Solenoid valve PI characteristic curve learning method and device of hybrid transmission and storage medium

Abstract

The invention discloses a solenoid valve PI characteristic curve learning method, system and device of a hybrid transmission and a storage medium, and belongs to the technical field of automobiles, and the method comprises the steps: judging whether a main oil pressure self-learning trigger condition is satisfied, and if yes, entering the next step; whether a fault exists or not is judged, and if not, the next step is executed; the average actual main oil way pressure and the average request main oil way pressure in the N periods are calculated; a pressure deviation value is calculated; the closest points A and B on the left side and the right side of the PI characteristic curve of the main oil way electromagnetic valve are found, and the deviation proportion of the pressure points is calculated; searching a corresponding current point on the PI characteristic curve of the electromagnetic valve of the main oil way; calculating a learning rate; the current points obtained in the fifth step are increased or decreased based on the learning rate to obtain current values after learning; and obtaining an electromagnetic valve characteristic curve based on the learned current value, and storing the electromagnetic valve characteristic curve so as to complete self-learning. According to the method, the PI characteristic curve of the electromagnetic valve is learned according to the actual pressure and the request pressure in the working process of the electromagnetic valve, the learning precision can be ensured to meet the design requirement, and the learning process can be ensured to be smooth and stable.

Description

Technical Field

[0001] The present invention belongs to the field of automobile technology, and in particular relates to a method, a device and a storage medium for learning a PI characteristic curve of a solenoid valve of a hybrid transmission. Background Art

[0002] For hybrid transmissions that match the HEV system, in actual applications, whether the response of the main oil circuit pressure regulating solenoid valve is timely and linear has a great impact on the NVR performance of the entire transmission system. If it is not timely and linear, it will affect the shifting quality and cause symptoms such as acceleration shock, uneven acceleration, and late shifting.

[0003] According to the characteristics of the main oil circuit solenoid valve, the main oil circuit pressure changes with the increase of the solenoid valve opening. Theoretically, the current-pressure curve of the main oil circuit solenoid valve is a fixed relationship. However, due to production consistency, the current-pressure characteristic curve of each solenoid valve is different. Due to wear and tear, the characteristics of the same solenoid valve in the whole life cycle also change. Therefore, the solenoid valve current-pressure curve (i.e., PI characteristic curve) needs to be self-learned. Summary of the invention

[0004] In view of the above-mentioned defects existing in the prior art, the present invention provides a method, device and storage medium for learning the PI characteristic curve of the solenoid valve of a hybrid transmission; the method learns the PI characteristic curve of the solenoid valve according to the actual pressure and the requested pressure during the operation of the solenoid valve, which can not only ensure that the learning accuracy meets the design requirements but also ensure that the learning process is smooth and stable.

[0005] The present invention is achieved through the following technical solutions:

[0006] A method for learning a PI characteristic curve of a solenoid valve of a hybrid transmission specifically comprises the following steps:

[0007] Step 1: Determine whether the triggering conditions for the main oil pressure self-learning are met. If so, proceed to step 2. If not, exit the main oil pressure self-learning.

[0008] Step 2: Determine whether there is a fault. If so, exit the main oil pressure self-learning. If not, proceed to step 3.

[0009] Step 3: Calculate the average actual main oil circuit pressure and the average requested main oil circuit pressure within N cycles;

[0010] Step 4: Calculate the pressure deviation value based on the difference between the average actual main oil circuit pressure and the average requested main oil circuit pressure;

[0011] Step 5: Based on the average requested main oil circuit pressure value, find the closest points A and B on the left and right sides of the main oil circuit solenoid valve PI characteristic curve, and calculate the pressure point deviation ratio based on the above two points; and find the corresponding current point on the main oil circuit solenoid valve PI characteristic curve based on the above two points A and B;

[0012] Step 6: Calculate the learning rate using the following formula:

[0013] Pressure deviation value / slope of PI characteristic curve of main oil circuit solenoid valve*pressure point deviation ratio;

[0014] Step 7: Based on the learning rate, increase or decrease the current point obtained in step 5 to obtain the learned current value;

[0015] Step 8: Obtain the solenoid valve characteristic curve based on the learned current value and store it, thereby completing self-learning.

[0016] Furthermore, in step 1, the triggering conditions for the main oil pressure self-learning need to simultaneously meet the following conditions:

[0017] A1, self-learning enable switch is turned on;

[0018] A2. The difference between the maximum and minimum values ​​of the main oil circuit pressure within N cycles is less than the threshold value;

[0019] A3. The minimum value of the main oil circuit pressure within N cycles is greater than the threshold value;

[0020] A4, oil temperature is greater than the threshold;

[0021] A5, not in the gear shifting process during N cycles;

[0022] A6, no clutch command request within N cycles;

[0023] A7, there is no gear self-learning action within N cycles;

[0024] A8, self-learning enable switch is turned on;

[0025] A9, the clutch pressure control valve CPV CPV and the main oil pressure control valve LPV are not in the solenoid valve flushing process;

[0026] A10, currently not in the state of storing and reading self-learning values;

[0027] The range of N is 2-10 cycles.

[0028] Further, in step 2, the fault includes:

[0029] D1, solenoid valve failure;

[0030] D2, pressure sensor failure;

[0031] D3, clutch failure;

[0032] D4, main oil circuit pressure build-up failure;

[0033] Among them, the solenoid valves include: main oil circuit pressure control valve LPV, clutch pressure control valve CPV, and shift flow control valve QPV.

[0034] Furthermore, in step 5, the pressure point deviation ratio is calculated based on the above two points, and the formula is as follows:

[0035]

[0036] In the formula, and is the deviation ratio between point A and point B, P π is the actual average pressure, P A and P B is the pressure at point A and point B.

[0037] Furthermore, in step 7, the learned current value is obtained by the following formula:

[0038]

[0039] In the formula, I A ,I B is the current at points A and B after learning, I A0 ,I B0 is the current at points A and B before learning.

[0040] In a second aspect, the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a solenoid valve PI characteristic curve learning method for a hybrid transmission as described in any one of the present invention is implemented.

[0041] In a third aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a solenoid valve PI characteristic curve learning method for a hybrid transmission as described in any one of the present inventions.

[0042] Compared with the prior art, the advantages of the present invention are as follows:

[0043] The present invention provides a method, system, device and storage medium for learning the PI characteristic curve of a solenoid valve of a hybrid transmission; the method learns the PI characteristic curve of the solenoid valve according to the actual pressure and the requested pressure during the operation of the solenoid valve, which can ensure that the learning accuracy meets the design requirements and that the learning process is smooth and stable. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0045] Figure 1 It is a flow chart of a method for learning a PI characteristic curve of a solenoid valve of a hybrid transmission of the present invention;

[0046] Figure 2 This is a schematic diagram of the principle of the solenoid valve PI characteristic learning method;

[0047] Figure 3 This is a schematic diagram of the structure of an electronic device in Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0048] In order to clearly and completely describe the technical solution and its specific working process of the present invention, the specific implementation methods of the present invention are as follows in conjunction with the accompanying drawings of the specification:

[0049] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0050] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0051] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0052] Example 1

[0053] According to the characteristics of the main oil circuit solenoid valve, the main oil circuit pressure changes with the increase of the solenoid valve opening. Theoretically, the current-pressure curve of the main oil circuit solenoid valve is a fixed relationship. However, due to production consistency, the current-pressure characteristic curve of each solenoid valve is different. Due to wear and tear, the characteristics of the same solenoid valve in the whole life cycle also change. Therefore, the solenoid valve current-pressure curve (i.e., PI characteristic curve) needs to be self-learned.

[0054] This embodiment proposes a hybrid transmission solenoid valve PI characteristic curve learning method based on Figure 2 The hybrid hydraulic system structure shown in the figure is realized. In terms of hydraulic system power, the mechanical pump is a high-pressure pump responsible for establishing the control system pressure, and the electric pump is a low-pressure pump responsible for lubrication and cooling functions. In terms of hydraulic system control, CPV is the clutch pressure control valve, LPV (LPR in the figure) is the main oil circuit pressure control valve, and QPV is the shift flow control valve. When the engine drives the mechanical pump to reach a certain speed, the main oil circuit solenoid valve opening can be controlled by controlling the current of the main oil circuit solenoid valve coil to adjust the main oil circuit pressure of the system.

[0055] like Figure 1 As shown in the flowchart, the learning method specifically includes the following steps:

[0056] A method for learning a PI characteristic curve of a solenoid valve of a hybrid transmission specifically comprises the following steps:

[0057] Step 1: Determine whether the triggering conditions for the main oil pressure self-learning are met. If so, proceed to step 2. If not, exit the main oil pressure self-learning.

[0058] like Figure 2 As shown, the triggering conditions for the main oil pressure self-learning must meet the following conditions at the same time:

[0059] A1, self-learning enable switch is turned on;

[0060] A2. The difference between the maximum and minimum values ​​of the main oil circuit pressure within N cycles is less than the threshold value;

[0061] A3. The minimum value of the main oil circuit pressure within N cycles is greater than the threshold value;

[0062] A4, oil temperature is greater than the threshold;

[0063] A5, not in the gear shifting process during N cycles;

[0064] A6, no clutch command request within N cycles;

[0065] A7, there is no gear self-learning action within N cycles;

[0066] A8, self-learning enable switch is turned on;

[0067] A9, the clutch pressure control valve CPV CPV and the main oil pressure control valve LPV are not in the solenoid valve flushing process;

[0068] A10, currently not in the state of storing and reading self-learning values;

[0069] The range of N is 2-10 cycles.

[0070] Step 2: Determine whether there is a fault. If so, exit the main oil pressure self-learning. If not, proceed to step 3.

[0071] The faults include:

[0072] D1, solenoid valve failure;

[0073] D2, pressure sensor failure;

[0074] D3, clutch failure;

[0075] D4, main oil circuit pressure build-up failure;

[0076] Among them, the solenoid valves include: main oil circuit pressure control valve LPV, clutch pressure control valve CPV, and shift flow control valve QPV.

[0077] Step 3: Calculate the average actual main oil circuit pressure and the average requested main oil circuit pressure within N cycles;

[0078] Step 4: Calculate the pressure deviation value based on the difference between the average actual main oil circuit pressure and the average requested main oil circuit pressure;

[0079] Step 5: Based on the average requested main oil circuit pressure value, find the closest points A and B on the left and right sides of the main oil circuit solenoid valve PI characteristic curve. In this embodiment, the average main oil circuit pressure is 2.4 bar, and the two closest points on the pressure axis are 2 bar and 3 bar.

[0080] Based on the above two points, the pressure point deviation ratio is calculated as follows:

[0081]

[0082]

[0083] In the formula, and is the deviation ratio between point A and point B, P π is the actual average pressure, P A and P B is the pressure at point A and point B.

[0084] In this embodiment, the deviation ratios obtained by the above calculations are 0.6 and 0.4 respectively;

[0085] Based on the above two points A and B, find the corresponding current point on the PI characteristic curve of the main oil circuit solenoid valve; in this embodiment, the current axis is [100 300 500 700 1000] mA, and the current points corresponding to the two nearest points on the pressure axis are 300 mA and 500 mA, then increase or decrease them at their respective learning speeds at these two points.

[0086] Step 6: Calculate the learning rate using the following formula:

[0087] Pressure deviation value / slope of PI characteristic curve of main oil circuit solenoid valve*pressure point deviation ratio;

[0088] Step 7: Based on the learning rate, increase or decrease the current point obtained in step 5 to obtain the learned current value;

[0089] The current value after learning is obtained by the following formula:

[0090]

[0091] In the formula, I A ,I B is the current at points A and B after learning, I A0 ,I B0 is the current at points A and B before learning.

[0092] Step 8: When the vehicle is powered off, the learned value is stored in NVM.

[0093] When the vehicle is powered on, the value of NVM is read into the system as the initial default value.

[0094] When the vehicle is powered on, the value of NVM is read into the system, or if the reading process fails, the initial EOL value is used as the default value.

[0095] Figure 2 The three curves are the default or initial solenoid valve curve, the updated solenoid valve curve after learning, and the real solenoid valve curve. In the figure, we can see that the software calculates the real pressure based on the requested pressure and the real solenoid valve curve, and then modifies the default solenoid valve curve at a certain speed and rule to obtain the learned solenoid valve curve until it gradually approaches the real value.

[0096] Example 2

[0097] Figure 3 This is a schematic diagram of the structure of a computer device in Example 2 of the present invention. Figure 3 A block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention is shown. Figure 3 The computer device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0098] like Figure 3 As shown, the computer device 12 is in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0099] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0100] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0101] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 3 not shown, usually called a "hard drive"). Although Figure 3 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0102] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in the memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0103] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), may also communicate with one or more devices that enable a user to interact with the computer device 12, and / or communicate with any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed through an input / output (I / O) interface 22. In addition, the computer device 12 in this embodiment, the display 24 does not exist as an independent individual, but is embedded in the mirror surface, and when the display surface of the display 24 is not displayed, the display surface of the display 24 and the mirror surface are visually integrated. In addition, the computer device 12 may also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN) and / or public network, such as the Internet) through a network adapter 20. As shown in the figure, the network adapter 20 communicates with other modules of the computer device 12 through a bus 18. It should be understood that although not shown in the figures, other hardware and / or software modules may be used in conjunction with the computer device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0104] The processing unit 16 executes various functional applications and data processing by running the programs stored in the system memory 28 , for example, implementing a solenoid valve PI characteristic curve learning method for a hybrid transmission provided in an embodiment of the present invention.

[0105] Example 3

[0106] Embodiment 3 of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, a method for learning a PI characteristic curve of a solenoid valve of a hybrid transmission as provided in all the embodiments of the present application is implemented.

[0107] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0108] Computer-readable signal media may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0109] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0110] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0111] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for learning a PI characteristic curve of a solenoid valve of a hybrid transmission, characterized in that: The specific steps include: Step 1: Determine whether the triggering conditions for the main oil pressure self-learning are met. If so, proceed to step 2. If not, exit the main oil pressure self-learning. Step 2: Determine whether there is a fault. If so, exit the main oil pressure self-learning. If not, proceed to step 3. Step 3: Calculate the average actual main oil circuit pressure and the average requested main oil circuit pressure within N cycles; Step 4: Calculate the pressure deviation value based on the difference between the average actual main oil circuit pressure and the average requested main oil circuit pressure; Step 5: Based on the average requested main oil circuit pressure value, find the closest points A and B on the left and right sides of the main oil circuit solenoid valve PI characteristic curve, and calculate the pressure point deviation ratio based on the above two points; and find the corresponding current point on the main oil circuit solenoid valve PI characteristic curve based on the above two points A and B; Step 6: Calculate the learning rate using the following formula: Pressure deviation value / slope of PI characteristic curve of main oil circuit solenoid valve*pressure point deviation ratio; Step 7: Based on the learning rate, increase or decrease the current point obtained in step 5 to obtain the learned current value; Step 8: Obtain the solenoid valve characteristic curve based on the learned current value and store it, thereby completing self-learning.

2. A method for learning a PI characteristic curve of a solenoid valve of a hybrid transmission as claimed in claim 1, characterized in that: In step 1, the triggering conditions for the main oil pressure self-learning must meet the following conditions at the same time: A1, self-learning enable switch is turned on; A2. The difference between the maximum and minimum values ​​of the main oil circuit pressure within N cycles is less than the threshold value; A3. The minimum value of the main oil circuit pressure within N cycles is greater than the threshold value; A4, oil temperature is greater than the threshold; A5, not in the gear shifting process during N cycles; A6, no clutch command request within N cycles; A7, there is no gear self-learning action within N cycles; A8, self-learning enable switch is turned on; A9, the clutch pressure control valve CPV CPV and the main oil pressure control valve LPV are not in the solenoid valve flushing process; A10, currently not in the state of storing and reading self-learning values; The range of N is 2-10 cycles.

3. The method for learning a PI characteristic curve of a solenoid valve of a hybrid transmission as claimed in claim 1, characterized in that: In step 2, the fault includes: D1, solenoid valve failure; D2, pressure sensor failure; D3, clutch failure; D4, main oil circuit pressure build-up failure; Among them, the solenoid valves include: main oil circuit pressure control valve LPV, clutch pressure control valve CPV, and shift flow control valve QPV.

4. A method for learning a PI characteristic curve of a solenoid valve of a hybrid transmission as claimed in claim 1, characterized in that: In step 5, the pressure point deviation ratio is calculated based on the above two points, and the formula is as follows: In the formula, and is the deviation ratio between point A and point B, P π is the actual average pressure, P A and P B is the pressure at point A and point B.

5. The method for learning a PI characteristic curve of a solenoid valve of a hybrid transmission as claimed in claim 1, characterized in that: In step 7, the learned current value is obtained by the following formula: In the formula, I A ,I B is the current at points A and B after learning, I A0 ,I B0 is the current at points A and B before learning.

6. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for learning a PI characteristic curve of a solenoid valve of a hybrid transmission as claimed in any one of claims 1 to 5 is implemented.

7. A computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the method for learning a PI characteristic curve of a solenoid valve of a hybrid transmission according to any one of claims 1 to 5 is implemented.

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