Self-learning method and device of engine, vehicle, medium and program product

Abstract

The invention relates to the technical field of automobile power control, in particular to a self-learning method and device of an engine, a vehicle, a medium and a program product.The method comprises the steps that under the condition that it is detected that the engine is started, if the rotating speed of the engine is within a certain rotating speed interval, the engine is started; and if a rotor of the variable inlet cam timing system of the engine is located at the initial position and the rotor of the variable inlet cam timing system of the engine is located at the initial position, entering a continuous self-learning mode, and collecting camshaft and crankshaft position signals of the variable inlet cam timing system so as to perform phase correction according to the camshaft and crankshaft position signals. Therefore, the problem that the valve timing control effect and the engine performance are affected due to signal deviation or response lag caused by the fact that engine control is conducted depending on fixed parameters or only based on an open-loop adjusting mode in the prior art, long-term operation of the engine and frequent working condition changes in a hybrid power mode are difficult to adapt is solved.

Description

Technical Field

[0001] This application relates to the field of automotive power control technology, and in particular to a self-learning method, device, vehicle, medium, and program product for an engine. Background Technology

[0002] Among related technologies, the electric VCT (Variable Camshaft Timing) system is an engine valve control technology that directly drives the camshaft adjustment mechanism with an electric motor, enabling fast and precise control of valve timing. The electric VCT system does not rely on engine oil pressure, has a faster response speed, higher adjustment accuracy, and can ensure the stability of engine valve timing.

[0003] However, the relevant technologies often use fixed parameter control or rely solely on open-loop adjustment, which makes it difficult to adapt to the long-term operation of the engine and the frequent changes in operating conditions under hybrid mode. This makes it impossible to guarantee the camshaft adjustment accuracy, which may lead to signal deviation or response lag, thereby affecting the valve timing control effect and engine performance. This problem urgently needs to be solved. Summary of the Invention

[0004] This application provides a self-learning method, device, vehicle, medium, and program product for an engine to solve the problem that in related technologies, electric VCT control methods rely on fixed parameters or are based solely on open-loop adjustment, which makes it difficult to adapt to long-term engine operation and frequent changes in operating conditions under hybrid power mode, and may cause signal deviation or response lag, thereby affecting valve timing control effect and engine performance.

[0005] The first aspect of this application provides a self-learning method for an engine, comprising the following steps: detecting whether the engine is started; if the engine is started, determining whether the engine speed is within a first preset speed range; and if it is within the first preset speed range and the rotor of the variable intake camshaft timing system of the engine is in the initial position, entering a continuous self-learning mode, acquiring the camshaft and crankshaft position signals of the variable intake camshaft timing system, and performing phase correction based on the camshaft and crankshaft position signals.

[0006] Through the above technical means, the embodiments of this application can collect the camshaft and crankshaft position signals of the variable intake camshaft timing system based on the self-learning mode, and then perform phase correction. The self-learning mode can continuously correct the camshaft signal deviation, making the electric VCT control more precise and the engine running stably according to the MAP (Mapping Table). It can correct the phase deviation caused by the elongation of the timing chain, thereby improving the accuracy of engine phase control and overall operational stability.

[0007] Optionally, in one embodiment of this application, before detecting whether the engine is started, the method further includes: determining whether the engine meets the preset first self-learning conditions; if the first self-learning conditions are met, then entering the first self-learning mode, learning according to the preset MAP table, and determining the initial phase.

[0008] Through the above technical means, the embodiments of this application can determine whether the engine has entered the first self-learning mode according to the preset first self-learning conditions. When the engine enters the first self-learning mode, the initial phase can be determined to establish reference phase data, provide a reference for subsequent continuous self-learning, and ensure the accuracy of valve timing control and the reliability of system operation.

[0009] Optionally, in one embodiment of this application, the preset first self-learning conditions include: the engine speed is in a second preset speed range; the variable intake cam timing system is in the self-learning flag position and the duration reaches a preset duration.

[0010] Through the above technical means, the embodiments of this application can ensure that self-learning is only performed under appropriate working conditions by judging conditions such as engine speed, self-learning flag and set duration, thereby accurately collecting camshaft and crankshaft position signals, calculating and correcting phase deviation, improving the accuracy of electric VCT control, and making valve timing closer to the target angle.

[0011] Optionally, in one embodiment of this application, the method further includes: detecting whether the engine meets a preset change condition; and if the engine meets the preset change condition, re-entering the initial self-learning mode.

[0012] Through the above technical means, the embodiments of this application re-establish the reference phase data under engine change conditions, thereby ensuring the accuracy of camshaft phase control and the reliability of valve timing, and ensuring that the engine can operate stably and efficiently according to the design goals in subsequent operation.

[0013] Optionally, in one embodiment of this application, the phase correction based on the camshaft and crankshaft position signals includes: determining the actual phase angle based on the camshaft and crankshaft position signals; and performing phase correction based on the actual phase angle and the target phase angle.

[0014] Through the above technical means, the embodiments of this application can perform phase correction according to the actual phase angle and the target phase angle, which can eliminate the phase deviation between the camshaft and the crankshaft in real time, enabling the electric VCT actuator to accurately adjust the camshaft position, thereby improving the valve timing control accuracy and ensuring that the engine runs stably according to the MAP.

[0015] A second aspect of this application provides a self-learning device for an engine, comprising: a checking module for detecting whether the engine is started; a first judging module for judging whether the engine speed is within a first preset speed range when the engine is detected to be started; and a self-learning module for entering a continuous self-learning mode if the engine is within the first preset speed range and the rotor of the variable intake camshaft timing system of the engine is in the initial position, and for acquiring the camshaft and crankshaft position signals of the variable intake camshaft timing system to perform phase correction based on the camshaft and crankshaft position signals.

[0016] Through the above technical means, the embodiments of this application can collect the camshaft and crankshaft position signals of the variable intake camshaft timing system based on the self-learning mode, and then perform phase correction. The self-learning mode can continuously correct the camshaft signal deviation, making the electric VCT control more precise and the engine run stably according to the ECU MAP. It can correct the phase deviation caused by the elongation of the timing chain, thereby improving the accuracy of engine phase control and overall operational stability.

[0017] Optionally, in one embodiment of this application, it further includes: a second judgment module, used to judge whether the engine meets the preset first self-learning conditions; and a determination module, used to enter the first self-learning mode if the first self-learning conditions are met, learn according to the preset MAP table, and determine the initial phase.

[0018] Through the above technical means, the embodiments of this application can determine whether the engine has entered the first self-learning mode according to the preset first self-learning conditions. When the engine enters the first self-learning mode, the initial phase can be determined to establish reference phase data, provide a reference for subsequent continuous self-learning, and ensure the accuracy of valve timing control and the reliability of system operation.

[0019] Optionally, in one embodiment of this application, the preset first self-learning conditions include: the engine speed is in a second preset speed range; the variable intake cam timing system is in the self-learning flag position and the duration reaches a preset duration.

[0020] Through the above technical means, the embodiments of this application can ensure that self-learning is only performed under appropriate working conditions by judging conditions such as engine speed, self-learning flag and set duration, thereby accurately collecting camshaft and crankshaft position signals, calculating and correcting phase deviation, improving the accuracy of electric VCT control, and making valve timing closer to the target angle.

[0021] Optionally, in one embodiment of this application, it further includes: a checking module for detecting whether the engine meets preset change conditions; and an entry module for re-entering the initial self-learning mode when the engine is detected to meet the preset change conditions.

[0022] Through the above technical means, the embodiments of this application re-establish the reference phase data under engine change conditions, thereby ensuring the accuracy of camshaft phase control and the reliability of valve timing, and ensuring that the engine can operate stably and efficiently according to the design goals in subsequent operation.

[0023] Optionally, in one embodiment of this application, the self-learning module includes: a determining unit, configured to determine the actual phase angle based on the camshaft and crankshaft position signals; and a correcting unit, configured to perform phase correction based on the actual phase angle and the target phase angle.

[0024] Through the above technical means, the embodiments of this application can perform phase correction according to the actual phase angle and the target phase angle, which can eliminate the phase deviation between the camshaft and the crankshaft in real time, enabling the electric VCT actuator to accurately adjust the camshaft position, thereby improving the valve timing control accuracy and ensuring that the engine runs stably according to the MAP.

[0025] A third aspect of this application provides a vehicle, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the self-learning method for an engine as described in the above embodiments.

[0026] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described self-learning method for an engine.

[0027] A fifth aspect of this application provides a computer program product, including a computer program that, when executed, is used to implement the self-learning method for the engine described above.

[0028] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0029] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a schematic diagram illustrating the operating principle of an electric VCT system according to an embodiment of this application; Figure 2This is a schematic diagram of the structure of an electric VCT actuator according to an embodiment of this application; Figure 3 This is a schematic diagram illustrating the working principle of the electric VCT self-learning mode after startup of a hybrid vehicle according to an embodiment of this application. Figure 4 This is a flowchart illustrating a self-learning method for an engine according to an embodiment of this application; Figure 5 This is a schematic diagram illustrating the initial self-learning principle of one embodiment of this application; Figure 6 This is a schematic diagram illustrating the continuous self-learning principle of one embodiment of this application; Figure 7 This is a block diagram of a self-learning device for an engine according to an embodiment of this application; Figure 8 This is a schematic diagram of the structure of a vehicle according to an embodiment of this application.

[0030] Figure label: 101-ECU (Electronic Control Unit), 102-Camshaft position sensor, 103-Crankshaft position sensor, 104-Electric VCT motor, 105-Electric VCT actuator, 106-Camshaft, 107-Battery; 201-Rotor, 202-Limit block, 203-Initial position, 204-Ignition position, 205-Maximum adjustment position; 10 - Engine self-learning device; 100 - Check module; 200 - First judgment module; 300 - Self-learning module; 801 - Memory; 802 - Processor; 803 - Communication interface. Detailed Implementation

[0031] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0032] The self-learning method, apparatus, vehicle, medium, and program product of the engine according to embodiments of this application are described below with reference to the accompanying drawings. To address the technical problems mentioned in the background art, where electric VCT control methods rely on fixed parameters or open-loop adjustment, making it difficult to adapt to long-term engine operation and frequent changes in operating conditions under hybrid mode, potentially causing signal deviations or response lags that affect valve timing control and engine performance, this application provides a self-learning method for engines. In this method, based on a self-learning mode, the camshaft and crankshaft position signals of the variable intake camshaft timing system are acquired. The corresponding relationship between the actual phase angle and the target phase angle deviation is then calculated and learned to generate a correction amount for phase correction. This self-learning mode continuously corrects camshaft signal deviations, making electric VCT control more precise. The engine can operate stably according to the ECU MAP. Simultaneously, it can correct phase deviations caused by timing chain elongation and component wear, thereby improving engine phase control accuracy and single-start control accuracy. Furthermore, it can optimize combustion efficiency, reduce emissions, enhance adaptability to hybrid and start-stop conditions, and improve the smoothness and reliability of long-term engine operation, achieving a comprehensive improvement in power performance and durability. This solves the problem that the related technologies are difficult to adapt to the long-term operation of the engine and the frequent changes in operating conditions in hybrid mode, which may lead to signal deviation or response lag, thereby affecting the valve timing control effect and engine performance.

[0033] Combination Figure 1 , Figure 2 , Figure 3 Before explaining the self-learning method for the engine provided in this application, the system structure and application scenarios involved in this application will be explained first.

[0034] like Figure 1 As shown, an electric VCT system typically includes an electric VCT motor 104 and an electric VCT actuator 105. The motor contains a chip that is powered by a battery 107. The ECU 101 can acquire camshaft and crankshaft position signals through the camshaft position sensor 102 and the crankshaft position sensor 103 and transmit them to the motor 104. The motor 104 can drive the actuator 105 after self-learning correction. The actuator 105 is connected to the camshaft 106 to adjust the camshaft phase.

[0035] Furthermore, such as Figure 2 As shown, the electric VCT actuator 105 typically includes a rotor 201, a limit block 202, an initial position 203, an ignition position 204, and a maximum adjustment position 205.

[0036] The rotor 201 can be unidirectionally limited by the stator limiting block 202, and after stopping, the rotor 201 may be in any position. During installation, auxiliary fixtures can be used to ensure that the rotor is in close contact with the stator limiting block 202. At this time, the actuator is in the initial position 203, the intake valve opens during the compression stroke, the engine starting cylinder pressure is <12 bar, and the starting vibration is <0.5 m / s². 2 This enables seamless engine starting. After the engine starts, the actuator rotates to the ignition position 204, the intake valve opens during the intake stroke, and the engine ignites. After engine ignition, the actuator adjusts between the ignition position and the maximum adjustment position 205 based on the ECU MAP.

[0037] It can be explained that due to factors such as machining errors, installation deviations, and wear during long-term use of the camshaft signal wheel, there may be a deviation between the actual acquired camshaft position signal and the theoretical design signal. The motor can record the actual difference through self-learning mode. After the ECU outputs the target angle, the electric VCT motor compensates for the difference during adjustment to achieve accurate phase adjustment.

[0038] As one possible way to achieve this, such as Figure 3 As shown, the self-learning mode of the electric VCT system in a hybrid vehicle typically has five working stages after startup: Phase 1: When the vehicle starts, it is in pure electric mode. The electric VCT actuator rotor is not in the initial position (e.g., 138°CA (Crank Angle)). The electric VCT motor is in state 0 (ready to shift) and has not performed self-learning.

[0039] Phase 2: Vehicle pure electric mode. The motor starts to drive the actuator rotor back to the initial position until the engine starts. The motor ready to shift changes from state 0 to state 1 to begin self-learning.

[0040] Phase 3: Vehicle pure electric mode. After the engine starts, the motor's ready-to-shift state changes from state 1 to state 2, completing self-learning.

[0041] Phase 4: Vehicle pure electric mode. After the ECU receives the motor ready to shift status 2, the motor drives the actuator to rotate from the initial position to the ignition position (18°CA).

[0042] Phase 5: Vehicle hybrid mode, engine ignition, electric VCT phase adjusted according to ECU MAP.

[0043] In this way, the embodiments of this application can perform phase correction based on a self-learning mode, thereby compensating for chain elongation, component wear and assembly errors, and maintaining the accuracy and stability of phase control under complex operating conditions such as frequent start-stop and pure electric switching in hybrid vehicles.

[0044] Based on the above system architecture and application scenarios, the self-learning method for the engine provided in this application can be realized. The self-learning method for the engine provided in this application will be described in detail below.

[0045] Specifically, Figure 4 This is a flowchart illustrating a self-learning method for an engine provided in an embodiment of this application.

[0046] like Figure 4 As shown, the self-learning method of this engine includes the following steps: In step S401, it is detected whether the engine is started.

[0047] The detection of whether the engine is started can be implemented by the vehicle control system or the engine ECU. Specifically, the vehicle control system can obtain engine speed signals, fuel injection signals, or ignition signals through the CAN (Controller Area Network) bus to determine whether the engine is running; the engine ECU can combine the crankshaft position sensor, camshaft position sensor, and combustion feedback signals to comprehensively determine whether the engine has started and entered a stable combustion state. These settings can be configured by those skilled in the art according to actual conditions, and no specific restrictions are imposed here.

[0048] In actual operation, the engine can be in two states: the engine is not running and the electric VCT motor has not performed self-learning; the engine is started and the electric VCT motor enters self-learning mode.

[0049] Optionally, in one embodiment of this application, before detecting whether the engine is started, the method further includes: determining whether the engine meets the preset first self-learning conditions; if the first self-learning conditions are met, then entering the first self-learning mode, learning according to the preset MAP table, and determining the initial phase.

[0050] The preset initial self-learning conditions can include, but are not limited to, engine speed, rotor position of the electric VCT actuator, and self-learning duration. The preset MAP table can be a control calibration table in the ECU, which can be used to map engine operating information (such as speed, load, intake pressure, throttle opening, etc.) into target control quantities, including but not limited to camshaft target phase, fuel injection quantity, ignition advance angle, and other control parameters. By looking up the table, the ECU can generate control signals based on real-time operating conditions, which can be used for closed-loop adjustment of the actuator or fuel injection and ignition. At the same time, in self-learning mode, the MAP table can be corrected and optimized to improve engine operating accuracy and control reliability.

[0051] The following is a specific example, such as Figure 5 As shown, the initial self-learning mode of this application embodiment will be described. The initial self-learning mode may include, but is not limited to, the following four working stages: Phase 1: The engine is not running, the electric VCT motor is in state 0 (ready to shift), the initial self-learning state is 0, and no self-learning has been performed.

[0052] Phase 2: The engine starts, and the motor is in state 1 (ready to shift) to begin self-learning for a certain period of time. The first self-learning is in state 1, and self-learning is in progress.

[0053] Phase 3: After the first self-learning is completed, the motor transitions to state 2. The motor is ready to shift to state 2. The phase is recorded, which can be used to ensure the accuracy of subsequent phase corrections.

[0054] Phase 4: Continuous self-learning lasts for a certain period of time. The continuous self-learning state changes from 0 to 1, the motor is ready to shift to state 3, and the electric VCT phase can be adjusted according to the ECU MAP table to achieve the best valve timing under different operating conditions, thereby optimizing combustion efficiency, power output and emission performance.

[0055] It can be noted that when the motor is ready to shift, it is either state 2 or state 3, and the electric VCT system can be adjusted according to the MAP.

[0056] Optionally, in one embodiment of this application, the preset first self-learning conditions include: the engine speed is in a second preset speed range; the variable intake cam timing system is in the self-learning flag position and the duration reaches a preset duration.

[0057] It can be explained that engine speed is the core input signal for the engine control system and the electric VCT system, directly affecting valve timing, fuel injection ignition, engine start determination, and actuator closed-loop adjustment strategy. The second preset speed range can be 500~2000 rpm; the lower limit of 500 rpm ensures stable engine start-up and a sufficiently long crankshaft and camshaft signal cycle, facilitating accurate acquisition and calculation of phase deviation by the ECU; the upper limit of 2000 rpm ensures that the actuator can safely and reliably complete rotor movement under inertia and friction constraints, achieving closed-loop phase correction, thereby improving valve timing accuracy and self-learning reliability.

[0058] The self-learning flag can be set when the engine is in the starting state or when the actuator rotor is in the initial position. The preset duration can be 5 seconds to ensure the system has enough data for phase deviation statistics and correction; it can also be set to reach a certain number of cycles, such as the duration of completing a certain number of crankshaft speed cycles or the time it takes for the engine to enter a specific operating range. Both the self-learning flag and the preset duration can be set by those skilled in the art according to actual conditions, and no specific limitations are imposed here.

[0059] Optionally, in one embodiment of this application, the method further includes: detecting whether the engine meets preset change conditions; and if the engine meets preset change conditions, re-entering the initial self-learning mode.

[0060] Among them, the preset change conditions can be changes to the ECU, electric VCT, engine, etc. during the vehicle's life cycle. For example, ECU program or hardware upgrades, electric VCT actuator replacement or maintenance, replacement of major engine components (such as camshaft, valve mechanism, etc.) may all lead to deviations in system characteristics.

[0061] In the embodiments of this application, the aforementioned changes may cause the original phase correction data to become invalid. Therefore, the electric VCT system needs to re-execute the initial self-learning to re-establish an accurate phase compensation reference and ensure the control accuracy of the electric VCT and the reliability of engine operation.

[0062] In step S402, when the engine is detected to be starting, it is determined whether the engine speed is within the first preset speed range.

[0063] The first preset speed range can be 500~2000rpm to fully collect dynamic response data of the camshaft position and the actuator, ensuring the accuracy of the learning results and the reliability of the system in subsequent operation; it can be set by those skilled in the art according to the actual situation, and no specific restrictions are made here.

[0064] In step S403, if the engine is in the first preset speed range and the rotor of the variable intake cam timing system is in the initial position, the engine enters the continuous self-learning mode and collects the camshaft and crankshaft position signals of the variable intake cam timing system to perform phase correction based on the camshaft and crankshaft position signals.

[0065] The initial position can be the reference angle of the electric VCT actuator rotor, typically corresponding to a mechanical limit or electrical zero position, used to prevent the rotor from exceeding the design angle range and ensure the safe and reliable operation of the actuator and camshaft. Before engine ignition, the rotor can rotate from the initial position to the ignition position to ensure that the valve timing meets the engine starting requirements; for example, the initial position can be set to 138°CA and the ignition position can be set to 18°CA.

[0066] The crankshaft position signal can be used to provide engine speed information and the reference angle position of the crankshaft, serving as the time reference for engine fuel injection and ignition control. The camshaft position signal can be used to characterize the absolute phase position of the camshaft. Combined with the crankshaft position signal, it can distinguish the working cycles of each cylinder, thereby realizing sequential fuel injection and independent ignition control. At the same time, it serves as a feedback signal for the electric VCT system to ensure the accuracy of valve phase adjustment.

[0067] It can be explained that the initial self-learning mode can be executed when the engine completes the assembly line and undergoes off-line hot testing to establish reference phase data. In subsequent use, if there are no changes in the ECU, electric VCT, or engine, the engine will enter the continuous self-learning mode every time it starts to adapt to the phase deviation caused by chain elongation and component wear. This can also reduce learning time, improve system response efficiency, and ensure the accuracy and stability of valve timing control.

[0068] As one possible way to achieve this, such as Figure 6 As shown, the continuous self-learning mode may include, but is not limited to, the following stages: Phase 1: The engine is not running, the motor is ready to shift (state 0), the first self-learning is state 2, and continuous self-learning is state 0 (no self-learning is performed).

[0069] Phase 2: Engine starts, motor is ready to shift (state 1), continuous self-learning (state 0).

[0070] Phase 3: The engine speed increases to 800 rpm, the electric VCT rotor returns to the initial position, and continuous self-learning begins. The motor is ready to shift (state 2).

[0071] Phase 4: Continuous self-learning lasts for 0.2s. The continuous self-learning state changes from 0 to 1. The motor is ready to shift (state 3). The motor VCT phase can be adjusted according to the ECU MAP.

[0072] Optionally, in one embodiment of this application, phase correction based on the camshaft and crankshaft position signals includes: determining the actual phase angle based on the camshaft and crankshaft position signals; and performing phase correction based on the actual phase angle and the target phase angle.

[0073] The actual phase angle can be determined by collecting the position signals of the camshaft and crankshaft, combining tooth count, time interpolation and reference mapping, calculating the angle difference between the camshaft and crankshaft, and obtaining a stable and reliable actual phase angle after filtering and anomaly processing. It can be set by those skilled in the art according to the actual situation, and no specific restrictions are made here.

[0074] Specifically, the embodiments of this application can collect the position signals of the crankshaft and camshaft in real time based on the self-learning mode to record the deviation between the actual phase angle and the target phase angle, establish and learn the correspondence between the deviation and different engine operating conditions, thereby forming a correction amount; furthermore, the embodiments of this application can store the learned correction amount and compensate for it in subsequent control, so that the electric VCT system can automatically correct the errors caused by chain elongation and component wear during long-term operation, and achieve more precise phase adjustment and stable engine valve timing control.

[0075] According to the self-learning method for engines proposed in this application, based on the self-learning mode, the camshaft and crankshaft position signals of the variable intake camshaft timing system are collected, and then the correspondence between the actual phase angle and the target phase angle deviation is calculated and learned to generate a correction amount for phase correction. The camshaft signal deviation can be continuously corrected through the self-learning mode, making the electric VCT control more precise. The engine can operate stably according to the ECU MAP. At the same time, it can correct the phase deviation caused by timing chain elongation and component wear, thereby improving the engine phase control accuracy and improving the control accuracy of single start. In addition, it can also optimize combustion efficiency, reduce emissions, enhance the adaptability of hybrid and start-stop conditions, and improve the smoothness and reliability of long-term engine operation, achieving a comprehensive improvement in power performance and durability.

[0076] Next, the self-learning device for an engine according to an embodiment of this application is described with reference to the accompanying drawings.

[0077] Figure 7 This is a block diagram of the self-learning device for an engine according to an embodiment of this application.

[0078] like Figure 7As shown, the self-learning device 10 of the engine includes: a checking module 100, a first judgment module 200 and a self-learning module 300.

[0079] The inspection module 100 is used to detect whether the engine is started.

[0080] The first judgment module 200 is used to determine whether the engine speed is within a first preset speed range when the engine is detected to have started.

[0081] The self-learning module 300 is used to enter a continuous self-learning mode if the engine is in a first preset speed range and the rotor of the variable intake cam timing system is in the initial position. It collects the camshaft and crankshaft position signals of the variable intake cam timing system to perform phase correction based on the camshaft and crankshaft position signals.

[0082] Optionally, in one embodiment of this application, it further includes: a second judgment module and a determination module.

[0083] The second judgment module is used to determine whether the engine meets the preset first self-learning conditions.

[0084] The determination module is used to enter the initial self-learning mode if the initial self-learning conditions are met, and to learn according to the preset MAP table to determine the initial phase.

[0085] Optionally, in one embodiment of this application, the preset first self-learning conditions include: the engine speed is in a second preset speed range; the variable intake cam timing system is in the self-learning flag position and the duration reaches a preset duration.

[0086] Optionally, in one embodiment of this application, it further includes: an inspection module and an entry module.

[0087] The inspection module is used to detect whether the engine meets preset change conditions.

[0088] The entry module is used to re-enter the initial self-learning mode when the engine is detected to meet preset change conditions.

[0089] Optionally, in one embodiment of this application, the self-learning module 300 includes: a determination unit and a correction unit.

[0090] The determining unit is used to determine the actual phase angle based on the position signals of the camshaft and crankshaft. The correction unit is used to perform phase correction based on the actual phase angle and the target phase angle. It should be noted that the foregoing explanation of the engine self-learning method embodiment also applies to the engine self-learning device of this embodiment, and will not be repeated here.

[0091] The self-learning device for the engine proposed in this application, based on the self-learning mode, collects the camshaft and crankshaft position signals of the variable intake camshaft timing system, and then calculates and learns the correspondence between the actual phase angle and the target phase angle deviation to generate a correction amount for phase correction. It can continuously correct the camshaft signal deviation through the self-learning mode, making the electric VCT control more precise, and the engine can operate stably according to the ECU MAP. At the same time, it can correct the phase deviation caused by timing chain elongation and component wear, thereby improving the engine phase control accuracy and improving the control accuracy of single start-up. In addition, it can optimize combustion efficiency, reduce emissions, enhance the adaptability of hybrid and start-stop conditions, and improve the smoothness and reliability of long-term engine operation, achieving a comprehensive improvement in power performance and durability.

[0092] Figure 8 A schematic diagram of the structure of a vehicle provided in an embodiment of this application. The vehicle may include: The memory 801, the processor 802, and the computer program stored on the memory 801 and capable of running on the processor 802.

[0093] When the processor 802 executes the program, it implements the engine self-learning method provided in the above embodiments.

[0094] Furthermore, the vehicle also includes: Communication interface 803 is used for communication between memory 801 and processor 802.

[0095] The memory 801 is used to store computer programs that can run on the processor 802.

[0096] The memory 801 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0097] If the memory 801, processor 802, and communication interface 803 are implemented independently, then the communication interface 803, memory 801, and processor 802 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized into address buses, data buses, control buses, etc. For ease of representation, Figure 8 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0098] Optionally, in a specific implementation, if the memory 801, processor 802, and communication interface 803 are integrated on a single chip, then the memory 801, processor 802, and communication interface 803 can communicate with each other through an internal interface.

[0099] The processor 802 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0100] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described engine self-learning method.

[0101] This application also provides a computer program product, including a computer program that can run computer instructions. When the computer instructions are executed by a processor, they implement the self-learning method for an engine provided in this application.

[0102] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0103] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0104] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0105] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0106] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0107] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0108] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0109] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A self-learning method for an engine, characterized in that, Includes the following steps: Check if the engine is running; If the engine is detected to be running, determine whether the engine speed is within a first preset speed range; as well as If the engine is in the first preset speed range and the rotor of the variable intake camshaft timing system is in the initial position, it enters the continuous self-learning mode, collects the camshaft and crankshaft position signals of the variable intake camshaft timing system, and performs phase correction based on the camshaft and crankshaft position signals.

2. The method according to claim 1, characterized in that, Before detecting whether the engine is started, the following is also included: Determine whether the engine meets the preset first self-learning conditions; If the initial self-learning conditions are met, the system enters the initial self-learning mode, learns according to the preset MAP table, and determines the initial phase.

3. The method according to claim 2, characterized in that, The preset initial self-learning conditions include: The engine speed is within the second preset speed range; The variable intake cam timing system is in the self-learning flag position and the duration reaches the preset duration.

4. The method according to claim 2, characterized in that, Also includes: Detect whether the engine meets the preset change conditions; If the engine is detected to meet the preset change conditions, the system will re-enter the initial self-learning mode.

5. The method according to claim 1, characterized in that, The phase correction based on the camshaft and crankshaft position signals includes: The actual phase angle is determined based on the camshaft and crankshaft position signals. Phase correction is performed based on the actual phase angle and the target phase angle.

6. A self-learning device for an engine, characterized in that, include: The inspection module is used to detect whether the engine is running; The first judgment module is used to determine whether the engine speed is within a first preset speed range when the engine is detected to be starting. as well as The self-learning module is used to enter a continuous self-learning mode if the engine is in the first preset speed range and the rotor of the variable intake cam timing system is in the initial position, and to collect the camshaft and crankshaft position signals of the variable intake cam timing system so as to perform phase correction based on the camshaft and crankshaft position signals.

7. The apparatus according to claim 6, characterized in that, Also includes: The second judgment module is used to determine whether the engine meets the preset first self-learning conditions; The determination module is used to enter the initial self-learning mode if the initial self-learning conditions are met, and to learn according to the preset MAP table to determine the initial phase.

8. A vehicle, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the self-learning method for an engine as described in any one of claims 1-5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the self-learning method for the engine as described in any one of claims 1-5.

10. A computer program product, comprising a computer program, characterized in that, The computer program is executed to implement the self-learning method for the engine as described in any one of claims 1-5.

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