Gear modification method for reducing gear noise

Abstract

The invention belongs to the technical field of new energy automobile noise optimization, and particularly relates to a gear modification method for reducing gear noise, which comprises the following steps: S1, constructing a gear transmission system model; s2, simulating gear transmission performance under different load conditions and extracting key parameters; s3, shaping parameters to be optimized are set; s4, performing optimization calculation on each to-be-optimized modification parameter by taking reduction of a transmission error and improvement of a gear contact area as targets; in the optimization calculation process, according to a preset weight distribution strategy, weight proportions are set for different operation conditions and used for representing priorities of all the operation conditions; and S5, adjusting the numerical value of the modification parameter in the optimization result in the step S4, so that the transmission error curve is in a sine or cosine trend under all operation conditions. According to the method, smoothing of a transmission error curve, optimization of tooth surface contact performance and uniformization of edge load distribution can be achieved within the full working condition range, gear meshing noise is remarkably reduced, and the noise quality of a whole vehicle is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of new energy vehicle noise optimization, and particularly relates to a gear modification method for reducing gear noise. Background Art

[0002] With the rapid development of new energy vehicle products and the continuous improvement of consumers' requirements for driving experience, the noise problem has gradually become the focus of attention of vehicle manufacturers and consumers. Compared with traditional fuel vehicles, the electric drive assembly of new energy vehicles lacks the masking effect provided by sound sources such as engines, making the noise of the electric drive system more prominent. As one of the main sound sources of the electric drive assembly, the quality of the reducer gear meshing noise directly affects the noise quality of the whole vehicle, and thus affects the driving experience of consumers. Therefore, reducing gear meshing noise has become an important link in enhancing the competitiveness of new energy vehicle products.

[0003] Currently, the main method for reducing gear meshing noise is to optimize gear modification to reduce the transmission error and make it meet the design target value. However, although this method reduces noise to a certain extent, it does not completely solve the gear noise problem and still has the following limitations: 1. The influence of different working conditions is not fully considered. Existing technologies usually optimize the transmission error based on static or single working conditions and fail to dynamically adjust the optimization weight according to different operating conditions (such as different loads, speeds, etc.). This results in the transmission error being difficult to achieve the optimal balance within the full range of working conditions, especially in extreme working conditions, where the noise problem may be further exacerbated. 2. The problem of sudden changes in the shape of the transmission error curve. Changes in gear meshing stiffness and contact ratio will cause non-periodic sudden changes (such as sawtooth fluctuations) in the transmission error curve. This sudden change will trigger significant high-frequency noise, and existing technologies do not put forward specific requirements for the shape of the transmission error curve, resulting in the optimized transmission error having a low value but the curve shape may still cause noise problems. 3. Uneven edge load distribution. In actual operation, load concentration is likely to occur in the edge areas of the gear tooth surface contact area at the tooth tip, tooth root, and both ends of the tooth direction. This uneven load distribution not only exacerbates the noise but also may cause premature wear or even failure of the tooth surface. However, the existing gear modification methods are insufficient in this regard and are difficult to effectively improve the tooth surface contact performance.

[0004] The root causes of the above problems are as follows: 1. Lack of global optimization strategy: Existing methods are mostly based on a single objective (such as minimizing transmission error), and fail to comprehensively consider multiple performance indicators (such as transmission error, tooth surface contact area, edge load distribution, etc.) within the full operating conditions. 2. Insufficient modeling of dynamic characteristics: The dynamic response characteristics of the gear transmission system are complex under different operating conditions, and existing methods fail to accurately simulate these characteristics, resulting in a deviation between the optimization results and the actual operating conditions. 3. Insufficient constraints on modification parameters: Traditional modification methods have less constraints on the tooth surface contact performance (such as the edge load distribution of the tooth surface), making it difficult to achieve comprehensive optimization.

[0005] The solutions to these problems are somewhat difficult, mainly reflected in the following aspects: 1. The complexity of multi-objective optimization: It is necessary to simultaneously consider multiple objectives such as transmission error, tooth surface contact area, and edge load distribution, and there may be conflicts between these objectives, increasing the complexity of optimization. 2. The challenge of full operating condition coverage: The gear performance varies greatly under different operating conditions. How to reasonably allocate the optimization weights for each operating condition and achieve performance balance within the full operating conditions is a difficult point. 3. The demand for computing resources: Accurately simulating the dynamic response characteristics of the gear transmission system requires a large amount of computing resources, which poses higher requirements for the efficiency of the optimization algorithm.

[0006] Therefore, how to achieve the smoothing of the transmission error curve, the optimization of the tooth surface contact performance, and the uniformity of the edge load distribution within the full operating conditions through a new gear modification method, so as to significantly reduce the gear meshing noise and improve the noise quality of the whole vehicle, has become an urgent problem to be solved at present. Summary of the Invention

[0007] In view of the above deficiencies of the prior art, the present invention provides a gear modification method for reducing gear noise, which can achieve the smoothing of the transmission error curve, the optimization of the tooth surface contact performance, and the uniformity of the edge load distribution within the full operating conditions, thereby significantly reducing the gear meshing noise and improving the noise quality of the whole vehicle.

[0008] To solve the above technical problems, the present invention adopts the following technical solutions:

[0009] A gear modification method for reducing gear noise, comprising the following steps:

[0010] S1. Construct a gear transmission system model including gear geometric parameters, material properties, and load condition information;

[0011] S2. Based on the gear transmission system model, simulate the gear transmission performance under different load conditions, analyze the gear transmission performance to extract key parameters, where the key parameters are used to reflect the defects of the gear in the initial state; and calculate the numerical values of the key parameters in the initial state under different load conditions.

[0012] S3. Set the modification parameters to be optimized based on the key parameters extracted in S2; the modification parameters to be optimized include gear tooth direction inclination, tooth direction crowning, tooth profile inclination, and tooth profile crowning.

[0013] S4. With the goal of reducing transmission error and increasing the gear contact area, perform optimization calculations (genetic iteration algorithm) on each modification parameter to be optimized based on the gear transmission system model; during the optimization calculation process, according to the preset weight distribution strategy, set the weight ratio for different operating conditions to represent the priority of each operating condition; the operating conditions include load conditions.

[0014] S5. Adjust the numerical values of the modification parameters in the optimization results of S4 so that the transmission error curve shows a sine or cosine trend under all operating conditions.

[0015] S6. Take the modification parameters with adjusted numerical values in S5 as the final modification parameters to complete the gear modification optimization.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] 1. Realize the optimization of transmission error within the full operating conditions. This method calculates the transmission error under different load conditions based on the gear transmission system model and combines the weight distribution strategy to assign the priority of each operating condition. This method overcomes the limitation in the prior art that does not fully consider the influence of different operating conditions and realizes the optimal balance of transmission error within the full operating conditions. Compared with the prior art: The traditional method only optimizes for a single operating condition or static conditions and is difficult to adapt to the complex and changeable actual operating environment. However, this method significantly improves the control effect of transmission error within the full operating conditions by dynamically adjusting the optimization weight.

[0018] 2. Improve the shape of the transmission error curve. During the optimization process, this method particularly emphasizes that the transmission error curve shows a sine or cosine trend under all operating conditions. This smoothed curve shape effectively avoids the high-frequency noise problem caused by sudden changes in transmission error (such as sawtooth fluctuations). Compared with the prior art: The prior art does not put forward specific requirements for the shape of the transmission error curve, resulting in significant noise that may still be caused by curve mutations even if the transmission error value is low. This method fundamentally solves this problem by clarifying the requirements for the curve shape.

[0019] 3. Improve the comprehensive performance within the full operating conditions. This method aims to reduce the transmission error and increase the tooth surface contact area, and uses a multi-objective optimization algorithm to optimize the gear modification parameters (tooth direction tilt, tooth direction crown, tooth profile tilt, tooth profile crown). The finally output modification parameters can achieve a good comprehensive performance balance within the full operating conditions. Compared with the existing technology: Traditional methods usually optimize based on a single objective and it is difficult to take into account multiple performance indicators. This method realizes the comprehensive optimization of transmission error, tooth surface contact area, and edge load distribution through a multi-objective optimization strategy.

[0020] In summary, this method can smooth the transmission error curve, optimize the tooth surface contact performance, and uniformize the edge load distribution within the full operating conditions, thereby significantly reducing the gear meshing noise and improving the noise quality of the whole vehicle. Compared with the existing technology, this method effectively solves the limitations existing in the traditional method by introducing dynamic weight distribution, specifying the shape requirements of the transmission error curve, and reasonably setting the tooth surface contact area constraint, demonstrating outstanding technical advantages and innovation.

[0021] Preferably, in S4, when setting the weight ratio for different operating conditions according to the preset weight distribution strategy, the weight ratio formula is: weight = 1 / (peak load ÷ 2).

[0022] With such a setting, this formula associates the weight with the reciprocal of the peak load, enabling higher load conditions to obtain higher weight values. This ensures that high load conditions, which have a greater impact on gear performance, are given priority in the optimization process, thereby improving the applicability of the optimization results under critical operating conditions.

[0023] Through the weight distribution strategy, the optimization objective function can more accurately reflect the requirements under actual operating conditions. For example, in the electric drive system of new energy vehicles, high load conditions usually correspond to important scenarios such as acceleration or climbing. Prioritizing the optimization of these conditions can significantly improve the noise quality and driving experience of the whole vehicle. Existing technologies often do not fully consider the influence of different operating conditions, resulting in optimization results that may only be applicable to a single operating condition or static conditions. The above weight distribution strategy overcomes this limitation by dynamically adjusting the optimization weight and achieves the optimal balance of transmission error within the full operating conditions.

[0024] Preferably, in S4, during the optimization calculation process, the contact area ratios at the tooth tip, tooth root, and both ends of the tooth direction are also constrained to be 85% - 90% to avoid local overload.

[0025] With such a setting, by restricting the proportion of the contact area at the tooth tip, tooth root, and both ends of the tooth direction to 85%-90%, the contact area distribution on the tooth surface is ensured to be uniform, avoiding local load concentration. This not only reduces the overload risk in the edge area but also significantly improves the tooth surface contact performance, thereby reducing noise and wear caused by uneven contact. Existing modification methods are insufficient in optimizing the tooth surface contact performance, easily leading to uneven load distribution at the tooth surface edge and exacerbating noise and wear problems. This method effectively solves this problem by reasonably setting the contact area constraint.

[0026] Preferably, in S3, the value ranges of the modification parameters to be optimized are also set according to the engineer's experience or the accuracy of the processing equipment.

[0027] With such a setting, 1. the feasibility of the modification parameters can be ensured. In step S3, the value ranges of the modification parameters to be optimized (such as tooth direction inclination, tooth direction crowning, tooth profile inclination, and tooth profile crowning) are set according to the engineer's experience or the accuracy of the processing equipment. This measure ensures that the parameter values generated during the optimization process can be achieved in actual processing, avoiding design results that exceed the equipment capabilities or are unreasonable.

[0028] 2. the optimization efficiency can also be improved. By presetting the value ranges of the modification parameters, the optimization search space can be effectively reduced, reducing unnecessary computational effort. This not only improves the operating efficiency of the optimization algorithm but also reduces the demand for computing resources, making the optimization process more efficient.

[0029] In the prior art, the setting of the modification parameters may lack sufficient consideration of the processing ability and engineering practice experience, resulting in the optimization results being difficult to directly apply to actual production. The above technical content makes up for this deficiency by introducing the engineer's experience and the accuracy of the processing equipment as constraint conditions, enhancing the practicality and operability of the gear modification method.

[0030] Preferably, in S2, the gear transmission performance includes gear meshing stiffness, transmission error, contact stress distribution, and dynamic response characteristics.

[0031] With such a setting, 1. the characteristics of the gear transmission system can be comprehensively reflected. By subdividing the gear transmission performance into multiple key indicators (meshing stiffness, transmission error, contact stress distribution, and dynamic response characteristics), the operating state and performance of the gear transmission system under different load conditions can be comprehensively reflected. This multi-dimensional description method helps to more deeply understand the working mechanism of the gear.

[0032] In the prior art, the analysis of the gear transmission performance is often limited to a single or a few indicators (such as transmission error), and other factors (such as contact stress distribution and dynamic response characteristics) are not fully considered. This may lead to poor results in actual applications. The above technical content makes up for this deficiency by introducing multiple key indicators, improving the scientificity and practicality of the gear modification method.

[0033] 2. Provide basic data for subsequent optimization. The purpose of S2 is to simulate the gear transmission performance under different load conditions based on the gear transmission system model and calculate the key parameters in the initial state. By clarifying the specific content of the gear transmission performance, accurate basic data support can be provided for subsequent optimization steps (such as the multi-objective optimization in S4). The data of gear mesh stiffness and transmission error can be used to evaluate the noise level under different working conditions. The data of contact stress distribution can be used to optimize the tooth surface contact performance and reduce local overload. The data of dynamic response characteristics can be used to analyze the vibration characteristics and stability of the gear system.

[0034] Preferably, in S2, the key parameters include the gear mesh misalignment, the peak load on the gear tooth surface, and the tooth surface edge load coefficient.

[0035] Such a setting can: 1. Accurately reflect the core problems in the initial state. By extracting these key parameters, the core performance problems of the gear transmission system in the initial state can be accurately reflected, providing a clear direction and basis for subsequent optimization. Gear mesh misalignment: It reflects the relative position deviation of the gears during meshing due to manufacturing errors or assembly errors. This parameter directly affects the transmission error and vibration characteristics. Peak load on the gear tooth surface: It represents the maximum pressure borne by the gear tooth surface under a certain working condition and is an important indicator for evaluating the tooth surface contact strength and fatigue life. Tooth surface edge load coefficient: It measures the degree of load concentration in the edge area of the tooth surface and is of great significance for reducing noise and avoiding local overload.

[0036] 2. Provide a quantitative basis for the optimization objectives. These key parameters provide a specific quantitative basis for subsequent optimization steps (such as the multi-objective optimization in S4), making the optimization process more targeted. Reduce transmission error: By analyzing the gear mesh misalignment, the main reasons for the transmission error can be found and corresponding modification measures can be taken. Improve the tooth surface contact performance: By evaluating the peak load and the edge load coefficient, the tooth surface contact area distribution can be optimized and local stress concentration can be reduced. Reduce the noise level: By controlling the tooth surface edge load coefficient, the high-frequency noise caused by overload in the edge area can be effectively reduced.

[0037] In the prior art, there is often a lack of comprehensive analysis of key parameters in the initial state, resulting in a lack of clear goals and bases in the optimization process. The above technical content compensates for this deficiency by introducing the gear meshing misalignment amount, peak load, and tooth flank edge load coefficient as key parameters, enhancing the scientificity and systematicness of the gear modification method. Brief Description of the Drawings

[0038] In order to make the objectives, technical solutions, and advantages of the invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings, where:

[0039] Figure 1 is a flowchart of this method. Detailed Embodiment

[0040] The following will be further described in detail through specific embodiments:

[0041] Embodiment:

[0042] As Figure 1 shown, in this embodiment, a gear modification method for reducing gear noise is disclosed, including the following steps:

[0043] S1. Construct a gear transmission system model including gear geometric parameters, material properties, and load condition information;

[0044] S2. Based on the gear transmission system model, simulate the gear transmission performance under different load conditions, and extract key parameters from the analysis of the gear transmission performance. The key parameters are used to reflect the defects of the gear in the initial state; and calculate the numerical values of the key parameters in the initial state under different load conditions.

[0045] Specifically, when implemented, the gear transmission performance includes gear meshing stiffness, transmission error, contact stress distribution, and dynamic response characteristics.

[0046] In this way, by subdividing the gear transmission performance into multiple key indicators (meshing stiffness, transmission error, contact stress distribution, dynamic response characteristics), the operating state and performance of the gear transmission system under different load conditions can be comprehensively reflected. This multi-dimensional description method helps to understand the working mechanism of gears more deeply. In the prior art, the analysis of gear transmission performance often focuses on a single or a few indicators (such as transmission error), without fully considering other factors (such as contact stress distribution and dynamic response characteristics). This may lead to poor optimization results in practical applications. The above technical content makes up for this deficiency by introducing multiple key indicators, improving the scientificity and practicality of the gear modification method. It can also provide basic data for subsequent optimization. The purpose of S2 is to simulate the gear transmission performance under different load conditions based on the gear transmission system model and calculate the key parameters in the initial state. By clarifying the specific content of the gear transmission performance, accurate basic data support can be provided for subsequent optimization steps (such as the multi-objective optimization in S4). The data of gear meshing stiffness and transmission error can be used to evaluate the noise level under different working conditions. The data of contact stress distribution can be used to optimize the tooth surface contact performance and reduce local overload. The data of dynamic response characteristics can be used to analyze the vibration characteristics and stability of the gear system.

[0047] Specifically, in implementation, the key parameters include the gear meshing misalignment amount, the peak load on the gear tooth surface, and the tooth surface edge load coefficient.

[0048] Such a setting can accurately reflect the core problems in the initial state. By extracting these key parameters, the core performance problems of the gear transmission system in the initial state can be accurately reflected, providing a clear direction and basis for subsequent optimization. Gear meshing misalignment: It reflects the relative position deviation of gears during meshing due to manufacturing errors or assembly errors. This parameter directly affects the transmission error and vibration characteristics. Peak load on the gear tooth surface: It represents the maximum pressure borne by the gear tooth surface under a certain working condition and is an important indicator for evaluating the tooth surface contact strength and fatigue life. Tooth surface edge load coefficient: It measures the degree of load concentration in the edge area of the tooth surface and is of great significance for reducing noise and avoiding local overload. It can also provide a quantitative basis for the optimization target. These key parameters provide a specific quantitative basis for subsequent optimization steps (such as the multi-objective optimization in S4), making the optimization process more targeted. Reducing the transmission error: By analyzing the gear meshing misalignment, the main causes of the transmission error can be found and corresponding modification measures can be taken. Improving the tooth surface contact performance: By evaluating the peak load and the edge load coefficient, the distribution of the tooth surface contact area can be optimized and local stress concentration can be reduced. Reducing the noise level: By controlling the tooth surface edge load coefficient, the high-frequency noise caused by overload in the edge area can be effectively reduced. In the prior art, there is often a lack of comprehensive analysis of the key parameters in the initial state, resulting in a lack of clear goals and basis for the optimization process. However, the above technical content makes up for this deficiency by introducing the gear meshing misalignment, peak load, and tooth surface edge load coefficient as key parameters, improving the scientificity and systematicness of the gear modification method.

[0049] S3. Based on the key parameters extracted in S2, set the modification parameters to be optimized; the modification parameters to be optimized include gear tooth direction inclination, tooth direction crowning, tooth profile inclination, and tooth profile crowning.

[0050] During specific implementation, the value ranges of the modification parameters to be optimized are also set according to the engineer's experience or the accuracy of the processing equipment.

[0051] In this way, the feasibility of the modification parameters can be ensured. In step S3, the value ranges of the modification parameters to be optimized (such as helix angle modification, crowning modification, profile angle modification, and profile crowning modification) are set according to the engineer's experience or the accuracy of the processing equipment. This measure ensures that the parameter values generated during the optimization process can be achieved in actual processing, avoiding design results that exceed the equipment's capabilities or are unreasonable. It can also improve the optimization efficiency. By presetting the value ranges of the modification parameters, the optimization search space can be effectively reduced, and unnecessary computational efforts can be minimized. This not only improves the operating efficiency of the optimization algorithm but also reduces the demand for computing resources, making the optimization process more efficient. In the prior art, the setting of the modification parameters may lack sufficient consideration of the processing capabilities and engineering practice experience, resulting in the optimization results being difficult to directly apply to actual production. However, the above technical content compensates for this deficiency by introducing the engineer's experience and the accuracy of the processing equipment as constraints, enhancing the practicality and operability of the gear modification method.

[0052] S4. Aiming at reducing the transmission error and increasing the gear contact area, perform an optimization calculation on each modification parameter to be optimized based on the gear transmission system model. The algorithm specifically used for the optimization calculation can be a commonly used genetic iteration algorithm; during the optimization calculation process, according to the preset weight distribution strategy, set the weight ratios for different operating conditions to represent the priorities of each operating condition. The operating conditions include load conditions.

[0053] Among them, when setting the weight ratios for different operating conditions according to the preset weight distribution strategy, the weight ratio formula is: weight = 1 / (peak load ÷ 2).

[0054] In this way, by associating the weight with the reciprocal of the peak load, this formula enables high-load operating conditions to obtain higher weight values. This ensures that high-load operating conditions, which have a greater impact on gear performance, are given priority consideration during the optimization process, thereby enhancing the applicability of the optimization results under critical operating conditions. Through the weight distribution strategy, the optimization objective function can more accurately reflect the requirements under actual operating conditions. For example, in the electric drive system of new energy vehicles, high-load operating conditions usually correspond to important scenarios such as acceleration or climbing. Optimizing these conditions first can significantly improve the noise quality and driving experience of the entire vehicle. The prior art often fails to fully consider the impact of different operating conditions, resulting in the optimization results being applicable only to a single operating condition or static conditions. However, the above weight distribution strategy overcomes this limitation by dynamically adjusting the optimization weights, achieving an optimal balance of transmission error across all operating conditions.

[0055] During specific implementation, during the optimization calculation process, also constrain the contact area ratios at the tooth tip, tooth root, and both ends of the helix to be 85% - 90% to avoid local overload.

[0056] In this way, by restricting the contact area ratio at the tooth tip, tooth root, and both ends of the tooth direction to be 85%-90%, the contact area distribution on the tooth surface is ensured to be uniform, avoiding local load concentration. This not only reduces the overload risk in the edge area but also significantly improves the tooth surface contact performance, thereby reducing noise and wear caused by uneven contact. Existing modification methods have insufficient optimization of the tooth surface contact performance, easily leading to uneven load distribution at the tooth surface edge and exacerbating the problems of noise and wear. This method effectively solves this problem by reasonably setting the contact area constraint.

[0057] S5. Adjust the numerical values of the modification parameters in the optimization result of S4 so that the transmission error curve shows a sine or cosine trend under all operating conditions.

[0058] S6. Take the modification parameters with adjusted numerical values in S5 as the final modification parameters to complete the gear modification optimization.

[0059] This method calculates the transmission error under different load conditions based on the gear transmission system model and combines a weight allocation strategy to assign the priorities of each operating condition. This method overcomes the limitation in the prior art of not fully considering the influence of different operating conditions and achieves the optimal balance of transmission error within the full range of operating conditions. Compared with the prior art: Traditional methods only optimize for a single operating condition or static conditions and are difficult to adapt to the complex and changeable actual operating environment. This method significantly improves the control effect of transmission error within the full range of operating conditions by dynamically adjusting the optimization weights. In addition, during the optimization process, this method particularly emphasizes that the transmission error curve shows a sine or cosine trend under all operating conditions. This smoothed curve shape effectively avoids high-frequency noise problems caused by sudden changes in transmission error (such as sawtooth fluctuations). Compared with the prior art: The prior art does not put forward specific requirements for the shape of the transmission error curve, resulting in significant noise that may still be caused by curve mutations even if the numerical value of the transmission error is low. This method fundamentally solves this problem by clarifying the curve shape requirements. Moreover, this method aims to reduce the transmission error and increase the tooth surface contact area, and uses a multi-objective optimization algorithm to optimize the gear modification parameters (tooth direction inclination, tooth direction crowning, tooth profile inclination, tooth profile crowning). The finally output modification parameters can achieve a good comprehensive performance balance within the full range of operating conditions. Compared with the prior art: Traditional methods usually optimize based on a single objective and are difficult to take into account multiple performance indicators. This method achieves the comprehensive optimization of transmission error, tooth surface contact area, and edge load distribution through a multi-objective optimization strategy.

[0060] In summary, the present method can smooth the transmission error curve, optimize the tooth surface contact performance, and uniformize the edge load distribution within the full operating conditions, thereby significantly reducing the gear meshing noise and improving the noise quality of the whole vehicle. Compared with the existing technologies, the present method effectively solves the limitations existing in the traditional methods by introducing dynamic weight allocation, specifying the shape requirements of the transmission error curve, and reasonably setting the tooth surface contact area constraint, demonstrating prominent technical advantages and innovativeness.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit them. Those of ordinary skill in the art should understand that any modifications or equivalent replacements made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions shall be covered by the scope of the claims of the present invention.

Claims

1. A gear modification method for reducing gear noise, characterized in that: The following steps are involved: S1. Construct a gear transmission system model including gear geometry parameters, material properties, and load condition information; S2. Based on the gear transmission system model, simulate the gear transmission performance under different load conditions, and extract key parameters from the gear transmission performance analysis, where the key parameters are used to reflect the defects of the gear in the initial state; and calculate the values ​​of the key parameters in the initial state under different load conditions; S3. Based on the key parameters extracted in S2, setting the modification parameters to be optimized; the modification parameters to be optimized include gear tooth inclination, tooth crown, tooth profile inclination, and tooth profile crown; S4. With the goal of reducing transmission error and increasing gear contact area, each modification parameter to be optimized is optimized based on the gear transmission system model; in the optimization calculation process, a weight ratio is set for different operating conditions according to a preset weight allocation strategy to indicate the priority of each operating condition; The operating conditions include load conditions; S5. Adjust the values ​​of the shaping parameters in the optimization result of S4 so that the transmission error curve shows a sine or cosine trend under all operating conditions; S6. Use the modification parameters adjusted by S5 as the final modification parameters to complete the gear modification optimization.

2. The gear modification method for reducing gear noise according to claim 1, characterized in that: In S4, when setting weight ratios for different operating conditions according to a preset weight allocation strategy, the weight ratio formula is: weight = 1 / (peak load ÷ 2).

3. The gear modification method for reducing gear noise according to claim 2, characterized in that: In S4, during the optimization calculation process, the contact area of ​​the tooth top, tooth root and both ends of the tooth is constrained to account for 85%-90%.

4. The gear modification method for reducing gear noise according to claim 1, characterized in that: In S3, the value range of each shaping parameter to be optimized is set according to the experience of engineers or the accuracy of processing equipment.

5. The gear modification method for reducing gear noise according to claim 4, characterized in that: In S2, the gear transmission performance includes gear meshing stiffness, transmission error, contact stress distribution, and dynamic response characteristics.

6. The gear modification method for reducing gear noise according to claim 5, characterized in that: In S2, the key parameters include the gear meshing misalignment, the peak load of the gear tooth surface, and the tooth surface edge load coefficient.

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