Ackerman rate simulation method, system, equipment and medium

Abstract

The invention discloses an Ackerman rate simulation method, system, device and medium, a CATIA software simulation module is used for building a variable wheelbase and wheelbase model, through addition of auxiliary parts and setting of constraint pairs, the Ackerman rate value of a vehicle under the variable wheelbase and wheelbase condition is simulated, whether the Ackerman rate value is within a standard range is judged, and if yes, the Ackerman rate value is judged to be within the standard range. And whether key parameters and hard points of an early-stage whole vehicle are reasonable or not is evaluated. The technology overcomes the defect that the Ackerman rate of the vehicle can be simulated only through a fixed wheelbase and a fixed wheel track each time in the prior art, for example, a model needs to be built for multiple times when the wheelbase and the wheel track need to be changed, the model needs to be re-built once when one parameter is changed, repeated work is repeatedly carried out, the blank of construction of a platform vehicle type wheelbase and wheel track variable simulation model is filled, and the platform vehicle type variable wheelbase and wheel track variable simulation model is established. Through the model, the reasonability of Ackerman rate values of vehicles with different wheel bases and wheel tracks can be quickly analyzed, and the hard spot design efficiency of a chassis platform in the early stage is greatly improved.

Description

Technical Field

[0001] The present application relates to the technical field of chassis design, and in particular to an Ackerman rate simulation method, system, device and medium. Background Art

[0002] In the design process of light vehicle chassis hard points, the Ackerman rate is an important performance parameter indicator. This indicator is required to be within a reasonable target range. If it is too low, although the high-speed cornering handling ability is strong, it will affect the pure rolling of the tire and cause uneven tire wear. If it is too high, the outer wheel turning angle will be much smaller than the inner wheel turning angle, which will cause understeer when cornering, and the handling stability will deteriorate when cornering at high speed, resulting in poor cornering ability.

[0003] Since the Ackerman rate is closely related to the track and wheelbase of the entire vehicle, multiple models with different wheelbases will be planned at the same time when the vehicle platform is designed. At this time, there is no mule car to conduct K&C test measurements, and it can only be obtained by modeling and simulating the data models of each different wheelbase one by one, which is a heavy workload.

[0004] Taking the previous McPherson suspension, rear leaf spring and rear axle assembly as an example, if the platform planning involves different wheelbases and track widths, the existing solution can only perform hard point simulation on the Ackerman rate of vehicles with different track widths and wheelbases and solve them one by one. If it is not appropriate, it is necessary to change the hard point design again, and build a simulation model for each model again to analyze whether the Ackerman rate is within the recommended standard range. This process is repeated until it is qualified, which is time-consuming and laborious. Summary of the invention

[0005] The present application provides an Ackerman rate simulation method, system, device and medium to solve the above-mentioned problems.

[0006] In one aspect, the present application provides an Ackerman rate simulation method, the method comprising the following steps:

[0007] Step S1: Input the chassis design hard points of the basic vehicle model into the CAITA assembly software to generate the front and rear overhang assembly files;

[0008] Step S2: Building DMU models of the front suspension and rear suspension based on the front suspension and rear suspension assembly files;

[0009] Step S3: adding the speed formula of the rack movement to the normal line in the simulation environment of the CAITA assembly software and performing a driving model, simulating and outputting the angle measurement data;

[0010] Step S4: Create a curve based on the data output by the simulation, and select the wheel angle at a preset angle as a representative value to analyze whether the Ackerman rate design target is achieved.

[0011] In one implementation of the present application, before step S3, the method further includes:

[0012] Adding auxiliary components to the CAITA assembly software to measure the theoretical rotation angle;

[0013] Solve the theoretical rotation angle under pure rolling conditions.

[0014] In one implementation of the present application, after step S4, the method further includes:

[0015] Analyze the output simulation data and produced curves;

[0016] It is determined whether the vehicle hard points are qualified under each changed wheelbase and track. If the Ackerman rate exceeds the preset threshold, the wheelbase, track and hard point data are adjusted to repeat steps S1-S4.

[0017] In one implementation of the present application, the theoretical turning angle is solved by taking the left front wheel as a reference, when the vehicle turns right, when the left front wheel turns a certain angle, calculating the angle that the right front wheel turns when achieving pure rolling.

[0018] In one implementation of the present application, angle calculation is specifically implemented by adding a formula to establish a functional relationship.

[0019] In one implementation of the present application, the added formula is specifically: theoretical turning angle φ = atan(1 / (1 / tan(`measured spacing.3\angle`+0.001deg)-(P+`mechanical device.1\command\left front wheelbase\length` / 1mm) / (L+`mechanical device.1\command\wheelbase\length` / 1mm))); where L is the wheelbase and P is the kingpin distance.

[0020] In one implementation of the present application, step S2 is specifically:

[0021] Group the 3D component data in the DMU model and divide them into fixed parts and movable parts;

[0022] Enter the simulation environment of the CAITA assembly software, apply constraints to the components, and form DMU models of the front and rear overhangs.

[0023] The present application also provides an Ackerman rate simulation system, the system comprising:

[0024] Hard point data input unit, used to input the chassis design hard points of the basic vehicle model into the CAITA assembly software to form the front and rear overhang assembly files;

[0025] A DMU model building unit, used to build DMU models of the front suspension and rear suspension based on the front suspension and rear suspension assembly files;

[0026] A driving simulation unit, used to add a speed formula of rack movement to a normal line in the simulation environment of the CAITA assembly software and to perform a driving model, simulate and output the angle measurement data;

[0027] The Ackerman rate analysis unit is used to create a curve based on the simulation output data, and select the wheel angle at a preset angle as a representative value to analyze whether the Ackerman rate design target is achieved.

[0028] The present application also provides an Ackerman rate simulation device, the device comprising:

[0029] at least one processor; and,

[0030] a memory communicatively connected to the at least one processor; wherein,

[0031] The memory stores instructions that can be executed by the at least one processor. The instructions are executed by the at least one processor so that the at least one processor can complete the aforementioned Ackerman rate simulation method.

[0032] The present application also provides a non-volatile computer storage medium for Ackerman rate simulation, which stores computer executable instructions. The computer executable instructions are executed by a processor to implement the aforementioned Ackerman rate simulation method.

[0033] The present application provides an Ackerman rate simulation method, system, device and medium, which can replace the traditional Ackerman rate simulation analysis method for the wheelbase and track of a single vehicle model, especially for vehicles with variable wheelbase and track that are translated with a quarter suspension hard point unchanged, avoiding the repetitive labor of analyzing and solving each vehicle model with different wheelbase and track one by one. This patent involves the construction of a general model. As long as the fixed parts and moving parts of the general model are separated, and constraint pairs are added to the parameters of the wheelbase and track, the change of variable wheelbase and track can be realized, thereby performing Ackerman rate analysis simulation and improving analysis efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0035] Figure 1 A flow chart of an Ackerman rate simulation method provided in an embodiment of the present application;

[0036] Figure 2A schematic diagram of the simulation model construction and wheelbase change adjustment provided in the embodiment of the present application;

[0037] Figure 3 A composition diagram of an Ackerman rate simulation system provided in an embodiment of the present application;

[0038] Figure 4 A schematic diagram of an Ackerman rate simulation device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0040] The embodiments of the present application provide an Ackerman rate simulation method, system, device and medium. The technical solutions proposed in the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0041] Figure 1 A flow chart of an Ackerman rate simulation method provided in an embodiment of the present application. Figure 1 As shown, the method mainly includes the following steps:

[0042] Step S1: Input the chassis design hard points of the basic vehicle model into the CAITA assembly software to generate the front and rear overhang assembly files;

[0043] Step S2: Building DMU models of the front suspension and rear suspension based on the front suspension and rear suspension assembly files;

[0044] Step S3: adding the speed formula of the rack movement to the normal line in the simulation environment of the CAITA assembly software and performing a driving model, simulating and outputting the angle measurement data;

[0045] Step S4: Create a curve based on the data output by the simulation, and select the wheel angle at a preset angle as a representative value to analyze whether the Ackerman rate design target is achieved.

[0046] In the embodiment of the present application, before step S3, the method further includes:

[0047] Adding auxiliary components to the CAITA assembly software to measure the theoretical rotation angle;

[0048] Solve the theoretical rotation angle under pure rolling conditions.

[0049] In the embodiment of the present application, after step S4, the method further includes:

[0050] Analyze the output simulation data and produced curves;

[0051] It is determined whether the vehicle hard points are qualified under each changed wheelbase and track. If the Ackerman rate exceeds the preset threshold, the wheelbase, track and hard point data are adjusted to repeat steps S1-S4.

[0052] In the embodiment of the present application, the theoretical turning angle is solved specifically as follows: taking the left front wheel as a reference, when the vehicle turns right, when the left front wheel turns a certain angle, the angle that the right front wheel turns when achieving pure rolling is calculated.

[0053] In the embodiment of the present application, angle calculation is specifically achieved by adding a formula to establish a functional relationship.

[0054] In the embodiment of the present application, the added formula is specifically: theoretical turning angle φ = atan(1 / (1 / tan(`measured spacing.3\angle`+0.001deg)-(P+`mechanical device.1\command\left front wheelbase\length` / 1mm) / (L+`mechanical device.1\command\wheelbase\length` / 1mm))); where L is the wheelbase and P is the kingpin distance.

[0055] In the embodiment of the present application, the step S2 is specifically as follows:

[0056] Group the 3D component data in the DMU model and divide them into fixed parts and movable parts;

[0057] Enter the simulation environment of the CAITA assembly software, apply constraints to the components, and form DMU models of the front and rear overhangs.

[0058] The following is a specific embodiment of the present application. This application uses the FV70 freight version as the basic model (wheelbase 1790mm, wheelbase 3500mm) to make a DMU model for simulation. The specific implementation steps are as follows:

[0059] First enter the hard points as shown in the table below.

[0060] Table 1 Hard point data table

[0061] Serial number Hard point name X Y Z 1 Front point of lower arm 4.834 -456.822 -250.455 2 Lower arm outer ball point -11.624 -843.345 -282.114 3 Lower arm rear point 306.213 -414.466 -238.129 4 Shock absorber lower point 4.666 -712.855 -60.199 5 Shock absorber upper point 50.911 -657.708 492.198 6 Steering rod inner point 182.814 -450.64 -201.898 7 Steering rod outer point 138.804 -814.457 -225.051 8 Front wheel center -2.621 -895.01 -143.715 9 Front stabilizer bar bushing points 305.905 -319.007 -176 10 Connecting rod upper point 60.95 -638.523 151.063 11 Connecting rod lower point 59.531 -655.325 -176.118 12 Rear wheel hub 3497.212 -895 -181

[0062] As attached Figure 2As shown, the simulation model is based on the DMU model of the front suspension (the construction of the DMU model of the front McPherson suspension will not be repeated here), splitting the left and right suspensions, keeping one quarter of the hard points relatively unchanged so that it can be translated left and right, and then splitting the rear axle from the front axle so that it can be translated front and back, and adding certain auxiliary parts and constraint pairs to build it. The key constraint pairs are explained as follows: Implementation of variable wheelbase of the front suspension: According to the principle that one quarter of the suspension hard points are relatively unchanged, the longitudinal beams on the left and right sides of the front suspension subframe are cut off and divided into three parts: the middle part, the left part, and the right part. The left longitudinal beam and the middle subframe adopt diamond constraints, the right longitudinal beam and the middle subframe also adopt diamond constraints, and the middle subframe adopts fixed constraints; the realization of variable wheelbase of rear suspension: the rear axle is divided into three parts, namely the left part, the middle part, and the right part. Similarly, the left rear axle and the right rear axle adopt diamond constraints with the middle part of the rear axle respectively; the wheelbase change is realized: the middle subframe part and the middle part of the rear axle adopt diamond constraints; the change of rack length is realized: when the quarter suspension hard points are translated left and right at the same time, the rack must also be translated with these hard points, so it needs to be divided into three parts: rack body, rack-left, and rack-right. The rack-left and rack-right are respectively constrained with the rack in a diamond shape, and the rack body is then constrained with the steering gear in a diamond shape.

[0063] To calculate the Ackerman rate, we first introduce the concept of Ackerman's theoretical turning angle. With the outer wheel as the reference, assuming that the vehicle turns right, the turning angle of the inner wheel must be larger than that of the outer wheel, otherwise it will not be able to roll around a point. The actual turning angle of the inner wheel may be smaller than the theoretical turning angle. The change of the theoretical turning angle can be limited by formula constraints. This formula includes parameters such as wheelbase, track width, and the distance from the kingpin to the ground. At this time, the Ackerman rate is calculated, and the inner and outer wheel turning angles must be measured to achieve it. Enter the formula in the CATIA environment as follows:

[0064] Theoretical rotation angle φ = atan (1 / (1 / tan(`measurement spacing.3\angle`+0.001deg)-(1784+`mechanical device.1\command\left front wheelbase\length` / 1mm) / (3500+`mechanical device.1\command\wheelbase\length` / 1mm))), where:

[0065] +0.001deg is a data setting for initial values ​​other than 0, which does not affect the result;

[0066] 1784 is the kingpin distance of the basic model, which is defined as the distance between the kingpin lines on the left and right sides of the front suspension and the ground contact points. The kingpin distance of the variable wheelbase is obtained by adding the wheelbase diamond constraint command value.

[0067] 3500 is the wheelbase of the basic model, and the wheelbase diamond constraint command value becomes a variable wheelbase;

[0068] The drive is steered at a rack speed of 7.56 mm / s.

[0069] The curve output of the Ackerman rate is simulated using the law curve, and the sensor data is collected in 40 steps. The test data obtained is output in an Excel spreadsheet to make the Ackerman rate curve for different wheelbase and track changes.

[0070] Export data from the CATIA simulation module and use EXCEL to draw the above Ackerman rate curve. Focus on analyzing whether the Ackerman rate value when the wheel turns 20 degrees and 30 degrees is within the required range (general standard: required to be within 40%-60%; Ford standard: 45%-55% when the wheel turns 20 degrees, 60%-70% when the wheel turns 30 degrees), as shown in Table 2 below.

[0071] Table 2 Ackerman rate values ​​when the wheel rotates 20 degrees and 30 degrees

[0072] Wheelbase change (mm) Ackerman rate at 20 degree turning angle Ackerman rate at 30 degree turning angle 3100 0.451392 0.530397 3500 0.501981 0.593329 3900 0.569436 0.677336 Wheelbase change (mm) Ackerman rate at 20 degree turning angle Ackerman rate at 30 degree turning angle 1690 0.485893 0.573306 1790 0.501981 0.593329 1890 0.518996 0.614517

[0073] According to Ford standards, it can be seen from the above table:

[0074] (1) When the wheelbase remains unchanged at 1790 mm, the wheelbase is 3100 mm, and the inner wheel turning angle is 30 degrees, the Ackerman rate value is low (0.530397, the lower limit of the standard value is 60%);

[0075] (2) When the track width remains unchanged at 1790 mm, the wheelbase is 3900 mm, and the inner wheel turning angle is 20 degrees, the Ackerman rate value is high (0.569436, the upper limit of the standard value is 55%);

[0076] (3) When the wheelbase remains unchanged at 3500 mm and the track width is 1690, the Ackerman rate value at a 30-degree turning angle is slightly lower than the standard value (0.573306, the standard value is 60%).

[0077] When the first situation mentioned above occurs, tire wear will inevitably occur. At this time, the above steps should be repeated to adjust the hard point so that the Ackerman rate is within the acceptable range; when the second situation occurs, it is acceptable if the vehicle is defined as home use. If the handling stability requirements are high, the hard point can be re-matched to make it qualified; when the third situation occurs, tire wear may occur. The above steps should be repeated to adjust the hard point so that the Ackerman rate is within the acceptable range.

[0078] The following rules can be obtained in this embodiment:

[0079] (1) When the wheelbase remains unchanged and the quarter-point of the suspension remains relatively unchanged for translational design, the larger the ratio of wheelbase to wheelbase, the larger the Ackerman rate; the smaller the ratio of wheelbase to wheelbase, the smaller the Ackerman rate;

[0080] (2) When the wheelbase remains unchanged and the quarter-point of the suspension is relatively unchanged for translational design, the larger the ratio of wheelbase to track, the smaller the Ackerman rate; the smaller the ratio of track to wheelbase, the larger the Ackerman rate;

[0081] (3) The above rules are only applicable to the hard point data summary of this model and similar models.

[0082] The above is an Ackerman rate simulation method provided by an embodiment of the present application. Based on the same inventive concept, an Ackerman rate simulation system is also provided by an embodiment of the present application. Figure 3 A composition diagram of an Ackerman rate simulation system provided in an embodiment of the present application, such as Figure 3 As shown, the system mainly includes: a hard point data input unit 301, which is used to input the chassis design hard points of the basic vehicle model in the CAITA assembly software to form the front suspension and rear suspension assembly files; a DMU model building unit 302, which is used to build the DMU model of the front suspension and rear suspension based on the front suspension and rear suspension assembly files; a driving simulation unit 303, which is used to add the speed formula of the rack movement to the normal line in the simulation environment of the CAITA assembly software and perform the driving model, simulate and output the angle measurement data; an Ackerman rate analysis unit 304, which is used to make a curve according to the simulation output data, and select the wheel angle at a preset angle as a representative value to analyze whether the Ackerman rate design target is achieved.

[0083] The above is an Ackerman rate simulation system provided by an embodiment of the present application. Based on the same inventive concept, an Ackerman rate simulation device is also provided by an embodiment of the present application. Figure 4 A schematic diagram of an Ackerman rate simulation device provided in an embodiment of the present application is shown in FIG. Figure 4 As shown, the device mainly includes: at least one processor 401; and a memory 402 that is communicatively connected to the at least one processor; wherein the memory 402 stores instructions that can be executed by the at least one processor 401, and the instructions are executed by the at least one processor 401 so that the at least one processor 401 can complete the aforementioned Ackerman rate simulation method.

[0084] In addition, an embodiment of the present application further provides a non-volatile computer storage medium for Ackerman rate simulation, which stores computer executable instructions, and the computer executable instructions are executed by a processor to implement the aforementioned Ackerman rate simulation method.

[0085] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0086] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0087] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0088] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0089] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0090] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0091] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. An Ackerman rate simulation method, characterized in that: The method comprises the following steps: Step S1: Input the chassis design hard points of the basic vehicle model into the CAITA assembly software to generate the front and rear overhang assembly files; Step S2: Building DMU models of the front suspension and rear suspension based on the front suspension and rear suspension assembly files; Step S3: adding the speed formula of the rack movement to the normal line in the simulation environment of the CAITA assembly software and performing a driving model, simulating and outputting the angle measurement data; Step S4: Create a curve based on the data output by the simulation, and select the wheel angle at a preset angle as a representative value to analyze whether the Ackerman rate design target is achieved.

2. The Ackerman rate simulation method according to claim 1, characterized in that: Before step S3, the method further includes: Adding auxiliary components to the CAITA assembly software to measure the theoretical rotation angle; Solve the theoretical rotation angle under pure rolling conditions.

3. The Ackerman rate simulation method according to claim 1, characterized in that: After step S4, the method further includes: Analyze the output simulation data and produced curves; It is determined whether the vehicle hard points are qualified under each changed wheelbase and track. If the Ackerman rate exceeds the preset threshold, the wheelbase, track and hard point data are adjusted to repeat steps S1-S4.

4. The Ackerman rate simulation method according to claim 2, characterized in that: The solution to the theoretical turning angle is as follows: taking the left front wheel as the reference, when the vehicle turns right, when the left front wheel turns a certain angle, calculate the angle that the right front wheel turns to achieve pure rolling.

5. The Ackerman rate simulation method according to claim 4, characterized in that: Angle calculation is specifically achieved by adding formulas to establish a functional relationship.

6. The Ackerman rate simulation method according to claim 5, characterized in that: The added formula is: theoretical turning angle φ = atan(1 / (1 / tan(`measured spacing.3\angle`+0.001deg)-(P+`mechanical device.1\command\left front wheelbase\length` / 1mm) / (L+`mechanical device.1\command\wheelbase\length` / 1mm))); where L is the wheelbase and P is the kingpin distance.

7. The Ackerman rate simulation method according to claim 1, characterized in that: The step S2 is specifically: Group the 3D component data in the DMU model and divide them into fixed parts and movable parts; Enter the simulation environment of the CAITA assembly software, impose constraints on the components, and form DMU models of the front and rear overhangs.

8. An Ackerman rate simulation system, characterized in that: The system comprises: Hard point data input unit, used to input the chassis design hard points of the basic vehicle model into the CAITA assembly software to form the front and rear overhang assembly files; A DMU model building unit, used to build DMU models of the front suspension and rear suspension based on the front suspension and rear suspension assembly files; A driving simulation unit, used to add a speed formula of rack movement to a normal line in the simulation environment of the CAITA assembly software and to perform a driving model, simulate and output the angle measurement data; The Ackerman rate analysis unit is used to create a curve based on the simulation output data, and select the wheel angle at a preset angle as a representative value to analyze whether the Ackerman rate design target is achieved.

9. An Ackerman rate simulation device, characterized in that: The device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can complete the Ackerman rate simulation method described in any one of claims 1 to 7.

10. A non-volatile computer storage medium for Ackerman rate simulation, storing computer executable instructions, characterized in that: The computer executable instructions are executed by a processor to implement an Ackerman rate simulation method according to any one of claims 1 to 7.

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