Optimization method and system for automobile road noise active control system

Abstract

The invention provides an optimization method and system for an automobile road noise active control system, and relates to the technical field of automobile road noise active control. Then randomly determining a target number of first sensors in the preset number of first sensors as a first sensor experiment group, and randomly determining a target number plus one second sensor in the preset number of second sensors as a second sensor test group; according to the method, the automobile road noise active control system is optimized by adopting a mode of calculating correlation to eliminate the sensor which has the worst contribution to the road noise in the automobile, and for a vehicle-mounted power amplifier company, the optimization design of the automobile road noise active control system can be met; and a high-cost professional multi-channel sound and vibration data acquisition device does not need to be purchased, so that the optimal solution of economy and design is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of active control of automobile road noise, and in particular to an optimization method and system for an active control system of automobile road noise. Background Art

[0002] Active noise reduction technology is an electroacoustic control technology based on the principle of sound wave superposition. Its implementation process depends on the location of the excitation source causing the road noise in the car. The active control system of automobile road noise relies on the microphone sensor and three-way acceleration sensor installed on the vehicle to determine the location of the excitation source causing the road noise in the car.

[0003] Active control technology for automobile road noise has been mass-produced in many models at home and abroad, among which vehicle sound source path identification plays a key role in the entire development of active control of automobile road noise; the existing technology mainly uses professional multi-channel sound and vibration data acquisition equipment, such as LMS, Hyde Acoustics and other brands, as well as microphone sensors and three-way acceleration sensors adapted to them, such as GRAS, B&K and other brands. By collecting the vibration data of multiple positions of the vehicle chassis and combining it with software analysis, the location of the excitation source causing the road noise in the car is finally confirmed, thereby optimizing the active control system of automobile road noise.

[0004] For the vehicle amplifier company, it only needs to determine the optimal positions of the microphone sensor and the three-axis acceleration sensor in the vehicle road noise active control system on the vehicle. The cost of using the current method to design and optimize the vehicle road noise active control system is relatively high (especially the cost of using multi-channel sound and vibration data acquisition equipment is relatively high). For this reason, the present invention provides an optimization method and system for a vehicle road noise active control system. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides an optimization method and system for an active control system for automobile road noise, which solves the problem of low-cost design of an active control system for automobile road noise by an on-board power amplifier company.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0007] An optimization method for an active control system of automobile road noise comprises the following steps:

[0008] S1. Arranging a predetermined number of first sensors and second sensors on the vehicle;

[0009] S2, randomly determining a target number of first sensors from a predetermined number of first sensors as a first sensor test group, randomly determining a target number of second sensors plus one from a predetermined number of second sensors as a second sensor test group, and determining a target number of second sensors from the second sensor test group in a combined manner to construct a second sensor test group group;

[0010] S3, performing coherence calculation on the data collected by each first sensor in the first sensor test group and the data collected by one of the sub-units in the second sensor test group, and performing average calculation to obtain a first average coherence value;

[0011] S4, repeating step S3, so that each sub-unit in the second sensor test group participates in the calculation, and removing the group with the lowest first average coherence value from the acquired first average coherence value data, thereby removing the second sensor with the worst contribution to the in-vehicle road noise from the second sensor test group;

[0012] S5. Randomly select a second sensor from the remaining second sensors after step S2 to add to the second sensor test group, repeat steps S3 and S4, and finally select the optimal target number of second sensors.

[0013] Preferably, the predetermined number of the first sensors is greater than or equal to the target number of the first sensors, the predetermined number of the second sensors is greater than or equal to the target number of the second sensors, and the sum of the predetermined numbers of the first and second sensors is greater than the sum of the target numbers of the first and second sensors.

[0014] Preferably, in S3, the data collected by each first sensor in the first sensor test group is respectively coherently calculated with the data collected by one of the sub-units in the second sensor test group, and the average value is calculated to obtain the first average coherence value, which specifically includes the following steps:

[0015] S31, using the data collected by the first first sensor in the first sensor test group as output and the data collected by the first subunit in the second sensor test group as input, performing multiple coherence calculations to obtain a first coherence value;

[0016] S32, using the data collected by the second first sensor in the first sensor test group as output and the data collected by the first subunit in the second sensor test group as input, performing multiple coherence calculations to obtain a second coherence value;

[0017] The above step S32 is repeated to traverse all first sensors in the first sensor experimental group, and the average value of the obtained multiple coherence values ​​is calculated to obtain a first average coherence value.

[0018] Preferably, the first sensor is a microphone sensor or a three-axis acceleration sensor, and the second sensor is another sensor of the microphone sensor and the three-axis acceleration sensor that is different from the first sensor.

[0019] Preferably, it also includes:

[0020] S6, taking the optimal target number of second sensors finally selected as the second sensor experimental group, and randomly determining the target number plus one of the first sensors from the predetermined number of first sensors as the first sensor test group, and determining the target number of first sensors from the first sensor test group in a combined manner to construct a first sensor test group group;

[0021] S7, performing coherence calculation on the data collected by each second sensor in the second sensor test group and the data collected by one of the sub-units in the first sensor test group, and performing average calculation to obtain a second average coherence value;

[0022] S8, repeating step S7, so that each sub-unit in the first sensor test group participates in the calculation, and removing the group with the lowest second average coherence value from the obtained second average coherence value data, thereby removing the first sensor with the worst contribution to the in-vehicle road noise from the first sensor test group;

[0023] S9. Randomly select a first sensor from the remaining first sensors after step S6 to add to the first sensor test group, repeat steps S7 and S8, and finally select the optimal target number of first sensors.

[0024] Another object of the present invention is to provide an optimization system for an active control system of automobile road noise, comprising: a data acquisition unit, a data processing unit, a plurality of first sensors and a plurality of second sensors, the data acquisition unit having a built-in A2B chip, the plurality of first sensors, the plurality of second sensors and the data acquisition unit being connected in series using an A2B communication protocol, and the data processing unit being communicatively connected to the data acquisition unit;

[0025] The data processing unit includes a processor and a memory, the memory stores a computer program, and the processor is used to run the computer program to implement the above-mentioned optimization method of the active control system of automobile road noise.

[0026] Preferably, the data acquisition unit is a vehicle-mounted power amplifier or an A2B analyzer, and the signals acquired by the plurality of first sensors and the plurality of second sensors are downsampled and then stored.

[0027] Another object of the present invention is to provide an optimization system for an active control system of automobile road noise, comprising: a data acquisition unit, a data processing unit, a plurality of first sensors and a plurality of second sensors, the data acquisition unit having an A2B chip and an ADC chip built therein, the plurality of first sensors and the data acquisition unit being connected in series using an A2B communication protocol, the plurality of second sensors being connected to the ADC chip, the data processing unit being in communication connection with the data acquisition unit;

[0028] The data processing unit includes a processor and a memory, the memory stores a computer program, and the processor is used to run the computer program to implement the above-mentioned optimization method of the active control system of automobile road noise.

[0029] The present invention provides an optimization method and system for an active control system of automobile road noise, which has the following beneficial effects:

[0030] 1. The present invention optimizes the active control system of automobile road noise by calculating the correlation to eliminate the sensor with the worst contribution to the road noise in the car. For the vehicle amplifier company, it can meet the optimization design of the active control system of automobile road noise, and does not need to purchase high-cost professional multi-channel sound and vibration data acquisition equipment, so as to achieve the optimal solution of economy and design; and the optimization method of implementing the active control system of automobile road noise is relatively simple, and the data analysis and experience requirements of the designer are relatively low. General vehicle amplifier companies can participate in the optimization design of the active control system of automobile road noise, which has a promoting effect on the efficient development of the active control system of automobile road noise.

[0031] 2. The present invention designs an optimization system for an active control system of automobile road noise, which includes a data acquisition unit, a data processing unit, a plurality of first sensors and a plurality of second sensors. The data acquisition unit can utilize an on-board power amplifier of the vehicle body, and each first sensor and second sensor only needs to meet data detection requirements. Compared with traditional multi-channel sound and vibration data acquisition equipment, its cost is greatly reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a schematic diagram of an optimization system for an active control system of automobile road noise proposed by the present invention;

[0033] Figure 2 This is a first wiring diagram of an optimization system for an active control system for automobile road noise proposed by the present invention;

[0034] Figure 3 This is a second wiring diagram of an optimization system for an active control system for automobile road noise proposed by the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Embodiment 1:

[0037] At present, models equipped with active road noise control technology usually use at least 4 microphone sensors and 4 three-axis acceleration sensors (a three-axis acceleration sensor contains vibration signals in the x, y, and z directions), totaling 16 channels. During the vehicle development stage, especially when identifying the vehicle sound source path, more sensors are often deployed. After data collection and analysis, the optimal solution is finally screened out, that is, the optimization plan for the active road noise control system is finally determined.

[0038] An embodiment of the present invention provides a method for optimizing an active control system for automobile road noise, comprising the following steps:

[0039] S1. A predetermined number of first sensors and second sensors are arranged on the automobile, the predetermined number of the first sensors is greater than or equal to a target number of the first sensors, the predetermined number of the second sensors is greater than or equal to a target number of the second sensors, and the sum of the predetermined numbers of the first sensors and the second sensors is greater than the sum of the target numbers of the first sensors and the second sensors, so that there is room for optimization of at least one of the first sensors and the second sensors. The optimization referred to here is to screen out the first sensors and the second sensors that contribute less to the road noise inside the vehicle.

[0040] When designing the number and position of the first sensor and the second sensor, the design is based on experience, vehicle structure, target requirements (the accuracy of determining the position of the excitation source causing the road noise in the vehicle), etc. Generally, the higher the target requirement, the more first sensors and second sensors are designed.

[0041] S2. Randomly determine a target number of first sensors from a predetermined number of first sensors as a first sensor experimental group, randomly determine a target number of second sensors plus one from a predetermined number of second sensors as a second sensor test group, and determine a target number of second sensors from the second sensor test group in a combined manner to construct a second sensor test group group.

[0042] For example, the target number of the first sensor and the target number of the second sensor are both 4. When executing step S2, the first sensor test group randomly selects 4 first sensors, and the second sensor test group randomly selects 5 second sensors. There are 5 ways to randomly select 4 from the 5 second sensors in the second sensor test group, and these 5 combination methods construct the second sensor test group.

[0043] S3. Perform coherence calculation on the data collected by each first sensor in the first sensor test group and the data collected by one of the sub-units in the second sensor test group, and calculate the average value to obtain a first average coherence value.

[0044] Randomly select 4 of all the second sensors, and perform coherence calculation on the data collected by the 4 second sensors and the first sensor to obtain the coherence value, which is set as:

[0045] coMic x Acc y1y3y3y4 (Formula 1)

[0046] Wherein x is the serial number of the first sensor, y1, y2, y3, y4 are the serial numbers of the second sensors respectively, and Formula 1 indicates that the value is obtained by calculating the multiple coherence of the four second sensors with serial numbers y1, y2, y3, y4 to the first sensor with serial number x.

[0047] For example, select the data collected by the first sensor in the first sensor test group and correspond to the data collected by one of the subunits in the second sensor test group to obtain: CoMic1Acc 1234 、CoMic1Acc 1235 、CoMic1Acc 1245 、CoMic1Acc 1345 、CoMic1Acc 2345 .

[0048] S4. Repeat step S3 to make each subunit in the second sensor test group participate in the calculation, and eliminate the group with the lowest first average coherence value from the acquired first average coherence value data, thereby eliminating the second sensor with the worst contribution to the in-vehicle road noise from the second sensor test group.

[0049] After repeating step S3 for 5 times, the following Table 1 is obtained:

[0050] <![CDATA[ACC 1234 ]]> <![CDATA[ACC 1235 ]]> <![CDATA[ACC 1245 ]]> <![CDATA[ACC 1345 ]]> <![CDATA[ACC 2345 ]]> <![CDATA[Mic1]]> <![CDATA[CoMic1Acc 1234 ]]> <![CDATA[CoMic1Acc 1235 ]]> <![CDATA[CoMic1Acc 1245 ]]> <![CDATA[CoMic1Acc 1345 ]]> <![CDATA[CoMic1Acc 2345 ]]> <![CDATA[Mic2]]> <![CDATA[CoMic2Acc 1234 ]]> <![CDATA[CoMic2Acc 1235 ]]> <![CDATA[CoMic2Acc 1245 ]]> <![CDATA[CoMic2Acc 1345 ]]> <![CDATA[CoMic2Acc 2345 ]]> <![CDATA[Mic3]]> <![CDATA[CoMic3Acc 1234 ]]> <![CDATA[CoMic3Acc 1235 ]]> <![CDATA[CoMic3Acc 1245 ]]> <![CDATA[CoMic3Acc 1345 ]]> <![CDATA[CoMic3Acc 2345 ]]> <![CDATA[Mic4]]> <![CDATA[CoMic4Acc 1234 ]]> <![CDATA[CoMic4Acc 1235 ]]> <![CDATA[CoMic4Acc 1245 ]]> <![CDATA[CoMic4Acc 1345 ]]> <![CDATA[CoMic4Acc 2345 ]]>

[0051] The average value of the column data in Table 1 is obtained as follows:

[0052] <![CDATA[ACC 1234 ]]> <![CDATA[ACC 1235 ]]> <![CDATA[ACC 1245 ]]> <![CDATA[ACC 1345 ]]> <![CDATA[ACC 2345 ]]> <![CDATA[Mic 1234 ]]> <![CDATA[CoMic 1234 Acc 1234 ]]> <![CDATA[CoMic 1234 Acc 1235 ]]> <![CDATA[CoMic 1234 Acc 1245 ]]> <![CDATA[CoMic 1234 Acc 1345 ]]> <![CDATA[CoMic 1234 Acc 2345 ]]>

[0053] For example, use the following formula 1 for calculation:

[0054]

[0055] In CoMic 1234 Acc 1234 、CoMic 1234 Acc 1235 、CoMic 1234 Acc 1245 、CoMic 1234 Acc 1345 、CoMic 1234 Acc 2345The group with the lowest coherence value among the five groups of data is eliminated, that is, the second sensor with the worst contribution to the road noise in the car is eliminated.

[0056] S5. Randomly select a second sensor from the remaining second sensors after step S2 to add to the second sensor test group, repeat steps S3 and S4, and finally select the optimal target number of second sensors.

[0057] S6. Use the optimal target number of second sensors finally selected as the second sensor experimental group, and randomly determine the target number plus one of the predetermined number of first sensors as the first sensor test group, and determine the target number of first sensors from the first sensor test group in a combined manner to construct a first sensor test group group.

[0058] S7. Perform coherence calculation on the data collected by each second sensor in the second sensor test group and the data collected by one of the sub-units in the first sensor test group, and calculate the average value to obtain a second average coherence value.

[0059] S8. Repeat step S7 to make each sub-unit in the first sensor test group participate in the calculation, and eliminate the group with the lowest second average coherence value from the obtained second average coherence value data, so as to eliminate the first sensor with the worst contribution to the in-vehicle road noise from the first sensor test group.

[0060] S9. Randomly select a first sensor from the remaining first sensors after step S6 to add to the first sensor test group, repeat steps S7 and S8, and finally select the optimal target number of first sensors.

[0061] The design ideas of steps S6-S9 are consistent with those of steps S2-S5, and they finally determine the optimal target number of first sensors.

[0062] In the above-described process, each of the first sensor and the second sensor corresponds to a specific position on the vehicle.

[0063] In one embodiment, in S3, the data collected by each first sensor in the first sensor test group is respectively coherently calculated with the data collected by one of the sub-units in the second sensor test group, and the average value is calculated to obtain the first average coherence value, which specifically includes the following steps:

[0064] The first sensor is a microphone sensor or a three-axis acceleration sensor, and the second sensor is a microphone sensor or a three-axis acceleration sensor that is different from the first sensor, that is, one is a microphone sensor and the other is a three-axis acceleration sensor; preferably, the first sensor is a microphone sensor, because the receiver mainly refers to the head space of the front and rear passengers, these spaces are basically fixed areas, and in the current mass production plan, the position of the microphone sensor is generally arranged on the roof of the car, so the adjustable range of the microphone sensor is not very large, and a small range of adjustment (it can be understood that the distance difference between the microphone sensor position adjustment range and the previous position is within 15cm) has little effect on the entire coherence calculation result, so that when the microphone sensor position initially determined in the early stage needs to be fine-tuned in the later stage, the calculation results initially determined in the early stage can also be used as a reference, that is, it can be determined through experience that the first sensor experimental group basically meets the final selected optimal target number of first sensors, so that steps S6-S9 can be omitted.

[0065] In all the above test methods, the test process needs to be strictly controlled, including:

[0066] 1) Time consistency: Multiple rounds of testing must be completed in the same period. It is not recommended to complete them over several days.

[0067] 2) Personnel consistency: Multiple rounds of testing require that the driver must be the same person, and other testers must be the same person as much as possible, and the number of people cannot change;

[0068] 3) Road surface consistency: Wheel testing requires testing on the same road surface and in the same direction;

[0069] 4) Consistency of working conditions: Multiple rounds of testing require that the gear position of the test vehicle is consistent and the speed is kept consistent as much as possible (it is recommended that the speed error be controlled within ±2kph);

[0070] 5) Vehicle condition consistency: Multiple rounds of testing require that the vehicle condition remain consistent during the test, such as the air conditioner is always on or off, and the seats in the car are not adjusted. If the vehicle condition is abnormal during the test, such as the sudden appearance of a door fault code or a sudden abnormal noise in the car, the test data should be invalidated.

[0071] The strict requirements of the present invention on the test process are intended to ensure that the coherence results of each round of test data calculation can be compared with each other, making up for the problem that the vehicle-mounted power amplifier cannot complete all the collection work at one time due to the limited number of collection channels.

[0072] Embodiment 2

[0073] An optimization system for an active control system of automobile road noise comprises: a data acquisition unit, a data processing unit, a plurality of first sensors and a plurality of second sensors, wherein the data acquisition unit has a built-in A2B chip, the plurality of first sensors, the plurality of second sensors and the data acquisition unit are connected in series using an A2B communication protocol, and the data processing unit is in communication connection with the data acquisition unit.

[0074] The data processing unit includes a processor and a memory, the memory stores a computer program, the processor is used to run the computer program to implement the optimization method of the active control system of automobile road noise in embodiment 1, the data acquisition unit is a vehicle-mounted power amplifier or an A2B analyzer, and the signals collected by the first sensors and the second sensors are downsampled and then stored.

[0075] The mass production solution of the active control technology of automobile road noise is usually that the vehicle-mounted amplifier collects data from the sensor at a sampling rate of 48kHz, and then after algorithm calculation, the obtained noise reduction signal is mixed with the media sound and transmitted to each speaker unit; in order to ensure that the mass production solution of the active control technology of automobile road noise is more consistent with the solution proposed by the present invention, while considering the limitation of the memory of the vehicle-mounted amplifier itself (for the same size of memory, the higher the sampling rate, the shorter the collected data duration, and too short data length is not conducive to analysis) and the frequency band of automobile road noise is mainly within 300Hz, the signal collected from the sensor is downsampled and then stored in the memory of the vehicle-mounted amplifier (it is recommended to downsample 48kHz by 32 times to 1.5kHz).

[0076] like Figure 1 As shown in , several first sensors and several second sensors are all A2B sensors, and the data acquisition unit is a vehicle-mounted amplifier; the vehicle-mounted amplifier serves as the A2B master node, and its BN and BP pins are connected to the AN and AP pins of the first A2B sensor through a twisted pair cable, and then the BN and BP pins of the first A2B sensor are connected to the AN and AP pins of the second A2B sensor, and so on; since the number of sensors that can be connected to the vehicle-mounted amplifier at one time is limited, it is recommended to connect 4 microphone sensors and 5 three-axis acceleration sensors at a time, for a total of 9 slave nodes; theoretically, as long as the total number of microphone sensors and three-axis acceleration sensors does not exceed the upper limit of the acceptable number of A2B nodes, it will be fine.

[0077] The data processing unit uses a computer device having a processor and a memory.

[0078] Embodiment 3

[0079] An optimization system for an active control system of automobile road noise comprises: a data acquisition unit, a data processing unit, a plurality of first sensors and a plurality of second sensors, wherein the data acquisition unit has an A2B chip and an ADC chip built therein, the plurality of first sensors are connected in series with the data acquisition unit using an A2B communication protocol, the plurality of second sensors are connected with the ADC chip, and the data processing unit is in communication connection with the data acquisition unit.

[0080] The data processing unit includes a processor and a memory. The memory stores a computer program. The processor is used to run the computer program to implement the optimization method of the active control system of automobile road noise in the first embodiment.

[0081] The first sensor is a three-axis acceleration sensor, the second sensor is a microphone sensor, the three-axis acceleration sensor selects an A2B sensor, the microphone sensor selects an analog sensor, and the data acquisition unit is a vehicle-mounted power amplifier with a built-in A2B chip and an ADC chip.

[0082] The data processing unit uses a computer device having a processor and a memory.

[0083] While the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that many changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the invention.

Claims

1. An optimization method for an active control system of automobile road noise, characterized in that: The following steps are involved: S1. Arranging a predetermined number of first sensors and second sensors on the vehicle; S2, randomly determining a target number of first sensors from a predetermined number of first sensors as a first sensor test group, randomly determining a target number of second sensors plus one from a predetermined number of second sensors as a second sensor test group, and determining a target number of second sensors from the second sensor test group in a combined manner to construct a second sensor test group group; S3, performing coherence calculation on the data collected by each first sensor in the first sensor test group and the data collected by one of the sub-units in the second sensor test group, and performing average calculation to obtain a first average coherence value; S4, repeating step S3, so that each sub-unit in the second sensor test group participates in the calculation, and removing the group with the lowest first average coherence value from the acquired first average coherence value data, thereby removing the second sensor with the worst contribution to the in-vehicle road noise from the second sensor test group; S5. Randomly select a second sensor from the remaining second sensors after step S2 to add to the second sensor test group, repeat steps S3 and S4, and finally select the optimal target number of second sensors.

2. The optimization method of an active control system for vehicle road noise according to claim 1, characterized in that: The predetermined number of the first sensors is greater than or equal to the target number of the first sensors, the predetermined number of the second sensors is greater than or equal to the target number of the second sensors, and the sum of the predetermined numbers of the first sensors and the second sensors is greater than the sum of the target numbers of the first sensors and the second sensors.

3. The optimization method of an active control system for vehicle road noise according to claim 1, characterized in that: In S3, the data collected by each first sensor in the first sensor test group is respectively subjected to coherence calculation with the data collected by one of the sub-units in the second sensor test group, and the average value is calculated to obtain the first average coherence value, which specifically includes the following steps: S31, using the data collected by the first first sensor in the first sensor test group as output and the data collected by the first subunit in the second sensor test group as input, performing multiple coherence calculations to obtain a first coherence value; S32, using the data collected by the second first sensor in the first sensor test group as output and the data collected by the first subunit in the second sensor test group as input, performing multiple coherence calculations to obtain a second coherence value; The above step S32 is repeated to traverse all first sensors in the first sensor experimental group, and the average value of the obtained multiple coherence values ​​is calculated to obtain a first average coherence value.

4. The optimization method of an active control system for vehicle road noise according to claim 1, characterized in that: The first sensor is a microphone sensor or a three-axis acceleration sensor, and the second sensor is another sensor of the microphone sensor and the three-axis acceleration sensor that is different from the first sensor.

5. The optimization method of an active control system for automobile road noise according to claim 1, characterized in that: Also includes: S6, taking the optimal target number of second sensors finally selected as the second sensor experimental group, and randomly determining the target number plus one of the first sensors from the predetermined number of first sensors as the first sensor test group, and determining the target number of first sensors from the first sensor test group in a combined manner to construct a first sensor test group group; S7, performing coherence calculation on the data collected by each second sensor in the second sensor test group and the data collected by one of the sub-units in the first sensor test group, and performing average calculation to obtain a second average coherence value; S8, repeating step S7, so that each sub-unit in the first sensor test group participates in the calculation, and removing the group with the lowest second average coherence value from the obtained second average coherence value data, thereby removing the first sensor with the worst contribution to the in-vehicle road noise from the first sensor test group; S9. Randomly select a first sensor from the remaining first sensors after step S6 to add to the first sensor test group, repeat steps S7 and S8, and finally select the optimal target number of first sensors.

6. An optimization system for an active control system of automobile road noise, characterized in that: include: A data acquisition unit, a data processing unit, a plurality of first sensors and a plurality of second sensors, wherein the data acquisition unit has a built-in A2B chip, the plurality of first sensors, the plurality of second sensors and the data acquisition unit are connected in series using the A2B communication protocol, and the data processing unit is in communication connection with the data acquisition unit; The data processing unit includes a processor and a memory, the memory stores a computer program, and the processor is used to run the computer program to implement the optimization method of the active control system of automobile road noise as described in any one of claims 1-5.

7. The optimization system for an active control system of automobile road noise according to claim 6, characterized in that: The data acquisition unit is a vehicle-mounted power amplifier or an A2B analyzer, and the signals acquired by the plurality of first sensors and the plurality of second sensors are downsampled and then stored.

8. An optimization system for an active control system of automobile road noise, characterized in that: include: A data acquisition unit, a data processing unit, a plurality of first sensors and a plurality of second sensors, wherein the data acquisition unit has a built-in A2B chip and an ADC chip, the plurality of first sensors and the data acquisition unit are connected in series using an A2B communication protocol, the plurality of second sensors are connected to the ADC chip, and the data processing unit is communicatively connected to the data acquisition unit; The data processing unit includes a processor and a memory, the memory stores a computer program, and the processor is used to run the computer program to implement the optimization method of the active control system of automobile road noise as described in any one of claims 1-5.

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