CN106353690A - Method for diagnosing lithium battery faults by Petri net - Google Patents
Method for diagnosing lithium battery faults by Petri net Download PDFInfo
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- CN106353690A CN106353690A CN201610835679.5A CN201610835679A CN106353690A CN 106353690 A CN106353690 A CN 106353690A CN 201610835679 A CN201610835679 A CN 201610835679A CN 106353690 A CN106353690 A CN 106353690A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02H—EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS
- H02H7/00—Emergency protective circuit arrangements specially adapted for specific types of electric machines or apparatus or for sectionalised protection of cable or line systems, and effecting automatic switching in the event of an undesired change from normal working conditions
- H02H7/18—Emergency protective circuit arrangements specially adapted for specific types of electric machines or apparatus or for sectionalised protection of cable or line systems, and effecting automatic switching in the event of an undesired change from normal working conditions for batteries; for accumulators
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- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention discloses a method for diagnosing lithium battery faults by the Petri net. For diagnosis of electric quantity nonuniformity of single lithium batteries, a Petri net system is adopted for constructing a fault diagnosis model, and fault information for analysis comes from external battery voltage, current, temperature and system operating time. According to the method for diagnosing the lithium battery faults, various factors are considered in fault diagnosis, and diagnosis operation is quick; high efficiency shows up in various complicated systems; the Petri net based fault diagnosis model is capable of quickly working out a fault position according to a corresponding incidence matrix and calling an associated judgment model for confirming fault occurrence, so that real-time monitoring of battery operating conditions can be well realized in an operation process of a battery pack system, and fault information can be processed timely.
Description
Technical field
The present invention relates to lithium battery fault diagnosis, the method particularly to netting diagnosis lithium battery fault using petri.
Background technology
The energy density of lithium battery is high, power density is big, have extended cycle life, and is suitable as electrokinetic cell, currently many needs
The occasion of electrokinetic cell to be applied all is consisted of series-parallel mode multisection lithium battery.But lithium battery is to working environment
Requirement stricter, in order to obtain the optimal working condition of battery it is necessary to battery management system is carried out to its state in real time
Monitoring, to ensure that running voltage, electric current, temperature and battery with two side terminals be maintained in normal scope.If there is exception
Signal, battery management system should be also equipped with the ability of fault diagnosis, can timely identify and fix a breakdown.Using two-stage
State machine realizing the on-line fault diagnosis of lithium battery, the program be first by the fault of battery module by cell fault
The order of severity be classified, for different grades of fault, system will take different measures.Utilize will be dissimilar simultaneously
Fault with different coded representations, be so easy to the communication of fault message and the computing of processor.For equal between set of cells
The problem of weighing apparatus, generally by the measurement to monomer battery voltage, and given threshold, when the inconsistent certain value that exceedes of voltage
When begin to carry out electric quantity balancing.Another kind of electrokinetic cell monomer fault diagnosis and method for maintaining, are based on to battery cell
The measurement of voltage, from measurement fault, total cell resistance fault and connect Resistance Fault to be analyzed in terms of these three and therefore
Barrier diagnosis, fault location when its fault diagnosis result can be keeped in repair with assist trouble.
The existing diagnostic method being directed to battery cell voltage differences is that whether voltage measurement for battery cell
The differentiation of fault, total internal resistance fault and contact resistance fault and diagnosis, the diagnostic result being given is very general, and for battery
The inconsistent of voltage only exists a threshold value, and the diagnostic result that can be given is too coarse, is relatively specific at offline fault
Reason, the requirement of inapplicable on-line fault diagnosis and process.For the method for on-line fault diagnosis, need the electricity to battery cell
Pressure, temperature, electric current carry out Real-time Collection it is desirable to be able to provide more clear and definite fault diagnosis result, thus realize fault
Line is processed.
When the inconsistent situation of voltage occurs between for battery cell, system need according to the inconsistent degree of voltage and
The operating current of battery, the situation of change of temperature judge for the state needing to carry out electric quantity balancing.Due to cell voltage
The inconsistent situation of appearance differs to establish a capital and is because the inconsistent of electricity, leads to can also be polarization electricity the reason voltage is inconsistent
The inconsistent and internal resistance of cell of pressure inconsistent.Therefore, occur simply by the measurement of cell voltage is just given with battery
The inconsistent fault diagnosis conclusion of electricity is inaccurate, so frequently can lead to electric quantity equalizing system and goes equilibrium originally not need all
The battery of weighing apparatus, has done idle work and has not said, also affected the poised state of battery in battery pack.
Content of the invention
Whether the problem to be solved in the present invention is to discriminate between opening is the real state needing electric quantity balancing, or be merely only
Strengthening radiating just can be with solve problem.In order to solve problem above, the present invention proposes a kind of lithium battery on-line fault diagnosis method,
Comprise n battery cell in set of cells, net the model solution building fault diagnosis using petri for electricity between single lithium battery
The inconsistent diagnosis of amount, the fault message for analysis comes from outside cell voltage, electric current, temperature and system operation
Time.
Petri net is made up of several places s, transition t, directed arc and torr (token)；Described place and transition are passed through
Described directed arc is attached, and according to described directed arc direction, described place is divided into input place and the transition of described transition
Output place；When the input place of described transition has torr then it represents that described transition are allowed to execute.The spy of petri net
Point is can to process asynchronous, concurrent signal it is adaptable to during to system malfunctions, the description to the dynamic change of system.When
During for fault diagnosis, place s is meant that various states, and the implication of transition t is so that the event of state change, the containing of torr
Justice is the presence of fault message, and what whole petri net was described is if wherein going out the fault message of present condition, then this information
It is how to transmit between state, thus reaching another state.The foundation of petri net is based on the reasoning that battery failures are diagnosed
Logic obtains, and from the beginning of bottom state (abnormality that can be separated by sensor regions), through intermediateness, reaches final
Failure cause.If the torr for describing fault degree information meets transition occurrence condition, in state, torr will occur
Transfer, the result of its weights between the torr number that the performance in petri net is in s deducts from s to t needs non-negative.For
The incidence matrix d of description petri net characteristic is exactly to be made up of the weights between from s to t and from t to s.
In battery failures diagnostic system, pass through when the inconsistent diagnosing malfunction of electricity between battery cell
Whether the multi-signal that the outside collection of analysis comes is in the state needing to carry out electric quantity balancing come the state to judge present battery,
Meanwhile, can also be by judging whether taken measure has improvement to the phenomenon of fault, if do not had after providing diagnostic result
If having improvement to be even degrading, more higher leveled measure will be taken.Then, the torr in petri net can be used for describing difference
The fault of grade, because for identical failure cause, if fault level difference, failure cause is also likely to be different
's.The computing of last the used state matrix of diagnosis algorithm by petri net, for fault quantitative analyses when will
Shorten the time of computing, for on-line analysis system, timely provide the enforcement that diagnostic result is conducive to control strategy.
It is necessary first to be built according to the operation principle of battery and the process breaking down before diagnostic system runs
Petri pessimistic concurrency control, this model is totally divided into three layers: ground floor, fault-signal detection layers, and it is straight by sensor that this layer is responsible for response
Connect the fault-signal of input, the detection limit for battery management system fault diagnosis system mainly includes following items: voltage, electricity
Stream, temperature, vibrations.Therefore fault-signal detection layers can determine the state of 4 inputs, is respectively as follows: the inspection of voltage inconsistent degree
Survey, charging and discharging currents become big, temperature is inconsistent, external vibration detection.
The second layer, accident analysis layer, this layer is processed to the fault-signal of input, by comparing, the side of logical operationss
The reason formula judges corresponding to this fault-signal.For battery management system fault diagnosis system, inconsistent when voltage occurs
During abnormal signal, need to be classified according to inconsistent degree, voltage inconsistent degree one-level, voltage can be divided into inconsistent
Two grades of degree, voltage inconsistent degree these three states of three-level, the rule of networking can not exist for three state simultaneously, needs to increase
Plus the inhibitor arc in petri net, to carry out the interlocking between state.It is then due to voltage occurring not for the inconsistent state of internal resistance
The next state that the state of consistent degree one-level is obtained by logical reasoning.When being merely only that the inconsistent shape of internal resistance occurs
State, when other detection limit electric currents, temperature, vibrations are all normal, then can obtain the state of cell degradation with reasoning.
Third layer, failure cause layer, this layer is the conclusion output after diagnosing for fault-signal.For battery management system
Fault diagnosis system, the conclusion of the fault diagnosis that can occur is that polarizing voltage is inconsistent, connector fault, cooling system therefore
Slightly short circuit, soc are inconsistent for barrier, inside battery.The reason inconsistent fault of polarizing voltage occurs wherein is led to be due to battery
The situation that the inconsistent state big with charging and discharging currents change of internal resistance occurs, leads to connector fault to be because the internal resistance of cell is inconsistent
With exterior vibration occur abnormal led to, cooling system fault is inconsistent with temperature to be led to because the internal resistance of cell is inconsistent
, the slight short trouble of inside battery is led to because two grades of the inconsistent degree of voltage is inconsistent with temperature, and soc is inconsistent
By the inconsistent degree of voltage, two grades are led to cell degradation.
By determining this three layers it is possible to construct the whole battery failures diagnostic system based on petri net.
The operating procedure of this diagnostic system is:
(1) according to the requirement of systematic function, fault level is divided.For the fault-signal of cell voltage, work as monomer
When the meansigma methodss difference of the magnitude of voltage of battery and battery in battery pack voltage is within 100mv, the inconsistent degree of cell voltage
For the first order；It is less than or equal to 500mv when the magnitude of voltage of battery is more than 100mv with the meansigma methodss difference of battery in battery pack voltage
When, the inconsistent degree of cell voltage is the second level；When the magnitude of voltage of cell and the meansigma methodss of battery in battery pack voltage
When difference is more than 500mv, the inconsistent degree of cell voltage is the third level.For the fault-signal of battery temperature, it is monomer electricity
The temperature of the neighbouring collection in pond is more than the temperature value at other temperature acquisition points in set of cells more than 1 DEG C.Event for electric current
Barrier signal is the work electricity of the set of cells that the current value that this battery cell is obtained by corresponding sampling resistor is located with this battery
Stream difference is more than maximum euqalizing current 500ma during electric quantity balancing circuit start.Rule of judgment for abnormal vibration is and deposits
The vibration amplitude of storage compares the normal vibration amplitude range (mm) more than system condition.In the running of battery system, such as
The parameter that fruit is monitored exceeds set threshold value, you can be judged as the signal that breaks down, this fault-signal is examined as fault
The input in of disconnected system.
(2) determine origin identification m that fault diagnosis system is run0.State equation m for petri net system0+ d*u=
M, wherein m0For initial mark, it is the matrix being made up of the torr that whole place in system under initial state comprises, table
The original state of bright system；U is to enable to m0To the transition sequence of m, show that system have passed through those during running
Transition or single step transition (t)；M identifies for result, shows the state that system is reached after transition；D is petri
The incidence matrix of net, is the intrinsic parameter of petri net.When the input in of fault diagnosis system is not zero, fault diagnosis
Program brings into operation.First, input in is assigned to m0, as origin identification.Then, if other places all do not contain in system
There is torr (show not breaking down in other states information), then enter (3rd) step；If existed containing torr in system
Place (show to break down in other states information), then according to m0'=m0+ m, by original status indicator m and m0Composition is new defeated
Enter status indicator m0', enter (3rd) step.
(3) system is by initial marking input state equation m0+ d*u=m is calculated and is only passed through a step in petri net between it
Change the status indicator that just can reach, enter (4th) step；If in the absence of one step transition mark or according to calculating
State equation calculates the mark (explanation is unsatisfactory for changing the condition occurring) being still equal to input originally, then go to (6th) step.
(4) according to determined by previous step, u (due to only one step, so u is t), judges that the generation of transition t therein is no
Rationally.The concrete method judging is as follows.For battery polarization voltage, conforming judgement is the single order capacitance-resistance model according to battery
The polarizing voltage formula u of battery can be obtainedp(t)=up(0)e-t/τ+irp(1-e-t/τ), u in formulapT () is the polarization in t
The size of voltage, τ=cprpFor battery polarization electric capacity cpWith battery polarization internal resistance rpProduct, i be operating current.By by electricity
The value of pond monomer actual measurement is compared with the value of system, you can obtain the result judging computing.For battery soh state, (battery is old
Change degree) conforming judgement is realized by look-up table, because the state of battery soh becomes during single work
Change less.For the impact to its capacity for the battery temperature, adopted model is c=c25(1-a* (25-t)), * wherein c is in temperature
Capacity (ah) for battery during t；c25It is the capacity (ah) of the battery when 25 DEG C；α is temperature correlation coefficient, and unit is ah/ DEG C, it
It is an empirical data；T is Current Temperatures.Judgement for soc state is to be come using the result that ampere-hour integration method calculates
Realize, formula is:
Wherein soctFor the state of the soc of t, η1For the coulomb efficiency of battery, generally take 1, η2Filling for battery
Discharging efficiency, is obtained by consulting battery parameter.For the total internal resistance of battery, inconsistent judgement is to measure fault by removal system
Mode determining, specific practice is exactly the history checking oneself and comparing voltage and electric current in data collecting system by system
The mode of parameter, judges whether data acquisition circuit breaks down, if inspection result is judged as normally, confirming battery system
The inconsistent fault of internal resistance occurs, is not due to the fault of detecting system and leads to.For cooling system fault judgement then
It is by comparing the parameter under the running parameter of cooling system under current state (voltage, rotating speed, air pressure) and normal condition.Above-mentioned
Determination methods be need to be determined according to t using therein which kind of, be not that each will be used under current procedures.If
T is identified generation rationally, then corresponding place s will give respective numbers according to the delivery value in set petri net
Torr, enters (5th) step.Occur unreasonable, then not assignment, retain original system banner, proceed to (6th) step.
(5) status indicator of system is updated, goes back to (3rd) step
(6) status indicator obtaining is exported as fault diagnosis result.
A kind of method of utilization petri net diagnosis lithium battery fault, comprises the following steps:
First, the foundation of the battery failures diagnostic cast based on petri net
It is necessary first to be built according to the operation principle of battery and the process breaking down before diagnostic system runs
Petri pessimistic concurrency control, this model is totally divided into three layers: fault-signal detection layers, and it is defeated by sensor that the place of this layer is responsible for response
The fault-signal entering；Accident analysis layer, the place of this layer is processed to the fault-signal of input, by comparing, logical operationss
Mode the reason judge corresponding to this fault-signal；Failure cause layer, the place of this layer be for fault-signal diagnosis after
Conclusion exports.Place s in petri net system is used for constituting the various states in above-mentioned three layers.Transition in petri net system
T is the event that the state that enables to changes, and the condition that it is activated is the token included in all of place of input
Number is more than the weights between them.Then the transition that have activated are after rational judgement, it will the storehouse follow-up to it
Given token, quantity depends on weights between the two.Token (token) in petri net system is then used for representing fault
The presence of information and the expression of fault degree.
2nd, divide the fault level of battery
For the fault-signal of cell voltage, when the magnitude of voltage of cell and the average value difference of battery in battery pack voltage
When value is within 100mv, the inconsistent degree of cell voltage is the first order；Magnitude of voltage and battery in battery pack voltage when battery
Meansigma methodss difference be more than 100mv be less than or equal to 500mv when, the inconsistent degree of cell voltage be the second level；Work as cell
Magnitude of voltage and battery in battery pack voltage meansigma methodss difference more than 500mv when, the inconsistent degree of cell voltage is the 3rd
Level；The fault-signal of battery temperature is that the temperature of the neighbouring collection of cell is more than at other temperature acquisition points in set of cells
Temperature value is more than 1 DEG C；Failure of the current signal be current value that corresponding battery cell obtains by corresponding sampling resistor and
The operating current difference of the set of cells that described battery cell is located is more than maximum euqalizing current during electric quantity balancing circuit start
500ma；The Rule of judgment of abnormal vibration is the normal vibration amplitude range compared with the vibration amplitude of storage more than system condition
(mm)；Using above fault-signal as method for diagnosing faults input in；
3rd, determine the origin identification of petri net
State equation for analyzing petri net system is m0+ d*u=m, wherein m0For initial mark, it is by initial shape
The row matrix that the token number that in system under state, each place comprises is constituted, shows the original state of system；U is to enable to
m0To the transition sequence of m, show that system have passed through those transition or single step transition (t) during running；M is
Result identifies, show into the state that reached of system after transition；The incidence matrix that d nets for petri, is that petri net is intrinsic
Parameter, is made up of to the weights changing or be transitted towards place place.Ms is institute in petri net each place in zero input
The row matrix that the token number comprising is constituted, original state when showing that the zero of system inputs.
Input: when break down signal in when, in fault-signal detection layers during petri is netted, corresponding place is carried out
Assignment, the token number of the place of the signal that do not break down keeps 0 constant, the place of the signal that breaks down, tight according to fault
Weight degree gives token number: the first order assigns 1, and the second level assigns 2 ... by that analogy.After assignment finishes, by each place
The row matrix that the token number comprising is constituted is denoted as min.
Output: origin identification m of petri net0=min+ms.Enter the 4th step.
4th, calculate the system mode mark m reaching after step transitionn
M will be identifiedn-1(initial value is m0) substitute into state equation mn-1+ d*u=mnIn, in calculating petri net between it only
The status indicator that just can be reached by step transition, enters the 5th step.Specific algorithm is to form whole transition first
Unit matrix be assigned to u, this matrix with petri net included in transition quantity as line number, place quantity be columns.Then take square
Every a line and m in battle array (d*u)n-1It is added, take the row matrix that wherein result does not contain negative to be designated as mnI (), i is corresponding row
Number.Next judge whether the generation changing i is reasonable, and the method for judgement is exactly the event that measured parameter is updated to transition
In function, verify whether this event occurs really.Finally, mn=∑Rational transition imn(i).If status indicator mnIn only fault
The place of reason layer contains token number or mn-1=mn(explanation is unsatisfactory for changing the condition occurring), then go to the 6th step, otherwise
Enter the 5th step.
5th, the system mode obtaining is identified as new input
Sequence number n of system mode mark adds 1, and n=n+1 is then return to the 4th step.
6th, according to mnOutput fault diagnosis result
By the status indicator obtaining mnIn belong to the place of failure cause layer as defeated the reason fault containing token number
Go out.
Further, for judge in step 4 the generation changing whether rational method particularly as follows: for battery polarization
The conforming judgement of voltage is the polarizing voltage formula u that can obtain battery according to the single order capacitance-resistance model of batteryp(t)=up(0)
e-t/τ+irp(1-e-t/τ), u in formulapT () is the size of the polarizing voltage in t, τ=cprpFor battery polarization electric capacity cpWith electricity
Pond polarization resistance rpProduct, i be operating current.Compared with the value of system by the value surveying battery cell, you can
To the result judging computing.It is to be realized by look-up table for battery soh state (cell degradation degree) conforming judgement
, because the state change of battery soh is little during single work.The impact to its capacity for the battery temperature is adopted
It is c=c with model25(1-a* (25-t)), * wherein c is the capacity (ah) of the battery when temperature is for t；c25It is the battery when 25 DEG C
Capacity (ah)；α is temperature correlation coefficient, and unit is ah/ DEG C, and it is an empirical data；T is Current Temperatures.For soc shape
The judgement of state is the result that calculated using ampere-hour integration method to be realized, and formula is:
Wherein soctFor the state of the soc of t, η1For the coulomb efficiency of battery, generally take 1, η2Filling for battery
Discharging efficiency, is obtained by consulting battery parameter.For the total internal resistance of battery, inconsistent judgement is to measure fault by removal system
Mode determining, specific practice is exactly the history checking oneself and comparing voltage and electric current in data collecting system by system
The mode of parameter, judges whether data acquisition circuit breaks down, if inspection result is judged as normally, confirming battery system
The inconsistent fault of internal resistance occurs, is not due to the fault of detecting system and leads to.For cooling system fault judgement then
It is by comparing the parameter under the running parameter of cooling system under current state (voltage, rotating speed, air pressure) and normal condition.
Brief description
Fig. 1 lithium battery fault diagnosis system operational flow diagram
Fig. 2 lithium battery fault diagnosis petri pessimistic concurrency control
Specific embodiment
Method for diagnosing faults in the present invention be by the information such as the voltage of Real-time Collection lithium battery, electric current and temperature Lai
Judge now whether lithium battery occurs to need fault to be processed, in the event of fault, it will take some treatment measures, such as
Open electric quantity balancing circuit, the effect increasing cooling system or the power reducing input/output, also continue to battery simultaneously
Monitoring state, the treatment effect to fault for the observed and recorded.Fault will be analyzed again produce when fault level rises
Raw the reason, and take further process action, point out for example to staff's dependent failure.When fault level is to the superlative degree
When will starting protection system, prevent fault from deteriorating further.And when improving situation is to normal condition, it will stop
The treatment measures taken before only, meanwhile, the fault message of system and the treatment measures taken also can be stored, enter
One step improves the efficiency of lithium battery fault diagnosis system, and the fault diagnosis model for setting up more perfect makes reference.Due to herein
Designed petri net fault diagnosis system is the system of a reaction equation, and in master control mcu, the program of fault diagnosis part is run
Flow chart is as shown in Figure 1.Because the feature of this system is that when only occurring input signal, system just can be called, normal shape
Under state being will not be invoked, therefore adopts this method of operation.When having input signal, system can be according to petri
Pessimistic concurrency control finds corresponding failure cause.
The specific implementation step of the inventive method is as follows:
Step one: the operation principle according to lithium battery and the process breaking down build petri pessimistic concurrency control.
In the present embodiment, diagnostic reasoning logic set up petri net according to lithium battery fault is as shown in Fig. 2 wherein storehouse
And transition implication as shown in table 1.The real work of lithium battery needs the parameter of monitoring to have voltage, electric current, temperature, vibration,
If occurring in that abnormal signal in them, then to represent for needing corresponding place in the petri net of fault diagnosis
The appearance of abnormal signal.Constitute petri net accordingly, as directly place s1, s7 that abnormal signal is responded, s8, s10
Fault-signal detection layers.The mode of concrete assignment is shown in step 2.Place s2, s3, s4, s11 constitute accident analysis layer, they
It is intermediateness when fault-signal is propagated in petri net.Place s5, s6, s9, s12, s13, s14 constitute failure cause
Layer, is responsible for the result of output fault diagnosis.T1～t10 is the judgement event that the token enabling in place occurs transition.
The implication of place and transition in table 1 petri net
Step 2: divide the fault level of battery
For the fault-signal of cell voltage, when the magnitude of voltage of cell and the average value difference of battery in battery pack voltage
When value is within 100mv, the inconsistent degree of cell voltage is the first order, and s1 obtains a token；When battery magnitude of voltage with
When the meansigma methodss difference of battery in battery pack voltage is more than 100mv and is less than or equal to 500mv, the inconsistent degree of cell voltage is the
Two grades, s1 obtains two tokens；When the magnitude of voltage of cell and the meansigma methodss difference of battery in battery pack voltage are more than 500mv
When, the inconsistent degree of cell voltage is the third level, and s1 obtains three tokens；The temperature of the neighbouring collection of cell is more than electricity
More than 1 DEG C, s10 obtains a token to temperature value at other temperature acquisition points in the group of pond；The corresponding electric current of battery cell is adopted
The current value obtaining at sample resistance is more than maximum Jun Heng electricity during electric quantity balancing circuit start with the operating current difference of set of cells
During stream 500ma, s7 obtains a token；The Rule of judgment of abnormal vibration is more than system condition compared with the vibration amplitude of storage
Normal vibration amplitude range (mm), s8 obtain a token.So when abnormal signal in battery parameter, petri net system
Place in the fault-signal detection layers of system just obtains token.Thus fault diagnosis system is started working.
Step 3: determine origin identification m of petri net0
m0By ms and minComposition.Ms is original state during zero input of system, unrelated with inputting.When fault-signal detection
When obtaining token in the place of layer, minObtain the change of analog value, thus updating m0Value.Enter step 4.
Step 4: calculate the system mode mark m reaching after step transitionn
In the present embodiment, for state equation mn-1+ d*u=mn, the unit matrix that u is 10 × 10 can be obtained, d is as follows
Shown.
*Do not occur for transition
Then solve mnIf, status indicator mnIn the place of only failure cause layer contain token number or mn-1=mn
(explanation is unsatisfactory for changing the condition occurring), then go to step 6, otherwise enters step 5.
Step 5: sequence number n of system mode mark adds 1, n=n+1 is then return to step 4.
Step 6: by the status indicator obtaining mnIn belong to the place of failure cause layer as fault containing token number
Reason exports.
Claims (1)
1. a kind of method using petri net diagnosis lithium battery fault is it is characterised in that comprise the following steps: one, according to lithium electricity
The operation principle in pond and the process structure petri pessimistic concurrency control breaking down:
Before diagnostic system runs, the operation principle first according to battery and the process breaking down build petri pessimistic concurrency control,
This model is divided into three layers: fault-signal detection layers, and the place of this layer is responsible for responding the fault-signal inputting by sensor；Fault
Analysis layer, the place of this layer is processed to the fault-signal of input, judges that this fault is believed by comparing, by way of logical operationss
The reason corresponding to number；Failure cause layer, the place of this layer is the conclusion output after diagnosing for fault-signal；Petri net mould
Place s in type is used for constituting the various states in above-mentioned three layers, and the transition t in petri net system is to enable to state to send out
The raw event changing, the condition that it is activated is that the token number included in all of place of input is more than the power between them
Value；Then the transition that have activated are after rational judgement, it will give token to its follow-up place, quantity depends on
In weights between the two；Token in petri net system is then used for representing the presence of fault message and the table of fault degree
Show；
Ground floor, fault-signal detection layers, it is responsible for the fault-signal that response is directly inputted by sensor, for cell tube for this layer
The detection limit of reason system fault diagnosis system includes following items: voltage, electric current, temperature, vibrations；Therefore fault-signal detection layers
Can determine the states of 4 inputs, be respectively as follows: the inconsistent degree detecting of voltage, that charging and discharging currents become big, temperature is inconsistent, outer
Portion's vibration detection；
The second layer, accident analysis layer, this layer is processed to the fault-signal of input, sentences by comparing, by way of logical operationss
The reason break corresponding to this fault-signal；When the inconsistent abnormal signal of voltage occurs, carry out point according to inconsistent degree
Level, is divided into voltage inconsistent degree one-level, two grades of the inconsistent degree of voltage, voltage inconsistent degree these three states of three-level, builds
The rule of net can not exist for three state simultaneously, need to increase the inhibitor arc in petri net, to carry out the interlocking between state；Right
It is then due to next that the state of voltage inconsistent degree one-level obtained by logical reasoning occurring in the inconsistent state of internal resistance
Individual state；When being merely only that the inconsistent state of internal resistance occurs, when other detection limit electric currents, temperature, vibrations are all normal
Wait, then can obtain the state of cell degradation with reasoning；
Third layer, failure cause layer, this layer is the conclusion output after diagnosing for fault-signal；Diagnosing the conclusion breaking down is
Polarizing voltage is inconsistent, slightly short circuit, soc are inconsistent for connector fault, cooling system fault, inside battery；Wherein lead to
The reason existing polarizing voltage inconsistent fault is the feelings being occurred due to the inconsistent state big with charging and discharging currents change of the internal resistance of cell
Condition, leads to connector fault to occur extremely being led to exterior vibration because the internal resistance of cell is inconsistent, cooling system fault
By the internal resistance of cell inconsistent inconsistent with temperature led to, the slight short trouble of inside battery is because voltage is inconsistent
Two grades of degree is inconsistent with temperature led to, soc is inconsistent be by the inconsistent degree of voltage two grades led with cell degradation
Cause；
2nd, the fault level of division battery:
Requirement according to systematic function divides to fault level；For the fault-signal of cell voltage, when cell
When the meansigma methodss difference of magnitude of voltage and battery in battery pack voltage is within 100mv, the inconsistent degree of cell voltage is first
Level；When the magnitude of voltage of battery is more than 100mv less than or equal to 500mv with the meansigma methodss difference of battery in battery pack voltage, battery
The inconsistent degree of voltage is the second level；When the magnitude of voltage of cell is exceeded with the meansigma methodss difference of battery in battery pack voltage
During 500mv, the inconsistent degree of cell voltage is the third level；For the fault-signal of battery temperature, it is the vicinity of cell
The temperature of collection is more than the temperature value at other temperature acquisition points in set of cells more than 1 DEG C；For failure of the current signal it is
The operating current difference of the set of cells that the current value that this battery cell is obtained by corresponding sampling resistor is located with this battery is big
Maximum euqalizing current 500ma when electric quantity balancing circuit start；The vibration that Rule of judgment for abnormal vibration is and stores
Amplitude compares the normal vibration amplitude range (mm) more than system condition；In the running of battery system, if monitored
Parameter exceed set threshold value, you can be judged as the signal that breaks down, using this fault-signal as fault diagnosis system
Input in；
3rd, determine origin identification m that fault diagnosis system is run0:
State equation m for petri net system0+ d*u=m, wherein m0For initial mark, it is by system under initial state
The matrix that the torr that whole places comprises is constituted, shows the original state of system；U is to enable to m0Transition sequence to m
Row, show system have passed through which transition or single step transition t during running；M be result mark, show into
The state that after crossing transition, system is reached；The incidence matrix that d nets for petri, is the intrinsic parameter of petri net；Work as fault diagnosis
When the input in of system is not zero, fault diagnostic program brings into operation；First, input in can be assigned to m0, as initial
Mark；Then, if other places all do not contain torr in system, that is, show not breaking down in other states information,
Then enter step 4；If there is the place containing torr in system, that is, show to break down in other states information, then basis
m0'=m0+ m, by original status indicator m and m0Form new input state mark m0', enter step 4；
4th, calculate the system mode mark m reaching after step transitionn:
System is by initial marking input state equation m0+ d*u=m calculates only can by step transition between it in petri net
With the status indicator reaching, enter step 5；If in the absence of one step transition mark or according to calculate state equation
Calculate the mark being still equal to input originally, i.e. explanation is unsatisfactory for changing the condition occurring, then go to step 7；
5th, transition occur reasonability to judge:
According to determined by previous step, u (due to only one step, so u is t), judges that the generation of transition t therein is no rationally；Tool
The method that body judges is as follows: for battery polarization voltage, conforming judgement is can be obtained according to the single order capacitance-resistance model of battery
The polarizing voltage formula u of batteryp(t)=up(0)e-t/τ+irp(1-e-t/τ), u in formulapT () is the big of the polarizing voltage in t
Little, τ=cprpFor battery polarization electric capacity cpWith battery polarization internal resistance rpProduct, i be operating current；By battery cell is real
The value surveyed is compared with the value of system, you can obtain the result judging computing；For battery soh state, i.e. cell degradation degree,
Conforming judgement is realized by look-up table, because the state change of battery soh is little during single work；
For the impact to its capacity for the battery temperature, adopted model is c=c25(1-a* (25-t)), * wherein c is the electricity when temperature is for t
The capacity (ah) in pond；c25It is the capacity (ah) of the battery when 25 DEG C；α is temperature correlation coefficient, and unit is ah/ DEG C, and it is one
Empirical data；T is Current Temperatures；Judgement for soc state is that the result being calculated using ampere-hour integration method to be realized, public
Formula is:
Wherein soctFor the state of the soc of t, η1For the coulomb efficiency of battery, generally take 1, η2Discharge and recharge for battery
Efficiency, is obtained by consulting battery parameter；For the total internal resistance of battery, inconsistent judgement is the side measuring fault by removal system
Determining, specific practice is exactly the history parameters checking oneself and comparing voltage and electric current in data collecting system by system to formula
Mode, judge whether data acquisition circuit breaks down, if inspection result be judged as normally, confirm battery system occur
The inconsistent fault of internal resistance, is not due to the fault of detecting system and leads to；Judgement for cooling system fault is then logical
Cross the parameter value under the running parameter (voltage, rotating speed, air pressure) comparing cooling system under current state and normal condition；Above-mentioned
Determination methods need to be determined according to t using therein which kind of, be not that each will be used under current procedures；If t quilt
Confirm to occur rationally, then corresponding place s will give the support of respective numbers according to the delivery value in set petri net
Agree, enter step 6；If the generation of transition t is unreasonable, not assignment retains original system banner, proceeds to step 7；
6th, the status indicator of system is updated, goes back to step 4；
7th, the status indicator obtaining is exported as fault diagnosis result.
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107402352A (en) * | 2016-05-03 | 2017-11-28 | 罗伯特·博世有限公司 | Diagnostic method, the operation method of cell apparatus, the operation method of equipment and equipment |
| CN108196190A (en) * | 2017-11-20 | 2018-06-22 | 上海理工大学 | A kind of battery pack on-line fault diagnosis method |
| CN108323186A (en) * | 2017-08-25 | 2018-07-24 | 深圳市云中飞网络科技有限公司 | Terminal device and its cell safety monitoring method and monitoring system |
| CN108646200A (en) * | 2018-08-23 | 2018-10-12 | 重庆雅讯电源技术有限公司 | Cell health state appraisal procedure and system |
| CN110967632A (en) * | 2019-12-17 | 2020-04-07 | 腾讯科技（深圳）有限公司 | Method, device, equipment and storage medium for determining fault battery |
| CN111983489A (en) * | 2020-08-18 | 2020-11-24 | 华中科技大学鄂州工业技术研究院 | Method for detecting discharge fault of SOFC (solid oxide Fuel cell) system with transition mode |
| CN112052233A (en) * | 2020-08-11 | 2020-12-08 | 杭州电子科技大学 | Multi-angle business process abnormity online detection method based on context awareness |
| CN112255560A (en) * | 2020-10-19 | 2021-01-22 | 奇瑞商用车（安徽）有限公司 | Battery core health degree prediction method |
| CN112632850A (en) * | 2020-12-14 | 2021-04-09 | 华中科技大学 | Method and system for detecting abnormal battery in lithium battery pack |
| WO2021169487A1 (en) * | 2020-02-24 | 2021-09-02 | 上海蔚来汽车有限公司 | Short-circuit monitoring method, system and device for cells in power battery |
| CN114167190A (en) * | 2021-12-10 | 2022-03-11 | 厦门金龙联合汽车工业有限公司 | Hybrid vehicle battery micro short circuit identification method |
| CN114167784A (en) * | 2021-12-08 | 2022-03-11 | 齐鲁工业大学 | Robot control system and method |
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2004086163A2 (en) * | 2003-03-24 | 2004-10-07 | British Telecommunications Public Limited Company | Mediator-based recovery mechanism for multi-agent system |
| CN101567814A (en) * | 2009-05-22 | 2009-10-28 | 清华大学 | Automatic network management method based on SNMP and stochastic Petri net |
| CN101726688A (en) * | 2009-09-17 | 2010-06-09 | 浙江大学 | Method for diagnosing multi-data-source information fusion-based power system fault |
| US20110202227A1 (en) * | 2010-02-17 | 2011-08-18 | Gm Global Technology Operations, Inc. | Health prognosis for complex system using fault modeling |
| CN102393922A (en) * | 2011-06-23 | 2012-03-28 | 山西省电力公司晋中供电分公司 | Fuzzy Petri inference method of intelligent alarm expert system of transformer substation |
| CN102592011A (en) * | 2011-12-30 | 2012-07-18 | 清华大学 | Layering aviation operation system HM/FM (health monitoring/fault management) modeling and evaluating method based on stochastic Petri net |
| CN102663500A (en) * | 2012-03-27 | 2012-09-12 | 许继集团有限公司 | Fuzzy Petri net transformer station fault diagnosis method based on time membership analysis |
| CN102680817A (en) * | 2012-04-28 | 2012-09-19 | 辽宁省电力有限公司朝阳供电公司 | Transformer fault diagnosis method based on fuzzy Petri net |
| CN103487723A (en) * | 2013-08-30 | 2014-01-01 | 中国南方电网有限责任公司 | Electric system fault diagnosis method and system |
-
2016
- 2016-09-20 CN CN201610835679.5A patent/CN106353690B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2004086163A2 (en) * | 2003-03-24 | 2004-10-07 | British Telecommunications Public Limited Company | Mediator-based recovery mechanism for multi-agent system |
| CN101567814A (en) * | 2009-05-22 | 2009-10-28 | 清华大学 | Automatic network management method based on SNMP and stochastic Petri net |
| CN101726688A (en) * | 2009-09-17 | 2010-06-09 | 浙江大学 | Method for diagnosing multi-data-source information fusion-based power system fault |
| US20110202227A1 (en) * | 2010-02-17 | 2011-08-18 | Gm Global Technology Operations, Inc. | Health prognosis for complex system using fault modeling |
| CN102163255A (en) * | 2010-02-17 | 2011-08-24 | 通用汽车环球科技运作有限责任公司 | Health prognosis for complex system using fault modeling |
| CN102393922A (en) * | 2011-06-23 | 2012-03-28 | 山西省电力公司晋中供电分公司 | Fuzzy Petri inference method of intelligent alarm expert system of transformer substation |
| CN102592011A (en) * | 2011-12-30 | 2012-07-18 | 清华大学 | Layering aviation operation system HM/FM (health monitoring/fault management) modeling and evaluating method based on stochastic Petri net |
| CN102663500A (en) * | 2012-03-27 | 2012-09-12 | 许继集团有限公司 | Fuzzy Petri net transformer station fault diagnosis method based on time membership analysis |
| CN102680817A (en) * | 2012-04-28 | 2012-09-19 | 辽宁省电力有限公司朝阳供电公司 | Transformer fault diagnosis method based on fuzzy Petri net |
| CN103487723A (en) * | 2013-08-30 | 2014-01-01 | 中国南方电网有限责任公司 | Electric system fault diagnosis method and system |
Non-Patent Citations (2)
| Title |
|---|
| 刘伟荣 等: "基于时间Petri网的生鲜肉冷链物流流程建模研究", 《物流技术》 * |
| 楚皓翔 等: "基于信息融合的智能一体化电站新型并网控制策略", 《电力自动化设备》 * |
Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107402352A (en) * | 2016-05-03 | 2017-11-28 | 罗伯特·博世有限公司 | Diagnostic method, the operation method of cell apparatus, the operation method of equipment and equipment |
| US10830828B2 (en) | 2017-08-25 | 2020-11-10 | Guangdong Oppo Mobile Telecommunications Corp., Ltd. | Electronic device and battery safety monitoring method and monitoring system thereof |
| CN108323186A (en) * | 2017-08-25 | 2018-07-24 | 深圳市云中飞网络科技有限公司 | Terminal device and its cell safety monitoring method and monitoring system |
| CN108196190A (en) * | 2017-11-20 | 2018-06-22 | 上海理工大学 | A kind of battery pack on-line fault diagnosis method |
| CN108196190B (en) * | 2017-11-20 | 2020-02-18 | 上海理工大学 | Online fault diagnosis method for battery pack |
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| CN112255560B (en) * | 2020-10-19 | 2024-05-10 | 奇瑞商用车（安徽）有限公司 | Battery cell health degree prediction method |
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| CN114167190B (en) * | 2021-12-10 | 2023-06-16 | 厦门金龙联合汽车工业有限公司 | Micro-short circuit identification method for hybrid vehicle battery |
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