Method and system for simulating vibration in whole vehicle based on block chain, and medium

Abstract

The invention discloses a whole vehicle interior vibration simulation method and system based on a block chain, and a medium, mainly relates to the technical field of whole vehicle interior vibration simulation, and is used for solving the problems that the precision of a whole vehicle interior vibration simulation effect is relatively low, simulation personnel perform simulation independently, and simulation data is easy to be unreasonable in an existing scheme. Comprising the following steps: acquiring simulation parameters through any acquisition node; uploading to a block chain; simulation parameters of the block chain are obtained through any simulation node, and building of a whole vehicle dynamic model is completed; creating a whole vehicle response index under a preset working condition by obtaining nodes; wherein the whole vehicle response indexes at least comprise seat guide rail vibration and steering wheel vibration; acquiring simulation termination time setting and simulation step number setting; and obtaining the built whole vehicle dynamic model from the block chain, running the whole vehicle dynamic model for simulation calculation, and obtaining the vibration isolation performance of the elastic vibration reduction system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of whole vehicle interior vibration simulation, and in particular to a whole vehicle interior vibration simulation method and system based on a blockchain and a medium. BACKGROUND

[0002] NVH (Noise Vibration Harshness) is a comprehensive problem for measuring the quality of automobile manufacturing, and directly relates to the user's experience of the automobile. One-third of the existing whole vehicle failure problems are caused by NVH problems. At present, large automobile enterprises spend a lot of effort to solve the NVH problem. A large amount of simulation analysis is performed in the early stage of the project to preliminarily evaluate and optimize the whole vehicle NVH vibration performance, but the effect is still unsatisfactory.

[0003] The existing whole vehicle NVH vibration performance simulation evaluation mainly includes two types: system level simulation and whole vehicle level simulation. The system level simulation mainly relies on the frequency decoupling of the powertrain suspension system and the modal frequency avoidance analysis of each system component. This method has a large workload and often appears to be satisfactory in system level simulation but unsatisfactory in actual whole vehicle vibration. The whole vehicle level simulation is to build a simplified model of the whole vehicle for simulation. This model is too simplified and does not build a suspension damping system and a tire system, so the simulation accuracy is low. In addition, although the mainstream automobile enterprises optimize the vibration performance through early simulation analysis, the traditional method mainly simulates by simulation personnel alone, which is prone to unreasonable simulation data, and the result is significantly biased. SUMMARY

[0004] In view of the above problems of the prior art, the present application provides a whole vehicle interior vibration simulation method and system based on a blockchain and a medium to solve the problems of low simulation accuracy of the existing whole vehicle interior vibration simulation method, simulation by simulation personnel alone, and unreasonable simulation data.

[0005] In a first aspect, the present application provides a whole vehicle interior vibration simulation method based on a blockchain, characterized in that the method comprises: obtaining simulation parameters through any obtaining node; wherein the simulation parameters include whole vehicle system component parameters and elastic damping system parameters; broadcasting the simulation parameters to all verification nodes, and uploading to the blockchain after obtaining the verification success information returned by a preset first number of verification nodes; The simulation parameters of the blockchain are obtained through any simulation node. Using the ADAMS dynamic simulation tool, each system component is equivalent to a lumped mass point, and the parameters of each system component in the simulation parameters are assigned to the corresponding lumped mass point. Each elastic damping system in the simulation parameters is equivalent to an elastic element, and the parameters of each elastic damping system are assigned to the corresponding elastic element. The connection relationship between each system component and each elastic element is obtained, and the construction of the whole vehicle dynamic model is completed. The completed whole vehicle dynamic model is broadcast to all simulation nodes. After receiving the verification success information returned by the second preset number of simulation nodes, it is uploaded to the blockchain. By obtaining nodes, vehicle response indicators under preset working conditions are created; among them, vehicle response indicators include at least: seat rail vibration and steering wheel vibration; simulation termination time setting and simulation step setting are obtained; the completed vehicle dynamics model is obtained from the blockchain, and the vehicle dynamics model simulation calculation is run to obtain the vibration isolation performance of the elastic damping system.

[0006] In one implementation of this application, simulation parameters are acquired through any acquisition node, specifically including: Obtain the parameters of each system component of the vehicle; among which, the component parameters include at least: hard point coordinates, component mass, component center of gravity, and component inertia parameters of the cab, cargo box, powertrain, frame, and suspension system components. Obtain the parameters of each elastic damping system of the whole vehicle; among them, the elastic damping system parameters include at least the stiffness, damping parameters, elastic center coordinates, and hard point coordinates of the powertrain mount, body mount, tire, suspension bushing, and suspension spring elastic damping system.

[0007] In one implementation of this application, the ADAMS dynamics simulation tool is used to represent each system component as a lumped mass point, and the simulation parameters of each system component are assigned to the corresponding lumped mass point. Specifically, this includes: The Body equivalent module of the ADAMS dynamics simulation tool is used to convert each system component into a lumped mass point. The parameters of each system component are assigned to the corresponding centralized mass point to construct each body containing parameters of centroid, mass, and inertia.

[0008] In one implementation of this application, each elastic damping system is equivalent to an elastic element, and the parameters of each elastic damping system are assigned to the corresponding elastic element, specifically including: Each elastic element is created according to the assembly logic of each system component, and each elastic damping system is equivalent to an elastic element through the elastic equivalent module of the ADAMS dynamic simulation tool; the elastic equivalent module of the tool includes: Bush or Spring-Damper elements; The parameters of each elastic damping system are assigned to the corresponding elastic element.

[0009] In one implementation of this application, creating vehicle response indicators under preset operating conditions specifically includes: Create simulation boundary conditions; the boundary conditions include applying engine torque excitation under various operating conditions, creating vehicle response indicators under different operating conditions, and the vehicle response indicators include seat rail vibration and steering wheel vibration.

[0010] Secondly, this application provides a blockchain-based vehicle in-vehicle vibration simulation system, the system comprising: The acquisition node is used to acquire simulation parameters, including parameters of various system components of the vehicle and parameters of the elastic damping system. The simulation parameters are broadcast to all verification nodes, and after receiving verification success information returned by a preset first number of verification nodes, they are uploaded to the blockchain. Simulation nodes are used to acquire simulation parameters from the blockchain. Using the ADAMS dynamics simulation tool, each system component is equivalent to a lumped mass point, and the parameters of each system component in the simulation parameters are assigned to the corresponding lumped mass point. Each elastic damping system in the simulation parameters is equivalent to an elastic element, and the parameters of each elastic damping system are assigned to the corresponding elastic element. The connection relationship between each system component and each elastic element is obtained, and the construction of the whole vehicle dynamics model is completed. The completed whole vehicle dynamics model is broadcast to all simulation nodes. After receiving the verification success information returned by the second preset number of simulation nodes, it is uploaded to the blockchain. Obtain nodes to create vehicle response indicators under preset working conditions; among which, the vehicle response indicators include at least: seat rail vibration and steering wheel vibration; obtain simulation termination time settings and simulation step settings; obtain the completed vehicle dynamics model from the blockchain, run the vehicle dynamics model simulation calculation, and obtain the vibration isolation performance of the elastic damping system.

[0011] In one implementation of this application, the node acquisition includes an acquisition unit. Used to obtain parameters of various system components of the vehicle; among which, the component parameters include at least: hard point coordinates, component mass, component center of gravity, and component inertia parameters of components such as cab, cargo box, powertrain, frame, and suspension system. Obtain the parameters of each elastic damping system of the whole vehicle; among them, the elastic damping system parameters include at least the stiffness, damping parameters, elastic center coordinates, and hard point coordinates of the powertrain mount, body mount, tire, suspension bushing, and suspension spring elastic damping system.

[0012] In one implementation of this application, the simulation node includes a component assembly unit. Used to convert each system component into a lumped mass point using the Body equivalent module of the ADAMS dynamics simulation tool; The parameters of each system component are assigned to the corresponding centralized mass point to construct each body containing parameters of centroid, mass, and inertia.

[0013] In one implementation of this application, the simulation node includes a component building unit. This tool is used to create each elastic element according to the assembly logic of each system component. The elastic damping system is equivalent to an elastic element through the elastic equivalent module of the ADAMS dynamic simulation tool. The elastic equivalent module of the tool includes: Bush or Spring-Damper elements. The parameters of each elastic damping system are assigned to the corresponding elastic element.

[0014] Thirdly, this application provides a non-volatile computer storage medium storing computer instructions, which, when executed, implement a blockchain-based whole-vehicle in-vehicle vibration simulation method as described above.

[0015] Those skilled in the art will understand that this application has at least the following beneficial effects: This application provides a blockchain-based, ADAMS-based method for simulating in-vehicle vibration. By acquiring component parameters (such as engine mass and suspension stiffness) and damping system parameters (such as damping coefficient and rubber bushing stiffness), it provides accurate input to the multibody dynamics model, avoiding simulation distortion caused by missing parameters. Complex components (such as driveshafts and body frames) are simplified into concentrated mass points, reducing model degrees of freedom and improving simulation efficiency while preserving key dynamic characteristics. The damping system (such as suspension and engine mounts) is modeled as spring-damped elements, directly quantifying its vibration isolation efficiency (such as transmissibility curves) to support accurate vibration prediction. Key vibration indicators are defined, focusing on areas with significant user perception, enhancing the practical guiding value of the simulation results. By adjusting the simulation step size and total duration, high-frequency vibration details are captured while avoiding wasted computational resources.

[0016] Furthermore, to avoid the problem of data silos, this application sets up parameter on-chaining, including acquisition nodes and verification nodes. Utilizing a consensus mechanism, the parameters are written to the blockchain after a predetermined number of nodes verify their physical rationality (e.g., non-negative stiffness values, damping coefficient thresholds). The verification nodes involved in this application can be expert roles such as test engineers or CAE experts. This distributed verification network breaks the traditional "single-point simulation" model.

[0017] In addition, this application puts all parameters and models involved in the simulation process onto the blockchain, enabling traceability of the simulation process in the event of a failure. Attached Figure Description

[0018] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of a blockchain-based vehicle in-vehicle vibration simulation method provided in an embodiment of this application.

[0020] Figure 2 This is a schematic diagram of the internal structure of a blockchain-based vehicle in-vehicle vibration simulation system provided in an embodiment of this application. Detailed Implementation

[0021] Those skilled in the art should understand that the embodiments described below are merely preferred embodiments of this disclosure and do not imply that this disclosure can only be implemented through these preferred embodiments. These preferred embodiments are merely used to explain the technical principles of this disclosure and are not intended to limit the scope of protection of this disclosure. Based on the preferred embodiments provided by this disclosure, all other embodiments obtained by those skilled in the art without creative effort should still fall within the scope of protection of this disclosure.

[0022] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0023] The technical solutions proposed in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0024] The embodiment provides a blockchain-based method for simulating in-vehicle vibration, such as... Figure 1 As shown in the embodiments of this application, the method mainly includes the following steps: Step 110: Obtain simulation parameters through any acquisition node; broadcast the simulation parameters to all verification nodes; after receiving a preset number of successful verification messages from the verification nodes, upload them to the blockchain; otherwise, report an upload failure message and obtain the simulation parameters again.

[0025] It should be noted that the simulation parameters include: parameters of each system component of the vehicle and parameters of the elastic damping system. Any acquisition node can be a server belonging to any experimenter. The verification node can be an expert terminal. The preset initial quantity can be 1 / 3 of the total quantity.

[0026] In some embodiments, "obtaining simulation parameters" in this step can specifically refer to: obtaining parameters of various system components of the vehicle through CAD software (CREO, CATIA) or CAE software (ANSA, HyperMesh). Component parameters include hard point coordinates, component mass, component center of gravity, component inertia parameters, etc., of system components such as the cab, cargo box, powertrain, frame, and suspension; obtaining parameters of various elastic damping systems of the vehicle through elastic damping system design drawings. Elastic damping system parameters include stiffness, damping parameters, elastic center point coordinates, hard point coordinates, etc., of elastic damping systems such as powertrain mounts, body mounts, tires, suspension bushings, and suspension springs.

[0027] Those skilled in the art will understand that this application allows any experimenter's server to initiate parameter submission as an acquisition node, which is then broadcast to a verification network (verification nodes) composed of expert terminals, overcoming the limitations of traditional single-point review. A 1 / 3 node consensus mechanism (e.g., at least 3 out of 9 verification nodes must confirm) ensures parameter rationality, avoiding both the bottleneck of excessive centralized review and preventing misjudgment by a single expert.

[0028] This step allows for unified verification of the geometric properties (hard point coordinates, inertial parameters) of the vehicle system components (cabin / frame, etc.) and the characteristics (stiffness / damping parameters) of the elastic damping system, ensuring the integrity of the input parameters for dynamic simulation. Design data is directly extracted using CAD / CAE software, eliminating errors from manual transcription.

[0029] This step automatically triggers a re-acquisition process for parameters that do not reach the consensus threshold, forming a closed loop of "submission-verification-feedback". This mechanism forcibly solves the problem of parameter errors being passed to downstream simulations in the traditional mode, improving the reliability of NVH analysis from the source.

[0030] Step 120: Obtain the simulation parameters of the blockchain through any simulation node; use the ADAMS dynamic simulation tool to convert each system component into a lumped mass point and assign the parameters of each system component in the simulation parameters to the corresponding lumped mass point; convert each elastic damping system in the simulation parameters into an elastic element and assign the parameters of each elastic damping system to the corresponding elastic element; obtain the connection relationship between each system component and each elastic element to complete the construction of the whole vehicle dynamic model; broadcast the completed whole vehicle dynamic model to all simulation nodes; after obtaining the verification success information returned by the second preset number of simulation nodes, upload it to the blockchain.

[0031] It should be noted that the simulation node can be an acquisition node or a standalone server node.

[0032] Specifically, using the ADAMS dynamics simulation tool, each system component is represented as a lumped mass point, and the parameters of each system component are assigned to the corresponding lumped mass point. This can be done as follows: The Body equivalent module of the ADAMS dynamics simulation tool is used to convert each system component into a lumped mass point; the parameters of each system component are assigned to the corresponding lumped mass point to build each Body containing the center of mass, mass, and inertial parameters.

[0033] In this process, the ADAMS dynamics simulation tool uses the Body equivalent module to represent each system component as a lumped mass point and simulates it. For example, the cab is named TB, the cargo box is named CheDou, the powertrain is named PT, the frame is named CheJia, and the suspension is named XuanGua.

[0034] Each elastic damping system is equivalent to an elastic element, and the parameters of each elastic damping system are assigned to the corresponding elastic element, specifically including: Each elastic element is created according to the assembly logic of each system component. Each elastic damping system is equivalent to an elastic element through the elastic equivalent module of the ADAMS dynamic simulation tool. The elastic equivalent module of the tool includes Bush or Spring-Damper elements. The parameters of each elastic damping system are assigned to the corresponding elastic element.

[0035] As an example, the Bush unit simulates the damping system, including powertrain mounts, body mounts, tires, and suspension bushings, while the Spring-Damper unit simulates the suspension springs.

[0036] Furthermore, the powertrain mounting bush units are created using the ADAMS dynamics simulation tool 2 Bod-1 Loc method. The powertrain mounting bush units are named Left, Right, and Rear. The stiffness and damping parameters of the powertrain mounting elastic units are assigned to their respective bush units. The powertrain mounting elastic units connect the powertrain and the frame, thus completing the creation of the powertrain mounting bush units. Create a tire bush element using the same creation method, assign the corresponding stiffness and damping parameters, connect the tire bush element to the ground and suspension system, and complete the creation of the tire bush element; The vehicle body suspension bushings were created using the ADAMS dynamics simulation tool 2 Bod-2 Loc method. The vehicle body suspension bushings were named PT_Left_N (N=1,2,3,4) and PT_Right_N (N=1,2,3,4). The stiffness and damping parameters of the vehicle body suspension elastic elements were assigned to their corresponding bushings. The vehicle body suspension elastic elements were connected to the cab and the frame, thus completing the creation of the vehicle body suspension bushings. Create the rear suspension bushing unit and the cargo box and frame rigid connection bushing unit in the same way, and assign the corresponding stiffness and damping parameters. The rear suspension bushing unit connects the rear suspension system to the frame, and the cargo box and frame rigid connection bushing unit connects the cargo box and the frame. After the creation of the rear suspension bushing unit and the cargo box and frame rigid connection bushing unit is completed. It should be noted that the cab and the frame are rigidly connected by studs, so the three-dimensional stiffness parameters of the Bush unit for the rigid connection between the cargo box and the frame are all assigned to 5000 N / mm. The front suspension spring-damper unit is created using the ADAMS dynamics simulation tool. The front suspension spring-damper unit is named Damper_Left and Damper_Right. The stiffness and damping parameters of the front suspension spring elastic unit are assigned to its corresponding spring-damper unit. The front suspension spring elastic unit connects the frame and the front suspension, thus completing the creation of the front suspension spring-damper unit. Finally, the dynamic model of the whole vehicle was built.

[0037] In addition, the second preset quantity can be 1 / 3 of the total number of simulation nodes.

[0038] Based on the above description, this step achieves an organic combination of distributed collaborative modeling and high-precision dynamic simulation. After obtaining the verified parameters pre-stored in the blockchain through any simulation node, the Body module of the ADAMS tool is used to represent system components such as the cab (TB) and cargo box (CheDou) as concentrated mass points with center of mass / mass / inertia parameters. At the same time, Bush elements (such as Left / Right / Rear suspensions) and Spring-Damper elements (Damper_Left / Right) are used to accurately restore the characteristics of the elastic damping system. This modular modeling method not only ensures the accurate assignment of physical parameters of key components such as the powertrain (PT) and chassis (CheJia), but also rigorously constructs special structures such as 24 body suspension points (PT_Left_N series) and 5000Nmm rigid connections through professional methods such as 2 Bod-1 Loc / 2 Bod-2 Loc, giving the whole vehicle model engineering-level topological accuracy.

[0039] After the model is built in this step, it needs to be broadcast to all nodes. It can only be uploaded to the chain after being verified and confirmed by 1 / 3 of the nodes. This mechanism ensures modeling quality and avoids single points of failure. All elastic elements (such as tire bushings and suspension bushings) are created according to the assembly logic and assigned measured stiffness / damping parameters. Special working conditions such as the cab-frame stud connection are clearly defined through three-dimensional stiffness parameters. This closed-loop process of "parameter-driven modeling - node collaborative verification - on-chain version fixation" solves the problems of parameter and model disconnect and chaotic version management in traditional simulation, providing a reliable digital prototype foundation for subsequent NVH analysis.

[0040] Step 130: By obtaining nodes, create vehicle response indicators under preset working conditions; among which, the vehicle response indicators include at least: seat rail vibration and steering wheel vibration; obtain simulation termination time settings and simulation step settings; obtain the completed vehicle dynamics model from the blockchain, run the vehicle dynamics model simulation calculation, and obtain the vibration isolation performance of the elastic damping system.

[0041] Among them, the vehicle response indicators include at least: seat rail vibration and steering wheel vibration.

[0042] Create vehicle response metrics under preset operating conditions, specifically: Create simulation boundary conditions; the boundary conditions include applying engine torque excitation under various operating conditions, creating vehicle response indicators under different operating conditions, and the vehicle response indicators include seat rail vibration and steering wheel vibration.

[0043] To further explain, in Adams View, vehicle response metrics are created under different operating conditions. The vehicle response metrics are: Startup_SW_F represents steering wheel vibration under startup conditions, Startup_SR_F represents seat rail vibration under startup conditions, Idle_SW_F represents steering wheel vibration under idling conditions, and Idle_SR_F represents seat rail vibration under idling conditions.

[0044] In some embodiments, "obtaining the simulation termination time setting, simulation step count setting, running the simulation calculation, and obtaining the vibration isolation performance of the elastic damping system" can specifically be as follows: setting simulation parameters using the ADAMS dynamic simulation tool, setting the simulation termination time to 5s, setting the simulation step count to 5000 steps, running the simulation calculation, and checking the overall vehicle vibration level; evaluating the vibration isolation performance of the elastic damping system; if the simulated value of the overall vehicle response is lower than the target value, then each elastic damping system is qualified; if the simulated value of the overall vehicle response exceeds the target value, then the stiffness and damping parameters of the elastic damping system need to be optimized.

[0045] Based on the above description, this step realizes a standardized evaluation process and quantitative analysis of the vehicle's vibration performance. By setting the engine torque excitation boundary conditions under preset operating conditions (start / idle), standardized response indicators such as Startup_SW_F (steering wheel vibration under start-up conditions) and Idle_SR_F (seat rail vibration under idle conditions) are established in ADAMS View, forming a complete evaluation system covering key occupant contact points. A 5-second simulation duration and a fine step size of 5000 steps are used to ensure that the vehicle dynamics model obtained from the blockchain accurately reflects the real vibration isolation performance of the elastic damping system (such as the Bush unit and Spring-Damper unit) under transient / steady-state conditions. This closed-loop verification mechanism of "operating condition definition - indicator quantification - threshold determination" allows engineers to directly compare simulation values ​​with target values ​​(such as whether steering wheel vibration exceeds the standard) to quickly determine the compliance of existing damping system parameter matching.

[0046] This step strongly correlates engine torque excitation with specific operating conditions (start-up / idle), enabling indicators such as Startup_SR_F to accurately reflect the vibration characteristics of vehicles in typical usage scenarios. The 5000-step high-resolution simulation setup captures the dynamic response details of damping components (such as the PT_Left_N suspension point), while blockchain ensures the evaluation model is consistent with the baseline model built in step 120. This binary judgment rule based on objective data—"simulation value - target value"—avoids the limitations of relying on subjective evaluation in traditional NVH tuning, providing a clear technical basis for the iterative optimization of the stiffness / damping parameters of elastic components.

[0047] Based on the above description, this application provides a blockchain-based method for simulating in-vehicle vibration using ADAMS: 1. By acquiring the parameters of various system components of the vehicle and the parameters of the elastic damping system, that is, by acquiring the component parameters (such as engine mass and suspension stiffness) and the damping system parameters (such as damping coefficient and rubber bushing stiffness), accurate input is provided for the multibody dynamics model, avoiding simulation distortion caused by missing parameters.

[0048] Example: If the engine mass of a certain vehicle model is 200kg and the suspension spring stiffness is 30kN / m, the parameters can be directly mapped to the concentrated mass point and elastic element after input, ensuring that the physical properties of the model are consistent with the real vehicle.

[0049] 2. By converting system components into lumped mass points (ADAMS tool), complex components (such as drive shafts and body frames) are simplified into lumped mass points, reducing the model's degrees of freedom, improving simulation efficiency, and preserving key dynamic characteristics.

[0050] Example: The vehicle frame is represented as multiple mass points (such as front and rear axle mass points, and mass points at the center of gravity). Inertial parameters are assigned using the ADAMS built-in algorithm to reduce the time required to solve differential equations.

[0051] 3. By equating the elastic damping system to an elastic element, the damping system (such as suspension and engine mount) is modeled as a spring-damping unit, and its vibration isolation efficiency (such as the transmissibility curve) is directly quantified to support accurate vibration prediction.

[0052] Example: The rubber bushing of a suspension system is modeled as a nonlinear spring damping element, and its force-displacement characteristic curve can simulate the vibration attenuation effect of a real vehicle on a bumpy road.

[0053] 4. By creating vehicle response indicators (seat rails, steering wheel vibration) under preset working conditions, key vibration indicators are defined, focusing on areas where users have obvious perception, thereby enhancing the practical guiding value of simulation results.

[0054] Example: Under engine cold start conditions, the model outputs the vibration amplitude of the steering wheel at the 12Hz frequency band. The error is less than 5% compared with the actual vehicle test data, verifying the model's accuracy.

[0055] 5. By setting the simulation termination time and number of steps, and adjusting the simulation step size (e.g., 0.001s) and total duration (e.g., 10s), high-frequency vibration details can be captured while avoiding waste of computational resources.

[0056] Example: For engine idling conditions (600rpm), setting the simulation step size to 0.0005s can accurately capture the resonance peak of 8-20Hz, while a step size of 0.01s will cause the loss of high-frequency signals.

[0057] In addition, this application Figure 2 This application provides a blockchain-based vehicle in-vehicle vibration simulation system as an embodiment. Figure 2 As shown in the embodiments of this application, the system mainly includes: Node 210 is used to acquire simulation parameters, which include parameters of various system components of the vehicle and parameters of the elastic damping system. The simulation parameters are broadcast to all verification nodes, and after receiving verification success information returned by a preset first number of verification nodes, they are uploaded to the blockchain.

[0058] Node 210 includes an acquisition unit. Used to obtain parameters of various system components of the vehicle; among which, the component parameters include at least: hard point coordinates, component mass, component center of gravity, and component inertia parameters of components such as cab, cargo box, powertrain, frame, and suspension system. Obtain the parameters of each elastic damping system of the whole vehicle; among them, the elastic damping system parameters include at least the stiffness, damping parameters, elastic center coordinates, and hard point coordinates of the powertrain mount, body mount, tire, suspension bushing, and suspension spring elastic damping system.

[0059] Those skilled in the art will understand that the acquisition node 210 allows any experimenter's server to initiate parameter submission as an acquisition node, which is then broadcast to a verification network (verification nodes) composed of expert terminals, overcoming the limitations of traditional single-point review. A 1 / 3 node consensus mechanism (e.g., at least 3 out of 9 verification nodes must confirm) ensures parameter rationality, avoiding both the bottleneck of excessive centralized review and preventing misjudgment by a single expert.

[0060] Node 210 allows for unified verification of the geometric properties (hard point coordinates, inertial parameters) and elastic damping system characteristics (stiffness / damping parameters) of the entire vehicle system components (cabin / frame, etc.), ensuring the integrity of the dynamic simulation input parameters. Design data is directly extracted from CAD / CAE software, eliminating errors from manual transcription.

[0061] Node 210 automatically triggers a re-acquisition process for parameters that have not reached the consensus threshold, forming a closed loop of "submission-verification-feedback". This mechanism forcibly solves the problem of parameter errors being passed to downstream simulations in the traditional mode, improving the reliability of NVH analysis from the source.

[0062] Simulation node 220 is used to obtain simulation parameters from the blockchain. Using the ADAMS dynamic simulation tool, each system component is equivalent to a lumped mass point, and the parameters of each system component in the simulation parameters are assigned to the corresponding lumped mass point. Each elastic damping system in the simulation parameters is equivalent to an elastic element, and the parameters of each elastic damping system are assigned to the corresponding elastic element. The connection relationship between each system component and each elastic element is obtained, and the construction of the whole vehicle dynamic model is completed. The completed whole vehicle dynamic model is broadcast to all simulation nodes. After receiving the verification success information returned by the second preset number of simulation nodes, it is uploaded to the blockchain.

[0063] Simulation node 220 includes component assembly units. This is used to convert each system component into a lumped mass point using the Body equivalent module of the ADAMS dynamics simulation tool; and to assign the parameters of each system component to the corresponding lumped mass point to build each Body containing the center of mass, mass, and inertial parameters.

[0064] In some embodiments, simulation node 220 can obtain parameters of various system components of the vehicle through CAD software (CREO, CATIA) or CAE software (ANSA, HyperMesh). The component parameters include hard point coordinates, component mass, component center of mass, component inertia parameters, etc. of system components such as cab, cargo box, powertrain, frame, and suspension. The parameters of various elastic damping systems of the vehicle can be obtained through the design drawings of the elastic damping system. The elastic damping system parameters include stiffness, damping parameters, elastic center point coordinates, hard point coordinates, etc. of elastic damping systems such as powertrain mounts, body mounts, tires, suspension bushings, and suspension springs.

[0065] Simulation node 220 can be specifically defined as follows: The powertrain mounting bush units were created using the ADAMS dynamics simulation tool 2 Bod-1 Loc method. The powertrain mounting bush units were named Left, Right, and Rear. The stiffness and damping parameters of the powertrain mounting elastic units were assigned to their respective bush units. The powertrain mounting elastic units connected the powertrain to the frame, thus completing the creation of the powertrain mounting bush units. Create a tire bush element using the same creation method, assign the corresponding stiffness and damping parameters, connect the tire bush element to the ground and suspension system, and complete the creation of the tire bush element; The vehicle body suspension bushings were created using the ADAMS dynamics simulation tool 2 Bod-2 Loc method. The vehicle body suspension bushings were named PT_Left_N (N=1,2,3,4) and PT_Right_N (N=1,2,3,4). The stiffness and damping parameters of the vehicle body suspension elastic elements were assigned to their corresponding bushings. The vehicle body suspension elastic elements were connected to the cab and the frame, thus completing the creation of the vehicle body suspension bushings. Create the rear suspension bushing unit and the cargo box and frame rigid connection bushing unit in the same way, and assign the corresponding stiffness and damping parameters. The rear suspension bushing unit connects the rear suspension system to the frame, and the cargo box and frame rigid connection bushing unit connects the cargo box and the frame. After the creation of the rear suspension bushing unit and the cargo box and frame rigid connection bushing unit is completed. It should be noted that the cab and the frame are rigidly connected by studs, so the three-dimensional stiffness parameters of the Bush unit for the rigid connection between the cargo box and the frame are all assigned to 5000 N / mm. The front suspension spring-damper unit is created using the ADAMS dynamics simulation tool. The front suspension spring-damper unit is named Damper_Left and Damper_Right. The stiffness and damping parameters of the front suspension spring elastic unit are assigned to its corresponding spring-damper unit. The front suspension spring elastic unit connects the frame and the front suspension, thus completing the creation of the front suspension spring-damper unit. Finally, the dynamic model of the whole vehicle was built.

[0066] Obtain node 230 to create vehicle response indicators under preset working conditions; the vehicle response indicators include at least: seat rail vibration and steering wheel vibration; obtain simulation termination time settings and simulation step settings; obtain the completed vehicle dynamics model from the blockchain, run the vehicle dynamics model simulation calculation, and obtain the vibration isolation performance of the elastic damping system.

[0067] To further explain, obtaining node 230 allows the creation of vehicle response metrics under different operating conditions in Adams View. The vehicle response metrics are: Startup_SW_F represents steering wheel vibration under startup conditions, Startup_SR_F represents seat rail vibration under startup conditions, Idle_SW_F represents steering wheel vibration under idling conditions, and Idle_SR_F represents seat rail vibration under idling conditions.

[0068] In some embodiments, node 230 can be obtained by setting simulation parameters using the ADAMS dynamic simulation tool, setting the simulation termination time to 5s, the simulation step count to 5000 steps, running the simulation calculation, and viewing the overall vehicle vibration level; evaluating the vibration isolation performance of the elastic damping system; if the simulated value of the overall vehicle response is lower than the target value, then each elastic damping system is qualified; if the simulated value of the overall vehicle response exceeds the target value, then the stiffness and damping parameters of the elastic damping system need to be optimized.

[0069] Based on the above description, this application provides a blockchain-based whole-vehicle in-vehicle vibration simulation system based on ADAMS: 1. By acquiring the parameters of various system components of the vehicle and the parameters of the elastic damping system, that is, by acquiring the component parameters (such as engine mass and suspension stiffness) and the damping system parameters (such as damping coefficient and rubber bushing stiffness), accurate input is provided for the multibody dynamics model, avoiding simulation distortion caused by missing parameters.

[0070] Example: If the engine mass of a certain vehicle model is 200kg and the suspension spring stiffness is 30kN / m, the parameters can be directly mapped to the concentrated mass point and elastic element after input, ensuring that the physical properties of the model are consistent with the real vehicle.

[0071] 2. By converting system components into lumped mass points (ADAMS tool), complex components (such as drive shafts and body frames) are simplified into lumped mass points, reducing the model's degrees of freedom, improving simulation efficiency, and preserving key dynamic characteristics.

[0072] Example: The vehicle frame is represented as multiple mass points (such as front and rear axle mass points, and mass points at the center of gravity). Inertial parameters are assigned using the ADAMS built-in algorithm to reduce the time required to solve differential equations.

[0073] 3. By equating the elastic damping system to an elastic element, the damping system (such as suspension and engine mount) is modeled as a spring-damping unit, and its vibration isolation efficiency (such as the transmissibility curve) is directly quantified to support accurate vibration prediction.

[0074] Example: The rubber bushing of a suspension system is modeled as a nonlinear spring damping element, and its force-displacement characteristic curve can simulate the vibration attenuation effect of a real vehicle on a bumpy road.

[0075] 4. By creating vehicle response indicators (seat rail and steering wheel vibration) under preset working conditions, defining key vibration indicators (such as seat rail vibration acceleration), focusing on areas that are clearly perceived by users, and improving the practical guiding value of simulation results.

[0076] Example: Under engine cold start conditions, the model outputs the vibration amplitude of the steering wheel at the 12Hz frequency band. The error is less than 5% compared with the actual vehicle test data, verifying the model's accuracy.

[0077] 5. By setting the simulation termination time and number of steps, and adjusting the simulation step size (e.g., 0.001s) and total duration (e.g., 10s), high-frequency vibration details can be captured while avoiding waste of computational resources.

[0078] Example: For engine idling conditions (600rpm), setting the simulation step size to 0.0005s can accurately capture the resonance peak of 8-20Hz, while a step size of 0.01s will cause the loss of high-frequency signals.

[0079] In addition, this application embodiment also provides a non-volatile computer storage medium storing executable instructions, which, when executed, implement the above-described blockchain-based vehicle in-vehicle vibration simulation method.

[0080] The technical solutions of this disclosure have been described in conjunction with the preceding embodiments. However, it will be readily understood by those skilled in the art that the scope of protection of this disclosure is not limited to these specific embodiments. Without departing from the technical principles of this disclosure, those skilled in the art can disassemble and combine the technical solutions in the above embodiments, and can also make equivalent changes or substitutions to the relevant technical features. Any changes, equivalent substitutions, improvements, etc., made within the technical concept and / or technical principles of this disclosure will fall within the scope of protection of this disclosure.

Claims

1. A method for simulating in-vehicle vibration based on blockchain, characterized in that, The method includes: Simulation parameters are acquired through any acquisition node. These simulation parameters include parameters of various system components of the vehicle and parameters of the elastic damping system. The simulation parameters are broadcast to all verification nodes. After receiving a preset number of successful verification messages from the verification nodes, the parameters are uploaded to the blockchain. Otherwise, an upload failure message is sent, and the simulation parameters are acquired again. The simulation parameters of the blockchain are obtained through any simulation node. Using the ADAMS dynamic simulation tool, each system component is equivalent to a lumped mass point, and the parameters of each system component in the simulation parameters are assigned to the corresponding lumped mass point. Each elastic damping system in the simulation parameters is equivalent to an elastic element, and the parameters of each elastic damping system are assigned to the corresponding elastic element. The connection relationship between each system component and each elastic element is obtained, and the construction of the whole vehicle dynamic model is completed. The completed whole vehicle dynamic model is broadcast to all simulation nodes. After receiving the verification success information returned by the second preset number of simulation nodes, it is uploaded to the blockchain. By obtaining nodes, vehicle response indicators under preset working conditions are created; among them, vehicle response indicators include at least: seat rail vibration and steering wheel vibration; simulation termination time setting and simulation step setting are obtained; the completed vehicle dynamics model is obtained from the blockchain, and the vehicle dynamics model simulation calculation is run to obtain the vibration isolation performance of the elastic damping system.

2. The vehicle interior vibration simulation method based on blockchain according to claim 1, characterized in that, Simulation parameters can be obtained through any acquisition node, specifically including: Obtain the parameters of each system component of the vehicle; among which, the component parameters include at least: hard point coordinates, component mass, component center of gravity, and component inertia parameters of the cab, cargo box, powertrain, frame, and suspension system components. Obtain the parameters of each elastic damping system of the whole vehicle; among them, the elastic damping system parameters include at least the stiffness, damping parameters, elastic center coordinates, and hard point coordinates of the powertrain mount, body mount, tire, suspension bushing, and suspension spring elastic damping system.

3. The vehicle interior vibration simulation method based on blockchain according to claim 1, characterized in that, Using the ADAMS dynamics simulation tool, each system component is represented as a lumped mass point, and the simulation parameters of each system component are assigned to the corresponding lumped mass point. Specifically, this includes: The Body equivalent module of the ADAMS dynamics simulation tool is used to convert each system component into a lumped mass point. The parameters of each system component are assigned to the corresponding centralized mass point to construct each body containing parameters of centroid, mass, and inertia.

4. The vehicle interior vibration simulation method based on blockchain according to claim 1, characterized in that, Each elastic damping system is equivalent to an elastic element, and the parameters of each elastic damping system are assigned to the corresponding elastic element, specifically including: Each elastic element is created according to the assembly logic of each system component, and each elastic damping system is equivalent to an elastic element through the elastic equivalent module of the ADAMS dynamic simulation tool; the elastic equivalent module of the tool includes: Bush or Spring-Damper elements; The parameters of each elastic damping system are assigned to the corresponding elastic element.

5. The vehicle interior vibration simulation method based on blockchain according to claim 1, characterized in that, Create vehicle response metrics under preset operating conditions, specifically including: Create simulation boundary conditions; the boundary conditions include applying engine torque excitation under various operating conditions, creating vehicle response indicators under different operating conditions, and the vehicle response indicators include seat rail vibration and steering wheel vibration.

6. A blockchain-based vehicle in-vehicle vibration simulation system, characterized in that, The system includes: The acquisition node is used to acquire simulation parameters, including parameters of various system components of the vehicle and parameters of the elastic damping system. The simulation parameters are broadcast to all verification nodes, and after receiving verification success information returned by a preset first number of verification nodes, they are uploaded to the blockchain. Simulation nodes are used to acquire simulation parameters from the blockchain. Using the ADAMS dynamics simulation tool, each system component is equivalent to a lumped mass point, and the parameters of each system component in the simulation parameters are assigned to the corresponding lumped mass point. Each elastic damping system in the simulation parameters is equivalent to an elastic element, and the parameters of each elastic damping system are assigned to the corresponding elastic element. The connection relationship between each system component and each elastic element is obtained, and the construction of the whole vehicle dynamics model is completed. The completed whole vehicle dynamics model is broadcast to all simulation nodes. After receiving the verification success information returned by the second preset number of simulation nodes, it is uploaded to the blockchain. Obtain nodes to create vehicle response indicators under preset working conditions; among which, the vehicle response indicators include at least: seat rail vibration and steering wheel vibration; obtain simulation termination time settings and simulation step settings; obtain the completed vehicle dynamics model from the blockchain, run the vehicle dynamics model simulation calculation, and obtain the vibration isolation performance of the elastic damping system.

7. The blockchain-based vehicle in-vehicle vibration simulation system according to claim 6, characterized in that, The node acquisition includes the acquisition unit. Used to obtain parameters of various system components of the vehicle; among which, the component parameters include at least: hard point coordinates, component mass, component center of gravity, and component inertia parameters of components such as cab, cargo box, powertrain, frame, and suspension system. Obtain the parameters of each elastic damping system of the whole vehicle; among them, the elastic damping system parameters include at least the stiffness, damping parameters, elastic center coordinates, and hard point coordinates of the powertrain mount, body mount, tire, suspension bushing, and suspension spring elastic damping system.

8. The blockchain-based vehicle in-vehicle vibration simulation system according to claim 6, characterized in that, Simulation nodes include component assembly units. Used to convert each system component into a lumped mass point using the Body equivalent module of the ADAMS dynamics simulation tool; The parameters of each system component are assigned to the corresponding centralized mass point to construct each body containing parameters of centroid, mass, and inertia.

9. The blockchain-based vehicle in-vehicle vibration simulation system according to claim 6, characterized in that, Simulation nodes include component building units. This tool is used to create each elastic element according to the assembly logic of each system component. The elastic damping system is equivalent to an elastic element through the elastic equivalent module of the ADAMS dynamic simulation tool. The elastic equivalent module of the tool includes: Bush or Spring-Damper elements. The parameters of each elastic damping system are assigned to the corresponding elastic element.

10. A non-volatile computer storage medium, characterized in that, It stores computer instructions, which, when executed, implement a blockchain-based whole-vehicle in-vehicle vibration simulation method as described in any one of claims 1-5.

Images