CN106127316A - Automated vehicle maintenance prediction system - Google Patents
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- CN106127316A CN106127316A CN201610496921.0A CN201610496921A CN106127316A CN 106127316 A CN106127316 A CN 106127316A CN 201610496921 A CN201610496921 A CN 201610496921A CN 106127316 A CN106127316 A CN 106127316A
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Abstract
Automated vehicle maintenance Prediction System, including: mobile unit, Real-time Collection vehicle data also uploads to cloud platform by network；Cloud platform, including: big Data processing core module, large data center module uses hadoop technology that big data are carried out classification process, it is provided that the underlying parameter needed for maintenance computing；Mobile phone A PP, automatically sends service report and informs that host vehicle maintains demand and quotation immediately.Native system accurately calculates vehicle maintenance information according to the data of various dimensions, it is provided that the maintenance project of vehicle and working hour expense, maintenance spare part and unit price, spare part number, makes maintenance Clear & Transparent.
Description
Technical field
The invention belongs to vehicle operational maintenance field, a kind of automated vehicle maintenance Prediction System.
Background technology
The society developed rapidly in the face of automobile industry, in city, the recoverable amount of private car is all increasing almost every day.
For numerous car owners, the careful care love car of oneself, periodic maintenance accomplish that safety traffic is also for inherently safe
Guarantee.Traditional maintenance needs car owner to estimate maintenance period, or the residue service cycle arranged according to vehicle is entered
Row maintenance operation, major part car owner do not know about maintenance project and content, needs to deliver to vehicle specify repair location, such as 4S
Shops etc., are detected the scope that just can determine that maintenance on the spot by technician, provide offer sheet, and such vehicle repair and maintenance exist passivity out of question
And hysteresis quality.
In prior art, the patent application of Publication No. 105313806A, main collection vehicle fluid, such as machine oil, cooling
Liquid etc., if determine the need for maintaining less than minimum liquid level；The patent application of Publication No. 105270293A, mainly
The project of maintenance is simply estimated according to gross vehicle mileage and maintenance manual.Above method simply simply carries out maintenance and estimates,
It is unable to reach the purpose accurately estimating maintenance；The working hour expense of each maintenance project, the maintenance unit price of spare part, number also cannot be provided
Information Deng car owner's actual concern.
Summary of the invention
The disadvantages mentioned above existed for prior art and deficiency, the invention provides the maintenance of a kind of automated vehicle and estimate and be
System, accurately calculates vehicle maintenance information according to the data of various dimensions, it is provided that the maintenance project of vehicle and working hour expense, maintenance spare part
With unit price, spare part number, make maintenance Clear & Transparent.
For achieving the above object, the invention provides a kind of automated vehicle maintenance Prediction System, including:
Mobile unit, Real-time Collection vehicle data also uploads to cloud platform by network；
Cloud platform, including: big Data processing core module, large data center module uses hadoop technology to come big data
Carry out classification process, it is provided that the underlying parameter needed for maintenance computing；
Mobile phone A PP, automatically sends service report and informs that host vehicle maintains demand and quotation immediately.
Further, described big Data processing core module, including: service time computing module, according to the residue of vehicle
Service cycle and per day distance travelled, calculate service time point T1 next time；Residue service time according to vehicle, calculates next time
Service time point T2, both employing arrive first principle, take a next service time.
Further, if T2 ＜ T1, then maintenance next time total kilometrage Y=distance travelled+per day distance travelled × natural law
Difference；If T2 >=T1, then maintenance next time total kilometrage Y=distance travelled+remaining mileage.
Further, large data center module, also include listener clustering module, by chassis number, total kilometrage and car age, come
Determine 5,000 kilometers of maintenance crowds and 10,000 kilometers of maintenance crowds, particularly as follows:
If averagely arranging ten thousand kilometers of OR average service cycle interval≤N2 of service cycle≤N1 ten thousand kilometers, belong to 5,000
Kilometer maintenance crowd；
Otherwise, 10,000 kilometers of maintenance crowds are belonged to.
Further, large data center module, also comprise determining that maintenance projects module, determine guarantor according to different crowd
Support project particularly as follows:
The first step, calculates remove-insurance number of times, and 5,000 kilometers of maintenance crowds are: (this maintenance total kilometrage-last time service cycle)
× 2-1；10000 kilometers of maintenance crowds are: this maintenance total kilometrage-last time service cycle-1；
Second step, according to remove-insurance number of times, carries out Path selection:
For 5,000 kilometers of maintenance crowds, if remove-insurance number of times is less than or equal to 1, then selecting path I is 1 people complete, scarce
Group；If remove-insurance number of times is more than 1, then select path II for lacking repeatedly crowd；
For 10,000 kilometers of maintenance crowds, if remove-insurance number of times is less than or equal to 1, then selecting path III is 1 people complete, scarce
Group；If remove-insurance number of times is more than 1, then select path IV for lacking repeatedly crowd.
Further, in path I, Y-0.4 < X≤Y+0.1, X is a set [0.5,1,1.5,2,2.5,3 ...], its
Middle X, in units of 0.5, is incremented by stepping；If X falls in the interval comprising 0.5 odd-multiple, then selection scheme I, if X falls at bag
Containing the interval of 0.5 even-multiple, then selection scheme II；
In path II, Y-0.4 < X≤Y+0.1, X is a set [0.5,1,1.5,2,2.5,3 ...], and wherein X with 0.5 is
Unit, is incremented by stepping；If X falls in the interval comprising 0.5 odd-multiple, then selection scheme I, if X falls is comprising 0.5 even-multiple
Interval, then selection scheme II；
Y_New=round (Y) in path III, round off inquiry maintenance knowledge base, wherein Y is this maintenance prediction
Value, also carries out in this path that CRM is counter to be looked into, if the last when changing this project mileage+correspondence guarantee the quality cycle mileage < Y+0.5,
Then this project needs to change；If the last when changing this project mileage+correspondence guarantee the quality cycle mileage > Y+0.5, then pick；
Review time, correspondence project was under deletion condition, if having replacing needs within the corresponding time, changed this if the last
Cycle duration of guaranteeing the quality < this service time+average service time interval vehicle of-30 days, it should changing should of mesh date+correspondence
Project, on the contrary it is changed without.
Y_New=round (Y) in path IV, round off inquiry maintenance knowledge base, wherein Y is this maintenance prediction
Value.
Further, scheme I project of maintaining is machine oil machine filter, fuel oil additive；Scheme I also carries out CRM is counter to be looked into,
CRM is anti-when looking in addition to machine oil machine filter, fuel oil additive, cleaning air throttle, and remaining project is required for counter looking into, and checks project last time
Whether have omission, if the last when changing this project mileage+respective items purpose guarantee the quality cycle mileage < Y+0.4, then this project
Need to change；If cycle of the guaranteeing the quality mileage of mileage+correspondence during the last this project of replacing > Y+0.4, then would pick；During inspection
Between corresponding project under deletion condition, if within the corresponding time, have replacing needs, if the last this Project dates of replacing+
Corresponding cycle duration of guaranteeing the quality < this service time+average service time interval vehicle of-30 days, it should change this project, instead
Be changed without；
Scheme II inquiry maintenance knowledge base, finds out the maintenance project of correspondence.
As further, the content of maintenance includes maintenance project and maintenance spare part, i.e. obtains each according to big data
The working hour expense of maintenance project, maintenance spare part unit price and number.
As further, native system also includes packing module, and the enter shop security actual by vehicle is supported history and obtained
The maintenance project that car owner omits, is filled with, and again ensures that the accurate and complete of vehicle maintenance content.
Due to the fact that the above technical scheme of employing, it is possible to obtain following technique effect: the present invention can be the most pre-
Estimate project and the spare part of vehicle maintenance next time, and estimate the maintenance amount of money.Car owner is made to understand the emm message of vehicle the most in advance.
Make vehicle maintenance open, transparent, preferably protection car owner's interests, protect vehicle health.
User uses mobile phone A PP or wechat, can remotely realize vehicle " health check-up ", and transmission service report is informed automatically
Host vehicle maintains demand and quotation immediately.Make the health condition understanding vehicle in advance that car owner is more convenient, transparent, to car owner's
Safety trip provides guarantee.
Accompanying drawing explanation
The present invention has accompanying drawing 3 width:
Fig. 1 is that automated vehicle maintains Prediction System Zhong great data processing centre module diagram；
Fig. 2 is that automated vehicle maintains Prediction System structural representation；
Fig. 3 is maintenance knowledge base schematic diagram.
Detailed description of the invention
Below by embodiment, and combine accompanying drawing, technical scheme is described in further detail.
Embodiment 1
Automated vehicle maintenance Prediction System, including:
Mobile unit, Real-time Collection vehicle data also uploads to cloud platform by network；
Mobile phone A PP, can remotely realize vehicle " health check-up ", and transmission service report informs that host vehicle maintains immediately automatically
Demand and quotation；
Cloud platform, including: big Data processing core module, large data center module uses hadoop technology to come big data
Carry out classification process, it is provided that the underlying parameter needed for maintenance computing；
Described big Data processing core module, including service time computing module, according to the residue service cycle of vehicle and
Per day distance travelled, calculates service time point T1 next time；Residue service time according to vehicle, calculates service time point next time
T2, both employing arrive first principle, take a next service time.If T2 ＜ T1, then maintenance next time total kilometrage Y=distance travelled
+ per day distance travelled × natural law is poor；If T2 >=T1, then maintenance next time total kilometrage Y=distance travelled+remaining mileage.
Large data center module, also includes listener clustering module, by chassis number, total kilometrage and car age, determines that 5,000 is public
In maintain crowd and 10,000 kilometers maintenance crowds, particularly as follows:
If averagely arranging the service cycle≤0.5 ten thousand kilometer average service cycle of OR to be spaced≤0.626 ten thousand kilometer, belong to
5000 kilometers of maintenance crowds；
Otherwise, 10,000 kilometers of maintenance crowds are belonged to.
Large data center module, also comprises determining that maintenance projects module, determines that maintenance project is concrete according to different crowd
For:
The first step, calculates remove-insurance number of times, and 5,000 kilometers of maintenance crowds are: [this maintenance total kilometrage (is rounded up to ten thousand public
In, without decimal)-service cycle last time (being rounded up to ten thousand kilometers, without decimal)] × 2-1；
10000 kilometers of maintenance crowds are: (four give up this maintenance total kilometrage (rounding up, without decimal)-last time service cycle
Five enter, without decimal)-1；
Second step, according to remove-insurance number of times, carries out Path selection:
Embodiment 2
Supplementing as embodiment 1, for 5,000 kilometers of maintenance crowds, if remove-insurance number of times is less than or equal to 1, then selects road
Footpath I is 1 crowd complete, scarce；If remove-insurance number of times is more than 1, then select path II for lacking repeatedly crowd；
In path I, Y-0.4 < X≤Y+0.1, X is a set [0.5,1,1.5,2,2.5,3 ...], and wherein X with 0.5 is
Unit, is incremented by stepping；If X falls in the interval (such as: 0.5/1.5/2.5) comprising 0.5 odd-multiple, then selection scheme I, if X
Fall the interval (such as: 1/2/3/4) comprising 0.5 even-multiple, then selection scheme II；
In path II, Y-0.4 < X≤Y+0.1, X is a set [0.5,1,1.5,2,2.5,3 ...], and wherein X with 0.5 is
Unit, is incremented by stepping；If X falls in the interval (such as: 0.5/1.5/2.5) comprising 0.5 odd-multiple, then selection scheme I, if X
Fall the interval (such as: 1/2/3/4) comprising 0.5 even-multiple, then selection scheme II；
Scheme I project of maintaining is machine oil machine filter, fuel oil additive；Scheme I also carries out CRM is counter to be looked into, CRM is counter look into time remove
Outside machine oil machine filter, fuel oil additive, cleaning air throttle, remaining project is required for counter looking into, and checks whether project last time has omission,
If mileage+respective items purpose is guaranteed the quality during the last this project of replacing, < Y+0.4, then this project needs to change cycle mileage；As
Cycle of the guaranteeing the quality mileage of mileage+correspondence during fruit this project of the last replacing > Y+0.4, then pick；Such as: these 40,000 kilometers are entered
Shop, should change spark plug, counter look into before push away 20,000 kilometers, in historical record, 30,000 kilometers were changed spark plug, then this rejects spark plug
Project；Review time correspondence project, such as brake fluid, inside and outside air conditioner filter element, under deletion condition, if having more within the corresponding time
Change needs, if the last cycle duration of guaranteeing the quality changing this Project dates+correspondence is < during this service time+averagely maintain
Between be spaced the vehicle of-30 days, it should change this project, otherwise be changed without；
Scheme II inquiry maintenance knowledge base, finds out the maintenance project of correspondence.
Being exemplified below: 1.4≤Y < 1.9, maintenance project is machine oil machine filter, fuel oil additive.0.9≤Y < 1.4, correspondence is looked into
The maintenance project of table (" mileage " of " maintenance knowledge base ").
Embodiment 3
Supplementing as embodiment 1, for 10,000 kilometers of maintenance crowds, if remove-insurance number of times is less than or equal to 1, then selects road
Footpath III is 1 crowd complete, scarce；If remove-insurance number of times is more than 1, then select path IV for lacking repeatedly crowd:
Y_New=round (Y) in path III, round off inquiry maintenance knowledge base, wherein Y is this maintenance prediction
Value, also carries out in this path that CRM is counter to be looked into, if the last when changing this project mileage+correspondence guarantee the quality cycle mileage < Y+0.5,
Then this project needs to change；If the last when changing this project mileage+correspondence guarantee the quality cycle mileage > Y+0.5, then pick；
(such as: these 40,000 kilometers are entered shop, spark plug should be changed, counter look into before push away 20,000 kilometers, in historical record, 30,000 kilometers were changed spark
Plug, then this rejects spark plug project).Review time correspondence project (brake fluid, inside and outside air conditioner filter element), under deletion condition, is
No have replacing needs within the corresponding time, if the last cycle duration of guaranteeing the quality < this guarantor changing this Project dates+correspondence
The time of supporting+average service time is spaced the vehicle of-30 days, it should changes this project, otherwise is changed without.
Y_New=round (Y) in path IV, round off inquiry maintenance knowledge base, wherein Y is this maintenance prediction
Value.It is exemplified below:
0≤Y≤1.5 1 ten thousand
1.5 < Y≤2.5 2 ten thousand
2.5 < Y≤3.5 3 ten thousand
Correspondence is tabled look-up the maintenance project of (" mileage " of " maintenance knowledge base ").
Embodiment 4
Supplementing as embodiment 2 and 3, the content of maintenance includes maintenance project and maintenance spare part, illustrates by machine oil machine filter
For, maintenance project is the filter of changing machine oil machine, is to have artificial work time cost.Maintenance spare part is exactly: 4 liters of machine oil etc., according to
The calculation of price of spare part.Total maintenance content includes the working hour expense of actual replacing price of spare parts+artificial.
The working hour expense of each maintenance project, maintenance spare part unit price and number is i.e. obtained according to big data.
According to the above-mentioned project determined, according to the parameter in table, it is corresponding in turn to form following word order: next time maintains changing machine
Oil machine filter, internal air conditioner filter element, outside air conditioner filter element, spark plug, foundation car body is tested and local conditions, may select and cleans
Air throttle.Wish that you are happy with car！
Maintenance time=take total man-hour calculation 100 man-hour=1 hour, it is accurate to 0.5 hour；As: 75-125 man-hour=1 is little
Time；125-175 man-hour=1.5 hour ....
For complete CRM record and the crowd only lacking 1 CRM record, report is write exactly and need to check that the upper second time of acquisition is all
The interim project do not done, and time not in current period project, add in short: the replacing week of XX project in maintenance manual please be pay close attention to
Phase.
Such as: 1) 5,000 kilometers maintenance crowds:
60000 maintenances are not done, 6.5 ten thousand maintenances: list in project list according to counter looking into；
60000 maintenances are not done, and 6.5 ten thousand maintenances are not done, and 70,000 enter shop comment changes as follows: maintenance next time changing machine oil machine
Filter, outside air conditioner filter element, spark plug, foundation car body is tested and local conditions, may select and cleans air throttle.Please pay close attention to maintenance
The replacement cycle of brake fluid, anti-icing fluid, gear box oil in handbook, wish that you are happy with car！
2) 10,000 kilometers of maintenance crowds:
60000 maintenances are not done, 70,000 maintenances: list in project list according to counter looking into.
60000 maintenances are not done, and 70,000 maintenances are not done, and 80,000 enter shop: maintenance next time changing machine oil machine is filtered, outside air-conditioning filter
Core, spark plug.Foundation car body is tested and local conditions, optional cleaning air throttle.Please pay close attention to brake fluid in maintenance manual,
Anti-icing fluid, the replacement cycle of gear box oil, wish that you are happy with car！
Native system also includes packing module, and the enter shop security actual by vehicle is supported history and obtained the maintenance item that car owner omits
Mesh, is filled with, and again ensures that the accurate and complete of vehicle maintenance content.
Preferably, said system is to use vehicle-mounted OBD equipment Real-time Collection vehicle data and by mobile communications network
Pass to cloud platform, be deposited to big Data processing core module；Large data center module uses hadoop technology to enter big data
Row classification processes, it is provided that the underlying parameter needed for maintenance computing.
The above, the only present invention preferably detailed description of the invention, but protection scope of the present invention is not limited thereto,
Any those familiar with the art in the technical scope of present disclosure, according to technical scheme and
Inventive concept equivalent or change in addition, all should contain within protection scope of the present invention.
Claims (10)
1. automated vehicle maintenance Prediction System, it is characterised in that including:
Mobile unit, Real-time Collection vehicle data also uploads to cloud platform by network；
Cloud platform, including: big Data processing core module, large data center module uses hadoop technology to carry out big data
Classification processes, it is provided that the underlying parameter needed for maintenance computing；
Mobile phone A PP, automatically sends service report and informs that host vehicle maintains demand and quotation immediately.
Automated vehicle the most according to claim 1 maintenance Prediction System, it is characterised in that described big data processing centre
Module, including: service time computing module, according to residue service cycle and the per day distance travelled of vehicle, calculate that next time protects
Support time point T1；Residue service time according to vehicle, calculates service time point T2 next time, and both employing arrive first principle, take one
Individual next service time.
Automated vehicle the most according to claim 2 maintenance Prediction System, it is characterised in that if T2 ＜ T1, then next time
Maintenance total kilometrage Y=distance travelled+per day distance travelled × natural law is poor；If T2 >=T1, then maintenance next time total kilometrage Y=row
Sail mileage+remaining mileage.
Automated vehicle the most according to claim 1 maintenance Prediction System, it is characterised in that large data center module, also
Including listener clustering module, by chassis number, total kilometrage and car age, determine 5,000 kilometers of maintenance crowds and 10,000 kilometers of maintenance people
Group, particularly as follows:
If averagely arranging ten thousand kilometers of OR average service cycle interval≤N2 of service cycle≤N1 ten thousand kilometers, belong to 5,000 kilometers
Maintenance crowd；
Otherwise, 10,000 kilometers of maintenance crowds are belonged to.
Automated vehicle the most according to claim 1 maintenance Prediction System, it is characterised in that large data center module, also
Comprise determining that maintenance projects module, determine maintenance project according to different crowd particularly as follows:
The first step, calculates remove-insurance number of times, and 5,000 kilometers of maintenance crowds are: (this maintenance total kilometrage-last time service cycle) × 2-
1；
10000 kilometers of maintenance crowds are: this maintenance total kilometrage-last time service cycle-1；
Second step, according to remove-insurance number of times, carries out Path selection:
For 5,000 kilometers of maintenance crowds, if remove-insurance number of times is less than or equal to 1, then selecting path I is 1 crowd complete, scarce；As
Really remove-insurance number of times is more than 1, then select path II for lacking repeatedly crowd；
For 10,000 kilometers of maintenance crowds, if remove-insurance number of times is less than or equal to 1, then selecting path III is 1 crowd complete, scarce；As
Really remove-insurance number of times is more than 1, then select path IV for lacking repeatedly crowd.
Automated vehicle the most according to claim 5 maintenance Prediction System, it is characterised in that Y-0.4 < X≤Y in path I
+ 0.1, X are set [0.5,1,1.5,2,2.5,3 ...], and wherein X is in units of 0.5, are incremented by stepping；Comprising if X falls
The interval of 0.5 odd-multiple, then selection scheme I, if X falls in the interval comprising 0.5 even-multiple, then selection scheme II；
In path II, Y-0.4 < X≤Y+0.1, X is a set [0.5,1,1.5,2,2.5,3 ...], and wherein X is with 0.5 for single
Position, is incremented by stepping；If X falls in the interval comprising 0.5 odd-multiple, then selection scheme I, if X falls is comprising 0.5 even-multiple
Interval, then selection scheme II；
Y_New=round (Y) in path III, round off inquiry maintenance knowledge base, wherein Y is that this maintains predictive value, should
Also carrying out in path that CRM is counter to be looked into, if the last, mileage+correspondence is guaranteed the quality when changing this project that cycle mileage < then should by Y+0.5
Project needs to change；If the last when changing this project mileage+correspondence guarantee the quality cycle mileage > Y+0.5, then pick this
Mesh；Review time, correspondence project was under deletion condition, if having replacing needs within the corresponding time, if the last replacing should
Cycle duration of guaranteeing the quality < this service time+average service time interval vehicle of-30 days, it should change of Project dates+correspondence
This project, on the contrary it is changed without.
Y_New=round (Y) in path IV, round off inquiry maintenance knowledge base, wherein Y is that this maintains predictive value.
Automated vehicle the most according to claim 6 maintenance Prediction System, it is characterised in that scheme I project of maintaining is machine
Oil machine filter, fuel oil additive；Scheme II inquiry maintenance knowledge base, finds out the maintenance project of correspondence.
Automated vehicle the most according to claim 7 maintenance Prediction System, it is characterised in that also carry out CRM in scheme I anti-
Look into, CRM is counter look into time in addition to machine oil machine filter, fuel oil additive, cleaning air throttle, remaining project is required for counter looking into, in inspection
Whether secondary project has omission, if the last when changing this project mileage+respective items purpose guarantee the quality cycle mileage < Y+0.4, then
This project needs to change；If cycle of the guaranteeing the quality mileage of mileage+correspondence during the last this project of replacing > Y+0.4, then would pick this
Project；Review time, correspondence project was under deletion condition, if having replacing needs within the corresponding time, changed if the last
Cycle duration of guaranteeing the quality < this service time+average service time interval vehicle of-30 days, it should more of this Project dates+correspondence
Change this project, otherwise be changed without.
Automated vehicle the most according to claim 5 maintenance Prediction System, it is characterised in that the content of maintenance includes maintenance
Project and maintenance spare part, i.e. obtain the working hour expense of each maintenance project, maintenance spare part unit price and number according to big data.
Automated vehicle the most according to claim 8 maintenance Prediction System, it is characterised in that native system also includes filling
Module, the enter shop security actual by vehicle is supported history and is obtained the maintenance project that car owner omits, and is filled with, again ensures that car
Maintenance content accurately with complete.
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| CN108628902A (en) * | 2017-03-23 | 2018-10-09 | 北京爱德盛业科技有限公司 | A kind of Motor Maintenance Digital Detecting report-generating method and system based on cloud platform |
| CN108665075A (en) * | 2018-03-14 | 2018-10-16 | 斑马网络技术有限公司 | Automobile maintenance system and its maintenance process |
| CN108944664A (en) * | 2017-05-27 | 2018-12-07 | 上海汽车集团股份有限公司 | Vehicle maintenance prompting method, apparatus and combined instrument for vehicle |
| CN111907444A (en) * | 2020-07-31 | 2020-11-10 | 东风商用车有限公司 | Intelligent engine oil maintenance system for heavy truck |
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