CN108846146A - A method of evaluation in-vehicle power noise TGW - Google Patents
A method of evaluation in-vehicle power noise TGW Download PDFInfo
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- CN108846146A CN108846146A CN201810297097.5A CN201810297097A CN108846146A CN 108846146 A CN108846146 A CN 108846146A CN 201810297097 A CN201810297097 A CN 201810297097A CN 108846146 A CN108846146 A CN 108846146A
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- G06F30/20—Design optimisation, verification or simulation
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The present invention proposes a kind of method for evaluating in-vehicle power noise TGW, the method is the demand according to user to in-vehicle power noise, TGW index engineering parameter corresponding with point is complained is established correlation to contact, establish the conversion regime of TGW index and engineering parameter, it is horizontal that vehicle noise is evaluated by TGW value, TGW performance after can also speculating listing by new model noise level in turn, assess the market effect of existing vehicle prioritization scheme, so that the kinetic noise for designing suitable TGW performance according to user demand is horizontal, so that more efficient instruct TGW work expansion.
Description
Technical field
The invention belongs to car mass assessment technique fields, are specifically designed for the market TGW performance of evaluation new model
Method.
Background technique
TGW/1000 (thousand trolley of things gone wrong complain of number) is mainly by user in 3 months after purchase vehicle
It provides electric questionnaire and investigates its overall merit to vehicle, mainly include noise, dynamic property, oil consumption etc..If user couple
Certain aspect has dissatisfied place then to will record lower complaint point, and TGW value is characterized to the feedback of certain problem with every 1000 user,
There are 5 people to complain this problem as being directed to certain problem, in 1000 people, then the TGW value of this problem is 5, i.e., with TGW value come
React the complaint size of user.Currently requirement of the user to in-vehicle power noise is higher and higher, and TGW work is also increasingly heavier
It wants, but current work has a generality, stating for user asks the conversion with engineering parameter not establish correlation,
To be predicted by TGW index guidance program recruitment evaluation and new model TGW etc..
Summary of the invention
Statistical data proposes a kind of method for evaluating in-vehicle power noise TGW to the present invention based on practical experience and largely, builds
Vertical TGW index is contacted with engineering parameter correlation, assesses market effect, the new model market TGW table of existing vehicle prioritization scheme
It is existing, so that the kinetic noise for designing suitable TGW performance according to user demand is horizontal.
Technical scheme is as follows:
A method of evaluation in-vehicle power noise TGW includes the following steps:
1. being based on GQRS investigation system (global quality investigating system), the TGW that vehicle power noise to be evaluated is complained is extracted
Data;
2. the initial data of pair GQRS investigation carries out call-on back by phone, classify to complaint problem;
3. pair part typical vehicle carries out real steering vectors, determine that user most really complains point to in-vehicle power noise, and
It is determined as two complaint modes according to the statistical conditions for complaining point:Warming-up operating condition and accelerating mode;
4. separating, respectively obtaining actual to TGW data according to call-on back by phone, practical complaint vehicle testing situation
TGW value:TGWWarming-upAnd TGWAccelerate, wherein warming-up operating condition TGWWarming-upComplain that point is accelerating mode TGW after starting in 60SAccelerateComplain point
The mutation of accelerator noise is noise peak;
5. complaining the TGW value of mode according to two of step (4), use the noise level of offline vehicle as the measurement of noise
Value;The noise level of offline vehicle is steady-state noise S under the warming-up operating condition and noise mutation value △ S under 2 grades of full throttles;
6. a pair selected vehicle repeats step (1)-(5), the noise figure and its each TGW for complaining mode of the vehicle are respectively obtained
Value;
7. (referring in step (1) and passing through back noise size S and △ S under each operating condition of each vehicle with the TGW value under the operating condition
The TGW value visit, isolated) correlation analysis is carried out, and fit relevance formula:TGWKinetic noise=TGWWarming-up+TGWAccelerate;
According to the formula, market effect, the new model market TGW performance of existing vehicle prioritization scheme are assessed, according to user
The kinetic noise of the suitable TGW performance of Demand Design is horizontal.
Specifically, in the methods of the invention, the noise level of the offline vehicle is:According to 6sigma mode pair
All vehicles carry out off-line tests, it is desirable that each vehicle random inspection, in the car it is main drive warming-up is acquired at auris dextra before 60s noise
With two grades of full throttle acceleration noises, steady-state noise S under the warming-up operating condition and noise mutation value △ S under 2 grades of full throttles is recorded
Size.
Specifically, in the methods of the invention, the step (7) is that noise and operating condition TGW value typing minitab are being united
In meter function matching line chart in response by TGW value, can also be by noise in response using noise as predictive variable, TGW value is made
For predictive variable, and confirm after selecting regression model type.
Preferably, the regression model type is 1 power model of fit.
Preferably, will at least 30 to each vehicle random inspection number, meet 6sigma requirement.
The present invention uses above method, and the demand according to user to in-vehicle power noise is corresponding with point is complained by TGW index
Engineering parameter establish correlation connection, that is, establish the conversion regime of TGW index and engineering parameter, pass through TGW value evaluate vehicle
Noise level, the TGW performance after can also speculating listing by new model noise level in turn, thus more efficient guidance
TGW work expansion.
Detailed description of the invention
Fig. 1;The flow diagram of the method for the present invention;
Fig. 2:Noise point layout schematic diagram;
Fig. 3:Certain vehicle 2WOT noise curve schematic diagram;
Fig. 4:Establish model of fit schematic diagram;
Fig. 5:Model of fit validity contrast schematic diagram;
1-master drives seat;2-sonic transducers.
Specific embodiment
Below with reference to attached drawing, the preferred embodiment of the present invention is described in detail.Preferred embodiment is only for explanation
The present invention, rather than limiting the scope of protection of the present invention.
Referring to Fig. 1, the step of method of this evaluation in-vehicle power noise TGW, is as follows:
1. being based on GQRS investigation system, the TGW data that power noise is complained are extracted.
2. a pair original questionnaire carries out 100% call-on back by phone, classify to complaint problem.
3. pair part typical vehicle carries out real steering vectors, determine that user most really complains point to in-vehicle power noise, and
It is determined as two complaint modes according to the statistical conditions for complaining point:Warming-up operating condition and accelerating mode.
4. separating, respectively obtaining actual to TGW data according to call-on back by phone, practical complaint vehicle testing situation
TGW value:TGWWarming-upAnd TGWAccelerate, wherein warming-up operating condition (TGWWarming-up) complain that noise is big in 60S after starting, and accelerating mode TGWAccelerateIt embraces
Blame accelerator noise mutation (noise peak).
5. new car is substantially belonged to based on customer's vehicle, so using the noise level of offline vehicle as the metric of noise.
The acquisition methods of the noise level of offline vehicle are as follows:
Off-line test is carried out to all vehicles according to 6sigma mode, it is desirable that each vehicle random inspection at least 30.It presses
As shown in Fig. 2, arrangement acoustic sensor 2 acquisition internal car noise at human ear is parallel in main 1 right side of seat of driving, before acquiring warming-up
60S noise and two grades of WOT (full throttle) acceleration noises, and using the noise average of 30 trolleys of each vehicle as the vehicle
The △ S that steady-state noise S (noise is maximum in the case of this) and 2 grades of full throttles accelerate under warming-up operating condition1.2 grades of full throttles are accelerated
Noise is then according to shown in Fig. 3, by each noise peak △ S on curveXData accumulation is carried out into △ S=△ S1+△S2+……+△
SX。
6. a pair selected vehicle repeats step 1- step 5, the noise figure and its each TGW for complaining mode of the vehicle are respectively obtained
Value, is finally aggregated into shown in table 1《Each operating condition noise and TGW value》.
Table 1 respectively complains operating condition noise and TGW value
Vehicle | Warming-up noise S | TGWWarming-up | Acceleration noise △ S | TGWAccelerate |
Vehicle 1 | 46.1 | 22.9 | 19 | 60.2 |
Vehicle 2 | 47.3 | 29.1 | 24.5 | 123.7 |
Vehicle 3 | 46.5 | 19.9 | 25 | 114.8 |
Vehicle 4 | 49.9 | 44 | 21.5 | 98.8 |
Vehicle 5 | 43.9 | 10 | 20 | 101.1 |
Vehicle 6 | 46.3 | 22 | 12 | 36 |
7. according to shown in Fig. 4 by table 1 noise and operating condition TGW value typing minitab, in statistical function matching line chart
In response by TGW value, using noise as predictive variable, and confirm after selecting regression model type.The correlation fitted is public
Formula:TGWKinetic noise=TGWWarming-up+TGWAccelerate。
By taking warming-up noise as an example, as shown in figure 5, occurring different model of fit according to different fit types.Choose R-
Its bigger degree of fitting of sq (adjustment) coefficient is better, and model is more effective.We have observed that 1 power model of fit is that most have from the figure
Effect, so the model of fit of warming-up operating condition is:TGWWarming-up=-242.4+5.721S.TGW can similarly be calculatedAccelerate=-47.71+
6.728 △ S, summarize rear TGWKinetic noise=TGWWarming-up+TGWAccelerate=-290.11+5.721S+6.728 △ S.
The TGW level of existing vehicle and the effect of corrective measure can be assessed according to model above.It makes an uproar simultaneously for known
The new model of sound level can carry out TGW prediction in advance, so that new model be instructed to assess whether existing noise level meets user's need
It asks.
The above description is only a preferred embodiment of the present invention, is not intended to restrict the invention, it is clear that those skilled in the art
Various changes and modifications can be made to the invention by member without departing from the spirit and scope of the present invention.If in this way, of the invention
Within the scope of the claims of the present invention and its equivalent technology, then the present invention is also intended to encompass these to these modifications and variations
Including modification and variation.
Claims (5)
1. a kind of method for evaluating in-vehicle power noise TGW, which is characterized in that include the following steps:
(1) it is based on GQRS investigation system, extracts the TGW data that vehicle power noise to be evaluated is complained;
(2) call-on back by phone is carried out to the initial data of GQRS investigation, classified to complaint problem;
(3) to part typical vehicle carry out real steering vectors, determine user to in-vehicle power noise most really complain point, and according to
Complain that the statistical conditions of point are determined as two complaint modes:Warming-up operating condition and accelerating mode;
(4) according to call-on back by phone, practical complaint vehicle testing situation, TGW data is separated, actual TGW is respectively obtained
Value:TGWWarming-upAnd TGWAccelerate, wherein warming-up operating condition TGWWarming-upComplain that point is accelerating mode TGW after starting in 60SAccelerateComplain that point adds
Fast process noise mutation is noise peak;
(5) the TGW value that mode is complained according to two of step (4), uses the noise level of offline vehicle as the metric of noise;
The noise level of offline vehicle is steady-state noise S under the warming-up operating condition and noise mutation value △ S under 2 grades of full throttles;
(6) step (1)-(5) are repeated to selected vehicle, respectively obtains the noise figure of the vehicle and its TGW value of each complaint mode;
(7) by noise size S and △ S under each operating condition of each vehicle, correlation analysis is carried out with the TGW value under the operating condition, and be fitted
Relevance formula out:TGWKinetic noise=TGWWarming-up+TGWAccelerate;
According to the formula, market effect, the new model market TGW performance of existing vehicle prioritization scheme are assessed, according to user demand
The kinetic noise for designing suitable TGW performance is horizontal.
2. the method for evaluation in-vehicle power noise TGW according to claim 1, which is characterized in that the offline vehicle
Noise level is:Off-line test is carried out to all vehicles according to 6sigma mode, it is desirable that each vehicle random inspection,
In the car it is main drive warming-up is acquired at auris dextra before 60s noise and two grades of full throttle acceleration noises, record stable state under warming-up operating condition and make an uproar
Noise mutation value △ S size under sound S and 2 grades of full throttles.
3. the method for evaluation in-vehicle power noise TGW according to claim 1, which is characterized in that step (7) is to use
Minitab software carries out a point correlation and analyses, described by noise and operating condition TGW value typing minitab, in statistical function matching line chart
It is middle by TGW value in response, using noise as predictive variable, can also by noise in response, TGW value as predictive variable, and
Confirm after selection regression model type.
4. the method for evaluation in-vehicle power noise TGW according to claim 1, which is characterized in that the regression model class
Type is 1 power model of fit.
5. the method for evaluation in-vehicle power noise TGW according to claim 1, which is characterized in that random to each vehicle
Spot-check number will at least 30, meets 6sigma requirement.
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110990752A (en) * | 2019-10-31 | 2020-04-10 | 重庆长安汽车股份有限公司 | Method for evaluating level of noise in automobile during driving process of automobile |
CN112881023A (en) * | 2021-01-08 | 2021-06-01 | 广西玉柴机器股份有限公司 | Linear metering method for acceleration noise of diesel engine |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102393246A (en) * | 2011-10-22 | 2012-03-28 | 重庆长安汽车股份有限公司 | Noise evaluation method for automobile generator under finished automobile state |
CN106996828A (en) * | 2017-05-04 | 2017-08-01 | 安徽江淮汽车集团股份有限公司 | The method for predicting the in-car noise contribution amount size of accelerating mode |
-
2018
- 2018-03-30 CN CN201810297097.5A patent/CN108846146B/en active Active
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102393246A (en) * | 2011-10-22 | 2012-03-28 | 重庆长安汽车股份有限公司 | Noise evaluation method for automobile generator under finished automobile state |
CN106996828A (en) * | 2017-05-04 | 2017-08-01 | 安徽江淮汽车集团股份有限公司 | The method for predicting the in-car noise contribution amount size of accelerating mode |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110990752A (en) * | 2019-10-31 | 2020-04-10 | 重庆长安汽车股份有限公司 | Method for evaluating level of noise in automobile during driving process of automobile |
CN110990752B (en) * | 2019-10-31 | 2023-03-28 | 重庆长安汽车股份有限公司 | Method for evaluating level of noise in automobile during driving process of automobile |
CN112881023A (en) * | 2021-01-08 | 2021-06-01 | 广西玉柴机器股份有限公司 | Linear metering method for acceleration noise of diesel engine |
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