An engine crankshaft system noise identification and optimization method
By identifying and optimizing engine crankshaft system noise through dynamic simulation models, the problem of low-frequency knocking noise under idling and creeping conditions of hybrid engines was solved, reducing development costs and time, and improving vehicle NVH performance.
Patent Information
- Application Number
- CN202211094017.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2022-09-08
- Publication Date
- 2026-02-27
- Estimated Expiration
- 2042-09-08
AI Technical Summary
When the hybrid engine charges the battery under idling and creeping conditions, regular low-frequency knocking noise occurs between the crankshaft and the bearing housing, which affects the noise quality inside the vehicle and leads to a decrease in the overall NVH performance. Existing improvement methods are costly and have long development cycles.
By establishing a dynamic simulation model, vibration data of the crankshaft and main bearing housing are extracted, and the vibration mode is evaluated in combination with the working vibration mode to identify noise sources. Optimization strategies such as reducing in-cylinder combustion pressure, flywheel inertia, and main stage structural stiffness are adopted to optimize engine design to eliminate low-frequency knocking noise.
Effectively identify and optimize engine crankshaft system noise, reduce product development cycle and cost, avoid low-frequency knocking noise problems under idling or creeping conditions, and improve NVH performance.
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Figure CN116305599B_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of vehicles, in particular to an engine crankshaft system noise identification and optimization method. BACKGROUND
[0002] The hybrid engine charges the battery, and compared with the traditional power engine, there is a large load in the idling and crawling working conditions to charge the battery. During the charging process, a regular low-frequency knocking noise occurs between the crankshaft and the bearing seat, which affects the in-vehicle noise quality and leads to the decline of the NVH (Noise, Vibration, Harshness) performance of the whole vehicle.
[0003] The existing improvement method generally measures the noise of the engine physical prototype, and then modifies the design of the physical engine according to the measurement results, which leads to a long overall development cycle and high cost. SUMMARY
[0004] The present application solves the problem of how to realize efficient engine crankshaft system noise identification and optimization.
[0005] To solve the above problems, the present application provides an engine crankshaft system noise identification and optimization method.
[0006] In a first aspect, the present application provides an engine crankshaft system noise identification method, comprising:
[0007] Obtaining parameter data of the engine, and establishing a dynamics simulation model according to the parameter data;
[0008] Extracting working vibration mode of the crankshaft of the engine in the working state and vibration acceleration data of each main bearing seat of the engine from the dynamics simulation model;
[0009] Evaluating the vibration acceleration data of the main bearing seat close to the flywheel side of the crankshaft in combination with the working vibration mode, and if the evaluation result does not meet the preset evaluation standard, it is judged that noise occurs between the crankshaft and the bearing seat of the engine.
[0010] Optionally, the parameter data includes engine component models, engine structure parameters and load input data applied to the engine component models, and the establishment of the dynamics simulation model according to the parameter data comprises:
[0011] Establishing the dynamics simulation model according to the engine component models, the engine structure parameters and the load input data.
[0012] Optionally, the engine component models include a cylinder assembly geometry model, a crank-connecting rod mechanism geometry model, a torsional damper geometry model, and a flywheel assembly geometry model, and the establishing of the engine component models includes:
[0013] establishing the cylinder assembly geometry model, the crank-connecting rod mechanism geometry model, the torsional damper geometry model, and the flywheel assembly geometry model for the cylinder assembly, the crank-connecting rod mechanism, the torsional damper, and the flywheel assembly, respectively.
[0014] Optionally, the engine structure parameters include a cylinder bore, a stroke, a crank radius, a piston eccentricity, a cylinder bore eccentricity, a bearing bore diameter, and a reciprocating inertia mass, and the establishing of the dynamic simulation model according to the engine component models, the engine structure parameters, and the load input data includes:
[0015] inputting the cylinder bore, the stroke, the crank radius, the piston eccentricity, the cylinder bore eccentricity, the bearing bore diameter, and the reciprocating inertia mass into the dynamic simulation model to simplify the dynamic simulation model.
[0016] Optionally, the load input data includes cylinder pressure input data under an idling charging working condition and crankshaft bearing bore nonlinear spring stiffness data, and the establishing of the dynamic simulation model according to the engine component models, the engine structure parameters, and the load input data includes:
[0017] inputting the cylinder pressure input data under the idling charging working condition and the crankshaft bearing bore nonlinear spring stiffness data into the dynamic simulation model to load the engine component models.
[0018] Optionally, the establishing of the dynamic simulation model according to the parameter data further includes:
[0019] obtaining an FE grid model according to the engine component models, and establishing the dynamic simulation model according to the FE grid model, the engine structure parameters, and the load input data.
[0020] Optionally, the establishing of the dynamic simulation model according to the parameter data further includes:
[0021] determining an idling or creep charging rotating speed range and a load range according to a hybrid working scenario.
[0022] Optionally, the evaluating of the vibration acceleration data of the main bearing seat close to the flywheel side of the crankshaft in combination with the working vibration mode includes:
[0023] Put the vibration acceleration data into the CAE database for evaluation, if the evaluation result meets the preset evaluation standard, it is judged that the idle charge knocking noise does not appear between the crankshaft and the bearing seat, if the evaluation result does not meet the preset evaluation standard, it is judged that the idle charge knocking noise appears between the crankshaft and the bearing seat.
[0024] In a second aspect, the application provides an engine crankshaft system noise optimization method, comprising:
[0025] When the engine crankshaft system noise identification method according to any one of the above is used to judge that noise appears between the crankshaft and the bearing seat of the engine, optimization is carried out according to a preset optimization strategy until the evaluation result of the vibration acceleration data of the main bearing seat near the flywheel side of the crankshaft meets the preset evaluation standard.
[0026] Optionally, the preset optimization strategy includes reducing the in-cylinder combustion pressure, reducing the flywheel inertia, reducing the main stage structure bending stiffness, reducing the idle charge speed and load optimization.
[0027] The engine crankshaft system noise identification and optimization method of the application uses a dynamic simulation model to simulate the running state of the engine crankshaft system, and analyzes the simulation results, combines the working vibration mode of the crankshaft in the working state, and evaluates the vibration acceleration data of the main bearing seat near the flywheel side of the crankshaft. The working vibration mode of the knocking noise can be effectively identified and the noise problem can be locked. Various optimization methods including optimization of in-cylinder pressure amplitude or flywheel main stage stiffness distribution can be used to reduce low-frequency knocking noise, so as to completely solve the low-frequency knocking noise problem of the engine under idle or creeping conditions. The low-frequency knocking noise problem can be avoided in the early stage of product development, which can reduce the product development cycle and cost. BRIEF DESCRIPTION OF DRAWINGS
[0028] Figure 1 It is a flowchart of the engine crankshaft system noise identification method of the embodiment of the application;
[0029] Figure 2 It is a simulation analysis flowchart of the embodiment of the application;
[0030] Figure 3 It is a main bearing seat vibration response comparison schematic diagram of the embodiment of the application;
[0031] Figure 4 It is a static schematic diagram of the dynamic simulation model simulation output animation of the embodiment of the application;
[0032] Figure 5 It is an NVH comparison schematic diagram of the embodiment of the application. DETAILED DESCRIPTION
[0033] In order to make the above objectives, characteristics and advantages of the present application more apparent, more comprehensible, specific embodiments of the present application are described in detail below with reference to the accompanying drawings.
[0034] As shown in Figure 1 , the embodiment of the present application provides an engine crankshaft system noise identification method, comprising:
[0035] Obtaining parameter data of the engine, and establishing a dynamic simulation model according to the parameter data.
[0036] Specifically, as shown in Figure 2 , first, parameter collection is performed to obtain hybrid power assembly parameter data, such as crankshaft system drawings, cylinder block assembly and crankshaft system 3D geometric numerical model, engine structure parameters, engine idling charging operating speed and load, etc., which are collectively referred to as parameter data of the engine, and then a dynamic simulation model is established according to the parameter data. Generally, a CAE (Computer Aided Engineering) model can be established based on CAE, that is, a 3D model of a product is divided into smaller elements (Mesh) using a computer; a load (Load) and a boundary condition (Boundary) are applied to the geometric body, in this embodiment, mainly including engine idling charging speed and charging load, in-cylinder pressure data, cylinder block assembly geometry, crankshaft system and flywheel moment of inertia and stiffness data; and then a stiffness matrix is solved to determine the behavior (Result) and response (Response) generated.
[0037] Extracting working vibration mode of the crankshaft of the engine in a working state and vibration acceleration data of each main bearing seat of the engine from the dynamic simulation model.
[0038] Specifically, as shown in Figure 2 , after the dynamic simulation model is established, result extraction needs to be performed on the dynamic simulation model. The simulation output of the dynamic simulation model includes vibration acceleration response (0-600Hz) of each main bearing seat, dynamic working mode in a working state and corresponding animation (see Figure 4 ), from which the dynamic working mode of the crankshaft system under the idling charging condition is extracted, the knocking frequency corresponding to the flywheel deflection vibration is locked (whether the knocking peak value and the vibration mode are consistent is determined), and according to the calculation result, the surface vibration acceleration response of each main bearing seat of the cylinder block is extracted, and whether the surface vibration acceleration response of the main bearing seat close to the flywheel is related to the flywheel side cylinder working impact is analyzed.
[0039] Evaluating the vibration acceleration data of the main bearing seat close to the flywheel side of the crankshaft according to the working vibration mode, and if the evaluation result does not meet the preset evaluation standard, it is determined that noise occurs between the crankshaft and the bearing seat of the engine.
[0040] Specifically, in combination with Figure 2 After the result extraction and data analysis, evaluation and subsequent optimization are needed. For the evaluation process, the vibration acceleration data of the main bearing seat near the flywheel side is put into the CAE database for evaluation. If it exceeds the evaluation standard, it is judged that noise occurs between the crankshaft and the bearing seat. That is, according to the working vibration mode of the crankshaft in the working state and the vibration acceleration data of the main bearing seat, the noise between the crankshaft and the bearing seat can be judged. According to the correlation between the idle knocking noise level of multiple models and the vibration acceleration amplitude of the main bearing seat, the CAE evaluation limit value requirement meeting the NVH standard can be determined.
[0041] Optionally, the parameter data includes an engine component model, engine structure parameters, and load input data applied to the engine component model, and the establishing a dynamics simulation model according to the parameter data includes:
[0042] establishing the dynamics simulation model according to the engine component model, the engine structure parameters, and the load input data.
[0043] Specifically, the input of the dynamics simulation model includes:
[0044] (1) Model input: cylinder block assembly geometry model, crank connecting rod mechanism geometry model, TVD (torsional vibration damper) and flywheel assembly geometry model;
[0045] (2) Parameter input: engine structure parameters, such as cylinder bore, stroke, crank radius, piston eccentricity, cylinder hole eccentricity, bearing hole diameter, and reciprocating inertia mass, etc.
[0046] (3) Load input: cylinder pressure input under idle charging working condition, crank bearing hole nonlinear spring stiffness data (CAE and test benchmarking to obtain reference value);
[0047] According to the above engine component model, engine structure parameters, and load input data, a dynamics simulation model is established.
[0048] Optionally, the engine component model includes a cylinder block assembly geometry model, a crank connecting rod mechanism geometry model, a torsional vibration damper geometry model, and a flywheel assembly geometry model, and the establishing process of the engine component model includes:
[0049] The cylinder block assembly geometry model, the crank connecting rod mechanism geometry model, the torsional vibration damper geometry model, and the flywheel assembly geometry model are established for the cylinder block assembly, the crank connecting rod mechanism, the torsional vibration damper, and the flywheel assembly, respectively.
[0050] Specifically, since the CAE model is a time-varying system of multi-body dynamics, the simulation model should be gradually simplified according to the idling charging working condition, for example, the engine main body part is modeled as a cylinder block assembly, a TVD, a crankshaft, a double-mass flywheel and other component entities, that is, a cylinder block assembly geometric model, a crank connecting rod mechanism geometric model, a torsional vibration damper geometric model and a flywheel assembly geometric model are respectively established for the cylinder block assembly, the crank connecting rod mechanism, the torsional vibration damper and the flywheel assembly.
[0051] Optionally, the engine structure parameters include a cylinder bore, a stroke, a crank radius, a piston eccentricity, a cylinder hole eccentricity, a bearing hole diameter and a reciprocating inertia mass, and the establishing the dynamics simulation model according to the engine component model, the engine structure parameters and the load input data includes:
[0052] inputting the cylinder bore, the stroke, the crank radius, the piston eccentricity, the cylinder hole eccentricity, the bearing hole diameter and the reciprocating inertia mass into the dynamics simulation model to simplify the dynamics simulation model.
[0053] Specifically, the gradually simplifying the simulation model further includes: inputting a connecting rod, a piston and simplified information such as mass and inertia into the CAE simulation model, that is, inputting the cylinder bore, the stroke, the crank radius, the piston eccentricity, the cylinder hole eccentricity, the bearing hole diameter and the reciprocating inertia mass as simplified information into the dynamics simulation model.
[0054] Optionally, the load input data includes cylinder pressure input data under the idling charging working condition and non-linear spring stiffness data of a crankshaft bearing hole, and the establishing the dynamics simulation model according to the engine component model, the engine structure parameters and the load input data includes:
[0055] inputting the cylinder pressure input data under the idling charging working condition and the non-linear spring stiffness data of the crankshaft bearing hole into the dynamics simulation model to load the engine component model.
[0056] Specifically, the gradually simplifying the simulation model further includes: adopting a non-linear spring unit between each journal of a crankshaft system and a bearing bush, and inputting an experience value consistent with the results of the previous CAE and test as a spring stiffness parameter.
[0057] Optionally, the establishing the dynamics simulation model according to the parameter data further includes:
[0058] obtaining an FE grid model according to the engine component model, and establishing the dynamics simulation model according to the FE grid model, the engine structure parameters and the load input data.
[0059] Specifically, in combination with Figure 2As shown, after parameter collection, finite element (FE) meshing is required for the engine component model, the mesh size can be set according to the requirements of the tester, the quality matrix and stiffness matrix of the FE mesh model are extracted, and a dynamic simulation model is established according to the extracted model.
[0060] Optionally, the dynamic simulation model established according to the parameter data further comprises:
[0061] According to the hybrid working scene, the idle speed or the creep charging speed range and the load range are determined.
[0062] Specifically, during simulation, the model needs to be loaded with load and boundary conditions, that is, the cylinder pressure data of the hybrid idle charging working condition is applied, and according to the hybrid working scene, the idle speed or the creep charging speed range and the load range are determined, and after the boundary confirmation, the simulation model is solved.
[0063] Optionally, the vibration acceleration data of the main bearing seat close to the flywheel side of the crankshaft is evaluated in combination with the working vibration mode, and the vibration acceleration data of the main bearing seat close to the flywheel side of the crankshaft is evaluated in combination with the working vibration mode.
[0064] The vibration acceleration data is put into the CAE database for evaluation, and if the evaluation result meets the preset evaluation standard, it is judged that the idle charging knocking noise does not occur between the crankshaft and the bearing seat, and if the evaluation result does not meet the preset evaluation standard, it is judged that the idle charging knocking noise occurs between the crankshaft and the bearing seat.
[0065] Specifically, during evaluation, the vibration acceleration data of the main bearing seat close to the flywheel side is put into the CAE database for evaluation, and if the evaluation standard is met, there is no idle charging knocking noise NVH risk, and if the evaluation standard is exceeded, it is judged that the idle charging knocking noise occurs between the crankshaft and the bearing seat.
[0066] Another embodiment of the application provides an engine crankshaft system noise optimization method, comprising:
[0067] When it is judged according to the above-mentioned engine crankshaft system noise identification method that noise occurs between the crankshaft and the bearing seat of the engine, optimization is performed according to the preset optimization strategy until the evaluation result of the vibration acceleration data of the main bearing seat close to the flywheel side of the crankshaft meets the preset evaluation standard.
[0068] Specifically, when it is judged that noise occurs between the crankshaft and the bearing seat, optimization is performed according to the preset optimization strategy until the CAE evaluation standard is met to avoid low-frequency knocking noise problems. Figure 3 and Figure 5As shown, the original flywheel does not meet the NVH target (NVH optimization target), flywheel main stage stiffness optimization A, although optimized relative to the original flywheel, still does not meet the NVH target, after adjusting the optimization scheme, flywheel main stage stiffness optimization B and flywheel main stage stiffness optimization C meet the NVH target.
[0069] Optionally, the preset optimization strategy includes reducing in-cylinder combustion pressure, reducing flywheel inertia, reducing main stage structure bending stiffness, reducing idle charging speed and load optimization.
[0070] Specifically, when it is judged that noise occurs between the crankshaft and the bearing seat, optimization needs to be performed from the aspects of reducing in-cylinder combustion pressure, flywheel inertia and main stage structure bending stiffness, and idle charging speed and load optimization, until the CAE evaluation standard is met, so as to avoid low-frequency knocking noise problems. By optimizing the flywheel main stage structure stiffness distribution or optimizing the in-cylinder combustion pressure, the flywheel axial swing is reduced, the force between the crankshaft main journal and the bearing seat caused by the flywheel swing is changed, the main bearing seat surface vibration acceleration response is reduced, and thus the engine low-frequency knocking noise problem (150Hz-400Hz) under idle or creeping working conditions is completely solved.
[0071] Although the present application is disclosed as above, the protection scope of the present application is not limited to this. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present application, and these changes and modifications will fall within the protection scope of the present application.
Claims
1. A method for noise identification in an engine crankshaft system, characterized in that, include: Obtain engine parameter data and establish a dynamic simulation model based on the parameter data; The working vibration mode of the crankshaft of the engine under working conditions and the vibration acceleration data of each main bearing housing of the engine are extracted from the dynamic simulation model. The vibration acceleration data of the main bearing housing on the flywheel side near the crankshaft is evaluated based on the working vibration mode. If the evaluation result does not meet the preset evaluation criteria, it is determined that noise occurs between the crankshaft and the bearing housing of the engine. The parameter data includes engine component models, engine structural parameters, and load input data applied to the engine component models. The step of establishing a dynamic simulation model based on the parameter data includes: The dynamic simulation model is established based on the engine component model, the engine structural parameters, and the load input data. The load input data includes cylinder pressure input data under idling charging conditions and crankshaft bearing bore nonlinear spring stiffness data. The step of establishing the dynamic simulation model based on the engine component model, the engine structural parameters, and the load input data includes: The cylinder pressure input data under the idling charging condition and the nonlinear spring stiffness data of the crankshaft bearing bore are input into the dynamic simulation model to apply loads to the engine component model.
2. The engine crankshaft system noise identification method according to claim 1, characterized in that, The engine component model includes a cylinder block assembly geometric model, a crankshaft and connecting rod mechanism geometric model, a torsional vibration damper geometric model, and a flywheel assembly geometric model. The process of establishing the engine component model includes: Geometric models of the cylinder block assembly, crank-connecting rod mechanism, torsional vibration damper, and flywheel assembly are established for the cylinder block assembly, crank-connecting rod mechanism, torsional vibration damper, and flywheel assembly, respectively.
3. The engine crankshaft system noise identification method according to claim 1, characterized in that, The engine structural parameters include cylinder bore, stroke, crank radius, piston eccentricity, cylinder bore eccentricity, bearing bore diameter, and reciprocating inertial mass. The establishment of the dynamic simulation model based on the engine component model, the engine structural parameters, and the load input data includes: The cylinder diameter, stroke, crank radius, piston eccentricity, cylinder bore eccentricity, bearing bore diameter, and reciprocating inertial mass are input into the dynamic simulation model to simplify the dynamic simulation model.
4. The engine crankshaft system noise identification method according to claim 1, characterized in that, The step of establishing a dynamic simulation model based on the parameter data also includes: The FE mesh model is obtained based on the engine component model, and the dynamic simulation model is established based on the FE mesh model, the engine structural parameters, and the load input data.
5. The engine crankshaft system noise identification method according to claim 1, characterized in that, The step of establishing a dynamic simulation model based on the parameter data also includes: Determine the idle or creep charging speed range and load range based on the hybrid power operating scenario.
6. The engine crankshaft system noise identification method according to claim 1, characterized in that, The evaluation of the vibration acceleration data of the main bearing housing on the flywheel side near the crankshaft, in conjunction with the working vibration mode, includes: The vibration acceleration data is placed into a CAE database for evaluation. If the evaluation result meets the preset evaluation criteria, it is determined that no idling charging knocking noise occurs between the crankshaft and the bearing housing. If the evaluation result does not meet the preset evaluation criteria, it is determined that idling charging knocking noise occurs between the crankshaft and the bearing housing.
7. A method for optimizing engine crankshaft system noise, characterized in that, include: When the engine crankshaft system noise identification method according to any one of claims 1 to 6 determines that noise occurs between the engine crankshaft and the bearing housing, optimization is performed according to a preset optimization strategy until the evaluation result of the vibration acceleration data of the main bearing housing on the flywheel side near the crankshaft meets the preset evaluation criteria.
8. The engine crankshaft system noise optimization method according to claim 7, characterized in that, The preset optimization strategies include reducing in-cylinder combustion pressure, reducing flywheel inertia, reducing main stage structural bending stiffness, reducing idle charging speed, and load optimization.
Citation Information
Patent Citations
Prediction method for abnormal knocking sound of small end of connecting rod
CN114997023A