A method of closed loop control of engine oil pressure

Abstract

The application discloses a kind of engine oil pressure closed-loop control methods, the method includes: introduce the coefficient about engine speed, the maximum of target VVT and actual VVT phase difference in intake and exhaust VVT, the state of piston cooling nozzle and engine oil temperature, oil pressure difference is corrected;Introduce the coefficient about engine retreat angle intensity coefficient and oil product octane number, and the oil pressure difference rate is corrected;Fuzzy controller is constructed and fuzzy control rule is set, and the oil pressure difference after correction and oil pressure difference rate are input fuzzy controller, and the control duty cycle of fuzzy controller output engine oil pump;According to control duty cycle, drive engine oil pump action to realize oil pressure following.The present application is by fuzzy control strategy, and the knowledge and thinking of relevant experts, learning and reasoning, association and decision-making process are identified and modeled by computer, and control is carried out, and the control precision and stability of oil pressure are further improved.

Description

Technical Field

[0001] This invention relates to the field of engine control, and more particularly to a closed-loop control method for oil pressure. Background Technology

[0002] Oil pump control can continuously change the oil pumping volume according to the oil pressure requirements of various power system components under different speed, temperature, load and other conditions, making the control more precise and achieving complete on-demand distribution. This avoids the oil loss of traditional fixed displacement oil pumps across the entire speed range and can effectively reduce friction and oil consumption.

[0003] However, in order to further improve the engine's fuel economy, power, and emissions performance, the complexity of engine control is required to increase. For example, piston cooling nozzles are installed on the engine to reduce the heat load on the piston and enhance the lubrication of the piston pin and connecting rod bearings; and the control accuracy of VVT is required, which in turn puts forward higher requirements for the control of the oil pump.

[0004] Based on the above objectives, how to accurately control oil pressure for different engine operating conditions is an urgent problem to be solved. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a closed-loop control method for oil pressure, which addresses the deficiencies in the prior art.

[0006] The technical solution adopted by this invention to solve its technical problem is:

[0007] This invention provides a closed-loop control method for engine oil pressure, the method comprising:

[0008] The oil pressure differential is corrected by introducing coefficients related to engine speed, the maximum value of the phase difference between the target VVT and the actual VVT in the intake and exhaust VVT, the state of the piston cooling nozzle, and the oil temperature; the oil pressure differential change rate is corrected by introducing coefficients related to the engine retraction angle strength coefficient and the oil octane number.

[0009] Construct a fuzzy controller and set fuzzy control rules. Input the corrected oil pressure difference and oil pressure difference change rate into the fuzzy controller. The fuzzy controller outputs the control duty cycle of the oil pump.

[0010] The oil pump is driven to follow the control duty cycle to achieve oil pressure tracking.

[0011] Furthermore, the method for correcting the oil pressure difference and the rate of change of oil pressure difference in the present invention specifically includes:

[0012] f(n,phi) VVTErr )×f(b PistonStatus ,T Oil )×p OilErrAs the corrected oil pressure difference p OilErrNew ;

[0013] Will The corrected rate of change of oil pressure difference dp OilErrNew ;

[0014] Where, p OilErr The oil pressure is the difference between the target oil pressure and the actual oil pressure, where n is the engine speed and phi is the oil pressure. VVTErr b is the maximum value of the phase difference between the target VVT and the actual VVT in both intake and exhaust VVT. PistonStatus For the state of the piston cooling nozzle, T Oil For engine oil temperature, r is the engine retraction angle strength coefficient. Oc tan eRatio The octane number of the oil; p OilErr dp represents the oil pressure difference before correction. OilErr This represents the rate of change in oil pressure differential before correction.

[0015] Furthermore, in the method of the present invention, the oil pressure difference p before correction... OilErr oil pressure differential change rate dp OilErr The calculation method is as follows:

[0016]

[0017] Where Δt is the time interval of the sampling period. For dp OilErr The value of the previous sampling period, the first sampled value dp OilErr (0) is 0. For p OilErr The value of the previous sampling period, the first sampled value p OilErr (0) Take 0, t c The time constant is used to calculate the rate of change.

[0018] Furthermore, the method of the present invention also includes a method for calibrating the parameters:

[0019] f(n,phi VVTErr The calibration method is as follows: by setting different target oil pressures, when the piston cooling nozzle is not activated, the oil temperature is 90℃, no knocking occurs, and the octane number coefficient is 0, the oil pressure control accuracy can be guaranteed to be within ±2kPa under any engine speed and any VVT phase deviation. Based on this condition, the calibration value is obtained.

[0020] f(b PistonStatus ,T OilThe calibration method is as follows: by setting different target oil pressures, under the conditions of engine speed of 3000rpm, VVT phase deviation equal to ±2° crankshaft angle, no knocking, and octane coefficient of 0, under any piston cooling nozzle condition and any oil temperature, the oil pressure control accuracy can be guaranteed to be within ±2kPa through fuzzy control, and the calibration value is obtained based on these conditions.

[0021] The calibration method is as follows: by setting different target oil pressures, when the engine speed is 3000 rpm, the VVT ​​phase deviation is equal to ±2° crankshaft angle, the piston cooling nozzle is not activated, and the oil temperature is 90℃, under the knock angle and any octane number coefficient, the oil pressure control accuracy can be guaranteed to be within ±2kPa through fuzzy control. Based on this condition, the calibration value is obtained.

[0022] Furthermore, the method for constructing a fuzzy controller in the method of the present invention includes:

[0023] Establish membership functions, and adopt triangular or trapezoidal membership functions for fuzzy control processes;

[0024] The oil pressure difference and the rate of change of oil pressure difference are fuzzified to obtain the first fuzzy quantity and the second fuzzy quantity; the fuzzy control quantity is obtained based on the first fuzzy quantity, the second fuzzy quantity and the preset fuzzy control rules.

[0025] The fuzzy control quantity is defuzzified to obtain the fuzzy control duty cycle Pct.

[0026] Furthermore, the method for establishing the membership function in the method of the present invention includes:

[0027] The oil pressure difference is divided into 5 fuzzy sets with the universe of discourse set to [-30, 30]. When the oil pressure difference is below -15 kPa, the fuzzy control rule belongs to negative large NB, and when the oil pressure difference is above 15 kPa, the fuzzy control rule belongs to positive large PB. Negative large NB indicates that the actual oil pressure is 15 kPa greater than the target oil pressure; negative small NS indicates that the actual oil pressure is 5 kPa greater than the target oil pressure; zero ZO indicates that the actual oil pressure is approximately equal to the target oil pressure; positive small PS indicates that the actual oil pressure is 5 kPa less than the target oil pressure; positive large PB indicates that the actual oil pressure is 15 kPa less than the target oil pressure. Based on this, the membership function of the oil pressure difference is obtained.

[0028] The oil pressure differential change rate is also divided into 5 fuzzy sets, with the universe of discourse set to [-100, 100]. When the oil pressure differential change rate is below -60 kPa / s, the fuzzy control rule belongs to negative large NB; when the oil pressure differential change rate is above 60 kPa / s, the fuzzy control rule belongs to positive large PB. Negative large NB indicates that the oil pressure differential change rate is -60 kPa / s; negative small NS indicates that the oil pressure differential change rate is -20 kPa / s; zero ZO indicates that the oil pressure differential change rate is 0 kPa / s; positive small PS indicates that the oil pressure differential change rate is 20 kPa / s; positive large PB indicates that the oil pressure differential change rate is 60 kPa / s. Based on this, the membership function of the oil pressure differential change rate is obtained.

[0029] The output of the fuzzy controller is a fuzzy control quantity, and the universe of discourse is set to [0, 100]. This means that the final fuzzy control quantity is limited to the range of 0 to 100. When the target oil pressure is close to the actual oil pressure, the final control duty cycle stabilizes near Z0, and the membership function of the fuzzy control quantity output is obtained.

[0030] Furthermore, the method for setting fuzzy control rules in the method of the present invention includes:

[0031] The preset fuzzy control rules are organized into a fuzzy control rule table and stored in advance. The fuzzy control rule table stores the fuzzy control output results when the oil pressure difference is {NB, NS, ZO, PS, PB} and the oil pressure difference change rate is {NB, NS, ZO, PS, PB}.

[0032] After fuzzifying the currently detected oil pressure difference and the rate of change of oil pressure difference to the corresponding fuzzy sets, the first fuzzy quantity and the second fuzzy quantity are determined, and the fuzzy control quantity is obtained according to the fuzzy control rule table.

[0033] Furthermore, the method for deblurring in the method of the present invention includes:

[0034] The centroid method is used for defuzzification. The fuzzy control output u corresponding to the oil pressure difference and the rate of change of oil pressure difference is calculated using the following formula. This fuzzy control output u is the fuzzy control correction coefficient r. fuzzy :

[0035]

[0036] Where, μ c (u i ) for u i membership degree, u i This represents the i-th fuzzy control input.

[0037] Furthermore, the method of the present invention also includes an update method using a wheel domain fuzzy set partitioning based on the coefficient oil pressure difference change rate. When the set update conditions are met, the following update is performed:

[0038] If all update conditions are met and the duration exceeds t1, then updating the oil pressure differential wheel domain fuzzy set is allowed; otherwise, updating is not allowed.

[0039] Read the average actual oil pressure within time t2;

[0040] 1) If the difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value, but the time during which the difference between the actual oil pressure and the target oil pressure exceeds the preset value divided by t2 exceeds 50%, then the negative small NS and positive small PS of the oil pressure difference change rate under the current working condition are adjusted in the wheel domain fuzzy set. The default value is that the negative small NS indicates that the oil pressure difference change rate is -20kPa / s; the positive small PS indicates that the oil pressure difference change rate is 20kPa / s.

[0041] The update method is as follows: NS(N+1) = NS(N) × 1.2, PS(N+1) = PS(N) × 1.2, PS(N) is the PS at the Nth update, PS(N+1) is the PS at the N+1th update, N = 0, 1, 2, 3. When N = 0, PS(0) indicates that the oil pressure difference change rate is 20 kPa / s, and NS(0) indicates that the oil pressure difference change rate is -20 kPa / s; N increases by 1 with each update.

[0042] 2) If the difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value, but the time during which the difference between the actual oil pressure and the target oil pressure exceeds the preset value divided by t2 exceeds 10%, then the negative small NS and positive small PS of the oil pressure difference change rate under the current working condition are adjusted in the wheel domain fuzzy set.

[0043] The update method is as follows: NS(N+1) = NS(N) × 1.1, PS(N+1) = PS(N) × 1.1, and N is incremented by 1 each time an update is performed;

[0044] 3) If the difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value, but the time during which the difference between the actual oil pressure and the target oil pressure exceeds the preset value within time t2 is greater than 0% but not more than 10%, then the negative small NS and positive small PS of the oil pressure difference change rate under the current working condition are adjusted in the wheel domain fuzzy set.

[0045] The update method is as follows: NS(N+1) = NS(N) × 1.05, PS(N+1) = PS(N) × 1.05, and N is incremented by 1 each time an update is performed;

[0046] 4) The difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value, and the difference between the actual oil pressure and the target oil pressure does not exceed the preset value within time t2. Record the number of times this condition is met consecutively (CNT).

[0047] 4.1) If CNT is less than the preset value at this time, then update NS(N+1) = NS(N) and PS(N+1) = PS(N) for the current operating condition;

[0048] 4.2) If CNT is less than the preset value at this time, then:

[0049] NS(N+1)=NS(N)×0.98, PS(N+1)=PS(N)×0.98;

[0050] If an error occurs after the update, clear CNT to zero and update NS(N+1) = NS(N) and PS(N+1) = PS(N);

[0051] The updated driving cycle will not be executed after the update. It will be saved after the vehicle is powered off and the updated wheel domain fuzzy set will be executed after the next driving cycle begins.

[0052] The present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described oil pressure closed-loop control method.

[0053] The beneficial effects of this invention are:

[0054] 1. The method of the present invention uses a fuzzy control strategy to enable the computer to identify and model the knowledge, thinking, learning and reasoning, association and decision-making processes of relevant experts, and then control them, thereby further improving the control accuracy and stability of hydraulic pressure.

[0055] 2. This invention introduces coefficients related to engine speed, the maximum value of the phase difference between the target VVT and the actual VVT in the intake and exhaust VVT, the state of the piston cooling nozzle, and the oil temperature to correct the oil pressure difference; it also introduces coefficients related to the engine retraction angle strength coefficient and the oil octane number to correct the oil pressure difference change rate; the corrected oil pressure difference and oil pressure difference change rate can more accurately reflect the impact of oil pressure on the vehicle.

[0056] 3. This invention provides a method for calibrating the corrected oil pressure difference and oil pressure difference change rate. This calibration method makes the correction of oil pressure difference and oil pressure difference change rate more accurate and more applicable to various working conditions.

[0057] 4. This invention constructs a fuzzy controller. The inputs of the fuzzy controller are: oil pressure difference and oil pressure difference change rate. The output of the fuzzy controller is: oil pump control duty cycle. Corresponding fuzzy control rules are formulated to obtain a more accurate control duty cycle. Attached Figure Description

[0058] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings:

[0059] Figure 1 This is a flowchart of the closed-loop control method for oil pressure according to an embodiment of the present invention;

[0060] Figure 2 It is the membership function of the oil pressure difference in this embodiment of the invention;

[0061] Figure 3 It is the membership function of the rate of change of oil pressure difference in this embodiment of the invention;

[0062] Figure 4 It is the membership function of the fuzzy control output in this embodiment of the invention;

[0063] Figure 5 This is the fuzzy control rule of this invention, and the output fuzzy control quantity corresponds to the oil pressure difference and the rate of change of oil pressure difference. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0065] Example 1

[0066] This invention proposes a closed-loop control method for engine oil pressure, wherein the oil pressure described in the embodiments refers to the engine oil pressure.

[0067] This invention uses a fuzzy control method to control the dynamic change process of oil pressure based on the difference between the target oil pressure and the actual oil pressure, as well as the rate of change of the oil pressure difference. It outputs a control duty cycle to drive the oil pump to achieve oil pressure following.

[0068] f(n,phi) VVTErr )×f(b PistonStatus ,T Oil )×p OilErr As the corrected oil pressure difference p OilErrNew ;

[0069] Will The corrected rate of change of oil pressure difference dp OilErrNew ;

[0070] According to the embodiments of the present invention, based on the corrected oil pressure difference p OilErrNew and the corrected rate of change of oil pressure difference dp OilErrNew The dynamic change process of oil pressure is controlled by fuzzy control method, and the output control duty cycle is determined.

[0071] Where, p OilErr The oil pressure is the difference between the target oil pressure and the actual oil pressure, where n is the engine speed and phi is the oil pressure.VVTErr b is the maximum value of the phase difference between the target VVT and the actual VVT in both intake and exhaust VVT. PistonStatus The state of the piston cooling nozzle (0 indicates the piston cooling nozzle is not working; 1 indicates the standard piston cooling nozzle is working, powered on, and open), T Oil For engine oil temperature, The engine retraction angle strength coefficient (phi) Knock For the current detonation delay ignition angle, phi KnockMax The maximum permissible ignition angle for detonation delay (10° in this example), r Oc tan eRatio This represents the octane number coefficient of the oil product. Oil pressure difference p OilErr rate of change dp OilErr The calculation method is as follows:

[0072]

[0073] Where Δt is the time interval of the sampling period (10ms in this example), For dp OilErr The value of the previous sampling period (specifically, the first sampled value dp) OilErr (0) take 0), For p OilErr The value of the previous sampling period (specifically, the first sampled value p) OilErr (0) take 0), t c The time constant for calculating the rate of change (20ms in this example).

[0074] f(n,phi) VVTErr )×f(b PistonStatus ,T Oil The reasons for compensating for the oil pressure difference are as follows: 1) The higher the engine speed, the more lubrication the engine needs to avoid cylinder scoring, requiring higher precision in oil pressure control. When performing wheel domain fuzzy set partitioning, the oil pressure difference is considered to be closer to the target oil pressure when it is smaller; 2) When the VVT ​​phase deviation is larger, higher precision oil pressure is needed to improve VVT ​​phase control. Therefore, when performing wheel domain fuzzy set partitioning, the oil pressure difference is considered to be closer to the target oil pressure when it is smaller; 3) When the piston cooling nozzle is activated, more accurate oil pressure is needed for piston cooling. Therefore, when performing wheel domain fuzzy set partitioning, the oil pressure difference is considered to be closer to the target oil pressure when it is smaller; 4) When the oil temperature is lower, the oil viscosity is higher, requiring a faster response oil pressure to ensure lubrication. Therefore, when performing wheel domain fuzzy set partitioning, the oil pressure difference is considered to be closer to the target oil pressure when it is smaller.

[0075] Example 2

[0076] This invention describes a method for calibrating various parameters, as detailed below:

[0077] f(n,phi VVTErr The calibration method is as follows: By setting different target oil pressures, under the conditions that the piston cooling nozzles are not activated, the oil temperature is 90℃, no knocking occurs, and the octane rating is 0, at any engine speed and with any VVT phase deviation, the following fuzzy control method can ensure that the oil pressure control accuracy is within ±2kPa (i.e., the difference between the target oil pressure and the actual oil pressure does not exceed ±2kPa, or the continuous time exceeding ±2kPa does not exceed 0.05s). Based on this, the calibration data for this example are as follows:

[0078]

[0079]

[0080] f(b PistonStatus ,T Oil The calibration method is as follows: By setting different target oil pressures, under conditions of engine speed 3000 rpm, VVT phase deviation equal to ±2° crankshaft angle, no knocking, and octane rating of 0, the following fuzzy control method can ensure oil pressure control accuracy within ±2 kPa (i.e., the difference between target oil pressure and actual oil pressure does not exceed ±2 kPa, or the continuous time exceeding ±2 kPa does not exceed 0.05 s) based on this. The calibration data for this example are as follows:

[0081]

[0082] Will The reason for compensating for the rate of change of oil pressure difference is: 1) Knock angle strength coefficient The higher the octane rating, the stronger the knocking. To suppress knocking, it is necessary to ensure a faster rate of oil pressure increase. 2) The lower the octane rating, the worse the oil quality. To reduce the possibility of knocking, it is necessary to ensure a faster rate of oil pressure increase.

[0083] The calibration method is as follows: By setting different target oil pressures, with an engine speed of 3000 rpm, a VVT phase deviation of ±2° crankshaft angle, piston cooling nozzles not activated, and oil temperature of 90°C, under the conditions of knock angle and arbitrary octane number, the following fuzzy control method can ensure that the oil pressure control accuracy is within ±2 kPa (i.e., the difference between the target oil pressure and the actual oil pressure does not exceed ±2 kPa, or the continuous time exceeding ±2 kPa does not exceed 0.05 s). Based on this, the calibration data for this example are as follows:

[0084]

[0085] Example 3

[0086] This invention provides an embodiment based on the corrected oil pressure difference p OilErrNew and the corrected rate of change of oil pressure difference dp OilErrNew The dynamic change process of oil pressure is controlled using a fuzzy control method, and the output result is the control duty cycle, as follows:

[0087] Understandably, establishing membership functions is necessary to implement fuzzy control. There are certain principles for establishing membership functions. Since the fuzzy control process is not sensitive to the shape of the membership function for linguistic variable values, but only to the range of membership degrees, in this embodiment, triangular or trapezoidal membership functions can be used, which is beneficial for calculating membership degrees.

[0088] In the specific implementation process, a fuzzy controller needs to be constructed. The inputs of the fuzzy controller are the oil pressure difference and the rate of change of the oil pressure difference. The output of the fuzzy controller is the oil pump control duty cycle Pct. The process of determining the fuzzy control duty cycle Pct based on the oil pressure difference, the rate of change of the oil pressure difference, and the preset fuzzy control rules may include: fuzzifying the oil pressure difference and the rate of change of the oil pressure difference to obtain a first fuzzy quantity and a second fuzzy quantity; obtaining the fuzzy control quantity based on the first fuzzy quantity, the second fuzzy quantity, and the preset fuzzy control rules; and defuzzifying the fuzzy control quantity to obtain the fuzzy control duty cycle Pct.

[0089] Before performing the above steps, the preset fuzzy control rules can be pre-organized into a fuzzy control rule table and stored. The following example illustrates the construction process of the fuzzy control rule table. Of course, in actual implementation, the number of fuzzy sets and the range of the universe of discourse can be set according to actual needs and multiple experiments.

[0090] The oil pressure difference is divided into 5 fuzzy sets, with the universe of discourse set to [-30, 30]. When the oil pressure difference is below -15 kPa, the fuzzy control rule is negative (NB), and when the oil pressure difference is above 15 kPa, the fuzzy control rule is positive (PB). It should be noted that the universe of discourse is chosen as [-30, 30] to indicate that the control rule is adjusted only when the oil pressure difference is between -30 kPa and 30 kPa, thereby improving control accuracy (a large oil pressure difference uses a "large step" to improve control response time, while a small oil pressure difference uses a "small step" to improve control response accuracy). The fuzzy set membership functions are as follows: Figure 3As shown in the diagram. Negative large (NB) indicates that the actual oil pressure is approximately 15 kPa higher than the target oil pressure; negative small (NS) indicates that the actual oil pressure is approximately 5 kPa higher than the target oil pressure; zero (ZO) indicates that the actual oil pressure is close to the target oil pressure; positive small (PS) indicates that the actual oil pressure is approximately 5 kPa lower than the target oil pressure; and positive large (PB) indicates that the actual oil pressure is approximately 15 kPa lower than the target oil pressure.

[0091] The oil pressure differential change rate is also divided into 5 fuzzy sets, with the universe of discourse set to [-100, 100]. When the oil pressure differential change rate is below -60 kPa / s, the fuzzy control rule is negative (NB), and when the oil pressure differential change rate is above 60 kPa / s, the fuzzy control rule is positive (PB). The reason for choosing the universe of discourse as [-100, 100] is to indicate that the control rule is only adjusted when the oil pressure differential change rate is between -100 kPa / s and 100 kPa / s (the oil pressure differential change rate is not large), thereby improving the control accuracy (a "large step" is used for a large oil pressure differential change rate to improve the control response time, and a "small step" is used for a small oil pressure differential change rate to improve the control response accuracy). Among them, negative large (NB) indicates that the oil pressure difference change rate is about -60 kPa / s; negative small (NS) indicates that the oil pressure difference change rate is about -20 kPa / s; zero (ZO) indicates that the oil pressure difference change rate is about 0 kPa / s; positive small (PS) indicates that the oil pressure difference change rate is about 20 kPa / s; and positive large (PB) indicates that the oil pressure difference change rate is about 60 kPa / s.

[0092] The output of the fuzzy controller is the fuzzy control quantity, and its universe of discourse can be set to [0, 100], indicating that the final fuzzy control quantity is limited to the range of 0 to 100. Its membership function can be as follows: Figure 4 As shown.

[0093] When the target oil pressure is close to the actual oil pressure, the duty cycle is eventually stabilized at around ZO.

[0094] For example, the standard for designing fuzzy control rules is: "The greater the target oil pressure is higher than the actual oil pressure and the faster the oil pressure rises, the greater the increase in fuzzy control quantity"; "When the target oil pressure is close to the actual oil pressure and the oil pressure does not change much, the fuzzy control quantity remains basically unchanged"; "The greater the target oil pressure is lower than the actual oil pressure and the faster the oil pressure falls, the greater the decrease in fuzzy control quantity".

[0095] Accordingly, the following 25 fuzzy control rules can be adopted:

[0096] Rule 1: If the target oil pressure is much smaller than the actual oil pressure and the oil pressure drops rapidly, then greatly reduce the fuzzy control quantity;

[0097] Rule 2: If the target oil pressure is much smaller than the actual oil pressure and the oil pressure decreases slowly, then greatly reduce the fuzzy control quantity;

[0098] Rule 3: If the target oil pressure is much smaller than the actual oil pressure and the oil pressure remains basically unchanged, then greatly reduce the fuzzy control quantity;

[0099] Rule 4: If the target oil pressure is significantly lower than the actual oil pressure and the oil pressure rises slowly, then moderately reduce the fuzzy control quantity.

[0100] Rule 5: If the target oil pressure is significantly lower than the actual oil pressure and the oil pressure rises rapidly, then slightly reduce the fuzzy control quantity.

[0101] Rule 6: If the target oil pressure is slightly lower than the actual oil pressure and the oil pressure drops rapidly, then greatly reduce the fuzzy control quantity;

[0102] Rule 7: If the target oil pressure is slightly lower than the actual oil pressure and the oil pressure decreases slowly, then moderately reduce the fuzzy control quantity;

[0103] Rule 8: If the target oil pressure is slightly lower than the actual oil pressure and the oil pressure remains basically unchanged, then slightly reduce the fuzzy control quantity;

[0104] Rule 9: If the target oil pressure is slightly lower than the actual oil pressure and the oil pressure rises slowly, then the fuzzy control quantity is basically maintained.

[0105] Rule 10: If the target oil pressure is slightly lower than the actual oil pressure and the oil pressure rises rapidly, then slightly increase the fuzzy control value;

[0106] Rule 11: If the target oil pressure is basically equal to the actual oil pressure and the oil pressure drops rapidly, then the fuzzy control quantity is greatly reduced.

[0107] Rule 12: If the target oil pressure is basically equal to the actual oil pressure and the oil pressure decreases slowly, then slightly reduce the fuzzy control quantity;

[0108] Rule 13: If the target oil pressure is basically equal to the actual oil pressure and the oil pressure remains basically unchanged, then the fuzzy control quantity is basically maintained.

[0109] Rule 14: If the target oil pressure is basically equal to the actual oil pressure and the oil pressure rises slowly, then slightly increase the fuzzy control value.

[0110] Rule 15: If the target oil pressure is basically equal to the actual oil pressure and the oil pressure rises rapidly, then increase the fuzzy control quantity moderately.

[0111] Rule 16: If the target oil pressure is slightly higher than the actual oil pressure and the oil pressure drops rapidly, then reduce the fuzzy control quantity by a moderate amount.

[0112] Rule 17: If the target oil pressure is slightly higher than the actual oil pressure and the oil pressure decreases slowly, then the fuzzy control quantity is basically maintained.

[0113] Rule 18: If the target oil pressure is slightly higher than the actual oil pressure and the oil pressure remains basically unchanged, then slightly increase the fuzzy control value;

[0114] Rule 19: If the target oil pressure is slightly higher than the actual oil pressure and the oil pressure rises slowly, then increase the fuzzy control amount by a moderate amount.

[0115] Rule 20: If the target oil pressure is slightly higher than the actual oil pressure and the oil pressure rises rapidly, then increase the fuzzy control quantity by a moderate amount;

[0116] Rule 21: If the target oil pressure is much higher than the actual oil pressure and the oil pressure drops rapidly, then slightly reduce the fuzzy control value;

[0117] Rule 22: If the target oil pressure is much higher than the actual oil pressure and the oil pressure decreases slowly, then slightly increase the fuzzy control value;

[0118] Rule 23: If the target oil pressure is much higher than the actual oil pressure and the oil pressure remains basically unchanged, then increase the fuzzy control quantity in a moderate way.

[0119] Rule 24: If the target oil pressure is much higher than the actual oil pressure and the oil pressure rises slowly, then increase the fuzzy control quantity in a moderate way.

[0120] Rule 25: If the target oil pressure is much higher than the actual oil pressure and the oil pressure rises rapidly, then greatly increase the fuzzy control quantity.

[0121] At this point, the above fuzzy control rules can be organized into the following form: Figure 5 The fuzzy control rule table is shown.

[0122] After fuzzifying the currently detected oil pressure difference and the rate of change of oil pressure difference to the corresponding fuzzy sets, and determining the first fuzzy quantity and the second fuzzy quantity, the fuzzy control quantity can be obtained according to the above fuzzy control rule table.

[0123] Example 4

[0124] This invention describes a method for defuzzifying the obtained fuzzy control quantities to obtain accurate control quantities. There are many defuzzification methods, such as the most commonly used methods: maximum membership degree method, centroid method, and weighted average method.

[0125] For example, in this embodiment, the center of gravity method can be used for defuzzification. The fuzzy control output u corresponding to the oil pressure difference and the rate of change of oil pressure difference is calculated using the following formula. This fuzzy control output u is the fuzzy control correction coefficient r.fuzzy .

[0126]

[0127] In the formula, μc(ui) is the membership degree of ui, u i This represents the i-th fuzzy control input.

[0128] Due to the complex structure of the hydraulic system in the engine design, and the sampling of hydraulic oil for control, it has nonlinear, time-varying, and large delay characteristics. It is difficult to control the oil pressure using conventional PID control. The embodiments in this manual adopt a fuzzy control strategy to achieve closed-loop control, which can mimic human control to a certain extent. It does not require an accurate model of the controlled object. It can use the knowledge, thinking, learning and reasoning, association and decision-making processes of relevant experts to identify and model the data, and then control the system to achieve self-tuning, thereby further improving the control accuracy of the oil pressure.

[0129] In the above fuzzy control process, since oil pressure is a parameter in the fuzzy control strategy, it has a certain degree of flexibility. In practical applications, the oil pressure can be set as a variable value to adapt to the oil pressure requirements of the internal combustion engine under different operating conditions.

[0130] By having computers identify and model the knowledge, thinking, learning, reasoning, association, and decision-making processes of relevant experts, and then control and self-tuning them, the intelligent control of hydraulic pressure can be further upgraded. This can compensate for the deviation between the actual hydraulic pressure and the target hydraulic pressure, which is conducive to achieving accurate control of hydraulic pressure. Under various working conditions, the hydraulic pump solenoid valve can be controlled based on the actual hydraulic pressure, achieving the technical effect of the actual hydraulic pressure quickly and stably following the target hydraulic pressure.

[0131] Example 5

[0132] This invention provides a detailed method for updating the wheel-domain fuzzy set partitioning of the coefficient oil pressure difference change rate. The update is performed under steady-state engine conditions, and the following conditions must be met simultaneously for each target oil pressure to be updated:

[0133] 1. The engine speed is within the preset range, which is 850rpm to 6000rpm in this example, and the engine speed fluctuation range is ±20rpm;

[0134] 2. The engine load is within the preset range, which in this example is 150mgpl~3000mgpl, and the engine load fluctuation range is ±15mgpl;

[0135] 3. The engine coolant temperature is within the preset range, which in this example is -45℃ to 100℃, with a fluctuation range of ±2℃;

[0136] 4. The engine oil temperature is within the preset range, which in this example is -45℃ to 100℃, with a fluctuation range of ±2℃;

[0137] 5. The ignition angle efficiency is within the preset range, which is 0.5 to 1 in this example, and the ignition angle fluctuation range is within ±0.1.

[0138] 6. The engine requires that the fluctuation of the firing torque be within ±2%.

[0139] 7. The engine requires that the torque fluctuation in the air passage be within ±2%.

[0140] 8. Intake pressure fluctuation range is within ±3℃;

[0141] 9. Vehicle speed fluctuation range is within ±2km / h;

[0142] 10. No detonation occurred;

[0143] 11. The number of injections (CNT) remained unchanged;

[0144] 12. The activation status of the piston cooling nozzles remained unchanged;

[0145] 13. VVT phase difference phi VVTErr Within ±2° crankshaft angle;

[0146] 14. The octane rating of the oil product has not been updated for more than the preset time; in this example, it is set to 60 minutes.

[0147] 15. No coefficients among k1, k2, and k3 were updated in this driving cycle;

[0148] 16. If the coefficients k1, k2, and k3 have not been updated, the corresponding vehicle mileage S exceeds the preset mileage. In this example, the initial mileage is set to 100km, and the preset mileage S will be continuously updated and stored when the vehicle is powered off.

[0149] Only after all the above conditions are met simultaneously and the duration exceeds t1 (2s in this example) is the update of the fuzzy set of the oil pressure differential wheel domain allowed. Otherwise, the update is not allowed. The next time the fuzzy set of the oil pressure differential wheel domain is updated, it is necessary to re-determine whether the conditions are met, and only if they are met can the fuzzy set of the oil pressure differential wheel domain be updated again.

[0150] The same operating conditions are defined in this technology as follows: engine speed deviation within ±20 rpm, load deviation within ±15 mgpl, engine requested torque within ±2%, water temperature deviation within ±2℃, oil temperature deviation within ±2℃, no knocking, and octane rating deviation within ±0.05.

[0151] It should be noted that the current operating condition refers to the same average engine speed, average load, average ignition efficiency, average engine requested torque, average oil temperature deviation, average coolant temperature deviation, average knock angle deviation, average octane number deviation, and knock condition (i.e., whether knocking has occurred or not) under the current stable conditions.

[0152] Read the average actual oil pressure within time t2 (t2 is 3 seconds; if the time after entering the learning update is shorter than t2, no update is performed; if it exceeds t2, only information within time t2 is read).

[0153] 1) The difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value (±2kPa in this example). However, if the time during which the difference between the actual oil pressure and the target oil pressure exceeds the preset value (±2kPa) within time t2 is divided by t2 and exceeds 50%, it indicates that the actual oil pressure oscillates significantly near the target oil pressure. Therefore, the fuzzy set of the oil pressure difference change rate under the current working condition is adjusted to negative small (NS) and positive small (PS). The default value of negative small (NS) indicates that the oil pressure difference change rate is about -20kPa / s; positive small (PS) indicates that the oil pressure difference change rate is about 20kPa / s. The update method is as follows: NS(N+1) = NS(N) × 1.2, PS(N+1) = PS(N) × 1.2, where PS(N) is the PS at the Nth update, and PS(N+1) is the PS at the (N+1)th update. N = 0, 1, 2, 3. Specifically, when N = 0, PS(0) indicates that the oil pressure difference change rate is approximately 20 kPa / s, and NS(0) indicates that the oil pressure difference change rate is approximately -20 kPa / s. N increases by 1 with each update. Assuming that the current PS(N) indicates that the oil pressure difference change rate is approximately 20 kPa / s, then PS(N+1) indicates that the oil pressure difference change rate is approximately 20 kPa / s * 1.2 = 24 kPa / s; assuming that the current NS(N) indicates that the oil pressure difference change rate is approximately -20 kPa / s, then NS(N+1) indicates that the oil pressure difference change rate is approximately -20 kPa / s * 1.2 = -24 kPa / s.

[0154] 2) The difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value (±2kPa in this example). However, if the time during which the difference between the actual oil pressure and the target oil pressure exceeds the preset value (±2kPa) within time t2 is divided by t2 and exceeds 10%, it indicates that the actual oil pressure oscillates significantly near the target oil pressure. Therefore, the negative small (NS) and positive small (PS) values ​​of the oil pressure difference change rate under the current working condition are adjusted. The update method is as follows: NS(N+1) = NS(N) × 1.1, PS(N+1) = PS(N) × 1.1. N is incremented by 1 each time it is updated. Assuming that the current PS(N) represents an oil pressure difference change rate of about 20 kPa / s, then PS(N+1) represents an oil pressure difference change rate of about 20 kPa / s * 1.1 = 22 kPa / s. Assuming that the current NS(N) represents an oil pressure difference change rate of about -20 kPa / s, then NS(N+1) represents an oil pressure difference change rate of about -20 kPa / s * 1.1 = -22 kPa / s.

[0155] 3) The difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value (±2kPa in this example). However, the time during which the difference between the actual oil pressure and the target oil pressure exceeds the preset value (±2kPa) within time t2, divided by t2, is greater than 0% but not more than 10%. This indicates that the actual oil pressure oscillates significantly near the target oil pressure. Therefore, the negative small (NS) and positive small (PS) values ​​of the oil pressure difference change rate under the current working condition are adjusted. The update method is as follows: NS(N+1) = NS(N) × 1.05, PS(N+1) = PS(N) × 1.05. N increases by 1 with each update. Assuming that the current PS(N) represents an oil pressure difference change rate of about 20 kPa / s, then PS(N+1) represents an oil pressure difference change rate of about 20 kPa / s * 1.05 = 21 kPa / s. Assuming that the current NS(N) represents an oil pressure difference change rate of about -20 kPa / s, then NS(N+1) represents an oil pressure difference change rate of about -20 kPa / s * 1.05 = -21 kPa / s.

[0156] 4) The difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value (±2kPa in this example), and the difference between the actual oil pressure and the target oil pressure also does not exceed the preset value (±2kPa) within time t2. This indicates that the actual oil pressure control is accurate, and the number of consecutive times that this condition is met (CNT) is recorded (if any of the previous 4 conditions are met, the count is reset to zero and the accumulation starts again).

[0157] 4.1) If CNT is less than the preset value (10 in this example), then update NS(N+1) = NS(N) and PS(N+1) = PS(N) for the current operating condition.

[0158] 4.2) If CNT is less than the preset value (10 in this example), then: NS(N+1) = NS(N) × 0.98, PS(N+1) = PS(N) × 0.98. That is, if high control accuracy is achieved over a long period (multiple learning iterations), reducing the filter time constant can improve the hydraulic pressure control response speed. Specifically, if the first three situations mentioned above occur after this update (inaccurate hydraulic pressure control fluctuations), CNT will also be reset to zero, and updated to NS(N+1) = NS(N), PS(N+1) = PS(N).

[0159] The learning coefficients will not be executed in the current driving cycle after they are updated. They will be saved after the vehicle is powered off and the updated wheel domain fuzzy set will be executed at the start of the next driving cycle.

[0160] It should be understood that those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A closed-loop control method for engine oil pressure, characterized in that, The method includes: The oil pressure difference is corrected by introducing coefficients related to engine speed, the maximum value of the phase difference between the target VVT and the actual VVT in the intake and exhaust VVT, the state of the piston cooling nozzle, and the oil temperature. The oil pressure difference is the difference between the target oil pressure and the actual oil pressure. The oil pressure difference change rate is corrected by introducing coefficients related to engine retraction strength coefficient and oil octane number coefficient. The engine retraction strength coefficient is the ratio of the current knock-delayed ignition angle to the maximum allowable knock-delayed ignition angle. Construct a fuzzy controller and set fuzzy control rules. Input the corrected oil pressure difference and oil pressure difference change rate into the fuzzy controller. The fuzzy controller outputs the control duty cycle of the oil pump. The oil pressure follows the control of the duty cycle, which drives the oil pump to operate. Oil pressure difference before correction Oil pressure differential change rate The calculation method is as follows: in, The time interval of the sampling period. for The value of the previous sampling period, the first sampled value Take 0, for The value of the previous sampling period, the first sampled value Take 0, The time constant is used to calculate the rate of change.

2. The closed-loop control method for oil pressure according to claim 1, characterized in that, The specific methods for correcting the oil pressure differential and the rate of change of oil pressure differential in this method include: Will As the corrected oil pressure difference ; Will As the corrected rate of change of oil pressure difference ; in, The difference between the target oil pressure and the actual oil pressure. Engine speed, It is the maximum value of the phase difference between the target VVT and the actual VVT in both intake and exhaust VVT. This refers to the state of the piston cooling nozzle. For engine oil temperature, This is the engine's retraction angle strength coefficient. The ignition angle is delayed due to the current detonation. The maximum permissible ignition angle delayed for detonation. This refers to the octane number coefficient of the oil product; The oil pressure difference before correction. This represents the rate of change in oil pressure differential before correction.

3. The closed-loop control method for oil pressure according to claim 2, characterized in that, This method also includes a method for calibrating the parameters: The calibration method is as follows: by setting different target oil pressures, when the piston cooling nozzle is not activated, the oil temperature is 90℃, no knocking occurs, and the oil octane number coefficient is 0, under any engine speed and at any maximum phase difference between the target VVT and the actual VVT, the oil pressure control accuracy can be guaranteed to be within ±2kPa through fuzzy control. Based on this condition, the calibration value is obtained. The calibration method is as follows: by setting different target oil pressures, under the conditions of engine speed of 3000rpm, maximum phase difference between target VVT and actual VVT equal to ±2° crankshaft angle, no knocking, and oil octane coefficient of 0, under any piston cooling nozzle condition and any oil temperature, the oil pressure control accuracy can be guaranteed to be within ±2kPa through fuzzy control. Based on this condition, the calibration value is obtained. The calibration method is as follows: by setting different target oil pressures, when the engine speed is 3000 rpm, the maximum phase difference between the target VVT and the actual VVT is equal to ±2° crankshaft angle, the piston cooling nozzle is not activated, and the oil temperature is 90℃, under any engine back angle strength coefficient and any oil octane number coefficient, the oil pressure control accuracy can be guaranteed to be within ±2kPa through fuzzy control. Based on this condition, the calibration value is obtained.

4. The closed-loop control method for oil pressure according to claim 1, characterized in that, The methods for constructing a fuzzy controller in this method include: Establish membership functions, and adopt triangular or trapezoidal membership functions for fuzzy control processes; The oil pressure difference and the rate of change of oil pressure difference are fuzzified to obtain the first fuzzy quantity and the second fuzzy quantity; the fuzzy control quantity is obtained based on the first fuzzy quantity, the second fuzzy quantity and the preset fuzzy control rules. The fuzzy control quantity is defuzzified to obtain the fuzzy control duty cycle. .

5. The closed-loop control method for oil pressure according to claim 4, characterized in that, The methods for establishing membership functions in this method include: The oil pressure difference is divided into 5 fuzzy sets with the universe of discourse set to [-30, 30]. When the oil pressure difference is below -15 kPa, the fuzzy control rule belongs to negative large NB, and when the oil pressure difference is above 15 kPa, the fuzzy control rule belongs to positive large PB. Negative large NB indicates that the actual oil pressure is 15 kPa greater than the target oil pressure; negative small NS indicates that the actual oil pressure is 5 kPa greater than the target oil pressure; zero ZO indicates that the actual oil pressure is approximately equal to the target oil pressure; positive small PS indicates that the actual oil pressure is 5 kPa less than the target oil pressure; positive large PB indicates that the actual oil pressure is 15 kPa less than the target oil pressure. Based on this, the membership function of the oil pressure difference is obtained. The oil pressure differential change rate is also divided into 5 fuzzy sets, with the universe of discourse set to [-100, 100]. When the oil pressure differential change rate is below -60 kPa / s, the fuzzy control rule belongs to negative large NB; when the oil pressure differential change rate is above 60 kPa / s, the fuzzy control rule belongs to positive large PB. Negative large NB indicates that the oil pressure differential change rate is -60 kPa / s; negative small NS indicates that the oil pressure differential change rate is -20 kPa / s; zero ZO indicates that the oil pressure differential change rate is 0 kPa / s; positive small PS indicates that the oil pressure differential change rate is 20 kPa / s; positive large PB indicates that the oil pressure differential change rate is 60 kPa / s. Based on this, the membership function of the oil pressure differential change rate is obtained. The output of the fuzzy controller is a fuzzy control quantity, and the universe of discourse is set to [0, 100]. This means that the final fuzzy control quantity is limited to the range of 0 to 100. When the target oil pressure is close to the actual oil pressure, the final control duty cycle stabilizes near Z0, and the membership function of the fuzzy control quantity output is obtained.

6. The closed-loop control method for oil pressure according to claim 5, characterized in that, The method for setting fuzzy control rules in this approach includes: The preset fuzzy control rules are organized into a fuzzy control rule table and stored in advance. The fuzzy control rule table stores the fuzzy control output results when the oil pressure difference is {NB, NS, ZO, PS, PB} and the oil pressure difference change rate is {NB, NS, ZO, PS, PB}. After fuzzifying the currently detected oil pressure difference and the rate of change of oil pressure difference to the corresponding fuzzy sets, the first fuzzy quantity and the second fuzzy quantity are determined, and the fuzzy control quantity is obtained according to the fuzzy control rule table.

7. The closed-loop control method for oil pressure according to claim 5, characterized in that, The methods for deblurring in this method include: The centroid method is used for defuzzification, and the fuzzy control output corresponding to the oil pressure difference and the rate of change of oil pressure difference is calculated using the following formula. u The fuzzy control output quantity u This is the fuzzy control correction coefficient. : in, for membership degree This represents the i-th fuzzy control output.

8. The closed-loop control method for oil pressure according to claim 5, characterized in that, This method also includes an update method that uses a fuzzy set partitioning of the universe of discourse for the coefficient oil pressure difference change rate. When the set update conditions are met, the following update is performed: If all update conditions are met and the duration exceeds t1, then updating the fuzzy set of the oil pressure difference universe is allowed; otherwise, updating is not allowed. Read the average actual oil pressure within time t2; 1) If the difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value, but the time during which the difference between the actual oil pressure and the target oil pressure exceeds the preset value divided by t2 exceeds 50%, then the negative small NS and positive small PS of the domain of the oil pressure difference change rate under the current working condition are adjusted. The default value is that the negative small NS indicates that the oil pressure difference change rate is -20 kPa / s; the positive small PS indicates that the oil pressure difference change rate is 20 kPa / s. The update method is as follows: , , This is the PS at the Nth update. This represents the PS at the (N+1)th update, where N = 0, 1, 2, 3, ..., and N = 0. This indicates that the rate of change of oil pressure differential is 20 kPa / s. This indicates that the oil pressure differential change rate is -20 kPa / s; N increases by 1 with each update. 2) If the difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value, but the time during which the difference between the actual oil pressure and the target oil pressure exceeds the preset value within time t2 is divided by t2 and exceeds 10%, then the negative small NS and positive small PS of the domain of the oil pressure difference change rate under the current working condition will be adjusted. The update method is as follows: , Each update increments N by 1; 3) If the difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value, but the time during which the difference between the actual oil pressure and the target oil pressure exceeds the preset value within time t2 is greater than 0% but not more than 10%, then the negative small NS and positive small PS of the domain of the oil pressure difference change rate under the current working condition will be adjusted. The update method is as follows: , Each update increments N by 1; 4) The difference between the average actual oil pressure and the target oil pressure within time t2 does not exceed the preset value, and the difference between the actual oil pressure and the target oil pressure does not exceed the preset value within time t2. Record the number of times this condition is met consecutively (CNT). 4.1) If CNT is less than the preset value at this time, then update the current operating condition. , ; 4.2) If CNT is greater than the preset value at this time, then: , ； If an error occurs after the update, clear CNT and update it to... , ; The updated driving cycle will not be executed. It will be saved after the vehicle is powered off and the updated universe fuzzy set will be executed after the next driving cycle begins.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the oil pressure closed-loop control method as described in any one of claims 1 to 8.

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