CN112069649B - Electric automobile EPS system reliability assessment method based on MDA - Google Patents
Electric automobile EPS system reliability assessment method based on MDA Download PDFInfo
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Abstract
The invention belongs to the field of electric automobiles, in particular to a reliability evaluation method of an electric automobile EPS system based on MDA, which aims at the problem that the reliability research of the prior EPS system only researches a single part, and provides the following scheme that the reliability evaluation method comprises the following steps: step one: combining MDA and FIA, and analyzing and evaluating the reliability of the EPS system; step two: starting from an EPS system model level, comprehensively adopting AADL and EMA languages to construct a system architecture model A-EPS and a system reliability model R-EPS; step three: researching and improving a mapping rule from an MDA model to an FTA model, and step four: and D, converting the R-EPS model into an EPS fault tree model according to the rule in the step three. Compared with the prior art, the invention comprehensively considers the dependency relationship among the components of the EPS system and the safety problems of softness and hardness in the system operation, realizes the analysis of the comprehensive reliability of the EPS system, and provides a theoretical basis for engineering practice.
Description
Technical Field
The invention relates to the field of electric automobiles, in particular to an electric automobile EPS system reliability assessment method based on a Model Driven Architecture (MDA).
Background
At present, the reliability research of the EPS system of the automobile at home and abroad mainly focuses on the modeling and control technology of the core components of the EPS system and the mechanical fault diagnosis. The modeling and control technology of the EPS system core component mainly refers to mathematical equation description of the EPS system core component, and the control technology refers to an EPS system control method and a control strategy. The mechanical fault diagnosis mainly comprises the following steps: fault diagnosis and isolation of components, component optimization design and fault tolerance control technology, fault statistics and prediction. The method is only researched for single parts of the EPS system, and a more effective reliability analysis method is needed to be adopted, so that a reliability model of the EPS system is built and reliability comprehensive evaluation is carried out from the system level.
Document Yao Zhigang A model-based automobile electric power steering fault diagnosis system research [ D ]. The university of the combined fertilizer industry, 2019,4 ] A model-based structure analysis method (StructuralAnalysis, SA) is provided, wherein fault mode and fault influence of EPS system components are analyzed by adopting fault mode influence and hazard analysis (FaultModeEffectAndCriticalityAnalysis, FMECA), key components of the system are determined through qualitative analysis, an EPS system fault model is built, but the method is a system fault model built under FMECA qualitative analysis, fuzzy uncertainty exists, and influence of software and hardware on system reliability is not comprehensively considered. Therefore, starting from a system model level, the dependency relationship among all components of the EPS system and the safety problems existing in the operation of the system are comprehensively considered, and the analysis of the comprehensive reliability of the EPS system is realized.
Disclosure of Invention
Based on the problem that the reliability research of the prior EPS system only researches a single component, the invention provides an electric automobile EPS system reliability evaluation method based on MDA.
The invention provides a reliability evaluation method of an electric vehicle EPS system based on MDA, which comprises the following steps:
step one: combining MDA and FTA, and analyzing and evaluating the reliability of the EPS system;
step two: starting from an EPS system model level, comprehensively adopting AADL and EMA languages to construct a system architecture model A-EPS and a system reliability model R-EPS;
step three: researching and improving the mapping rule from the MDA model to the FTA model;
step four: according to the rule in the third step, the conversion from the R-EPS model to the EPS fault tree model is realized;
step five: predicting failure rate of the EPS system through FTA quantitative analysis, determining key parts of EPS reliability through FTA qualitative analysis, and giving reasonable suggestions to provide theoretical basis for engineering practice;
the mapping rule in the third step:
the mapping rule in the third step:
definition 1: basic fault tree fta= (TE, IE, BE, G),
TE is Top Event Top Event, which is located at the Top of the fault tree and represents the result of the joint occurrence of all events;
an IE Intermediate Event middle event, located between the top event and the bottom event; TE and IE are both represented by rectangular symbols;
BE, bottom Event, including Basic Event, indicating that the Event has not been continuously ascertained, and that the failure mode is known, usually indicated by a circular symbol;
the Gate comprises an OR Gate AND an AND Gate,
or gate: when at least one input event occurs, an output event occurs; and (3) AND gate: meaning that the output event will only occur when all input events occur,
definition 2: according to EMA base elements, it can be expressed as ema= (ES, EE, T, OD);
ES: set of all error states, es= { ES 1 ，es 2 ，…，es m }；
EE: set of all error events, ee= { EE 1 ，ee 2 ，…，ee m }；
OD: occurrence Distribution fault distribution of error events and probability of occurrence;
t: the set of all transitions between error states, transfer function T (es i ，ee j )＝es k ，
By comparing the EMA and FTA model basic elements, the corresponding relation of the elements in the two models can be obtained, and the conversion rule is as follows:
rule1 EMA (EE) -FTA (BE), the error event in the error model is converted into a bottom event in the fault tree;
rule2 EMA (EEOD) -FTA (BE), the fault distribution type and probability of the fault event in the fault model are converted into the probability of the bottom event in the fault tree;
rule3 EMA (ES) -FTA (ME) \ (TE), the error state in the error model is converted into an intermediate event or top event in the fault tree;
rule4 EMA (T) -FTA (G), the connection arc of the error model is converted into logic gates in the fault tree, wherein the conversion rules of the logic gates are two types:
(1) The composite error behavior in EMA describes a composite fault behavior, expressing the relationship between error events and state transitions,
and indicates that several error events all occur to cause state transition, or indicates that any event occurrence will cause state transition, for which purpose, an and gate in EMA and to FTA, or an or gate to FTA may be converted;
(2) Correlation between different fault events, when EE i With EE j The correlation exists between the fault events, namely the occurrence of the fault event i can cause the occurrence of the fault event j, and the fault event i can be converted into an AND gate; if EE is i With EE j There is no correlation between the two components, i.e. the occurrence of the fault event i will not cause the occurrence of the fault event j, and the fault event i can be converted into an or gate, which expresses the mutual dependency between the different components.
Preferably, in the first step: the model driving structure method, namely MDA, can be researched from a system model level, the functions and non-functional attributes of the system, namely the real-time performance and the safety, are verified and analyzed, the development period of the system is greatly shortened, the development cost is reduced, the system is an important means for ensuring the reliability of the system, the system structure analysis and design language, namely AADL, is a structural design analysis language which is provided by SAE and is coordinated with software and hardware, is an important system structure description language in the MDA method, wherein AADL comprises a core language and an expansion accessory, the AADL core language can model a complex system architecture model, an error model accessory, namely EMA, can be used for evaluating the reliability of the system, the fault information during the operation of the system is described, the AADL module fault, fault state transition and fault propagation are greatly shortened, the AADL core language and EMA sub-language can be utilized for constructing the AADL reliability model of the system, and the AADL reliability model is verified and analyzed more accurately, the AADL reliability model is converted into a Petri network finite state machine in various forms of PN and SPN, fault tree form deducing, the fault tree form is adopted, and the system is optimized by strictly optimizing the system design by means of the tool, and the system reliability is evaluated by the theoretical analysis model;
in the formal model, the FTA has the characteristics of simplicity, high efficiency and strong logic, can perform qualitative and quantitative analysis on the reliability of the system, and can track and obtain the weakest link of the system through the qualitative analysis of the FTA; and the probability of the overall failure of the system can be obtained through FTA quantitative analysis.
Preferably, the AADL reliability model in the second step includes an AADL architecture model and an AADL error model;
according to the working principle and the components of an EPS system, the EPS system in an AADL architecture model of the system consists of a control unit, a sensor, a motor, an electromagnetic clutch and a steering mechanism; the AADL error model describes information about component reliability; the method comprises fault types, fault events, fault states, fault state transitions and fault distribution information; and combining the AADL architecture model and the AADL error model to construct the R-EPS.
Preferably, in the fourth step: after an EPS system reliability model, namely R-EPS is built, the R-EPS system is instantiated, the instantiation content comprises an EPS system architecture instance and an error model instance, the error model instances are converted based on mapping rules of the three steps, a. FTA file is generated through a software OSATE plug-in Run fault tree analysis, and finally the. FTA file is analyzed through an Open FTA tool to generate an EPS fault tree model.
Preferably, in the fifth step, TE is first set as the top event of the fault tree, and x= { X 1 ,X 2 ,……,X n The method comprises the steps of carrying out quantitative analysis on the FTA of the R-EPS system according to a structural function to obtain the probability of a top event, and then carrying out qualitative analysis on the FTA of the R-EPS system, wherein the contribution of the bottom event or the minimum cut set of the fault tree to the top event can be determined, and the weak links of the system can be determined so as to improve the scheme design of the system and can be divided into probability importance, critical importance and structural importance.
The beneficial effects of the invention are as follows:
the invention provides a reliability assessment method of an electric vehicle EPS system based on a Model Driving Architecture (MDA), which is characterized in that according to fault tracking records of an autonomous brand electric vehicle in a development test period and failure characteristic parameter derivation theory of part of components, common fault events and failure probability of the EPS system are obtained through analysis, a system architecture model (A-EPS) is built by utilizing an AADL language, an EMA sub-language is used for building a system reliability model (R-EPS) on the basis, an EMA model-to-FTA model conversion rule is improved, a system FTA model is generated, and finally the following conclusion is obtained through quantitative and qualitative analysis of the FTA:
1. according to FTA quantitative analysis, the probability of an event on the top of the system is 0.274, the actual test result is 0.266, the theoretical and actual errors are 3%, and the accuracy is high.
2. Three major events leading to EPS failure in terms of the failure probability of the element itself are: the relay contact is normally closed, the torque sensor outputs a constant value, and the electromagnetic clutch fails; the least influencing faults belong to the software type, so that the key events of the system are found and reasonable suggestions are given.
3. In terms of the position of the element in the system, the events such as sampling resistor failure, feedback current signal processing failure, feedback current circuit failure and the like have the highest importance degree and are positioned at key parts of the system; and secondly, the weak links of the system software and hardware architecture are found for the failure of the corner signal processing, the failure of the torque signal processing and the like, and theoretical reference is provided for EPS system developers.
The method system can be used for checking the weak links of the system in the early stage of system development, and provides theoretical basis for system improvement and element health management.
Compared with the prior art, the invention comprehensively considers the dependency relationship among the components of the EPS system and the safety problems of softness and hardness in the system operation, realizes the analysis of the comprehensive reliability of the EPS system, and provides a theoretical basis for engineering practice.
Drawings
Fig. 1 is a flowchart of an electric vehicle EPS system reliability evaluation method based on MDA according to the present invention;
fig. 2 is a schematic diagram of an EPS system structure and a working principle of an EPS system reliability evaluation method for an electric vehicle based on MDA according to the present invention;
fig. 3 is an AADL model architecture diagram of an EPS system of the MDA-based electric vehicle EPS system reliability evaluation method according to the present invention;
fig. 4 is a schematic diagram of a partial attribute definition of an a-EPS of an electric vehicle EPS system reliability evaluation method based on MDA according to the present invention;
fig. 5 is a schematic diagram of a subsystem general error model library of an electric vehicle EPS system reliability evaluation method based on MDA according to the present invention;
fig. 6 is a schematic diagram of a reliability model of eps_control of the MDA-based electric vehicle EPS system reliability evaluation method according to the present invention;
fig. 7 is a schematic diagram of an EPS system FTA model of the MDA-based electric vehicle EPS system reliability evaluation method according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
In this embodiment, referring to fig. 1-7, a reliability evaluation method for an EPS system of an electric vehicle based on MDA includes the following steps:
step one: combining MDA and FTA, and analyzing and evaluating the reliability of the EPS system;
step two: starting from an EPS system model level, comprehensively adopting AADL and EMA languages to construct a system architecture model A-EPS and a system reliability model R-EPS;
step three: researching and improving the mapping rule from the MDA model to the FTA model;
step four: according to the rule in the third step, the conversion from the R-EPS model to the EPS fault tree model is realized;
step five: predicting failure rate of the EPS system through FTA quantitative analysis, determining key parts of EPS reliability through FTA qualitative analysis, and giving reasonable suggestions to provide theoretical basis for engineering practice;
wherein, in the first step: the model driving structure method, namely MDA, can be researched from a system model level, the functions and non-functional attributes of the system, namely the real-time performance and the safety performance, are verified and analyzed, the development period of the system is greatly shortened, the development cost is reduced, the system is an important means for guaranteeing the reliability of the system, the system structure analysis and design language, namely AADL, is a structural design analysis language cooperated with software and hardware and proposed by SAE, is an important system structure description language in the MDA method, wherein AADL comprises a core language and an expansion accessory, the AADL core language can model a complex system architecture model, an error model accessory, namely EMA, can be used for evaluating the reliability of the system, fault information during the operation of the system is described, the AADL module fault, fault state transition and fault propagation are greatly shortened, the AADL reliability model of the system can be constructed by utilizing the AADL core language and the EMA sub-language, the AADL reliability model is converted into a Petri network finite state machine and fault tree form derivation in various forms of PN and SPN for enabling the system reliability model to be verified and analyzed more accurately, and the system reliability model is optimized through strict tool to evaluate the system reliability model through the theoretical analysis and the theoretical analysis form.
In the formal model, the FTA has the characteristics of simplicity, high efficiency and strong logic, can perform qualitative and quantitative analysis on the reliability of the system, and can track and obtain the weakest link of the system through the qualitative analysis of the FTA; and the probability of the overall failure of the system can be obtained through FTA quantitative analysis.
The AADL reliability model in the second step comprises an AADL architecture model and an AADL error model;
according to the working principle and components of EPS system, in the AADL architecture model of the system, EPS system is composed of control unit (process EPS_control), sensor (torque_sensor), motor (Electric motor), electromagnetic clutch (Electromagnetic clutch), steering mechanism (Steering mechanism), wherein the process EPS_control comprises
Three threads (subtasks) of signal_processing, control_decision and Startup, wherein the thread Startup is responsible for self-checking an EPS system, and when the system is normal, a Control command is sent out to Control the thread control_decision to carry out decision Control; the thread Signal Processing is responsible for carrying out data Processing on the collected speed (speed_signal), torque (torque_signal) and rotation Angle Signal (angle_signal), and giving the collected speed, torque and rotation Angle Signal to the thread control_decision for decision Control, finally giving the target speed, torque and rotation Angle Signal to the motor, controlling the effective operation of the motor, binding the process EPS_control to the MCU, and connecting each sensor, the motor, the electromagnetic clutch and the steering mechanism through a CAN bus, wherein part of attribute definition of the A-EPS is shown in figure 4;
according to the software part parameters of the experimental sample car, the standard attribute set and the custom attribute set can be used for describing the I/O port, the task type, the bus attribute, the processor related attribute and the like in detail. The thread precision is periodic and the period is 30ms, the calculation cut-off time defaults to be equal to the period, the calculation execution time is 3ms, the processor adopts NXPSTM32L431RCT6, the thread exchange execution time is 2-3ns, and the scheduling policy adopts EDF; the bus adopts a high-speed CAN, adopts a Carrier Sense Multiple Access (CSMA) protocol, and adopts a VHDL description language in a hardware part; in addition, the priority of the thread, the scheduling policy, the processing rate of the processor, the priority range, the bandwidth of the bus, etc. can be described in detail.
The AADL error model describes information related to the reliability of the component, including information such as fault type, fault event, fault state transition, fault distribution, etc., for constructing the EPS system EMA model, the fault information of each element needs to be described, FIG. 5 shows a detailed subsystem general error model library, in which the label (1) defines the fault type, including equipment fault (fault_fault), signal processing fault
(speed_signal_failure), a short circuit fault (io_modulefaire), an output value fault (mcu_keep_high), and the like; the fault type may be provided in the EMA standard set, and may also be customized, for example, signal_processing_failure, etc. The fault event (Speed, etc.) and the fault state (fault) are defined by the mark (2), the fault transition is defined by the mark (3), the fault distribution type is defined by the mark (4), the mark can be divided into Poisson probability distribution and Fixed probability distribution, the severity level, the possibility, the hazard and the like can be defined, and the fault behavior models are defined by the marks (2), the marks (3) and the marks (4); an EPS reliability model (R-EPS) can be constructed by combining the AADL architecture model and the AADL error model, and the reliability model of EPS system process control is shown in FIG. 6.
The mapping rule in the third step:
definition 1: basic fault tree fta= (TE, IE, BE, G),
TE is Top Event Top Event, which is located at the Top of the fault tree and represents the result of the joint occurrence of all events;
an IE Intermediate Event middle event, located between the top event and the bottom event; TE and IE are both represented by rectangular symbols;
BE, bottom Event, including Basic Event, indicating that the Event has not been continuously ascertained, and that the failure mode is known, usually indicated by a circular symbol;
the Gate comprises an OR Gate AND an AND Gate;
or gate: when at least one input event occurs, an output event occurs; and (3) AND gate: meaning that an output event will only occur when all input events occur;
definition 2: according to EMA base elements, it can be expressed as ema= (ES, EE, T, OD);
ES: set of all error states, es= { ES 1 ，es 2 ，…，es m }；
EE: set of all error events, ee= { EE 1 ，ee 2 ，…，ee m }；
OD: occurrence Distribution fault distribution of error events and probability of occurrence;
t: the set of all transitions between error states, transfer function T (es i ，ee j )＝es k ；
By comparing the EMA and FTA model basic elements, the corresponding relation of the elements in the two models can be obtained, and the conversion rule is as follows:
rule1 EMA (EE) -FTA (BE), the error event in the error model is converted into a bottom event in the fault tree;
rule2 EMA (EEOD) -FTA (BE), the fault distribution type and probability of the fault event in the fault model are converted into the probability of the bottom event in the fault tree;
rule3 EMA (ES) -FTA (ME) \ (TE), the error state in the error model is converted into an intermediate event or top event in the fault tree;
rule4 EMA (T) -FTA (G), the connection arc of the error model is converted into logic gates in the fault tree, wherein the conversion rules of the logic gates are two types:
(1) The composite error behavior in EMA describes a composite fault behavior, expressing the relationship between error events and state transitions,
and indicates that several error events all occur to cause state transition, or indicates that any event occurrence will cause state transition, for which purpose, an and gate in EMA and to FTA, or an or gate to FTA may be converted;
(2) Correlation between different fault events, when EE i With EE j The correlation exists between the fault events, namely the occurrence of the fault event i can cause the occurrence of the fault event j, and the fault event i can be converted into an AND gate; if EE is i With EE j There is no correlation between the two components, i.e. the occurrence of the fault event i will not cause the occurrence of the fault event j, and the fault event i can be converted into an or gate, which expresses the mutual dependency between the different components.
In the fourth step,: after the reliability model of the EPS system, namely R-EPS is built, the R-EPS system is instantiated, the instantiation content comprises an EPS system architecture instance and an error model instance, the error model instances are converted based on mapping rules of three steps, a file FTA is generated through a software OSATE plug-in Runfault reenealy, the file FTA is finally analyzed through an OpenFTA tool to generate an EPS fault tree model, and FIG. 7 is a finally generated EPS system FTA model, wherein the names and numbers of all intermediate events are shown in Table 1.
Table 1 intermediate event names and numbers
As shown in fig. 7, the and gate is adopted between the basic events X26 and X27, which indicates that the correlation between the "open circuit of the input circuit of the motor driving chip" and the "constant low output of the motor driving chip" is high, the occurrence of the former will lead to the occurrence of the latter, and the and gate is adopted between the basic events X19 to X23, which indicates that when the "torque sensor has no signal output", "vehicle speed signal processing failure", "rotation angle signal processing failure", "torque signal processing failure", "vehicle speed sensor has no signal output", these conditions occur, the sensor will have no signal.
In the fifth step, TE is first set as a top event of the fault tree, x= { X1, X2,..xn } is a set of n independent bottom events of the fault tree, and according to a structural function, the quantitative analysis of the R-EPS system FTA is performed, where the structural function is expressed as follows:
wherein n is the number of all bottom events of the fault tree, and xi is a state indicating whether the bottom events occur or not; 0 indicates that the ith bottom event does not occur; 1 indicates that the ith bottom event occurs.
The structural functions of the basic logic gate are:
A. and (3) AND gate:
B. or gate:
probability calculation of logic gate:
A. and (3) AND gate: fs (t) =e [ phi (X) ]=f1 (t) ·f2 (t) ·fn (t) (5)
B. Or gate: fs (t) =1- [1-F1 (t) ] [1-F2 (t) ].[ 1-Fn (t) ] (6)
According to the EPS system FTA model, the EPS fault bottom events and the probabilities thereof in table 1, the probabilities of all intermediate events can be calculated layer by layer, the top event probability is finally calculated, the calculated top event probability is 0.274, the fault statistics data are compared, EPS fault early warning accounts for 26.6% of the total number of faults, the error of actual test and model analysis data is 3%, and the accuracy is high.
Then, performing qualitative analysis on the FTA of the R-EPS system, wherein the contribution of a fault tree bottom event or a minimum cut set to a top event can be determined, and the system weak links can be determined so as to improve the scheme design of the system and can be divided into probability importance, critical importance and structural importance;
1) Basic event probability importance analysis
Expressing the degree of the unreliable degree of the system caused by the unreliable degree of the ith element, wherein the occurrence probability g function of the top event is a multiple linear function, and the probability importance coefficient of the basic event can be obtained by deviating the independent variable Fi (t), and the mathematical formula is expressed as follows:
I gi probability importance
Fi (t) -component uncertainty
-probability of occurrence of an event->
Fs (t) -system unreliability,the probability importance of each basic event can be found by using the formula (7), as shown in table 2.
TABLE 2 probability significance of basic events
The basic event probability importance ranking is shown in table 2, from which it can be seen that the event X7, the influence caused by the normal close of the relay contact is the greatest, and then X5, the torque sensor outputs a constant value, and X3, the electromagnetic clutch fails itself, so that the system engineer should pay more attention to these key components in design, reduce the probability of failure as much as possible, design a fault tolerant system if necessary, thereby improving the reliability of the whole system, and the event is X19-X23, and the influence is the least, and belong to the software type faults (vehicle speed signal processing failure, corner signal processing failure, torque signal processing failure).
Critical importance analysis
The critical importance is also called critical importance, and is expressed by the ratio of the relative change rate of the occurrence probability of the basic event to the relative change rate of the occurrence probability of the overhead event from the aspect of system safety, and is an importance standard for measuring each basic event by comprehensively considering the sensitivity and the occurrence probability of the basic event, wherein the formula is as follows:
the relation between the probability importance and the critical importance is as follows:
the critical importance of each basic event can be obtained according to formulas (8) and (9), as shown in table 3:
TABLE 3 basic event Critical importance
As can be seen from Table 3, the three events with highest critical importance are respectively X7-relay contact normally closed, X5-torque sensor output constant value, and X3-electromagnetic clutch failure, which are similar to the basic event probability importance result analysis.
(3) Structural importance analysis
The structural importance represents the importance of the element in the system, has no relation with the fault probability of the element of the system, only analyzes the influence degree of each basic event on the occurrence of the overhead event structurally, and the mathematical expression is as follows:
structural importance of i-th element
n=number of components contained in the system
The importance of the EPS system structure is I (X18) =i (X17) = I (X16) = I (X15) = I (X11) = I (X10) = I (X9) = I (X8) = I (X7) = I (X6) = I (X5) = I (X4) = I (X3) = I (X2) = I (X1) > I (X27) = I (X26) = I (X25) = I (X24) = I (X14) = I (X13) > = I (X23) = I (X22) = I (X21) = I (X20) = I (X19) and the highest importance of events such as sampling resistor failure, feedback current signal processing failure, feedback current circuit failure and the like are found in the EPS structure, and the key parts are the output constant, the input circuit of the motor driving chip is opened, and the like, and finally the rotation angle signal processing failure and the torque signal processing failure are found.
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should make equivalent substitutions or modifications according to the technical scheme of the present invention and the inventive concept thereof, and should be covered by the scope of the present invention.
Claims (5)
1. The reliability evaluation method of the electric automobile EPS system based on MDA is characterized by comprising the following steps of:
step one: combining MDA and FTA, and analyzing and evaluating the reliability of the EPS system;
step two: starting from an EPS system model level, comprehensively adopting AADL and EMA languages to construct a system architecture model A-EPS and a system reliability model R-EPS;
step three: researching and improving the mapping rule from the MDA model to the FTA model;
step four: according to the rule in the third step, the conversion from the R-EPS model to the EPS fault tree model is realized;
step five: predicting failure rate of the EPS system through FTA quantitative analysis, determining key parts of EPS reliability through FTA qualitative analysis, and giving reasonable suggestions to provide theoretical basis for engineering practice;
the mapping rule in the third step:
definition 1: basic fault tree fta= (TE, IE, BE, G),
TE is Top Event Top Event, which is located at the Top of the fault tree and represents the result of the joint occurrence of all events;
an IE Intermediate Event middle event, located between the top event and the bottom event; TE and IE are both represented by rectangular symbols;
BE, bottom Event, including Basic Event, indicating that the Event has not been continuously ascertained, and that the failure mode is known, usually indicated by a circular symbol;
the Gate comprises an OR Gate AND an AND Gate,
or gate: when at least one input event occurs, an output event occurs; and (3) AND gate: meaning that the output event will only occur when all input events occur,
definition 2: according to EMA base elements, it can be expressed as ema= (ES, EE, T, OD);
ES: set of all error states, es= { ES 1 ，es 2 ，…，es m }；
EE: set of all error events, ee= { EE 1 ，ee 2 ，…，ee m }；
OD: occurrence Distribution fault distribution of error events and probability of occurrence;
t: the set of all transitions between error states, transfer function T (es i ，ee j )＝es k ，
By comparing the EMA and FTA model basic elements, the corresponding relation of the elements in the two models can be obtained, and the conversion rule is as follows:
rule1 EMA (EE) -FTA (BE), the error event in the error model is converted into a bottom event in the fault tree;
rule2 EMA (EEOD) -FTA (BE), the fault distribution type and probability of the fault event in the fault model are converted into the probability of the bottom event in the fault tree;
rule3 EMA (ES) -FTA (ME) \ (TE), the error state in the error model is converted into an intermediate event or top event in the fault tree;
rule4 EMA (T) -FTA (G), the connection arc of the error model is converted into logic gates in the fault tree, wherein the conversion rules of the logic gates are two types:
(1) The composite error behavior in EMA describes a composite fault behavior, expressing the relationship between error events and state transitions,
and indicates that several error events all occur to cause state transition, or indicates that any event occurrence will cause state transition, for which purpose, an and gate in EMA and to FTA, or an or gate to FTA may be converted;
(2) Correlation between different fault events, when EE i With EE j The correlation exists between the fault events, namely the occurrence of the fault event i can cause the occurrence of the fault event j, and the fault event i can be converted into an AND gate; if EE is i With EE j There is no correlation between the two components, i.e. the occurrence of the fault event i will not cause the occurrence of the fault event j, and the fault event i can be converted into an or gate, which expresses the mutual dependency between the different components.
2. The method for evaluating reliability of an EPS system of an electric vehicle based on MDA according to claim 1, wherein in the first step: the model driving structure method, namely MDA, can be researched from a system model level, the functions and non-functional attributes of the system, namely the real-time performance and the safety, are verified and analyzed, the development period of the system is greatly shortened, the development cost is reduced, the system is an important means for ensuring the reliability of the system, the system structure analysis and design language, namely AADL, is a structural design analysis language which is provided by SAE and is coordinated with software and hardware, is an important system structure description language in the MDA method, wherein AADL comprises a core language and an expansion accessory, the AADL core language can model a complex system architecture model, an error model accessory, namely EMA, can be used for evaluating the reliability of the system, the fault information during the operation of the system is described, the AADL module fault, fault state transition and fault propagation are greatly shortened, the AADL core language and EMA sub-language can be utilized for constructing the AADL reliability model of the system, and the AADL reliability model is verified and analyzed more accurately, the AADL reliability model is converted into a Petri network finite state machine in various forms of PN and SPN, fault tree form deducing, the fault tree form is adopted, and the system is optimized by strictly optimizing the system design by means of the tool, and the system reliability is evaluated by the theoretical analysis model;
in the formal model, the FTA has the characteristics of simplicity, high efficiency and strong logic, can perform qualitative and quantitative analysis on the reliability of the system, and can track and obtain the weakest link of the system through the qualitative analysis of the FTA; and the probability of the overall failure of the system can be obtained through FTA quantitative analysis.
3. The method for evaluating reliability of an EPS system of an electric vehicle based on MDA according to claim 1, wherein the AADL reliability model in the second step includes an AADL architecture model and an AADL error model;
according to the working principle and the components of an EPS system, the EPS system in an AADL architecture model of the system consists of a control unit, a sensor, a motor, an electromagnetic clutch and a steering mechanism; the AADL error model describes information about component reliability; the method comprises fault types, fault events, fault states, fault state transitions and fault distribution information; and combining the AADL architecture model and the AADL error model to construct the R-EPS.
4. The method for evaluating reliability of an EPS system of an electric vehicle based on MDA according to claim 1, wherein in the fourth step: after the reliability model of the EPS system, namely R-EPS is built, the R-EPS system is instantiated, the instantiation content comprises an EPS system architecture instance and an error model instance, the error model instances are converted based on the mapping rule in the step three, a file of FTA is generated through a software OSATE plug-in Run fault tree analysis, and finally the file of FTA is analyzed through an Open FTA tool to generate an EPS fault tree model.
5. The reliability evaluation method of an electric vehicle EPS system based on MDA as claimed in claim 1, wherein in the fifth step, TE is first set as a top event of a fault tree, x= { X 1 ,X 2,……, X n The method comprises the steps of carrying out quantitative analysis on the FTA of the R-EPS system according to a structural function to obtain the probability of a top event, and then carrying out qualitative analysis on the FTA of the R-EPS system, wherein the contribution of the bottom event or the minimum cut set of the fault tree to the top event can be determined, and the weak links of the system can be determined so as to improve the scheme design of the system and can be divided into probability importance, critical importance and structural importance.
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