CN110097219A - A kind of electric vehicle O&M optimization method based on security tree model - Google Patents
A kind of electric vehicle O&M optimization method based on security tree model Download PDFInfo
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Abstract
The present invention relates to a kind of electric vehicle O&M optimization method based on security tree model, comprising: S1. building safety tree；S2. the sequence of security-critical degree is carried out to each bottom event based on the safety tree；S3. determine whether the safe condition of the electric vehicle has reached threshold value, if it is step S4 is executed, otherwise continue to assess；S4. the branch high to security-critical degree in the safety tree is checked and is debugged, then return step S3.Implement the electric vehicle O&M optimization method of the invention based on security tree model, it can be for during actual operation, the safety of the continually changing electric vehicle of Motor vehicle security performance carries out real-time, accurate, digitized assessment, to according to safety tree module, comprehensive each safety failure state, to be timed quantitative description to the safe condition of electric vehicle, and then the guidance that maintenance operation maintenance is manufactured to electric vehicle is realized, to improve the safety of electric vehicle.
Description
Technical field
The present invention relates to means of transports, excellent more specifically to a kind of electric vehicle O&M based on security tree model
Change method.
Background technique
The popularity rate of fast development with world economy and the attention to environmental consciousness, automobile is higher and higher while right
Motor vehicle exhaust emission requirement is also higher and higher, and energy saving, safe and pollution-free electric vehicle is following development trend.However, electric
Motor-car generally has the electrical system of up to upper hectovolt, this has just been more than the safe voltage range of direct current, such as without reasonable
Design and protection, it would be possible to bring the high pressures safety problems such as personnel's electric shock.In addition, electric vehicle includes such as steering system, system
Multiple composition departments, each component parts such as dynamic system, safety control system include multiple building blocks again.The mistake of any part
Perhaps failure may cause the perhaps failure out of control of entire vehicle all so as to cause driver or passenger's experience danger to effect.So
And still lack at present being capable of the effective theory analysis of system and engineering experience the Motor vehicle security management and control that combine
Method；And lacks quantitative description Motor vehicle security state, accurately embodies each system security feature Motor vehicle security state
Method.
Summary of the invention
The technical problem to be solved in the present invention is that in view of the above drawbacks of the prior art, providing a kind of based on safety tree
The electric vehicle O&M optimization method of model.
The technical solution adopted by the present invention to solve the technical problems is: constructing a kind of electric vehicle based on security tree model
O&M optimization method, comprising:
S1. building safety tree, the safety tree includes multiple bottom events, middle layer event, top layer event and described
Bottom event, the middle layer event, the logic causality between the top layer event and security-critical degree；
S2. the sequence of security-critical degree is carried out to each bottom event based on the safety tree；
S3. determine whether the safe condition of the electric vehicle has reached threshold value, if it is step S4 is executed, otherwise continue to comment
Estimate；
S4. the branch high to security-critical degree in the safety tree is checked and is debugged, then return step S3.
In the electric vehicle O&M optimization method of the present invention based on security tree model, the step S4 is further
Include:
S41. according to the security-critical degree sequencing selection of each bottom event safely tree in be not labeled and
The high branch of security-critical degree is labeled, to obtain from the high branch of the security-critical degree slave bottom event to top layer
The event train of thought line of event；
S42. the event train of thought line is analyzed to obtain the bottom event argument of the event train of thought line；
S43. malfunction elimination is carried out to the bottom event based on the bottom event argument and eliminates failure, then returned
Step S3.
In the electric vehicle O&M optimization method of the present invention based on security tree model, the step S42 is into one
Step includes:
S421. according to each level event in bottom event, middle layer event or the top layer event on the event train of thought line
The changing rule of different degree the event train of thought line is analyzed；
S422. for according to the bottom event on the event train of thought line, different degree in middle layer event or top layer event
The event of variation abnormality finds out the bottom event actually occurred according to the upstream and downstream of the event train of thought line, determines the bottom
The causality of event and the bottom event argument for obtaining the bottom event.
In the electric vehicle O&M optimization method of the present invention based on security tree model, the elimination failure includes
Maintenance, replacement components, the redesign of function and/or structure.
In the electric vehicle O&M optimization method of the present invention based on security tree model, the step S1 is further
Include:
S11. the Motor vehicle security fault data of electric vehicle is acquired；
S12. Motor vehicle security fault data mapping is referred in different security incident groups, and united respectively
Count each security incident group frequency data；
S13. using conjoint analysis method to the Motor vehicle security fault data in each security incident group into
Row classification building safety tree.
In the electric vehicle O&M optimization method of the present invention based on security tree model, the step S13 is into one
Step includes:
S131. the Motor vehicle security fault data is at least divided into Fisrt fault classification, the second fault category, third
Fault category and the 4th fault category；
S132. using Fisrt fault classification, second fault category, the third described in different analyticals
The Motor vehicle security fault data of fault category and the 4th fault category, with the determination Motor vehicle security event
Hinder the hierarchical relationship between data so that it is determined that bottom event, middle layer event and top layer event and the bottom event, institute
State the logic causality and security-critical degree between middle layer event, the top layer event；
S133. Failure causality is successively established until traversing all Motor vehicle security fault datas to complete
The safety tree building of electric vehicle.
In the electric vehicle O&M optimization method of the present invention based on security tree model, the step S2 is further
Including
S21. the acquisition and statistics for passing through middle layer event, analyze the existing parameter error of the middle layer event, will
The original frequency data reduction of the middle layer event is standardized intermediate event frequency data at different levels；
S22. it counts to obtain each bottom event by the interpretation of result of the logic causality and the intermediate event
Probability of happening；
S23. acquisition and the intermediate event frequency data statistics based on the safety tree and the middle layer event obtain
To the probability of happening of each top layer event；
S24. based on each bottom event to the probability of each intermediate event and the probability of happening of each top layer event, meter
Calculation obtains influence probability of each bottom event to top layer event；
S25. safety weight is carried out to each bottom event based on influence probability of each bottom event to each top layer event
Spend sequence.
In the electric vehicle O&M optimization method of the present invention based on security tree model, the step S21 includes:
S211. it acquires the fault data of the intermediate event of the electric vehicle and carries out Statistical Solutions coupling, for described electronic
The dynamic change of the operating parameter of vehicle analyzes existing parameter error；It will be in the parameter error and the fault data
Original frequency data of the Failure Alarm event that happens suddenly as the middle layer event；
S212. it is directed to the corresponding working environment of original frequency data of intermediate events at different levels, by the original frequency data
It is scaled standardized intermediate event frequency data at different levels；And/or
The step S22 includes: the standardized intermediate events at different levels for counting and applying, test at the scene, under inspection scene
Frequency data, and calculate separately the probability of happening of corresponding each bottom event.
In the electric vehicle O&M optimization method of the present invention based on security tree model, in the step S23,
By the risk angle value of the generation frequency statistics and distribution, each intermediate event of intermediate event, the probability of happening of top layer event is calculated；
And/or
In the step S24, it is general that influence of each bottom event to the top layer event is calculated using bayesian algorithm
Rate.
Another technical solution that the present invention solves the use of its technical problem is to construct a kind of computer readable storage medium,
It is stored thereon with computer program, the electric vehicle based on security tree model is realized when described program is executed by processor
O&M optimization method.
Implement the electric vehicle O&M optimization method and computer readable storage medium of the invention based on security tree model,
Can for during actual operation, the safety of the continually changing electric vehicle of Motor vehicle security performance carry out in real time,
Accurately, digitized assessment, thus according to safety tree module, comprehensive each safety failure state, thus to the safety of electric vehicle
State is timed quantitative description, and then realizes the guidance that maintenance operation maintenance is manufactured to electric vehicle, to improve electronic
The safety of vehicle.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing:
Fig. 1 is the stream of the electric vehicle O&M optimization method based on security tree model of the first preferred embodiment of the present invention
Journey schematic diagram；
Fig. 2 is the electric vehicle of the electric vehicle O&M optimization method based on security tree model of the preferred embodiment of the present invention
The classification schematic diagram of safety failure data；
Fig. 3 a-3c is the portion of the electric vehicle O&M optimization method based on security tree model of the preferred embodiment of the present invention
Divide the schematic diagram set safely.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
The present invention relates to a kind of electric vehicle O&M optimization method based on security tree model, comprising: S1. building safety
Tree, the safety tree includes multiple bottom events, middle layer event, top layer event and the bottom event, the middle layer
Logic causality and security-critical degree between event, the top layer event；S2. based on the safety tree to each bottom thing
Part carries out the sequence of security-critical degree；S3. determine whether the safe condition of the electric vehicle has reached threshold value, if it is execution step
Otherwise S4 continues to assess；S4. the branch high to security-critical degree in the safety tree is checked and is debugged, and is then returned
Return step S3.Implement the electric vehicle O&M optimization method and computer-readable storage medium of the invention based on security tree model
Matter, can be for during actual operation, the safety of the continually changing electric vehicle of Motor vehicle security performance carries out real
When, accurate, digitized assessment, thus according to safety tree module, comprehensive each safety failure state, thus to the peace of electric vehicle
Total state is timed quantitative description, and then realizes the guidance that maintenance operation maintenance is manufactured to electric vehicle, to improve electricity
The safety of motor-car.
In the present invention, electric vehicle safety tree be comprehensively solve Motor vehicle security problem systems approach, be by
Interrelated logic system is established by top layer event, bottom event, interrelated logic and data, passes through Motor vehicle security demand analysis
Dendrogram is established with electric vehicle system building security incident model, is retouched to logical relation between vehicle different levels event
It states, carry out profiles characteristic for multiple subsystems such as such as braking system, steering system, vehicle body parts or component and qualitative retouches
It states.Safety tree is absorbed in true generation event, and barrier, modularization style of opening System Design is arranged in tracking penetrating system.At this
In invention, it is the main degree that quantitative analysis and evaluation bottom event influence significance level on top layer event that safety, which sets security-critical degree,
Amount, it reflects the weight that each bottom event influences Motor vehicle security.In the present invention, the safety weight set safely
Spend the differentiation of the probability, each intermediate event of having forgiven each bottom event and the risk of each top layer event
Degree factor is quantitative assessment of each bottom event to the influence size of each top layer event.Security-critical degree represents electricity
The safe weight of each bottom event of motor-car.In the present invention, bottom event is understood that as basic failure, and top layer event
It can be understood as surface layer failure.There are direct causalities between bottom event and top layer event, or indirectly cause and effect is closed
System.Between bottom event and top layer event, it is understood that there may be middle layer event.In the present invention, security-critical degree assigns each bottom
Layer event is the quantificational description to security of system, is the work of quantitative analysis electric vehicle system safety with statistical nature
Tool.
During electric vehicle actual operation, Motor vehicle security performance is constantly in variation at any time.When electronic
When vehicle operation duration reaches certain numerical value or undergoes certain situation, components or subsystem may be lost due to components aging
Etc. reasons significant impact is generated to the security performance of electric vehicle.If these information cannot obtain in time, to electric vehicle
Speech may cause extreme loss, therefore it is necessary for carrying out real-time, accurate, digitized assessment to the safety of electric vehicle
's.Motor vehicle security state, which refers to, plans as a whole the complete security tree model of electric vehicle, and comprehensive each safety failure state calculates
There are indicative significance and the unified electric vehicle important parameter embodied to Motor vehicle security, this is based on security tree model to electricity
The real-time quantitative of motor-car security situation describes.
On the basis of automotive safety status assessment, can for the real-time assessed value of Motor vehicle security state to vehicle into
Row security maintenance.When Motor vehicle security status assessment value reaches danger threshold, maintenance is repaired to vehicle in time, will be endangered
Dangerous components are updated replacement.It, can be based on safety tree to electric vehicle before defective mode occurs in Motor vehicle security system
Safe condition carries out real time monitoring assessment, to decide whether maintenance, maintenance etc..It, can be right by security tree model
The basic damaged structure different degree of the Motor vehicle security tree event high with criticality importance is first checked, to important in associated branch
It spends higher limb to be labeled, to obtain an event train of thought by safety failure top event to basic failure bottom event
Line.The event train of thought line is further analyzed, can be obtained safety failure corresponding to this failure train of thought, basic failure,
And the fault messages such as basic fault parameter.For the safety failure practical problem, safety failure can be carried out to it and excludes to examine,
Fault coverage is reduced, while corresponding portion is repaired or replaced, and assesses the reasonability of maintenance program.After completing maintenance,
It needs to assess automotive safety state again, be needed when the vehicle ages under new safe condition valuation are unable to satisfy realistic objective
It when asking, also needs again to overhaul it, continues to search dangerous components, until completing estimated maintenance target.In addition, according to thing
The changing rule of each level fault importance on part train of thought line, by importance value occurring the judgement of jump failure node, energy
Enough facilitate the analysis to important key foundation failure problems.Different degree is evaluated and abnormal safety failure occurs, according to it
The safety tree vein structure at place, is further analyzed the upstream and downstream of the safety failure to find out physical fault and save
Point, determines causality.According to the logical relation of malfunctioning module node, for the malfunction or damage that components occur, Ke Yiwei
It repairs or replaces；If the reason of failure occurs is that the design of its structure or function there are unreasonable part, is needed to the portion
Divide and is redesigned.
Fig. 1 is the stream of the electric vehicle O&M optimization method based on security tree model of the first preferred embodiment of the present invention
Journey schematic diagram.As shown in Figure 1, in step sl, constructing safety tree.The safety tree includes multiple bottom events, middle layer thing
Part, top layer event and the bottom event, the middle layer event, logic causality and peace between the top layer event
Full different degree.In a preferred embodiment of the invention, can be using known any method building safety tree, it can also be using
Some safety trees.
The method that the building of preferred embodiment in accordance with the present invention is set safely is described below.Those skilled in the art know
It knows, in other preferred embodiments of the invention, building safety tree with other methods can be adopted.The present invention is not herein by the tool
The limitation of body construction method.
In a preferred embodiment of the invention, the step of building safety tree includes: the electric vehicle for acquiring electric vehicle
Safety failure data；Motor vehicle security fault data mapping is referred in different security incident groups, and is counted
Calculate each security incident group frequency data；Using conjoint analysis method to the electric vehicle in each security incident group
Safety failure data carry out classification building safety tree.
In a preferred embodiment of the invention, the step of Motor vehicle security fault data of the acquisition electric vehicle
It may further include the electric vehicle controller, safety governor and driving recording by CAN bus by the electric vehicle
Data transmission in instrument is to platform database；Then the Motor vehicle security failure of the electric vehicle is obtained from the data
Data.For example, it is more Motor vehicle security fault data can be mapped to classification braking system, steering system, vehicle body parts etc.
The Motor vehicle security fault data is thus included in different groups according to the principle that mapping is sorted out by a subsystem or component
In not, and counts each security incident group and batch occurs.
As shown in Fig. 2, in a preferred embodiment of the invention, it can be by the Motor vehicle security fault data point
It is not mapped to structure security incident, electrical safety event, function logic security incident, collision safety event, thermally safe event, prevents
Quick-fried security incident, operation maintenance security incident, Environmental security event and Life cycle security incident.Also, returned according to data
Class, analysis and calculating, can obtain its base's probability of happening be respectively structure security incident 30%, electrical safety event 10%,
Function logic security incident 20%, collision safety event 5%, thermally safe event 5%, anti-explosion safety event 8%, operation maintenance peace
Total event 9%, Environmental security event 8%, Life cycle security incident 5%.The above-mentioned process that summarizes and analyzes can use ability
Known various methods in domain can also calculate each security incident group using known method and account for the general of whole safety failures
Rate, can also be using the respective measurement of electric vehicle manufacturer and acquisition empirical data.
In a preferred embodiment of the invention, it is described using conjoint analysis method in each security incident group
The Motor vehicle security fault data carry out classification building safety tree the step of further comprise: by the Motor vehicle security
Fault data is at least divided into Fisrt fault classification, the second fault category, third fault category and the 4th fault category；Using difference
Analytical described in Fisrt fault classification, second fault category, the third fault category and it is described 4th therefore
Hinder the Motor vehicle security fault data of classification, with the hierarchical relationship between the determination Motor vehicle security fault data
So that it is determined that bottom event, middle layer event and top layer event and the bottom event, the middle layer event, the top layer
Logic causality and security-critical degree between event；Failure causality is successively established until traversing all described electronic
Vehicle safety fault data is constructed with the safety tree for completing electric vehicle.Wherein, the Fisrt fault classification be mechanism it is clear or
Person's mechanism can verify that failure, and second fault category is that mechanism is unintelligible but failure with empirical verification basis, described the
Three fault categories are the failure that mechanism is not known but has operation data to support；4th class fault category is that mechanism is clear but system knot
Structure complex fault.For example, the Motor vehicle security fault data of Fisrt fault classification is divided into top layer thing according to mechanism
Part, middle layer event and bottom event；The Motor vehicle security of the second fault category is analyzed using Bayes estimation
The failure of fault data is because of data/coherency, thus based on result is analyzed by the Motor vehicle security failure of the second fault category
Data are divided into top layer event, middle layer event and bottom event；Using the institute of machine learning method analysis third fault category
The failure of Motor vehicle security fault data is stated because of data/coherency, thus based on result is analyzed by the electricity of third fault category
Motor-car safety failure data are divided into top layer event, middle layer event and bottom event；Using interpretative structural modeling method parsing the
The failure of the Motor vehicle security fault data of four fault categories is because of data/coherency, thus based on result is analyzed by the 4th event
The Motor vehicle security fault data of barrier classification is divided into top layer event, middle layer event and bottom event.
In a preferred embodiment of the invention, it is described using conjoint analysis method in each security incident group
The Motor vehicle security fault data carries out the step of classification building safety tree and further comprises: for top layer event and
Its corresponding whole bottom event is successively established between " IF ... THEN ... " regular description event according to its multilayer causality
Causality, until it is right to traverse all " top layer events-bottom event "；Based on the top layer event, the bottom event
And the middle layer event of the causality and experience between it generates and expresses patrolling for the top layer event and the bottom event
The regular collection for the relationship of collecting；Based on the regular collection, the top layer event, the bottom event and the middle layer thing
Part and the safety tree module building safety tree；The regular collection is verified to remove logical relation mistake or event
Mistake.
Fig. 3 a-3c is the schematic diagram of the Partial security tree of the preferred embodiment of the present invention.As shown in figs 3 a-3 c, structure is pacified
Three intermediate events, i.e. brake safe event, travel transmission security incident can be segmented below total event, and turn to safe thing
Part, we can construct safety tree to each event respectively.We are then illustrated by taking brake safe event as an example.Such as figure
3b, using the brake safe event as top layer event, it has been found that its actually with multiple middle security events and multiple bottoms
There are causalities between layer security incident.For the first kind, mechanism is clear or mechanism can verify that the event of failure, for example makes
Dynamic valve damage X14, pipe joint damage X16, hydraulic controller exception X21, The hydraulic oil are abnormal less than X24, hydraulic electric motor
X22 can directly obtain their causality, at this moment directly can determine that brake valve damages X14, pipe joint according to mechanism
It is bottom event that X16, hydraulic controller exception X21, The hydraulic oil, which are damaged, less than X24, hydraulic electric motor exception X22, using " IF ...
Causality between THEN ... " rule description event is if brake valve damage X14, pipe joint damage X16, hydraulic control
Device exception X21, The hydraulic oil are less than X24, hydraulic electric motor exception X22, then brake safe event occurs.
For the second class, mechanism is unintelligible but failure with empirical verification basis, analyzes the using Bayes estimation
The failure of the Motor vehicle security fault data of two fault categories is because of data/coherency, thus based on result is analyzed by the second event
The Motor vehicle security fault data of barrier classification is divided into top layer event, middle layer event and bottom event.With as schemed
Shown in 3c, using the brake safe event as top layer event, we are by bayesian algorithm, it can be found that turning to security incident
As the first middle layer event, respectively with the second middle layer event steering operation mechanism-trouble, turning machine failure, turn to execution machine
Structure failure causalnexus.And steering operation mechanism-trouble fastens abnormal, direction tubular shaft with multiple bottom event steering wheels respectively
It damages, steering hub column spline wear spline is tight, the direct causalnexus of solid screw sliding teeth, spline lubrication shortage of oil.Turning machine event
Barrier respectively with multiple bottom event turning machines lubrication shortage of oil X6, turning machine spline damage X7, turning machine gear wear damage X8,
Turning machine fastening screw pine X9, the turning machine immersion direct causalnexus of X10.Turn to actuator failure respectively with multiple bottom things
Part knuckle arm damage X11, steering ball end damage X12, steering goat's horn deform/are broken X13, stable direction bar fracture X14, turn to
Interfere the direct causalnexus of X15.
For third class, the failure that do not know for mechanism but have operation data to support can be using machine learning method point
The failure of the Motor vehicle security fault data of third fault category is analysed because of data/coherency, thus based on analysis result by the
The Motor vehicle security fault data of three fault categories is divided into top layer event, middle layer event and bottom event.Together
As shown in Figure 3b, using the brake safe event as top layer event, we are by similar state comparison method it can be found that parking
Brake fault effectively can function as first layer intermediate event, and itself and as first layer intermediate event service brake failure one
Sample and second layer intermediate event brake pressure deposit causality extremely.And brake pressure exception is braked with multiple bottom events
There are causalities by oil sealing damage X6, brake oil leak X5 and brake backing plate deformation X8.Simultaneously parking braking failure also with
Multiple bottom event handle damage X8, the sassafras pad wear X1 that rubs, brake cylinder clamping stagnation X2, tripping spring damage X3, transmission shaft damage
Directly there is causality in X12.
For the 4th class, mechanism is clear but system structure complex fault；4th fault category is parsed using interpretative structural modeling method
The Motor vehicle security fault data failure because of data/coherency, thus based on analysis result by the institute of the 4th fault category
It states Motor vehicle security fault data and is divided into top layer event, middle layer event and bottom event.It is same as shown in Figure 3b, by institute
Brake safe event is stated as top layer event, we are by interpretative structural modeling method it can be found that service brake failure can actually
As first layer intermediate event, and its sassafras pad wear X1 that rubs with multiple bottom events, brake cylinder clamping stagnation X2, tripping spring damage
Directly there is causality, while depositing cause and effect pass extremely with second layer intermediate event brake pressure again in X3, bracket bearing damage X4
System.And brake pressure is abnormal with bottom event braking oil sealing damages X6 and brake oil leak X5 there are causalities.
Therefore, those skilled in the art can according to the above instruction, and the entire safety that construct electric vehicle is set and/or it
Middle a part safety tree in a preferred embodiment of the invention, after building safety tree, verifies the regular collection to remove
Logical relation mistake or event mis.For " IF ... THEN ... " rule set that description is set safely, searches wherein affair logic and close
The mistake of system, common event relation mistake.
Safety tree of the invention be it is a kind of based on the analysis of data-driven, probability calculation and security-critical degree it is comprehensive, open
Formula, the security system in complete period are put, is the system model for evaluating vehicle safety state, is quantitative analysis system safety
The powerful of property.The safe tree body system can be designed for different safety failure classification, break through individually for each system
Component carries out the limitation of safety analysis, can preferably reflect Motor vehicle security situation.Safety tree is for security fields event
Barrier data are set up, and the correlation between each level safety failure data is other than logic-based is deduced, also by event of failure
Statistical nature and data are determined.Security tree model is absorbed in the event that really breaks down, is unfolded by mentality of designing or system
It tracks and barrier, modularization style of opening System Design is arranged in penetrating system.Based on new fault data can real-time update safely set,
Benign cycle is formed to continuously optimize.Safety tree application produces O&M process towards actual design, is more in line with engineering practice
It is required that.
In step s 2, the sequence of security-critical degree is carried out to each bottom event based on the safety tree.Of the invention
In preferred embodiment, the step S2 may further include S21. by the acquisition and statistics of middle layer event, described in analysis
The existing parameter error of middle layer event, by the original frequency data reduction of the middle layer event be it is standardized it is at different levels in
Between event frequency data；S22. it counts to obtain each bottom by the interpretation of result of the logic causality and the intermediate event
The probability of happening of layer event；S23. acquisition and the intermediate event frequency number based on the safety tree and the middle layer event
The probability of happening of each top layer event is obtained according to statistics；S24. based on each bottom event to the probability of each intermediate event, and
Influence probability of each bottom event to top layer event is calculated in the probability of happening of each top layer event；S25. based on each
Bottom event carries out the sequence of security-critical degree to each bottom event to the influence probability of each top layer event.
Preferably, in the step S21, by the acquisition and statistics of middle layer event, the middle layer event is analyzed
Existing parameter error, by the original frequency data reduction of the middle layer event be the standardized intermediate event frequencys at different levels
Data.In a preferred embodiment of the invention, the intermediate event fault data that can acquire the electric vehicle is united
Meter decoupling, for the dynamic change of operating parameter, analyzes parameter error that may be present.Parameter error and burst Failure Alarm,
Intermediate event initial data at different levels are constituted, and finally convert frequency data；It is corresponding for the original frequency data of intermediate events at different levels
Working environment, by original frequency data reduction be standardized intermediate event frequency data at different levels.Those skilled in the art know
It knows, the generation frequency of any each intermediate event of method statistic as known in the art can be used and is standardized amendment.
Preferably, in the step S22, the standardized intermediate events frequencies at different levels applying, test at the scene, under inspection scene are counted
Secondary data, and calculate separately the probability of happening of corresponding each bottom event.Preferably, in the step S22, pass through intermediate thing
The risk angle value of the generation frequency statistics and distribution, each intermediate event of part, calculates the probability of happening of top layer event；Preferably, exist
In the step S24, based on each bottom event to the probability of each intermediate event and the probability of happening of each top layer event,
Influence probability of the available each bottom event to top layer event is calculated by Bayes；Those skilled in the art know, remove
Except following calculation methods, those skilled in the art can also be counted using other calculation formula according to the actual situation
It calculates.The present invention is not limited herein by circular.
In a preferred embodiment of the invention, the different degree of the bottom event is equal to the generation of the top layer event
The probability of happening of the relatively described revised bottom event of standardization of probability seeks local derviation.It is of the invention it is further preferably
In embodiment, the security-critical degree of the bottom event can be calculated based on following formula:
Wherein, IGIt (i) is bottom event XiSecurity-critical degree；qiIt is the hair for standardizing the revised bottom event
Raw probability；G is the probability of happening of the top layer event, is about q1,q2,…qi,…,qNCut set set.
It, can be based on the hair for standardizing the revised bottom event in further preferred embodiment of the invention
Raw probability building structure function, building minimal cut set set, the knot of bottom event is calculated according to safety tree security-critical degree formula
Structure security-critical degree.For example it is assumed that there is i bottom event, the probability of happening of each bottom event is Xi, construct structure functionThen creation minimal cut set collection is combined into { X1, { X2, { X3},……,{Xi}。
Based on safety tree security-critical degree formulaIt can be with
Calculate safe tree construction security-critical degree
In step s3, determine whether the safe condition of the electric vehicle has reached threshold value.The threshold value for example can basis
The actual operation parameters of electric vehicle are configured, such as can be highest running speed, highest power consumption, etc. per hour.
The threshold value can be arranged according to actual manufacture, service experience in those skilled in the art.The threshold value can be one or more
Numerical value, certainly preferably multiple numerical value, the numerical value of the defective mode of especially multiple characterization electric vehicles.As previously mentioned, electronic
Vehicle safety performance is constantly in variation at any time.When electric vehicle operation duration reaches certain numerical value or undergoes certain situation
When, components or subsystem may generate great shadow to the security performance of electric vehicle due to components aging loss etc.
It rings, if at this time without processing, it may occur that catastrophe failure or even accident bring about great losses.Therefore when described
When the safe condition of electric vehicle centainly reaches threshold value, step S4 is needed to be implemented, carries out subsequent processing.If not reaching threshold
Value, it was demonstrated that the safe condition of the electric vehicle is fine, at this time without carrying out subsequent processing, continues real-time monitoring.
In step s 4, the branch high to security-critical degree in the safety tree is checked and is debugged.In failure
After exclusion, it can continue to monitor with return step S3.If the safe condition of monitoring discovery or the electric vehicle is
It is no to have reached threshold value, it was demonstrated that failure completely, needs further to check again without investigation.In this way, can be suitable according to security-critical degree
Sequence checks one, two in safety tree even more than branch, up to failure all exclusions, or will most of event
Barrier excludes, until the safe condition of the electric vehicle is lower than threshold value.The elimination failure includes maintenance, replacement components, function
The redesign of energy and/or structure.According to malfunctioning node occur logical relation, for components occur malfunction or damage,
It can repair or replace；If the reason of failure occurs is that the design of its structure or function there are unreasonable part, needs
The part is redesigned
In a preferred embodiment of the invention, it can be sorted and be selected according to the security-critical degree of each bottom event first
It selects and is not labeled in the safety tree and branch that security-critical degree is high is labeled, to obtain from the security-critical degree
The event train of thought line slave bottom event to top layer event of high branch；Then the event train of thought line is analyzed to obtain
The bottom event argument of the event train of thought line；Failure row is finally carried out to the bottom event based on the bottom event argument
It looks into and eliminates failure.After troubleshooting, it can continue to monitor with return step S3.If monitoring discovery is still described
Whether the safe condition of electric vehicle has reached threshold value, it was demonstrated that failure completely, needs further to check again without investigation.In this way,
One, two in safety tree can be checked even more than branch, according to security-critical degree sequence until failure is whole
It excludes, or by most of troubleshooting, until the safe condition of the electric vehicle is lower than threshold value.
It is described that the event train of thought line is analyzed described in acquisition in further preferred embodiment of the invention
The bottom event argument of event train of thought line further comprise according on the event train of thought line bottom event, middle layer event or
The changing rule of the different degree of each level event analyzes the event train of thought line in top layer event；For according to the thing
The event of different degree variation abnormality in bottom event, middle layer event or top layer event on part train of thought line, according to the event
The upstream and downstream of train of thought line finds out the bottom event actually occurred, determines the causality of the bottom event and obtains the bottom
The bottom event argument of event；For the event of no different degree variation abnormality, the bottom thing of the bottom event is directly acquired
Part parameter.
Below with reference to embodiment shown in Fig. 2-3b, the present invention is described as follows.For example, in the operation process of electric vehicle
In, it has been found that the safe condition of electric vehicle has reached danger threshold, for example braking distance is excessive, is more than danger threshold,
We will analyze its event train of thought line according to safety tree, it has been found that according to its different degree, braking distance is more than danger threshold
Event train of thought line is structure security incident-brake safe event-brake piping oil leak event/hydrostatic sensor anomalous event, because
This two-way event train of thought line is labeled by we for this.Then we are according to the bottom event (brake pipe on the event train of thought line
Road oil leak event/hydrostatic sensor anomalous event) middle layer event (brake safe event) or top layer event (the safe thing of structure
Part) in the changing rule of different degree of each level event the event train of thought line is analyzed, find the event train of thought line
On bottom event, do not have any anomalous variation in middle layer event or top layer event, therefore, it is considered that brake piping oil leak thing
A possibility that part/hydrostatic sensor anomalous event occurs is maximum, therefore obtains bottom event (brake piping and the hydraulic sensing
Device) bottom event argument, and be based on the bottom event argument, decision be brake piping and hydrostatic sensor overhaul also
It is replacement, still carry out redesigning etc..It has been reached in the safe condition that troubleshooting terminates and then judge electric vehicle
To danger threshold.If the safe condition of electric vehicle is already less than danger threshold at this time, it was demonstrated that our troubleshooting is very
Success, if the safe condition of electric vehicle still has reached danger threshold at this time, it was demonstrated that our troubleshooting is unsuccessful,
Problem may be actually occurred is other bottom events.Therefore we again return to safe tree, at this moment because of the safe thing of structure
This event train of thought line of part-brake safe event-brake piping oil leak event/hydrostatic sensor anomalous event has been marked
, in addition we will select an event train of thought line according to its different degree from safety tree, such as we can choose structure peace
Total event-brake safe event-brake pressure exception-braking oil sealing damage.Similarly, we can repeat aforesaid operations, until
The safe condition of electric vehicle is already less than danger threshold.
There is a kind of situation, for according to bottom event, middle layer event or the top layer event on the event train of thought line
The event of middle different degree variation abnormality finds out the bottom event actually occurred according to the upstream and downstream of the event train of thought line, determines
The causality of the bottom event and the bottom event argument for obtaining the bottom event.Such as assume us according to event arteries and veins
Winding thread, such as we can choose the damage of structure security incident-brake safe event-brake pressure exception-braking oil sealing, still
It was found that the degree of safety of braking oil sealing damage is abnormal, abnormal for brake pressure, at this moment, we will continue to consider braking
Other bottom events of pressure anomaly, brake oil leak, brake backing plate deform situations such as, last those skilled in the art according to
Actual Vehicular behavior and priori could be aware that the bottom event actually occurred is actually that brake backing plate becomes
At this moment shape obtains the bottom event argument of the bottom event (brake backing plate deformation), and be based on the bottom event argument,
Decision is that brake backing plate is overhauled or replaced, still carry out redesigning etc..Terminate in troubleshooting and then
Judge that the safe condition of electric vehicle has reached danger threshold.If the safe condition of electric vehicle is already less than danger at this time
Threshold value, it was demonstrated that our troubleshooting is extremely successful, if the safe condition of electric vehicle still has reached danger threshold at this time
Value, it was demonstrated that our troubleshooting is unsuccessful, and may actually occur problem is other bottom events.Therefore we again return to
To safe tree, at this moment because structure security incident-brake safe event-brake pressure exception-brake backing plate deforms this thing
Part train of thought line has been marked, in addition we will select an event train of thought line according to its different degree from safety tree, can be with
Aforesaid operations are repeated, until the safe condition of electric vehicle is already less than danger threshold.
Implement the electric vehicle O&M optimization method of the invention based on security tree model, it can be in actual operation mistake
The safety of Cheng Zhong, the continually changing electric vehicle of Motor vehicle security performance carry out real-time, accurate, digitized assessment, from
And according to safety tree module, comprehensive each safety failure state, to be timed quantitative retouch to the safe condition of electric vehicle
It states, and then realizes the guidance for manufacturing maintenance operation maintenance to electric vehicle, to improve the safety of electric vehicle.
Another technical solution that the present invention solves the use of its technical problem is to construct a kind of computer readable storage medium,
It is stored thereon with computer program, the electric vehicle based on security tree model is realized when described program is executed by processor
O&M optimization method.
Therefore, the present invention can be by hardware, software or soft and hardware in conjunction with realizing.The present invention can be at least one
It is realized in a centralised manner in a computer system, or the different piece in the computer system by being distributed in several interconnection is to divide
Scattered mode is realized.Any computer system that the method for the present invention may be implemented or other equipment are all applicatory.It commonly uses soft or hard
The combination of part can be the general-purpose computing system for being equipped with computer program, by installing and executing program-con-trolled computer system
System, runs it by the method for the present invention.
The present invention can also be implemented by computer program product, and program includes that can be realized the complete of the method for the present invention
Method of the invention may be implemented when it is installed in computer system in portion's feature.Computer program in this document is signified
: system can be made using any expression formula for one group of instruction that any program language, code or symbol are write, the instruction group
With information processing capability, to be directly realized by specific function, or after carrying out one or two following step specific function is realized
Can: a) it is converted into other Languages, coding or symbol；B) it reproduces in a different format.
Therefore the invention further relates to a kind of computer readable storage mediums, are stored thereon with computer program, described program
The safe tree constructing method of the electric vehicle is realized when being executed by processor.
The invention further relates to electric vehicle, including processor, the computer program being stored in the processor, the journey
The safe tree constructing method of the electric vehicle is realized when sequence is executed by processor.
Implement the electric vehicle O&M optimization method and computer readable storage medium of the invention based on security tree model,
Can for during actual operation, the safety of the continually changing electric vehicle of Motor vehicle security performance carry out in real time,
Accurately, digitized assessment, thus according to safety tree module, comprehensive each safety failure state, thus to the safety of electric vehicle
State is timed quantitative description, and then realizes the guidance that maintenance operation maintenance is manufactured to electric vehicle, to improve electronic
The safety of vehicle.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (10)
1. a kind of electric vehicle O&M optimization method based on security tree model characterized by comprising
S1. building safety tree, the safety tree includes multiple bottom events, middle layer event, top layer event and the bottom
Event, the middle layer event, the logic causality between the top layer event and security-critical degree；
S2. the sequence of security-critical degree is carried out to each bottom event based on the safety tree；
S3. determine whether the safe condition of the electric vehicle has reached threshold value, if it is step S4 is executed, otherwise continue to assess；
S4. the branch high to security-critical degree in the safety tree is checked and is debugged, then return step S3.
2. the electric vehicle O&M optimization method according to claim 1 based on security tree model, which is characterized in that described
Step S4 further comprises:
S41. it is not labeled in being set safely according to the security-critical degree sequencing selection of each bottom event and safe
The high branch of different degree is labeled, to obtain from the high branch of the security-critical degree slave bottom event to top layer event
Event train of thought line；
S42. the event train of thought line is analyzed to obtain the bottom event argument of the event train of thought line；
S43. malfunction elimination is carried out to the bottom event based on the bottom event argument and eliminates failure, then return step
S3。
3. the electric vehicle O&M optimization method according to claim 2 based on security tree model, which is characterized in that described
Step S42 further comprises:
S421. according to the weight of each level event in bottom event, middle layer event or the top layer event on the event train of thought line
The changing rule to be spent analyzes the event train of thought line；
S422. for according on the event train of thought line bottom event, different degree changes in middle layer event or top layer event
Abnormal event, the bottom event actually occurred is found out according to the upstream and downstream of the event train of thought line, determines the bottom event
Causality and obtain the bottom event argument of the bottom event；For the event of no different degree variation abnormality, directly
Obtain the bottom event argument of the bottom event.
4. the electric vehicle O&M optimization method according to claim 3 based on security tree model, which is characterized in that described
Eliminating failure includes maintenance, replacement components, the redesign of function and/or structure.
5. the electric vehicle O&M optimization method described in any one of -4 based on security tree model according to claim 1,
It is characterized in that, the step S1 further comprises:
S11. the Motor vehicle security fault data of electric vehicle is acquired；
S12. Motor vehicle security fault data mapping is referred in different security incident groups, and statistics is each respectively
A security incident group frequency data；
S13. the Motor vehicle security fault data in each security incident group is divided using conjoint analysis method
Class building safety tree.
6. the electric vehicle O&M optimization method according to claim 5 based on security tree model, which is characterized in that described
Step S13 further comprises:
S131. the Motor vehicle security fault data is at least divided into Fisrt fault classification, the second fault category, third failure
Classification and the 4th fault category；
S132. using Fisrt fault classification, second fault category, the third failure described in different analyticals
The Motor vehicle security fault data of classification and the 4th fault category, with the determination Motor vehicle security number of faults
Hierarchical relationship between so that it is determined that bottom event, middle layer event and top layer event and the bottom event, it is described in
Logic causality and security-critical degree between interbed event, the top layer event；
S133. it is electronic to complete up to traversing all Motor vehicle security fault datas successively to establish Failure causality
The safety tree building of vehicle.
7. the electric vehicle O&M optimization method described in any one of -4 based on security tree model according to claim 1,
It is characterized in that, the step S2 further comprises
S21. the acquisition and statistics for passing through middle layer event, analyze the existing parameter error of the middle layer event, will be described
The original frequency data reduction of middle layer event is standardized intermediate event frequency data at different levels；
S22. it counts to obtain the hair of each bottom event by the interpretation of result of the logic causality and the intermediate event
Raw probability；
S23. acquisition and the intermediate event frequency data statistics based on the safety tree and the middle layer event obtain respectively
The probability of happening of a top layer event；
S24. the probability of each intermediate event and the probability of happening of each top layer event are calculated based on each bottom event
Influence probability to each bottom event to top layer event；
S25. security-critical degree is carried out to each bottom event based on influence probability of each bottom event to each top layer event
Sequence.
8. the electric vehicle O&M optimization method according to claim 7 based on security tree model, which is characterized in that described
Step S21 includes:
S211. it acquires the fault data of the intermediate event of the electric vehicle and carries out Statistical Solutions coupling, for the electric vehicle
Operating parameter dynamic change, analyze existing parameter error；By the burst in the parameter error and the fault data
Original frequency data of the Failure Alarm event as the middle layer event；
S212. it is directed to the corresponding working environment of original frequency data of intermediate events at different levels, by the original frequency data reduction
For standardized intermediate event frequency data at different levels；And/or
The step S22 includes: the standardized intermediate event frequencys at different levels for counting and applying, test at the scene, under inspection scene
Data, and calculate separately the probability of happening of corresponding each bottom event.
9. the electric vehicle O&M optimization method according to claim based on security tree model, which is characterized in that in institute
It states in step S23, by the risk angle value of the generation frequency statistics and distribution, each intermediate event of intermediate event, calculates top layer thing
The probability of happening of part；And/or
In the step S24, each bottom event is calculated to the influence probability of the top layer event using bayesian algorithm.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that described program is processed
The electric vehicle fortune described in any one of -9 claims according to claim 1 based on security tree model is realized when device executes
Tie up optimization method.
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| CN112700156A (en) * | 2021-01-07 | 2021-04-23 | 武汉理工大学 | Construction method of new energy automobile operation safety performance evaluation system |
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| WO2020211846A1 (en) | 2020-10-22 |
| CN110097219B (en) | 2020-04-24 |
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