
10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for detecting the carbon load of a particulate trap according to any one of claims 1 to 6 is implemented.