A new energy vehicle suspension system design optimization method and system

Abstract

The application relates to the technical field of new energy vehicles, and provides a new energy vehicle suspension system design optimization method and system, which comprises the following steps: acquiring power assembly parameters and initial design parameters of a suspension system; performing rigid body modal decoupling analysis on the suspension system to determine suspension system design parameters meeting a target system decoupling rate; performing stress simulation analysis on the suspension system under a plurality of preset typical working conditions, a plurality of limit working conditions and a plurality of damage working conditions; performing fatigue analysis based on the maximum stress simulation value under the plurality of typical working conditions; performing static strength analysis based on the stress simulation value under the plurality of damage working conditions; and acquiring suspension system design parameters meeting stress requirements, fatigue strength and static strength requirements under all working conditions. The application expands the investigation range in the suspension system design stage, guarantees the performance of the suspension system from the source, and improves the reliability by comprehensively performing fatigue analysis and static strength analysis under multiple working conditions.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of new energy vehicles, and particularly relates to a new energy vehicle suspension system design optimization method and system. BACKGROUND

[0002] The statements in this section merely provide background information related to the present application and do not necessarily constitute the prior art.

[0003] Suspension load analysis is an important analysis project for evaluating the powertrain suspension. Generally, the universal 28 working conditions can comprehensively simulate the stress and displacement of the powertrain suspension system under typical and extreme conditions. However, the universal 28 working conditions are originally a theoretical analysis method for fuel vehicles, and there are differences in power stress characteristics between fuel vehicles and new energy vehicles. Specifically, the power response of pure electric vehicles is fast, the starting torque is large, and through actual road test verification, as the off-road performance requirements of electric vehicles increase, the number of extreme conditions appearing during driving increases. Therefore, for new energy vehicles, using the existing universal 28 working conditions for evaluation during the suspension system design stage, on the one hand, the fatigue strength analysis may be insufficient due to incomplete stress analysis, thereby causing the problem of suspension frame fatigue cracking, and on the other hand, the current analysis and evaluation do not consider the fatigue cracking risk of the vehicle under long-time extreme conditions. SUMMARY

[0004] To overcome the deficiencies of the prior art, the present application provides a new energy vehicle suspension system design optimization method and system, which adds a damage working condition on the basis of the original 28 working conditions, and carries out fatigue analysis and static strength analysis based on the typical working conditions and the damage working conditions respectively, thereby obtaining suspension system design parameters suitable for new energy vehicles.

[0005] To achieve the above-mentioned purpose, the first aspect of the present application provides a new energy vehicle suspension system design optimization method, comprising the following steps:

[0006] Obtaining powertrain parameters and initial design parameters of the suspension system;

[0007] Performing rigid body modal decoupling analysis on the suspension system to determine suspension system design parameters that meet the target system decoupling rate;

[0008] Performing stress simulation analysis on the suspension system under a plurality of preset typical working conditions, a plurality of extreme working conditions and a plurality of damage working conditions, respectively;

[0009] Performing fatigue analysis based on the maximum value of the stress simulation under the plurality of typical working conditions;

[0010] Performing static strength analysis based on the stress simulation value under the plurality of damage working conditions;

[0011] Obtain the design parameters of the suspension system that meet the stress requirements, fatigue strength and static strength requirements under all working conditions.

[0012] In some embodiments, the powertrain parameters include maximum torque, power output, transmission ratio, moment of inertia, center of mass coordinates, and wheel-side torque.

[0013] In some embodiments, the initial design parameters of the suspension system include the suspension system's elastic center and dynamic and static stiffness.

[0014] In some embodiments, the destructive conditions include conditions that apply triaxial destructive forces to the vehicle and conditions that apply destructive forces to the suspension.

[0015] In some embodiments, fatigue analysis is performed based on the maximum simulated stress values ​​under eight typical operating conditions.

[0016] In some embodiments, during the stress simulation analysis, fatigue analysis, and static strength analysis, the simulated stress value / maximum simulated stress value is multiplied by a safety factor before analysis.

[0017] A second aspect of the present invention provides a design optimization system for a new energy vehicle mounting system, comprising:

[0018] The initial parameter acquisition module is configured to acquire powertrain parameters and initial design parameters of the suspension system.

[0019] The rigid body modal analysis module is configured to perform rigid body modal decoupling analysis on the suspension system and determine the suspension system design parameters that meet the target system decoupling rate.

[0020] The full-condition stress simulation module is configured to perform stress simulation analysis on the suspension system under multiple preset typical conditions, multiple extreme conditions, and multiple failure conditions.

[0021] The fatigue analysis module is configured to perform fatigue analysis based on the maximum simulated force values ​​under multiple typical working conditions.

[0022] The static strength analysis module is configured to perform static strength analysis based on the simulated force values ​​under multiple failure conditions.

[0023] The optimal design parameter acquisition module is configured to acquire suspension system design parameters that meet the stress requirements, fatigue strength, and static strength requirements under all working conditions.

[0024] A third aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the aforementioned new energy vehicle suspension system design optimization method.

[0025] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned method for optimizing the design of a new energy vehicle suspension system.

[0026] The fifth aspect of the present invention provides a computer program product, the computer program product comprising a computer program, which, when executed by a processor, implements the aforementioned method for optimizing the design of a new energy vehicle suspension system.

[0027] By expanding multiple failure conditions beyond traditional typical and extreme conditions, the scope of consideration during the design phase of the suspension system is maximized, ensuring the performance of the suspension system from the source. At the same time, the fatigue analysis based on a single condition is transformed into a fatigue analysis based on multiple conditions, improving the reliability of the fatigue analysis. Static strength analysis based on the expanded multiple failure conditions can effectively prevent the suspension system from fracture failure caused by external forces. Attached Figure Description

[0028] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0029] Figure 1 This is a flowchart of a method for designing and optimizing the mounting system of a new energy vehicle in one or more embodiments of the present invention;

[0030] Figure 2 This is a schematic diagram illustrating the principle of the new energy vehicle suspension system design optimization method in one or more embodiments of the present invention. Detailed Implementation

[0031] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0032] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0033] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0034] Since the engine itself is an internal vibration source, it is also subject to various external vibration interferences. If these vibrations are not filtered, they will reduce ride comfort and may also damage automotive parts. Therefore, a suspension system is set up to minimize the vibration transmitted from the engine to the support system and improve vehicle comfort. Generally speaking, the engine suspension system has the following requirements: (1) It can withstand dynamic and static loads under all operating conditions and keep the displacement of the engine assembly in all directions within an acceptable range, without interfering with other parts on the chassis, and without damage to parts before engine overhaul; (2) It can fully isolate the transmission of vibration generated by the engine to the frame and cab, reducing vibration noise; (3) It can fully isolate the vibration transmitted to the engine through the suspension due to uneven road surface, reducing vibration noise; (4) It ensures that the bending moment of the connection surface between the engine body and the flywheel housing does not exceed the allowable value of the engine manufacturer.

[0035] As described in the background section, the existing 28 analytical conditions are insufficient to meet the analytical needs of electric vehicles. To address these issues, one or more embodiments of the present invention provide a method for optimizing the design of a new energy vehicle mounting system. Figure 1 As shown, it includes the following steps:

[0036] Step 1: Obtain the powertrain parameters and the initial design parameters of the suspension system;

[0037] Step 2: Perform rigid body modal decoupling analysis on the suspension system to determine the suspension system design parameters that satisfy the target system decoupling rate;

[0038] Step 3: Perform stress simulation analysis on the suspension system under multiple preset typical working conditions, multiple extreme working conditions, and multiple failure working conditions; determine whether the stress simulation analysis results meet the requirements. If yes, proceed to step 4; otherwise, return to step 2.

[0039] Step 4: Perform fatigue analysis based on the maximum stress simulation values ​​under multiple typical working conditions; perform static strength analysis based on the stress simulation values ​​under multiple failure conditions.

[0040] Step 5: Determine whether both fatigue strength and static strength meet the requirements. If yes, the current suspension system design parameters are the optimal parameters. If not, repeat steps 2-5, that is, determine the new suspension system design parameters that meet the target system decoupling rate, and perform fatigue analysis and static strength analysis based on the new suspension system design parameters until both fatigue strength and static strength meet the requirements.

[0041] By expanding multiple failure conditions beyond traditional typical and extreme conditions, the scope of consideration during the design phase of the suspension system is maximized, ensuring the performance of the suspension system from the source. At the same time, the fatigue analysis based on a single condition is transformed into a fatigue analysis based on multiple conditions, improving the reliability of the fatigue analysis. Static strength analysis based on the expanded multiple failure conditions can effectively prevent the suspension system from fracture failure caused by external forces.

[0042] By comprehensively considering the stress conditions of the suspension system under various working conditions and conducting fatigue and static strength analyses, the design process of the suspension system was supplemented and optimized, thereby improving the performance of the suspension system.

[0043] In step 1, the powertrain parameters include inertia, center of mass coordinates, maximum torque, power, transmission ratio, etc.

[0044] The initial design parameters of the suspension system are related to the parameters and layout of the vehicle's powertrain. First, based on the overall vehicle layout and the powertrain's location, the available space for the suspension system is determined. Then, according to the spatial characteristics, the installation position of the suspension system, and its initial design parameters, are determined using a three-point or four-point arrangement. These initial design parameters include the suspension's structural parameters, materials, center of elasticity, and moment of inertia. Furthermore, the initial design parameters also include the dynamic and static stiffness of the suspension system. The static stiffness is defined according to the vehicle's target performance level and preliminarily determined based on empirical values. The dynamic stiffness depends on the supplier's capabilities, with a common dynamic-to-static ratio of 1.4.

[0045] In step 2, firstly, based on the powertrain parameters and the initial design parameters of the suspension system, and under the premise of satisfying the vehicle boundary conditions, a rigid body modal decoupling analysis is performed on the suspension system to determine whether the target system decoupling rate is met. If not, the design parameters of the suspension system are adjusted until the target system decoupling rate is met. The adjustment of the suspension system design parameters mainly involves adjusting the elastic center and dynamic and static stiffness of the suspension system. By optimizing with the target system decoupling rate as the objective, the elastic center and dynamic and static stiffness of the suspension system are locked.

[0046] Modal decoupling design is a crucial aspect of vibration isolation design for powertrain mounting systems under idling conditions. The goal is to maximize the decoupling rate of the mounting system, ensuring vibration decoupling in the three around-the-cylinder coordinates and the three principal parallel directions. In some embodiments, a decoupling rate of ≥90% in the two principal directions is required.

[0047] For example, multibody dynamics software or optimization tools based on the MATLAB development platform can be used to optimize the elastic center and dynamic and static stiffness of each suspension, thereby achieving the adjustment of the elastic center and dynamic and static stiffness.

[0048] Currently, the commonly used powertrain mounting system analysis conditions are the 28 conditions used by General Motors. These 28 conditions include 16 typical conditions and 12 extreme conditions, as shown in conditions 1-28 in Table 1. In step 3, based on the existing analysis conditions, 8 additional destructive conditions are added for electric vehicles, as shown in conditions 29-36 in Table 1. In conditions 29-34, 20g, 9g, and 36g represent the applied destructive force. Condition 35 is based on condition 2, with the destructive force applied at twice the level of condition 2. Similarly, condition 36 is based on condition 3, with the destructive force applied at twice the level of condition 3. The calculation methods for the 8 newly added destructive conditions are, for example, 18g in the +Z direction and -21g in the -Z direction. The data sources are all collected from various road test conditions.

[0049] Table 1 Powertrain Suspension System Analysis Conditions

[0050]

[0051]

[0052]

[0053] In step 3, stress simulation analysis is performed on the suspension system based on 36 different analytical conditions. The stress on the suspension mainly comes from the reverse force of the powertrain torque output and the acceleration force supporting the powertrain during vehicle operation and transportation. When the stress simulation results meet the requirements, fatigue analysis and static strength analysis are further performed.

[0054] In step 4, such as Figure 2 As shown, this method abandons the traditional fatigue strength analysis method that only uses conditions 2 and 3. Instead, it uses the maximum values ​​of eight WOT conditions (conditions 2 to 9) as the fatigue analysis conditions, expanding the scope of fatigue analysis and avoiding the problem of suspension fatigue cracking due to insufficient fatigue strength analysis in the theoretical analysis stage. It also abandons the traditional method of using only the maximum values ​​from 28 conditions for static strength analysis, and uses the stress values ​​of eight newly added failure conditions more suitable for electric vehicles for static strength analysis.

[0055] Furthermore, to improve the reliability of stress analysis, some embodiments multiply the original stress results by a safety factor to amplify the stress conditions. By re-evaluating the stress analysis results to determine whether they meet the performance requirements, the analysis results become more reliable. Moreover, compared to directly judging whether performance requirements are met based on simulation results, this approach is more adaptable to situations where vehicles are under extreme operating conditions for extended periods.

[0056] Specifically, in step 3, the specific parameter values ​​of the suspension system are input into the simulation software to obtain the magnitude values ​​of 36 working conditions. The force value of each extreme working condition and failure working condition is multiplied by an amplified safety factor, and the amplified force value is used to determine whether it meets the index requirements. In step 4, fatigue analysis is performed based on the maximum values ​​of the eight WOT working conditions (conditions 2 to 9) after being amplified by the safety factor; static strength analysis is performed based on the force values ​​of the eight newly added failure working conditions more suitable for electric vehicles, which are multiplied by an amplified safety factor respectively.

[0057] One or more embodiments of the present invention also provide a new energy vehicle mounting system design optimization system, comprising:

[0058] The initial parameter acquisition module is configured to acquire powertrain parameters and initial design parameters of the suspension system.

[0059] The rigid body modal analysis module is configured to perform rigid body modal decoupling analysis on the suspension system and determine the suspension system design parameters that meet the target system decoupling rate.

[0060] The full-condition stress simulation module is configured to perform stress simulation analysis on the suspension system under multiple preset typical conditions, multiple extreme conditions, and multiple failure conditions.

[0061] The fatigue analysis module is configured to perform fatigue analysis based on the maximum simulated force values ​​under multiple typical working conditions.

[0062] The static strength analysis module is configured to perform static strength analysis based on the simulated force values ​​under multiple failure conditions.

[0063] The optimal design parameter acquisition module is configured to acquire suspension system design parameters that meet the stress requirements, fatigue strength, and static strength requirements under all working conditions.

[0064] One or more embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the aforementioned method for optimizing the design of a new energy vehicle mounting system. The electronic device includes one or more processors, one or more memories coupled to the processor, and a communication module coupled to the processor.

[0065] The memory may include one or more non-volatile memories and one or more volatile memories. Examples of non-volatile memories include, but are not limited to, at least one of the following: read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, hard disk, compact disc (CD), digital video disc (DVD), or other magnetic and / or optical storage. Examples of volatile memories include, but are not limited to, at least one of the following: random access memory (RAM), or other volatile memories that do not persist during the duration of a power outage. The computer program may be stored in the ROM. When the processor executes the computer program, it implements any one of the above-described methods for sending and receiving passwords.

[0066] In some embodiments, the program may be tangibly contained in a computer-readable medium, which may include a device (such as in memory) or other storage device accessible by the device. The program may be loaded from the computer-readable medium into RAM for execution. The computer-readable medium may include any type of tangible non-volatile memory, such as ROM, EPROM, flash memory, hard disk, whereby the computer-readable storage medium stores a computer program that, when executed by a processor, implements any of the methods described above: the attachment file sending method, the attachment file receiving method, and the quantum key distribution method.

[0067] Various embodiments of the present invention can be implemented in hardware or dedicated circuitry, software, logic, or any combination thereof. Some aspects can be implemented in hardware, while others can be implemented in firmware or software, which can be executed by a controller, microprocessor, or other computing device. Although various aspects of the embodiments of this application are shown and described as block diagrams, flowcharts, or represented using some other illustration, it should be understood that the blocks, apparatuses, systems, techniques, or methods described herein can be implemented as, as non-limiting examples, in hardware, software, firmware, dedicated circuitry or logic, general-purpose hardware or controllers or other computing devices, or some combination thereof.

[0068] Although the operation of the method of the present invention is described in a specific order in the accompanying drawings, this does not require or imply that the operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Rather, the steps depicted in the flowcharts may be performed in a different order. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps. It should also be noted that the features and functions of two or more devices according to this application may be embodied in one device. Conversely, the features and functions of one device described above may be further divided and embodied by multiple devices.

Claims

1. A new energy vehicle suspension system design optimization method, characterized in that, The method comprises the following steps: acquiring power assembly parameters and initial design parameters of a suspension system; performing rigid body modal decoupling analysis on the suspension system to determine suspension system design parameters that meet a target system decoupling rate; performing stress simulation analysis on the suspension system under a plurality of preset typical working conditions, a plurality of limit working conditions and a plurality of damage working conditions respectively; performing fatigue analysis based on the maximum stress simulation values under the plurality of typical working conditions; performing static strength analysis based on the stress simulation values under the plurality of damage working conditions; acquiring suspension system design parameters that meet stress requirements, fatigue strength and static strength requirements under all working conditions; the damage working conditions include a working condition of applying three-directional damage forces to the vehicle and a working condition of applying damage forces to the suspension; the fatigue analysis is based on the maximum stress simulation values under the eight typical working conditions; in the stress simulation analysis, fatigue analysis and static strength analysis, the stress simulation values / stress simulation maximum values are multiplied by a safety factor before analysis.

2. The new energy vehicle suspension system design optimization method of claim 1, wherein, The power assembly parameters include maximum torque, power value, transmission ratio, moment of inertia, mass center coordinates and wheel edge torque.

3. The new energy vehicle suspension system design optimization method of claim 1, wherein, The initial design parameters of the suspension system include suspension system elastic center and dynamic and static stiffness.

4. A new energy vehicle suspension system design optimization system, characterized in that, The method comprises: an initial parameter acquisition module configured to acquire power assembly parameters and initial design parameters of a suspension system; a rigid body modal analysis module configured to perform rigid body modal decoupling analysis on the suspension system to determine suspension system design parameters that meet a target system decoupling rate; a full working condition stress simulation module configured to perform stress simulation analysis on the suspension system under a plurality of preset typical working conditions, a plurality of limit working conditions and a plurality of damage working conditions respectively; a fatigue analysis module configured to perform fatigue analysis based on the maximum stress simulation values under the plurality of typical working conditions; a static strength analysis module configured to perform static strength analysis based on the stress simulation values under the plurality of damage working conditions; an optimal design parameter acquisition module configured to acquire suspension system design parameters that meet stress requirements, fatigue strength and static strength requirements under all working conditions; the damage working conditions include a working condition of applying three-directional damage forces to the vehicle and a working condition of applying damage forces to the suspension; the fatigue analysis is based on the maximum stress simulation values under the eight typical working conditions; in the stress simulation analysis, fatigue analysis and static strength analysis, the stress simulation values / stress simulation maximum values are multiplied by a safety factor before analysis.

5. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The processor implements the new energy automobile suspension system design optimization method of any one of claims 1-3 when executing the program.

6. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the new energy automobile suspension system design optimization method of any one of claims 1-3.

7. A computer program product, characterised in that, The computer program product comprises a computer program, and the computer program is executed by the processor to implement the new energy automobile suspension system design optimization method of any one of claims 1-3.

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