Vehicle fault detection method and device based on fuel consumption

Abstract

The invention relates to the technical field of new energy vehicle diagnosis, in particular to a vehicle fault detection method and device based on fuel consumption, and the method comprises the steps: calculating the predicted fuel consumption of engine fuel based on the reducing agent information of a reducing agent in a vehicle post-processing device; judging whether the predicted fuel consumption is greater than the actual fuel consumption; if the difference value is greater than the first threshold value, determining that the fault detection result is a flow meter fault or a test bed fault based on the predicted fuel consumption when the vehicle breaks down; and if the difference value is smaller than the second threshold value, determining that the fault detection result is a leakage fault, a sensor fault or a test bench fault based on the predicted fuel consumption amount. Therefore, the problems of missing detection, incapability of coping with various complicated working conditions and environmental conditions and the like caused by complicated judgment conditions, high processing capability and response speed of the system and incapability of covering all possible fault conditions in the related technologies are solved.

Description

Technical Field

[0001] The present application relates to the technical field of new energy vehicle diagnosis, and in particular to a vehicle fault detection method and device based on fuel consumption. Background Art

[0002] Ammonia is a renewable zero-carbon fuel that produces no carbon dioxide after combustion. Large-scale use of ammonia fuel can significantly reduce carbon emissions from industry and transportation, helping to curb global warming. Since the technology of ammonia fuel engines is not mature enough and is still in the research and development and testing stage, some unknown problems and failures may occur during use.

[0003] In the related art, the pressure error value and the flow error value can be determined by acquiring the current power value, the current pressure value and the current flow value of the fuel cell in the vehicle and the corresponding historical pressure value and historical flow value, and then the fault detection result of the fuel cell can be determined; the fault detection result of the fuel cell hydrogen system can also be determined by setting the flow path between the pressure reducing valve and the fuel cell as the first flow path, and introducing judgment conditions such as the fuel cell start-stop state and the real-time power change rate of the fuel cell.

[0004] However, in the related technologies, the judgment conditions are complex, requiring the system to have high processing capabilities and response speeds, and these judgment conditions may not cover all possible fault conditions, resulting in missed detections, and are unable to cope with various complex working conditions and environmental conditions, which urgently need to be improved. Summary of the invention

[0005] The present application provides a vehicle fault detection method and device based on fuel consumption to solve the problems in the related technology that the judgment conditions are complex, the system needs to have high processing capabilities and response speed, and these judgment conditions may not cover all possible fault conditions, resulting in missed detections, and the system cannot cope with various complex working conditions and environmental conditions.

[0006] A first aspect embodiment of the present application provides a vehicle fault detection method based on fuel consumption, comprising the following steps: calculating the predicted fuel consumption of the engine fuel based on the reducing agent information of the reducing agent in the vehicle after-treatment device; judging whether the predicted fuel consumption is greater than the actual fuel consumption of the engine fuel; if the predicted fuel consumption is greater than the actual fuel consumption of the engine fuel, and the difference between the predicted fuel consumption and the actual fuel consumption is greater than a first threshold value, then determining based on the predicted fuel consumption that the fault detection result when the vehicle fails is a flow meter failure or a test bench failure; if the predicted fuel consumption is less than the actual fuel consumption, and the difference between the predicted fuel consumption and the actual fuel consumption is less than a second threshold value, then determining based on the predicted fuel consumption that the fault detection result is a leakage failure, a sensor failure or a test bench failure.

[0007] Through the above technical scheme, the predicted fuel consumption of the engine fuel can be calculated first, and then the fault detection result when the vehicle fails can be determined by judging the size of the predicted fuel consumption and the actual fuel consumption. By considering the reducing agent information in the vehicle post-processing device, the fuel consumption of the engine can be predicted more accurately, and by setting the first threshold and the second threshold as the basis for judging the fault, abnormal changes in fuel consumption can be discovered in time, which helps to quickly locate the fault point and improve maintenance efficiency. It is simple and clear and easy to implement.

[0008] Optionally, in one embodiment of the present application, the predicted fuel consumption of the engine fuel is calculated based on the reducing agent information of the reducing agent in the vehicle after-treatment device, including: when the reducing agent information includes liquid ammonia data, calculating the predicted fuel consumption based on a first predicted fuel consumption calculation formula; when the reducing agent information includes urea data, calculating the predicted fuel consumption based on a second predicted fuel consumption calculation formula.

[0009] Through the above technical solution, different predicted fuel consumption calculation formulas can be used to calculate the predicted fuel consumption for the liquid ammonia data and urea data in the reducing agent information in the vehicle after-treatment device, thereby avoiding the errors that may be caused by using a unified calculation formula, improving the accuracy and reliability of the prediction, and thus more comprehensively reflecting the contribution of the reducing agent to the fuel consumption.

[0010] Optionally, in one embodiment of the present application, before calculating the predicted fuel consumption of the engine fuel, the method further includes: obtaining the purity of ammonia and the fuel density in the engine fuel; detecting the ammonia in the exhaust gas; density and concentration, The density and concentration of density and concentration; according to the The density and concentration of The density and concentration and The density and concentration of the engine fuel exhaust are calculated respectively. Emission mass per unit mileage, exhaust gas Emission mass per unit mileage and exhaust gas Emissions per unit mileage.

[0011] Through the above technical solution, before calculating the predicted fuel consumption of the engine fuel, the purity of ammonia and fuel density in the engine fuel can be obtained, and multiple gases in the exhaust gas can be detected ( , and ) and then calculate the emission mass per unit mileage in the engine fuel exhaust, so as to more accurately predict the combustion efficiency and fuel consumption of the engine fuel, which helps to more accurately evaluate the performance and fuel consumption of the engine.

[0012] Optionally, in one embodiment of the present application, the first predicted fuel consumption calculation formula may be, but is not limited to: , The second predicted fuel consumption calculation formula may be, but is not limited to,: , in, The fuel consumption of the test vehicle, in m 3 / 100km; is the number of trials performed, ; is the ammonia purity of the fuel expressed as mole fraction or volume fraction, unit: %; It is the fuel density at standard reference conditions of 0℃ and 101.325kPa, in kg / m 3 ; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the Test (Selective Catalytic Reduction, Selective Catalytic Reduction Technology) The injection amount per unit mileage is in g / km; For the Test The injection amount of urea aqueous solution per unit mileage, in g / km; is the mass fraction of hydrogen atoms in the urea aqueous solution to the total mass; is the ammonia fuel coefficient.

[0013] Through the above technical solution, the first predicted fuel consumption calculation formula and the second predicted fuel consumption calculation formula can be obtained. The formula contains multiple key parameters. The introduction of these parameters makes the prediction more comprehensive and accurate, and can more truly reflect the fuel consumption in the actual operation process, thereby reducing unnecessary fuel waste and achieving the goal of energy conservation and emission reduction.

[0014] Optionally, in one embodiment of the present application, the calculation of the predicted fuel consumption of the engine fuel based on the reductant information of the reductant in the vehicle after-treatment device includes: detecting the driving condition of the vehicle; calculating at least one initial fuel consumption of the vehicle engine fuel in different speed ranges based on the driving condition and the reductant information; and determining the predicted fuel consumption based on the at least one initial fuel consumption.

[0015] Through the above technical scheme, at least one initial fuel consumption in different speed ranges can be calculated according to the vehicle's driving conditions and reducing agent information, and then the predicted fuel consumption can be determined. By combining the driving conditions and calculating the initial fuel consumption for different speed ranges, the change in fuel consumption can be analyzed more carefully, which helps to more accurately reflect the fuel consumption characteristics of the vehicle under different driving conditions, making the prediction results closer to reality and improving the accuracy of the prediction.

[0016] A second aspect of the present application provides a vehicle fault detection device based on fuel consumption, including: a first calculation module, used to calculate the predicted fuel consumption of the engine fuel based on the reducing agent information of the reducing agent in the vehicle post-processing device; a judgment module, used to judge whether the predicted fuel consumption is greater than the actual fuel consumption of the engine fuel; a first determination module, used to determine that the fault detection result when the vehicle fails is a flow meter failure or a test bench failure based on the predicted fuel consumption when the predicted fuel consumption is greater than the actual fuel consumption of the engine fuel and the difference between the predicted fuel consumption and the actual fuel consumption is greater than a first threshold; a second determination module, used to determine that the fault detection result is a leakage failure, a sensor failure or a test bench failure based on the predicted fuel consumption when the predicted fuel consumption is less than the actual fuel consumption and the difference between the predicted fuel consumption and the actual fuel consumption is less than a second threshold.

[0017] Through the above technical scheme, the predicted fuel consumption of the engine fuel can be calculated first, and then the fault detection result when the vehicle fails can be determined by judging the size of the predicted fuel consumption and the actual fuel consumption. By considering the reducing agent information in the vehicle post-processing device, the fuel consumption of the engine can be predicted more accurately, and by setting the first threshold and the second threshold as the basis for judging the fault, abnormal changes in fuel consumption can be discovered in time, which helps to quickly locate the fault point and improve maintenance efficiency. It is simple and clear and easy to implement.

[0018] Optionally, in one embodiment of the present application, the first calculation module includes: a first calculation unit, used to calculate the predicted fuel consumption based on a first predicted fuel consumption calculation formula when the reductant information includes liquid ammonia data; a second calculation unit, used to calculate the predicted fuel consumption based on a second predicted fuel consumption calculation formula when the reductant information includes urea data.

[0019] Through the above technical solution, different predicted fuel consumption calculation formulas can be used to calculate the predicted fuel consumption for the liquid ammonia data and urea data in the reducing agent information in the vehicle after-treatment device, thereby avoiding the errors that may be caused by using a unified calculation formula, improving the accuracy and reliability of the prediction, and thus more comprehensively reflecting the contribution of the reducing agent to the fuel consumption.

[0020] Optionally, in one embodiment of the present application, it further includes: an acquisition module for acquiring the purity and fuel density of ammonia in the engine fuel before calculating the predicted fuel consumption of the engine fuel; a detection module for detecting the purity and fuel density of ammonia in the exhaust gas; density and concentration, The density and concentration of density and concentration; a second calculation module for calculating the density and concentration according to the The density and concentration of The density and concentration and The density and concentration of the engine fuel exhaust are calculated respectively. Emission mass per unit mileage, exhaust gas Emission mass per unit mileage and exhaust gas Emissions per unit mileage.

[0021] Through the above technical solution, before calculating the predicted fuel consumption of the engine fuel, the purity of ammonia and fuel density in the engine fuel can be obtained, and multiple gases in the exhaust gas can be detected ( , and ) and then calculate the emission mass per unit mileage in the engine fuel exhaust, so as to more accurately predict the combustion efficiency and fuel consumption of the engine fuel, which helps to more accurately evaluate the performance and fuel consumption of the engine.

[0022] Optionally, in one embodiment of the present application, the first predicted fuel consumption calculation formula may be, but is not limited to: , The second predicted fuel consumption calculation formula may be, but is not limited to,: , in, The fuel consumption of the test vehicle, in m 3 / 100km; is the number of trials performed, ; is the ammonia purity of the fuel expressed as mole fraction or volume fraction, unit: %; It is the fuel density at standard reference conditions of 0℃ and 101.325kPa, in kg / m 3 ; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the Test In The injection amount per unit mileage is in g / km; For the Test The injection amount of urea aqueous solution per unit mileage, in g / km; is the mass fraction of hydrogen atoms in the urea aqueous solution to the total mass; is the ammonia fuel coefficient.

[0023] Through the above technical solution, the first predicted fuel consumption calculation formula and the second predicted fuel consumption calculation formula can be obtained. The formula contains multiple key parameters. The introduction of these parameters makes the prediction more comprehensive and accurate, and can more truly reflect the fuel consumption in the actual operation process, thereby reducing unnecessary fuel waste and achieving the goal of energy conservation and emission reduction.

[0024] Optionally, in one embodiment of the present application, the first calculation module includes: a detection unit for detecting the driving condition of the vehicle; a third calculation unit for calculating at least one initial fuel consumption of the vehicle engine fuel in different speed ranges based on the driving condition and the reductant information; and a determination unit for determining the predicted fuel consumption based on the at least one initial fuel consumption.

[0025] Through the above technical scheme, at least one initial fuel consumption in different speed ranges can be calculated according to the vehicle's driving conditions and reducing agent information, and then the predicted fuel consumption can be determined. By combining the driving conditions and calculating the initial fuel consumption for different speed ranges, the change in fuel consumption can be analyzed more carefully, which helps to more accurately reflect the fuel consumption characteristics of the vehicle under different driving conditions, making the prediction results closer to reality and improving the accuracy of the prediction.

[0026] The third aspect of the present application provides a vehicle, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle fault detection method based on fuel consumption as described in the above embodiment.

[0027] A fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the above-mentioned vehicle fault detection method based on fuel consumption.

[0028] The fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, implements the above-mentioned vehicle fault detection method based on fuel consumption.

[0029] The embodiment of the present application can first calculate the predicted fuel consumption of the engine fuel, and then determine the fault detection result when the vehicle fails by judging the size of the predicted fuel consumption and the actual fuel consumption. By considering the reductant information in the vehicle post-processing device, the fuel consumption of the engine can be predicted more accurately. By setting the first threshold and the second threshold as the basis for judging the fault, the abnormal change of the fuel consumption can be discovered in time, which helps to quickly locate the fault point and improve the maintenance efficiency. It is simple and easy to implement. Therefore, the problem in the related art that the judgment conditions are complex and the system needs to have a high processing power and response speed, and these judgment conditions may not cover all possible fault conditions, resulting in missed detection, and it is even more impossible to cope with various complex working conditions and environmental conditions.

[0030] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which: Figure 1 A block diagram of a vehicle fault detection test system based on fuel consumption according to an embodiment of the present application; Figure 2 A flowchart of a vehicle fault detection method based on fuel consumption provided according to an embodiment of the present application; Figure 3 A flowchart of the working principle of a vehicle fault detection method based on fuel consumption according to an embodiment of the present application; Figure 4 A block diagram of a vehicle fault detection device based on fuel consumption according to an embodiment of the present application; Figure 5 It is a schematic diagram of the structure of a vehicle provided according to an embodiment of the present application.

[0032] Reference numerals: Among them, 10-Fuel consumption-based vehicle fault detection test system; 101-Road simulation cooling fan, 102-Chassis dynamometer, 103-Test vehicle, 104- Exhaust gas analyzer, 105- Exhaust gas analyzer, 106- Exhaust analyzer, 107-exhaust pipeline; 40-vehicle fault detection device based on fuel consumption; 401-first calculation module, 402-judgment module, 403-first determination module, 404-second determination module; 501-memory, 502-processor, 503-communication interface. DETAILED DESCRIPTION

[0033] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0034] The following describes the vehicle fault detection method and device based on fuel consumption of the embodiment of the present application with reference to the accompanying drawings. In view of the complex judgment conditions mentioned in the above background technology, the system needs to have a high processing capacity and response speed, and these judgment conditions may not cover all possible fault conditions, resulting in missed detection, and it is even more impossible to cope with various complex working conditions and environmental conditions. The present application provides a vehicle fault detection method based on fuel consumption, in which the predicted fuel consumption of the engine fuel can be calculated first, and then the fault detection result when the vehicle fails can be determined by judging the size of the predicted fuel consumption and the actual fuel consumption. By considering the reductant information in the vehicle post-processing device, the fuel consumption of the engine can be predicted more accurately. By setting the first threshold and the second threshold as the basis for judging the fault, the abnormal change of fuel consumption can be discovered in time, which is helpful to quickly locate the fault point and improve the maintenance efficiency. It is simple and clear and easy to implement. Therefore, the problem that the judgment conditions in the related technology are complex, the system needs to have a high processing capacity and response speed, and these judgment conditions may not cover all possible fault conditions, resulting in missed detection, and it is even more impossible to cope with various complex working conditions and environmental conditions is solved.

[0035] Before introducing the vehicle fault detection method based on fuel consumption proposed in the embodiment of the present application, a vehicle fault detection test system based on fuel consumption involved in the embodiment of the present application is first introduced.

[0036] Specifically, Figure 1 The present invention is a block diagram of a vehicle fault detection test system based on fuel consumption according to an embodiment of the present application.

[0037] like Figure 1 As shown, the vehicle fault detection test system 10 based on fuel consumption includes: a road simulation cooling fan 101, a chassis dynamometer 102, a test vehicle 103, Exhaust gas analyzer 104, Exhaust gas analyzer 105, Exhaust gas analyzer 106 and exhaust gas line 107 .

[0038] The fuel consumption test of the test vehicle 103 is conducted on the chassis dynamometer 102. After the test vehicle 103 is prepared and confirmed according to the relevant standards, the chassis dynamometer 102 is powered on to put the chassis dynamometer 102 in the detection state. Then, the lifter pallet is raised to allow the test vehicle 103 to drive smoothly in the direction perpendicular to the rollers, and the driving wheels are placed on the lifter pallet between the two rollers. The chassis dynamometer 102 is operated to lower the lifter pallet. The engine is started, and the rollers of the chassis dynamometer 102 are driven to run idle for a while by the test vehicle 103 to make the working temperature of the moving parts of the chassis dynamometer 102 normal.

[0039] Furthermore, the rear end of the test vehicle 103 of the present application is installed Exhaust gas analyzer 104, Exhaust gas analyzer 105, The exhaust gas analyzer 106 measures the fuel consumption of the test vehicle 103 during the test. , and If the fuel consumption and exhaust emission tests are carried out simultaneously, a full-flow dilution system and a lean exhaust gas analyzer must be additionally arranged.

[0040] In addition, in the embodiment of the present application, a fixed road simulation cooling fan 101 is installed at an appropriate position directly in front of the test vehicle 103, and is turned on synchronously during the test to cool the vehicle.

[0041] It should be noted that, before the formal test, the embodiment of the present application can measure the driving resistance of the test vehicle 103 according to Appendix C of GB / T 27840-2021, and record the parameters of the test vehicle 103 according to the provisions of Appendix D; or determine the driving resistance according to the recommended value of the driving resistance coefficient specified in Appendix E as an alternative method; the test equipment can also be preheated, and the exhaust gas analyzer, such as Exhaust gas analyzer 104, Exhaust gas analyzer 105, The exhaust gas analyzer 106 is used to check for leaks, the analyzer is calibrated with standard gas, and the zero point of the analyzer is calibrated with nitrogen; the test vehicle 103 can also be started to run 1-2 complete driving conditions or other methods can be used to fully preheat the test vehicle 103 and the chassis dynamometer 102. In order to eliminate or reduce the influence of various hydrogen-containing components in the background air on the test measurement results, the exhaust gas analyzer is used to collect and record the corresponding components in the background air before the test ( , , , It can also confirm whether the fuel flow meter, exhaust sampling system and other testing equipment of the test vehicle 103 and the exhaust pipe 107 are leak-free and can operate normally, etc. This application does not impose specific restrictions.

[0042] Specifically, Figure 2 The present invention provides a flowchart of a vehicle fault detection method based on fuel consumption according to an embodiment of the present application.

[0043] like Figure 2 As shown, the vehicle fault detection method based on fuel consumption includes the following steps: In step S201 , a predicted fuel consumption amount of engine fuel is calculated based on reducing agent information of a reducing agent in a vehicle post-treatment device.

[0044] It is understood that in the embodiments of the present application, the vehicle post-processing device can be understood as a device installed in the vehicle exhaust system for reducing the emission of harmful substances in the exhaust gas. It can include, but is not limited to, a catalytic converter, a particulate trap, etc., and the present application does not make specific restrictions.

[0045] In addition, it should be noted that the vehicle post-processing device of the embodiment of the present application can use a reducing agent to chemically react with harmful substances in the exhaust gas to convert them into harmless substances, such as The reducing agent may include but is not limited to liquid ammonia and urea, etc., which are not specifically limited in this application.

[0046] As a possible implementation method, the embodiment of the present application can first determine the reducing agent information of the reducing agent of the vehicle post-processing device, and then use the reducing agent information to calculate the predicted fuel consumption of the engine fuel.

[0047] For example, in an embodiment of the present application, when the reducing agent information includes liquid ammonia data, the predicted fuel consumption is calculated based on the liquid ammonia data; when the reducing agent information includes urea data, the predicted fuel consumption is calculated based on the urea data.

[0048] Optionally, in one embodiment of the present application, before calculating the predicted fuel consumption of the engine fuel, the method further includes: obtaining the purity of ammonia and the fuel density in the engine fuel; detecting the ammonia in the exhaust gas; density and concentration, The density and concentration of density and concentration; according to density and concentration, The density and concentration of The density and concentration of the engine fuel exhaust are calculated respectively. Emission mass per unit mileage, exhaust gas Emission mass per unit mileage and exhaust gas Emissions per unit mileage.

[0049] In the actual implementation process, before calculating the predicted fuel consumption of the engine fuel, the embodiment of the present application can also obtain the purity of ammonia and fuel density in the engine fuel, and detect the ammonia in the exhaust gas. density and concentration, The density and concentration of density and concentration, and then according to density and concentration, The density and concentration of The density and concentration of the engine fuel exhaust are calculated respectively. Emission mass per unit mileage, exhaust gas Emission mass per unit mileage and exhaust gas Emissions per unit mileage.

[0050] For example, in the tail gas of the embodiment of the present application The calculation formula of emission mass per unit mileage may be, but is not limited to, the following: , in, For exhaust Density, kg / m 3 ; is the exhaust mass per unit time, in kg / s; For exhaust The concentration of, in ppm; For ambient air The concentration of, in ppm; Exhaust density (atmospheric density), unit: kg / m 3 ; It is a single measurement mileage, in km; is the sampling frequency, in Hz.

[0051] Exhaust The calculation formula of emission mass per unit mileage may be, but is not limited to, the following: , in, For exhaust Density, kg / m 3 ; is the exhaust mass per unit time, in kg / s; For exhaust The concentration of, in ppm; For ambient air The concentration of, in ppm; Exhaust density (atmospheric density), unit: kg / m 3 ; It is a single measurement mileage, in km; is the sampling frequency, in Hz.

[0052] Exhaust The calculation formula for emission mass per unit mileage may be, but is not limited to: , in, For exhaust Density, kg / m 3 ; is the exhaust mass per unit time, in kg / s; For exhaust The concentration of, in ppm; For ambient air The concentration of, in ppm; Exhaust density (atmospheric density), unit: kg / m 3 ; It is a single measurement mileage, in km; is the sampling frequency, in Hz.

[0053] It can also obtain the purity of ammonia and fuel density in engine fuel and detect density and concentration, The density and concentration of density and concentration, and then according to density and concentration, The density and concentration of The density and concentration of the engine fuel exhaust are calculated respectively. Emission mass per unit mileage, exhaust gas Emission mass per unit mileage and exhaust gas Emissions per unit mileage.

[0054] For example, combining Figure 1 As shown, the engine fuel of the embodiment of the present application can be pure ammonia fuel or ammonia hydrogen fuel. The specific configuration can be made by technicians in this field according to actual conditions, and this application does not impose any specific restrictions.

[0055] Furthermore, in the embodiment of the present application, when the engine fuel is pure ammonia fuel, the ammonia purity and fuel density can be measured according to the method of GB / T8570.2-2010; when the engine fuel is ammonia-hydrogen fuel, the ammonia purity and fuel density can be measured according to the methods of GB / T 8570.2-2010 and GB / T 37244-2018.

[0056] Furthermore, the embodiments of the present application can utilize Exhaust gas analyzer, Exhaust gas analyzers and Exhaust gas analyzer detects density and concentration, The density and concentration of The density and concentration of the engine fuel exhaust can be calculated Emission mass per unit mileage, exhaust gas Emission mass per unit mileage and exhaust gas Emissions per unit mileage.

[0057] Optionally, in one embodiment of the present application, based on the reducing agent information of the reducing agent in the vehicle post-processing device, the predicted fuel consumption of the engine fuel is calculated, including: when the reducing agent information includes liquid ammonia data, the predicted fuel consumption is calculated based on a first predicted fuel consumption calculation formula; when the reducing agent information includes urea data, the predicted fuel consumption is calculated based on a second predicted fuel consumption calculation formula. The first predicted fuel consumption calculation formula may be, but is not limited to: , The second predicted fuel consumption calculation formula may be, but is not limited to,: , in, The fuel consumption of the test vehicle, in m 3 / 100km; is the number of trials performed, ; is the ammonia purity of the fuel expressed as mole fraction or volume fraction, unit: %; It is the fuel density at standard reference conditions of 0℃ and 101.325kPa, in kg / m 3 ; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the Test In The injection amount per unit mileage is in g / km; For the Test The injection amount of urea aqueous solution per unit mileage, in g / km; is the mass fraction of hydrogen atoms in the urea aqueous solution to the total mass; is the ammonia fuel coefficient.

[0058] It can be understood by those skilled in the art that the embodiment of the present application can calculate the predicted fuel consumption according to different reductant information in the reductant. Specifically, in the embodiment of the present application, when the reductant information includes liquid ammonia data, the predicted fuel consumption is calculated by the first predicted fuel consumption calculation formula; when the reductant information includes urea data, the predicted fuel consumption is calculated based on the second predicted fuel consumption calculation formula. The first predicted fuel consumption calculation formula can be, but is not limited to: , The second predicted fuel consumption calculation formula may be, but is not limited to,: , in, The fuel consumption of the test vehicle, in m 3 / 100km; is the number of trials performed, ; is the ammonia purity of the fuel expressed as mole fraction or volume fraction, unit: %; It is the fuel density at standard reference conditions of 0℃ and 101.325kPa, in kg / m 3 ; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the Test In The injection amount per unit mileage is in g / km; For the Test The injection amount of urea aqueous solution per unit mileage, in g / km; is the mass fraction of hydrogen atoms in the urea aqueous solution to the total mass; is the ammonia fuel coefficient. When the fuel is pure ammonia only, ; When the fuel is a mixture of ammonia and hydrogen, It needs to be calculated based on the proportion of ammonia and hydrogen.

[0059] Furthermore, in the embodiments of the present application, In The calculation formula of the injection volume per unit mileage can be but is not limited to: , in, Post-processing device In Concentration, unit: ppm.

[0060] In addition, in order to ensure the integrity of the post-processing device, the embodiment of the present application does not damage the pipeline of the post-processing device, does not use a measuring instrument to obtain the spray ammonia concentration in the post-processing device, and adopts a control strategy soft measurement method to obtain the spray ammonia concentration in the post-processing device. In Concentration. Among them, the embodiment of the present application obtains according to the control strategy The calculation formula can be but is not limited to: , in, is the concentration of feedforward ammonia injection, obtained by the control unit, in ppm; It is the P adjustment parameter of PI (Proportional-Integral Controller) control; Adjustment parameters for PI control I; For the goal Concentration and actual NOx sensor measurement The difference in concentration.

[0061] For example, combining Figure 1 In the embodiment of the present application, when the reducing agent information includes liquid ammonia data and an ammonia cracking device is installed, the additional A mass flow meter is installed in the reactant supply system in the system, and a mass flow meter is installed in the ammonia supply system in the cracking system, and the predicted fuel consumption is calculated in combination with the first predicted fuel consumption calculation formula.

[0062] Optionally, in one embodiment of the present application, based on the reductant information of the reductant in the vehicle after-treatment device, the predicted fuel consumption of the engine fuel is calculated, including: detecting the driving condition of the vehicle; based on the driving condition and the reductant information, calculating at least one initial fuel consumption of the vehicle engine fuel in different speed ranges; and determining the predicted fuel consumption based on the at least one initial fuel consumption.

[0063] It is understood that in the embodiment of the present application, the driving condition of the vehicle adopts the CHTC condition (China heavy-duty commercial vehicle test cycle) specified in GB / T38146.2-2019 "China Automobile Driving Condition Part 2: Heavy Commercial Vehicles". Among them, city buses adopt CHTC-B driving conditions; ordinary buses adopt CHTC-C driving conditions; trucks adopt CHTC-LT driving conditions (GVW (Gross Vehicle Weight, maximum design gross mass) ≤ 5500kg) or CHTC-HT driving conditions (GVW> 5500kg); semi-trailer tractors adopt CHTC-TT driving conditions; dump trucks adopt CHTC-D driving conditions.

[0064] As a possible implementation method, the embodiment of the present application can detect the driving condition of the vehicle, and based on the driving condition and the reducing agent information, calculate at least one initial fuel consumption of the vehicle engine fuel in different speed ranges, and then determine the predicted fuel consumption.

[0065] For example, combining Figure 1 Before the test, the embodiment of the present application first detects the vehicle's driving resistance, preheats the test equipment, checks the exhaust gas analyzer for leaks, and confirms that the fuel flow meter, exhaust gas sampling system and other test equipment and exhaust pipes connected to the vehicle have no leaks and can operate normally.

[0066] Furthermore, during the test of the embodiment of the present application, the vehicle's shifting strategy and deceleration driving are operated in accordance with the requirements of GB / T27840-2021. The vehicle test should run three complete CHTC driving conditions, and the test results should be recorded after each complete CHTC driving condition. Between two adjacent complete CHTC driving conditions, the vehicle and related equipment should continue to run or adopt other methods to maintain the hot engine state.

[0067] Furthermore, the embodiment of the present application can calculate at least one initial fuel consumption of the vehicle engine fuel in different speed intervals based on the driving condition and the reducing agent information, and then determine the predicted fuel consumption. The initial fuel consumption can be understood as each test result when the vehicle performs the CHTC driving condition fuel consumption test, and the predicted fuel consumption can be understood as the fuel consumption and comprehensive fuel consumption when the vehicle performs the CHTC driving condition fuel consumption test in different speed intervals. Its main contents can be: The present application embodiment calculates the standard deviation of the 95th percentile distribution of the comprehensive fuel consumption test results of multiple complete CHTC driving conditions and the difference between the highest and lowest comprehensive fuel consumption values ​​in multiple test results For comparison, if , then the repeatability test is passed; otherwise, the repeatability test is not passed. Among them, in the embodiment of the present application, ,in, is the standard deviation of the 95th percentile distribution, in g / 100km; It is the arithmetic mean of the comprehensive fuel consumption test results of three complete CHTC driving conditions, in g / 100km; Among them, in the embodiment of the present application, passing the repeatability test can be understood as the average value of the three test results, which is the fuel consumption and comprehensive fuel consumption in different speed ranges of the vehicle's CHTC driving condition; failing the repeatability test can be understood as adopting the average value of the two CHTC driving condition test results with higher comprehensive fuel consumption in multiple test results as the fuel consumption and comprehensive fuel consumption in different speed ranges of the vehicle's CHTC driving condition.

[0068] In step S202, it is determined whether the predicted fuel consumption is greater than the actual fuel consumption of the engine fuel.

[0069] It can be understood that the embodiments of the present application can measure the actual fuel consumption of the engine fuel through an ammonia flow meter at the front end of the engine, and can also measure the actual fuel consumption of the engine fuel through the vehicle's fuel metering system or other testing equipment. The specific settings can be made by technicians in this field according to actual conditions, and this application does not impose specific limitations.

[0070] As a possible implementation method, the embodiment of the present application can determine whether a vehicle failure occurs by comparing the predicted fuel consumption and the actual fuel consumption, and determine the fault detection result when the vehicle fails.

[0071] In step S203, if the predicted fuel consumption is greater than the actual fuel consumption of the engine fuel, and the difference between the predicted fuel consumption and the actual fuel consumption is greater than a first threshold, the fault detection result when the vehicle fails is determined based on the predicted fuel consumption to be a flow meter failure or a test bench failure leakage failure.

[0072] In some embodiments, when the predicted fuel consumption is greater than the actual fuel consumption of the engine fuel, and the difference between the predicted fuel consumption and the actual fuel consumption is greater than a first threshold, the embodiment of the present application determines that the vehicle has a fault, and determines that the fault detection result when the vehicle has a fault is a flow meter fault or a test bench fault. The first threshold can be set by a person skilled in the art according to actual conditions, and this application does not impose any specific restrictions.

[0073] It can be understood that when the predicted fuel consumption of the embodiment of the present application is much greater than the actual fuel consumption measured by the ammonia flow meter, the fault detection result when the vehicle fails can be determined to be, but not limited to, a flow meter failure or a test bench failure, etc., and the present application does not impose any specific restrictions.

[0074] In step S204, if the predicted fuel consumption is less than the actual fuel consumption, and the difference between the predicted fuel consumption and the actual fuel consumption is less than a second threshold, the fault detection result is determined to be a leakage fault, a sensor fault or a test bench fault based on the predicted fuel consumption.

[0075] In some embodiments, when the predicted fuel consumption is less than the actual fuel consumption of the engine fuel, and the difference between the predicted fuel consumption and the actual fuel consumption is less than a second threshold, the embodiment of the present application determines that the vehicle has a fault, and determines that the fault detection result when the vehicle has a fault is a leakage fault, a sensor fault, or a test bench fault. The second threshold can be set by a person skilled in the art according to actual conditions, and this application does not impose any specific restrictions.

[0076] It can be understood that when the predicted fuel consumption of the embodiment of the present application is far less than the actual fuel consumption measured by the ammonia flow meter, the fault detection result when the vehicle fails can be determined to be, but not limited to, a leakage fault, a sensor fault or a test bench fault, etc., and the present application does not impose any specific restrictions.

[0077] Combine the following Figure 1 and Figure 3 As shown, the vehicle fault detection method based on fuel consumption proposed in the embodiment of the present application is introduced with multiple specific embodiments.

[0078] Embodiment 1: The embodiment of the present application determines the fault detection result when the vehicle fails by measuring the fuel consumption of the pure ammonia engine equipped with an ammonia cracking device. The main steps are: Step S301: measuring ammonia purity and fuel density.

[0079] Among them, the embodiment of the present application can measure the ammonia purity and fuel density according to the method of GB / T 8570.2-2010.

[0080] Step S302: Driving condition selection.

[0081] Among them, the embodiment of the present application can adopt the CHTC working condition.

[0082] Step S303: Record driving data.

[0083] Among them, the embodiment of the present application checks for leaks on the exhaust analyzer before the test and confirms that the fuel flow meter, exhaust sampling system and other test equipment and exhaust pipes connected to the vehicle have no leaks and can operate normally; during the test, the vehicle's shifting strategy and deceleration driving are operated in accordance with the requirements of GB / T 27840-2021. The vehicle test should run three complete CHTC driving conditions, and record the test results separately after each complete CHTC driving condition. Between two adjacent complete CHTC driving conditions, the vehicle and related equipment should continue to run or adopt other methods to maintain the hot engine state.

[0084] Step S304: Calculate fuel consumption.

[0085] In this embodiment of the present application, a pure ammonia engine equipped with an ammonia cracking device is used, and when the reducing agent information includes liquid ammonia data, the predicted fuel consumption is calculated using the first predicted fuel consumption calculation formula.

[0086] Step S305: Calculate the degree of repetition.

[0087] Among them, the embodiment of the present application can calculate the standard deviation of the 95th percentile distribution of the comprehensive fuel consumption test results of multiple complete CHTC driving conditions and the difference between the highest and lowest comprehensive fuel consumption values ​​in multiple test results For comparison, if , the repeatability test passes; otherwise, the repeatability test fails.

[0088] Step S306: Fault detection.

[0089] Among them, the embodiment of the present application compares the actual fuel consumption measured by the ammonia flow meter, and determines that the vehicle has no fault when the predicted fuel consumption is basically consistent with the actual fuel consumption.

[0090] Embodiment 2: The embodiment of the present application determines the fault detection result when a vehicle fault occurs by measuring the fuel consumption of the vehicle equipped with an ammonia hydrogen engine. The main steps are: Step S301: measuring ammonia purity and fuel density.

[0091] Among them, the embodiments of the present application can measure ammonia purity and fuel density according to the methods of GB / T 8570.2-2010 and GB / T 37244-2018.

[0092] Step S302: Driving condition selection.

[0093] Step S303: Record driving data.

[0094] Step S304: Calculate fuel consumption.

[0095] Among them, the embodiment of the present application uses an ammonia-hydrogen engine, and when the reducing agent information includes liquid ammonia data, the predicted fuel consumption is calculated using the first predicted fuel consumption calculation formula.

[0096] Step S305: Calculate the degree of repetition.

[0097] Step S306: Fault detection.

[0098] Among them, the embodiment of the present application compares the actual fuel consumption measured by the ammonia flow meter, and when the predicted fuel consumption is much smaller than the actual fuel consumption measured by the ammonia flow meter, determines that the fault detection result when the vehicle fails is a leakage fault.

[0099] According to the vehicle fault detection method based on fuel consumption proposed in the embodiment of the present application, the predicted fuel consumption of the engine fuel can be calculated first, and then the fault detection result when the vehicle fails can be determined by judging the size of the predicted fuel consumption and the actual fuel consumption. By considering the reductant information in the vehicle post-processing device, the fuel consumption of the engine can be predicted more accurately. By setting the first threshold and the second threshold as the basis for judging the fault, the abnormal change of fuel consumption can be discovered in time, which helps to quickly locate the fault point and improve the maintenance efficiency. It is simple and easy to implement. Therefore, the problem in the related technology that the judgment conditions are complex and the system needs to have a high processing power and response speed, and these judgment conditions may not cover all possible fault conditions, resulting in missed detection, and it is even more impossible to cope with various complex working conditions and environmental conditions.

[0100] Next, a vehicle fault detection device based on fuel consumption according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0101] Figure 4 It is a block diagram of a vehicle fault detection device based on fuel consumption provided according to an embodiment of the present application.

[0102] like Figure 4 As shown, the vehicle fault detection device 40 based on fuel consumption includes: a first calculation module 401 , a judgment module 402 , a first determination module 403 and a second determination module 404 .

[0103] The first calculation module 401 is used to calculate the predicted fuel consumption of the engine fuel based on the reducing agent information of the reducing agent in the vehicle post-processing device.

[0104] The judgment module 402 is used to judge whether the predicted fuel consumption is greater than the actual fuel consumption of the engine fuel.

[0105] The first determination module 403 is used to determine that the fault detection result when a vehicle fails is a flow meter failure or a test bench failure based on the predicted fuel consumption when the predicted fuel consumption is greater than the actual fuel consumption of the engine fuel and the difference between the predicted fuel consumption and the actual fuel consumption is greater than a first threshold.

[0106] The second determination module 404 is used to determine that the fault detection result is a leakage fault, a sensor fault or a test bench fault based on the predicted fuel consumption when the predicted fuel consumption is less than the actual fuel consumption and the difference between the predicted fuel consumption and the actual fuel consumption is less than a second threshold.

[0107] Optionally, in one embodiment of the present application, the first calculation module 401 includes: a first calculation unit and a second calculation unit.

[0108] The first calculation unit is used to calculate the predicted fuel consumption based on the first predicted fuel consumption calculation formula when the reducing agent information includes liquid ammonia data.

[0109] The second calculation unit is used to calculate the predicted fuel consumption based on the second predicted fuel consumption calculation formula when the reducing agent information includes urea data.

[0110] Optionally, in one embodiment of the present application, it further includes: an acquisition module, a detection module and a second calculation module.

[0111] The acquisition module is used to obtain the ammonia purity and fuel density in the engine fuel before calculating the predicted fuel consumption of the engine fuel.

[0112] Detection module, used to detect density and concentration, The density and concentration of density and concentration.

[0113] The second calculation module is used to calculate density and concentration, The density and concentration of The density and concentration of the engine fuel exhaust are calculated respectively. Emission mass per unit mileage, exhaust gas Emission mass per unit mileage and exhaust gas Emissions per unit mileage.

[0114] Optionally, in one embodiment of the present application, the first predicted fuel consumption calculation formula may be, but is not limited to: , The second predicted fuel consumption calculation formula may be, but is not limited to,: , in, The fuel consumption of the test vehicle, in m 3 / 100km; is the number of trials performed, ; is the ammonia purity of the fuel expressed as mole fraction or volume fraction, unit: %; It is the fuel density at standard reference conditions of 0℃ and 101.325kPa, in kg / m 3 ; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the Test In The injection amount per unit mileage is in g / km; For the Test The injection amount of urea aqueous solution per unit mileage, in g / km; is the mass fraction of hydrogen atoms in the urea aqueous solution to the total mass; is the ammonia fuel coefficient.

[0115] Optionally, in one embodiment of the present application, the first calculation module 401 includes: a detection unit, a third calculation unit and a determination unit.

[0116] Among them, the detection unit is used to detect the driving condition of the vehicle.

[0117] The third calculation unit is used to calculate at least one initial fuel consumption of the vehicle engine fuel in different speed ranges based on the driving condition and the reducing agent information.

[0118] The determining unit is configured to determine a predicted fuel consumption based on at least one initial fuel consumption.

[0119] It should be noted that the above explanation of the embodiment of the vehicle fault detection method based on fuel consumption is also applicable to the vehicle fault detection device based on fuel consumption of this embodiment, and will not be repeated here.

[0120] According to the vehicle fault detection device based on fuel consumption proposed in the embodiment of the present application, the predicted fuel consumption of the engine fuel can be calculated first, and then the fault detection result when the vehicle fails can be determined by judging the size of the predicted fuel consumption and the actual fuel consumption. By considering the reductant information in the vehicle post-processing device, the fuel consumption of the engine can be predicted more accurately. By setting the first threshold and the second threshold as the basis for judging the fault, the abnormal change of fuel consumption can be discovered in time, which helps to quickly locate the fault point and improve the maintenance efficiency. It is simple and easy to implement. Therefore, the problem in the related technology that the judgment conditions are complex and the system needs to have a high processing power and response speed, and these judgment conditions may not cover all possible fault conditions, resulting in missed detection, and it is even more impossible to cope with various complex working conditions and environmental conditions.

[0121] Figure 5 This is a schematic diagram of the structure of a vehicle provided according to an embodiment of the present application. The vehicle may include: A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0122] When the processor 502 executes the program, the vehicle fault detection method based on fuel consumption provided in the above embodiment is implemented.

[0123] Furthermore, the vehicle also includes: The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0124] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0125] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0126] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0127] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0128] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0129] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned vehicle fault detection method based on fuel consumption.

[0130] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed, implements the above-mentioned vehicle fault detection method based on fuel consumption.

[0131] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0132] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0133] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0134] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection with one or N wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0135] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of multiple of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0136] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0137] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0138] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A vehicle fault detection method based on fuel consumption, characterized in that: The following steps are involved: calculating predicted fuel consumption of engine fuel based on reducing agent information of a reducing agent in an aftertreatment device of the vehicle; determining whether the predicted fuel consumption is greater than an actual fuel consumption of the engine fuel; If the predicted fuel consumption is greater than the actual fuel consumption of the engine fuel, and the difference between the predicted fuel consumption and the actual fuel consumption is greater than a first threshold, determining based on the predicted fuel consumption that the fault detection result when the vehicle fails is a flow meter failure or a test bench failure; If the predicted fuel consumption is less than the actual fuel consumption, and the difference between the predicted fuel consumption and the actual fuel consumption is less than a second threshold, the fault detection result is determined to be a leakage fault, a sensor fault, or a test bench fault based on the predicted fuel consumption.

2. The method according to claim 1, characterized in that The method of calculating the predicted fuel consumption of the engine fuel based on the reducing agent information of the reducing agent in the vehicle post-processing device includes: When the reducing agent information includes liquid ammonia data, the predicted fuel consumption is calculated based on a first predicted fuel consumption calculation formula; When the reducing agent information includes urea data, the predicted fuel consumption is calculated based on a second predicted fuel consumption calculation formula.

3. The method according to claim 1, characterized in that Before calculating the predicted fuel consumption of the engine fuel, the method further includes: Obtaining the purity of ammonia and the fuel density in the engine fuel; Detection of exhaust gas density and concentration, The density and concentration of density and concentration; According to the The density and concentration of The density and concentration and The density and concentration of the engine fuel exhaust are calculated respectively. Emission mass per unit mileage, exhaust gas Emission mass per unit mileage and exhaust gas Emissions per unit mileage.

4. The method according to claim 2, characterized in that: in, The first predicted fuel consumption calculation formula is: ， The second predicted fuel consumption calculation formula is: ， in, The fuel consumption of the test vehicle, in m 3 / 100km; is the number of trials performed, ; is the ammonia purity of the fuel expressed as mole fraction or volume fraction, unit: %; It is the fuel density at standard reference conditions of 0℃ and 101.325kPa, in kg / m 3 ; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the The exhaust gas in the test Unit mileage mass, unit is g / km; For the Selective catalytic reduction technology In The injection amount per unit mileage is in g / km; For the Test The injection amount of urea aqueous solution per unit mileage, in g / km; is the mass fraction of hydrogen atoms in the urea aqueous solution to the total mass; is the ammonia fuel coefficient.

5. The method according to claim 1, characterized in that The method of calculating the predicted fuel consumption of the engine fuel based on the reducing agent information of the reducing agent in the vehicle post-processing device includes: detecting a driving condition of the vehicle; Calculating at least one initial fuel consumption of the vehicle engine fuel in different speed intervals based on the driving condition and the reducing agent information; The predicted fuel consumption is determined based on the at least one initial fuel consumption.

6. A vehicle fault detection device based on fuel consumption, characterized in that: include: a calculation module for calculating a predicted fuel consumption of an engine fuel based on the reducing agent information of the reducing agent in the vehicle aftertreatment device; A judging module, used for judging whether the predicted fuel consumption is greater than the actual fuel consumption of the engine fuel; a first determination module, configured to determine, based on the predicted fuel consumption, that a fault detection result when the vehicle fails is a flow meter failure or a test bench failure when the predicted fuel consumption is greater than an actual fuel consumption of the engine fuel and a difference between the predicted fuel consumption and the actual fuel consumption is greater than a first threshold; The second determination module is used to determine that the fault detection result is a leakage fault, a sensor fault or a test bench fault based on the predicted fuel consumption when the predicted fuel consumption is less than the actual fuel consumption and the difference between the predicted fuel consumption and the actual fuel consumption is less than a second threshold.

7. The device according to claim 6, characterized in that The computing module comprises: a first calculation unit, configured to calculate the predicted fuel consumption based on a first predicted fuel consumption calculation formula when the reducing agent information includes liquid ammonia data; The second calculation unit is used to calculate the predicted fuel consumption based on a second predicted fuel consumption calculation formula when the reducing agent information includes urea data.

8. A vehicle, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the vehicle fault detection method based on fuel consumption as described in any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the vehicle fault detection method based on fuel consumption as described in any one of claims 1 to 5.

10. A computer program product, characterized in that It comprises a computer program, which, when executed, is used to implement the vehicle fault detection method based on fuel consumption as claimed in any one of claims 1 to 5.

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