Intelligent control system and method for engine combustion diagnosis

Abstract

The invention discloses an intelligent control system and method for engine combustion diagnosis, and belongs to the technical field of engine diagnosis. The system comprises an ECU automatic control module, a combustion data acquisition module, a maintenance data acquisition module, an intelligent calculation module, a model analysis module and a diagnosis early warning module. The ECU automatic control module is used for the ECU to automatically control the combustion process of the engine; the combustion data acquisition module is used for acquiring supply data and tail gas data; the maintenance data acquisition module is used for acquiring maintenance data; the intelligent calculation module is used for calculating a target excess air coefficient and an actually measured excess air coefficient; the model analysis module is used for analyzing the influence of loss of parts in the engine on combustion of the engine; the diagnosis and early warning module is used for judging whether an engine is abnormal or not currently; according to the method, the loss condition of each part is analyzed, and the accuracy of engine combustion diagnosis and the fault judgment capability are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of engine diagnosis, in particular to an intelligent control system and method for engine combustion diagnosis. BACKGROUND

[0002] In many fields such as transportation and industrial production, the stability and efficient operation of the engine as the core power device is crucial, and the engine combustion as the key link of energy conversion directly determines the power output efficiency of the engine. Therefore, accurate diagnosis of the engine combustion state is an important guarantee for realizing the optimized control and performance improvement of the engine.

[0003] The ECU (Engine Control Unit) as the core component of the engine electronic control system usually combines the theoretical air-fuel ratio, the fuel correction value and the collected real-time running data of the engine to construct a powerful diagnostic decision matrix, so as to realize accurate regulation and control of the engine combustion. However, in order to meet the needs of power or emission, the modern ECU will actively deviate from the theoretical air-fuel ratio, which will not only interfere with the engine combustion diagnosis, but also increase the misjudgment probability of the system. The theoretical air-fuel ratio is generally analyzed according to the measurement ratio of fuel and air, but pure tail gas analysis cannot accurately locate the internal faults of the engine, thereby causing the fuzziness of engine fault diagnosis and increasing the maintenance cost. SUMMARY

[0004] The purpose of the present application is to provide a technical solution to solve the problems in the prior art.

[0005] To achieve the above purpose, the present application provides the following technical scheme: an intelligent control method for engine combustion diagnosis, comprising: The ECU automatically controls the combustion process of the engine, and collects the supply data before the engine combustion and the tail gas data after the engine combustion. The supply data includes the total mass of air and the total mass of fuel entering the engine cylinder. The tail gas data includes the tail gas composition after the combustion reaction of air and fuel in the engine cylinder. Periodic maintenance is performed on the engine, and maintenance data during the engine maintenance is collected. The maintenance data includes the maintenance period and replacement time of each part in the engine. According to the supply data, the target excess air coefficient of air and fuel before combustion in the engine cylinder is calculated, and according to the tail gas data, the measured excess air coefficient of air and fuel after combustion in the engine cylinder is calculated. Based on the maintenance data, the target excess air coefficient and the measured excess air coefficient, an engine diagnosis model is established to analyze the influence of the wear of each part in the engine on the engine combustion. According to the established engine diagnosis model, the wear of each part in the engine is monitored in real time, whether the current engine is abnormal is judged, and the engine abnormality is warned, and the warning information is sent to the user.

[0006] Further, the target excess air coefficient is specifically a ratio of an actual air-fuel ratio to a theoretical air-fuel ratio; and the actual air-fuel ratio is specifically a ratio of a total mass of air entering the engine cylinder to a total mass of fuel.

[0007] Further, the method for calculating the measured excess air coefficient is that: analyzing the tail gas data, respectively determining each gas after the air and fuel combustion reaction in the engine cylinder and the corresponding volume fraction, and respectively substituting the determined each gas and the corresponding volume fraction into the Brettschneider formula to calculate the measured excess air coefficient after the air and fuel combustion in the engine cylinder.

[0008] Further, the method steps for analyzing the influence of the wear of each part in the engine on the engine combustion are: S1, analyzing the collected maintenance data to determine the number n of parts that have an influence on the engine combustion, and respectively determining the maintenance frequency and the total operation time of each part; according to the time stamp, determining the changes of the target excess air coefficient and the measured excess air coefficient before and after the engine combustion under different maintenance periods and replacement times of the parts, and obtaining the deviation change between the target excess air coefficient and the measured excess air coefficient; S2, establishing an engine diagnosis model, taking the maintenance period and the replacement time of each part as the independent variable, and taking the deviation between the target excess air coefficient and the measured excess air coefficient as the dependent variable, analyzing the influence of the wear of each part in the engine on the engine combustion, and fitting the relationship curve of the influence of the wear of each part in the engine on the engine combustion: ; Wherein, CZ represents the deviation between the target excess air coefficient and the measured excess air coefficient; m represents the number of parts whose wear will cause the air-fuel ratio in the engine to decrease; w i represents the influence weight of the wear of part i on the engine combustion; a i represents the influence degree of the wear of part i on the engine combustion; h i represents the wear recovery value of part i after maintenance; T represents the total operation time of the part; and M represents the maintenance frequency of the part. S3, taking the analysis result of the maintenance data in S1 as the training data, substituting it into the relationship curve in S2 for fitting, and respectively determining the influence weight, the influence degree and the wear recovery value of different parts on the engine combustion according to the least square method.

[0009] Further, the method steps for real-time monitoring of the wear of each part in the engine to determine whether there is an engine abnormality at present are: S10, analyze the real-time maintenance data of each part, calculate the total impact value Y0 of the part wear on the engine combustion according to the maintenance number and total operation time of each part through the engine diagnosis model; determine the real-time deviation CZ0 between the target excess air coefficient and the measured excess air coefficient according to the real-time supply data and real-time tail gas data of the engine; S20, analyze the historical maintenance data, target excess air coefficient and measured excess air coefficient when there is an engine fault, and determine the alarm threshold K of the influence of part wear on the deviation between the target excess air coefficient and the measured excess air coefficient of the engine i ; the engine fault indicates that there is a part failure leading to engine failure; S30, judge the engine abnormality, when K i > |Y0-CZ0|, the engine part is normal; when K i ≤ |Y0-CZ0|, the engine part is abnormal, and the abnormal engine part is alarmed.

[0010] Further, each part in the engine is determined and a full-part digital list of the engine is constructed, a corresponding maintenance period and replacement time threshold are configured for each individual part, the maintenance period and replacement time of each part are recorded in the digital list, and the digital list of each part is integrated to obtain the maintenance data in the engine maintenance process.

[0011] An intelligent control system for engine combustion diagnosis, the system comprising an ECU automatic control module, a combustion data acquisition module, a maintenance data acquisition module, an intelligent calculation module, a model analysis module and a diagnosis and early warning module; The ECU automatic control module is used for the ECU to automatically control the combustion process of the engine. The combustion data acquisition module is used for acquiring the supply data before the engine combustion and the tail gas data after the engine combustion; the supply data includes the total mass of air and the total mass of fuel entering the engine cylinder; the tail gas data includes the tail gas composition after the combustion reaction of air and fuel in the engine cylinder; and the acquired supply data and tail gas data are sent to the intelligent calculation module; The maintenance data acquisition module is used for acquiring the maintenance data in the engine maintenance process; the maintenance data includes the maintenance period and replacement time of each part in the engine; and the acquired maintenance data is sent to the model analysis module; The intelligent calculation module is configured to calculate a target excess air coefficient of air in a cylinder of the engine before combustion of fuel according to supply data, and calculate a measured excess air coefficient of air in the cylinder of the engine after combustion of the fuel according to tail gas data; and send the calculated target excess air coefficient and the measured excess air coefficient to the model analysis module. The model analysis module is configured to establish an engine diagnosis model based on the maintenance data, the target excess air coefficient and the measured excess air coefficient, and analyze influences of wear of each part in the engine on combustion of the engine. The diagnosis and early warning module is configured to monitor the wear of each part in the engine in real time according to the established engine diagnosis model, judge whether there is an engine abnormality at present, and give an alarm for the engine abnormality and send alarm information to a user.

[0012] Further, a man-machine interaction platform is provided, and a user can check alarm information through the man-machine interaction platform; and a maintenance personnel can record a maintenance period and a replacement time of each part through the man-machine interaction platform.

[0013] Compared with the prior art, the present application has the following beneficial effects: the engine diagnosis model is established to analyze influences of wear of each part in the engine on a deviation change trend, so that the wear of each part is analyzed, and the accuracy of engine combustion diagnosis is improved; influences of the wear of each part on a deviation between the target excess air coefficient and the measured excess air coefficient are predicted to judge whether other factors except the wear of each part will affect the deviation between the target excess air coefficient and the measured excess air coefficient, and the fault judgment ability of the engine is improved. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 is a structural schematic diagram of an intelligent control system for engine combustion diagnosis. DETAILED DESCRIPTION

[0015] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0016] Please refer to Figure 1 The present application provides the technical solutions: In the first embodiment: an intelligent control method for engine combustion diagnosis is provided, comprising: The ECU automatically controls the engine's combustion process, collecting supply data before combustion and exhaust gas data after combustion. The supply data includes the total mass of air and fuel entering the engine cylinders, while the exhaust gas data includes the components of the exhaust gas after the air and fuel in the engine cylinders react with each other.

[0017] It should be noted that during the automatic control of the engine's combustion process by the ECU, when the engine's air intake increases, the ECU will calculate the corresponding basic fuel injection quantity based on the signal from the air flow sensor and the theoretical air-fuel ratio. For example, the theoretical air-fuel ratio of gasoline is 14.7:1. However, under conditions such as high engine load and acceleration, it is necessary to enrich the air-fuel mixture to increase power. This is achieved by controlling the fuel trim value to add to the mixture.

[0018] Regular maintenance is performed on the engine, and maintenance data is collected during the engine maintenance process; the maintenance data includes the maintenance cycle and replacement time of each part in the engine.

[0019] Furthermore, the individual components within the engine are identified and a complete digital inventory of engine components is constructed. A corresponding maintenance cycle and replacement time threshold are configured for each individual component, and the maintenance cycle and replacement time of each component are recorded in the digital inventory. The digital inventories of each component are then integrated to obtain maintenance data during the engine maintenance process.

[0020] In this embodiment, the parts inside the engine include, but are not limited to, the throttle body, intake manifold, fuel injector, ignition coil, cylinder, and valve. Due to the different types and degrees of damage of the parts, maintenance personnel will selectively maintain or directly replace various parts inside the engine according to different scenarios. After the maintenance personnel complete the engine maintenance, they will fill in the maintenance status of each part in the digital list. When maintaining a part, the maintenance cycle and number of maintenance times for that part will be recorded.

[0021] Based on the supply data, calculate the target excess air coefficient of the air and fuel in the engine cylinder before combustion, and based on the exhaust gas data, calculate the measured excess air coefficient of the air and fuel in the engine cylinder after combustion.

[0022] Specifically, the target excess air coefficient is the ratio of the actual air-fuel ratio to the stoichiometric air-fuel ratio; the actual air-fuel ratio is the ratio of the total mass of air entering the engine cylinder to the total mass of fuel; wherein, the target excess air coefficient is the expected value of the excess air coefficient calculated by the ECU from the internally stored three-dimensional pulse spectrum diagram based on current driving needs, engine power and emissions optimization targets.

[0023] Specifically, the method for calculating the measured excess air coefficient is: analyzing the exhaust data, respectively determining each gas after the air in the engine cylinder and the fuel combustion reaction and the corresponding volume fraction, and respectively substituting the determined each gas and the corresponding volume fraction into the Brettschneider formula to calculate the measured excess air coefficient after the air in the engine cylinder and the fuel combustion.

[0024] In the embodiment, the exhaust data is analyzed, the carbon monoxide volume fraction [CO], the carbon dioxide volume fraction [CO2], the oxygen volume fraction [O2] and the hydrocarbon volume fraction [HC] % after the air in the engine cylinder and the fuel combustion reaction are respectively determined, and are respectively substituted into the Brettschneider formula to calculate the measured excess air coefficient λ: ; K1 and K2 respectively represent fuel hydrogen-carbon ratio related constants, which are determined according to the fuel characteristics, and the specific fuel is gasoline.

[0025] It should be noted that the target excess air coefficient is determined by the direct method, and the measured excess air coefficient is inversely deduced by the indirect method, the difference between before and after the air in the engine cylinder and the fuel combustion reaction is reflected according to the target excess air coefficient and the measured excess air coefficient, and the wear of each part in the engine is analyzed according to the difference, thereby improving the accuracy of engine fault diagnosis.

[0026] Based on the maintenance data, the target excess air coefficient and the measured excess air coefficient, an engine diagnosis model is established to analyze the influence of the wear of each part in the engine on the engine combustion.

[0027] Specifically, the method steps for analyzing the influence of the wear of each part in the engine on the engine combustion are: S1, analyzing the collected maintenance data to determine the number n of parts that have an influence on the engine combustion, and respectively determining the maintenance times and the total operation time of each kind of part; according to the time stamp, determining the changes of the target excess air coefficient and the measured excess air coefficient before and after the engine combustion under different maintenance periods and replacement times of the parts, and obtaining the deviation change between the target excess air coefficient and the measured excess air coefficient; S2, establishing an engine diagnosis model, taking the maintenance period and the replacement time of each part as the independent variable, and taking the deviation between the target excess air coefficient and the measured excess air coefficient as the dependent variable, analyzing the influence of the wear of each part in the engine on the engine combustion, and fitting the relationship curve of the influence of the wear of each part in the engine on the engine combustion: ; Wherein, CZ represents the deviation between the target excess air coefficient and the measured excess air coefficient; m represents the number of parts whose wear will cause the air-fuel ratio in the engine to decrease; wi represents the influence weight of the loss of part i on engine combustion; a i represents the influence degree of the loss of part i on engine combustion; h i represents the loss recovery value of part i after maintenance; T represents the total operation time of the part; M represents the number of maintenance of the part; S3, the analysis result of the maintenance data in S1 is substituted into the relationship curve in S2 for fitting, and the influence weight, influence degree and loss recovery value of different parts on engine combustion are respectively determined according to the least square method.

[0028] It should be noted that by establishing an engine diagnosis model, the deviation CZ between the target excess air coefficient λ0 and the measured excess air coefficient λ is determined according to the supply data and the tail gas data: , the total operation time and the number of maintenance of each part are determined according to the maintenance data; wherein when the part is replaced, the total operation time of the replaced part is recalculated; the influence of the deviation between the target excess air coefficient and the measured excess air coefficient under the loss of different parts is determined according to the time stamp, so as to analyze the influence of the loss of each part on engine combustion, accurately locate the parts that have influence on engine internal combustion, and improve the accuracy of engine combustion diagnosis.

[0029] It should be noted that the number of parts m whose loss will cause the air-fuel ratio in the engine to decrease and the number of parts n-m whose loss will cause the air-fuel ratio in the engine to increase are determined respectively, because the loss of different parts will make the deviation between the target excess air coefficient and the measured excess air coefficient change in different directions; for example, when the loss of the fuel injector causes the fuel injection amount to increase, the measured excess air coefficient will decrease, and the deviation will go to the positive direction; for example, the loss of the throttle valve causes the seal to be not tight, which causes more air leakage, the measured excess air coefficient will increase, and the deviation will develop in the negative direction; by analyzing the influence of the loss of each part in the engine on the change trend of the deviation between the target excess air coefficient and the measured excess air coefficient, the abnormal condition of each part is judged.

[0030] According to the established engine diagnosis model, the loss of each part in the engine is monitored in real time, whether there is an engine abnormality at present is judged, and the engine abnormality is warned, and the warning information is sent to the user.

[0031] Specifically, the method steps for monitoring the loss of each part in the engine in real time and judging whether there is an engine abnormality at present are as follows: S10, analyze the real-time maintenance data of each part, calculate the total influence value Y0 of the part wear on the engine combustion according to the maintenance times and total operation time of each part through the engine diagnosis model; determine the real-time deviation CZ0 between the target excess air coefficient and the measured excess air coefficient according to the real-time supply data and real-time tail gas data of the engine; S20, analyze the historical maintenance data, target excess air coefficient and measured excess air coefficient when the engine fault exists, determine the alarm threshold K of the influence of part wear on the deviation between the target excess air coefficient and the measured excess air coefficient of the engine i ; the engine fault indicates that there is a part failure leading to engine failure; S30, judge the engine abnormality, when K i > |Y0-CZ0|, the engine part is normal; when K i ≤ |Y0-CZ0|, the engine part is abnormal, and the abnormal engine part is alarmed.

[0032] It should be noted that the alarm threshold K i is determined according to the deviation between Y0 and CZ0 when the engine fault exists in the historical data; the maintenance times and total operation time of each part are respectively substituted into the relationship curve of S2, the total influence value of part wear on engine combustion is calculated according to the influence weight, influence degree and wear recovery value of different parts on engine combustion, the influence of part wear on the deviation between the target excess air coefficient and the measured excess air coefficient is predicted, and the predicted total influence value and real-time deviation CZ0 are analyzed to judge whether other factors except part wear have influence on the deviation between the target excess air coefficient and the measured excess air coefficient, so that the influence of other interference factors on engine combustion is considered, and the fault judgment ability of the engine is improved.

[0033] Please refer to Figure 1 , in the second embodiment: an intelligent control system for engine combustion diagnosis is provided, which comprises an ECU automatic control module, a combustion data acquisition module, a maintenance data acquisition module, an intelligent calculation module, a model analysis module and a diagnosis and early warning module; The ECU automatic control module is used for the ECU to automatically control the combustion process of the engine. The combustion data acquisition module is used for acquiring the supply data before engine combustion and the tail gas data after engine combustion; the supply data includes the total mass of air and the total mass of fuel entering the engine cylinder; the tail gas data includes the tail gas composition after the combustion reaction of air and fuel in the engine cylinder; and the acquired supply data and tail gas data are sent to the intelligent calculation module; The maintenance data collection module is configured to collect maintenance data in the engine maintenance process, wherein the maintenance data comprises maintenance periods and replacement times of each part in the engine; and the collected maintenance data is sent to the model analysis module. The intelligent calculation module is configured to calculate a target excess air coefficient of air and fuel before combustion in the engine cylinder according to the supply data, and calculate a measured excess air coefficient of air and fuel after combustion in the engine cylinder according to the tail gas data; and the calculated target excess air coefficient and measured excess air coefficient are sent to the model analysis module. The model analysis module is configured to establish an engine diagnosis model based on the maintenance data, the target excess air coefficient and the measured excess air coefficient, and analyze the influence of wear of each part in the engine on the engine combustion. The diagnosis and early warning module is configured to monitor the wear of each part in the engine in real time according to the established engine diagnosis model, judge whether there is an engine abnormality at present, and give an alarm for the engine abnormality, and send the alarm information to the user.

[0034] Further, a man-machine interaction platform is provided, and the user can check the alarm information through the man-machine interaction platform; wherein the maintenance personnel can record the maintenance period and replacement time of each part through the man-machine interaction platform.

[0035] It is apparent for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application. Therefore, the embodiments should be regarded as exemplary and non-limiting, and the scope of the present application is defined by the appended claims rather than the above description, and all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present application. Any reference signs in the claims should not be regarded as limiting the involved claims.

Claims

1. An intelligent control method for engine combustion diagnosis, characterized in that: include: The ECU automatically controls the engine's combustion process, collecting supply data before combustion and exhaust gas data after combustion. The supply data includes the total mass of air and fuel entering the engine cylinders, and the exhaust gas data includes the components of the exhaust gas after the air and fuel in the engine cylinders react with each other during combustion. Regular maintenance is performed on the engine, and maintenance data is collected during the engine maintenance process; the maintenance data includes the maintenance cycle and replacement time of each part in the engine; Based on the supply data, calculate the target excess air coefficient of the air in the engine cylinder before combustion of fuel, and based on the exhaust gas data, calculate the measured excess air coefficient of the air in the engine cylinder after combustion of fuel. Based on maintenance data, target excess air coefficient and measured excess air coefficient, an engine diagnostic model is established to analyze the impact of wear and tear on engine combustion of various engine components. Based on the established engine diagnostic model, the wear and tear of various parts in the engine is monitored in real time to determine whether there is an engine abnormality, and an alarm is issued for the abnormality and the alarm information is sent to the user.

2. The intelligent control method for engine combustion diagnosis according to claim 1, characterized in that: The target excess air coefficient is specifically the ratio of the actual air-fuel ratio to the stoichiometric air-fuel ratio; the actual air-fuel ratio is specifically the ratio of the total mass of air entering the engine cylinder to the total mass of fuel.

3. The intelligent control method for engine combustion diagnosis according to claim 1, characterized in that: The method for calculating the measured excess air coefficient is as follows: Analyze the exhaust gas data, determine the individual gases and their corresponding volume fractions after the combustion reaction of air and fuel in the engine cylinder, and substitute the determined gases and their corresponding volume fractions into the Brettschneider formula to calculate the measured excess air coefficient after the combustion of air and fuel in the engine cylinder.

4. The intelligent control method for engine combustion diagnosis according to claim 1, characterized in that: The steps for analyzing the impact of wear and tear on engine combustion of individual components are as follows: S1. Analyze the collected maintenance data to determine the number n of parts that affect engine combustion, and determine the maintenance frequency and total operation time for each part. Based on the timestamp, the changes in the target excess air coefficient and the measured excess air coefficient before and after engine combustion are determined under different maintenance cycles and replacement times of different parts, and the deviation between the target excess air coefficient and the measured excess air coefficient is obtained. S2. Establish an engine diagnostic model, using the maintenance cycle and replacement time of each component as independent variables, and the deviation between the target excess air coefficient and the measured excess air coefficient as the dependent variable. Analyze the impact of wear on engine combustion of each component, and fit the relationship curves between the wear of each component and engine combustion. ； Where CZ represents the deviation between the target excess air coefficient and the measured excess air coefficient; m represents the number of parts whose wear causes a decrease in the air-fuel ratio of the engine; w i The weight α represents the impact of component i's wear on engine combustion. i This indicates the degree to which the wear and tear of component i affects engine combustion; h i T represents the wear recovery value of part i after maintenance; M represents the total operation time of part i; and M represents the number of maintenance cycles for part i. S3. Use the analysis results of the maintenance data in S1 as training data and substitute them into the relationship curve in S2 for fitting. According to the least squares method, determine the influence weight, influence degree and loss recovery value of different parts on engine combustion respectively.

5. The intelligent control method for engine combustion diagnosis according to claim 4, characterized in that: The steps for real-time monitoring of wear and tear on various engine components to determine if any engine malfunctions exist are as follows: S10. Analyze the real-time maintenance data of each part, and calculate the total impact value Y0 of part wear on engine combustion through the engine diagnostic model based on the maintenance frequency and total operation time of each part; determine the real-time deviation CZ0 between the target excess air coefficient and the measured excess air coefficient based on the engine's real-time supply data and real-time exhaust gas data. S20. Analyze historical maintenance data, target excess air coefficient, and measured excess air coefficient when engine failure occurs, and determine the alarm threshold K for the impact of component wear on the deviation between the target and measured excess air coefficients of the engine. i The engine malfunction indicates that a component failure is causing the engine failure. S30. Detect engine malfunctions; when K... i When >|Y0-CZ0|, the engine parts are normal; when K exists... i When the value is less than or equal to |Y0-CZ0|, an engine part is abnormal, and an alarm is issued for the abnormal engine part.

6. The intelligent control method for engine combustion diagnosis according to claim 1, characterized in that: Identify all the components within the engine and construct a complete digital inventory of engine components. Assign a corresponding maintenance cycle and replacement time threshold to each individual component, and record the maintenance cycle and replacement time of each component in the digital inventory. By integrating the digital inventory of each part, maintenance data can be obtained during the engine maintenance process.

7. An intelligent control system for engine combustion diagnosis, characterized in that: The system includes an ECU automatic control module, a combustion data acquisition module, a maintenance data acquisition module, an intelligent computing module, a model analysis module, and a diagnostic and early warning module; The ECU automatic control module is used by the ECU to automatically control the combustion process of the engine; The combustion data acquisition module is used to collect engine supply data before combustion and engine exhaust gas data after combustion; the supply data includes the total mass of air and fuel entering the engine cylinder; the exhaust gas data includes the exhaust gas composition after the air and fuel in the engine cylinder react with each other; and the collected supply data and exhaust gas data are sent to the intelligent computing module. The maintenance data acquisition module is used to collect maintenance data during the engine maintenance process; the maintenance data includes the maintenance cycle and replacement time of each part in the engine; and the collected maintenance data is sent to the model analysis module. The intelligent computing module is used to calculate the target excess air coefficient of the air and fuel in the engine cylinder before combustion based on the supply data, and to calculate the measured excess air coefficient of the air and fuel in the engine cylinder after combustion based on the exhaust gas data; and to send the calculated target excess air coefficient and the measured excess air coefficient to the model analysis module. The model analysis module is used to establish an engine diagnostic model based on maintenance data, target excess air coefficient and measured excess air coefficient, and to analyze the impact of wear and tear of various parts in the engine on engine combustion. The diagnostic and early warning module is used to monitor the wear and tear of various parts in the engine in real time based on the established engine diagnostic model, determine whether there is an engine abnormality, issue an alarm for the abnormality, and send the alarm information to the user.

8. The intelligent control system for engine combustion diagnosis according to claim 7, characterized in that: A human-machine interaction platform is provided, through which users can view alarm information; maintenance personnel can also use the human-machine interaction platform to record the maintenance cycle and replacement time of each part.

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