An engine fuel injection curve optimization method, device and computer storage medium

Abstract

The present invention discloses an optimization method for an engine fuel injection curve, comprising the following steps: determining the basic conditions for engine optimization calculation, with the object of optimization being the shape of the engine fuel injection curve; establishing a fuel nozzle curve using a CAD spline curve; first setting a rough selection range through curve control points, and obtaining the corresponding engine diesel injection curve according to parameter sample points, and then redefining its detailed optimization range based on the parameters corresponding to the engine diesel injection curve with the maximum engine power as the initial optimization range reference point; adopting a population optimization method to obtain the best individual with the goal of maximizing the engine power corresponding to the population individuals, and outputting the best engine fuel injection curve using the CAD method based on the best individual. The present invention also discloses a corresponding optimization device and a computer storage medium. The present invention improves the optimization efficiency while accurately and reasonably obtaining the injection curve shape, and improves the output power of the engine.

Description

Technical Field

[0001] The present invention relates to a method for optimizing an engine fuel injection curve, and particularly to a method, device and computer storage medium for optimizing an engine fuel injection curve. Background Art

[0002] The fuel injection curve is a curve formed by the duration of each fuel injection of an injector calculated by an electronic control unit according to various sensor signals under different operating conditions of the engine. It can effectively ensure the normal operation of the engine. A suitable fuel injection curve shape can effectively improve fuel economy and increase the output power of the engine.

[0003] Currently, the fuel injection curve is mainly obtained through experiments or selected based on the experience of designers. The shape of the curve has a non-linear impact on the performance of the engine, which makes it impossible to obtain the best curve through experience or experiments. Summary of the Invention

[0004] Aiming at the defects of the above-mentioned prior art, the present invention provides a method for optimizing an engine fuel injection curve. The fuel injection curve shape is expressed by a spline curve, and the best curve shape is obtained by continuously optimizing the control point parameters on the spline curve to improve the output power of the engine and ensure the optimization efficiency. The present invention also provides an apparatus for optimizing an engine fuel injection curve and a computer storage medium.

[0005] The technical solution of the present invention is as follows: A method for optimizing an engine fuel injection curve includes the following steps:

[0006] Step 1: Determine the basic conditions for engine optimization calculation. The object of optimization calculation is the control point parameters of the engine fuel injection curve, and the control point parameters are used to control the shape of the engine fuel injection curve;

[0007] Step 2: Based on the initial optimization range of the control point parameters of the set engine fuel injection curve, select sample points of the control point parameters, and use the CAD spline curve method to obtain the corresponding engine diesel injection curve. The engine diesel injection curve with the maximum engine power is used as the detailed optimization reference point by its corresponding control point parameters;

[0008] Step 3: Redefine the detailed optimization range of the parameters based on the detailed optimization reference point of the control point parameters;

[0009] Step 4: Based on the detailed optimization range of the control point parameters, use the population optimization method to obtain the best individual with the goal of maximizing the engine power corresponding to the population individuals. Based on the best individual, use the CAD method to output the best engine fuel injection curve, and the population individuals are composed of the control point parameters of the engine fuel injection curve.

[0010] Furthermore, the size of the control point parameter that controls the curve deformation represents the coordinate value in the vertical direction in the two-dimensional rectangular coordinate system, and the abscissa of the control point remains unchanged during the optimization process.

[0011] Furthermore, step 2 specifically includes:

[0012] 201. Determine the initial optimization range of the control point parameters of the engine fuel injection curve;

[0013] 202. Generate several groups of parameter combinations belonging to the initial optimization range to form a sample set;

[0014] 203. Set the boundary conditions and initial simulation parameters;

[0015] 204. Set the initial crankshaft angle, final crankshaft angle, and engine speed during simulation;

[0016] 205. Set the iterative time step parameter;

[0017] 206. Through iterative calculation using the simulation software ANSYS-FORTE, output the engine power corresponding to the engine diesel injection curve of each sample in the sample set;

[0018] 207. Select the parameter point on the engine diesel injection curve with the maximum engine power value as the detailed optimization reference point of the control point parameter.

[0019] Furthermore, in step 202, the optimal Latin hypercube algorithm is used to generate parameter combinations.

[0020] Furthermore, during the iterative calculation in step 206, the RNG k-ε turbulence model and the KH-RT method are used.

[0021] Furthermore, step 4 specifically includes:

[0022] 401. Initialize the population and iterative parameters;

[0023] 402. Use the CAD spline curve method to draw the fuel injection spline curve of the population individuals, and then input it into the simulation software;

[0024] 403. Through simulation iterative calculation, output the engine power corresponding to each individual in the population;

[0025] 404. Group the population based on the engine power obtained in step 403 to form several sub-populations;

[0026] 405. Update the individual positions of the sub-populations based on the inertia weight and update the inertia weight based on the population iteration steps until the maximum number of update iteration steps of the sub-populations is reached;

[0027] 406. A new population is formed by the updated sub-populations, and steps 404, 405, and 406 are repeated to iteratively update the population until the population iteration step reaches the maximum.

[0028] 407. Based on the individual with the maximum engine power in the optimized population, the best engine fuel injection curve is output using the CAD spline curve method.

[0029] Further, the formula for updating the position of the sub-population individuals based on the inertia weight in step 405 is as follows:

[0030] ,

[0031] where, is the position of the i-th individual in the k-th population, s is the sub-population update iteration step, is the inertia weight, is a random number between 0 and 1, is the individual with the maximum power in the k-th sub-population, is the individual with the minimum power in the k-th sub-population.

[0032] Further, the update method of the inertia weight in step 405 is:

[0033] ,

[0034] where, is the set weight coefficient, S max is the maximum value of the population iteration step.

[0035] The present invention also provides an engine fuel injection curve optimization device, including:

[0036] A basic condition module, used to determine the basic conditions for the engine optimization calculation. The object of the optimization calculation is the control point parameters of the engine fuel injection curve, and the control point parameters are used to control the shape of the engine fuel injection curve;

[0037] An optimization reference point determination module, used to select sample points of the control point parameters based on the initial optimization range of the set control point parameters of the engine fuel injection curve, obtain the corresponding engine diesel injection curve using the CAD spline curve method, and use the control point parameters corresponding to the engine diesel injection curve with the maximum engine power as the detailed optimization reference point;

[0038] A detailed optimization range determination module, used to redefine the detailed optimization range of the parameters based on the detailed optimization reference point of the control point parameters;

[0039] An iterative optimization calculation module is used to obtain the best individual based on the refined optimization range of the control point parameters by using a population optimization method with the goal of maximizing the engine power corresponding to the individuals in the population. Based on the best individual, a CAD spline curve method is used to output the best engine fuel injection curve, and the individuals in the population are composed of the control point parameters of the engine fuel injection curve.

[0040] The present invention also provides a computer storage medium with a computer program stored thereon. When the computer program is executed by a processor, the above-mentioned engine fuel injection curve optimization method is implemented.

[0041] The advantages of the technical solution provided by the present invention are as follows:

[0042] The present invention constructs a fuel injection curve through a spline curve, quickly modifies the curve shape through several control points on the curve, uses the optimal Latin hypercube algorithm for initial optimization to quickly find the spatial position with the maximum engine power in the design space, and finally uses a global optimization algorithm to perform a detailed search around the sample point corresponding to the maximum power to achieve detailed optimization calculation. While improving the optimization efficiency, a reliable injection curve shape is accurately and reasonably obtained, avoiding blindly selecting the fuel injection curve, and effectively improving the output power of the engine. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic flow chart of the engine fuel injection curve optimization method according to an embodiment of the present invention.

[0044] Figure 2 It is the shape of the fuel injection curve generated by using the sample point parameters with j = 1 in the table. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] The present invention will be further described below in conjunction with embodiments. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. After reading this description, various equivalent modifications of this description by those skilled in the art all fall within the scope defined by the appended claims of this application.

[0046] Please refer to Figure 1 As shown, the engine fuel injection curve optimization method of this embodiment includes the following steps:

[0047] Step 1: Determine the basic conditions for the engine optimization calculation and the object of the optimization calculation.

[0048] This step specifically includes:

[0049] 101. Establish a three-dimensional engine geometric model. First, a piston top geometry needs to be established, and then relevant physical parameters of the engine are set, including the bore diameter, stroke, clearance width between the piston and the cylinder wall, and the distance between the piston top and the cylinder head bottom when the piston moves to the top dead center.

[0050] 102. Mesh the three-dimensional engine geometric model. Use the sector mesh generator in the ANSYS-FORTE software to mesh the model, and the number of meshes in the radial and axial directions needs to be set.

[0051] 103. Set the specific calculation method for the simulation. The calculation methods include the RNG k-ε turbulence model and the KH-RT method.

[0052] 104. Set the geometric parameters of the engine fuel nozzle. The geometric parameters include the nozzle position and nozzle diameter; and set the injection parameters of the engine fuel nozzle. The injection parameters include the starting angle, duration, and total injection mass.

[0053] Step 2. Based on the initial optimization range of the parameter control points of the set engine fuel injection curve, select a specified number of sample points of the parameter control points, use the CAD spline curve method to obtain the corresponding engine diesel injection curve, and use the control point parameters corresponding to the engine diesel injection curve with the maximum engine power as the detailed optimization reference points.

[0054] This step specifically includes:

[0055] 201. There are five parameters for the control points of the engine fuel injection curve. Different shapes of fuel injection curves can be obtained by modifying the values of these five parameters. These five parameters are named a, b, c, d, and e respectively. The ranges of the five parameters are defined as: 5 ≤ a ≤ 9, 6 ≤ b ≤ 11, 7 ≤ c ≤ 12, 7 ≤ d ≤ 12, 3 ≤ e ≤ 9. The magnitudes of the control point parameters represent the coordinate values in the vertical direction in the two-dimensional rectangular coordinate system, and the abscissa remains fixed during the optimization process. The area enclosed by the generated fuel injection curve and the horizontal axis represents the total mass of the fuel injection, and the amount of fuel injection at different times can be obtained through calculation using the simulation software ANSYS-FORTE.

[0056] 202. Use the optimal Latin hypercube algorithm to generate 20 groups of samples to form a set U. The set U = {a j , b j , c j , d j , e j}, where 1 ≤ j ≤ 20. The following table lists some of the 20 groups of samples.

[0057]

[0058] Use the CAD method to draw the fuel injection spline curves corresponding to 20 sample points, passing through 1, a j , b j , c j , d j , e j and 2 to generate the diesel curve. Among them, 1 represents the starting point of the curve, 2 represents the ending point of the curve, and the positions of 1 and 2 always remain unchanged. Input these 20 spline curves into the simulation software respectively as the engine diesel injection curves. Among them Figure 2 is the fuel injection curve constructed when j = 1 in the table.

[0059] 203. Set the boundary conditions and initial simulation parameters. The setting of boundary conditions includes the parameters of the engine piston, engine cylinder head, and engine cylinder liner. The initial simulation parameters include parameters such as the temperature and pressure in the engine cylinder.

[0060] 204. Set the corresponding simulation control parameters, including the initial crankshaft angle, final crankshaft angle, and engine speed during simulation.

[0061] 205. Iterative setting, including the iterative time step parameter.

[0062] 206. Use the simulation software ANSYS - FORTE for iterative calculation and output the engine power P corresponding to 20 engine diesel injection curves j .

[0063] 207. Compare the 20 obtained engine powers, and select the control point parameters on the engine diesel injection curve with the maximum engine power as the subsequent detailed optimization reference point. In this embodiment, through calculation and comparison, it is found that: a corresponding to the maximum power j , b j , c j , d j , e j are respectively: 7.53, 10.47, 9.37, 7.79, 8.37 (i.e., the sample points when j = 18 in the table). Subsequently, further optimization is carried out by expanding this point into the detailed optimization range of the control point parameters.

[0064] Step 3. Redefine the variable range of detailed optimization based on the reference point obtained in Step 2.

[0065] In this step, based on the reference points obtained in Step 207, namely 7.53, 10.47, 9.37, 7.79, 8.37, the ranges of a, b, c, d, and e are redefined according to this result. Specifically, the ranges of a, b, c, d, and e are defined as 7 ≤ a ≤ 8, 10 ≤ b ≤ 11, 9 ≤ c ≤ 10, 7 ≤ d ≤ 8, and 8 ≤ e ≤ 9. Step 4: Based on the ranges in Step 3, using the population optimization method, with the goal of maximizing the engine power corresponding to the population individuals, the best individual is obtained, and based on the best individual, the best engine fuel injection curve is output using the CAD spline curve method.

[0066] This step specifically includes the following parts:

[0067] 401. Initialize the population parameters, with the maximum number of iterations being T max , the weight parameters ω1, ω2. Generate a group of populations Y = {y1, y2, y3,..., y 6n}, which contains 6n individuals. Among them, the i-th individual y i is {z i1 , z i2 , z i3 , z i4 , z i5}, where z i1 , z i2 , z i3 , z i4 , z i5 represents the ordinate values of the control points of the diesel curve, and let the iteration count t = 1.

[0068] 402. Use the CAD spline curve method to draw the fuel injection spline curve corresponding to the individual y i , which passes through 1, z i1 , z i2 , z i3 , z i4 , z i5 and 2 to generate the diesel curve. Among them, 1 represents the starting point of the curve, 2 represents the end point of the curve, and the positions of 1 and 2 always remain unchanged. Then, the fuel injection curve is input into the simulation software in sequence.

[0069] 403. Based on the basic conditions for engine optimization calculation determined in Step 1 and the boundary conditions, initial simulation parameters, simulation control parameters, and iteration time step parameters determined in Steps 203 to 205, perform iterative calculations and output the engine power P i corresponding to the i-th individual in the population Y, where i ranges from 1 to 6n.

[0070] 404. According to the power P iSort the 6n individuals in descending order, and then divide the population into 6 subpopulations. Assign the sorted individuals to the 6 subpopulations in sequence. The k-th population Q k ={Q k1 , Q k2 , Q k3 , ...,Q kn}, where 1 ≤ k ≤ 6. Let s = 1, and the maximum number of iterations be S max .

[0071] 405a. For each subpopulation Q k Update the individuals, and the individual position update method is as follows:

[0072] ,

[0073] where is the position of the i-th individual in the k-th population, s is the subpopulation update iteration step, is the inertia weight, is a random number between 0 and 1, is the individual with the maximum power in the k-th subpopulation, is the individual with the minimum power in the k-th subpopulation.

[0074] 405b. The update method of the inertia weight is as follows:

[0075] ,

[0076] where s is the subpopulation update iteration step, and S max is the maximum value of the population iteration step.

[0077] 405c. If the power of the updated individual is greater than the original one, replace the original individual with the smallest power with the new individual. Otherwise, randomly generate a new individual to replace the original individual with the smallest power.

[0078] 405d. Judge whether s = S max holds. If it holds, execute step 406. Otherwise, let s = s + 1, return to step 405a to continue the iterative calculation, and update these 6 subpopulations.

[0079] 406. Combine the 6 subpopulations obtained in step 405d into a new set YY, and judge whether t = T max holds. If it holds, execute step 407. Otherwise, let t = t + 1, and return to step 404 for iterative calculation.

[0080] 407. Output the optimal engine fuel injection curve using the CAD spline curve method for the individual with the maximum engine power in the population optimized based on the population.

[0081] The engine fuel injection curve optimization device of the embodiment includes modules:

[0082] The basic condition module is used to determine the basic conditions for engine optimization calculation. The object of optimization calculation is the control point parameters of the engine fuel injection curve, and the control point parameters are used to control the shape of the engine fuel injection curve;

[0083] The optimization reference point determination module is used to select sample points of the control point parameters based on the initial optimization range of the control point parameters of the set engine fuel injection curve, obtain the corresponding engine diesel injection curve by using the CAD spline curve method, and use the control point parameters corresponding to the engine diesel injection curve with the maximum engine power as the detailed optimization reference point;

[0084] The detailed optimization range determination module is used to redefine the detailed optimization range of the parameters based on the detailed optimization reference point of the control point parameters;

[0085] The iterative optimization calculation module is used to adopt the population optimization method based on the detailed optimization range of the control point parameters, obtain the best individual with the goal of maximizing the engine power corresponding to the population individuals, and output the best engine fuel injection curve by using the CAD spline curve method based on the best individual. The population individuals are composed of the control point parameters of the engine fuel injection curve.

[0086] The above-mentioned various modules cooperate to implement the aforementioned engine fuel injection curve optimization method.

[0087] It should be noted that the specific method of the above embodiment can form a computer program product. Therefore, the computer program product implemented by this application can be stored on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.). In addition, this application can be implemented in a way that combines hardware, software, or hardware and software, or constitutes a computer device that includes at least one processor and a memory. The memory stores the computer program for implementing the above process steps, and the processor is used to execute the computer program on the memory to form the method steps of the above embodiment.

Claims

1. An engine fuel injection curve optimization method, characterized in that, It includes the following steps: Step 1: Determine the basic conditions for engine optimization calculation. The object of optimization calculation is the control point parameters of the engine fuel injection curve. The control point parameters are used to control the shape of the engine fuel injection curve. The magnitude of the control point parameters that control the curve deformation represents the coordinate value in the vertical direction in the two-dimensional rectangular coordinate system. During the optimization process, the abscissa of the control points remains unchanged; Step 2: Based on the initially set optimization range of the control point parameters of the engine fuel injection curve, select sample points of the control point parameters, and use the CAD spline curve method to obtain the corresponding engine diesel injection curve. Take the control point parameters corresponding to the engine diesel injection curve with the maximum engine power as the detailed optimization reference point; Step 3: Redefine the parameter detailed optimization range based on the detailed optimization reference point of the control point parameters; Step 4: Based on the detailed optimization range of the control point parameters, use the population optimization method to obtain the best individual with the goal of maximizing the engine power corresponding to the population individuals. Based on the best individual, use the CAD spline curve method to output the best engine fuel injection curve. The population individuals are composed of the control point parameters of the engine fuel injection curve, specifically including:

401. Initialize the population and iteration parameters; 402. Use the CAD spline curve method to draw the fuel injection spline curves of the population individuals, and then input them into the simulation software; 403. Perform simulation iterative calculations to output the engine power corresponding to each individual in the population; 404. Group the population based on the engine power obtained in step 403 to form several sub-populations; 405. Update the positions of the sub-population individuals based on the inertia weight and update the inertia weight based on the population iteration steps until the sub-population update iteration steps reach the maximum; 406. Use the updated sub-populations to form a new population, and repeat steps 404, 405, and 406 to iteratively update the population until the population iteration steps reach the maximum; 407. Based on the individual with the maximum engine power in the population after population optimization, use the CAD spline curve method to output the best engine fuel injection curve, The formula for updating the positions of the sub-population individuals based on the inertia weight in step 405 is as follows: ， wherein, is the position of the i-th individual in the k-th population, s is the number of steps for updating and iterating the sub-population, is the inertia weight, is a random number between 0 and 1, is the individual with the maximum power in the k-th sub-population, is the individual with the minimum power in the k-th sub-population, The update method of the inertia weight is: ， Among them, is the set weight coefficient, S max is the maximum value of the population iteration step number.

2. The method for optimizing the engine fuel injection curve according to claim 1, wherein Step 2 specifically includes:

201. Determine the initially set optimization range of the control point parameters of the engine fuel injection curve; 202. Generate several groups of parameter combinations belonging to the initially set optimization range to form a sample set; 203. Set the boundary conditions and initial simulation parameters; 204. Set the initial crankshaft angle, final crankshaft angle, and engine speed during simulation; 205. Set the iteration time step parameter; 206. Through iterative calculations using the simulation software ANSYS-FORTE, output the engine power corresponding to the engine diesel injection curves of each sample in the sample set; 207. Select the parameter points on the engine diesel injection curve with the maximum engine power value as the detailed optimization reference point of the control point parameters.

3. The method for optimizing the engine fuel injection curve according to claim 2, characterized in that The optimal Latin hypercube algorithm is used to generate parameter combinations in step 202.

4. The method for optimizing the engine fuel injection curve according to claim 2, characterized in that The RNG k-ε turbulence model and the KH-RT method are used for the iterative calculations in step 206.

5. An engine fuel injection curve optimization device, characterized in that, It includes: A basic condition module, which is used to determine the basic conditions for the optimization calculation of the engine. The object of the optimization calculation is the control point parameters of the engine fuel injection curve, and the control point parameters are used to control the shape of the engine fuel injection curve; An optimized reference point determination module, which is used to select sample points of the control point parameters based on the initial optimization range of the control point parameters of the set engine fuel injection curve, obtain the corresponding engine diesel injection curve by using the CAD spline curve method, and use the control point parameters corresponding to the engine diesel injection curve with the maximum engine power as the detailed optimization reference point; A detailed optimization range determination module, which is used to redefine the detailed optimization range of the parameters based on the detailed optimization reference point of the control point parameters; An iterative optimization calculation module, which is used to obtain the best individual based on the detailed optimization range of the control point parameters by using the population optimization method with the goal of maximizing the engine power corresponding to the population individuals, and output the best engine fuel injection curve by using the CAD spline curve method based on the best individual. The population individuals are composed of the control point parameters of the engine fuel injection curve.

6. A computer storage medium, on which a computer program is stored, characterized in that, When the computer program is executed by a processor, it implements the engine fuel injection curve optimization method according to any one of claims 1 to 4.

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