CN-121973584-A - Semi-active suspension vibration reduction method and system for electric vehicle based on magnetorheological fluid damper

CN121973584ACN 121973584 ACN121973584 ACN 121973584ACN-121973584-A

Abstract

The invention relates to the technical field of automobile vibration reduction, in particular to a method and a system for vibration reduction of a semi-active suspension of an electric automobile based on a magnetorheological fluid damper, wherein a vehicle road simulation test bed is utilized to test a target suspension according to a preset scheme, and an initial vibration reduction performance data set is obtained; the method comprises the steps of carrying out deviation analysis by combining the structural characteristics of the whole vehicle, outputting an influence coefficient set to adjust initial data to obtain an optimized data set, predicting performance attenuation according to a plurality of preset mileage intervals according to the road environmental characteristics of a common driving area, outputting an attenuation coefficient set and correcting the optimized data to generate a multi-stage predicted data set, synthesizing each mileage interval and the predicted data set to generate a self-adaptive semi-active suspension vibration damping control result, realizing accurate mapping from static test in a laboratory to dynamic application of the whole life cycle of the real vehicle, effectively solving the problems that the traditional method ignores the coupling effect of the whole vehicle and the long-term service performance degradation, and remarkably improving the self-adaptability and long-term reliability of vibration damping control.

Inventors

LU HE
DENG RUI
DING HONGXING
LI LONGHAI

Assignees

连云港师范学院

Dates

Publication Date: 20260505
Application Date: 20260319

Claims (10)

1. The method for damping the vibration of the semi-active suspension of the electric automobile based on the magnetorheological fluid damper is characterized by comprising the following steps of: According to a preset test scheme, a vehicle road simulation test bed is utilized to test vibration damping performance of a target semi-active suspension, and an initial vibration damping performance data set is obtained; Performing vibration damping performance deviation analysis by combining the whole vehicle structural characteristics of the electric vehicle where the target semi-active suspension is positioned, outputting a vibration damping performance influence coefficient set, and adjusting the initial vibration damping performance data set to obtain an optimized vibration damping performance data set; combining the road environment characteristics of the target semi-active suspension common driving area, performing damping performance attenuation prediction according to a plurality of preset driving mileage intervals, outputting a plurality of predicted damping performance attenuation coefficient sets, and respectively correcting the optimized damping performance data sets to obtain a plurality of predicted damping performance data sets; And generating a semi-active suspension vibration damping control result according to the plurality of preset driving mileage intervals and the plurality of predicted vibration damping performance data sets.
2. The method for damping vibration of an electric vehicle semi-active suspension based on a magnetorheological fluid damper according to claim 1, wherein the step of performing a vibration damping performance test on a target semi-active suspension by using a vehicle road simulation test bed according to a preset test scheme to obtain an initial vibration damping performance data set comprises the following steps: Acquiring a preset test scheme, wherein the preset test scheme comprises test indexes, a test flow and parameter configuration, and the test indexes at least comprise vehicle body acceleration, suspension dynamic deflection, tire dynamic displacement, damping adjustment response speed and damping energy consumption rate; and based on the test indexes, according to the test flow and parameter configuration, carrying out multi-station road surface loading test on the semi-active suspension carrying the magnetorheological fluid damper by using a vehicle road simulation test bed, and outputting an initial vibration damping performance data set.
3. The method for damping vibration of an electric vehicle semi-active suspension based on a magnetorheological fluid damper according to claim 2, wherein the step of performing vibration damping performance deviation analysis by combining the whole vehicle structural characteristics of the electric vehicle in which the target semi-active suspension is located and outputting a vibration damping performance influence coefficient set comprises the steps of: Acquiring the whole vehicle structural characteristics of an electric vehicle in which a target semi-active suspension is positioned, wherein the whole vehicle structural characteristics at least comprise vehicle type, preparation quality, chassis structural form and axle load distribution; obtaining structural attribute information of a target semi-active suspension, and expanding the structural attribute information according to a preset characteristic tolerance interval to obtain a structural attribute interval, wherein the structural attribute information at least comprises damper specification, suspension configuration, spring stiffness and lower swing arm mechanical parameters; taking a target semi-active suspension as a guide, taking the structural attribute interval as a retrieval comparison condition, taking a preset time range as a constraint, and carrying out sample data retrieval by utilizing a big data technology to obtain a sample whole vehicle structural feature set and a plurality of sample vibration reduction performance influence coefficient sets; adopting the whole sample structure feature set as input, adopting the plurality of sample vibration reduction performance influence coefficient sets as supervision, training a BP neural network until convergence, and obtaining a vibration reduction performance influence analysis model; And carrying out vibration damping performance deviation analysis according to the whole vehicle structural characteristics by using the vibration damping performance influence analysis model, and outputting a vibration damping performance influence coefficient set, wherein the vibration damping performance influence coefficients correspond to the test indexes one by one.
4. The method for damping vibration of an electric vehicle semi-active suspension based on a magnetorheological fluid damper according to claim 3, wherein the step of retrieving sample data by using a big data technology to obtain a sample whole vehicle structural feature set and a plurality of sample vibration damping performance influence coefficient sets comprises the following steps: searching sample data by utilizing a big data technology, acquiring a plurality of sample whole vehicle structural features meeting the structural attribute interval and the preset time range, and constructing a sample whole vehicle structural feature set; acquiring a plurality of historical vibration reduction data of different sample whole vehicle structural features under actual running loads, and carrying out mapping deviation comparison according to the plurality of historical vibration reduction data and a plurality of vibration reduction test data under the same test pavement load based on the test indexes to obtain a plurality of index deviation sets, and calculating to obtain an index deviation mean value set as a sample vibration reduction performance influence coefficient set to obtain a plurality of sample vibration reduction performance influence coefficient sets, wherein the index deviation is the ratio of the difference value between the historical vibration reduction data and the vibration reduction test data to the vibration reduction test data.
5. The method for damping vibration of an electric vehicle semi-active suspension based on a magnetorheological fluid damper according to claim 1, wherein the combining the road environment characteristics of the target semi-active suspension common driving area, performing damping performance damping prediction according to a plurality of preset driving range intervals, and outputting a plurality of predicted damping performance damping coefficient sets comprises: Configuring a plurality of preset driving mileage intervals according to preset mileage intervals; Acquiring road environment characteristics of a common driving area of the target semi-active suspension, wherein the road environment characteristics comprise road surface flatness distribution, annual average driving temperature difference, road ponding frequency and bumpy road section occupation ratio; obtaining a damping performance attenuation prediction model based on BP neural network training; and respectively carrying out damping performance attenuation prediction according to a plurality of preset driving mileage intervals by using the damping performance attenuation prediction model according to the road environment characteristics, and outputting a plurality of predicted damping performance attenuation coefficient sets.
6. The method for damping vibration of an electric vehicle semi-active suspension based on a magnetorheological fluid damper according to claim 5, wherein the training based on the BP neural network to obtain the damping performance damping prediction model comprises the following steps: Collecting a sample driving mileage set and a sample road environment characteristic set according to historical operation and maintenance monitoring records of the same type of magnetorheological fluid semi-active suspension, counting performance attenuation ratios of a plurality of test indexes under different sample driving mileage and sample environment characteristics, setting the performance attenuation ratios as sample performance attenuation coefficients, and obtaining a sample performance attenuation coefficient set; And training the BP neural network until convergence by taking the sample driving mileage set and the sample road environment characteristic set as inputs and taking the sample performance attenuation coefficient set as supervision to obtain a vibration reduction performance attenuation prediction model.
7. The method of damping vibration of an electric vehicle semi-active suspension based on a magnetorheological fluid damper of claim 1, wherein generating semi-active suspension damping control results from the plurality of preset range intervals and the plurality of predicted damping performance data sets comprises: and mapping and combining the plurality of preset driving mileage intervals and the plurality of predicted vibration damping performance data sets to generate a semi-active suspension vibration damping control parameter table which is suitable for different use stages, and taking the semi-active suspension vibration damping control parameter table as a semi-active suspension vibration damping control result.
8. An electric vehicle semi-active suspension vibration reduction system based on a magnetorheological fluid damper, the system comprising: the bench test module is used for testing vibration damping performance of the target semi-active suspension by utilizing the vehicle road simulation test bed according to a preset test scheme to obtain an initial vibration damping performance data set; the structure correction module is used for carrying out vibration reduction performance deviation analysis by combining the whole vehicle structural characteristics of the electric vehicle where the target semi-active suspension is positioned, outputting a vibration reduction performance influence coefficient set, and adjusting the initial vibration reduction performance data set to obtain an optimized vibration reduction performance data set; the damping prediction module is used for carrying out damping performance damping prediction according to a plurality of preset driving mileage intervals by combining with the road environment characteristics of the target semi-active suspension common driving area, outputting a plurality of predicted damping performance damping coefficient sets, and respectively correcting the optimized damping performance data sets to obtain a plurality of predicted damping performance data sets; and the control generation module is used for generating a semi-active suspension vibration damping control result according to the plurality of preset driving mileage intervals and the plurality of predicted vibration damping performance data sets.
9. A magnetorheological fluid damper-based electric vehicle semi-active suspension vibration damping device, characterized in that the device comprises a memory, a processor and a magnetorheological fluid damper-based electric vehicle semi-active suspension vibration damping program stored on the memory and operable on the processor, wherein the magnetorheological fluid damper-based electric vehicle semi-active suspension vibration damping program is configured to implement the steps of the magnetorheological fluid damper-based electric vehicle semi-active suspension vibration damping method according to any one of claims 1 to 7.
10. A computer readable storage medium, wherein the computer readable storage medium stores a magnetorheological fluid damper-based electric vehicle semi-active suspension damping program, and the magnetorheological fluid damper-based electric vehicle semi-active suspension damping program when executed by a processor implements the steps of the magnetorheological fluid damper-based electric vehicle semi-active suspension damping method according to any one of claims 1 to 7.

Description

Semi-active suspension vibration reduction method and system for electric vehicle based on magnetorheological fluid damper Technical Field The invention relates to the technical field of automobile vibration reduction, in particular to an electric automobile semi-active suspension vibration reduction method and system based on a magnetorheological fluid damper. Background With the rapid development of electric automobile technology, vehicle running smoothness and riding comfort become one of important indexes for measuring the performance of the whole automobile. Semi-active suspension systems are widely used in high-end electric vehicles because of their good damping properties and low energy consumption. The semi-active suspension based on the magnetorheological fluid damper has the advantages of high response speed, continuously adjustable damping, high control precision and the like, and becomes a hot spot for research and application of the current intelligent suspension system. However, in the actual use process of the existing semi-active suspension, the vibration damping performance of the existing semi-active suspension is not only influenced by the structural parameters of the existing semi-active suspension, but also is closely related to the mass distribution, the running working condition and the long-term service environment of the whole vehicle, so that the vibration damping data obtained by laboratory tests are difficult to accurately reflect the actual performance of the vehicle in the whole life cycle. At present, most vibration damping performance evaluation methods depend on bench tests or simulation analysis under standard working conditions, lack comprehensive consideration of multi-factor coupling effect in actual running of vehicles, and especially neglect matching influence of structural features of different vehicle types on suspension performance and performance time-varying attenuation problem caused by complex road environment. In addition, the magnetorheological fluid damper is easily affected by factors such as temperature change, road surface excitation, sealing aging and the like in the long-term use process, so that the damping force output is reduced, and the dynamic regulation and control capability of a suspension system is further weakened. Therefore, it has been difficult for conventional static test methods to meet the high-precision, long-period, adaptive vibration damping control requirements. The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art. Disclosure of Invention The invention mainly aims to provide a damping method and a damping system for an electric vehicle semi-active suspension based on a magnetorheological fluid damper, and aims to solve the technical problem that laboratory test data are difficult to accurately reflect actual damping efficiency in a full life cycle of a vehicle due to neglecting structural feature matching of the whole vehicle, complex road environment influence and long-term service performance attenuation in the conventional semi-active suspension damping evaluation method. In order to achieve the above purpose, the invention provides a method for damping vibration of a semi-active suspension of an electric vehicle based on a magnetorheological fluid damper, which comprises the following steps: According to a preset test scheme, a vehicle road simulation test bed is utilized to test vibration damping performance of a target semi-active suspension, and an initial vibration damping performance data set is obtained; Performing vibration damping performance deviation analysis by combining the whole vehicle structural characteristics of the electric vehicle where the target semi-active suspension is positioned, outputting a vibration damping performance influence coefficient set, and adjusting the initial vibration damping performance data set to obtain an optimized vibration damping performance data set; combining the road environment characteristics of the target semi-active suspension common driving area, performing damping performance attenuation prediction according to a plurality of preset driving mileage intervals, outputting a plurality of predicted damping performance attenuation coefficient sets, and respectively correcting the optimized damping performance data sets to obtain a plurality of predicted damping performance data sets; And generating a semi-active suspension vibration damping control result according to the plurality of preset driving mileage intervals and the plurality of predicted vibration damping performance data sets. Optionally, according to a preset test scheme, the vibration damping performance test is performed on the target semi-active suspension by using a vehicle road simulation test stand, and the initial vibration damping performance data set is obt