Fault detection method and device of engine, vehicle and program product

Abstract

The invention discloses an engine fault detection method and device, a vehicle and a program product. The method comprises the steps that in response to the running state of an engine of the vehicle, running state parameters and at least two running index parameters of the engine are obtained, the running state parameters are used for representing and describing the current working condition of the engine, and the different running index parameters are used for representing the current values of different performance indexes of the engine under the current working condition; based on the operation state parameter and the operation index parameter, determining a preliminary fault detection result corresponding to the operation index parameter, the preliminary fault detection result being used for representing whether the operation index parameter is in a preset normal range; and determining a target fault detection result based on the weights corresponding to the at least two operation index parameters and the initial fault detection results corresponding to the at least two operation index parameters. According to the invention, the technical problem of low fault detection accuracy of the engine in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicles, in particular to an engine fault detection method and device, a vehicle and a program product. BACKGROUND

[0002] In the context of the rapid development of the vehicle industry today, the engine as the heart of the vehicle, its health status is directly related to the performance, safety and economy of the vehicle. The traditional engine fault detection mostly relies on manual experience, however, with the complication of engine design and the progress of technology, this detection method gradually exposes limitations, especially in the face of diversified fault modes and subtle performance changes, its accuracy and reliability are greatly reduced, thereby leading to low engine fault detection accuracy in related technologies.

[0003] In view of the above problems, no effective solution has been proposed so far. SUMMARY

[0004] The embodiments of the present application provide an engine fault detection method, device, vehicle and program product to at least solve the technical problem of low engine fault detection accuracy in related technologies.

[0005] According to an aspect of the embodiments of the present application, an engine fault detection method is provided, comprising: in response to the engine of a vehicle being in a running state, obtaining an operating state parameter of the engine and at least two operating indicator parameters, wherein the operating state parameter is used to represent the current working condition of the engine, and different operating indicator parameters are used to represent the current values of different performance indicators of the engine under the current working condition; determining a preliminary fault detection result corresponding to the operating indicator parameter based on the operating state parameter and the operating indicator parameter, wherein the preliminary fault detection result is used to indicate whether the operating indicator parameter is within a preset normal range; determining a target fault detection result based on the weights corresponding to the at least two operating indicator parameters and the preliminary fault detection results corresponding to the at least two operating indicator parameters, wherein the target fault detection result is used to indicate whether the engine is in a fault state.

[0006] Further, determining the preliminary fault detection result corresponding to the operating indicator parameter based on the operating state parameter and the operating indicator parameter comprises: determining a target preset three-dimensional coordinate system corresponding to a target parameter type of the operating indicator parameter from a plurality of preset three-dimensional coordinate systems based on the target parameter type, wherein different preset three-dimensional coordinate systems are used to detect whether operating indicator parameters of different parameter types are within a preset normal range; inputting the operating state parameter and the operating indicator parameter into the target preset three-dimensional coordinate system for comparison to obtain the preliminary fault detection result corresponding to the operating indicator parameter.

[0007] Further, the running state parameter and the running index parameter are input into a target preset three-dimensional coordinate system for comparison to obtain a preliminary fault detection result corresponding to the running index parameter, including: mapping the running state parameter into the target preset three-dimensional coordinate system to obtain a preset normal range corresponding to the running index parameter; comparing the running index parameter with the preset normal range to obtain the preliminary fault detection result.

[0008] Further, based on the weight corresponding to the at least two running index parameters and the preliminary fault detection result corresponding to the at least two running index parameters, a target fault detection result is determined, including: based on the weight corresponding to the at least two running index parameters and the at least two preliminary fault detection results, a comprehensive fault detection result is determined; based on a preset credibility threshold, the comprehensive fault detection result is judged to obtain the target fault detection result, wherein the preset credibility threshold is used to judge the reliability of the comprehensive fault detection result, and the target fault detection result is used to indicate whether the comprehensive fault detection result exceeds the preset credibility threshold.

[0009] Further, based on the weight corresponding to the at least two running index parameters and the preliminary fault detection result corresponding to the at least two running index parameters, a comprehensive fault detection result is determined, including: based on the parameter type, the weight corresponding to the running index parameter is determined; the weight corresponding to the at least two running index parameters and the preliminary fault detection result corresponding to the at least two running index parameters are weighted to obtain the comprehensive fault detection result.

[0010] Further, based on the preset credibility threshold, the comprehensive fault detection result is judged to obtain the target fault detection result, including: in response to the comprehensive fault detection result exceeding the preset credibility threshold, it is determined that the target fault detection result is that the engine is in a fault state; in response to the comprehensive fault detection result not exceeding the preset credibility threshold, it is determined that the target fault detection result is that the engine is not in a fault state.

[0011] According to another aspect of the embodiment of the application, a fault detection device of an engine is also provided, including: an acquisition module, configured to acquire a running state parameter and at least two running index parameters of an engine in response to the engine of a vehicle being in a running state, wherein the running state parameter is used to indicate a current working condition of the engine, and different running index parameters are used to indicate current values of different performance indexes of the engine in the current working condition; a first determination module, configured to determine a preliminary fault detection result corresponding to the running index parameter based on the running state parameter and the running index parameter, wherein the preliminary fault detection result is used to indicate whether the running index parameter is in a preset normal range; and a second determination module, configured to determine a target fault detection result based on the weight corresponding to the at least two running index parameters and the preliminary fault detection result corresponding to the at least two running index parameters, wherein the target fault detection result is used to indicate whether the engine is in a fault state.

[0012] According to another aspect of the embodiments of the present application, a vehicle is also provided, comprising: a memory storing an executable program; and a processor configured to execute the program, wherein the program, when executed, implements the method in the embodiments of the present application.

[0013] According to another aspect of the embodiments of the present application, a computer readable storage medium is also provided, comprising a stored executable program, wherein the executable program, when executed, controls a device in which the computer readable storage medium is located to implement the method in the embodiments of the present application.

[0014] According to another aspect of the embodiments of the present application, a computer program product is also provided, comprising a computer program which, when executed by a processor, implements the method in the embodiments of the present application.

[0015] According to another aspect of the embodiments of the present application, a computer program product is also provided, comprising a non-volatile computer readable storage medium storing a computer program which, when executed by a processor, implements the method in the embodiments of the present application.

[0016] According to another aspect of the embodiments of the present application, a computer program is also provided which, when executed by a processor, implements the method in the embodiments of the present application.

[0017] In the embodiment of the present application, when the engine of the vehicle is in a running state, the running state parameter of the engine and at least two running index parameters are acquired; then, based on the running state parameter and the running index parameter, a preliminary fault detection result corresponding to the running index parameter is determined; finally, based on the weight corresponding to at least two running index parameters and the preliminary fault detection result corresponding to at least two running index parameters, a target fault detection result is determined. It is easy to note that the present application can first determine the current working condition of the engine by acquiring the running state parameter of the engine, and can determine the current values of different performance indicators of the engine under the current working condition by acquiring at least two running index parameters, thereby widening the perspective of fault detection and improving the comprehensiveness of fault detection; then, at least two preliminary fault detection results for reflecting whether different running index parameters are in a preset normal range are obtained through the running state parameter and the running index parameter; finally, the weight corresponding to at least two running index parameters is assigned to the contribution degree of different running index parameters to engine fault detection, and the weight and at least two preliminary fault detection results are weighted and fused to obtain the target fault detection result. Through the weighted fusion of the weight and the preliminary fault detection result, it can be ensured that the target fault detection result comprehensively considers the dynamic influence of all indicators, avoids misdiagnosis caused by a single indicator exception, realizes high-precision intelligent identification and early warning of engine faults, achieves the purpose of accurately detecting engine faults, thereby realizing the technical effect of significantly improving the fault detection accuracy, and further solving the technical problem of low fault detection accuracy of the engine in the related art. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are included to provide a further understanding of the present application and are incorporated in and constitute a part of this application, illustrate embodiments of the present application and serve to explain the present application. In the drawings:

[0019] Figure 1 is a flow chart of an engine fault detection method according to an embodiment of the present application;

[0020] Figure 2 is a schematic diagram of an engine fault detection device according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order for those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0022] It is to be understood that the terminology "first", "second" and the like used in the specification and the claims of the application as well as the appended drawings is merely used for distinguishing between similar objects and does not necessarily imply a specific order or chronology. It is to be understood that the use of the term "about" along with a value or range of values of a given property, such as a dimension, weight, time, etc., is intended to encompass not only the recited value or range of values, but also the value or range of values plus or minus 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20% or more of the recited value or range of values, as appropriate. Moreover, the use of the term "about" is intended to encompass not only the recited value or range of values, but also the value or range of values plus or minus 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20% or more of the recited value or range of values, as appropriate. It is to be understood that the term "including", used in the specification and the claims, should not be interpreted as being restricted to the listed items only. In other words, "including" or "comprising" should not be interpreted as being confined to the means listed subsequent to such term only. In other words, the term "including" or "comprising" should not be interpreted as implying that the listed items are the only available items. On the contrary, any item not listed should also be potentially included in the scope of the present application.

[0023] According to an embodiment of the present application, there is provided an embodiment of a method for detecting faults of an engine. It is to be understood that the steps illustrated in the flowcharts of the drawings can be performed in a computer system such as a set of computer-executable instructions, and although the logical flow of the steps is shown in the flowcharts, in some cases, the steps shown or described can be performed in a different order than that shown.

[0024] Figure 1 is a flowchart of a method for detecting faults of an engine according to an embodiment of the present application, as shown in Figure 1 The method comprises the following steps:

[0025] In step S102, in response to the engine of the vehicle being in an operating state, an operating state parameter of the engine and at least two operating index parameters are obtained, wherein the operating state parameter is used to represent the current working condition of the engine, and different operating index parameters are used to represent the current values of different performance indexes of the engine under the current working condition.

[0026] The vehicle can be a mobile device equipped with a power source (such as an internal combustion engine, an electric motor) and capable of carrying passengers or goods for transportation. The type of vehicle can include but is not limited to electric vehicles, oil vehicles, hybrid vehicles, etc. The specific type of vehicle needs to be determined according to the actual control requirements, which is not limited here. The vehicle can be used to determine the type of engine that needs to be detected for faults and to preliminarily judge the state of the engine.

[0027] The engine can be an important component for providing power to the vehicle. The type of engine can include but is not limited to gasoline engine, diesel engine, turbocharged engine, etc. The specific type of engine needs to be determined according to the vehicle system design, which is not limited here. The engine can be used to convert the chemical energy of fuel into kinetic energy, thereby pushing the vehicle forward, while also affecting the acceleration, speed, fuel efficiency and emission performance of the vehicle.

[0028] The running state can be a state in which the engine is working. The running state can be used to determine that the engine is in a working state, and then actual working parameters are obtained on this basis to facilitate fault diagnosis of the engine.

[0029] The running state parameter can be a parameter used to describe the current running state of the engine. The running state parameter can include, but is not limited to, a speed, a load, a cooling water temperature, an oil pressure, a battery voltage, an intake air temperature, etc. The specific running state parameter needs to be determined according to actual requirements, which is not limited here. The running state parameter can be used to accurately reflect the current running state of the engine, and can also be used as reference data for determining the preset normal range of the running index parameter under the current working condition.

[0030] The running index parameter can be an index parameter reflecting the performance and health condition of the engine. The running index parameter can include, but is not limited to, a lambda correction factor, an exhaust gas temperature (exhaust temperature), a supercharging pressure, etc. The specific running index parameter needs to be determined according to the type of engine and actual requirements, which is not limited here. The running index parameter can be used to determine whether the engine is in a fault state.

[0031] The current working condition can be a running mode or state of the engine at a certain time point. The type of the current working condition can include, but is not limited to, idling, acceleration, deceleration, high-speed operation, and specific load, etc. The specific current working condition needs to be determined according to the actual running state, which is not limited here. The current working condition is the background environment for judging whether the running index parameter is normal or not. The reasonable range of the same index may be different under different working conditions, so it is necessary to evaluate the running index parameter under a specific working condition.

[0032] In an optional embodiment, when the engine of the vehicle is started and in a running state, the running state parameters of the engine are first obtained, which include, but are not limited to, a speed, a load, a cooling water temperature, etc. They collectively depict the current working condition of the engine, i.e., the running mode and working condition of the engine at the current time. At the same time, at least two running index parameters of the engine are obtained, such as a lambda correction factor, an exhaust gas temperature, a supercharging pressure, etc. These parameters directly reflect the performance and health condition of the engine under the current working condition. By obtaining the running state parameters and the at least two running index parameters of the engine, the current working condition of the engine can be accurately determined, and in addition, the at least two running index parameters can be used to detect faults of the engine from multiple angles, thereby improving the accuracy of engine fault detection.

[0033] In an alternative embodiment, when the engine starts and begins to operate, a series of built-in sensors and actuators initiate the data collection process to monitor the engine's status in real time. To obtain the operating state parameters and operating index parameters, sensors such as speed sensors are used to monitor engine speed, torque sensors to measure engine load, and temperature sensors to record cooling water temperature and exhaust gas temperature, etc. In addition, oxygen sensors are used to measure the lambda correction coefficient, i.e. the difference between the actual air-fuel ratio and the theoretical air-fuel ratio, and the boost pressure sensor monitors the additional intake pressure provided by the turbocharger or other superchargers. All these sensors will transmit real-time data to the vehicle-mounted computer or engine control unit, which processes and analyzes these data through pre-programmed algorithms, compares them with the multi-dimensional threshold model stored in the system, to determine whether the current working condition and corresponding performance indicators of the engine meet the expected normal range. This process not only relies on the high-precision collection of sensors, but also involves complex signal processing and data interpretation techniques, ensuring that the subtle changes in the engine's operating state and performance can be accurately captured at every moment of its operation, providing a solid data foundation for real-time fault diagnosis and preventive maintenance.

[0034] In step S104, based on the operating state parameters and the operating index parameters, a preliminary fault detection result corresponding to the operating index parameters is determined, wherein the preliminary fault detection result is used to indicate whether the operating index parameters are within a preset normal range.

[0035] The preliminary fault detection result can be the preliminary detection result obtained by comparing and analyzing at least two operating index parameters with the preset normal range. The type of preliminary fault detection result can include binary detection results and quantitative index (deviation) detection results, wherein the binary detection results include normal and abnormal results. The specific type of preliminary fault detection result needs to be determined according to the fault detection requirements, which is not limited here. The preliminary fault detection result can be used to provide a basis for subsequent fault confirmation and in-depth analysis, help to quickly identify potential performance problems or health risks, ensure timely measures to prevent fault escalation, and ensure driving safety.

[0036] The above-mentioned preset normal range can refer to the reasonable value interval that the operating index parameters should maintain under different working conditions. The types of preset normal range can include but are not limited to Lambda correction coefficient normal range, exhaust gas temperature (exhaust temperature) normal range, boost pressure normal range, and oil pressure normal range, etc. The type of preset normal range corresponds one-to-one to the type of operating index parameter, and the specific preset normal range needs to be determined according to the engine design specifications, performance tests, working condition simulations, etc. which are not limited here. The preset normal range can be used as a criterion for determining whether the operating index parameter is healthy.

[0037] In an optional embodiment, when the engine starts and runs, based on the real-time collected running state parameters and running index parameters, preliminary fault detection is rapidly carried out, which is a key link to ensure the performance and safety of the vehicle. The running state parameters, such as engine speed and load, are used to determine the current working condition of the engine, while the running index parameters, such as lambda correction coefficient, exhaust temperature (exhaust temperature) and supercharging pressure, directly reflect the performance of the engine in this working condition. By comparing the real-time measured values of the running index parameters with the preset normal range, any abnormal situation deviating from the standard can be immediately identified, and the corresponding preliminary fault detection results such as "lambda correction coefficient deviates from the normal range" or "supercharging pressure is lower than expected" are generated. These preliminary fault detection results not only can immediately alert the driver to the potential engine problem, but also provide precise fault positioning clues for maintenance personnel. The above real-time monitoring and rapid comparison analysis mechanism ensures the immediacy of fault warning, reduces the fault response time, at the same time, the fault detection based on multi-dimensional data improves the accuracy of diagnosis, reduces the false alarm rate, and enhances the reliability of the system.

[0038] Step S106, based on the weight corresponding to at least two running index parameters and the preliminary fault detection result corresponding to at least two running index parameters, determine the target fault detection result, wherein the target fault detection result is used to indicate whether the engine is in a fault state.

[0039] The above-mentioned weight can refer to the importance coefficient of each running index parameter in determining the target fault detection result. The weight type can include but is not limited to Lambda correction coefficient weight, exhaust temperature weight, supercharging pressure weight, etc., and the specific weight type needs to be determined according to the type of running index parameter. The weight can be used to reflect the relative influence of the index in the overall fault diagnosis. The weight ensures that when multiple performance indicators of the engine appear abnormal at the same time, the preliminary fault detection results can be weighted and fused according to the importance of the indicators and the reliability of the diagnosis, so as to more accurately judge the overall state of the engine.

[0040] The above-mentioned target fault detection result can refer to the comprehensive judgment after the weighted fusion of the preliminary fault detection result. The target fault detection result can include but is not limited to that the engine is in a fault state, the engine is not in a fault state, etc., and the detection result can be further subdivided based on actual needs. The specific target fault detection result needs to be determined according to the actual situation, which is not limited here. The target fault detection result can be used to provide clear fault information for the driver and maintenance personnel, guiding them to take appropriate measures.

[0041] The above fault state can refer to a situation where one or more operating index parameters of the engine are not within the preset normal range, resulting in a decline in engine performance or potential safety hazards. Identifying the engine fault state is the core goal of fault diagnosis, which determines whether timely maintenance is needed and what level of maintenance action to take.

[0042] In an optional embodiment, preliminary fault detection is first performed on the Lambda correction coefficient, exhaust gas temperature, boost pressure and other operating index parameters to obtain preliminary fault detection results reflecting whether these indicators deviate from the preset normal range. Subsequently, based on a deep understanding of the importance and reliability of each operating index parameter, a corresponding weight is assigned to each operating index parameter. These weights not only consider physical principles, but also incorporate statistical analysis of historical fault data, ensuring the dominant position of key indicators in diagnosis. Then, the preliminary fault detection results corresponding to at least two operating index parameters are weighted and calculated using the weights corresponding to the at least two operating index parameters, to obtain a target fault detection result that comprehensively reflects the current state of the engine. The determination of this result greatly enhances the accuracy and reliability of fault detection, avoiding misdiagnosis that may be caused by a single indicator anomaly. For example, a significant change in the lambda correction coefficient may indicate a combustion efficiency problem, while a decrease in boost pressure may be associated with a supercharger failure. Through weight fusion, these changes can be identified and evaluated simultaneously to form a comprehensive fault judgment. The above process of determining the target fault detection result in combination with the weights and preliminary fault detection results not only significantly improves the accuracy and timeliness of fault diagnosis, but also provides data support for maintenance strategies, enabling targeted preventive maintenance, avoiding cost waste caused by excessive maintenance, and reducing economic losses caused by fault downtime.

[0043] In an optional embodiment, firstly, the correlation and importance between each operating index parameter and engine failure are analyzed by AHP (Analytic Hierarchy Process) and entropy weight method to determine the weight of each operating index parameter. For example, the lambda correction coefficient may be given a higher weight because it is directly related to combustion efficiency, and the supercharging pressure, as an indicator reflecting the state of the intake system, also has a relatively high weight. Then, the preliminary fault detection results of at least two operating index parameters are multiplied by their respective weights to obtain weighted fault signals. All weighted fault signals are summarized and compared with a pre-set comprehensive fault judgment threshold. If the summarized weighted fault signals exceed the threshold, a target fault detection result is generated, indicating that the engine is in a failure state. Otherwise, it is determined that the engine is operating normally. This process combines weight distribution, threshold comparison and comprehensive decision-making to form a closed-loop fault monitoring and diagnosis system, which can quickly and accurately identify the health status of the engine, provide real-time fault warning information for the driver and maintenance personnel, and thus achieve early diagnosis and preventive maintenance of faults, significantly enhancing the reliability of the engine and the driving safety of the vehicle.

[0044] In the embodiment of the present application, when the engine of the vehicle is in an operating state, the operating state parameters and at least two operating index parameters of the engine are obtained; then, based on the operating state parameters and the operating index parameters, preliminary fault detection results corresponding to the operating index parameters are determined; finally, based on the weights corresponding to the at least two operating index parameters and the preliminary fault detection results corresponding to the at least two operating index parameters, a target fault detection result is determined. It is easy to note that the present application first obtains the operating state parameters of the engine to determine the current operating condition of the engine, and obtains at least two operating index parameters to determine the current values of different performance indicators of the engine under the current operating condition, thereby widening the perspective of fault detection and improving the comprehensiveness of fault detection; then, at least two preliminary fault detection results reflecting whether different operating index parameters are within a pre-set normal range are obtained through the operating state parameters and the operating index parameters; finally, the weights corresponding to the at least two operating index parameters are assigned to determine the contribution of different operating index parameters to engine fault detection, and the target fault detection result is obtained by weighting and fusing the weights and the at least two preliminary fault detection results. Through the weighting and fusion of the weights and the preliminary fault detection results, the target fault detection result can comprehensively consider the dynamic influence of all indicators, avoiding misdiagnosis caused by single indicator abnormality, achieving high-precision intelligent identification and early warning of engine failure, and achieving the purpose of accurately detecting engine failure, thereby realizing the technical effect of significantly improving the accuracy of fault detection, and further solving the technical problem of low accuracy of engine fault detection in related technologies.

[0045] Optionally, based on the running state parameter and the running index parameter, a preliminary fault detection result corresponding to the running index parameter is determined, including: based on a target parameter type of the running index parameter, a target preset three-dimensional coordinate system corresponding to the target parameter type is determined from a plurality of preset three-dimensional coordinate systems, wherein different preset three-dimensional coordinate systems are used to detect whether running index parameters of different parameter types are in a preset normal range; the running state parameter and the running index parameter are input into the target preset three-dimensional coordinate system for comparison to obtain the preliminary fault detection result corresponding to the running index parameter.

[0046] The target parameter type can refer to the type of the running index parameter currently being judged. The target parameter type corresponds to the running index parameter one by one, and based on the target parameter type, a target preset three-dimensional coordinate system corresponding to a certain running index parameter can be determined to complete the judgment of the certain running index parameter.

[0047] The target preset three-dimensional coordinate system can be a multi-dimensional analysis model used for fault detection. The types of the target preset three-dimensional coordinate system can include but are not limited to a Lambda correction coefficient three-dimensional coordinate system, an exhaust gas temperature three-dimensional coordinate system, and a boost pressure three-dimensional coordinate system. The specific target preset three-dimensional coordinate system needs to be determined according to the parameter type, which is not limited here. The target preset three-dimensional coordinate system takes the engine speed, the load, and a specific running index parameter as three dimensions to define the normal working range of the index parameter. Different parameter types correspond to different three-dimensional coordinate systems.

[0048] In an optional embodiment, first, one running index parameter is determined from at least two running index parameters (such as a Lambda correction coefficient, an exhaust gas temperature, and a boost pressure), and a target parameter type corresponding to the running index parameter is determined. Then, according to the target parameter type, a target preset three-dimensional coordinate system matching the target parameter type is selected from a plurality of preset three-dimensional coordinate system models for data comparison. Next, the real-time collected running state parameter and the running index parameter are input into the matched target preset three-dimensional coordinate system to judge whether the index parameter deviates from the preset normal range and generate a preliminary fault detection result. The selection based on the target parameter type and the analysis of the preset normal range in the target preset three-dimensional coordinate system can accurately distinguish different types of faults, avoid false positives and false negatives, and improve the accuracy of fault positioning. At the same time, through early warning and accurate diagnosis, further damage caused by not timely handling of the fault is avoided, and the cost caused by emergency repair and excessive maintenance is reduced.

[0049] For example, in a car equipped with a turbocharger system, real-time fault detection is crucial to ensure the safety of driving and the durability of the engine. In this scenario, the target parameter types can include, but are not limited to, turbocharger boost pressure, exhaust gas temperature, and lambda correction factor. At the same time, a plurality of preset three-dimensional coordinate systems for detecting the above target parameter types are established, including establishing a three-dimensional coordinate system for boost pressure, in which the X-axis represents engine speed, the Y-axis represents engine load, and the Z-axis represents boost pressure. This coordinate system defines the normal range of boost pressure under different engine speed and load conditions. A three-dimensional coordinate system for exhaust gas temperature is established, in which the X-axis represents speed, the Y-axis represents load, and the Z-axis represents exhaust gas temperature. This coordinate system defines the normal range of exhaust gas temperature under different engine speed and load conditions. A three-dimensional coordinate system for lambda correction factor is established, in which the X-axis and Y-axis represent speed and load respectively, and the Z-axis represents lambda correction factor. This coordinate system defines the normal range of lambda correction factor under different engine speed and load conditions.

[0050] On this basis, the target parameter type of the operating index parameter is determined, and the target preset three-dimensional coordinate system corresponding to the target parameter type is determined from the plurality of preset three-dimensional coordinate systems based on the target parameter type. These operating state parameters and operating index parameters are input into the respective target preset three-dimensional coordinate systems for comparison. During the comparison process, if any operating index parameter is found to be outside the preset normal range in its corresponding three-dimensional coordinate system, the generation of a preliminary fault detection result is triggered, indicating that a specific type of fault may exist.

[0051] For example, assume that at a certain time, the system monitors that the engine speed is 3000 RPM, the load is 50%, the boost pressure reading at this time is 0.8 bar, the exhaust gas temperature is 580°C, and the lambda correction factor is 1.1. According to the preset three-dimensional coordinate system, the boost pressure should be between 0.9 bar and 1.1 bar, the exhaust gas temperature should be below 600°C, and the lambda correction factor should be close to 1.0 (±0.05). However, the lambda correction factor deviates from the ideal range, suggesting that there may be a problem with the combustion efficiency or improper air-fuel ratio adjustment. Although the boost pressure is also slightly low, since the weight of the boost pressure in the system is lower than that of the lambda correction factor, the preliminary fault detection result focuses more on the warning of abnormal combustion efficiency. The above process combines the operating state parameters and operating index parameters with the preset three-dimensional coordinate system for comparison and analysis, achieving early warning of engine faults. The above values are only examples, and the specific values should be determined according to the actual situation, which is not limited here.

[0052] Optionally, the running state parameter and the running index parameter are input to a target preset three-dimensional coordinate system for comparison to obtain a preliminary fault detection result corresponding to the running index parameter, including: mapping the running state parameter into the target preset three-dimensional coordinate system to obtain a preset normal range corresponding to the running index parameter; comparing the running index parameter with the preset normal range to obtain the preliminary fault detection result.

[0053] In an optional embodiment, first, the real-time collected engine running state parameters, such as the speed and the load, are digitally mapped and projected onto the X and Y axes of the target preset three-dimensional coordinate system. The three-dimensional coordinate system is established through in-depth experimental research and data analysis, and the normal ranges of the running index parameters under various working conditions are preset, including the Lambda correction coefficient, the exhaust temperature, the supercharging pressure, etc., which constitute the monitoring dimension on the Z axis. Next, the real-time measured multiple running index parameters are compared with the corresponding preset normal ranges in the target preset three-dimensional coordinate system to obtain multiple preliminary fault detection results. Through real-time data mapping and automatic comparison with the preset three-dimensional coordinate system, the system can quickly identify any index change deviating from the normal range, ensuring the instantaneity and accuracy of the fault warning.

[0054] For example, assume that a high-performance car equipped with a turbocharged engine is driving on the road. In order to ensure the health of the engine and prevent potential faults, the intelligent fault detection system of the vehicle begins to monitor and perform the following key steps in real time:

[0055] First, the sensor array continuously monitors the engine's operating state parameters, such as the current speed (RPM) of 2500 and the engine load of 60%. When the system receives these operating state parameters, it maps them into a target preset three-dimensional coordinate system. In this coordinate system, the X-axis represents the speed, the Y-axis represents the load, and the Z-axis represents the boost pressure. Then, according to the current operating state (i.e., 2500 RPM and 60% load), the system queries the three-dimensional coordinate system to quickly locate and obtain the preset normal range of boost pressure corresponding to the current operating condition. For example, under this condition, the normal boost pressure range should be between 1.0 bar and 1.2 bar. At the same time, the sensor also monitors the real-time boost pressure value of 0.9 bar. The system compares this real-time measured boost pressure with the preset normal range obtained from the three-dimensional coordinate system. Since 0.9 bar is slightly lower than the lower limit of the normal range of 1.0 bar, the system marks this difference and considers it as an indicator of potential failure. Finally, based on the comparison analysis, the preliminary fault detection result shows that the boost pressure may be lower than expected, indicating that the turbocharger has a risk of functional decline. The system then generates a preliminary fault alarm, which transmits this information to the driver's instrument panel display, and records the fault log for subsequent in-depth analysis and maintenance. Accompanied by the generation of the preliminary fault detection result, the vehicle's intelligent fault detection system can also automatically adjust the parameters of the engine control unit, such as temporarily reducing the boost level, to prevent further damage to the engine, while recommending the nearest repair service point to the driver or providing remote fault diagnosis support to ensure the vehicle can safely reach the destination. The above values are only examples, and the specific values should be determined according to the actual situation, which is not limited here.

[0056] Through the above embodiments, it can be seen that mapping the operating state parameters to the target preset three-dimensional coordinate system and comparing them with the operating indicator parameters is an effective means to ensure the normal operation of the turbocharged engine under complex operating conditions. Not only can it instantly identify the slight changes in the performance of the turbocharger, but also can effectively prevent the escalation of faults through intelligent decision assistance, protect the engine from damage, and thus ensure driving safety.

[0057] Optionally, based on the weights corresponding to the at least two operating indicator parameters and the preliminary fault detection results corresponding to the at least two operating indicator parameters, the target fault detection result is determined, comprising: based on the weights corresponding to the at least two operating indicator parameters and the at least two preliminary fault detection results, a comprehensive fault detection result is determined; based on a preset credibility threshold, the comprehensive fault detection result is judged to obtain the target fault detection result, wherein the preset credibility threshold is used to judge the reliability of the comprehensive fault detection result, and the target fault detection result is used to indicate whether the comprehensive fault detection result exceeds the preset credibility threshold.

[0058] The comprehensive fault detection result can refer to diagnosing information of multiple operating index parameters being fused by weighting based on preliminary fault detection, forming a more comprehensive evaluation result of the engine health status. The comprehensive fault detection result can include but is not limited to weighted average result, classification result based on machine learning, fuzzy logic evaluation result, etc., and the specific comprehensive fault detection result needs to be determined according to different algorithm types, which is not limited here. The comprehensive fault detection result integrates the preliminary fault detection results of different indicators by weighted average or intelligent algorithm, so as to obtain an evaluation conclusion closer to the real fault status. The comprehensive fault detection result can be used to help the system reduce the probability of false positives and false negatives when dealing with complex fault scenarios, and provide more reliable fault prompts.

[0059] The preset reliability threshold can refer to a standard value preset for judging whether the comprehensive fault detection result is reliable enough. For high-risk fault types, the preset reliability threshold can be set higher to ensure that an alarm is only issued when the fault signal is very clear. For low-risk but timely handling fault types, the threshold can be relatively low to facilitate early warning. Therefore, the preset reliability threshold needs to be determined according to different fault types and diagnostic parameters, which is not limited here. The preset reliability threshold can be used to prevent the system from producing false positives due to noise interference or data anomalies, to help the system distinguish between real faults and potential misdiagnoses, and to improve the accuracy of fault detection.

[0060] In an optional embodiment, at least two operating index parameters such as Lambda correction coefficient, exhaust gas temperature, etc. are first collected, and a comprehensive fault detection result is determined based on the preliminary fault detection result and the predefined weight using data fusion technology. This result integrates the monitoring data of multiple independent indicators, improving the comprehensiveness and accuracy of fault detection. Subsequently, the preset reliability threshold is used to further judge the comprehensive fault detection result to verify the reliability of the detection result. The reliability threshold is determined based on historical data analysis, vehicle manufacturer recommendations and industry standards, and it serves as a filtering mechanism to ensure that fault alarms are only triggered when the comprehensive detection result reaches a certain confidence level, avoiding false positives caused by noise or temporary fluctuations and reducing unnecessary maintenance costs and driver anxiety. This process can quickly identify and confirm abnormal changes in engine performance, ensuring timely response measures and avoiding potential serious faults. At the same time, through the reliability threshold judgment, the system effectively distinguishes between real faults and non-fault events, significantly reducing the probability of false positives and improving the accuracy of fault warning.

[0061] For example, consider a modern car equipped with an advanced engine health monitoring system. During a long drive, the system uses two operating indicator parameters, Lambda correction factor and exhaust gas temperature, to detect engine faults.

[0062] The system first obtains preliminary fault detection results for each of the two operating indicator parameters by comparing their real-time monitoring values against pre-set normal ranges. For example, the Lambda correction factor is 1.03, while the normal range is set between 0.95 and 1.05. Meanwhile, the exhaust gas temperature reading is 640°C, while the pre-set upper safety limit is 650°C. Although both indicators are not significantly deviated from the normal range, the slight increase in the Lambda correction factor may indicate a potential fault in the exhaust gas recirculation valve (EGR).

[0063] In the fault detection algorithm, the Lambda correction factor is assigned a higher weight of 0.6 due to its direct reflection of combustion efficiency. The exhaust gas temperature is assigned a lower weight of 0.4 due to its impact on the engine cooling system. The system then obtains a comprehensive fault detection result by performing a weighted average of the preliminary fault detection results based on the above-mentioned weights. In this example, even though both indicators only show slight abnormalities, the weighted comprehensive result may still point to a potential fault signal, especially when the Lambda correction factor has a higher weight.

[0064] Subsequently, the system compares the comprehensive fault detection result against a pre-set confidence threshold, which is set at 0.7, to ensure that only fault signals reaching a certain confidence level are adopted by the system. If the calculated comprehensive result score is higher than 0.7, the system determines that the detection result is reliable enough to indicate a possible real engine fault. In this example, if the comprehensive fault detection result indeed exceeds the pre-set confidence threshold of 0.7, the system generates a target fault detection result, which alerts the driver and maintenance team: "Attention: Preliminary signs of engine knock are detected. Please check the exhaust gas recirculation system as soon as possible." This not only provides an immediate fault warning to the driver but also guides the subsequent repair action, avoiding unnecessary comprehensive checks or emergency stops. The numerical values in the above example are for illustration only, and the specific values should be determined according to the actual situation, which is not limited herein.

[0065] Optionally, determining the comprehensive fault detection result based on the weights corresponding to the at least two operating indicator parameters and the preliminary fault detection results corresponding to the at least two operating indicator parameters comprises: determining the weights corresponding to the operating indicator parameters based on the parameter types; and performing weighted calculation on the weights corresponding to the at least two operating indicator parameters and the preliminary fault detection results corresponding to the at least two operating indicator parameters to obtain the comprehensive fault detection result.

[0066] The parameter type can refer to a parameter type corresponding to the operation index parameter. The parameter type can include, but is not limited to, a lambda correction factor, an exhaust gas temperature, a supercharging pressure, and the like. The specific parameter type needs to be determined according to the operation index parameter, which is not limited here. The parameter type can be used to determine the weight corresponding to each operation index parameter.

[0067] In an optional embodiment, the weight corresponding to the operation index parameter is first determined according to the parameter type, i.e., according to the nature of the monitoring data and the depth of the influence on the engine performance. The lambda correction factor, the exhaust gas temperature, and the supercharging pressure are given a higher weight because of their key role in engine thermodynamic efficiency monitoring, while other auxiliary indicators are assigned weights according to their contribution to fault diagnosis. Next, the system performs a weighted calculation of the preliminary fault detection results corresponding to the weights of at least two operation index parameters, which ensures that the fault detection is not only comprehensive but also highlights the most likely source of the fault. For example, when the lambda correction factor shows a slight anomaly and the supercharging pressure has a significant drop, even if the single preliminary fault detection result is not enough to trigger an alarm, the comprehensive fault detection result can reveal the underlying Miller cycle problem through weighted calculation, thereby providing early warning and avoiding potential engine damage. Through the weighted calculation process based on the parameter type to determine the weight, combined with the preliminary fault detection result of the operation index parameter, the intelligent fault diagnosis system realizes the fine management of the engine health status, effectively improves the accuracy of fault warning, and realizes the comprehensive guarantee of driving experience and vehicle safety.

[0068] Optionally, the comprehensive fault detection result is judged based on a preset credibility threshold to obtain a target fault detection result, including: in response to the comprehensive fault detection result exceeding the preset credibility threshold, determining that the target fault detection result is that the engine is in a fault state; and in response to the comprehensive fault detection result not exceeding the preset credibility threshold, determining that the target fault detection result is that the engine is not in a fault state.

[0069] In an optional embodiment, after the comprehensive fault detection result is calculated by weighting, the comprehensive fault detection result is compared with a preset confidence threshold to determine the current state of the engine. In response to the comprehensive fault detection result exceeding the preset confidence threshold, it means that the abnormal signal combination detected by the system has reached a certain confidence level, which is sufficient to infer that the engine may have a fault. In this case, the system generates a target fault detection result indicating that the engine is in a fault state, and immediately notifies the driver through the vehicle display or mobile application, suggesting taking necessary safety measures or arranging professional inspection, so as to avoid potential driving risks. In response to the comprehensive fault detection result not exceeding the preset confidence threshold, if the calculated comprehensive result indicates that although there are some indicators deviating from the normal range, they have not formed sufficient fault evidence. At this time, the target fault detection result of the system is that the engine is not in a fault state, which avoids false positives caused by slight fluctuations in data, reduces unnecessary worries of the driver and non-planned maintenance of the vehicle, thereby ensuring normal operation and service quality of the vehicle. The intelligent judgment process through the preset confidence threshold can effectively distinguish between real fault signals and accidental data fluctuations, avoid ineffective or premature maintenance activities, save maintenance costs, and prolong the normal use period of the engine.

[0070] According to an embodiment of the present application, an embodiment of an engine fault detection device is provided. It should be noted that the device can be used to execute the above-mentioned engine fault detection method, and the specific implementation method and preferred application scenario are the same as those of the above-mentioned embodiment, which will not be repeated here.

[0071] Figure 2 is a schematic diagram of an engine fault detection device according to an embodiment of the present application, as shown in Figure 2 The device comprises the following: an acquisition module 202, a first determination module 204, and a second determination module 206.

[0072] The acquisition module 202 is configured to acquire an operating state parameter of the engine and at least two operating indicator parameters in response to the engine of the vehicle being in an operating state, wherein the operating state parameter is used to represent the current working condition of the engine, and different operating indicator parameters are used to represent the current values of different performance indicators of the engine under the current working condition; the first determination module 204 is configured to determine a preliminary fault detection result corresponding to the operating indicator parameter based on the operating state parameter and the operating indicator parameter, wherein the preliminary fault detection result is used to indicate whether the operating indicator parameter is within a preset normal range; and the second determination module 206 is configured to determine a target fault detection result based on the weights corresponding to the at least two operating indicator parameters and the preliminary fault detection results corresponding to the at least two operating indicator parameters, wherein the target fault detection result is used to indicate whether the engine is in a fault state.

[0073] Optionally, the first determining module comprises: a unit configured to determine, based on the target parameter type of the running index parameter, a target preset three-dimensional coordinate system corresponding to the target parameter type from a plurality of preset three-dimensional coordinate systems, wherein different preset three-dimensional coordinate systems are used to detect whether the running index parameter of different parameter types is in a preset normal range; and a unit configured to input the running state parameter and the running index parameter into the target preset three-dimensional coordinate system for comparison to obtain a preliminary fault detection result corresponding to the running index parameter.

[0074] Optionally, the first determining module further comprises: a unit configured to map the running state parameter into the target preset three-dimensional coordinate system to obtain a preset normal range corresponding to the running index parameter; and a unit configured to compare the running index parameter with the preset normal range to obtain the preliminary fault detection result.

[0075] Optionally, the second determining module comprises: a unit configured to determine a comprehensive fault detection result based on the weights corresponding to the at least two running index parameters and the at least two preliminary fault detection results; and a unit configured to judge the comprehensive fault detection result based on a preset credibility threshold to obtain a target fault detection result, wherein the preset credibility threshold is used to judge the reliability of the comprehensive fault detection result, and the target fault detection result is used to indicate whether the comprehensive fault detection result exceeds the preset credibility threshold.

[0076] Optionally, the second determining module further comprises: a unit configured to determine the weights corresponding to the running index parameters based on the parameter types; and a unit configured to perform weighted calculation on the weights corresponding to the at least two running index parameters and the preliminary fault detection results corresponding to the at least two running index parameters to obtain the comprehensive fault detection result.

[0077] Optionally, the second determining module further comprises: a unit configured to determine, in response to the comprehensive fault detection result exceeding the preset credibility threshold, that the target fault detection result is that the engine is in a fault state; and a unit configured to determine, in response to the comprehensive fault detection result not exceeding the preset credibility threshold, that the target fault detection result is that the engine is not in a fault state.

[0078] Embodiments of the present application also provide a vehicle, comprising: a memory storing an executable program; and a processor configured to run the program, wherein the program, when running, performs the method in the embodiments of the present application.

[0079] Embodiments of the present application also provide a computer-readable storage medium comprising a stored executable program, wherein the executable program, when running, controls a device in which the computer-readable storage medium is located to perform the method in the embodiments of the present application.

[0080] The embodiments of the present application further provide a computer program product comprising a computer program which, when executed by a processor, implements the method in each of the embodiments of the present application.

[0081] The embodiments of the present application further provide a computer program product comprising a non-volatile computer readable storage medium for storing a computer program which, when executed by a processor, implements the method in each of the embodiments of the present application.

[0082] The embodiments of the present application further provide a computer program which, when executed by a processor, implements the method in each of the embodiments of the present application.

[0083] In the above-described embodiments of the present application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0084] In several embodiments provided in the present application, it should be understood that the disclosed technical contents can be implemented by other manners. Among them, the apparatus embodiment described above is only schematic, for example, the division of the units can be a logical function division, and in actual implementation, there can be another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units or modules shown or discussed can be indirect coupling or communication connection through some interfaces, units or modules, which can be electrical or other forms.

[0085] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the present embodiment.

[0086] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of software functional unit.

[0087] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to make a computer device (which can be a personal computer, a server or a network device, etc.) execute all or part of the steps of the methods described in various embodiments of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0088] The above is only the preferred embodiment of the present application, it should be pointed out that, for those skilled in the art, without departing from the principles of the present application, can make a number of improvements and refinements, these improvements and refinements should also be considered as the protection scope of the present application.

Claims

1. An engine failure detection method characterized by comprising: The method comprises the following steps: in response to the engine of the vehicle being in an operating state, obtaining an operating state parameter of the engine and at least two operating index parameters, wherein the operating state parameter is used to represent the current working condition of the engine, and different operating index parameters are used to represent the current values of different performance indicators of the engine under the current working condition; based on the operating state parameter and the operating index parameter, determining a preliminary fault detection result corresponding to the operating index parameter, wherein the preliminary fault detection result is used to indicate whether the operating index parameter is within a preset normal range; based on the weights corresponding to at least two operating index parameters and the preliminary fault detection results corresponding to at least two operating index parameters, determining a target fault detection result, wherein the target fault detection result is used to indicate whether the engine is in a fault state.

2. The engine failure detection method according to claim 1, characterized by, Based on the operating state parameter and the operating index parameter, the preliminary fault detection result corresponding to the operating index parameter is determined, comprising: based on the target parameter type of the operating index parameter, determining a target preset three-dimensional coordinate system corresponding to the target parameter type from a plurality of preset three-dimensional coordinate systems, wherein different preset three-dimensional coordinate systems are used to detect whether operating index parameters of different parameter types are within the preset normal range; inputting the operating state parameter and the operating index parameter into the target preset three-dimensional coordinate system for comparison to obtain the preliminary fault detection result corresponding to the operating index parameter.

3. The engine failure detection method according to claim 2, characterized by, Inputting the operating state parameter and the operating index parameter into the target preset three-dimensional coordinate system for comparison to obtain the preliminary fault detection result corresponding to the operating index parameter, comprising: mapping the operating state parameter into the target preset three-dimensional coordinate system to obtain the preset normal range corresponding to the operating index parameter; comparing the operating index parameter with the preset normal range to obtain the preliminary fault detection result.

4. The engine failure detection method according to claim 1, characterized by, Based on the weights corresponding to at least two operating index parameters and the preliminary fault detection results corresponding to at least two operating index parameters, the target fault detection result is determined, comprising: based on the weights corresponding to at least two operating index parameters and at least two preliminary fault detection results, determining a comprehensive fault detection result; judging the comprehensive fault detection result based on a preset credibility threshold to obtain the target fault detection result, wherein the preset credibility threshold is used to judge the reliability of the comprehensive fault detection result, and the target fault detection result is used to indicate whether the comprehensive fault detection result exceeds the preset credibility threshold.

5. The engine failure detection method according to claim 4, characterized by, Based on the weights corresponding to at least two operating index parameters and the preliminary fault detection results corresponding to at least two operating index parameters, the comprehensive fault detection result is determined, comprising: based on the parameter type, determining the weight corresponding to the operating index parameter; weighting the weights corresponding to at least two operating index parameters and the preliminary fault detection results corresponding to at least two operating index parameters to obtain the comprehensive fault detection result.

6. The engine failure detection method according to claim 4, characterized by, The comprehensive fault detection result is judged based on a preset credibility threshold, and the target fault detection result is obtained, including: In response to the comprehensive fault detection result exceeding the preset credibility threshold, it is determined that the target fault detection result is that the engine is in the fault state; In response to the comprehensive fault detection result not exceeding the preset credibility threshold, it is determined that the target fault detection result is that the engine is not in the fault state.

7. An engine failure detection device characterized by comprising: Including: The acquisition module is configured to, in response to an engine of a vehicle being in an operating state, acquire an operating state parameter of the engine and at least two operating indicator parameters, wherein the operating state parameter is used to represent a current working condition of the engine, and different operating indicator parameters are used to represent current values of different performance indicators of the engine in the current working condition; The first determination module is configured to determine a preliminary fault detection result corresponding to the operating indicator parameter based on the operating state parameter and the operating indicator parameter, wherein the preliminary fault detection result is used to indicate whether the operating indicator parameter is in a preset normal range; The second determination module is configured to determine a target fault detection result based on weights corresponding to at least two operating indicator parameters and preliminary fault detection results corresponding to the at least two operating indicator parameters, wherein the target fault detection result is used to indicate whether the engine is in a fault state.

8. A vehicle characterized by comprising: Including: The memory stores an executable program; The processor is configured to run the executable program, wherein the executable program performs the method of any one of claims 1 to 6 when running.

9. A computer program product, characterised in that, The computer program, when executed by a processor, implements the method of any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein the computer-readable storage medium controls the device where the computer-readable storage medium is located to perform the method of any one of claims 1 to 6 when the executable program is running.

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