An adaptive method and system for gain value of dual-clutch automatic transmission
By calculating the difference between the clutch input torque and output torque in real time, updating the adaptive gain matrix, and performing linear regression, the problem of pressure-torque relationship deviation caused by clutch wear is solved, thereby improving the vehicle's power and smoothness.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ZHIXIN TECH CO LTD
- Filing Date
- 2023-09-06
- Publication Date
- 2026-05-26
Smart Images
Figure CN117108734B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of vehicle control technology, and specifically to a method and system for adaptive gain value of a dual-clutch automatic transmission. Background Technology
[0002] The execution strategy of a wet dual-clutch transmission differs from other automatic transmissions. It features a clutch pressure-torque model built into the TCU software. The TCU executes corresponding clutch pressure based on the torque input from the engine to control engine speed and provide driving force to the vehicle. Due to manufacturing differences in clutch hardware or wear caused by long-term operation, the actual clutch pressure-torque relationship will deviate from the clutch pressure-torque model built into the software. Therefore, a correction coefficient, i.e., a gain value, is needed to correct this pressure-torque relationship. When the dual-clutch automatic transmission is completed at end-of-life (EOL), the gain value deviation caused by hardware manufacturing differences can be determined on a test bench using torque sensors. However, as clutch wear increases, this correction coefficient needs to be adjusted in real time. Therefore, adaptive learning of the gain value is required during vehicle use to compensate for the gain value deviation caused by clutch wear. Summary of the Invention
[0003] The purpose of this invention is to address the shortcomings of existing technologies by providing a dual-clutch automatic transmission gain value adaptive method and system that can verify and adapt the clutch gain value in real time without disrupting the vehicle's operating state during normal operation.
[0004] This invention discloses an adaptive gain value method for a dual-clutch automatic transmission, the technical solution of which includes the following steps:
[0005] The adaptive gain value matrix of the dual-clutch automatic transmission is obtained by adaptively initializing the gain value.
[0006] When the vehicle and transmission are running normally, determine whether the vehicle meets the conditions for adaptation, and start adaptive learning if the conditions are met;
[0007] The difference between the clutch input torque and the clutch output torque is calculated.
[0008] The adaptive gain matrix is updated based on the difference.
[0009] Linear regression calculation is performed on the updated adaptive gain matrix to obtain linear regression coefficients, including clutch speed correlation coefficient b1, clutch torque correlation coefficient b2 and constant term b3.
[0010] Based on the linear regression coefficients, and combined with the clutch input torque and clutch input speed corresponding to the real-time operating conditions, the real-time clutch gain value is calculated.
[0011] Preferably, the adaptive initialization of the dual-clutch automatic transmission gain value includes:
[0012] After the vehicle supplies power to the control unit of the automatic transmission, read the EOL offline self-learning gain value gain_ti and the initial adaptive gain value linear regression coefficient from the EEPROM;
[0013] The adaptive gain matrix is obtained by performing an inverse linear regression operation based on the initial adaptive gain value linear regression coefficients.
[0014] Preferably, the conditions for determining whether the vehicle meets the adaptive criteria include:
[0015] Determine if the vehicle simultaneously meets the following conditions:
[0016] a. The clutch input torque, clutch output torque, and clutch target torque are all within the set upper and lower limits, and the difference between two adjacent sampling times is not greater than the set limit value, and the above conditions are continuously met until the set time limit is reached.
[0017] b. The clutch slippage speed, clutch drive plate speed, and clutch drive plate speed change rate are all within the set upper and lower limits, and continuously meet the set time limit.
[0018] c. The clutch friction plate temperature and transmission oil temperature are both within the set upper and lower limits, and continuously meet the set time limit.
[0019] d. The target clutch is in torque control mode, and the non-target clutch is in non-operation mode.
[0020] If all of the above conditions are met, then the vehicle is determined to meet the conditions for adaptive operation.
[0021] Preferably, updating the adaptive gain matrix based on the difference includes:
[0022] Based on the clutch input torque and clutch input speed under the current operating conditions, the matrix elements are determined in the adaptive gain value matrix;
[0023] The matrix elements are added or subtracted based on the difference.
[0024] More preferably, performing addition and subtraction operations on the determined matrix elements based on the difference includes:
[0025] When the difference is greater than the set limit, a subtraction operation is performed on the determined matrix elements;
[0026] When the difference is less than the negative value of the set limit, the determined matrix elements are added.
[0027] Otherwise, no operations are performed on the given matrix elements.
[0028] Preferably, the calculation of the real-time clutch gain value includes:
[0029] The clutch gain value is calculated using the following formula:
[0030] Clutch gain value = Clutch EOL lower limit gain value * Adaptive gain value
[0031] Adaptive gain value = Clutch speed correlation coefficient b1 * Clutch input speed + Clutch torque correlation coefficient b2 * Clutch input torque + Constant term b3.
[0032] Preferably, when the vehicle's TCU is adapted to new transmission hardware, the adaptive gain value matrix is set to the default value, and adaptive learning is performed again according to the new hardware.
[0033] The present invention also provides a dual-clutch automatic transmission gain value adaptive system, including a signal processing module, an adaptive condition judgment module, an adaptive process management module, and a gain value calculation module;
[0034] The signal processing module is used to process the relevant variables that affect the clutch gain value and calculate the difference between the clutch input torque and the clutch output torque.
[0035] The adaptive condition judgment module is used to determine whether the vehicle meets the adaptive conditions when the vehicle and transmission are running normally, and to start adaptive learning when the conditions are met.
[0036] The adaptive process management module is used to adaptively initialize the gain value of the dual-clutch automatic transmission to obtain an adaptive gain value matrix. Based on the difference between the clutch input torque and the clutch output torque, the adaptive gain value matrix is updated and calculated. The updated adaptive gain value matrix is then subjected to linear regression calculation, and the linear regression coefficients are output.
[0037] The gain value calculation module is used to calculate the real-time clutch gain value based on the linear regression coefficients and the clutch input torque and clutch input speed corresponding to the real-time operating conditions.
[0038] Preferably, the adaptive process management module updates the adaptive gain matrix based on the difference between the clutch input torque and the clutch output torque, including:
[0039] Based on the clutch input torque and clutch input speed under the current operating conditions, the matrix elements are determined in the adaptive gain value matrix;
[0040] When the difference is greater than the set limit, a subtraction operation is performed on the determined matrix elements;
[0041] When the difference is less than the negative value of the set limit, the determined matrix elements are added.
[0042] Otherwise, no operations are performed on the given matrix elements.
[0043] Preferably, the gain value calculation module calculates the real-time clutch gain value by:
[0044] The clutch gain value is calculated using the following formula:
[0045] Clutch gain value = Clutch EOL lower limit gain value * Adaptive gain value
[0046] Adaptive gain value = Clutch speed correlation coefficient b1 * Clutch input speed + Clutch torque correlation coefficient b2 * Clutch input torque + Constant term b3.
[0047] The beneficial effects of this invention are as follows: This method can adaptively learn the dual-clutch gain value based on the actual operating state of the vehicle during operation, once certain conditions are met. This corrects the pressure-torque relationship deviation caused by clutch wear during vehicle use, improving vehicle smoothness and transmission durability. This process can be executed automatically during vehicle use without affecting normal driving functions. The vehicle can consistently maintain good power and comfort, including creeping, engine speed fluctuations during start-up, and smoothness. Attached Figure Description
[0048] Figure 1 This is a schematic diagram of the method flow of the present invention;
[0049] Figure 2 This is a schematic diagram illustrating the application logic of clutch gain value in transmission operation;
[0050] Figure 3 A schematic diagram of the workflow of the adaptive learning model for clutch gain value;
[0051] Figure 4 This is a schematic diagram illustrating the specific operating principle of the adaptive learning model for the clutch gain value in this system.
[0052] Figure 5 This is an adaptive schematic diagram for whole vehicle data simulation. Detailed Implementation
[0053] To make the technical problems, technical solutions, and beneficial effects to be solved by this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.
[0054] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.
[0055] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.
[0056] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."
[0057] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0058] References to "one embodiment" or "some embodiments" in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized. "A plurality" means "two or more."
[0059] Example 1
[0060] Figure 1The diagram illustrates a flowchart of a dual-clutch automatic transmission gain value adaptive method according to a preferred embodiment of this application. For ease of explanation, only the parts relevant to this embodiment are shown, and the details are as follows:
[0061] This invention discloses an adaptive gain value method for dual-clutch automatic transmissions, applicable to existing wet dual-clutch automatic transmissions. It can adaptively obtain a more accurate clutch pressure-torque relationship, which can be applied to the vehicle's operation to solve the problem of torque distortion caused by clutch wear, affecting transmission control and overall vehicle smoothness. The method includes the following steps:
[0062] S11, Initialize the adaptive gain value of the dual-clutch automatic transmission to obtain the adaptive gain value matrix;
[0063] This process occurs after the vehicle powers the control unit of the automatic transmission, including reading the EOL offline self-learning gain value gain_ti and the initial adaptive gain value linear regression coefficient from the EEPROM;
[0064] The adaptive gain matrix is obtained by performing an inverse linear regression operation based on the initial adaptive gain value linear regression coefficients.
[0065] The initial adaptive gain value linear regression coefficients include b1′, b2′, and b3′, where b1′, b2′, and b3′ are the initial values of the clutch speed correlation coefficient b1, the clutch torque correlation coefficient b2, and the constant term b3, respectively. Based on b1′, b2′, and b3′, the matrix elements corresponding to each torque-speed are calculated with the set torque breakpoint and speed breakpoint, thus obtaining the adaptive gain value matrix Gain[torque_point speed_point].
[0066] S12 calculates and monitors the clutch input torque, clutch output torque, clutch target torque, clutch slip speed, clutch drive plate speed, clutch drive plate speed change rate, clutch friction plate temperature, transmission oil temperature, and clutch working status when the vehicle and transmission are running normally. It then determines whether the vehicle meets the conditions for adaptive learning and starts adaptive learning when the conditions are met.
[0067] In one embodiment, determining whether the vehicle meets the adaptive conditions includes:
[0068] a. The clutch input torque, clutch output torque, and clutch target torque are all within the set upper and lower limits, and the difference between two adjacent sampling times is not greater than the set limit value, and the above conditions are continuously met until the set time limit is reached.
[0069] b. The clutch slippage speed, clutch drive plate speed, and clutch drive plate speed change rate are all within the set upper and lower limits, and continuously meet the set time limit.
[0070] c. The clutch friction plate temperature and transmission oil temperature are both within the set upper and lower limits, and continuously meet the set time limit.
[0071] d. The target clutch is in torque control mode, and the non-target clutch is in non-operation mode.
[0072] If all of the above conditions are met, then the vehicle is determined to meet the conditions for adaptive operation.
[0073] Specifically, the clutch input torque should be within a suitable range based on the engine's output torque and the rotational inertia of the engine flywheel and clutch drive plate. Maximum and minimum values need to be set, i.e., the upper and lower limits of the clutch input torque. The clutch output torque is obtained by looking up a table using the clutch pressure-torque model integrated in the software. It should also be within a suitable range, and maximum and minimum values need to be set, i.e., the upper and lower limits of the clutch output torque. The clutch target torque is calculated by the TCU based on the actual operating conditions of the vehicle. It should also be within a suitable range, and maximum and minimum values need to be set, i.e., the upper and lower limits of the clutch target torque.
[0074] The clutch slippage speed is calculated by taking the difference between the engine speed and the clutch input shaft speed. It should be within a suitable range and requires setting maximum and minimum values, i.e., setting the upper and lower limits of the clutch slippage speed. The clutch drive plate speed and the clutch drive plate speed change rate are equal to the engine speed and the speed change rate, and should be within a suitable range. It also requires setting maximum and minimum values, i.e., setting the upper and lower limits of the clutch drive plate speed and the clutch drive plate speed change rate.
[0075] The clutch friction plate temperature is calculated by the TCU model, and the transmission oil temperature is measured by the sensor. It should be within a suitable range. Maximum and minimum values need to be set, that is, the upper and lower limits of the clutch friction plate temperature and the transmission oil temperature need to be set.
[0076] The two clutches should ensure that the adaptive learning clutch handles torque control, while the non-adaptive learning clutch is in an inactive state.
[0077] S13, the calculation of the difference between the clutch input torque and the clutch output torque;
[0078] S14, Update the adaptive gain matrix based on the difference;
[0079] In one embodiment, updating the adaptive gain matrix based on the difference includes:
[0080] Based on the clutch input torque and clutch input speed under the current operating conditions, the matrix elements are determined in the adaptive gain value matrix;
[0081] The matrix elements are added or subtracted based on the difference.
[0082] The addition and subtraction operations include:
[0083] When the difference is greater than the set limit, a subtraction operation is performed on the determined matrix elements;
[0084] When the difference is less than the negative value of the set limit, the determined matrix elements are added.
[0085] Otherwise, no operations are performed on the given matrix elements.
[0086] In one embodiment, when the vehicle's TCU is adapted to new transmission hardware, the adaptive gain value matrix is set to its default value and adaptive learning is performed again based on the new hardware.
[0087] S15, perform linear regression calculation on the updated adaptive gain value matrix to obtain linear regression coefficients, including clutch speed correlation coefficient b1, clutch torque correlation coefficient b2 and constant term b3;
[0088] The adaptive gain value matrix in S15 is the updated adaptive gain value matrix. Under certain circumstances, this matrix is the default value matrix (i.e., the initially read matrix). The least squares method is used to perform linear regression calculation on this binary matrix to obtain the new clutch speed correlation coefficient b1, clutch torque correlation coefficient b2 and constant term b3.
[0089] S16. Based on the linear regression coefficients, and combined with the clutch input torque and clutch input speed corresponding to the real-time operating conditions, calculate the real-time clutch gain value.
[0090] In one embodiment, calculating the real-time clutch gain value includes:
[0091] The clutch gain value is calculated using the following formula:
[0092] Clutch gain value = Clutch EOL lower limit gain value * Adaptive gain value
[0093] Adaptive gain value = Clutch speed correlation coefficient b1 * Clutch input speed + Clutch torque correlation coefficient b2 * Clutch input torque + Constant term b3.
[0094] like Figure 2As shown, the TCU calculates the target torque based on external input. This target torque is multiplied by a gain coefficient to obtain the torque used to look up the torque-pressure map, thus determining the amplified or reduced target clutch execution pressure. The clutch pump then applies the corresponding pressure. If the clutch has wear, the gain value is greater than 1, requiring a higher actual clutch execution pressure to output the same torque. Conversely, if the clutch has stronger friction than a standard clutch, the gain value is less than 1, allowing for a lower actual clutch execution pressure to output the same torque. Once the clutch pressure reaches the target value, the lookup torque is calculated based on the pressure-torque map. This lookup torque is then divided by the gain value to obtain the actual clutch output torque. Therefore, the application of the clutch gain value does not change the true value of the clutch output torque; it only adjusts the clutch execution pressure accordingly.
[0095] Example 2
[0096] like Figure 3 As shown, this invention also provides a dual-clutch automatic transmission gain adaptive system, which is based on MATLAB / Simulink modeling and simulation. It includes a signal processing module, an adaptive condition judgment module, an adaptive process management module, and a gain calculation module.
[0097] The signal processing module is used to process the relevant variables that affect the clutch gain value and calculate the difference between the clutch input torque and the clutch output torque.
[0098] The variables affecting the clutch gain value include clutch input torque, clutch output torque, clutch target torque, clutch slippage speed, clutch drive plate speed and its rate of change, etc. Rolling filtering is used to process the signal and obtain smoother data to eliminate signal interference.
[0099] The adaptive condition judgment module is used to determine whether the vehicle meets the adaptive conditions when the vehicle and transmission are running normally, and to start adaptive learning when the conditions are met.
[0100] The specific judgment process is as follows:
[0101] Determine if the vehicle simultaneously meets the following conditions:
[0102] a. The clutch input torque, clutch output torque, and clutch target torque are all within the set upper and lower limits, and the difference between two adjacent sampling times is not greater than the set limit value, and the above conditions are continuously met until the set time limit is reached.
[0103] b. The clutch slippage speed, clutch drive plate speed, and clutch drive plate speed change rate are all within the set upper and lower limits, and continuously meet the set time limit.
[0104] c. The clutch friction plate temperature and transmission oil temperature are both within the set upper and lower limits, and continuously meet the set time limit.
[0105] d. The target clutch is in torque control mode, and the non-target clutch is in non-operation mode.
[0106] If all of the above conditions are met, then the vehicle is determined to meet the conditions for adaptive operation.
[0107] The adaptive process management module includes an adaptive process scheduling module, an initialization value retrieval module, a self-learning calculation module, a default value module, and a final linear regression calculation module. The adaptive process management module is used to adaptively initialize the gain values of the dual-clutch automatic transmission, obtaining an adaptive gain value matrix. Based on the difference between the clutch input torque and the clutch output torque, it updates the adaptive gain value matrix and performs linear regression calculations on the updated adaptive gain value matrix, outputting the linear regression coefficients.
[0108] The adaptive scheduling module is responsible for scheduling the operation of other modules. Upon power-up, it schedules the initialization value acquisition module, which calculates the initial gain matrix using inverse linear regression based on the linear regression coefficients read from the EEPROM. After receiving a suitable adaptive learning signal from the adaptive condition judgment module, the adaptive scheduling module, combined with the adaptive learning requirement input from the self-learning module, decides whether to perform self-learning operations. Based on the external request to restore default values signal, it runs the default value module, forcibly setting the adaptive gain value to the default value. The self-learning gain matrix output from the initialization value acquisition module, the adaptive learning module, and the default value module is merged and calculated. Then, under the control of the adaptive scheduling module, linear regression is performed in the linear regression calculation module, outputting the linear regression coefficients.
[0109] The gain value calculation module is used to calculate the real-time clutch gain value based on the linear regression coefficients and the clutch input torque and clutch input speed corresponding to the real-time operating conditions.
[0110] Example 3
[0111] This embodiment is another example of a dual-clutch automatic transmission gain value adaptive method, such as... Figure 4 The diagram shown illustrates the operational principle of the adaptive learning model for clutch gain, which includes the following execution steps:
[0112] Step 1: When the vehicle is powered on, read the adaptive gain value linear regression coefficients [b1′, b2′, b3′], where b1′, b2′, and b3′ are the initial values of the clutch speed correlation coefficient b1, the clutch torque correlation coefficient b2, and the constant term b3, respectively. Read the EOL offline self-learning gain value gain_ti. Based on the read [b1′, b2′, b3′] and the set torque and speed coordinates, initialize the values through the inverse linear regression operation to obtain the adaptive gain value matrix Gain[torque_point speed_point].
[0113] Step 2, signal processing and adaptive condition judgment before adaptive learning, is performed continuously during software operation.
[0114] Signal processing involves using variables acquired from other modules, such as clutch input torque, clutch output torque, clutch target torque, clutch slippage speed, clutch drive plate speed and rate of change, which may affect the clutch gain value. Rolling filtering is then applied to the signals to obtain smoother data and eliminate signal interference. Simultaneously, the torque difference tq_error is calculated based on the filtered clutch input torque and clutch output torque.
[0115] The adaptive learning condition judgment is based on the clutch input torque, clutch output torque, clutch target torque, clutch slip speed, clutch drive plate speed and rate of change input from the signal processing module, and the clutch friction plate temperature and the working status of the two clutches input from other modules to determine whether the current working conditions are suitable for adaptive learning.
[0116] Specifically, determine whether the vehicle simultaneously meets the following conditions:
[0117] a. The clutch input torque, clutch output torque, and clutch target torque are all within the set upper and lower limits, and the difference between two adjacent sampling times is not greater than the set limit value, and the above conditions are continuously met until the set time limit is reached.
[0118] b. The clutch slippage speed, clutch drive plate speed, and clutch drive plate speed change rate are all within the set upper and lower limits, and continuously meet the set time limit.
[0119] c. The clutch friction plate temperature and transmission oil temperature are both within the set upper and lower limits, and continuously meet the set time limit.
[0120] d. The target clutch is in torque control mode, and the non-target clutch is in non-operation mode.
[0121] If all of the above conditions are met, then the vehicle is determined to meet the conditions for adaptive operation.
[0122] Step 3: When the adaptive learning conditions are met, compare the difference tq_error calculated in Step 2 with the set limit tq_error_min, and determine the matrix operation based on the relationship:
[0123] When tq_error <- tq_error_min, the gain matrix is added, i.e.:
[0124] Gain[torque_point][speed_point] t0+1 =Gain[torque_point][speed_point] t0 +g
[0125] ain_step
[0126] When tq_error > tq_error_min, the gain matrix is subtracted, i.e.:
[0127] Gain[torque_point][speed_point] t0+1 =Gain[torque_point][speed_point] t0 -g
[0128] ain_step
[0129] When -tq_error_min ≤ = tq_error ≤ tq_error_min, the gain matrix remains the same as the previous time step, that is:
[0130] Gain[torque_point][speed_point] t0+1 =Gain[torque_point][speed_point] t0
[0131] Wherein, gain_step is the step value calculated by the set gain value matrix elements.
[0132] The matrix elements used for the calculation are determined by the clutch input torque and clutch input speed under the current operating conditions and the matrix torque-speed coordinates.
[0133] Step 4: Based on the adaptive gain matrix generated in Step 3, perform matrix linear regression using the least squares method. The specific steps are as follows:
[0134] <![CDATA[t1]]> <![CDATA[t2]]> <![CDATA[t3]]> <![CDATA[t4]]> <![CDATA[t5]]> <![CDATA[t6]]> <![CDATA[t7]]> <![CDATA[t8]]> <![CDATA[s1]]> <![CDATA[g1]]> <![CDATA[g2]]> <![CDATA[g3]]> * * * * <![CDATA[g8]]> <![CDATA[s2]]> <![CDATA[g9]]> * * * * * * * <![CDATA[s3]]> * * * * * * * * <![CDATA[s4]]> * * * * * * * * <![CDATA[s5]]> * * * * * * <![CDATA[g 39 ]]> <![CDATA[g 40 ]]>
[0135] Using rotational speed as the ordinate with 5 breakpoints and torque as the abscissa with 8 breakpoints, the matrix is shown in the figure above.
[0136] make:
[0137]
[0138] Let the ideal regression curve be g(s,t) = b1*s + b2*t + b3. Using the least squares method:
[0139] (GS*B) 2 Take the derivative, set it to 0, and obtain matrix B.
[0140] B = (S T S) -1 S T G
[0141] Right now:
[0142]
[0143]
[0144]
[0145] Step 5: Based on the linear regression coefficients b1, b2, and b3 calculated in Step 4, and the EOL lower bound learning value read from EEPROM, the clutch gain value is obtained using the following formula:
[0146] Gain_cor=(b1*S+b2*T+b3)*Gain_ti
[0147] Figure 5 The model simulates the clutch gain value based on data collected from the whole vehicle, and the linear regression coefficients are obtained. gta_clu_gain_cor is the calculated clutch gain value, b1 is the clutch speed correlation coefficient, b2 is the clutch torque correlation coefficient, and b3 is a constant term.
[0148] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process may be rearranged without departing from the scope of this disclosure. The appended method claims provide elements of various steps in an exemplary order and are not intended to limit the scope to the specific order or hierarchy described.
[0149] In the above detailed description, various features are combined together in a single embodiment to simplify this disclosure. This approach to disclosure should not be construed as reflecting an intention that embodiments of the claimed subject matter require more features than are explicitly stated in each claim. Rather, as reflected in the appended claims, the invention is presented with fewer features than all of the features of the single disclosed embodiment. Therefore, the appended claims are hereby explicitly incorporated into the detailed description, wherein each claim stands alone as a preferred embodiment of the invention.
[0150] The disclosed embodiments have been described above to enable any person skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be applied to other embodiments without departing from the spirit and scope of this disclosure. Therefore, this disclosure is not limited to the embodiments given herein, but is consistent with the broadest scope of the principles and novel features disclosed in this application.
[0151] The foregoing description includes examples of one or more embodiments. It is certainly impossible to describe all possible combinations of components or methods in order to describe the above embodiments, but those skilled in the art will recognize that further combinations and arrangements of the various embodiments are possible. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. Furthermore, the term "comprising" as used in the specification or claims is interpreted in a manner similar to the term "including," as it is used as a conjunction in the claims. Additionally, the use of any term "or" in the specification of the claims is intended to mean "non-exclusive or."
[0152] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.
Claims
1. A method for adaptive gain value of a dual-clutch automatic transmission, characterized in that, Includes the following steps: The adaptive gain value matrix of the dual-clutch automatic transmission is obtained by adaptively initializing the gain value. When the vehicle and transmission are running normally, determine whether the vehicle meets the conditions for adaptation, and start adaptive learning if the conditions are met; Calculate the difference between the clutch input torque and the clutch output torque; The adaptive gain matrix is updated based on the difference. Linear regression calculation is performed on the updated adaptive gain matrix to obtain linear regression coefficients, including clutch speed correlation coefficient b1, clutch torque correlation coefficient b2 and constant term b3. Based on the linear regression coefficients, and combined with the clutch input torque and clutch input speed corresponding to the real-time operating conditions, the real-time clutch gain value is calculated. The adaptive initialization of the dual-clutch automatic transmission gain value includes: After the vehicle supplies power to the control unit of the automatic transmission, read the EOL offline self-learning gain value gain_ti and the initial adaptive gain value linear regression coefficient from the EEPROM; The adaptive gain value matrix is obtained by performing an inverse linear regression operation based on the linear regression coefficients of the initial adaptive gain value. The conditions for determining whether a vehicle meets the adaptive criteria include: Determine if the vehicle simultaneously meets the following conditions: a. The clutch input torque, clutch output torque, and clutch target torque are all within the set upper and lower limits, and the difference between two adjacent sampling times is not greater than the set limit value, and the above conditions are continuously met until the set time limit is reached. b. The clutch slippage speed, clutch drive plate speed, and clutch drive plate speed change rate are all within the set upper and lower limits, and continuously meet the set time limit. c. The clutch friction plate temperature and transmission oil temperature are both within the set upper and lower limits, and continuously meet the set time limit. d. The target clutch is in torque control mode, and the non-target clutch is in non-operation mode. If all of the above conditions are met, then the vehicle is determined to meet the conditions for adaptive operation. The update calculation of the adaptive gain value matrix based on the difference includes: Based on the clutch input torque and clutch input speed under the current operating conditions, the matrix elements are determined in the adaptive gain value matrix; The matrix elements are added or subtracted based on the difference. The addition and subtraction operations performed on the determined matrix elements based on the difference include: When the difference is greater than the set limit, a subtraction operation is performed on the determined matrix elements; When the difference is less than the negative value of the set limit, the determined matrix elements are added. Otherwise, no operations are performed on the given matrix elements.
2. The adaptive gain method for a dual-clutch automatic transmission according to claim 1, characterized in that, The calculation of the real-time clutch gain value includes: The clutch gain value is calculated using the following formula: Clutch gain value = Clutch EOL lower limit gain value Adaptive gain value Adaptive gain value = Clutch speed correlation coefficient b1 Clutch input speed + clutch torque correlation coefficient b2 Clutch input torque + constant term b3.
3. The adaptive gain value method for a dual-clutch automatic transmission according to claim 1, characterized in that: When the vehicle's TCU is adapted to new transmission hardware, the adaptive gain matrix is set to its default value and relearned adaptively based on the new hardware.
4. A dual-clutch automatic transmission gain adaptive system for implementing the method as described in any one of claims 1 to 3, characterized in that: This includes a signal processing module, an adaptive condition judgment module, an adaptive process management module, and a gain value calculation module; The signal processing module is used to process the relevant variables that affect the clutch gain value and calculate the difference between the clutch input torque and the clutch output torque. The adaptive condition judgment module is used to determine whether the vehicle meets the adaptive conditions when the vehicle and transmission are running normally, and to start adaptive learning when the conditions are met. The adaptive process management module is used to adaptively initialize the gain value of the dual-clutch automatic transmission to obtain an adaptive gain value matrix. Based on the difference between the clutch input torque and the clutch output torque, the adaptive gain value matrix is updated and calculated. The updated adaptive gain value matrix is then subjected to linear regression calculation, and the linear regression coefficients are output. The gain value calculation module is used to calculate the real-time clutch gain value based on the linear regression coefficients and the clutch input torque and clutch input speed corresponding to the real-time operating conditions.
5. The dual-clutch automatic transmission gain adaptive system as described in claim 4, characterized in that, The adaptive process management module updates the adaptive gain matrix based on the difference between the clutch input torque and the clutch output torque, including: Based on the clutch input torque and clutch input speed under the current operating conditions, the matrix elements are determined in the adaptive gain value matrix; When the difference is greater than the set limit, a subtraction operation is performed on the determined matrix elements; When the difference is less than the negative value of the set limit, the determined matrix elements are added. Otherwise, no operations are performed on the given matrix elements.
6. The dual-clutch automatic transmission gain adaptive system as described in claim 4, characterized in that, The gain value calculation module calculates the real-time clutch gain value, including: The clutch gain value is calculated using the following formula: Clutch gain value = Clutch EOL lower limit gain value Adaptive gain value Adaptive gain value = Clutch speed correlation coefficient b1 Clutch input speed + clutch torque correlation coefficient b2 Clutch input torque + constant term b3.