Dpf fault diagnosis method, device, equipment and medium

Abstract

Embodiments of the present application provide a DPF fault diagnosis method, device, equipment and medium, and relate to the technical field of vehicles. The method comprises: acquiring a state parameter of a diesel particulate filter (DPF); wherein the state parameter comprises a DPF upstream pressure value and a DPF downstream pressure value; if the state parameter satisfies a corresponding abnormal state judgment condition, it is determined that the DPF is in an abnormal state; the DPF upstream pressure value and the DPF downstream pressure value corresponding to the DPF in the abnormal state are respectively subjected to integral processing to obtain a pressure cumulative value of the DPF; and based on the pressure cumulative value of the DPF, a DPF pressure value and a preset pressure threshold, the fault type of the DPF is determined. The method of the present application effectively solves the problem of insufficient accuracy of DPF fault diagnosis in the related art.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a DPF fault diagnosis method, apparatus, equipment and medium. Background Technology

[0002] DPF, or Diesel Particulate Filter, is widely used in diesel engines. Its main function is to reduce particulate emissions to meet stringent emission regulations. The proper functioning of the DPF is crucial for ensuring efficient engine operation and compliance. Therefore, fault diagnosis of the DPF, to quickly identify the possible causes of failure when abnormalities are detected, and to carry out timely repairs, is essential for the normal operation of the DPF.

[0003] In related technologies, DPF fault diagnosis mainly relies on the differential pressure measurement across the DPF to determine the efficiency and blockage of the DPF. However, when there is leakage in the upstream or downstream pipelines or differential pressure intake pipe, the differential pressure measurement value may be inaccurate, leading to false alarms or missed alarms. Summary of the Invention

[0004] This application provides a DPF fault diagnosis method, apparatus, equipment, and medium to address the problem of insufficient accuracy in DPF fault diagnosis in related technologies.

[0005] Firstly, this application provides a DPF fault diagnosis method, the method comprising:

[0006] Obtain the status parameters of the diesel particulate filter (DPF); the status parameters include the upstream pressure value and the downstream pressure value of the DPF.

[0007] If the status parameters meet the corresponding abnormal state determination conditions, then the DPF is determined to be in an abnormal state.

[0008] The upstream and downstream pressure values ​​of the DPF corresponding to the DPF in an abnormal state are integrated to obtain the cumulative pressure value of the DPF.

[0009] Based on the cumulative DPF pressure value, the DPF pressure value, and the preset pressure threshold, the type of DPF failure is determined.

[0010] In one embodiment of this disclosure, the abnormal state determination condition is determined as follows: a DPF with structural abnormality is obtained, and the abnormal state parameter corresponding to the DPF with structural abnormality is measured. The DPF with structural abnormality includes a DPF with a leak point in the pipeline. The value of the abnormal state parameter is used as the threshold of the abnormal state determination condition, and the abnormal state determination condition is determined based on the threshold corresponding to the abnormal state parameter.

[0011] In one embodiment of this disclosure, the DPF with structural anomalies is obtained based on simulation, or the DPF with structural anomalies is a DPF sample containing a leak point; measuring the abnormal state parameters corresponding to the DPF with structural anomalies includes: obtaining the abnormal state parameters based on the simulation results, or obtaining the abnormal state parameters based on the measurement of the DPF sample containing the leak point.

[0012] In one embodiment of this disclosure, the abnormal state parameters include the exhaust flow rate change rate, the exhaust flow rate, and the corresponding exhaust temperature range.

[0013] In one embodiment of this disclosure, the fault type of the DPF is determined based on the cumulative pressure value of the DPF, the DPF pressure value, and a preset pressure threshold. This includes: if the cumulative pressure value upstream or downstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition, the fault type of the DPF is determined to be a leak; if the cumulative pressure value upstream or downstream of the DPF is greater than the cumulative value of the corresponding threshold in the abnormal state determination condition, the pressure difference between the upstream and downstream of the DPF is determined; if the pressure difference is less than the corresponding minimum pressure difference threshold, the fault type is determined to be low DPF efficiency; if the pressure difference is greater than the corresponding maximum pressure difference threshold, the fault type is determined to be DPF blockage.

[0014] In one embodiment of this disclosure, if the cumulative pressure value upstream or downstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition, the fault type of the DPF is determined to be a leak point, including: if the cumulative pressure value upstream of the DPF is less than the cumulative value of the corresponding upstream threshold in the abnormal state determination condition, the fault type of the DPF is determined to be a leak point upstream of the DPF; if the cumulative pressure value downstream of the DPF is less than the cumulative value of the corresponding downstream threshold in the abnormal state determination condition, the fault type of the DPF is determined to be a leak point downstream of the DPF.

[0015] In one embodiment of this disclosure, obtaining the state parameters of a diesel particulate filter (DPF) includes: determining the upstream pressure value and the downstream pressure value of the DPF based on a pre-configured dual-membrane differential pressure sensor.

[0016] Secondly, embodiments of this disclosure provide a DPF fault diagnosis device, which includes:

[0017] The acquisition module is used to acquire the status parameters of the diesel particulate filter (DPF), wherein the status parameters include the upstream pressure value and the downstream pressure value of the DPF.

[0018] The judgment module is used to determine that the DPF is in an abnormal state if the state parameter meets the corresponding abnormal state judgment condition.

[0019] The calculation module is used to integrate the upstream pressure value and downstream pressure value of the DPF corresponding to the DPF in an abnormal state to obtain the cumulative pressure value of the DPF.

[0020] The determination module is used to determine the fault type of the DPF based on the cumulative DPF pressure value, the DPF pressure value, and a preset pressure threshold.

[0021] Optionally, the judgment module is specifically used to determine the abnormal state judgment conditions in the following way: obtain the DPF with structural abnormality, and measure the abnormal state parameters corresponding to the DPF with structural abnormality, including DPF with leakage point in pipeline; use the value of the abnormal state parameter as the threshold of the abnormal state judgment condition, and determine the abnormal state judgment condition based on the threshold corresponding to the abnormal state parameter.

[0022] Optionally, the judgment module is specifically used to: if the DPF with structural anomalies is obtained based on simulation, or if the DPF with structural anomalies is a DPF sample containing leakage points; obtain abnormal state parameters based on the simulation results, or obtain abnormal state parameters based on the measurement of the DPF sample containing leakage points.

[0023] Optionally, the judgment module specifically includes abnormal state parameters such as exhaust flow rate change rate, exhaust flow rate, and corresponding exhaust temperature range.

[0024] Optionally, the determining module is specifically used to: determine the DPF fault type as having a leak if the cumulative pressure value upstream or downstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition; determine the corresponding pressure difference between the upstream and downstream of the DPF if the cumulative pressure value upstream or downstream of the DPF is greater than the cumulative value of the corresponding threshold in the abnormal state determination condition; determine the fault type as low DPF efficiency if the pressure difference is less than the corresponding minimum pressure difference threshold; and determine the fault type as DPF blockage if the pressure difference is greater than the corresponding maximum pressure difference threshold.

[0025] Optionally, the determining module is specifically used to determine the fault type of the DPF as an upstream leak if the cumulative pressure value upstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition; and to determine the fault type of the DPF as a downstream leak if the cumulative pressure value downstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition.

[0026] Optionally, the acquisition module specifically includes determining the upstream pressure value and the downstream pressure value of the DPF based on a pre-configured dual-membrane differential pressure sensor.

[0027] Thirdly, embodiments of this application provide a control device, including: a memory and a processor;

[0028] The memory stores the instructions that the computer executes;

[0029] The processor executes computer execution instructions stored in memory, causing the processor to perform a DPF fault diagnosis method as described in the first aspect of this disclosure.

[0030] Fourthly, embodiments of this disclosure also provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the DPF fault diagnosis method as described in the first aspect of this disclosure.

[0031] Fifthly, embodiments of this disclosure also provide a computer program product comprising computer-executable instructions, which, when executed by a processor, are used to implement the DPF fault diagnosis method as described in the first aspect of this disclosure.

[0032] The DPF fault diagnosis method, apparatus, equipment, and medium provided in this disclosure improve the accuracy of DPF fault diagnosis by acquiring upstream and downstream pressure values ​​of the DPF and performing pressure integration processing when abnormal state judgment conditions are met. Through comprehensive analysis of cumulative pressure values, pressure values, and preset pressure thresholds, the types of DPF faults can be effectively identified. This not only allows for rapid location of fault causes but also reduces false alarms or missed alarms caused by pipeline leaks, improving the operational reliability and maintenance efficiency of the DPF and ensuring the efficient operation and compliance of the engine. Attached Figure Description

[0033] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0034] Figure 1 This is an application scenario diagram of the DPF fault diagnosis method, apparatus, equipment and medium provided in the embodiments of this disclosure;

[0035] Figure 2 A flowchart of a DPF fault diagnosis method provided in one embodiment of this disclosure;

[0036] Figure 3 A flowchart of a DPF fault diagnosis method provided in yet another embodiment of this disclosure;

[0037] Figure 4 A schematic diagram of the structure of a DPF fault diagnosis device provided in yet another embodiment of this disclosure;

[0038] Figure 5This is a schematic diagram of the structure of a control device provided in yet another embodiment of this disclosure.

[0039] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0040] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0041] Diesel particulate filters (DPFs) are widely used devices in diesel engines, designed to reduce particulate emissions to meet stringent emission regulations. Proper DPF operation is crucial for ensuring efficient engine operation and compliance. However, current technology for DPF fault diagnosis primarily relies on differential pressure measurements across the DPF to determine its efficiency and blockage status. This method can lead to inaccurate differential pressure measurements when there are leaks in the upstream or downstream lines or the differential pressure intake, resulting in false alarms or missed alarms, affecting the normal function of the DPF and potentially causing it to fail due to overload.

[0042] In related technologies, the ability to identify DPF functions is insufficient, which can easily lead to misjudgments due to pipeline leaks, thereby affecting the operational reliability and maintenance efficiency of the DPF, resulting in the engine not operating efficiently and easily affecting its compliance.

[0043] The diesel particulate filter (DPF) fault diagnosis method, apparatus, equipment, and medium provided in this application address the problem of inaccurate DPF fault diagnosis by acquiring the upstream and downstream pressure values ​​of the DPF and performing pressure integration processing when abnormal state judgment conditions are met. Through comprehensive analysis of cumulative pressure values, pressure values, and preset pressure thresholds, the types of DPF faults are effectively identified, improving the accuracy and reliability of fault diagnosis and ensuring the normal operation of the DPF and the high efficiency and compliance of the engine.

[0044] Figure 1 This application provides a schematic diagram illustrating the application scenarios of the DPF fault diagnosis method, apparatus, equipment, and medium. Figure 1 As shown, in DPF fault diagnosis, the control unit 100 acquires the status parameters of DPF110 and determines the specific fault type based on the status parameters.

[0045] It should be noted that, Figure 1 The scenario shown includes control units and DPFs, which are only used as examples of one or a specific number of units. However, this disclosure is not limited to this. In other words, the number of control units and DPFs can be arbitrary.

[0046] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0047] Figure 2 This is a flowchart illustrating the DPF fault diagnosis method provided in the embodiments of this application. The following is a summary of the process. Figure 2 The main process of DPF fault diagnosis method is explained below:

[0048] S201. Obtain the status parameters of the diesel particulate filter (DPF).

[0049] The state parameters include the upstream pressure value of the DPF and the downstream pressure value of the DPF.

[0050] Specifically, the execution subject of this embodiment is a control module or control unit capable of monitoring the status of the diesel vehicle's DPF. It may be a control chip of a vehicle containing a diesel engine, or a server corresponding to a vehicle containing a diesel engine. For ease of explanation, it will be referred to as the control unit below.

[0051] Obtaining the DPF's status parameters is a fundamental step in the entire fault diagnosis process. These status parameters include the upstream and downstream pressure values ​​of the DPF, which are measured in real time by sensors installed in the DPF system.

[0052] The accuracy and real-time nature of the data are ensured by measuring the pressure values ​​upstream and downstream of the DPF separately.

[0053] S202. If the state parameters meet the corresponding abnormal state determination conditions, then the DPF is determined to be in an abnormal state.

[0054] Specifically, after obtaining the DPF status parameters, the next step is to determine whether these parameters meet the abnormal state determination conditions.

[0055] The abnormal state determination criteria are obtained through experiments or simulations of DPFs with structural anomalies.

[0056] Specifically, the parameter thresholds for abnormal states can be determined by artificially creating leaks on the DPF sample or by simulating the pressure changes of the DPF under different fault conditions using simulation software.

[0057] These thresholds serve as the benchmark for determining whether the DPF is in an abnormal state. Once the state parameters exceed the preset abnormal state determination conditions, the control unit will mark the DPF as being in an abnormal state.

[0058] In actual calculations, it is also necessary to take into account various operating conditions that may occur during the operation of the diesel engine in order to avoid misjudgment or omission. For example, the parameter thresholds may be different under different ambient temperatures.

[0059] In some embodiments, the control unit combines multiple parameters for judgment, such as determining an abnormal state only when the thresholds corresponding to the exhaust volume and flow rate change rate are met simultaneously, thereby improving the accuracy of abnormal state determination.

[0060] S203. Integrate the upstream and downstream pressure values ​​of the DPF corresponding to the DPF in an abnormal state to obtain the cumulative pressure value of the DPF.

[0061] Specifically, once the DPF is determined to be in an abnormal state, the control unit will integrate the pressure values ​​upstream and downstream to obtain the cumulative pressure value.

[0062] The purpose of integral processing is to more accurately reflect the state of DPF over a period of time by accumulating pressure changes, especially under dynamic operating conditions.

[0063] By taking into account the time and magnitude of pressure changes, the pressure characteristics of the DPF can be accurately captured over different time periods, thereby accurately determining whether there are leaks or other issues.

[0064] During the integral processing, the control unit can also perform data smoothing and filtering to remove noise and outliers. This improves the accuracy of the accumulated pressure value, thus providing reliable data support for subsequent fault diagnosis.

[0065] In some embodiments, the control unit can dynamically adjust the integration time window and frequency according to different operating conditions and environmental conditions to adapt to different diagnostic needs.

[0066] S204. Based on the cumulative DPF pressure value, the DPF pressure value, and the preset pressure threshold, determine the type of DPF fault.

[0067] Specifically, the control unit can determine the type of DPF fault based on the accumulated pressure value, the current pressure value, and the preset pressure threshold.

[0068] This process involves the comprehensive analysis of various data to identify different types of faults, such as leaks, inefficiencies, or blockages.

[0069] The control unit compares the cumulative pressure value with a preset threshold to determine whether the pressure change exceeds the normal range, and can identify the specific fault type.

[0070] For different fault types, the control unit can be set with different response measures, such as reminding the user of an abnormality, reminding that maintenance is needed, issuing an alarm directly, or shutting down the machine, so as to carry out maintenance and repair in a timely manner.

[0071] In some embodiments, during the process of determining the type of fault, the control unit can also combine historical data and other auxiliary parameters for comprehensive analysis to improve the accuracy and reliability of fault diagnosis. For example, based on the fault history of the DPF, the more likely faults to occur in the DPF can be determined (faults that occur frequently can have their weight increased during fault determination).

[0072] Furthermore, the control unit can be configured with machine learning algorithms to automate fault identification and adapt to constantly changing operating conditions and environmental factors. This adaptive diagnostic capability can significantly improve the operating efficiency and reliability of the DPF system, ensuring efficient operation of the diesel engine and emissions compliance.

[0073] The DPF fault diagnosis method provided in this application improves the accuracy of DPF fault diagnosis by acquiring upstream and downstream pressure values ​​of the DPF and performing pressure integration processing when abnormal state judgment conditions are met. Through comprehensive analysis of cumulative pressure values, pressure values, and preset pressure thresholds, the type of DPF fault can be effectively identified. This not only allows for rapid location of the fault cause but also reduces false alarms or missed alarms caused by pipeline leaks, improving the operational reliability and maintenance efficiency of the DPF and ensuring the efficient operation and compliance of the engine.

[0074] Figure 3 Another embodiment of the DPF fault diagnosis method provided in this disclosure, in Figure 2 Based on the illustrated embodiment, the following is combined with Figure 3 The implementation process of the DPF fault diagnosis method is explained in detail, which includes the following steps:

[0075] S301. Based on a pre-configured dual-diaphragm differential pressure sensor, determine the upstream pressure value and downstream pressure value of the DPF respectively.

[0076] Specifically, in this embodiment, the control unit uses a dual-diaphragm differential pressure sensor to measure the pressure values ​​upstream and downstream of the DPF. This sensor can simultaneously measure the pressure values ​​upstream and downstream of the DPF, providing high-precision and real-time data.

[0077] The advantage of the dual-film design is that it can reduce external interference and improve measurement accuracy.

[0078] Typically, dual-diaphragm differential pressure sensors are installed near the inlet and outlet of the DPF to monitor pressure changes in real time.

[0079] In some embodiments, in addition to upstream and downstream pressure values, the control unit also needs to collect data such as current ambient temperature, ambient pressure, exhaust flow rate, and exhaust temperature to ensure the accuracy of subsequent fault diagnosis.

[0080] S302. If the status parameters meet the corresponding abnormal status determination conditions, then the DPF is determined to be in an abnormal state.

[0081] Specifically, after obtaining the DPF's state parameters, the next step is to determine whether these parameters meet the abnormal state criteria. These criteria are obtained through experiments or simulations of DPFs with structural anomalies. Specifically, leak points can be artificially created on the DPF sample, or pressure changes in the DPF under different fault conditions can be simulated using simulation software to determine the parameter thresholds for abnormal states. This part will be described in further detail below.

[0082] Furthermore, the conditions for determining abnormal states are determined in the following manner:

[0083] Step A1: Obtain the DPF with structural anomalies and measure the abnormal state parameters corresponding to the DPF with structural anomalies.

[0084] Among them, DPFs with structural abnormalities include DPFs with leaks in the pipeline.

[0085] Specifically, actual leaks are usually small cracks or gaps. Therefore, to simulate leaks, small holes (such as 2mm or 5mm in diameter) can be enlarged in the DPF to simulate leaks, thus creating a DPF with structural anomalies.

[0086] When determining the conditions for abnormal conditions, leak points can be set up upstream and downstream of the DPF (the upstream and downstream leak points can exist in one DPF at the same time, or the upstream leak point and the downstream leak point can be set up on two DPFs respectively).

[0087] The specific location of the leak can be chosen arbitrarily upstream or downstream of the DPF; there are no restrictions here.

[0088] In this embodiment, the DPF with structural anomalies is obtained based on simulation, or the DPF with structural anomalies is a DPF sample containing leakage points.

[0089] Therefore, the abnormal state parameters can be obtained by either obtaining the abnormal state parameters based on the simulation results, or by obtaining the abnormal state parameters based on the measurement of DPF samples containing leakage points.

[0090] Specifically, to determine the criteria for anomaly detection, it is necessary to obtain DPF samples with structural anomalies. These samples can be obtained through simulation or actual manufacturing. In simulation, software tools are used to simulate pressure changes when leaks occur at different locations on the DPF. This simulation can provide a large amount of experimental data to help determine the parameters of the anomaly.

[0091] In addition, actual DPF samples can be obtained by artificially creating leaks in the pipeline.

[0092] Based on this, the abnormal state parameters include the rate of change of exhaust flow, exhaust flow, and the corresponding exhaust temperature range.

[0093] Specifically, these samples are used to measure abnormal state parameters, such as the rate of change of exhaust flow, exhaust flow rate, and exhaust temperature range.

[0094] By measuring these abnormal state parameters, the performance of DPF under different fault conditions can be determined more accurately.

[0095] In some embodiments, in practical applications, simulation data and actual measurement data can be combined (e.g., averaging the obtained abnormal state parameters) to improve the accuracy and reliability of abnormal state determination conditions.

[0096] Step A2: Use the values ​​of the abnormal state parameters as the thresholds for the abnormal state determination conditions, and determine the abnormal state determination conditions based on the thresholds corresponding to the abnormal state parameters.

[0097] Specifically, once the values ​​of the abnormal state parameters are obtained, these values ​​will be used as thresholds for determining abnormal states. These thresholds are used to determine whether the DPF is in an abnormal state.

[0098] By comparing the real-time measured status parameters with these thresholds, the control unit can quickly identify abnormal states of the DPF. For example, when the actual pressure of the DPF is lower than the pressure corresponding to the DPF with a leak, it can be directly confirmed that the actual DPF also has a leak.

[0099] To improve the accuracy of abnormal state determination, the threshold of abnormal state determination conditions can be dynamically adjusted according to different operating conditions and environmental conditions. For example, the pressure values ​​are different under different ambient temperatures (or exhaust temperatures). The specific correlation can be obtained by establishing a graph of operating conditions and environmental conditions (this graph can be obtained by measuring abnormal state parameters under different environmental conditions).

[0100] S303. Integrate the upstream pressure value and downstream pressure value of the DPF corresponding to the DPF in an abnormal state to obtain the cumulative pressure value of the DPF.

[0101] Specifically, this step is related to Figure 2 The corresponding steps in the illustrated embodiments are the same and will not be repeated here.

[0102] S304. If the cumulative pressure value upstream or downstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state judgment condition, the fault type of the DPF is determined to be that there is a leak.

[0103] Specifically, after obtaining the accumulated pressure value, the control unit compares it with a threshold value in the abnormal state determination criteria. If the accumulated pressure value is less than the corresponding threshold value, it indicates that there may be a leak in the DPF.

[0104] This judgment, based on the cumulative effect of pressure changes, can more accurately identify air leakage faults. In this way, the control unit can quickly locate the cause of the fault and take appropriate maintenance measures.

[0105] In some embodiments, to improve the accuracy of leak detection, the control unit can combine other auxiliary parameters, such as exhaust flow rate and temperature changes, for comprehensive analysis.

[0106] Furthermore, determining the leak point specifically includes the following steps:

[0107] Step B1: If the cumulative pressure value upstream of the DPF is less than the cumulative value of the corresponding upstream threshold in the abnormal state judgment condition, the fault type of the DPF is determined to be that there is a leak upstream of the DPF.

[0108] Specifically, since the pressure threshold values ​​upstream and downstream of the DPF typically differ, the control unit compares the accumulated pressure value upstream with the corresponding threshold value to determine if a leak exists upstream of the DPF. If the accumulated value is less than the threshold, a leak is confirmed to exist upstream of the DPF.

[0109] Step B2: If the cumulative pressure value downstream of the DPF is less than the cumulative value of the corresponding threshold downstream in the abnormal state judgment condition, the fault type of the DPF is determined to be that there is a leak downstream of the DPF.

[0110] Specifically, similar to identifying upstream leaks, the control unit compares the accumulated downstream pressure with a corresponding downstream threshold. If the accumulated pressure is less than the threshold, a leak can be identified downstream of the DPF.

[0111] In this way, the control unit can quickly locate the location of the air leak (because the air leak point itself is small, and if it cannot be located quickly, the troubleshooting will be time-consuming), thereby improving the efficiency of troubleshooting and maintenance.

[0112] S305. If the cumulative pressure value upstream or downstream of the DPF is greater than the cumulative value of the corresponding threshold in the abnormal state judgment condition, determine the pressure difference between the upstream and downstream of the DPF.

[0113] Specifically, if it is determined that there is no leak in the DPF, the control unit will further analyze the pressure difference between the upstream and downstream.

[0114] If the cumulative pressure value is greater than the corresponding threshold, it indicates that the DPF may have other types of faults, such as inefficiency or blockage.

[0115] By calculating the pressure difference between upstream and downstream, the control unit can more accurately identify these fault types. The calculation of the pressure difference needs to take into account the time and magnitude of pressure changes (requiring the selection of upstream and downstream pressure values ​​at the same moment to calculate the corresponding pressure difference) to ensure accuracy.

[0116] Similar to the calculation of cumulative pressure values, in order to improve the accuracy of pressure difference judgment, the control unit can combine other auxiliary parameters, such as exhaust flow rate and temperature changes, for comprehensive analysis, such as dynamically adjusting the corresponding pressure difference threshold according to temperature changes.

[0117] S306. If the pressure difference is less than the corresponding minimum pressure difference threshold, the fault type is determined to be low DPF efficiency.

[0118] Specifically, after calculating the pressure difference, the control unit compares it with a preset minimum threshold.

[0119] If the pressure difference is less than the minimum threshold, it indicates that the DPF's filtration efficiency may be lower than normal.

[0120] In this case, the DPF may need to be cleaned or replaced to restore its normal function.

[0121] In this way, the control unit can quickly identify inefficient faults and take corresponding maintenance measures.

[0122] S307. If the pressure difference is greater than the corresponding maximum pressure difference threshold, the fault type is determined to be DPF blockage.

[0123] Specifically, if the pressure difference is greater than the preset maximum threshold, it indicates that the DPF may be clogged.

[0124] In this situation, the DPF's filtration capacity may be severely impaired, requiring immediate cleaning or replacement.

[0125] In this way, the control unit can quickly identify blockage faults and take corresponding maintenance measures.

[0126] The DPF fault diagnosis method provided in this disclosure achieves efficient fault diagnosis by accurately acquiring and analyzing the upstream and downstream pressure values ​​of the DPF. By using a dual-diaphragm differential pressure sensor and integral processing technology, it can accurately identify various fault types such as leakage, inefficiency, and blockage. By setting abnormal state judgment conditions based on simulation and actual measurement data, the accuracy and reliability of the diagnosis are improved. The system enhances its adaptability to different operating conditions and environmental conditions by dynamically adjusting thresholds in conjunction with various auxiliary parameters. Therefore, it significantly improves the operating efficiency and maintenance effectiveness of the DPF system, ensuring the efficient operation of the diesel engine and emission compliance.

[0127] Figure 4 This is a schematic diagram of the structure of a DPF fault diagnosis device provided in one embodiment of this disclosure. Figure 4 As shown, the DPF fault diagnosis device 400 includes:

[0128] The acquisition module 410 is used to acquire the status parameters of the diesel particulate filter (DPF), including the upstream pressure value and the downstream pressure value of the DPF.

[0129] The judgment module 420 is used to determine that the DPF is in an abnormal state if the state parameters meet the corresponding abnormal state judgment conditions.

[0130] The calculation module 430 is used to integrate the upstream pressure value and the downstream pressure value of the DPF corresponding to the DPF in an abnormal state to obtain the cumulative pressure value of the DPF.

[0131] The determination module 440 is used to determine the type of DPF fault based on the cumulative DPF pressure value, the DPF pressure value, and the preset pressure threshold.

[0132] Optionally, the judgment module 420 is specifically used to determine the abnormal state judgment conditions in the following manner: obtain the DPF with structural abnormality, and measure the abnormal state parameters corresponding to the DPF with structural abnormality, including DPF with leakage point in pipeline; use the value of the abnormal state parameter as the threshold of the abnormal state judgment condition, and determine the abnormal state judgment condition based on the threshold corresponding to the abnormal state parameter.

[0133] Optionally, the judgment module 420 is specifically used to: if the DPF with structural anomalies is obtained based on simulation, or if the DPF with structural anomalies is a DPF sample containing leakage points; obtain abnormal state parameters based on the simulation results, or obtain abnormal state parameters based on the measurement of the DPF sample containing leakage points.

[0134] Optionally, the judgment module 420 specifically includes abnormal state parameters including exhaust flow rate change rate, exhaust flow rate and corresponding exhaust temperature range.

[0135] Optionally, the determining module 440 is specifically used to: determine the DPF fault type as having a leak if the cumulative pressure value upstream or downstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition; determine the corresponding pressure difference between the upstream and downstream of the DPF if the cumulative pressure value upstream or downstream of the DPF is greater than the cumulative value of the corresponding threshold in the abnormal state determination condition; determine the fault type as low DPF efficiency if the pressure difference is less than the corresponding minimum pressure difference threshold; and determine the fault type as DPF blockage if the pressure difference is greater than the corresponding maximum pressure difference threshold.

[0136] Optionally, the determining module 440 is specifically used to determine the fault type of the DPF as an upstream leak if the cumulative pressure value upstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition; and to determine the fault type of the DPF as a downstream leak if the cumulative pressure value downstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition.

[0137] Optionally, the acquisition module 410 specifically includes determining the upstream pressure value of the DPF and the downstream pressure value of the DPF based on a pre-configured dual-membrane differential pressure sensor.

[0138] In this embodiment, the DPF fault diagnosis device solves the problem of insufficient accuracy in DPF fault diagnosis in related technologies by combining various modules.

[0139] Figure 5 This is a schematic diagram of the structure of a control device provided in one embodiment of the present disclosure, as shown below. Figure 5 As shown, the control device 500 includes a memory 510 and a processor 520.

[0140] The memory 510 stores a computer program that can be executed by at least one processor 520. This computer program is executed by at least one processor 520 to enable the control device to implement the battery SOC estimation method provided in any of the above embodiments.

[0141] The memory 510 and the processor 520 can be connected via a bus 530.

[0142] The relevant explanations can be understood by referring to the corresponding descriptions and effects in the method embodiments, and will not be repeated here.

[0143] One embodiment of this disclosure provides a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the DPF fault diagnosis method provided in any of the above embodiments.

[0144] The computer-readable storage medium may be ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0145] One embodiment of this disclosure provides a computer program product comprising computer-executable instructions that, when executed by a processor, are used to implement the DPF fault diagnosis method provided in any of the above embodiments.

[0146] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0147] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0148] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0149] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for diagnosing faults in a diesel particulate filter (DPF), characterized in that, include: Obtain the status parameters of the diesel particulate filter (DPF); wherein, the status parameters include the upstream pressure value and the downstream pressure value of the DPF; If the state parameters meet the corresponding abnormal state determination conditions, then the DPF is determined to be in an abnormal state. The abnormal state determination conditions are determined as follows: obtain a DPF with structural abnormalities and measure the abnormal state parameters corresponding to the DPF with structural abnormalities, including DPFs with leaks in the pipeline; use the values ​​of the abnormal state parameters as the threshold of the abnormal state determination conditions, and determine the abnormal state determination conditions based on the threshold corresponding to the abnormal state parameters. The upstream and downstream pressure values ​​of the DPF corresponding to the DPF in an abnormal state are integrated to obtain the cumulative pressure value of the DPF. Based on the cumulative DPF pressure value, the DPF pressure value, and the preset pressure threshold, the type of DPF failure is determined. The method of determining the fault type of the DPF based on the cumulative DPF pressure value, the DPF pressure value, and a preset pressure threshold includes: If the cumulative pressure value upstream or downstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition, the fault type of the DPF is determined to be that there is a leak. If the cumulative pressure value upstream or downstream of the DPF is greater than the cumulative value of the corresponding threshold in the abnormal state determination condition, the pressure difference between the upstream and downstream of the DPF is determined. If the pressure difference is less than the corresponding minimum pressure difference threshold, the fault type is determined to be low DPF efficiency. If the pressure difference is greater than the corresponding maximum pressure difference threshold, the fault type is determined to be DPF blockage.

2. The method according to claim 1, characterized in that, The DPF with structural anomalies is obtained based on simulation, or the DPF with structural anomalies is a DPF sample containing leakage points. The measurement of the abnormal state parameters corresponding to the DPF with structural anomalies includes: The abnormal state parameters are obtained based on the simulation results, or based on the measurement of a DPF sample containing a leak point.

3. The method according to claim 1, characterized in that, The abnormal state parameters include the rate of change of exhaust flow, exhaust flow, and the corresponding exhaust temperature range.

4. The method according to claim 1, characterized in that, If the cumulative pressure value upstream or downstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition, the fault type of the DPF is determined to be a leak, including: If the cumulative pressure value upstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition, the fault type of the DPF is determined to be that there is a leak upstream of the DPF. If the cumulative pressure value downstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition, the fault type of the DPF is determined to be that there is a leak downstream of the DPF.

5. The method according to any one of claims 1 to 3, characterized in that, The acquisition of the status parameters of the diesel particulate filter (DPF) includes: Based on a pre-configured dual-membrane differential pressure sensor, the upstream pressure value and the downstream pressure value of the DPF are determined respectively.

6. A DPF fault diagnosis apparatus for performing the method according to any one of claims 1-5, characterized in that, The DPF fault diagnosis device includes: The acquisition module is used to acquire the status parameters of the diesel particulate filter (DPF), wherein the status parameters include the upstream pressure value and the downstream pressure value of the DPF. The judgment module is used to determine that the DPF is in an abnormal state if the state parameter meets the corresponding abnormal state judgment condition. The abnormal state judgment condition is determined by: acquiring a DPF with structural abnormality and measuring the abnormal state parameter corresponding to the DPF with structural abnormality, the DPF with structural abnormality including DPF with a leak point in the pipeline; using the value of the abnormal state parameter as the threshold of the abnormal state judgment condition, and determining the abnormal state judgment condition based on the threshold corresponding to the abnormal state parameter. The calculation module is used to integrate the upstream pressure value and downstream pressure value of the DPF corresponding to the DPF in an abnormal state to obtain the cumulative pressure value of the DPF. The determination module is used to determine the fault type of the DPF based on the cumulative DPF pressure value, the DPF pressure value, and a preset pressure threshold. The determination module is specifically used to determine the fault type of the DPF as having a leak if the cumulative pressure value upstream or downstream of the DPF is less than the cumulative value of the corresponding threshold in the abnormal state determination condition; to determine the pressure difference between the upstream and downstream of the DPF if the cumulative pressure value upstream or downstream of the DPF is greater than the cumulative value of the corresponding threshold in the abnormal state determination condition; to determine the fault type as low DPF efficiency if the pressure difference is less than the corresponding minimum pressure difference threshold; and to determine the fault type as DPF blockage if the pressure difference is greater than the corresponding maximum pressure difference threshold.

7. A control device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 5.

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