An oil pump control method, system, electronic device and storage medium

Abstract

The application relates to the technical field of vehicles and provides a machine oil pump control method, a machine oil pump control system, an electronic device and a storage medium; the machine oil pump control method comprises the following steps: pre-dividing engine operation conditions into a plurality of condition zones based on collected engine operation data, collecting operation data in real time when the vehicle is running to match a corresponding target condition zone, and performing PID integral learning in the matched target condition zone; wherein the operation data at least comprises an engine speed, a load and an oil temperature; self-learning values of the condition zones are acquired and stored when the vehicle is powered off; when the vehicle is powered on and runs, the self-learning values of the condition zones stored when the vehicle is powered off are recalled based on current engine operation data, and compensation control is performed on an electromagnetic valve of the machine oil pump. The application solves the technical problem that the output characteristics of the electromagnetic valve deviate, thereby causing the control precision of the machine oil pressure to decrease.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and in particular to an oil pump control method, system, electronic device, and storage medium. Background Technology

[0002] Currently, the variable displacement oil pump is a key component of modern engine lubrication systems. By controlling the solenoid valve, the oil displacement can be continuously adjusted, thereby reducing pump power loss and improving fuel economy while meeting engine lubrication requirements. Existing control strategies are based on parameters such as engine speed, load, oil temperature, and oil pressure. The engine control unit (ECU) calculates the target oil pressure and the duty cycle of the oil pump solenoid valve, and uses pulse width modulation (PWM) signals to drive the solenoid valve to adjust the oil circuit opening, thereby adjusting the oil pump displacement in real time and controlling the oil pressure.

[0003] After prolonged use, the performance of the solenoid valve may deteriorate due to internal mechanical wear, spring fatigue, and foreign object accumulation. Specifically, the response speed of the solenoid valve may slow down, or the control of the oil circuit opening may become inaccurate, causing the actual oil pressure to fail to quickly and accurately follow the target oil pressure. Summary of the Invention

[0004] The purpose of this invention is to provide an oil pump control method, system, electronic device, and storage medium; this invention solves the technical problem of decreased oil pressure control accuracy caused by solenoid valve output characteristic deviation. The specific solution is as follows: An oil pump control method includes the following steps: S1: Based on the collected engine operating data, the engine operating conditions are pre-divided into several operating condition zones, and operating data is collected in real time during vehicle operation to match the corresponding target operating condition zone. PID integral learning is performed in the matched target operating condition zone. S2: Obtain the self-learning values ​​of each working condition partition and store them when the vehicle is powered off; S3: When the vehicle is powered on, it performs working condition partition matching based on the current engine operating data, retrieves the self-learning value of the working condition partition stored after power-off, and performs compensatory control on the solenoid valve of the oil pump.

[0005] Optionally, step S1 includes: S101: Real-time acquisition of engine operating data; the engine operating data includes at least: engine speed, load, and oil temperature; S102: Based on the preset range of engine speed, load, and oil temperature, the engine operating conditions are divided into several operating condition zones in advance, and the operating condition zones are numbered. S103: Based on the currently collected engine speed, load, and oil temperature, look up the corresponding operating condition zone in the table; S104: Based on the acquired operating condition partition, execute PID closed-loop control of oil pressure, continuously accumulate the difference between the actual oil pressure and the target oil pressure, and calculate the target PID integral term of the corresponding operating condition partition in real time. S105: When the engine operating condition changes, it automatically switches to the corresponding operating condition zone and recalculates the PID integral term of the switched operating condition zone.

[0006] Optionally, step S2 includes: Determine whether the enabling conditions for the self-learning function are met; If satisfied, the target PID integral term of the PID control calculated for different operating conditions will be recorded as a self-learning value and stored when the power is off. Specifically, for the self-learning function to be enabled, the following conditions must be met simultaneously: The vehicle is in closed-loop oil pressure control mode; The rate of change of the integral term did not exceed the set threshold. The target oil pressure falls within the preset range; None of the following abnormalities were found. The abnormality is: The solenoid valve control duty cycle is less than the first set low threshold, and the actual oil pressure is greater than the target oil pressure, and this continues for a first preset time. The solenoid valve control duty cycle is greater than the first set high threshold, and the actual oil pressure is less than the target oil pressure, and this continues for a first preset time.

[0007] Optionally, step S3 includes: S301: Collects current engine operating data; S302: After filtering the self-learning value of the corresponding working condition partition stored from the last power-down, it is compensated into the integral term of the PID control to obtain the target duty cycle, and the oil pump solenoid valve is controlled to operate according to the target duty cycle.

[0008] Optionally, it also includes step S4: detecting whether the solenoid valve is in an abnormal operating state; Step S4 includes: The self-learning values ​​of each working condition partition are compared with the corresponding fault thresholds. If there are at least three operating condition zones that exceed the fault threshold, and at least two of these operating condition zones fall into different preset oil temperature ranges, and the self-learning value of the operating condition zone that exceeds the fault threshold exceeds the fault threshold for a duration greater than a second preset time, then the solenoid valve is judged to be in an abnormal operating state, and a fault prompt is generated based on the abnormal operating state of the solenoid valve.

[0009] An oil pump control system is applied to the method described above; the system includes: The learning module is configured to pre-divide the engine operating conditions into several operating condition zones based on the collected engine operating data, and collect operating data in real time during vehicle operation to match the corresponding target operating condition zone, and perform PID integral learning in the matched target operating condition zone; wherein, the operating data includes at least: engine speed, load and oil temperature; The acquisition module is configured to acquire self-learning values ​​for each operating condition zone and store them when the vehicle is powered off. The compensation module is configured to, when the vehicle is powered on, retrieve the self-learning value of the operating condition partition stored after power-off based on the current engine operating data, and perform compensatory control on the solenoid valve of the oil pump.

[0010] Optionally, the learning module includes: The data acquisition unit is used to collect engine speed, load, and oil temperature in real time. The partitioning unit is configured to pre-divide the engine operating conditions into several operating condition partitions based on preset ranges of engine speed, load, and oil temperature, and to number the operating condition partitions. The acquisition unit is configured to look up the corresponding operating condition zone based on the currently collected engine speed, load, and oil temperature; The learning unit is configured to perform PID closed-loop control of oil pressure based on the acquired operating condition partitions, continuously accumulating the difference between the actual oil pressure and the target oil pressure, and calculating the target PID integral term for the corresponding operating condition partition in real time; and When the engine operating conditions change, it automatically switches to the corresponding operating condition zone and recalculates the PID integral term of the switched operating condition zone.

[0011] Optionally, it may also include: an anomaly detection module; The anomaly detection module is used to detect whether the solenoid valve is operating abnormally.

[0012] An electronic device includes: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus; characterized in that the memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the method.

[0013] A computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method.

[0014] The beneficial effects of this invention are as follows: This invention provides an oil pump control method, system, electronic device, and storage medium. The invention pre-divides multiple operating condition zones based on engine speed, load, and oil temperature. During vehicle operation, it matches real-time operating conditions to perform PID integral learning for each zone, generating self-learning values ​​for each zone. After the vehicle is powered off, the self-learning values ​​are saved; upon power-on, the self-learning values ​​for the corresponding operating condition zone are directly retrieved to compensate for the oil pump solenoid valve. The advantage of this design is that, compared to the traditional global self-learning strategy with unified compensation parameters, this invention, through operating condition zone learning, can adapt to oil pressure control deviations caused by differences in oil viscosity and oil circuit resistance under different engine speeds, loads, and oil temperatures. This effectively accelerates the convergence speed of the PID integral term, improves the accuracy of oil pressure control under all operating conditions, and reduces the impact of solenoid valve output characteristic deviations on oil pressure regulation. By reusing historically stored operating condition zone self-learning values ​​upon power-on, the time required for oil pressure stabilization in the initial power-on period is shortened, improving lubrication control stability under cold starts, high and low temperatures, and different load conditions. Attached Figure Description

[0015] Figure 1 This is a schematic flowchart of an oil pump control method according to an embodiment of the present invention; Figure 2 This is a schematic flowchart of an oil pump control method according to one embodiment of the present invention; Figure 3 This is a schematic diagram illustrating how the engine operating conditions are divided into 27 regions based on operating data, according to one embodiment of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the following description will be provided in conjunction with the appendix. Figures 1 to 3 The present invention will be described in further detail below. It is obvious that the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0017] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0018] It should be understood that the term "and / or" used in this article is merely a description of 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. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0019] It should be understood that although the terms first, second, third, etc., may be used in the embodiments of the present invention, these descriptions should not be limited to these terms. These terms are only used to distinguish the descriptions. For example, first may also be referred to as second without departing from the scope of the embodiments of the present invention, and similarly, second may also be referred to as first.

[0020] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0021] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0022] It should be noted that any symbols and / or numbers present in the specification that are not marked in the accompanying drawings are not reference numerals.

[0023] The optional embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0024] like Figure 1 The oil pump control method shown includes the following steps: S1: Based on the collected engine operating data, the engine operating conditions are pre-divided into several operating condition zones, and operating data is collected in real time during vehicle operation to match the corresponding target operating condition zone. PID integral learning is performed in the matched target operating condition zone. S2: Obtain the self-learning values ​​of each working condition partition and store them when the vehicle is powered off; S3: When the vehicle is powered on, it performs working condition partition matching based on the current engine operating data, retrieves the self-learning value of the working condition partition stored after power-off, and performs compensatory control on the solenoid valve of the oil pump.

[0025] Specifically, this invention pre-divides multiple operating condition zones based on engine speed, load, and oil temperature. During vehicle operation, it matches real-time operating conditions to perform PID integral learning for each zone and generates self-learning values ​​corresponding to each operating condition zone. After the vehicle is powered off, the self-learning values ​​are saved; upon power-on, the self-learning values ​​for the corresponding operating condition zone are directly retrieved to compensate for the oil pump solenoid valve. The advantage of this design is that, compared to the traditional global self-learning strategy with uniform compensation parameters, this invention, through operating condition zone learning, can adapt to oil pressure control deviations caused by differences in oil viscosity and oil circuit resistance under different engine speeds, loads, and oil temperatures, effectively accelerating... The convergence speed of the PID integral term improves the accuracy of oil pressure control under all operating conditions and reduces the impact of solenoid valve output characteristic deviation on oil pressure regulation. By reusing historically stored self-learning values ​​of operating conditions partitions upon power-on, it is not necessary to start learning from scratch every time the engine is started, shortening the time required for oil pressure stabilization in the initial power-on stage and improving the stability of lubrication control under cold start, high and low temperature, and different load conditions. At the same time, the self-learning values ​​stored separately for each operating condition partition can support subsequent solenoid valve performance degradation identification and fault warning based on multi-operating condition partition self-learning values, realize early component failure monitoring, and improve the operational reliability of the engine lubrication system.

[0026] In one specific embodiment, step S1 includes: S101: Real-time engine operating data; wherein, the engine operating data includes at least: engine speed, load, and oil temperature; S102: Based on the preset range of engine speed, load, and oil temperature, the engine operating conditions are divided into several operating condition zones in advance, and the operating condition zones are numbered. S103: Based on the currently collected engine speed, load, and oil temperature, look up the corresponding operating condition zone in the table; S104: Based on the acquired operating condition partition, execute PID closed-loop control of oil pressure, continuously accumulate the difference between the actual oil pressure and the target oil pressure, and calculate the target PID integral term of the corresponding operating condition partition in real time. S105: When the engine operating condition changes, it automatically switches to the corresponding operating condition zone and recalculates the PID integral term of the switched operating condition zone.

[0027] Specifically, in this embodiment, multiple operating condition zones are pre-defined and numbered based on preset ranges of engine speed, load, and oil temperature. During vehicle operation, operating parameters are collected in real time and matched with the current operating condition zone by looking up a table. Oil pressure PID closed-loop control is executed independently within the corresponding zone. The difference between the actual oil pressure and the target oil pressure is continuously accumulated to calculate the PID integral term corresponding to the operating condition zone in real time. When the operating condition changes, the operating condition zone is automatically switched and the integral calculation is performed again. The advantage of this design is that it can fully adapt to the objective characteristics of differences in oil viscosity, oil circuit resistance, and solenoid valve operating characteristics under different speeds, loads, and oil temperatures. It avoids the defect that a single integral parameter cannot meet the control requirements of all operating conditions, effectively reduces mutual interference between operating condition zones, and improves the response speed and steady-state control accuracy of oil pressure PID closed-loop regulation under each operating condition zone.

[0028] For example: the engine oil temperature is preset to 3 ranges: low temperature -40 to 10℃, medium temperature 10 to 90℃, and high temperature 90 to 140℃; Within a single temperature zone, the engine speed is preset to three ranges: 0 to 2000 rpm, 2000 to 4000 rpm, and >4000 rpm. The load within a single temperature zone is preset to three ranges: 0 to 40%, 40% to 90%, and >90%. A 3×3×3 combination yields 27 numbered working condition partitions.

[0029] In one specific embodiment, step S2 includes: Determine whether the enabling conditions for the self-learning function are met; If satisfied, the target PID integral term of the PID control calculated for different operating conditions will be recorded as a self-learning value and stored when the power is off. Specifically, for the self-learning function to be enabled, the following conditions must be met simultaneously: The vehicle is in closed-loop oil pressure control mode; The rate of change of the integral term did not exceed the set threshold. The target oil pressure falls within the preset range; None of the following abnormalities were found. The abnormality is: The solenoid valve control duty cycle is less than the first set low threshold, and the actual oil pressure is greater than the target oil pressure, and this continues for a first preset time. The solenoid valve control duty cycle is greater than the first set high threshold, and the actual oil pressure is less than the target oil pressure, and this continues for a first preset time.

[0030] Specifically, this invention configures multi-layered self-learning function enable conditions. Only when the vehicle system is in oil pressure closed-loop control mode, the PID integral term changes smoothly, the target oil pressure is within the normal range, and there is no abnormal operating condition where the solenoid valve duty cycle and oil pressure deviate in opposite directions, will the stable and effective target PID integral term for each operating condition zone be recorded as a self-learning value and stored after the vehicle is powered off. Compared with the conventional strategy of directly and continuously recording integral values, this design can effectively filter out distorted integral data under disturbance scenarios such as rapid acceleration and deceleration, open-loop control, and solenoid valve jamming failure. It avoids abnormal interference causing incorrect updates of self-learning values, ensuring that the self-learning values ​​of each operating condition zone can truly reflect the inherent characteristic deviations of the solenoid valve under steady-state operation, improving the accuracy of self-learning compensation, preventing oil pressure runaway caused by incorrect compensation, and providing a reliable data source for subsequent solenoid valve degradation fault diagnosis.

[0031] It is understandable that when the self-learning function is enabled, the integral terms of the PID control calculated by the ECU under different operating conditions are recorded as IntglAdap1……IntglAdap27, and these self-learning values ​​are stored in the EEPROM when the power is off.

[0032] Example The threshold for the rate of change of the integral term is ±0.06 bar / s; the normal range for the target oil pressure is 2.0 to 4.0 bar; and the duration of the prohibited operating condition is 5 seconds.

[0033] Vehicle cruising at a constant speed, engine oil temperature 60℃ (mid-temperature zone R25): Condition 1 is met: The vehicle is operating normally in PID closed-loop control mode for oil pressure, without switching to open-loop modes such as cold start rapid pressure build-up or fault pressure limiting; Condition 2 is met: the oil pressure fluctuates smoothly, the integral term of PID2 changes by only 0.02 bar per second, which is less than the ±0.06 bar threshold, and the integral is stable without drastic jumps; Condition 3 is met: The ECU is set to a target oil pressure of 2.8 bar, which falls within the normal range of 2.0 to 4.0 bar; Condition 4 is met: Neither of the two reverse abnormal operating conditions occurred. The solenoid valve duty cycle is 42% (slightly low), the actual oil pressure is 2.7 bar < the target 2.8 bar, which is in line with normal logic (the smaller the duty cycle, the lower the oil pressure), and there is no reverse direction; There is no reverse state where "the duty cycle is high but the oil pressure is low".

[0034] In one specific embodiment, step S3 includes: S301: Collects current engine operating data; S302: After filtering the self-learning value of the corresponding working condition partition stored from the last power-down, it is compensated into the integral term of the PID control to obtain the target duty cycle, and the oil pump solenoid valve is controlled to operate according to the target duty cycle.

[0035] It is understandable that when the performance of the solenoid valve deteriorates, the integral term of the PID control will continuously accumulate calculations to eliminate the persistent oil pressure tracking deviation, resulting in an output value higher than the control value under normal conditions. Therefore, based on the engine's operating conditions, the self-learning value of the corresponding operating condition region saved from the last power failure is used to compensate the integral term of the PID control, thereby enabling the integral term to reach a stable state more quickly and improving the oil pressure control effect.

[0036] Specifically, based on the engine speed, load, and oil temperature, corresponding self-learning values ​​are used to compensate the integral term. To ensure that the integral term does not change abruptly when switching between different operating conditions, the corresponding self-learning values ​​are filtered and then added to the integral term. The final calculated duty cycle is used to control the oil pump solenoid valve.

[0037] In one specific embodiment, the method further includes step S4: detecting whether the solenoid valve is in an abnormal operating state; Step S4 includes: The self-learning values ​​of each working condition partition are compared with the corresponding fault thresholds. If there are at least three operating condition zones that exceed the fault threshold, and at least two of these operating condition zones fall into different preset oil temperature ranges, and the self-learning value of the operating condition zone that exceeds the fault threshold exceeds the fault threshold for a duration greater than a second preset time, then the solenoid valve is judged to be in an abnormal operating state, and a fault prompt is generated based on the abnormal operating state of the solenoid valve.

[0038] In this embodiment, the solenoid valve is judged to be abnormal by comparing the self-learning value of each working condition zone with the fault threshold and setting multiple constraints. When there are no less than 3 over-limit working condition zones, at least two of which are distributed in different oil temperature ranges, and the duration of the over-limit exceeds the second preset time, the solenoid valve is judged to be abnormal and a fault prompt is output. The advantage of this design is that, by differentiating itself from the diagnostic method of alarming when a single zone exceeds the limit, it can effectively avoid false alarms caused by local working conditions (oil viscosity changes, oil circuit resistance fluctuations) in a single temperature zone. Thus, it can accurately distinguish between inherent deviations in working conditions and faults such as wear of the solenoid valve core and fatigue of the spring, which deviate from the overall working condition characteristics of the solenoid valve body. This improves the reliability of fault diagnosis, enables early identification of solenoid valve performance degradation, facilitates timely warning, and protects the safe operation of the engine lubrication system.

[0039] For example, during vehicle operation, the ECU compares the self-learning compensation values ​​stored in 27 operating condition zones in real time. Among them, the self-learning values ​​of three operating condition zones—low temperature zone R14, medium temperature zone R25, and high temperature zone R36—are +24%, +26%, and +23%, respectively, all exceeding the fault threshold of +20%. These three exceeding zones belong to three completely different oil temperature ranges: low temperature, medium temperature, and high temperature. If the self-learning value of each of the three operating condition zones exceeds the threshold continuously for 8 seconds, exceeding the second preset time of 5 seconds, the ECU determines that the oil pump solenoid valve is operating abnormally. It stores the corresponding fault code, illuminates the instrument fault light, and outputs a fault indication of solenoid valve performance degradation. If only three adjacent zones (R37, R38, and R39) in the high temperature zone exceed the limit, and there are no exceeding limits in the low temperature or medium temperature zones, or only two zones that cross temperature zones exceed the limit, or the exceeding time is less than 5 seconds, the solenoid valve is determined to be normal, and no fault indication is generated.

[0040] It's understandable that thresholds are set for different operating conditions, and the self-learning value is compared with the corresponding threshold. If the value exceeds the threshold, a fault is reported. If a very large self-learning value is required to compensate for the control error caused by the performance degradation of the oil pump solenoid valve, it indicates that the characteristics of the solenoid valve have deviated too much, or that the solenoid valve is damaged. In this case, an oil pump fault is reported, prompting the user to inspect the vehicle to prevent more serious consequences from the failure of oil pressure control.

[0041] In one specific embodiment, the oil pump control method includes: S1: Divide the engine operating conditions into n zones based on engine speed, load, and oil temperature; S2: When the self-learning function is enabled, the integral terms of the PID control calculated by the software under different operating conditions are recorded as self-learning values, and each self-learning value is stored in the EEPROM when the power is off. S3: When the power is turned on again, the corresponding self-learning value is added to the integral term of the PID control for compensation based on the engine speed, load and oil temperature. S4: Compare the self-learning value with the preset threshold. If the self-learning value exceeds the threshold, report an oil pump failure.

[0042] Understandable. S1: The integral value of the oil pump solenoid valve feedback control varies under different engine speed, load and oil temperature conditions. Therefore, multiple operating condition zones are divided according to speed, load and oil temperature, and zone learning is performed.

[0043] S2: The integral term of the feedback control of the oil pump solenoid valve reflects the cumulative error between the actual oil pressure and the target oil pressure. This value reflects the degree of performance degradation of the solenoid valve to a certain extent. Therefore, under certain conditions, this integral value is recorded as a self-learning value.

[0044] The conditions for enabling the self-learning function are as follows: 1. The control system is in closed-loop control mode for oil pressure; 2. The rate of change of the integral term did not exceed the set threshold; 3. The target oil pressure is within a certain range; 4. The following situation does not occur (when the following situation occurs, it indicates that the adjustment capability of the control system is insufficient to make the actual oil pressure follow the target oil pressure, and the integral value at this time is not suitable as a self-learning value): (1) The solenoid valve control duty cycle is too small, but the actual oil pressure is higher than the target oil pressure, and this state continues for a period of time; (2) The solenoid valve control duty cycle is too large, but the actual oil pressure is lower than the target oil pressure, and this state continues for a period of time.

[0045] When the self-learning function is enabled, the integral values ​​under different operating conditions are recorded and stored when the power is off so that they can be used after the power is turned on again.

[0046] S3: When the performance of the solenoid valve deteriorates, in order to eliminate the persistent oil pressure tracking deviation, the integral term of the PID control will continuously accumulate calculations, and its output value will be higher than the control quantity under normal conditions. Therefore, based on the engine's operating conditions, the self-learning value of the corresponding operating condition region saved from the last power failure is used to compensate the integral term of the PID control, thereby enabling the integral term to reach a stable state more quickly and improving the oil pressure control effect. Specifically, based on the engine speed, load, and oil temperature, the corresponding self-learning value is used to compensate the integral term. To ensure that the integral term does not change abruptly when switching between different operating condition regions, the corresponding self-learning value is filtered before being added to the integral term. The final calculated duty cycle is used to control the oil pump solenoid valve.

[0047] S4: Set thresholds for different operating conditions, compare the self-learning value with the corresponding threshold, and report a fault if the value exceeds the threshold. If a large self-learning value is required to compensate for the control error caused by the performance degradation of the oil pump solenoid valve, it indicates that the characteristics of the solenoid valve have deviated too much or the solenoid valve is damaged. In this case, report an oil pump fault, prompting the user to inspect the vehicle to prevent more serious consequences from the failure of oil pressure control.

[0048] On the other hand, the present invention provides an oil pump control system applied to the method described; the system includes: The learning module is configured to pre-divide the engine operating conditions into several operating condition zones based on the collected engine operating data, and collect operating data in real time during vehicle operation to match the corresponding target operating condition zone, and perform PID integral learning in the matched target operating condition zone; wherein, the operating data includes at least: engine speed, load and oil temperature; The acquisition module is configured to acquire self-learning values ​​for each operating condition zone and store them when the vehicle is powered off. The compensation module is configured to, when the vehicle is powered on, retrieve the self-learning value of the operating condition partition stored after power-off based on the current engine operating data, and perform compensatory control on the solenoid valve of the oil pump.

[0049] In one specific embodiment, the learning module includes: The data acquisition unit is used to collect engine speed, load, and oil temperature in real time. The partitioning unit is configured to pre-divide the engine operating conditions into several operating condition partitions based on preset ranges of engine speed, load, and oil temperature, and to number the operating condition partitions. The acquisition unit is configured to look up the corresponding operating condition partition based on the currently collected engine speed, load, and oil temperature; The learning unit is configured to perform PID closed-loop control of oil pressure based on the acquired operating condition partitions, continuously accumulating the difference between the actual oil pressure and the target oil pressure, and calculating the target PID integral term for the corresponding operating condition partition in real time; and When the engine operating conditions change, it automatically switches to the corresponding operating condition zone and recalculates the PID integral term of the switched operating condition zone.

[0050] In one specific embodiment, the present invention further includes: an anomaly detection module; The anomaly detection module is used to detect whether the solenoid valve is operating abnormally.

[0051] On the other hand, the present invention provides an electronic device, comprising: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; characterized in that the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of the method described therein.

[0052] On the other hand, the present invention provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method.

[0053] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the appended claims.

Claims

1. A method for controlling an oil pump, characterized in that, Includes the following steps: S1: Based on the collected engine operating data, the engine operating conditions are pre-divided into several operating condition zones, and operating data is collected in real time during vehicle operation to match the corresponding target operating condition zone. PID integral learning is performed in the matched target operating condition zone. S2: Obtain the self-learning values ​​of each working condition partition and store them when the vehicle is powered off; S3: When the vehicle is powered on, it performs working condition partition matching based on the current engine operating data, retrieves the self-learning value of the corresponding working condition partition stored after power-off, and performs compensatory control on the solenoid valve of the oil pump.

2. The oil pump control method according to claim 1, characterized in that, Step S1 includes: S101: Real-time engine operating data; wherein, the engine operating data includes at least: engine speed, load, and oil temperature; S102: Based on the preset range of engine speed, load, and oil temperature, the engine operating conditions are divided into several operating condition zones in advance, and the operating condition zones are numbered. S103: Based on the currently collected engine speed, load, and oil temperature, look up the corresponding operating condition zone in the table; S104: Based on the acquired operating condition partition, execute PID closed-loop control of oil pressure, continuously accumulate the difference between the actual oil pressure and the target oil pressure, and calculate the target PID integral term of the corresponding operating condition partition in real time. S105: When the engine operating condition changes, it automatically switches to the corresponding operating condition zone and recalculates the PID integral term of the switched operating condition zone.

3. The oil pump control method according to claim 2, characterized in that, Step S2 includes: Determine whether the enabling conditions for the self-learning function are met; If satisfied, the target PID integral term of the PID control calculated for different operating conditions will be recorded as a self-learning value and stored when the power is off. Specifically, for the self-learning function to be enabled, the following conditions must be met simultaneously: The vehicle is in closed-loop oil pressure control mode; The rate of change of the integral term did not exceed the set threshold. The target oil pressure falls within the preset range; None of the following abnormalities were found. The abnormality is: The solenoid valve control duty cycle is less than the first set low threshold, and the actual oil pressure is greater than the target oil pressure, and this continues for a first preset time. The solenoid valve control duty cycle is greater than the first set high threshold, and the actual oil pressure is less than the target oil pressure, and this continues for a first preset time.

4. The oil pump control method according to claim 3, characterized in that, Step S3 includes: S301: Collects current engine operating data; S302: After filtering the self-learning value of the corresponding working condition partition stored from the last power-down, it is compensated into the integral term of the PID control to obtain the target duty cycle, and the oil pump solenoid valve is controlled to operate according to the target duty cycle.

5. The oil pump control method according to claim 1, characterized in that, It also includes step S4: detecting whether the solenoid valve is operating abnormally; Step S4 includes: The self-learning values ​​of each working condition partition are compared with the corresponding fault thresholds. If there are at least three operating condition zones that exceed the fault threshold, and at least two of these operating condition zones fall into different preset oil temperature ranges, and the self-learning value of the operating condition zone that exceeds the fault threshold exceeds the fault threshold for a duration greater than a second preset time, then the solenoid valve is judged to be in an abnormal operating state, and a fault prompt is generated based on the abnormal operating state of the solenoid valve.

6. An oil pump control system, characterized in that, The system comprises: (The method described in any one of claims 1-5) The learning module is configured to pre-divide the engine operating conditions into several operating condition zones based on the collected engine operating data, and collect operating data in real time during vehicle operation to match the corresponding target operating condition zone, and perform PID integral learning in the matched target operating condition zone; wherein, the operating data includes at least: engine speed, load and oil temperature; The acquisition module is configured to acquire the self-learning values ​​of each working condition partition from the learning module and store them when the vehicle is powered off. The compensation module is configured to, when the vehicle is powered on, retrieve the self-learning value of the operating condition partition stored in the acquisition module after power-off based on the current engine operating data, and perform compensatory control on the solenoid valve of the oil pump.

7. The oil pump control system according to claim 6, characterized in that, The learning module includes: The data acquisition unit is used to collect engine speed, load, and oil temperature in real time. The partitioning unit is configured to pre-divide the engine operating conditions into several operating condition partitions based on preset ranges of engine speed, load, and oil temperature, and to number the operating condition partitions. The acquisition unit is configured to look up the corresponding operating condition zone based on the currently collected engine speed, load, and oil temperature; The learning unit is configured to perform PID closed-loop control of oil pressure based on the acquired operating condition partitions, continuously accumulating the difference between the actual oil pressure and the target oil pressure, and calculating the target PID integral term for the corresponding operating condition partition in real time; and When the engine operating conditions change, it automatically switches to the corresponding operating condition zone and recalculates the PID integral term of the new operating condition zone.

8. The oil pump control system according to claim 7, characterized in that, Also includes: Anomaly detection module; The anomaly detection module is used to detect whether the solenoid valve is operating abnormally.

9. An electronic device, comprising: The system comprises a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus; characterized in that the memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the method described in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The device stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the method as described in any one of claims 1 to 5.

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