Vehicle fault processing method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention provides a vehicle fault processing method and device, equipment, a storage medium and a program product. The method comprises the steps that when a vehicle is in a running state, whether knocking abnormity exists in an engine or not is determined according to target knocking parameters of the engine of the vehicle, and the target knocking parameters comprise at least one of a knocking learning value, a knocking fast learning value and knocking signal intensity. And if the engine has the knock abnormity, the knock abnormity processing operation is executed, and the knock abnormity processing operation comprises at least one of limiting the torque of the engine and outputting abnormity prompt information. The method is used for achieving the effects of reducing the knocking condition of the vehicle engine, improving the operation stability of the engine and prolonging the service life of the engine.

Description

Technical Field

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

[0002] In the field of vehicle technology, both gasoline-powered vehicles and hybrid vehicles that can burn fuel require power from fuel. When a gasoline engine burns different types of fuel, the varying octane ratings of these fuels can cause different degrees of knocking. Specifically, gasoline engines experience more knocking when using lower-octane fuels than when using higher-octane fuels. However, fuel quality varies significantly across different regions. If a gasoline engine uses fuel with an octane rating lower than its standard, it will lead to increased knocking during operation, resulting in reduced engine life and decreased operational stability.

[0003] Therefore, how to reduce knocking in vehicle fuel engines, improve engine lifespan and operational stability are urgent problems that need to be solved. Summary of the Invention

[0004] The vehicle fault handling method, apparatus, equipment, storage medium, and program products provided in this application are used to reduce the knocking of the vehicle's fuel engine, improve the engine's service life, and enhance its operational stability.

[0005] In a first aspect, embodiments of this application provide a vehicle fault handling method, including:

[0006] When the vehicle is in operation, it is determined whether the engine has knocking abnormality based on the target knocking parameters of the vehicle's engine. The target knocking parameters include at least one of knocking learning value, knocking fast learning value, and knocking signal intensity.

[0007] If the engine has a knocking abnormality, a knocking abnormality handling operation is performed, which includes at least one of limiting the engine torque and outputting an abnormality prompt message.

[0008] Optionally, determining whether the engine has knocking abnormalities based on the target knocking parameters of the vehicle's engine includes:

[0009] Obtain the anomaly detection threshold for the target detonation parameters;

[0010] Based on the target knock parameters and the anomaly discrimination threshold, it is determined whether the engine has a knock anomaly.

[0011] Optionally, determining whether the engine has a knocking abnormality based on the target knocking parameters and the anomaly discrimination threshold includes:

[0012] Based on the target detonation parameters and the anomaly detection threshold, determine the number of times the target detonation parameters are greater than or equal to the anomaly detection threshold;

[0013] If the target number of times is greater than or equal to a preset number threshold, then it is determined that the engine has the knocking abnormality.

[0014] Optionally, determining that the engine has the knocking abnormality if the target number is greater than or equal to a preset number threshold includes:

[0015] If the target number of times is greater than or equal to the preset number threshold within the preset detection period, then it is determined that the engine has the knocking abnormality.

[0016] Optionally, the target detonation parameters include the detonation learning value, and the anomaly discrimination threshold for obtaining the target detonation parameters includes:

[0017] Obtain the operating condition range of the engine;

[0018] Based on the operating condition range and the mapping relationship between the operating condition range and the anomaly discrimination parameters, the target anomaly discrimination parameters are obtained;

[0019] Based on the target anomaly discrimination parameters, the anomaly discrimination threshold is determined.

[0020] Optionally, obtaining the target anomaly discrimination parameters based on the operating condition range and the mapping relationship between the operating condition range and the anomaly discrimination parameters includes:

[0021] Obtain the engine's status parameters, including engine speed, intercooler temperature, and cylinder block identification.

[0022] Based on the operating condition range, the engine state parameters, and the mapping relationship between the operating condition range, state parameters, and anomaly discrimination parameters, the target anomaly discrimination parameters are obtained. The target anomaly discrimination parameters include knock threshold parameters, speed compensation parameters, and intercooler temperature compensation parameters.

[0023] Determining the anomaly detection threshold based on the target anomaly detection parameters includes:

[0024] The anomaly detection threshold is determined based on the knock threshold parameter, the speed compensation parameter, and the temperature compensation parameter after intercooling.

[0025] Optionally, the mapping relationship between the operating condition range, state parameters, and anomaly discrimination parameters is obtained based on the average of the first knock learning value test data corresponding to the first grade fuel and the second knock learning value test data corresponding to the second grade fuel.

[0026] Optionally, the target knock parameters include the fast knock learning value, and the anomaly discrimination threshold is obtained based on the fast knock learning value test data corresponding to the third grade fuel.

[0027] Optionally, the target detonation parameters include the detonation signal intensity, and the anomaly discrimination threshold for obtaining the target detonation parameters includes:

[0028] Based on the cylinder block identification of the engine and the engine speed, an abnormality discrimination threshold for the knock signal intensity corresponding to each cylinder block is obtained.

[0029] Optionally, the method further includes:

[0030] When the vehicle is in operation, it is determined whether the engine's operating status parameters meet preset enabling conditions. The operating status parameters include at least one of engine speed and mean effective indicated pressure.

[0031] If the conditions are met, the knock anomaly detection process will be initiated.

[0032] Secondly, embodiments of this application provide a vehicle fault handling device, comprising:

[0033] The processing module is used to determine whether there is a knocking abnormality in the engine based on the target knocking parameters of the engine of the vehicle when the vehicle is in operation. The target knocking parameters include at least one of knocking learning value, knocking fast learning value, and knocking signal intensity.

[0034] The control module is configured to perform a knock anomaly handling operation if the engine has a knock anomaly, the knock anomaly handling operation including at least one of limiting the engine torque and outputting an anomaly prompt message.

[0035] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0036] The memory stores computer-executed instructions;

[0037] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0038] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0039] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0040] The vehicle fault handling method, apparatus, device, storage medium, and program product provided in this application determine whether the engine has a knocking abnormality when the vehicle is in operation, based on at least one of the target knocking parameters of the vehicle's engine, including knocking learning value, knocking fast learning value, and knocking signal intensity. If the engine has a knocking abnormality, a knocking abnormality handling operation is performed, including limiting the engine torque and providing an abnormal output prompt message, to adjust the engine's operating state in a timely manner, preventing the knocking from further aggravating irreversible damage to internal engine components (such as pistons, cylinder walls, etc.), while optimizing the engine's combustion process, enabling the engine to output power more smoothly in subsequent operation, reducing power loss and fuel waste caused by knocking, thereby improving engine life and operational stability. Attached Figure Description

[0041] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0042] Figure 1 A schematic flowchart illustrating a vehicle fault handling method provided in an embodiment of this application;

[0043] Figure 2 A flowchart illustrating another vehicle fault handling method provided in this application embodiment;

[0044] Figure 3 A flowchart illustrating another vehicle fault handling method provided in this application embodiment;

[0045] Figure 4 A schematic diagram illustrating an operating condition range provided for an embodiment of this application;

[0046] Figure 5 A schematic diagram illustrating a mapping relationship provided in an embodiment of this application;

[0047] Figure 6 A schematic diagram illustrating another mapping relationship provided in an embodiment of this application;

[0048] Figure 7 A schematic diagram illustrating yet another mapping relationship provided in an embodiment of this application;

[0049] Figure 8 A schematic diagram illustrating another mapping relationship provided in an embodiment of this application;

[0050] Figure 9 A schematic flowchart illustrating another vehicle fault handling method provided in an embodiment of this application;

[0051] Figure 10 This is a schematic diagram of the structure of a vehicle fault handling device provided in an embodiment of this application;

[0052] Figure 11 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0053] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0054] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0055] Currently, in the field of vehicle technology, for gasoline vehicles and hybrid vehicles that can burn fuel, existing technologies mainly focus on improving the engine's adaptability to different types of fuel by optimizing the engine's hardware design (such as improving the combustion chamber structure and optimizing the ignition system) or adjusting the engine's control strategy (such as adjusting parameters such as ignition advance angle and air-fuel ratio) to reduce the risk of knocking.

[0056] However, hardware improvements require structural adjustments to the engine itself, which is not only costly but also difficult to adapt to mass-produced models. In addition, the current fixed-parameter control strategy cannot dynamically respond to real-time changes in fuel quality in different regions. When the engine uses fuel with an octane rating lower than the design standard, it will still suffer from serious malfunctions such as piston ring breakage and cylinder wall scoring due to increased knocking, which in turn leads to technical problems such as shortened engine life, decreased operational stability, and increased maintenance costs.

[0057] In view of this, this application provides a vehicle fault handling method. While the vehicle is in operation, the method determines whether the engine has a knocking abnormality based on at least one of the following target knocking parameters: knocking learning value, knocking fast learning value, and knocking signal intensity. If the engine has a knocking abnormality, the method performs a knocking abnormality handling operation, including limiting engine torque and providing an output abnormality warning message, to adjust the engine's operating state in a timely manner. This prevents the knocking from further aggravating irreversible damage to internal engine components (such as pistons and cylinder walls), while optimizing the engine's combustion process. This allows the engine to output power more smoothly in subsequent operation, reducing power loss and fuel waste caused by knocking, thereby improving engine lifespan and operational stability.

[0058] The vehicle fault handling method provided in this application can be executed by an electronic device with data processing capabilities. This electronic device can be, for example, an in-vehicle terminal, or a computing device such as a computer or server. For instance, the computing device could be the vehicle's Electronic Control Unit (ECU) or a cloud server corresponding to the vehicle system. This electronic device can be equipped with software or program code that runs the vehicle fault handling method. During vehicle operation, the software or program code detects whether there is an abnormal knocking in the engine based on parameters such as knock learning value, knock fast learning value, and knock signal intensity, and executes corresponding fault handling operations when an abnormality is detected.

[0059] It should be understood that the vehicle mentioned in the embodiments of this application can be a vehicle powered by a fuel engine, such as a fuel vehicle, a hybrid vehicle, etc., including but not limited to motorcycles, cars, SUVs, etc. The engine mentioned in the embodiments of this application can be, for example, a single-cylinder fuel engine, a two-cylinder fuel engine, a three-cylinder fuel engine, a four-cylinder fuel engine, a six-cylinder fuel engine, an eight-cylinder fuel engine, etc.

[0060] The technical solution of this application and how it solves the above-mentioned technical problems will be described in detail below through specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0061] Figure 1 This is a flowchart illustrating a vehicle fault handling method provided in an embodiment of this application. Figure 1 As shown, the method may include:

[0062] S101. When the vehicle is in operation, determine whether there is an abnormal knocking in the engine based on the target knocking parameters of the vehicle's engine.

[0063] The target knock parameters include at least one of the following: knock learning value, knock fast learning value, and knock signal intensity. The target knock parameters are observations collected during vehicle engine operation, i.e., actual knock data during engine operation.

[0064] Knock learning value is a core parameter for engine knock control. The vehicle's engine control module (ECM) calculates the knock learning value by monitoring the knocking behavior of each cylinder over a long period. Knock learning establishes a correction benchmark for ignition advance angle across different speed / load ranges, optimizing power, fuel consumption, and emissions, while compensating for long-term factors such as engine aging and changes in fuel octane rating. In other words, the knock learning value is a cumulative value obtained based on long-term operating condition statistics.

[0065] The fast learning value for knock is used for rapid suppression of transient knock. The ECM can calculate the fast learning value for knock in real time within each combustion cycle or short time window. The average value of the fast learning value for knock can reflect the dynamic correction intensity over a short period of time, avoiding the impact of strong knock on the engine. In other words, the fast learning value for knock is the instantaneous value based on the current cycle or short window.

[0066] The knock signal intensity is the amplitude of the knock signal detected by the knock sensor in the engine, which can be represented, for example, by voltage.

[0067] When a vehicle is in operation, it means that the vehicle's engine is running and outputting power, such as when the vehicle is driving at a steady speed on a city road, accelerating on a highway, or climbing a hill on a suburban road.

[0068] In this step, any one of the following—knock learning value, knock fast learning value, and knock signal intensity—can be used as the basis for determining whether the engine has knock anomalies. Alternatively, the combined result of any two of these three factors can be used as the basis for determining whether the engine has knock anomalies. Or, the combined result of all three factors can be used as the basis for determining whether the engine has knock anomalies.

[0069] The following section will use the comprehensive judgment of three factors—knock learning value, knock fast learning value, and knock signal intensity—to illustrate how to determine whether an engine has knocking abnormalities.

[0070] One possible implementation involves obtaining anomaly thresholds for the knock learning value, fast knock learning value, and knock signal intensity based on knock test data obtained from different fuel types. Then, by comparing these thresholds with their respective anomaly thresholds, if at least one target knock parameter exceeds its corresponding anomaly threshold, the engine is confirmed to have a knock anomaly. In this implementation, if the engine comprises multiple cylinders, the average of the target knock parameters across all cylinders can be used as the target knock parameter, and the overall knock severity of the engine can be directly determined using the anomaly threshold.

[0071] Another possible implementation involves using knock test data obtained from each cylinder of the engine under different oil conditions to derive the knock learning value, fast knock learning value, and anomaly detection threshold corresponding to the knock signal intensity for each cylinder. Then, the knock learning value, fast knock learning value, knock signal intensity, and anomaly detection threshold corresponding to each target knock parameter for each cylinder are compared. If at least one target knock parameter of at least one cylinder is greater than its corresponding anomaly detection threshold, then the engine is determined to have a knock anomaly.

[0072] S102. If the engine has knocking abnormality, then perform knocking abnormality handling operation.

[0073] Among them, the knocking abnormality handling operation includes at least one of limiting the engine torque and output abnormality warning information.

[0074] In this step, if engine knocking is confirmed, it indicates a high level of knocking, which will affect the engine's operational stability and service life. In this case, knocking control procedures can be implemented to reduce engine knocking, thereby improving engine operational stability and service life, and reducing the risk of engine damage.

[0075] Limiting engine torque can be achieved by adjusting the engine's throttle opening, fuel injection quantity, or ignition timing. For example, engine torque can be limited by adjusting the throttle opening, such as by reducing the throttle opening from a larger value to a smaller value, thereby reducing the amount of air entering the cylinder and thus lowering the engine's output torque. For instance, the maximum flywheel torque of the engine can be limited to a preset torque value of 100 Nm or less, ensuring that the maximum flywheel torque does not exceed 100 Nm.

[0076] Outputting abnormal information can be achieved through methods such as displaying fault codes on the vehicle's instrument panel, illuminating fault lights, issuing a buzzer alarm, or displaying text prompts on the central control screen. Specifically, the fault code can be a code value directly indicating engine knocking abnormality (i.e., if knocking abnormality exists in any cylinder of the engine, regardless of how many cylinders have knocking abnormality, this code value will be output, for example, the code value is P2336); or, different fault codes can be displayed for different cylinders of the engine to indicate which cylinder currently has knocking abnormality. For example, abnormal information may include fault type (e.g., Type C), illuminating fault lights (e.g., SVS light illuminated but engine fault light not illuminated, or SVS light illuminated and engine fault light illuminated, or engine fault light illuminated, etc.), and outputting fault code P2336, etc.

[0077] The method provided in this application determines whether an engine has a knocking abnormality when the vehicle is in operation, based on at least one of the target knocking parameters of the vehicle's engine, including knocking learning value, knocking fast learning value, and knocking signal intensity. If the engine has a knocking abnormality, a knocking abnormality handling operation is performed, including limiting the engine torque and providing an abnormal output prompt message, to adjust the engine's operating state in a timely manner, preventing further damage to internal engine components (such as pistons and cylinder walls) caused by knocking, while optimizing the engine's combustion process so that the engine can output power more smoothly in subsequent operation, reducing power loss and fuel waste caused by knocking, thereby improving engine life and operational stability.

[0078] The following section provides a detailed explanation of how to determine whether the engine has knocking abnormalities based on the target knocking parameters of the vehicle's engine in step S101. Figure 2 This is a flowchart illustrating another vehicle fault handling method provided in an embodiment of this application. Figure 2 As shown, step S101 may specifically include:

[0079] S201. Obtain the anomaly detection threshold for the target detonation parameters.

[0080] Anomaly detection thresholds are reference values ​​used to determine whether target detonation parameters are abnormal, and their dimensions are consistent with those of the target detonation parameters. Specifically, the dimension of the anomaly detection threshold for detonation learning values ​​can be, for example, angle; the dimension of the anomaly detection threshold for fast detonation learning values ​​can be, for example, angle; and the dimension of the anomaly detection threshold for detonation signal intensity can be, for example, voltage.

[0081] One possible implementation is that the anomaly detection threshold can be stored in the non-volatile memory of the engine control unit, and the engine control unit can obtain the anomaly detection threshold by reading the data in the memory.

[0082] Another possible implementation is to obtain the anomaly detection threshold of the target knock parameters from the cloud through interaction with the cloud server corresponding to the vehicle.

[0083] For details on the specific parameters required for obtaining the anomaly discrimination thresholds for each target's detonation parameters, please refer to the descriptions in the subsequent embodiments.

[0084] S202. Based on the target knock parameters and the anomaly detection threshold, determine whether there is an engine knock anomaly.

[0085] One possible implementation involves comparing multiple target knock parameters with their corresponding anomaly detection thresholds to obtain a judgment result for each target knock parameter. Then, the multiple judgment results are weighted, and the presence of an engine knock anomaly is determined based on the weighted result. For example, the weighted result can be compared with a preset value; if it is greater than or equal to the preset value, the engine exhibits a knock anomaly; if it is less than the preset value, the engine does not exhibit a knock anomaly. The weights used in this weighting process can be determined according to actual needs, and this application does not impose any restrictions on them.

[0086] Another possible implementation is to compare the target knock parameters with an anomaly detection threshold. If at least one target knock parameter is greater than or equal to the anomaly detection threshold, then it is determined that the engine has a knock anomaly.

[0087] Another possible implementation involves comparing target knock parameters with anomaly detection thresholds and determining whether an engine knock anomaly exists based on the number of times each target knock parameter is greater than or equal to the anomaly detection threshold. This implementation can be achieved, for example, through the following sub-steps:

[0088] S2021. Based on the target detonation parameters and the anomaly discrimination threshold, determine the number of times the target detonation parameters are greater than or equal to the anomaly discrimination threshold.

[0089] In this step, based on the comparison results between the target detonation parameters and the anomaly discrimination threshold, the number of times each target detonation parameter is greater than or equal to its corresponding anomaly discrimination threshold can be accumulated, and the accumulated number of times for each target detonation parameter can be stored separately.

[0090] Alternatively, based on the comparison results between the target detonation parameters and the anomaly discrimination threshold, the number of times each target detonation parameter is greater than or equal to its corresponding anomaly discrimination threshold can be accumulated, and the accumulated counts corresponding to each target detonation parameter can be added together to obtain the target count.

[0091] Alternatively, based on the comparison results between the target detonation parameters and the anomaly discrimination threshold, the number of times each target detonation parameter is greater than or equal to its corresponding anomaly discrimination threshold can be accumulated, and the accumulated counts corresponding to each target detonation parameter can be weighted and merged to obtain the target count.

[0092] S2022. If the target number of times is greater than or equal to the preset number of times threshold, then it is determined that the engine has knocking abnormality.

[0093] The preset threshold number is a reference value used to determine the number of times an engine may experience knocking.

[0094] One possible implementation is to directly determine whether the engine has knocking abnormalities based on whether the cumulative target number of knocks is greater than or equal to a preset threshold. If the cumulative target number of knocks is greater than or equal to the preset threshold, then knocking abnormalities exist.

[0095] Another possible implementation is to set different preset frequency thresholds based on different engine operating conditions. Then, based on the engine's operating conditions, the corresponding preset frequency thresholds, and the target frequency, it can be determined whether the engine has knocking abnormalities. If the target frequency is greater than or equal to the preset frequency threshold for the operating condition, then it is determined that the engine has knocking abnormalities.

[0096] Another possible implementation is to determine whether the target number of times is greater than or equal to a preset threshold within a preset detection period. If it is greater than or equal to the threshold, then the engine is confirmed to have knocking abnormalities. Here, the preset detection period is the time range used to count the target number of times. For example, it can be set according to a preset duration (e.g., 10 seconds as a period) or determined according to the number of times engine knocking data is collected (e.g., 6000 collections as a period).

[0097] For example, the method to determine whether an engine has knocking abnormality can be as follows: the preset number threshold is 5 times, the preset detection period is 10 seconds, and if the target number is counted to be 6 times within 10 seconds, and 6 times is greater than the preset number threshold of 5 times, then the engine is determined to have knocking abnormality; if the engine is in high-speed operating condition, the preset number threshold can be set to 6 times, and if the target number is counted to be 7 times within 10 seconds, and 7 times is greater than the preset number threshold of 6 times, then the engine is determined to have knocking abnormality.

[0098] For example, taking a four-cylinder engine as an example, each cylinder block of the engine can correspond to a fault flag bit. The initial value of this fault flag bit indicates no knocking abnormality, for example, it can be true. When the knocking learning value, knocking fast learning value, and knocking signal intensity of a cylinder block are all greater than or equal to its corresponding abnormality discrimination threshold, the corresponding fault counter is incremented by 1. When the fault counter increments more than a preset limit (for example, when the value of the fault counter exceeds the preset limit of 15), the fault flag bit is modified from its initial value to a specific value to indicate that knocking abnormality exists in that cylinder block.

[0099] The method provided in this application compares the target knock parameter with an anomaly discrimination threshold or compares the target knock parameter with an anomaly discrimination threshold after weighting multiple target knock parameters, and counts the number of times the target knock parameter is greater than or equal to the anomaly discrimination threshold and compares it with a preset number threshold, so as to more accurately determine whether there is knock anomaly in the engine, thereby avoiding misjudgment caused by the random fluctuation of a single parameter and improving the accuracy and reliability of knock anomaly detection.

[0100] The following section details the acquisition of anomaly detection thresholds for each target detonation parameter, including detonation learning value, detonation fast learning value, and detonation signal intensity:

[0101] When the target detonation parameters include detonation learning values:

[0102] Figure 3 This is a flowchart illustrating another vehicle fault handling method provided in an embodiment of this application. Figure 3 As shown, step S201 may specifically include:

[0103] S301. Obtain the operating range of the engine.

[0104] The operating range of an engine can be determined by parameters such as engine speed (ENGRPM) and load. For example, the engine speed range can be from a first speed value to a second speed value, and the load range can be from a first load value to a second load value. The load can be, for example, the engine's mean effective indicated pressure (IMEP_MBT).

[0105] In this step, the engine speed can be collected from the speed sensor and the engine load can be collected from the pressure sensor. Based on the collected speed and load, the operating range of the engine can be determined.

[0106] For example, Figure 4 This is a schematic diagram illustrating an operating condition range provided in an embodiment of this application. For example... Figure 4As shown, the engine's operating range is divided into 15 units, each based on engine speed (ENGRPM) and mean effective indicated pressure (IMEP_MBT). Based on the engine's current speed and current mean effective indicated pressure, the operating conditions can be determined... Figure 4 The current operating condition range of the engine is determined from the operating condition range shown.

[0107] S302. Based on the operating condition range and the mapping relationship between the operating condition range and the anomaly discrimination parameters, the target anomaly discrimination parameters are obtained.

[0108] The mapping relationship between the operating condition range and the anomaly discrimination parameters can be obtained through experiments or simulations. For different operating condition ranges, the corresponding anomaly discrimination parameters can also be different. For example, within the operating condition range where the engine speed is from the first speed value to the third speed value and the load is from the first load value to the fourth load value, the target anomaly discrimination parameters corresponding to the current operating condition range of the engine can be determined according to the mapping relationship between the operating condition range and the anomaly discrimination parameters.

[0109] When the target knock parameters include knock learning values, the anomaly discrimination parameters corresponding to the knock learning values ​​may include knock threshold parameters. Optionally, the anomaly discrimination parameters corresponding to the knock learning values ​​may also include at least one of speed compensation parameters and intercooler post-temperature compensation parameters.

[0110] One possible implementation is that the anomaly discrimination parameters corresponding to the knock learning value only include the knock threshold parameter. In this case, the knock threshold parameter, i.e., the target anomaly discrimination parameter, can be obtained based on the engine block identifier, the operating condition range, and the mapping relationship between the engine block identifier, the operating condition range, and the anomaly discrimination parameters.

[0111] For example, Figure 5 This is a schematic diagram illustrating a mapping relationship provided in an embodiment of this application. The diagram uses a four-cylinder engine as an example. Figure 5 As shown, this mapping relationship is the mapping relationship between engine block identifier, operating condition range, and anomaly discrimination parameters. Figure 5 The horizontal axis (x) represents the cylinder block identifiers, namely cylinder block 1, cylinder block 2, cylinder block 3, and cylinder block 4. The vertical axis (y) represents the operating condition range identifiers, namely the 15 operating condition range units from 0 to 14. Figure 5 The value in the value represents the knock threshold parameter corresponding to different cylinder blocks and different operating conditions of the engine. For example, it can be the knock retraction angle threshold.

[0112] Another possible implementation involves obtaining the target anomaly discrimination parameters based on the operating condition range, engine state parameters, and the mapping relationship between the operating condition range, state parameters, and anomaly discrimination parameters. Specifically, this implementation can be achieved through the following sub-steps:

[0113] S3021. Obtain engine status parameters.

[0114] The status parameters include engine speed, intercooler temperature, and cylinder block identification. Engine speed can be obtained through a speed sensor, intercooler temperature through a temperature sensor, and cylinder block identification can be determined through the engine's serial number.

[0115] Cylinder block markings are used for the above Figure 5 The mapping relationship shown is used to obtain the knock threshold parameter. The intercooler temperature is used to obtain the intercooler temperature compensation parameter (i.e., the knock threshold parameter related to the intercooler temperature). The engine speed is used to obtain the engine speed compensation parameter (i.e., the knock threshold parameter related to the engine speed).

[0116] Optionally, the status parameters may include only the engine speed or the intercooler temperature, or both, in addition to the cylinder block identifier. When the status parameters include only the engine speed or the intercooler temperature, the target anomaly discrimination parameters corresponding to the knock learning value include the knock threshold parameter and the intercooler temperature compensation parameter or the engine speed compensation parameter. When the status parameters include the cylinder block identifier, engine speed, and the intercooler temperature, the target anomaly discrimination parameters corresponding to the knock learning value include the knock threshold parameter, the intercooler temperature compensation parameter, and the engine speed compensation parameter.

[0117] The following embodiments will be described using the cylinder block identification, speed, and intercooler temperature as examples of status parameters.

[0118] S3022. Based on the operating condition range, engine status parameters, and the mapping relationship between the operating condition range, status parameters, and anomaly discrimination parameters, the target anomaly discrimination parameters are obtained.

[0119] Among them, the target anomaly discrimination parameters include knock threshold parameters, speed compensation parameters, and temperature compensation parameters after intercooling.

[0120] In this step, the target anomaly discrimination parameters corresponding to each state parameter can be obtained based on the operating condition range, multiple state parameters of the engine, and the mapping relationship between the operating condition range, state parameters, and anomaly discrimination parameters.

[0121] For example, the knock threshold parameter can be obtained based on the operating condition range, cylinder block identification, and the mapping relationship between the operating condition range, cylinder block identification, and anomaly detection parameters; the speed compensation parameter can be obtained based on the operating condition range, engine speed, and the mapping relationship between the operating condition range, engine speed, and anomaly detection parameters; and the intercooler temperature compensation parameter can be obtained based on the operating condition range, intercooler temperature, and the mapping relationship between the operating condition range, intercooler temperature, and anomaly detection parameters.

[0122] For example, Figure 6 This is a schematic diagram illustrating another mapping relationship provided in an embodiment of this application. The diagram uses a four-cylinder engine as an example. Figure 6 As shown, this mapping relationship is the mapping relationship between speed, operating condition range, and anomaly detection parameters. Figure 6 The horizontal axis (x) represents the rotational speed, such as 1500, 1600, 1700, 2000, etc. The vertical axis (y) represents the operating condition range, which consists of 15 operating condition range units from 0 to 14. Figure 6 The value in the value represents the speed compensation parameter corresponding to different engine speeds and different operating conditions. For example, it can be used for knock angle threshold compensation.

[0123] For example, Figure 7 This is a schematic diagram illustrating yet another mapping relationship provided in an embodiment of this application. The diagram uses a four-cylinder engine as an example. Figure 7 As shown, this mapping relationship is the mapping relationship between the intercooled temperature, the operating condition range, and the anomaly detection parameters. Figure 7 The horizontal axis (x) represents the temperature after intercooling, i.e., 20, 30, 40, 50, etc. The vertical axis (y) represents the operating condition range, i.e., 15 operating condition range units from 0 to 14. Figure 7 The value in the value represents the intercooler temperature compensation parameter corresponding to different intercooler temperatures and different operating conditions of the engine. For example, it can be used for knock angle threshold compensation.

[0124] For example, the mapping relationship between the operating condition range, status parameters, and anomaly detection parameters (i.e., the above) Figures 5-7 The contents of the three mapping tables shown can be obtained based on the average of the first knock learning value test data corresponding to the first grade of fuel and the second knock learning value test data corresponding to the second grade of fuel.

[0125] For example, the first grade of fuel can be RON90 fuel, and the first knock learning value test data is the knock learning value obtained from experiments based on RON90 fuel. Based on this first knock learning value test data, an anomaly discrimination threshold corresponding to RON90 fuel can be set, representing the safe knock threshold of the engine using RON90 fuel. The second grade of fuel can be RON92 fuel, and the second knock learning value test data is the knock learning value obtained from experiments based on RON92 fuel. Based on this second knock learning value test data, an anomaly discrimination threshold corresponding to RON92 fuel can be set, representing the safe knock threshold of the engine using RON92 fuel.

[0126] Then, the average of the first knock learning value test data and the second knock learning value test data can be calculated to obtain the mapping relationship between the operating condition range, state parameters, and anomaly discrimination parameters. This is used to detect knock anomalies in vehicles using both RON92 and RON90 fuel, ensuring that no false alarms occur when the vehicle uses RON92 fuel and that knock anomalies can be detected more sensitively when using RON90 fuel.

[0127] S303. Determine the anomaly detection threshold based on the target anomaly detection parameters.

[0128] In this step, when the target anomaly discrimination parameters are obtained based on the operating condition range and engine state parameters, the anomaly discrimination thresholds for each engine block can be determined based on the knock threshold parameters, speed compensation parameters, and intercooler temperature compensation parameters.

[0129] Specifically, the knock threshold parameter, speed compensation parameter, and intercooler temperature compensation parameter can be summed to obtain the anomaly detection threshold. For example, if the knock threshold parameter is the first knock threshold parameter, the speed compensation parameter is the first speed compensation parameter, and the intercooler temperature compensation parameter is the first intercooler temperature compensation parameter, then the anomaly detection threshold is the first knock threshold parameter + the first speed compensation parameter + the first intercooler temperature compensation parameter.

[0130] For example, the implementation method for determining the anomaly discrimination threshold can be as follows: when the engine block identifier is the first identifier, the knock threshold parameter is 3 degrees within the operating condition range of 1000 rpm to 2000 rpm and 20% to 50% load; when the engine block identifier is the second identifier, the knock threshold parameter is 2.5 degrees within the same operating condition range; when the target anomaly discrimination parameter is obtained based on the operating condition range and engine state parameters, the knock threshold parameter is 3 degrees, the speed compensation parameter is 1 degree, and the intercooler temperature compensation parameter is 0.5 degrees; then the anomaly discrimination threshold is 3 + 1 + 0.5 = 4.5 degrees.

[0131] Optionally, it is possible to determine whether the knock learning value of each cylinder of the engine exceeds its corresponding anomaly detection threshold, thereby achieving knock anomaly detection at the cylinder level.

[0132] When the target detonation parameters include the fast learning value of detonation:

[0133] One possible implementation is to use the knock fast learning value threshold of each cylinder block of the engine as the anomaly discrimination threshold corresponding to the knock fast learning value of each cylinder block.

[0134] Another possible implementation is to use the weighted fusion value (such as the mean) of the knock fast learning value threshold of each cylinder block of the engine as the anomaly discrimination threshold corresponding to the knock fast learning value of the engine.

[0135] In both of the above implementation methods, the knock fast learning value threshold (i.e., the anomaly discrimination threshold corresponding to the knock fast learning value) can be obtained based on the knock fast learning value test data corresponding to the third grade fuel. For example, the knock fast learning value test data corresponding to the third grade fuel consists of knock fast learning values ​​collected under different operating conditions. These knock fast learning values ​​are statistically analyzed to obtain the anomaly discrimination threshold corresponding to the knock fast learning value.

[0136] For example, the third grade fuel could be RON90 fuel, so as to accurately identify knocking abnormalities when the engine is using RON90 fuel and reduce false alarms.

[0137] When the target detonation parameters include the detonation signal intensity:

[0138] The aforementioned step S201 may specifically include:

[0139] Based on the engine block markings and engine speed, anomaly detection thresholds for the knock signal intensity corresponding to each cylinder block are obtained.

[0140] Specifically, the mapping relationship between engine cylinder block identification, engine speed, and the anomaly detection threshold for knock signal intensity can be obtained through experiments or simulations. For example, when the engine cylinder block identification is the first identification, the anomaly detection threshold for knock signal intensity is the first knock signal intensity threshold within the range of engine speeds from the first to the third speed value; when the engine cylinder block identification is the second identification, the anomaly detection threshold for knock signal intensity is the second knock signal intensity threshold within the same speed range. For instance, the corresponding anomaly detection threshold for knock signal intensity can be found based on the engine cylinder block identification and engine speed.

[0141] For example, Figure 8 This is a schematic diagram illustrating another mapping relationship provided in an embodiment of this application. The diagram uses a four-cylinder engine as an example. Figure 8As shown, this mapping relationship is the mapping relationship between the engine speed, cylinder block identifier, and anomaly detection parameters. Figure 8 The horizontal axis (x) represents the cylinder block designation, i.e., cylinder block 1, cylinder block 2, cylinder block 3, cylinder block 4, etc. The vertical axis (y) represents the rotational speed, from 400 to 6400 revolutions per minute. Figure 8 The value in the value represents the threshold for identifying abnormal knock signal intensity for different engine speeds and different cylinder blocks.

[0142] In this implementation, the abnormal judgment threshold of the knock signal intensity corresponding to each cylinder of the engine can be determined based on the detected knock signal intensity and the current engine speed. Then, by comparing the knock signal intensity of each cylinder with the abnormal judgment threshold, it can be determined whether there is a knock abnormality caused by the knock signal intensity exceeding the limit.

[0143] Figure 9 This is a schematic flowchart illustrating another vehicle fault handling method provided in an embodiment of this application. Figure 9 As shown, the method may further include:

[0144] S901. When the vehicle is in operation, determine whether the engine's operating parameters meet the preset enabling conditions.

[0145] The operating status parameters include at least one of engine speed and mean effective indicated pressure. Engine speed can be acquired by a speed sensor, and mean effective indicated pressure can be acquired by a pressure sensor.

[0146] The preset enabling conditions can be determined based on the engine's design parameters and operating requirements. Examples include engine speed greater than or equal to a first speed threshold, or average effective indicated pressure greater than or equal to a first pressure threshold, or engine speed greater than or equal to the first speed threshold and less than or equal to a second speed threshold, or average effective indicated pressure greater than or equal to the first pressure threshold and less than or equal to the second pressure threshold. Another example is engine speed greater than or equal to the first speed threshold and average effective indicated pressure greater than or equal to the first pressure threshold, or engine speed greater than or equal to the first speed threshold and less than or equal to the second speed threshold, and average effective indicated pressure greater than or equal to the first pressure threshold and less than or equal to the second pressure threshold.

[0147] In this step, the engine speed can be collected from the speed sensor, and the engine's average effective indicated pressure can be collected from the pressure sensor.

[0148] For example, the engine's operating state parameters can be determined to meet preset enabling conditions based on the engine speed, mean effective indicated pressure, preset enabling conditions corresponding to the engine speed, and preset enabling conditions corresponding to the mean effective indicated pressure. For instance, the preset enabling condition corresponding to the engine speed is [600, 10000]. If the engine speed is within this range, it indicates that the engine speed meets the preset enabling condition. Similarly, the preset enabling condition corresponding to the mean effective indicated pressure is [600, 10000]. If the mean effective indicated pressure is within this range, it indicates that the mean effective indicated pressure meets the preset enabling condition. When both conditions meet their corresponding preset enabling conditions, the engine's operating state parameters are determined to meet the preset enabling conditions. If at least one of the conditions does not meet its corresponding preset enabling condition, the engine's operating state parameters are determined to not meet the preset enabling conditions.

[0149] S902. If the conditions are met, the knocking anomaly detection process will be initiated.

[0150] The detonation anomaly detection process can be initiated by sending a start command to the ECM. For example, the ECM sends a start command to the detonation sensor, causing the detonation sensor to start collecting the aforementioned target detonation parameters and return the collected target detonation parameters to the ECM.

[0151] Specifically, after the engine's operating parameters meet the preset enabling conditions, the engine's knock anomaly detection flag can be enabled. For example, the knock anomaly detection flag (such as DLCFECM) can be set to true to indicate that the knock anomaly detection function has been activated.

[0152] Then, the value of the detection counter can be increased each time the target detonation parameter is sampled, or at a preset time interval. After the value of the detection counter reaches the preset value (such as 6000), the detection completion flag (such as DLCFSC) is set to true to indicate that the detonation anomaly detection of one cycle is completed.

[0153] Afterwards, if the knock anomaly detection function is still in the activated state, the value of the detection counter is initialized, and the detection completion flag is set to false (i.e., entering the next cycle of knock anomaly detection), to indicate that the knock anomaly detection of the current cycle has not yet been completed.

[0154] Optionally, the implementation method in this step can also be applied to each cylinder block of the engine to perform knock anomaly detection on each cylinder block separately, thereby more accurately locating the possible knock anomaly problem in each cylinder block, improving the accuracy and pertinence of knock anomaly detection, and thus effectively improving the overall operating stability and performance of the engine.

[0155] In this implementation, the knock anomaly detection flag DLCFECM can be changed to DLCFECM[x], where x is the cylinder block identifier. For example, the knock anomaly detection flags corresponding to the four cylinder blocks of a four-cylinder engine are DLCFECM[1], DLCFECM[2], DLCFECM[3], and DLCFECM[4]. Similarly, the detection completion flag DLCFSC can also be changed to DLCFSC[1], DLCFSC[2], DLCFSC[3], and DLCFSC[4]. Optionally, a detection counter can be configured for each cylinder block. The preset values ​​of the detection counters corresponding to different cylinder blocks can be the same or different. When the preset values ​​of the detection counters corresponding to different cylinder blocks are different, the different preset values ​​can be determined according to the operating differences of each cylinder block.

[0156] The method provided in this application determines whether the engine's operating parameters meet preset enabling conditions when the vehicle is in operation. If they do, the knock anomaly detection process is initiated. This ensures that the detection is performed when the engine is in a suitable operating state for knock anomaly detection, avoiding detection in unsuitable operating states such as the initial engine startup or idling, thereby improving the accuracy and reliability of knock anomaly detection.

[0157] Figure 10 This is a schematic diagram of a vehicle fault handling device provided in an embodiment of this application. Figure 10 As shown, the vehicle fault handling device may include: a processing module 11 and a control module 12.

[0158] The processing module 11 is used to determine whether there is an engine knocking abnormality when the vehicle is in operation, based on the target knocking parameters of the vehicle's engine. The target knocking parameters include at least one of the following: knocking learning value, knocking fast learning value, and knocking signal intensity.

[0159] The control module 12 is used to perform knock abnormality handling operations if the engine has knock abnormality. The knock abnormality handling operations include at least one of limiting the engine torque and outputting abnormality prompt information.

[0160] Optionally, the processing module 11 is specifically used to obtain the anomaly detection threshold of the target knock parameters. Based on the target knock parameters and the anomaly detection threshold, it is determined whether the engine has knock anomalies.

[0161] Optionally, the processing module 11 is specifically used to determine the target number of times the target knock parameter is greater than or equal to the anomaly discrimination threshold based on the target knock parameter and the anomaly discrimination threshold. If the target number is greater than or equal to a preset number threshold, it is determined that the engine has a knock anomaly.

[0162] Optionally, the processing module 11 is specifically used to determine that the engine has knocking abnormality if the target number is greater than or equal to the preset number threshold within the preset detection cycle.

[0163] Optionally, when the target knock parameters include knock learning values, processing module 11 is specifically used to obtain the engine's operating condition range. Based on the operating condition range and the mapping relationship between the operating condition range and the anomaly discrimination parameters, the target anomaly discrimination parameters are obtained. Based on the target anomaly discrimination parameters, an anomaly discrimination threshold is determined.

[0164] Optionally, processing module 11 is specifically used to acquire engine status parameters. Based on the operating condition range, engine status parameters, and the mapping relationship between the operating condition range, status parameters, and anomaly discrimination parameters, target anomaly discrimination parameters are obtained. Anomaly discrimination thresholds are determined based on knock threshold parameters, speed compensation parameters, and intercooler post-temperature compensation parameters. The status parameters include engine speed, intercooler post-temperature, and cylinder block identifier; the target anomaly discrimination parameters include knock threshold parameters, speed compensation parameters, and intercooler post-temperature compensation parameters.

[0165] Optionally, the mapping relationship between the operating condition range, status parameters, and anomaly discrimination parameters is obtained based on the average of the first knock learning value test data corresponding to the first grade of fuel and the second knock learning value test data corresponding to the second grade of fuel.

[0166] Optionally, when the target knock parameters include the fast knock learning value, the anomaly discrimination threshold is obtained based on the fast knock learning value test data corresponding to the third grade fuel.

[0167] Optionally, when the target knock parameters include knock signal intensity, the processing module 11 is specifically used to obtain the abnormal judgment threshold of the knock signal intensity corresponding to each cylinder based on the engine cylinder block identifier and the engine speed.

[0168] Optionally, the processing module 11 is further configured to determine whether the engine's operating status parameters meet preset enabling conditions when the vehicle is in operation. The operating status parameters include at least one of engine speed and mean effective indicated pressure. The control module 12 is further configured to initiate a knock anomaly detection process if the conditions are met.

[0169] The vehicle fault handling device provided in this application embodiment can execute the vehicle fault handling method in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described again here.

[0170] Figure 11 This is a schematic diagram of an electronic device provided in an embodiment of this application. The electronic device is used to execute the aforementioned vehicle fault handling method. Figure 11As shown, the electronic device 1100 may include at least one processor 1101, a memory 1102, and a communication interface 1103.

[0171] The memory 1102 is used to store programs. Specifically, the program may include program code, which includes computer operation instructions.

[0172] The memory 1102 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage.

[0173] The processor 1101 is used to execute computer execution instructions stored in the memory 1102 to implement the method described in the foregoing method embodiments. The processor 1101 may be a CPU, an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0174] The processor 1101 can communicate and interact with external devices through the communication interface 1103. In specific implementations, if the communication interface 1103, memory 1102, and processor 1101 are implemented independently, they can be interconnected via a bus to complete communication. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc., but this does not imply that there is only one bus or one type of bus.

[0175] Optionally, in a specific implementation, if the communication interface 1103, memory 1102 and processor 1101 are integrated on a single chip, then the communication interface 1103, memory 1102 and processor 1101 can communicate through an internal interface.

[0176] This application also provides a computer-readable storage medium, which may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. Specifically, the computer-readable storage medium stores program instructions, which are used in the methods described in the above embodiments.

[0177] This application also provides a program product including executable instructions stored in a readable storage medium. At least one processor of a computing device can read the executable instructions from the readable storage medium, and the at least one processor executes the executable instructions to cause the computing device to implement the above-described vehicle fault handling method.

[0178] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A vehicle fault handling method, characterized in that, The method includes: When the vehicle is in operation, it is determined whether the engine has knocking abnormality based on the target knocking parameters of the vehicle's engine. The target knocking parameters include at least one of knocking learning value, knocking fast learning value, and knocking signal intensity. If the engine has a knocking abnormality, a knocking abnormality handling operation is performed, which includes at least one of limiting the engine torque and outputting an abnormality prompt message.

2. The method according to claim 1, characterized in that, The step of determining whether the engine has knocking abnormalities based on the target knocking parameters of the vehicle's engine includes: Obtain the anomaly detection threshold for the target detonation parameters; Based on the target knock parameters and the anomaly discrimination threshold, it is determined whether the engine has a knock anomaly.

3. The method according to claim 2, characterized in that, The step of determining whether the engine has a knocking abnormality based on the target knocking parameters and the anomaly discrimination threshold includes: Based on the target detonation parameters and the anomaly detection threshold, determine the number of times the target detonation parameters are greater than or equal to the anomaly detection threshold; If the target number of times is greater than or equal to a preset number threshold, then it is determined that the engine has the knocking abnormality.

4. The method according to claim 3, characterized in that, The step of determining that the engine has the knocking abnormality if the target number is greater than or equal to a preset number threshold includes: If the target number of times is greater than or equal to the preset number threshold within the preset detection period, then it is determined that the engine has the knocking abnormality.

5. The method according to claim 2, characterized in that, The target detonation parameters include the detonation learning values, and the anomaly discrimination threshold for obtaining the target detonation parameters includes: Obtain the operating condition range of the engine; Based on the operating condition range and the mapping relationship between the operating condition range and the anomaly discrimination parameters, the target anomaly discrimination parameters are obtained; The anomaly detection threshold is determined based on the target anomaly detection parameters.

6. The method according to claim 5, characterized in that, The step of obtaining the target anomaly discrimination parameters based on the operating condition range and the mapping relationship between the operating condition range and the anomaly discrimination parameters includes: The status parameters of the engine are obtained, including engine speed, intercooler temperature, and cylinder block identification. Based on the operating condition range, the engine state parameters, and the mapping relationship between the operating condition range, state parameters, and anomaly discrimination parameters, the target anomaly discrimination parameters are obtained. The target anomaly discrimination parameters include knock threshold parameters, speed compensation parameters, and intercooler temperature compensation parameters. Determining the anomaly detection threshold based on the target anomaly detection parameters includes: The anomaly detection threshold is determined based on the knock threshold parameter, the speed compensation parameter, and the temperature compensation parameter after intercooling.

7. The method according to claim 6, characterized in that, The mapping relationship between the operating condition range, state parameters, and anomaly discrimination parameters is obtained based on the average of the first knock learning value test data corresponding to the first grade fuel and the second knock learning value test data corresponding to the second grade fuel.

8. The method according to claim 2, characterized in that, The target knock parameters include the knock fast learning value, and the anomaly discrimination threshold is obtained based on the knock fast learning value test data corresponding to the third grade fuel.

9. The method according to claim 2, characterized in that, The target detonation parameters include the detonation signal intensity, and the anomaly discrimination threshold for obtaining the target detonation parameters includes: Based on the cylinder block identification of the engine and the engine speed, an abnormality discrimination threshold for the knock signal intensity corresponding to each cylinder block is obtained.

10. The method according to any one of claims 1-9, characterized in that, The method further includes: When the vehicle is in operation, it is determined whether the engine's operating status parameters meet preset enabling conditions. The operating status parameters include at least one of engine speed and mean effective indicated pressure. If the conditions are met, the knock anomaly detection process will be initiated.

11. A vehicle fault handling device, characterized in that, The device includes: The processing module is used to determine whether there is a knocking abnormality in the engine based on the target knocking parameters of the engine of the vehicle when the vehicle is in operation. The target knocking parameters include at least one of knocking learning value, knocking fast learning value, and knocking signal intensity. The control module is configured to perform a knock anomaly handling operation if the engine has a knock anomaly, the knock anomaly handling operation including at least one of limiting the engine torque and outputting an anomaly prompt message.

12. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-10.

14. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-10.

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