CN108846146A - A method of evaluation in-vehicle power noise TGW - Google Patents

A method of evaluation in-vehicle power noise TGW Download PDF

Info

Publication number
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
Authority
CN
China
Prior art keywords
tgw
noise
vehicle
warming
value
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201810297097.5A
Other languages
Chinese (zh)
Other versions
CN108846146B (en
Inventor
辜庆伟
詹樟松
杨少波
杨金才
张亮
唐朝阳
伯红玲
李祥
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Chongqing Changan Automobile Co Ltd
Original Assignee
Chongqing Changan Automobile Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Chongqing Changan Automobile Co Ltd filed Critical Chongqing Changan Automobile Co Ltd
Priority to CN201810297097.5A priority Critical patent/CN108846146B/en
Publication of CN108846146A publication Critical patent/CN108846146A/en
Application granted granted Critical
Publication of CN108846146B publication Critical patent/CN108846146B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/10Geometric CAD
    • G06F30/15Vehicle, aircraft or watercraft design
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201Market modelling; Market analysis; Collecting market data
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02TCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation

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

A method of evaluation in-vehicle power noise TGW
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.
CN201810297097.5A 2018-03-30 2018-03-30 Method for evaluating power noise TGW in vehicle Active CN108846146B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810297097.5A CN108846146B (en) 2018-03-30 2018-03-30 Method for evaluating power noise TGW in vehicle

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810297097.5A CN108846146B (en) 2018-03-30 2018-03-30 Method for evaluating power noise TGW in vehicle

Publications (2)

Publication Number Publication Date
CN108846146A true CN108846146A (en) 2018-11-20
CN108846146B CN108846146B (en) 2022-11-04

Family

ID=64211927

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810297097.5A Active CN108846146B (en) 2018-03-30 2018-03-30 Method for evaluating power noise TGW in vehicle

Country Status (1)

Country Link
CN (1) CN108846146B (en)

Cited By (2)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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

Patent Citations (2)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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

Also Published As

Publication number Publication date
CN108846146B (en) 2022-11-04

Similar Documents

Publication Publication Date Title
US20210279155A1 (en) Diagnostic Baselining
CN106596123B (en) Method, device and system for diagnosing equipment fault
De Moura et al. Evaluation of principal component analysis and neural network performance for bearing fault diagnosis from vibration signal processed by RS and DF analyses
Moravec et al. Development of psychoacoustic model based on the correlation of the subjective and objective sound quality assessment of automatic washing machines
US20170050590A1 (en) System for assessing and/or optimising the operating behaviour
US20020026252A1 (en) Computer system for vehicle battery selection based on vehicle operating conditions
CN108846146A (en) A method of evaluation in-vehicle power noise TGW
JP5816217B2 (en) Interrogation device and interrogation method
CN108304348A (en) A kind of bearing residual life prediction technique based on binary Wiener-Hopf equation
CN112100816A (en) Method for predicting noise in electric vehicle based on motor acoustic model
CN110196098B (en) Heart rate change-based vehicle sound quality evaluation method
CN108920854A (en) It is a kind of based on wireless interconnected and noise inline diagnosis harmony method for evaluating quality and system of athe portable client
CN110809280A (en) Detection and early warning method and device for railway wireless network quality
CN111189646A (en) Vehicle NVH self-diagnosis method and device, vehicle, controller and medium
CN116151460A (en) Optimization method and device for intelligent vehicle product, server and storage medium
Peng et al. Research on the virtual reality of vibration characteristics in vehicle cabin based on neural networks
Guastadisegni et al. Ride analysis tools for passenger cars: objective and subjective evaluation techniques and correlation processes–a review
CN116340332A (en) Method and device for updating scene library of vehicle-mounted intelligent system and vehicle
JP2006258510A (en) Server, inspection device, and sensory evaluation information sampling method of user
CN116109357A (en) Method, system and medium for calculating comprehensive scores of online comments of automobiles
CN107867294B (en) Apparatus and method for evaluating driving sensitivity of vehicle
Klein et al. Social media in the product development process of the automotive industry: A new approach
Owczarzak et al. Assessing the effect of inconsistent assessors on summarization evaluation
CN114266013A (en) Deep learning virtual perception network-based transmission system vibration decoupling method
CN110263408B (en) Method for evaluating NTF risk by using BNI curve

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant