Vehicle engine-based gear learning method, device, equipment and storage medium

Abstract

The present application relates to a kind of based on the tooth information learning method of vehicle engine, device, equipment and storage medium, the method is applied to EMS in vehicle;Including: obtaining the current mileage information and state information of vehicle, determine the preset mileage range to which mileage information belongs;Mileage information characterizes the cumulative fuel mileage of vehicle, state information characterizes the running state of vehicle;If according to the preset mileage range to which mileage information belongs, determine that state information satisfies preset tooth information learning trigger condition, then obtain the current factor set of engine;Factor set includes the current tooth factor of each cylinder of engine;If the current factor set of engine satisfies preset check condition, then according to the current factor set of engine and the historical set of engine, determine the target set of engine;Historical set is the target set determined out last time, target set includes the target factor of each cylinder of engine, and target factor represents tooth factor after tooth information learning.

Description

Technical Field

[0001] This invention relates to the field of automotive engine technology, and specifically to a method, apparatus, device, and storage medium for learning gear signals based on a vehicle engine. Background Technology

[0002] When an engine operates at high speeds and under heavy loads, significant machining deviations in the gearbox can lead to false alarms or incorrect cylinder identification in misfire detection, impacting driving experience and safety. Therefore, gearbox learning is necessary to ensure the quality of misfire detection.

[0003] However, conventional dental information learning is scheduled during the factory's off-line electrical inspection process, which wastes a lot of time and manpower, and dental information learning has poor flexibility. Summary of the Invention

[0004] The purpose of this invention is to provide a method, apparatus, device, and storage medium for learning gear signals based on vehicle engines, so as to improve the efficiency and flexibility of gear signal learning.

[0005] In a first aspect, the present invention provides a gear signal learning method based on a vehicle engine, which is applied to an engine management system (EMS) in a vehicle; the method includes:

[0006] The vehicle's current mileage and status information are obtained, and the preset mileage range to which the mileage information belongs is determined; wherein, the mileage information represents the vehicle's cumulative fuel mileage, and the status information represents the vehicle's operating status.

[0007] If the state information satisfies the preset gear learning trigger condition based on the preset mileage range to which the mileage information belongs, then the current factor set of the engine is obtained; wherein, the factor set includes the current gear information factors of each cylinder of the engine.

[0008] If the current factor set of the engine meets the preset verification conditions, then the target set of the engine is determined based on the current factor set of the engine and the historical set of the engine; wherein, the historical set is the previously determined target set, and the target set includes the target factors of each cylinder of the engine, and the target factors represent the gear signal factors after gear signal learning.

[0009] Secondly, the present invention provides a gear signal learning device based on a vehicle engine, which is applied to the engine management system (EMS) in a vehicle; the device includes:

[0010] An information acquisition unit is used to acquire the vehicle's current mileage information and status information, and determine the preset mileage range to which the mileage information belongs; wherein, the mileage information represents the vehicle's cumulative fuel mileage, and the status information represents the vehicle's operating status.

[0011] The condition judgment unit is used to obtain the current factor set of the engine if it is determined that the state information meets the preset gear learning trigger condition based on the preset mileage range to which the mileage information belongs; wherein the factor set includes the current gear information factors of each cylinder of the engine.

[0012] The factor determination unit is used to determine the target set of the engine based on the current factor set of the engine and the historical set of the engine if the current factor set of the engine meets the preset verification conditions; wherein the historical set is the previously determined target set, and the target set includes the target factors of each cylinder of the engine, and the target factors represent the tooth signal factors after tooth signal learning.

[0013] Thirdly, the present invention provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0014] The memory stores computer-executed instructions;

[0015] The processor executes computer execution instructions stored in the memory to implement the method as described in the first aspect.

[0016] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described in the first aspect.

[0017] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0018] This invention provides a method, apparatus, device, and storage medium for gear signal learning based on a vehicle engine. By acquiring the vehicle's current mileage information, a preset mileage range to which this mileage information belongs can be determined. Based on the preset mileage range to which the mileage information belongs, targeted conditional judgments are made on the state information to determine whether the state information meets preset gear signal learning trigger conditions, thereby deciding whether to acquire the engine's current factor set. The factor set includes the current gear signal factors of each cylinder of the engine. It is then determined whether the engine's current factor set meets preset verification conditions. If so, the engine's target set is determined based on the engine's current factor set and the engine's historical set, thus obtaining the gear signal factors after gear signal learning. During vehicle operation, by determining the vehicle's current fuel mileage range, different strategies for triggering gear signal learning are driven, supporting gear signal learning on the vehicle at any time, eliminating dependence on factory electrical inspection equipment, and improving the flexibility of gear signal learning. By combining the current factor set and the historical set, high-precision and highly robust gear signal learning is achieved, improving the efficiency and accuracy of gear signal factor determination. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0020] Figure 1 A schematic flowchart of a vehicle engine-based gear signal learning method provided in an embodiment of the present invention;

[0021] Figure 2 A schematic flowchart of a vehicle engine-based gear signal learning method provided in an embodiment of the present invention;

[0022] Figure 3 A schematic diagram of the interaction process between EMS and VCU provided in an embodiment of the present invention;

[0023] Figure 4 A schematic flowchart of a vehicle engine-based gear signal learning method provided in an embodiment of the present invention;

[0024] Figure 5 This is a schematic diagram of the EMS tooth signal learning process provided in an embodiment of the present invention;

[0025] Figure 6 This is a schematic diagram of the continuous tooth signal learning process provided in an embodiment of the present invention;

[0026] Figure 7 A structural block diagram of a vehicle engine-based gear signal learning device provided in an embodiment of the present invention;

[0027] Figure 8A structural block diagram of an electronic device provided in an embodiment of the present invention;

[0028] Figure 9 This is a structural block diagram of an electronic device provided in an embodiment of the present invention.

[0029] The accompanying drawings have illustrated specific embodiments of the invention, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the invention in any way, but rather to illustrate the concept of the invention to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0030] The embodiments of the present invention will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention and not for limiting the scope of protection of the present invention.

[0031] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0032] In the description of this invention, it should be understood that the terms "first," "second," "third," etc., are used only to distinguish similar objects and are not necessarily used to describe a specific order or sequence, nor should they be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances. Furthermore, in the description of this invention, unless otherwise stated, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0033] It should be noted that, due to space limitations, this specification does not exhaustively list all possible implementation methods. Those skilled in the art, after reading this specification, should be able to deduce that any combination of technical features can constitute an optional implementation method, provided that the technical features do not contradict each other. The following provides a detailed description of each embodiment.

[0034] During vehicle use, the OBD (On-Board Diagnostics) system needs to identify cylinders experiencing engine misfires. Currently, the industry standard for misfire noise signal (characterizing the smoothness of engine flywheel rotation) algorithms generally uses the time consumed by the cylinder driving the 58-tooth rotor during its power stroke as the signal source; this time will be referred to as the segmented time. Taking a four-cylinder engine as an example, ideally, from the start of power stroke in one cylinder to the start of power stroke in the next cylinder, under the same engine boundary conditions, the segmented time for each cylinder to perform power stroke should be the same. Therefore, when a misfire event such as poor combustion occurs in a cylinder, this segmented time will be prolonged due to the poor power stroke, thus making two consecutive segmented times uneven. Based on this segmented time behavior, mathematical processing can be performed to obtain the misfire noise signal. However, there may be deviations in the machining of the 58-tooth gear. When the engine is running at high speed and high load, the segment time values ​​will be generally smaller. At this time, if there are large machining deviations in the gear, it will amplify the unevenness of the segment time between two consecutive cylinders, leading to false alarms or incorrect cylinder identification in misfire detection. Therefore, it is necessary to calibrate the original segment time of the misfire noise signal through gear learning to ensure the quality of misfire detection.

[0035] In conventional hybrid vehicles, gear signal learning is typically conducted during the factory's off-line electrical inspection process. Factory personnel use electrical inspection equipment to trigger specific commands to control the vehicle into a specific fuel cut-off gear signal learning mode. This process requires a fixed electrical inspection station and necessitates specialized human resources investment in production line planning, process maintenance, and technical support.

[0036] In other words, current gear learning methods largely rely on production line electrical testing equipment to trigger a cut-off gear learning mode, which has problems such as dependence on dedicated diagnostic instruments, long processing time per vehicle, and the need to configure production line workstations and process maintenance resources. Under high-speed and high-load conditions, the machining deviation of the 58-tooth flywheel disc will amplify the unevenness of the segmented time, leading to misjudgment of engine misfire or cylinder identification by the OBD system, affecting emission compliance and vehicle reliability.

[0037] The present invention provides a method, apparatus, device and storage medium for learning gear signals based on a vehicle engine, which aims to solve the above-mentioned technical problems of the prior art.

[0038] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of the present invention will now be described with reference to the accompanying drawings.

[0039] Figure 1This is a flowchart illustrating a vehicle engine-based gear signal learning method according to an embodiment of the present invention. This method can be executed by a vehicle engine-based gear signal learning device. The method is applied to the engine management system (EMS) in a vehicle. Figure 1 As shown, the method includes the following steps:

[0040] S101. Obtain the vehicle's current mileage information and status information, and determine the preset mileage range to which the mileage information belongs; wherein, the mileage information represents the vehicle's cumulative fuel mileage, and the status information represents the vehicle's operating status.

[0041] For example, mileage information can refer to the equivalent mileage driven by the vehicle since it left the factory, corresponding to the cumulative fuel consumption. The EMS (Engine Management System) can obtain the current mileage information at any time. Status information can refer to observable parameters reflecting the real-time operating conditions of the vehicle, including but not limited to vehicle speed, engine speed, engine coolant temperature, ignition voltage, EMS fault code status, road type identification results, engine running time, battery discharge power, and drive mode identification. The EMS can obtain the current status information at any time.

[0042] The preset mileage range consists of several pre-defined continuous mileage intervals. Multiple preset mileage ranges can be defined; for example, the preset mileage range could include a first preset range, a second preset range, and a third preset range. The first preset range is 0-50km, the second preset range is 50-200km, and the third preset range is ≥200km. That is, the first preset range is shorter than the second preset range, and the second preset range is shorter than the third preset range. Each preset mileage range corresponds to a different intensity of the dental signal learning trigger strategy and the degree of VCU collaborative intervention, facilitating subsequent targeted processing and improving the completion rate of dental signal learning. For example, within the first preset range, since the fuel mileage is still relatively low, the need for gear signal learning is not urgent enough. The vehicle can passively meet the conditions for collecting gear signal factors before learning them. When the fuel mileage exceeds the first preset range and reaches the second preset range, the VCU can adjust the engine's operating mode to quickly meet the conditions for collecting gear signal factors, improving the learning efficiency. When the fuel mileage exceeds the second preset range and reaches the third preset range, the fuel mileage is relatively high. With the accumulation of fuel mileage, the error of the gear signal factors gradually increases, making the learning need more urgent. Especially in pure electric mode, the engine may be stopped. In this case, it is necessary to actively start the engine so that it can meet the conditions for collecting gear signal factors, improving the learning efficiency. In other words, by dividing the mileage into multiple ranges, different strategies can be used to collect gear signal factors according to the urgency of learning when the vehicle is at different fuel mileage levels. In the first preset range, the system passively waits for the collection conditions to be met, but does not perform intrusive control on the engine to avoid affecting the user experience. In the second preset range, the engine is appropriately adjusted, i.e., intrusive control is performed, which improves the efficiency of gear signal learning and has little impact on the user experience. In the third stage, forcibly starting the engine may have a minor impact on the user experience, but it enables rapid learning of gear signal factors, improves the learning accuracy of gear signal factors, and thus ensures the detection quality of subsequent misfires.

[0043] After determining the vehicle's current mileage information, it can be determined which preset mileage range this mileage information belongs to, thus identifying the preset mileage range to which the mileage information belongs. For example, if the mileage information is 20km, then the preset mileage range to which it belongs can be determined as the first preset range. In this embodiment, the current accumulated fuel mileage value can be read from the EMS's built-in mileage counter to determine the preset mileage range to which it belongs, thereby accurately identifying the current learning stage of the vehicle and providing a basis for subsequent differentiated triggering logic.

[0044] S102. If the state information meets the preset gear learning trigger condition based on the preset mileage range to which the mileage information belongs, then obtain the current factor set of the engine; wherein the factor set includes the current gear information factors of each cylinder of the engine.

[0045] For example, the preset gear signal learning trigger condition can refer to the constraint condition used to determine whether the current state information meets the prerequisite for collecting gear signal factors. Different preset mileage ranges can correspond to different trigger conditions. After determining the preset mileage range to which the mileage information belongs, the gear signal learning trigger condition corresponding to that preset mileage range can be determined. It is determined whether the current state information meets the gear signal learning trigger condition. If yes, the current factor set of the engine is obtained; if not, the current factor set is not obtained, and mileage information and state information are collected again for re-determination.

[0046] The current factor set of the engine includes the current gear signal factors for each cylinder. These gear signal factors can be correction factors obtained by weighting the segmented time corresponding to the power cycle of each cylinder within a single effective sampling window, based on the 58-tooth flywheel signal output by the crankshaft position sensor. Each gear signal factor corresponds to one cylinder and characterizes the gear signal deviation weight of that cylinder under the current operating condition. For a four-cylinder engine, this factor set can contain four scalar elements, which can be denoted as F1, F2, F3, and F4, respectively. In this embodiment, the gear signal factors can be calculated from the segmented time; the specific process for obtaining the gear signal factors is not limited in this embodiment.

[0047] This embodiment can retrieve the corresponding trigger conditions based on a preset mileage range, by looking up a table. It then logically compares each item of the real-time collected status information with the threshold values ​​in the trigger conditions. When all conditions are met, the tooth signal factor collection process is initiated, thus obtaining a reliable and robust timing for tooth signal factor collection and avoiding the introduction of noise data under transient or disturbed conditions. By dividing the mileage range into different ranges, the vehicle has the opportunity to learn tooth signal factors regardless of its fuel mileage, improving the completion rate of tooth signal learning. Furthermore, different mileage ranges correspond to different trigger conditions, allowing for targeted tooth signal learning based on the urgency of the learning within different mileage ranges. Generally, the higher the fuel mileage, the more urgent the need for tooth signal learning.

[0048] S103. If the current factor set of the engine meets the preset verification conditions, then the target set of the engine is determined based on the current factor set of the engine and the historical set of the engine; wherein, the historical set is the previously determined target set, and the target set includes the target factors of each cylinder of the engine, and the target factors represent the gear signal factors after gear signal learning.

[0049] For example, the preset verification conditions are used to evaluate the quality of the factor set obtained from a single acquisition. Their purpose is to eliminate data samples distorted by transient interference, sensor malfunctions, or unsteady combustion. After obtaining the current factor set, it is determined whether the current factor set meets the preset verification conditions. If so, the engine's historical data set can be obtained, and the target set is determined comprehensively based on the current factor set and the historical data set. If not, S101 and S102 are executed again to acquire a new factor set, and the judgment is performed again.

[0050] The engine's historical set can refer to the target set that was successfully verified and confirmed in the previous round. The contents of the historical set can be persistently stored in non-volatile memory as a baseline reference for the current iteration. The target set can refer to the final output obtained by fusing the current factor set (after verification) with the historical set. The target factors for each cylinder are used for subsequent gear signal deviation compensation in the OBD misfire noise signal. Both the historical set and the target set contain gear signal factors for each cylinder.

[0051] For example, the preset verification conditions can include a threshold for the tooth signal factor. The system checks if any tooth signal factor in the current factor set exceeds the preset threshold. If so, the preset verification conditions are not met; otherwise, they are met. If the preset verification conditions are met, for each cylinder, the average of the tooth signal factor of that cylinder in the current factor set and the tooth signal factor of that cylinder in the historical set can be calculated, or other calculations can be performed. The result is the target factor for that cylinder. The target factors of all cylinders are then combined into a target set.

[0052] In this embodiment, the gear information factor of each cylinder in the current factor set can be subtracted from the gear information factors of its counterpart cylinders (e.g., cylinders 1 and 4 in a four-cylinder engine, and cylinders 2 and 3 in a four-cylinder engine), and the absolute deviation can be determined to be less than a preset first deviation threshold (e.g., ±0.001). If all cylinder pair deviations meet the threshold, the verification is passed. This embodiment can also introduce a time series consistency test, which performs trend fitting between the current factor set and the most recent N historical sets, and removes abnormal samples that deviate from the regression line by more than a preset residual band, thereby improving the accuracy of gear information factor determination.

[0053] This invention provides a gear signal learning method based on a vehicle engine. By acquiring the vehicle's current mileage information, a preset mileage range to which this mileage information belongs can be determined. Based on the preset mileage range, the state information is subjected to targeted conditional judgment to determine whether the state information meets preset gear signal learning trigger conditions, thereby deciding whether to acquire the engine's current factor set. The factor set includes the current gear signal factors of each cylinder of the engine. It is then determined whether the engine's current factor set meets preset verification conditions. If so, the engine's target set is determined based on the engine's current factor set and its historical set, thus obtaining the gear signal factors after gear signal learning. During vehicle operation, by determining the vehicle's current fuel mileage range, different strategies for triggering gear signal learning are driven, supporting gear signal learning on the vehicle at any time, eliminating reliance on factory electrical inspection equipment, and improving the flexibility of gear signal learning. By combining the current factor set and the historical set, high-precision and highly robust gear signal learning is achieved, improving the efficiency and accuracy of gear signal factor determination.

[0054] Figure 2 This is a flowchart illustrating a tooth signal learning method based on a vehicle engine, which is an optional embodiment based on the above embodiments.

[0055] In this embodiment, if the state information meets the preset gear learning trigger condition based on the preset mileage range to which the mileage information belongs, then the current factor set of the engine is obtained, including: determining the preset gear learning trigger condition corresponding to the vehicle based on the preset mileage range to which the mileage information belongs; and if the state information meets the preset gear learning trigger condition corresponding to the vehicle, then the current factor set of the engine is obtained.

[0056] like Figure 2 As shown, the method includes the following steps:

[0057] S201. Obtain the vehicle's current mileage information and status information, and determine the preset mileage range to which the mileage information belongs; wherein, the mileage information represents the vehicle's cumulative fuel mileage, and the status information represents the vehicle's operating status.

[0058] For example, this step can refer to step S101 above, and will not be repeated here.

[0059] S202. Based on the preset mileage range to which the mileage information belongs, determine the preset tooth signal learning trigger condition corresponding to the vehicle at present.

[0060] For example, the preset mileage range can refer to dividing the vehicle's accumulated fuel mileage into several continuous or non-continuous numerical intervals, each interval corresponding to a set of independently configured gear signal learning trigger logic. The preset gear signal learning trigger condition corresponding to the vehicle at present can refer to a set of operating state constraints that the EMS must satisfy to initiate gear signal learning within the current mileage range. In this embodiment, the trigger condition is used as the benchmark for subsequent state judgment and forms a correlation with the mileage range, so that the EMS can quickly locate the judgment rule to be executed at present without real-time parsing of complex logic, thereby improving the certainty and timeliness of trigger judgment, and supporting different vehicle platforms to flexibly adapt the learning strategy of each mileage stage through calibration.

[0061] In this embodiment, the preset tooth learning trigger condition corresponding to the vehicle is determined according to the preset mileage range to which the mileage information belongs. This includes: determining the preset tooth learning trigger condition corresponding to the preset mileage range to which the mileage information belongs, based on the preset association relationship, as the preset tooth learning trigger condition corresponding to the vehicle; wherein, the preset association relationship represents the association relationship between the preset mileage range and the preset tooth learning trigger condition.

[0062] Specifically, a preset relationship between a mileage range and a tooth signal learning trigger condition is pre-set and stored. This preset relationship can be in the form of a lookup table, a piecewise linear function, or a key-value pair index. Essentially, it decouples the abstract mileage stage from the specific working condition judgment logic, so that the calibration of the trigger condition is no longer hard-coded in the code and becomes data-driven.

[0063] This preset association can be calibrated before the vehicle leaves the factory and written to the EMS during software flashing. During vehicle operation, the EMS only needs to read the current mileage information, identify its preset mileage range, and then directly retrieve the trigger conditions that strictly correspond to the preset mileage range based on this association, thus obtaining the preset gear learning trigger conditions currently corresponding to the vehicle.

[0064] The advantage of this setup is that it explicitly binds the preset mileage range to the preset gear learning trigger conditions, achieving data-driven encapsulation of the trigger logic. This association allows for adaptation to the gear learning stage segmentation requirements of different vehicle models, calibration strategies, or scenarios, thereby ensuring the functional integrity and engineering feasibility of the entire gear learning process across multiple mileage stages.

[0065] S203. If the status information meets the preset tooth learning trigger condition corresponding to the current vehicle, then obtain the current factor set of the engine.

[0066] For example, after determining the preset gear learning trigger condition corresponding to the vehicle, it is determined whether the current state information meets the gear learning trigger condition. The state information may contain multiple operating parameters, and each operating parameter may have its own value range in the gear learning trigger condition. It can be determined whether each operating parameter falls within the value range defined in the trigger condition; if so, it is considered that the preset gear learning trigger condition corresponding to the vehicle is met.

[0067] The current factor set of the engine can refer to the set of values ​​characterizing the degree of gear deviation of each cylinder, which is collected and calculated in real time from the crankshaft / camshaft sensor signals by the EMS at the moment when the trigger condition is met. It includes at least the current gear factor corresponding to each cylinder of the engine, which reflects the normalized offset of the corresponding cylinder's flywheel tooth segment time relative to the ideal value under the current operating condition. In this embodiment, the acquisition of this factor set is only performed after the above-determined trigger condition is fully met, ensuring that the collected data is under controlled steady-state operating conditions and avoiding noise interference introduced by sudden changes in operating conditions.

[0068] In this embodiment, the trigger condition corresponding to the current mileage range can be retrieved from a preset mileage-trigger condition mapping table by means of table lookup matching, and used as the preset tooth signal learning trigger condition for the current vehicle.

[0069] In this embodiment, by explicitly structuring the mapping relationship between mileage and triggering conditions into a binding mechanism, the EMS can accurately switch triggering strategies for different mileage stages without increasing runtime logic complexity. Based on this, the triggering conditions are verified using status information to ensure that the factor set is collected only within a window of controlled operating conditions and reliable signals, providing a high-quality input data foundation for subsequent verification and target set determination.

[0070] In this embodiment, the preset mileage range to which the mileage information belongs is the first preset range, and the status information includes the vehicle's driving information and the engine's rotational speed information. If the status information meets the preset gear learning trigger condition corresponding to the vehicle, then the current factor set of the engine is obtained, including: if the vehicle's driving information meets the preset enabling condition, and the engine's rotational speed information is within the preset rotational speed range, then it is determined that the status information meets the preset gear learning trigger condition corresponding to the vehicle, and the current factor set of the engine is obtained.

[0071] Specifically, the first preset range represents the initial stage of low-mileage operation of the vehicle, during which the engine is running. For example, the first preset range is the mileage range where the vehicle's accumulated fuel mileage is less than 50km. Within the first preset range, the EMS does not need to request the VCU (Vehicle Control Unit) to coordinate operating conditions, passively waiting for the vehicle to meet preset conditions before triggering the collection of information factors. In other words, the first preset range serves as the initial segmentation basis for the information learning strategy, used to trigger non-intrusive learning requests. Non-intrusive requests represent passively waiting for the vehicle's operating conditions to meet preset enabling conditions and for the engine to run stably before learning, i.e., limiting the mileage boundary at which the system enters a completely passive waiting state, ensuring that learning behavior only occurs in the initial operating stage where the vehicle's mechanical state is stable, the impact of sensor aging is negligible, and there is no production line calibration data coverage, thus providing a unified benchmark for subsequent learning stages.

[0072] Status information can include vehicle driving information and engine speed information. Driving information can be data reflecting the dynamic operation of the vehicle and environmental constraints, while speed information can characterize the engine speed and its fluctuations.

[0073] The preset enabling conditions are used to determine whether the vehicle is currently in a learnable state. This involves determining whether the vehicle's driving conditions meet these preset conditions; for example, a preset enabling condition might be that the vehicle's speed is sufficient. A preset speed range is also included. When determining whether the driving information meets the preset enabling conditions, it's also possible to determine whether the engine speed is within the preset range. If the vehicle's driving information meets the preset enabling conditions and the engine speed is within the preset range, then the current state information is considered to meet the vehicle's current preset gear signal learning trigger condition, and the engine's current factor set can be obtained.

[0074] Determining whether the engine speed is within a preset range essentially means determining whether the engine is operating stably. In this embodiment, multiple conditions can be set to determine engine stability. For example, it can be determined whether the engine speed is within a preset range and whether the engine speed fluctuation is within a preset fluctuation range. If both are true, the engine is considered to be operating stably. If the vehicle's driving information meets preset enabling conditions and the engine is operating stably, the state information meets the preset gear learning trigger conditions corresponding to the current vehicle, and the current factor set of the engine can be obtained.

[0075] The beneficial effect of this setting is that, within the first preset range, the need for learning dental information is not urgent enough. The EMS triggers the first stage of non-intrusive dental learning request, passively waits for the vehicle's operating conditions to meet the boundary of dental information collection, and then begins to collect dental information factors. This supports the EMS in autonomously completing the learning start-up without VCU intervention, avoiding the impact of VCU intervention on the user's riding experience.

[0076] In this embodiment, the vehicle's driving information includes at least one of the following: EMS fault type information, vehicle speed information, road surface type information, ignition voltage information, engine running time information, and engine coolant temperature information. The vehicle's driving information meets preset enabling conditions, including: if the EMS fault type information is not a preset fault type, the vehicle speed information is within a preset speed range, the road surface type information is not a preset road surface type, the ignition voltage information is within a preset voltage range, the engine running time information exceeds a preset time threshold, and / or the engine coolant temperature information is within a preset temperature range, then the vehicle's driving information meets the preset enabling conditions.

[0077] Specifically, driving information can include EMS fault type information, vehicle speed information, road surface type information, ignition voltage information, engine running time information, engine coolant temperature information, and vehicle operating mode. EMS fault type information refers to the currently active fault code category identified and reported in real time by the EMS internal diagnostic module, characterizing the integrity of the EMS's own functions and the reliability of sensor signals. The EMS fault type information can determine whether there are faults interfering with the EMS's operation. Vehicle speed information refers to the vehicle's current instantaneous speed, collected by the vehicle speed sensor and transmitted to the EMS via the CAN bus. Road surface type information refers to the current road roughness level inferred from the vehicle acceleration sensor, suspension displacement signals, or historical wheel slip rate statistics, characterizing the vehicle's ride comfort. Ignition voltage information refers to the actual DC voltage value of the EMS power supply bus after the ignition switch is turned on. Engine running time information refers to the cumulative duration of continuous operation since the engine was successfully started. Engine coolant temperature information refers to the real-time temperature value measured after the coolant flows through the engine block, which can be collected by the coolant temperature sensor.

[0078] The preset enabling conditions can be a composite set of logical conditions consisting of general enabling conditions and specific enabling conditions. That is, the preset enabling conditions can include both general and specific enabling conditions. The general enabling conditions are used to exclude globally unlearnable states, while the specific enabling conditions are used to confirm that the local operating condition has entered a learning-ready state. These two can be used to construct a dual safety threshold, preventing false data acquisition due to system-level faults and ensuring that the engine has exited transient processes unfavorable to gear deviation identification, such as cold starts, transient transitions, and low loads, thereby improving the efficiency of single-shot factor acquisition.

[0079] General enabling conditions may include EMS non-interference gear faults, sufficient vehicle speed, vehicle driving on non-bumpy roads (bad road monitoring disabled), ignition voltage within a reasonable range, and the vehicle not being in the delay process of switching from parallel mode to series mode. In other words, it can determine whether the EMS fault type information is a preset fault type, whether the vehicle speed information is within a preset speed range, whether the road surface type information is a preset road surface type, and whether the ignition voltage information is within a preset voltage range. Preset fault types can refer to one or more of the following: crankshaft position sensor fault, camshaft position sensor fault, misfire fault, rich or lean fuel system fault, and intake system fault. This serves to eliminate unreliable gear signal conditions caused by critical sensor failure or abnormal basic combustion, thereby ensuring the physical validity of the collected time-segmented data. The preset speed range can be 60km / h to 120km / h, ensuring that the engine speed is within the effective sampling range while reducing the user's subjective perception of engine noise and vibration. The preset road surface type can be a bad road, a washboard road, or an unpaved road. When the identification result falls into one of the preset road surface types, the road surface type is determined not to meet the enabling conditions. The preset voltage range can be 11V to 16V, which covers the normal operating range of the battery and provides redundancy to cope with the voltage drop during cold starts and the output fluctuation of the generator under high load.

[0080] Special enabling conditions may include sufficient engine running time, engine coolant temperature within the target range, and not being in a delay process due to abnormal gear information factor collection. That is, it can determine whether the engine running time exceeds a preset time threshold and whether the engine coolant temperature is within a preset temperature range. The preset time threshold can be 60 seconds, which corresponds to the engineering experience window from start-up to when the coolant temperature, oil temperature, and combustion cycle of a typical four-cylinder engine tend to stabilize. The preset temperature range can be 70℃ to 110℃, which covers the optimal thermal efficiency operating range of most gasoline engines and is also the engineering calibration bandwidth for minimal thermal deformation of the gear disc material.

[0081] If the driving information simultaneously meets both general and specific enabling conditions, then the vehicle's driving information is considered to meet the preset enabling conditions. That is, if the EMS fault type information is not a preset fault type, the vehicle speed information is within a preset speed range, the road surface type information is not a preset road surface type, the ignition voltage information is within a preset voltage range, the engine running time information exceeds a preset time threshold, and the engine coolant temperature information is within a preset temperature range, then the vehicle's driving information is determined to meet the preset enabling conditions. It is possible that all of the above conditions must be met for the preset enabling conditions to be considered met, or that meeting only some of the above conditions is sufficient to meet the preset enabling conditions.

[0082] The beneficial effect of this setup is that it enables collaborative verification of multiple types of driving information, constructs a multi-dimensional safety barrier, ensures accurate triggering of dental signal learning, and improves the learning accuracy of dental signal factors.

[0083] In this embodiment, a vehicle controller (VCU) is deployed in the vehicle. The preset mileage range to which the mileage information belongs is a second preset range. The status information includes the vehicle's driving information. If the status information meets the preset gear learning trigger condition corresponding to the vehicle, the current factor set of the engine is obtained, including: if the vehicle's driving information meets the preset enabling condition, the engine's torque information and speed information are adjusted based on the VCU; if the engine's torque information is within a preset torque range and the engine's speed information is within a preset speed range, it is determined that the status information meets the preset gear learning trigger condition corresponding to the vehicle, and the current factor set of the engine is obtained.

[0084] Specifically, the values ​​in the second preset range are greater than those in the first preset range; that is, the second preset range indicates that the vehicle is in the next stage of the first preset range. The second preset range indicates that the vehicle's accumulated fuel mileage is in the middle range, for example, between 50km and 200km. This range corresponds to the vehicle having completed its initial break-in period but not yet entered a stable aging stage, possessing the mechanical and control foundation for active gear learning. The vehicle is equipped with a VCU, which is the core unit for coordinating the control of the entire vehicle's powertrain system, used to coordinate the operating strategies and condition scheduling of the engine, motor, battery, and transmission system. Driving information represents the vehicle's operating parameters that can be collected in real-time by the EMS during the current driving process and used to determine the feasibility of gear learning, including but not limited to at least one of the following: EMS fault type information, vehicle speed information, road surface type information, ignition voltage information, engine running time information, and engine coolant temperature information.

[0085] When the vehicle is within the second preset range, the EMS can issue an intrusive learning request. This intrusive learning request actively requests the VCU to coordinate the engine operating conditions to meet the learning boundary. Within the second preset range, the EMS's intrusive learning request is issued after satisfying general and special enabling conditions, continuously requesting the VCU to coordinate the learning conditions. That is, it first determines whether the vehicle's driving information meets the preset enabling conditions. If so, the VCU can adjust the learning conditions, i.e., coordinate the engine's torque and speed information. In this embodiment, coordinating the engine's torque and speed information means adjusting them to preset stable values. The preset enabling conditions are multi-dimensional entry thresholds set to ensure safe, reliable, and effective gear learning. Their function is to exclude unsuitable operating states for learning, such as sensor failure, powertrain limitations, abnormal thermal management, or external interference, thereby avoiding amplification of gear factor deviations due to data contamination. The preset enabling conditions corresponding to the second preset range can be the same as those corresponding to the first preset range.

[0086] In this embodiment, driving information may include vehicle speed, ignition voltage, operating mode, etc. For the second preset range, the preset enabling conditions may include general enabling conditions and special enabling conditions. General enabling conditions may include: EMS non-interference gear faults, including crankshaft and camshaft sensor-related faults, misfire faults, rich or lean fuel system faults, intake system-related faults, etc.; vehicle speed exceeding a preset threshold, which can be set based on NVH (Noise, Vibration, Harshness) target calibration to cover engine rotation noise and improve user experience. The threshold corresponding to different mileage ranges may be different; the threshold corresponding to the first preset range is 60 km / h, the threshold corresponding to the second preset range is 70 km / h, and the threshold corresponding to the third preset range is 40 km / h; bad road monitoring is disabled; ignition voltage is within the range of 11-16V, which can be calibrated; the vehicle is not in the delay process of switching from parallel mode to series mode. Special enabling conditions may include: engine running time exceeding 60 seconds (this time can be calibrated); engine coolant temperature within the range of 70-110℃ (this range can be calibrated); and the vehicle not being in a delay process due to abnormal collection of gear signal factors. It is possible to first determine whether the general enabling conditions are met, and then determine whether the special enabling conditions are met, or to determine whether both general and special enabling conditions are met simultaneously.

[0087] The VCU can coordinate the vehicle's operating conditions, that is, adjust the engine's operating status. When coordination is complete, the VCU can send a coordination success flag to the EMS, or send the adjusted engine torque and speed information to the EMS. Based on the received feedback, the EMS determines whether the engine is operating stably. If so, it can trigger gear signal factor collection, that is, it considers the status information to meet the preset gear signal learning trigger conditions corresponding to the current vehicle, and can obtain the current set of engine factors.

[0088] After receiving feedback from the VCU, the EMS can determine whether the current engine torque information is within the preset torque range and whether the engine speed information is within the preset speed range. If both are true, the EMS can be considered to have entered a stable engine torque control mode and can collect gear signal factors.

[0089] The beneficial effect of this setting is that, for the second preset range, under vehicle operating conditions, the EMS actively sends a tooth learning coordination request to the VCU. The VCU adjusts the engine's operating mode and controls the engine to enter a steady-state operating condition, thereby quickly meeting the collection conditions for tooth information factors. After receiving feedback permission from the VCU, the EMS begins to collect and calculate tooth deviation signals, breaking through the limitations of passive waiting conditions and significantly improving the success rate and convergence efficiency of tooth information learning.

[0090] In this embodiment, adjusting the engine's torque and speed information based on the VCU includes: sending an intrusive learning request to the VCU and receiving the engine's torque and speed information fed back by the VCU; wherein, the intrusive learning request is used to instruct the VCU to obtain the vehicle's current operating condition; if the priority of the current operating condition is lower than the priority of the learning condition, then the vehicle's current speed information is obtained; if the vehicle's current speed information is greater than or equal to a preset speed threshold, then the battery's discharge power is obtained; if the battery's discharge power is greater than or equal to a preset power threshold, then the engine's torque and speed information are adjusted after a preset delay time.

[0091] Specifically, after determining that the vehicle's driving information meets preset enabling conditions, the EMS can send an intrusive gear learning request to the VCU. Upon receiving the intrusive gear learning request, the VCU, based on preset gear communication condition coordination logic, controls the engine to enter a steady-state operating condition, thereby sending a successful condition coordination flag to the EMS. This flag can indicate successful condition coordination, or it can indicate the engine's current torque and speed information. Upon receiving the flag, the EMS determines whether the engine is operating stably, thereby triggering the collection of gear communication factors.

[0092] In the VCU's gear communication condition coordination logic, the VCU can obtain the vehicle's current operating condition. The vehicle's operating condition can characterize the vehicle's running status. For example, the vehicle's operating condition can include gear learning condition, severely restricted vehicle condition, generally restricted vehicle condition, external discharge condition, and battery overcharge protection condition. Different operating conditions have their own priorities. The VCU determines whether the priority of the current operating condition is lower than the priority of the gear learning condition. If so, it can continue to obtain the vehicle's current speed information; otherwise, it cannot continue gear learning and must operate according to the vehicle's current operating condition.

[0093] After determining that the priority of the current working condition is lower than the priority of the learning condition, the current vehicle speed information is compared with the preset vehicle speed threshold. If the current vehicle speed information is greater than or equal to the preset vehicle speed threshold, the battery discharge power is acquired. If the current vehicle speed information is less than the preset vehicle speed threshold, the learning process cannot continue, the learning process ends, or S201 and S202 are re-executed.

[0094] If the vehicle battery's discharge power can be obtained, it is compared with a preset power threshold. A delay time is preset. If the battery's discharge power is greater than or equal to the preset power threshold, the engine's operating state becomes relatively stable after the preset delay time. At this point, the engine's torque and speed information are adjusted to meet the requirements of the gear-training conditions. For example, the engine's torque and speed information are adjusted to a preset stable value to achieve coordination of the gear-training conditions. The coordination result is then sent to the EMS for subsequent collection of gear information factors.

[0095] The beneficial effect of this configuration is that it transforms the VCU into an intelligent collaborator with multi-level priority perception, multi-source operating condition fusion judgment, and a delayed execution mechanism. This transforms intrusive gear learning requests from simple command transmissions into a closed-loop decision-making process that integrates vehicle safety boundaries, energy state, and driving scenarios. Furthermore, the coordination success flag information output by the VCU is highly reliable and verifiable, providing solid technical support for the initiation timing, data validity determination, and anomaly handling procedures of EMS-side gear signal factor acquisition. Ultimately, this achieves highly robust and adaptable road-based autonomous learning of engine gear signal deviations.

[0096] In this embodiment, a vehicle control unit (VCU) is deployed in the vehicle. The preset mileage range to which the mileage information belongs is a third preset range. The status information includes at least one of the following: EMS fault type information, vehicle speed information, road surface type information, ignition voltage information, engine running time information, and engine coolant temperature information. If the status information meets the preset gear learning trigger conditions corresponding to the current vehicle, the current factor set of the engine is obtained, including: if the EMS fault type information is not a preset fault type, the vehicle speed information is within a preset speed range, the road surface type information is not a preset road surface type, and the ignition voltage information is within a preset voltage range, then the current state of the engine is determined; wherein, the current state is either a working state or a stopped state; if the current state of the engine is a stopped state, then the engine is started through the VCU; if the engine running time information exceeds a preset time threshold, and the engine coolant temperature information is within a preset temperature range, then the engine torque information and speed information are adjusted based on the VCU; if the engine torque information is within a preset torque range, and the engine speed information is within a preset speed range, then the status information is determined to meet the preset gear learning trigger conditions corresponding to the current vehicle, and the current factor set of the engine is obtained.

[0097] Specifically, the value in the third preset range is greater than the value in the second preset range; that is, the third preset range indicates that the vehicle is in the next stage of the second preset range. The third preset range indicates that the vehicle's accumulated fuel mileage is in a high mileage range, for example, a mileage range greater than or equal to 200 km. The status information may include driving information, including but not limited to at least one of the following: EMS fault type information, vehicle speed information, road surface type information, ignition voltage information, engine running time information, and engine coolant temperature information.

[0098] When the vehicle is within the third preset range, the EMS can issue an intrusive learning request. This request actively requests the VCU to coordinate engine operating conditions to meet the learning boundary. Within the third preset range, the EMS first determines whether the driving information meets the general enabling conditions. If the general enabling conditions are met, the EMS can directly request the VCU to start the engine and simultaneously begin judging specific enabling conditions. Once the specific enabling conditions are met, the EMS immediately issues an intrusive learning request, continuously requesting the VCU to coordinate the learning operating conditions. After receiving a successful VCU operating condition coordination signal, the EMS proceeds to judge engine operating stability conditions. If these conditions are met, the collection of information factors is triggered. It is worth noting that when the fuel mileage is within the third preset range, the vehicle can be in pure electric mode. In pure electric mode, the engine can be stopped. In this case, if the EMS meets the general enabling conditions, it can directly request the VCU to start the engine. However, if the engine is already running, the engine starting process can be omitted. That is, after the EMS meets the general enabling conditions, it can first determine the current state of the engine. If the current state of the engine is stopped, the engine can be started through the VCU; if the engine is in working state, the subsequent judgment process can be carried out directly.

[0099] In this embodiment, it is first determined whether the general enabling conditions are met, namely, whether the EMS fault type information is a preset fault type, whether the vehicle speed information is within a preset speed range, whether the road surface type information is a preset road surface type, and whether the ignition voltage information is within a preset voltage range. If the EMS fault type information is not a preset fault type, the vehicle speed information is within a preset speed range, the road surface type information is not a preset road surface type, and the ignition voltage information is within a preset voltage range, then the general enabling conditions are considered met, and the current state of the engine can be determined. If the current state of the engine is a stopped state, the engine is started via the VCU. That is, for the third preset range, after determining that the vehicle meets some conditions, the current state of the engine needs to be confirmed first, and only after confirming that the engine has started will it be determined whether the other part of the conditions are met. The second preset range does not need to determine the current state of the engine, but directly determines whether all conditions are met.

[0100] After the VCU starts the engine, it checks whether special enabling conditions are met. Specifically, it checks if the engine running time exceeds a preset time threshold and if the engine coolant temperature is within a preset temperature range. If the engine running time exceeds the preset time threshold and the engine coolant temperature is within the preset temperature range, the special enabling conditions are met, and an intrusive learning request can be sent to the VCU. Based on the VCU's gear-based operating condition coordination logic, the engine's torque and speed information are adjusted. If the engine is determined to be in a working state, the same special enabling conditions are checked: the engine running time exceeds a preset time threshold and the engine coolant temperature is within a preset temperature range. If the engine running time exceeds the preset time threshold and the engine coolant temperature is within the preset temperature range, the special enabling conditions are met, and an intrusive learning request can be sent to the VCU. Based on the VCU's gear-based operating condition coordination logic, the engine's torque and speed information are adjusted.

[0101] The EMS receives feedback information from the VCU to determine whether the engine is operating stably. For example, it can determine whether the engine torque information is within a preset torque range and whether the engine speed information is within a preset speed range. If the engine torque information is within the preset torque range and the engine speed information is within the preset speed range, then the engine is considered to be operating stably, meaning that the state information meets the preset gear signal learning trigger conditions corresponding to the current vehicle, and the current factor set of the engine can be obtained.

[0102] The beneficial effect of this setup is that within the third preset mileage range, the need for gear signal learning is more urgent. Therefore, the VCU can be triggered to force-start the engine based on general enabling conditions, and then the warm-up state can be confirmed based on special enabling conditions. Finally, the steady-state learning condition can be constructed by leveraging the VCU's coordinated control of torque and speed, achieving a paradigm upgrade from passively waiting for operating conditions to actively creating operating conditions. This allows for reliable collection and updating of gear signal factors even in traditional learning blind spots such as long-term vehicle parking, cold start-stop, and low-speed stationary conditions, fully supporting the robustness requirements for misfire diagnosis.

[0103] S204. If the current factor set of the engine meets the preset verification conditions, then the target set of the engine is determined based on the current factor set of the engine and the historical set of the engine; wherein, the historical set is the previously determined target set, and the target set includes the target factors of each cylinder of the engine, and the target factors represent the tooth signal factors after tooth signal learning.

[0104] For example, this step can refer to step S103 above, and will not be repeated here.

[0105] Figure 3This is a schematic diagram of the interaction process between EMS and VCU. Figure 3 In the process, the EMS enters the gear learning logic. First, it determines if the current gear learning is incomplete. If complete, the learning logic stops. If incomplete, it determines if the current accumulated fuel mileage exceeds a third preset range. If it does, the EMS needs to issue an intrusive gear learning request. At this point, the EMS determines if the vehicle's driving information meets the general enabling conditions. If not, it continues to acquire new driving information to determine the general enabling conditions. If met, it requests the VCU to start the engine. The VCU enters the engine control logic, and simultaneously, the EMS determines if the driving information meets the special enabling conditions. If not, it continues to acquire new driving information to determine the special usage conditions.

[0106] If the current cumulative fuel mileage is determined to be within the third preset range, then it is determined whether the current cumulative fuel mileage exceeds the second preset range. If it does, the EMS needs to issue an intrusive learning request. At this point, the EMS determines whether the vehicle's driving information meets the general enabling conditions. If not, it continues to acquire new driving information to determine the general enabling conditions; if it does, it determines whether the driving information meets the special enabling conditions. If not, it continues to acquire new driving information to determine the special usage conditions.

[0107] If the current cumulative fuel mileage does not exceed the second preset range, it means that the current cumulative fuel mileage is within the first preset range. In this case, the request that EMS needs to send is a non-invasive gear learning request. In this situation, EMS needs to determine whether the driving information simultaneously meets the general enabling conditions and the special enabling conditions. If not, it acquires new driving information to determine these two conditions. If they are met, it determines whether the engine is currently driving stably. If not, it continues to determine the engine until it is stable, at which point it can collect gear information factors.

[0108] For vehicles with accumulated fuel mileage within the second and third preset ranges, when driving information meets specific enabling conditions, the VCU enters the gear-based operating condition coordination logic. At this time, the VCU determines whether the current operating condition takes precedence over the learning gear-based operating condition. If so, the priority arbitration condition is not met, and the current operating condition is re-acquired for priority arbitration. If the current priority is lower than the learning gear-based operating condition, the priority arbitration condition is considered met, and vehicle speed can be further determined. The VCU then determines whether the vehicle speed meets the condition of being greater than or equal to a preset speed threshold. If not, the priority is re-evaluated; if so, the battery discharge power is acquired. The VCU then determines whether the battery discharge power meets the condition of being greater than or equal to a preset power threshold. If not, the priority is re-evaluated; if so, the current vehicle mode and operating condition are determined. If the vehicle is in a preset mode and preset operating condition, timing begins; if not, the priority is re-evaluated. In this embodiment, the preset mode can be a non-pure electric driving mode, and the preset operating condition can be a series operating condition.

[0109] The system checks if the preset delay time has been reached. If not, it continues timing until the preset delay time is reached, at which point the VCU controls the engine to enter a specific torque control mode. The VCU sends a signal indicating successful gear learning condition coordination to the EMS. The EMS then checks if the engine is running stably. If not, it continues to assess the engine's operating status; if so, it begins collecting gear signal factors.

[0110] This invention provides a gear signal learning method based on a vehicle engine. By acquiring the vehicle's current mileage information, a preset mileage range to which this mileage information belongs can be determined. Based on the preset mileage range, the state information is subjected to targeted conditional judgment to determine whether the state information meets preset gear signal learning trigger conditions, thereby deciding whether to acquire the engine's current factor set. The factor set includes the current gear signal factors of each cylinder of the engine. It is then determined whether the engine's current factor set meets preset verification conditions. If so, the engine's target set is determined based on the engine's current factor set and its historical set, thus obtaining the gear signal factors after gear signal learning. During vehicle operation, by determining the vehicle's current fuel mileage range, different strategies for triggering gear signal learning are driven, supporting gear signal learning on the vehicle at any time, eliminating reliance on factory electrical inspection equipment, and improving the flexibility of gear signal learning. By combining the current factor set and the historical set, high-precision and highly robust gear signal learning is achieved, improving the efficiency and accuracy of gear signal factor determination.

[0111] Figure 4 This is a flowchart illustrating a tooth signal learning method based on a vehicle engine, which is an optional embodiment based on the above embodiments.

[0112] In this embodiment, the current factor set of the engine satisfies the preset verification conditions, including: for each cylinder, obtaining the cylinder's gear information factor and the gear information factor of the cylinder's counterpart from the current factor set of the engine; if the deviation between the cylinder's gear information factor and the cylinder's counterpart's gear information factor is less than a preset first deviation threshold, then it is determined that the current factor set of the engine satisfies the preset verification conditions.

[0113] like Figure 4 As shown, the method includes the following steps:

[0114] S401. Obtain the vehicle's current mileage information and status information, and determine the preset mileage range to which the mileage information belongs; wherein, the mileage information represents the vehicle's cumulative fuel mileage, and the status information represents the vehicle's operating status.

[0115] For example, this step can refer to step S101 above, and will not be repeated here.

[0116] S402. If the state information meets the preset gear learning trigger condition based on the preset mileage range to which the mileage information belongs, then obtain the current factor set of the engine; wherein the factor set includes the current gear information factors of each cylinder of the engine.

[0117] For example, this step can refer to step S102 above, and will not be repeated here.

[0118] S403. For each cylinder, obtain the cylinder's gear information factor and the cylinder's paired gear information factor from the engine's current factor set.

[0119] For example, in a four-stroke reciprocating engine, the counterpart cylinder refers to the other cylinder that completes the power stroke when the crankshaft rotates half a turn (180 degrees). In a four-cylinder engine, cylinders 1 and 4 are counterpart cylinders, and cylinders 2 and 3 are counterpart cylinders. This correspondence is determined by the engine's firing order and crankshaft structure and does not change with operating conditions.

[0120] The gear signal factor represents the correction coefficient obtained after normalization or weighting of the flywheel tooth plate segment time corresponding to the corresponding cylinder within a single ignition cycle. It is used for subsequent tooth deviation compensation of the original segment time signal. The current factor set contains the gear signal factor for each cylinder. Therefore, for each cylinder, the gear signal factor for that cylinder and the gear signal factor for its counterpart cylinder can be obtained from the engine's current factor set.

[0121] S404. If the deviation between the gear signal factor of the cylinder and the gear signal factor of the cylinder is less than the preset first deviation threshold, then the current factor set of the engine is determined to meet the preset verification conditions. Based on the current factor set of the engine and the historical set of the engine, the target set of the engine is determined.

[0122] For example, the gear signal factor of a cylinder and its counterpart cylinder constitute a pair of verification units. If the deviation between the two significantly exceeds the normal manufacturing tolerance range, it indicates that the data acquisition may be affected by transient interference, such as single-cylinder knocking, fuel pulsation, short-term sensor noise, or ignition vibration. Under interference conditions, the reliability of the data decreases.

[0123] The preset verification conditions are used to determine whether the data in the factor set is reasonable, avoiding data learning errors. The absolute difference between gear information factors that are paired cylinders can be determined. A first deviation threshold is preset, and it is determined whether each difference is less than the preset first deviation threshold. If so, the current factor set of the engine is determined to meet the preset verification conditions; otherwise, it is considered not to meet the preset verification conditions.

[0124] Taking a four-cylinder engine as an example, the current factor set contains the gear information factors of cylinders 1 to 4, denoted as F1, F2, F3, and F4. First, the cylinder pair of cylinder 1 is identified as cylinder 4, and the cylinder pair of cylinder 2 is identified as cylinder 3. Then, |F1-F4| and |F2-F3| are calculated respectively. If both are less than the preset first deviation threshold, the factor set is deemed to have passed the verification; otherwise, it is deemed to have failed.

[0125] This embodiment constructs an intrinsic data self-consistency mechanism based on the structural symmetry of the engine body by comparing the gear information factors of each cylinder with its physical counterpart and using a first deviation threshold as a unified criterion. This mechanism does not rely on external reference benchmarks, requires no additional sensors or communication interactions, and can complete validity verification using only the internal coupling relationship of a single acquisition. It effectively filters out single-point distortions caused by instantaneous combustion anomalies, mechanical shocks, or electrical noise, improving the stability of gear information learning results.

[0126] In this embodiment, the method further includes: if the deviation between the gear signal factor of the cylinder and the gear signal factor of the cylinder is equal to or greater than a preset first deviation threshold, then it is determined that the current factor set of the engine does not meet the preset verification conditions, the current factor set of the engine is discarded, and a new factor set of the engine is obtained based on a preset delay time.

[0127] Specifically, the first deviation threshold is a preset tolerance boundary used to determine whether the consistency of the gear signal factors of the paired cylinders is within an acceptable range. The deviation between the gear signal factors of the paired cylinders is calculated. When a deviation exceeds the limit, it indicates that there are extreme operating conditions such as transient interference, local flywheel deformation, or ignition anomalies in the current sampling segment. Continuing to retain this factor set will lead to inaccurate calculations of subsequent target sets. By immediately discarding this factor set and initiating a delay mechanism, the transmission of abnormal data downstream can be blocked, providing the system with a time window for the operating conditions to return to a steady state.

[0128] In other words, when it is determined that the current factor set of the engine does not meet the preset verification conditions, the factor set collected this time can be discarded, and a new factor set can be collected. A preset delay time is set, after which the collection of a new factor set can begin, avoiding the collection of abnormal factor sets again. During the delay time, the gear signal acquisition enable signal can be turned off, and the coordination success flag response from the VCU can be blocked until the delay ends. The number of times the factor set is re-collected can be recorded, with a preset threshold. When the recorded number reaches the preset threshold, the gear signal learning method based on the vehicle engine can be restarted from S401.

[0129] The beneficial effect of this setting is that when the deviation of the cylinder gear information factor exceeds the limit, the current factor set is immediately discarded, the single sampling is verified, and the preset delay is enforced. This effectively avoids the resource waste problem caused by repeated sampling and verification failures under continuous harsh operating conditions, provides a necessary buffer period for the self-recovery of vehicle operating status, and improves the overall robustness and success rate of the gear information learning process.

[0130] In this embodiment, the target set of the engine is determined based on the current factor set and the historical factor set of the engine. This includes: for each cylinder, determining the initial factor of the cylinder based on the gear signal factor of the cylinder in the current factor set and the gear signal factor of the cylinder in the historical factor set of the engine; wherein, the initial factor represents the initially determined gear signal factor; if the deviation between the initial factor of the cylinder and a preset first factor threshold is less than a preset second deviation threshold, then the initial factor of the cylinder is subtracted from the preset second factor threshold to obtain the difference value corresponding to the cylinder; if the sum of the differences corresponding to each cylinder is less than a preset third deviation threshold, then the initial factor of the cylinder is determined as the target factor of the cylinder; and the target set of the engine is determined based on the target factors of each cylinder.

[0131] Specifically, the initial factor is an intermediate computational quantity used to characterize the learning results of single-cylinder gear signals. The initial factor can be a weighted fusion of the gear signal factors for that cylinder in the current factor set of the engine and the gear signal factors for that cylinder in the engine's historical set. That is, after determining that the current factor set of the engine meets the preset verification conditions, the previously determined target set is obtained as the historical set. The historical set contains the gear signal factors for each cylinder after the previous learning. In other words, the number of factors in the current factor set is the same as the number of factors in the historical set.

[0132] For each cylinder, the gear signal factor can be obtained from the current factor set and from the engine's historical data set. Based on these two factors, an initial factor for the cylinder can be derived. For example, the average of these two factors can be used as the initial factor. The initial factor serves as a transitional state representation between the current sample and the historical baseline, preserving the latest gear state change trend reflected in the current sampling while suppressing abrupt changes caused by single-shot noise, transient conditions, or sensor jitter, thus providing a stable input for subsequent hierarchical verification.

[0133] A first factor threshold is preset, which represents the ideal reference benchmark for the gear signal factor. For example, it could be an equivalent of 1, representing the theoretical gear signal factor value that each cylinder should have when there is no gear disc deviation. For each cylinder, the absolute difference between the initial factor of that cylinder and the first factor threshold is calculated, which yields the deviation between the initial factor of the cylinder and the preset first factor threshold. A second deviation threshold is preset to limit the acceptable fluctuation range of the initial factor of a single cylinder relative to the ideal benchmark, for example, a value of ±0.005. The deviation between the initial factor of the cylinder and the preset first factor threshold is compared with the preset second deviation threshold. If the deviation between the initial factor of each cylinder and the preset first factor threshold is less than the preset second deviation threshold, the initial factor of the cylinder can be subtracted from the preset second factor threshold to obtain the difference corresponding to that cylinder, i.e., the subtraction result. The second factor threshold is the benchmark value participating in the difference calculation, which is consistent with the first factor threshold or has a calibration offset relationship.

[0134] For each cylinder, there is a corresponding subtraction result. The sum of the subtraction results for each cylinder is calculated, yielding the sum of the differences for each cylinder. A third deviation threshold is pre-set, limiting the allowable cumulative deviation of the sum of differences for all cylinders. The sum of differences for each cylinder is compared to the third deviation threshold. If the sum of differences for all cylinders is less than the pre-set threshold, the initial factor for that cylinder is determined as its final target factor. The target factor is the gear signal calibration parameter ultimately written into non-volatile memory and used for subsequent misfire signal correction. As a gear signal deviation correction amount verified by double validation, the target factor participates in the segmented time compensation calculation in the OBD system, thereby improving the accuracy of misfire detection and cylinder determination robustness.

[0135] After obtaining the target factors for each cylinder, the set of all target factors is defined as the target set. That is, the target set is an ordered set composed of the target factors of all cylinders, and its structure is consistent with the current factor set and the historical factor set of the engine.

[0136] The beneficial effect of this setup is that by combining current and historical factors, initial factors for each cylinder are obtained, enabling continuous single-cylinder verification. The initial factors for each cylinder are then compared with a first factor threshold for single-cylinder deviation verification. For initial factors that pass verification, the difference between the initial factor and a second factor threshold is calculated. Finally, the sum of the differences for each cylinder is compared with a third deviation threshold at the system level, achieving comprehensive verification of each cylinder. This allows for the selection of initial factors that satisfy both single-cylinder rationality and overall cylinder consistency as target factors. This achieves dual filtering of the gear signal learning results, preventing abnormal disturbances in a single cylinder from causing overall updates, and avoiding systemic drift caused by the accumulation of deviations in multiple cylinders in the same direction, thus ensuring the stability of gear signal learning results under road conditions.

[0137] In this embodiment, multiple combinations of judgments can be made based on single-sample cylinder sequence verification, single-sample deviation verification between cylinders, deviation verification of each cylinder under multiple sampling, and cumulative deviation verification of each cylinder under multiple sampling. This enables the discarding or resetting of outliers, thereby achieving systematic and continuous deviation processing, continuously reducing the impact of deviations on the gear signal learning results, and improving the accuracy of gear signal learning.

[0138] In this embodiment, the method further includes: if the deviation between the initial factor of the cylinder and the preset first factor threshold is equal to or greater than the preset second deviation threshold, then the current factor set of the engine is determined as abnormal data, the abnormal data is discarded, and the number of times the abnormal data is discarded is recorded; if the sum of the differences corresponding to each cylinder is equal to or greater than the preset third deviation threshold, then the current factor set of the engine is determined as abnormal data, the abnormal data is discarded, and the number of times the abnormal data is discarded is recorded.

[0139] Specifically, after obtaining the initial factors for each cylinder, for each cylinder, the initial factor is compared with a first factor threshold. If the deviation between the initial factor of a cylinder and the preset first factor threshold is equal to or greater than a preset second deviation threshold, the current factor set of the engine can be identified as abnormal data, discarded (i.e., the current factor set is discarded), and a new factor set of the engine is obtained based on a preset delay time. The number of times abnormal data is discarded is recorded, i.e., the number of times the factor set is re-acquired is recorded. A preset threshold for the number of times is set, and when the number of times recorded reaches the preset threshold, the engine-based gear signal learning can be restarted from step S401.

[0140] After obtaining the sum of the differences corresponding to each cylinder, the sum of the differences corresponding to each cylinder can be compared with a preset third deviation threshold. If the sum of the differences corresponding to each cylinder is equal to or greater than the preset third deviation threshold, the current factor set of the engine can be identified as abnormal data, discarded (i.e., the current factor set is discarded), and a new factor set of the engine is obtained based on a preset delay time. The number of times abnormal data is discarded is recorded, i.e., the number of times the factor set is re-acquired is recorded. A preset threshold for the number of times is set. When the number of times recorded reaches the preset threshold, the engine-based gear signal learning can be restarted from step S401.

[0141] The beneficial effect of this setup is that it constructs a two-level anomaly identification mechanism, focusing on the sudden inaccuracies of individual cylinders and the systematic deviation of multiple cylinders as a whole. When anomalies are found, the current set of factors is discarded and the number of discards is increased, thus ensuring the learning accuracy of the gear signal learning process in road operation scenarios.

[0142] In this embodiment, the method further includes: if the number of discards is less than a preset threshold, then a new set of factors for the engine is obtained; if the number of discards is equal to or greater than the preset threshold, then the process of obtaining the current mileage and status information of the vehicle is repeated.

[0143] Specifically, the number of discards represents the number of times the current set of factors of the engine is discarded during the current tooth signal learning process. The preset threshold is the maximum number of consecutive abnormal sampling failures allowed by the system, used to define the critical point between local retries and global resets.

[0144] Each time the discard count is updated, it is compared with the discard count threshold. If the discard count is less than the preset threshold, it indicates that the current learning process is still within a controllable abnormal range, and the system has the ability to recover convergence by supplementing new samples. At this time, the current milestone stage (first preset range, second preset range, or third preset range) and the corresponding state judgment logic are continued to be used. Only the temporary data cache on which this sampling failure depends is reset, without changing the stage judgment result and the VCU coordination strategy.

[0145] If the number of discards equals or exceeds a preset threshold, it indicates that, under the current mileage stage, multiple consecutive attempts have failed to obtain a set of factors that meet the verification conditions. This reflects that the adaptability of the corresponding operating conditions for this stage has failed, possibly due to misjudgment of mileage information, long-term sensor drift, continuous deterioration of the road environment, or systematic deviation of the vehicle's operating boundaries. In this case, the confirmation of the current stage is abandoned, and the learning process is rolled back to the initial input layer, that is, the vehicle's current accumulated fuel mileage information and real-time status information are reread to trigger a new round of mileage range determination.

[0146] The advantage of this setting is that by comparing the number of discards with a preset threshold, it dynamically decides whether to perform a local retry or a global reset. This helps to break out of the learning deadlock caused by the mismatch of phased operating conditions, and ultimately achieves robust closed-loop control of the gear signal learning process, ensuring reliable and adaptive gear signal factor calibration can be completed in complex road scenarios and throughout the entire vehicle life cycle.

[0147] Figure 5 This is a schematic diagram of the EMS dental information learning process. Figure 5 In this process, the collection of gear signal factors begins. First, segmented time data is collected, which can be based on a complete buffered sampling segment formed by multiple consecutive ignitions. Then, the segmented time data for each cylinder is collected and weights are calculated to obtain the gear signal factor for each cylinder. Various industry-standard methods can be used for weight calculation; this embodiment does not impose specific limitations. To ensure sample integrity, the correspondence between the cylinder number at the start and end of each sampling segment needs to be verified, i.e., cylinder sequence verification. If the cylinder sequence verification fails, the current sample is discarded to ensure data sampling accuracy. Taking a four-cylinder engine as an example, if a complete sample involves eight ignitions, and the first ignition is logic cylinder 1, then the last ignition cylinder should be logic cylinder 4.

[0148] After the cylinder sequence verification passes, the current gear signal factor for each cylinder is calculated. For each cylinder, the gear signal factor of the cylinder and the gear signal factor of its counterpart cylinder are determined. If the deviation between the cylinder's gear signal factor and its counterpart cylinder's gear signal factor is less than a preset first deviation threshold, the deviation of the counterpart cylinder factor is considered normal; otherwise, it is not abnormal. If abnormal, the current sampling is discarded, and sampling is repeated. If normal, the initial factor of the cylinder is determined based on the gear signal factors of the cylinders in the current factor set of the engine and the cylinder gear signal factors in the engine's historical factor set. For example, filtering or averaging can be performed. If the deviation between the initial factor of the cylinder and the preset first factor threshold is less than a preset second deviation threshold, the initial factor of a single cylinder is considered to be within the limit; otherwise, it exceeds the limit. If it does not exceed the limit, the sum of the differences of each cylinder is calculated, i.e., the cumulative deviation is obtained. It is then determined whether the cumulative deviation exceeds the limit. If the sum of the differences corresponding to each cylinder is less than a preset third deviation threshold, it does not exceed the limit; otherwise, it exceeds the limit.

[0149] If the cumulative deviation of each cylinder does not exceed the limit, it means that the factor set of this sampling is qualified, and the sampling quantity is incremented by one. The required number of samples is preset, and it is determined whether the current sampling quantity meets the standard. If yes, the initial factors obtained from this sampling are determined as target factors, and the tooth signal learning is completed; if not, the set of initial factors obtained from this sampling is used as a new historical set, and sampling is performed again until the sample quantity meets the standard.

[0150] If the initial factor of a single cylinder exceeds the limit or the cumulative deviation of each cylinder exceeds the limit, the number of sampling anomalies can be recorded. It can be determined whether the number of sampling anomalies has reached the preset threshold. If so, the number of sampling anomalies is reset, and the entire mileage information and status information are collected again or the gear learning is terminated directly. If not, the samples collected this time are discarded, and sampling is performed again after a preset delay time until the gear learning is completed or the number of anomalies reaches the threshold.

[0151] Figure 6 A flowchart illustrating the process of continuous dental information learning. Figure 6 In this process, after the vehicle completes its initial gear learning, if the calibration allows for continuous collection of gear information factors throughout the vehicle's lifespan, mileage checks can be bypassed, and non-invasive gear learning requests can be continuously activated. If continuous collection of gear information factors is not allowed, the entire gear learning process is completed, awaiting the next trigger. In new gear learning, the system can passively wait for the gear learning boundaries to be met—that is, if preset enabling conditions are met and stable engine operation is confirmed—before initiating new sampling. Based on... Figure 5The process determines whether the tooth information collection process has ended. If not, sampling continues; if it has ended, the tooth information factors are updated, the current learning phase ends, and then it is determined whether further continuous learning is needed. In other words, the tooth information learning process can be designed as continuous learning throughout the entire vehicle lifecycle. After the initial tooth information learning is completed, non-intrusive learning is continuously activated, and the next stage of tooth information factor collection begins once the tooth information learning boundary conditions are met. The tooth information learning results throughout the vehicle's lifecycle can be dynamically learned by performing a moving weighted average based on each collected tooth information factor, thus mitigating the impact of tooth deviation. This ensures that the tooth information learning results are not affected by factors such as sensor offset, component aging, 58-tooth gearbox repair, or combustion deviations in each cylinder.

[0152] This invention provides a gear signal learning method based on a vehicle engine. By acquiring the vehicle's current mileage information, a preset mileage range to which this mileage information belongs can be determined. Based on the preset mileage range, the state information is subjected to targeted conditional judgment to determine whether the state information meets preset gear signal learning trigger conditions, thereby deciding whether to acquire the engine's current factor set. The factor set includes the current gear signal factors of each cylinder of the engine. It is then determined whether the engine's current factor set meets preset verification conditions. If so, the engine's target set is determined based on the engine's current factor set and its historical set, thus obtaining the gear signal factors after gear signal learning. During vehicle operation, by determining the vehicle's current fuel mileage range, different strategies for triggering gear signal learning are driven, supporting gear signal learning on the vehicle at any time, eliminating reliance on factory electrical inspection equipment, and improving the flexibility of gear signal learning. By combining the current factor set and the historical set, high-precision and highly robust gear signal learning is achieved, improving the efficiency and accuracy of gear signal factor determination.

[0153] Figure 7 This is a structural block diagram of a vehicle engine-based gear signal learning device provided in an embodiment of the present invention. This device is applied to the engine management system (EMS) in a vehicle. For ease of explanation, only the parts relevant to the embodiments of this disclosure are shown. (Refer to...) Figure 7 The vehicle engine-based gear learning device 700 includes: an information acquisition unit 701, a condition judgment unit 702, and a factor determination unit 703.

[0154] The information acquisition unit 701 is used to acquire the vehicle's current mileage information and status information, and determine the preset mileage range to which the mileage information belongs; wherein, the mileage information represents the vehicle's cumulative fuel mileage, and the status information represents the vehicle's operating status.

[0155] The condition judgment unit 702 is used to obtain the current factor set of the engine if the state information meets the preset tooth signal learning trigger condition based on the preset mileage range to which the mileage information belongs; wherein the factor set includes the current tooth signal factors of each cylinder of the engine.

[0156] The factor determination unit 703 is used to determine the target set of the engine based on the current factor set of the engine and the historical set of the engine if the current factor set of the engine meets the preset verification conditions; wherein, the historical set is the previously determined target set, and the target set includes the target factors of each cylinder of the engine, and the target factors represent the tooth signal factors after tooth signal learning.

[0157] In one example, the condition judgment unit 702 includes:

[0158] The condition determination module is used to determine the preset tooth signal learning trigger conditions corresponding to the vehicle based on the preset mileage range to which the mileage information belongs.

[0159] The condition judgment module is used to obtain the current factor set of the engine if the state information meets the preset tooth learning trigger condition corresponding to the current vehicle.

[0160] In one example, the condition determination module is specifically used for:

[0161] Based on the preset association relationship, a preset gear signal learning trigger condition corresponding to the preset mileage range to which the mileage information belongs is determined, which is the preset gear signal learning trigger condition currently corresponding to the vehicle; wherein, the preset association relationship represents the association relationship between the preset mileage range and the preset gear signal learning trigger condition.

[0162] In one example, the mileage information belongs to a first preset mileage range, and the status information includes vehicle driving information and engine speed information; the condition judgment module is specifically used for:

[0163] If the vehicle's driving information meets the preset enabling conditions and the engine speed information is within the preset speed range, then the state information is determined to meet the preset gear learning trigger conditions corresponding to the current vehicle, and the current factor set of the engine is obtained.

[0164] In one example, the vehicle's driving information includes at least one of the following: EMS fault type information, vehicle speed information, road surface type information, ignition voltage information, engine running time information, and engine coolant temperature information; the condition judgment module is specifically used for:

[0165] If the EMS fault type information is not a preset fault type, the vehicle speed information is within a preset speed range, the road surface type information is not a preset road surface type, the ignition voltage information is within a preset voltage range, the engine running time information exceeds a preset time threshold, and / or the engine coolant temperature information is within a preset temperature range, then the vehicle's driving information is determined to meet the preset enabling conditions.

[0166] In one example, the vehicle is equipped with a vehicle control unit (VCU), the mileage information belongs to a second preset mileage range, and the status information includes the vehicle's driving information; the condition judgment module is specifically used for:

[0167] If the vehicle's driving information meets the preset enabling conditions, the engine's torque and speed information are adjusted based on the VCU.

[0168] If the engine torque information is within a preset torque range and the engine speed information is within a preset speed range, then the state information is determined to meet the preset gear learning trigger condition corresponding to the current vehicle, and the current factor set of the engine is obtained.

[0169] In one example, the conditional judgment module is specifically used for:

[0170] An intrusive learning request is sent to the VCU, and the engine torque and speed information fed back by the VCU are received. The intrusive learning request is used to instruct the VCU to obtain the current operating condition of the vehicle. If the priority of the current operating condition is lower than the priority of the learning condition, the current vehicle speed information is obtained. If the current vehicle speed information is greater than or equal to a preset vehicle speed threshold, the battery discharge power is obtained. If the battery discharge power is greater than or equal to a preset power threshold, the engine torque and speed information are adjusted after a preset delay time.

[0171] In one example, the vehicle is equipped with a vehicle control unit (VCU). The mileage information falls within a third preset mileage range. The status information includes at least one of the following: EMS fault type information, vehicle speed information, road surface type information, ignition voltage information, engine running time information, and engine coolant temperature information. The condition judgment module is specifically used for:

[0172] If the EMS fault type information is not a preset fault type, the vehicle speed information is within a preset speed range, the road surface type information is not a preset road surface type, and the ignition voltage information is within a preset voltage range, then the current state of the engine is determined; where the current state is either the working state or the stopped state.

[0173] If the engine is currently stopped, start the engine via VCU;

[0174] If the engine running time exceeds the preset time threshold and the engine coolant temperature is within the preset temperature range, the engine torque and speed information will be adjusted based on the VCU.

[0175] If the engine torque information is within a preset torque range and the engine speed information is within a preset speed range, then the state information is determined to meet the preset gear learning trigger condition corresponding to the current vehicle, and the current factor set of the engine is obtained.

[0176] In one example, factor determination unit 703 includes:

[0177] The factor acquisition module is used to acquire the gear information factor of the cylinder and the gear information factor of the cylinder relative to the cylinder from the current factor set of the engine for each cylinder.

[0178] The factor verification module is used to determine that the current factor set of the engine meets the preset verification conditions if the deviation between the gear signal factor of the cylinder and the gear signal factor of the cylinder is less than a preset first deviation threshold.

[0179] In one example, it also includes:

[0180] The deviation judgment unit is used to determine that the current factor set of the engine does not meet the preset verification conditions if the deviation between the gear signal factor of the cylinder and the gear signal factor of the cylinder is equal to or greater than a preset first deviation threshold, discard the current factor set of the engine, and obtain the new factor set of the engine based on a preset delay time.

[0181] In one example, factor determination unit 703 includes:

[0182] The initial determination module is used to determine the initial factor of each cylinder based on the gear information factor of the cylinder in the current factor set of the engine and the gear information factor of the cylinder in the historical set of the engine; wherein the initial factor represents the initially determined gear information factor.

[0183] The difference acquisition module is used to subtract the initial factor of the cylinder from the preset second factor threshold if the deviation between the initial factor of the cylinder and the preset first factor threshold is less than the preset second deviation threshold, so as to obtain the difference value corresponding to the cylinder.

[0184] The target determination module is used to determine the initial factor of the cylinder as the target factor of the cylinder if the sum of the differences corresponding to each cylinder is less than a preset third deviation threshold.

[0185] The set determination module is used to determine the target set of the engine based on the target factors of each cylinder.

[0186] In one example, it also includes:

[0187] The first discard unit is used to determine the current set of factors of the engine as abnormal data if the deviation between the initial factor of the cylinder and the preset first factor threshold is equal to or greater than the preset second deviation threshold, discard the abnormal data, and record the number of times the abnormal data is discarded.

[0188] The second discard unit is used to determine the current set of factors of the engine as abnormal data if the sum of the differences corresponding to each cylinder is equal to or greater than a preset third deviation threshold, discard the abnormal data, and record the number of times the abnormal data is discarded.

[0189] In one example, it also includes:

[0190] The number of discards is determined by a unit that, if the number of discards is less than a preset threshold, obtains the current set of factors for the engine.

[0191] The re-execution unit is used to re-execute the acquisition of the vehicle's current mileage and status information if the number of discards is equal to or greater than a preset threshold.

[0192] Figure 8 A structural block diagram of an electronic device provided in an embodiment of this application, such as... Figure 8 As shown, the electronic device includes: a memory 81 and a processor 82; the memory 81 is a memory used to store instructions executable by the processor 82.

[0193] The processor 82 is configured to perform the methods provided in the above embodiments.

[0194] The electronic device also includes a receiver 83 and a transmitter 84. The receiver 83 is used to receive instructions and data sent by other devices, and the transmitter 84 is used to send instructions and data to external devices.

[0195] Figure 9 This is a block diagram illustrating an electronic device according to an exemplary embodiment. The device may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, personal digital assistant, vehicle, or other similar device.

[0196] The device 900 may include one or more of the following components: a processing component 902, a memory 904, a power supply component 906, a multimedia component 908, an audio component 910, an input / output (I / O) interface 912, a sensor component 914, and a communication component 916.

[0197] Processing component 902 typically controls the overall operation of device 900, such as operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 902 may include one or more processors 920 to execute instructions to perform all or part of the steps of the methods described above. Furthermore, processing component 902 may include one or more modules to facilitate interaction between processing component 902 and other components. For example, processing component 902 may include a multimedia module to facilitate interaction between multimedia component 908 and processing component 902.

[0198] The device 900 may include one or more of the following components: a processing component 902, a memory 904, a power supply component 906, a multimedia component 908, an audio component 910, an input / output (I / O) interface 912, a sensor component 914, and a communication component 916.

[0199] Memory 904 is configured to store various types of data to support the operation of device 900. Examples of this data include instructions for any application or method operating on device 900, contact data, phonebook data, messages, pictures, videos, etc. Memory 904 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0200] Power supply component 906 provides power to various components of device 900. Power supply component 906 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power to device 900.

[0201] Multimedia component 908 includes a screen that provides an output interface between the device 900 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 908 includes a front-facing camera and / or a rear-facing camera. When the device 900 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0202] Audio component 910 is configured to output and / or input audio signals. For example, audio component 910 includes a microphone (MIC) configured to receive external audio signals when device 900 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 904 or transmitted via communication component 916. In some embodiments, audio component 910 also includes a speaker for outputting audio signals.

[0203] I / O interface 912 provides an interface between processing component 902 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0204] Sensor assembly 914 includes one or more sensors for providing status assessments of various aspects of device 900. For example, sensor assembly 914 may detect the on / off state of device 900, the relative positioning of components such as the display and keypad of device 900, changes in position of device 900 or a component of device 900, the presence or absence of user contact with device 900, orientation or acceleration / deceleration of device 900, and temperature changes of device 900. Sensor assembly 914 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 914 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 914 may also include an accelerometer, gyroscope, magnetometer, pressure sensor, or temperature sensor.

[0205] Communication component 916 is configured to facilitate wired or wireless communication between device 900 and other devices. Device 900 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 916 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 916 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0206] In an exemplary embodiment, the apparatus 900 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0207] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 904 including instructions, which can be executed by a processor 920 of the device 900 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0208] A non-transitory computer-readable storage medium, wherein instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the aforementioned tooth signal learning method based on a vehicle engine.

[0209] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0210] The above embodiments are merely preferred embodiments provided to fully illustrate the present invention, and the scope of protection of the present invention is not limited thereto. Equivalent substitutions or modifications made by those skilled in the art based on the present invention are all within the scope of protection of the present invention.

Claims

1. A tooth signal learning method based on a vehicle engine, characterized in that, The method is applied to the engine management system (EMS) in a vehicle; the method includes: The vehicle's current mileage and status information are obtained, and the preset mileage range to which the mileage information belongs is determined; wherein, the mileage information represents the vehicle's cumulative fuel mileage, and the status information represents the vehicle's operating status. If the state information satisfies the preset gear learning trigger condition based on the preset mileage range to which the mileage information belongs, then the current factor set of the engine is obtained; wherein, the factor set includes the current gear information factors of each cylinder of the engine. If the current factor set of the engine meets the preset verification conditions, then the target set of the engine is determined based on the current factor set of the engine and the historical set of the engine; wherein, the historical set is the previously determined target set, and the target set includes the target factors of each cylinder of the engine, and the target factors represent the gear signal factors after gear signal learning.

2. The method according to claim 1, characterized in that, If, based on the preset mileage range to which the mileage information belongs, it is determined that the status information meets the preset gear learning trigger condition, then the current factor set of the engine is obtained, including: Based on the preset mileage range to which the mileage information belongs, determine the preset tooth signal learning trigger condition currently corresponding to the vehicle; If the state information satisfies the preset gear learning trigger condition corresponding to the current vehicle, then the current factor set of the engine is obtained.

3. The method according to claim 2, characterized in that, The mileage information belongs to a first preset mileage range, and the status information includes vehicle driving information and engine speed information. If the state information satisfies the preset gear learning trigger condition corresponding to the current state of the vehicle, then the current set of factors of the engine is obtained, including: If the vehicle's driving information meets the preset enabling conditions and the engine's speed information is within the preset speed range, then the state information is determined to meet the preset gear learning trigger condition corresponding to the vehicle, and the current factor set of the engine is obtained.

4. The method according to claim 3, characterized in that, The vehicle's driving information includes at least one of the following: EMS fault type information, vehicle speed information, road surface type information, ignition voltage information, engine running time information, and engine coolant temperature information. The vehicle's driving information meets preset enabling conditions, including: If the EMS fault type information is not a preset fault type, the vehicle speed information is within a preset speed range, the road surface type information is not a preset road surface type, the ignition voltage information is within a preset voltage range, the engine running time information exceeds a preset time threshold, and / or the engine coolant temperature information is within a preset temperature range, then the vehicle's driving information is determined to meet the preset enabling conditions.

5. The method according to claim 2, characterized in that, The vehicle is equipped with a vehicle control unit (VCU), the mileage information belongs to a second preset mileage range, and the status information includes the vehicle's driving information. If the state information satisfies the preset gear learning trigger condition corresponding to the current state of the vehicle, then the current set of factors of the engine is obtained, including: If the vehicle's driving information meets the preset enabling conditions, the engine's torque and speed information are adjusted based on the VCU. If the engine torque information is within a preset torque range and the engine speed information is within a preset speed range, then the state information is determined to satisfy the preset gear learning trigger condition corresponding to the current vehicle, and the current factor set of the engine is obtained.

6. The method according to claim 5, characterized in that, Based on the VCU, the engine's torque and speed information are adjusted, including: An intrusive learning request is sent to the VCU, and the engine torque and speed information fed back by the VCU are received. The intrusive learning request instructs the VCU to acquire the vehicle's current operating condition. If the priority of the current operating condition is lower than the priority of the learning condition, the current vehicle speed information is acquired. If the current vehicle speed information is greater than or equal to a preset speed threshold, the battery discharge power is acquired. If the battery discharge power is greater than or equal to a preset power threshold, the engine torque and speed information are adjusted after a preset delay time.

7. The method according to claim 2, characterized in that, The vehicle is equipped with a vehicle control unit (VCU), the mileage information belongs to a third preset mileage range, and the status information includes at least one of the following: EMS fault type information, vehicle speed information, road surface type information, ignition voltage information, engine running time information, and engine coolant temperature information. If the state information satisfies the preset gear learning trigger condition corresponding to the current state of the vehicle, then the current set of factors of the engine is obtained, including: If the EMS fault type information is not a preset fault type, the vehicle speed information is within a preset speed range, the road surface type information is not a preset road surface type, and the ignition voltage information is within a preset voltage range, then the current state of the engine is determined; wherein, the current state is either a working state or a stopped state. If the engine is currently in a stopped state, then the engine is started via the VCU; If the engine running time exceeds a preset time threshold and the engine coolant temperature is within a preset temperature range, then the engine torque and speed information are adjusted based on the VCU. If the engine torque information is within a preset torque range and the engine speed information is within a preset speed range, then the state information is determined to satisfy the preset gear learning trigger condition corresponding to the current vehicle, and the current factor set of the engine is obtained.

8. The method according to claim 2, characterized in that, Based on the preset mileage range to which the mileage information belongs, determine the preset tooth learning trigger conditions currently corresponding to the vehicle, including: Based on a preset association relationship, a preset gear learning trigger condition corresponding to a preset mileage range to which the mileage information belongs is determined, which is the preset gear learning trigger condition currently corresponding to the vehicle; wherein, the preset association relationship represents the association relationship between the preset mileage range and the preset gear learning trigger condition.

9. The method according to claim 1, characterized in that, The current set of factors for the engine satisfies preset verification conditions, including: For each cylinder, obtain the gear information factor of the cylinder and the gear information factor of the cylinder's counterpart from the current factor set of the engine; If the deviation between the gear signal factor of the cylinder and the gear signal factor of the cylinder is less than a preset first deviation threshold, then it is determined that the current factor set of the engine meets the preset verification condition.

10. The method according to claim 9, characterized in that, Also includes: If the deviation between the gear signal factor of the cylinder and the gear signal factor of the cylinder is equal to or greater than a preset first deviation threshold, then it is determined that the current factor set of the engine does not meet the preset verification conditions, the current factor set of the engine is discarded, and a new factor set of the engine is obtained based on a preset delay time.

11. The method according to claim 1, characterized in that, Based on the current factor set and the historical factor set of the engine, the target set of the engine is determined, including: For each cylinder, an initial factor is determined based on the gear signal factor of the cylinder in the current factor set of the engine and the gear signal factor of the cylinder in the historical set of the engine; wherein the initial factor represents the initially determined gear signal factor. If the deviation between the initial factor of the cylinder and the preset first factor threshold is less than the preset second deviation threshold, then the initial factor of the cylinder is subtracted from the preset second factor threshold to obtain the difference value corresponding to the cylinder. If the sum of the differences corresponding to each cylinder is less than the preset third deviation threshold, then the initial factor of the cylinder is determined as the target factor of the cylinder. The target set of the engine is determined based on the target factors of each cylinder.

12. The method according to claim 11, characterized in that, Also includes: If the deviation between the initial factor of the cylinder and the preset first factor threshold is equal to or greater than the preset second deviation threshold, then the current factor set of the engine is determined as abnormal data, the abnormal data is discarded, and the number of times the abnormal data is discarded is recorded. If the sum of the differences corresponding to each cylinder is equal to or greater than the preset third deviation threshold, then the current factor set of the engine is determined as abnormal data, the abnormal data is discarded, and the number of times the abnormal data is discarded is recorded.

13. The method according to claim 12, characterized in that, Also includes: If the number of discards is less than a preset threshold, then obtain the engine's current new set of factors; If the number of discards is equal to or greater than a preset threshold, then the process of obtaining the vehicle's current mileage and status information is repeated.

14. A gear signal learning device based on a vehicle engine, characterized in that, The device is used in the engine management system (EMS) of a vehicle; the device includes: An information acquisition unit is used to acquire the vehicle's current mileage information and status information, and determine the preset mileage range to which the mileage information belongs; wherein, the mileage information represents the vehicle's cumulative fuel mileage, and the status information represents the vehicle's operating status. The condition judgment unit is used to obtain the current factor set of the engine if it is determined that the state information meets the preset gear learning trigger condition based on the preset mileage range to which the mileage information belongs; wherein the factor set includes the current gear information factors of each cylinder of the engine. The factor determination unit is used to determine the target set of the engine based on the current factor set of the engine and the historical set of the engine if the current factor set of the engine meets the preset verification conditions; wherein the historical set is the previously determined target set, and the target set includes the target factors of each cylinder of the engine, and the target factors represent the tooth signal factors after tooth signal learning.

15. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1-13.

16. 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 1-13.

17. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method of any one of claims 1-13.

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