CN115757437A - Test data construction method and system of on-chain battery swapping platform and storage medium - Google Patents
Test data construction method and system of on-chain battery swapping platform and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of system test, in particular to a test data construction method, a system and a storage medium for a chain swapping platform, wherein the method comprises the following steps: randomly generating a vehicle message; receiving vehicle messages, account and battery information; checking the vehicle message by using the vehicle state data checking model, and removing the vehicle message which cannot be checked; after the vehicle message is associated with the account of the uploading personnel and the battery information, transaction information is generated and uploaded to a block chain for storage; the inquiry block chain downloads the inquired transaction information containing the vehicle message; extracting a vehicle message in the transaction information, and sending the vehicle message to a to-be-tested on-chain battery replacement platform; the downloading module periodically generates reward transactions and transfers the pass corresponding to the downloaded times to the account of the uploading personnel. The beneficial technical effects of the invention comprise: the quality of the test data is improved, and meanwhile, the test efficiency is improved.
Description
Technical Field
The invention relates to the technical field of system test, in particular to a test data construction method, a system and a storage medium for a chain swapping platform.
Background
The battery replacement service of the new energy vehicle gradually falls to the ground, and the new energy vehicle battery replacement micro-service platform is a functional platform for performing the battery replacement service and settling accounts. Before the new energy vehicle battery replacement micro-service platform runs online, the service logic of the new energy vehicle battery replacement micro-service platform needs to be tested. However, in a service scenario in which the new energy battery swapping is combined with the block link, the automation degree of the test for the battery swapping service process is not high. Currently existing test methods are: 1. the method comprises the steps that a tester constructs information of the new energy vehicle such as SoC, kWh and TRIP at will, the information is directly pushed into a message middleware, and the message middleware forwards the information to an IOT service module for message processing, so that the new energy vehicle battery replacement micro-service platform is tested. However, this test method has two disadvantages: (1) The values of SoC, kWh and TRIP with any structure have no correlation, so that a real test scene is not easy to simulate, some test conditions which cannot occur are easy to construct, and the test accuracy and the test efficiency are reduced; (2) The method directly sends the message to the message middleware, the test flow is not incomplete due to the fact that the message does not pass through the block chain link, and the fault scene of the battery replacement service caused by the abnormal block chain is easily lost. 2. The tester passes the real vehicle test. The test method can actually simulate real data of a user. However, the method has extremely low test efficiency, and many abnormal scenes cannot be tested, so that the test cases are not completely covered.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the technical problem of lack of a test data scheme for an on-chain battery swapping platform is solved at present. The test data construction method and system for the chain swapping platform are provided, and test data closer to an actual use environment can be provided.
To solve the technical problem, the invention adopts the following technical scheme: a test data construction method of a chain swapping platform comprises the following steps:
randomly generating a vehicle message;
receiving a vehicle message, account and battery information, wherein the vehicle message comprises at least one vehicle state data;
the vehicle state data verification model is used for verifying vehicle messages, the vehicle messages which are not verified to be passed are removed, the vehicle state data verification model verifies whether at least one piece of vehicle state data are matched with each other or not, if the vehicle state data are matched with each other, the vehicle state data are verified to be passed, and if the vehicle state data are not matched with each other, the vehicle state data are verified to be not passed;
after the vehicle message is associated with the account of the uploading personnel and the battery information, transaction information is generated and uploaded to a block chain for storage;
the inquiry block chain downloads the inquired transaction information containing the vehicle message;
extracting a vehicle message in the downloaded and inquired transaction information, and sending the vehicle message to a to-be-tested on-chain battery replacement platform;
and periodically generating reward transactions, and transferring the pass corresponding to the downloaded times to the account corresponding to the uploading personnel.
Preferably, the vehicle state data includes a battery pack SoC, a battery pack remaining capacity, a mileage subtotal, or a vehicle alarm code, the mileage subtotal is a mileage traveled by the battery of the vehicle this time, the battery information includes a BMU number of the vehicle corresponding to the battery pack, the uploading module receives vehicle registration information sent by an uploading person, and the registered vehicle is assigned with a unique BMU number.
Preferably, the method for establishing the vehicle state data verification model comprises the following steps:
setting a numerical value filtering rule, wherein the numerical value filtering rule records the value taking rules of the battery pack SoC, the battery pack residual capacity, the mileage subtotal and the vehicle alarm code, and the vehicle state data which does not conform to the value taking rules are not checked and checked.
Preferably, the vehicle state data verification model further includes an exclusion rule, and the method for establishing the exclusion rule includes:
enumerating numerical range intervals of the SoC of the battery pack, the residual electric quantity of the battery pack and the mileage subtotal;
dividing the numerical range interval into at least one value interval as a value interval association interval identification code, and regarding the battery pack SoC, the battery pack residual capacity and the mileage subtotal as interval identification codes corresponding to numerical values, and regarding the vehicle alarm codes as interval identification codes;
establishing an exclusion entry, wherein the exclusion entry records an interval identification code into which other vehicle state data cannot fall when one vehicle state data falls into the interval identification code;
the exclusion entry is established a plurality of times so that the exclusion entry covers each section identification code of each vehicle state data.
Preferably, the method for establishing the vehicle state data verification model comprises the following steps:
reading at least one vehicle message, and associating a verification result of the vehicle message as sample data;
randomly generating a vehicle message, comparing the randomly generated vehicle message with the exclusion rule, marking the vehicle message as a non-passing check if the vehicle message is matched with the exclusion item, and marking the vehicle message as a passing check if the vehicle message is not matched with the exclusion item;
bringing the marked vehicle message into sample data;
establishing a neural network model, wherein an input layer neuron of the neural network model corresponds to vehicle state data contained in the vehicle message, and the output of the neural network model is the distribution probability of a verification result;
and training and testing the neural network model by using the sample data until the accuracy of the neural network model reaches a preset threshold value, wherein the neural network model is a vehicle state data verification model.
Preferably, the method for establishing the vehicle state data verification model comprises the following steps:
reading at least one vehicle message, and associating a verification result of the vehicle message as sample data;
establishing a neural network model, wherein an input layer neuron of the neural network model corresponds to vehicle state data contained in the vehicle message, and the output of the neural network model is the distribution probability of a verification result;
and training and testing the neural network model by using the sample data until the accuracy of the neural network model reaches a preset threshold value, wherein the neural network model is a vehicle state data verification model.
Preferably, a plurality of docking modules of different types of SDKs are established, and the vehicle message, the account information and the battery information are received through the docking modules.
A computer system comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the computer program when executed by the processor implementing a method of test data construction for a chain swap platform as described above.
A computer-readable storage medium, in which a computer program is stored, which computer program, when being executed by a processor, carries out a method of test data construction for a chaining mode power station as set forth above.
A test data construction system of a chain battery swapping platform is used for executing a test data construction method of the chain battery swapping platform, and comprises a generation module, an uploading module and a downloading module, wherein the generation module randomly generates a vehicle message, the uploading module receives the vehicle message uploaded by an uploading person or generated by the generation module, the vehicle message comprises at least one piece of vehicle state data, the uploading module verifies the vehicle message by using a vehicle state data verification model, eliminates the vehicle message which is not verified to pass, verifies whether at least one piece of vehicle state data is matched with one another by using the vehicle state data verification model, if so, verifies to pass, if not, the uploading module associates the vehicle message with the account and the battery information of the corresponding uploading person, generates transaction information and uploads the transaction information to a block chain for storage; the downloading module inquires a block chain, downloads the inquired transaction information containing the vehicle messages, extracts the vehicle messages in the transaction information, sends the vehicle messages to a chain battery replacement platform to be tested, periodically generates reward transactions, and transfers the corresponding certificates corresponding to the downloaded times to the account of the corresponding uploading personnel.
The beneficial technical effects of the invention comprise: 1) Test data which are not easy to generate in the real vehicle test are generated by means of the generation module, so that the test of the on-chain battery replacement platform is more comprehensive, and the stability and the reliability of the operation of the on-chain battery replacement platform are guaranteed; 2) The uploading module is used for receiving vehicle state data of a real vehicle uploaded by an uploading person, the real vehicle state can be obtained, a vehicle state data verification model is further established according to the vehicle state data of the real vehicle, unreasonable vehicle state data are removed from vehicle messages screened by the vehicle state data verification model, the quality of test data is improved, and meanwhile, the test efficiency is improved; 3) The vehicle message is stored by means of the block chain, the authenticity of the vehicle message can be guaranteed, the using times of the vehicle message are recorded through the downloading module, the uploading personnel are rewarded based on the using times, the enthusiasm of the uploading personnel can be stimulated, and more real vehicle data are uploaded to the block chain; 4) Uploading personnel of different SDK types are used in butt joint through the butt joint module, the uploading personnel can conveniently upload vehicle messages, and the range of the uploading module capable of receiving vehicle state data is enlarged.
Other features and advantages of the present invention will be disclosed in more detail in the following detailed description of the invention and the accompanying drawings.
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The invention is further described below with reference to the accompanying drawings:
fig. 1 is a flowchart illustrating a test data construction method according to an embodiment of the invention.
Fig. 2 is a flowchart illustrating a method for establishing an exclusion rule according to an embodiment of the present invention.
FIG. 3 is a diagram illustrating a computer system structure according to an embodiment of the present invention.
FIG. 4 is a block diagram of a test data structure system according to an embodiment of the present invention.
Fig. 5 is a schematic flow chart of a method for establishing a vehicle state data verification model according to a second embodiment of the present invention.
Fig. 6 is a schematic flow chart of a method for establishing a vehicle state data verification model according to a third embodiment of the present invention.
Wherein: 10. the system comprises a computer system, 11, a memory, 12, a computer program, 13, a processor, 20, a block chain, 21, an uploading module, 22, a generating module, 23 and a downloading module.
Detailed Description
The technical solutions of the embodiments of the present invention are explained and illustrated below with reference to the drawings of the embodiments of the present invention, but the following embodiments are only preferred embodiments of the present invention, and not all embodiments. Based on the embodiments in the implementation, other embodiments obtained by those skilled in the art without any creative effort belong to the protection scope of the present invention.
In the following description, the appearances of the indicating orientation or positional relationship such as the terms "inner", "outer", "upper", "lower", "left", "right", etc. are only for convenience in describing the embodiments and for simplicity in description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and are not to be construed as limiting the present invention.
The noun explains: state of charge (SoC).
Before the technical solution of the present embodiment is introduced, an application scenario and related technologies of the present embodiment are introduced.
The sales volume and the maintenance volume of new energy vehicles are rapidly increased, so that the demand for charging piles is rapidly increased. At present, new energy vehicles, especially pure electric vehicles, have some driving range anxiety to a greater or lesser extent, so that the problem of charging is solved, and the new energy vehicles are important contents of new energy vehicle services. Although the construction growth rate of the charging piles keeps a high level all the time, the number of the charging piles is still not enough to meet the charging demand of increasing more quickly. And use and fill electric pile charge and need consume a large amount of time, lead to the car owner to need long-time waiting, user experience effect is not good. Therefore, the new energy battery replacement mode can be generated at the same time. The new energy battery replacement mode is that the power battery is installed in the automobile in a mode of a module convenient to detach. When the battery is replaced, the original battery pack is detached by automatic detaching equipment, and then a new battery pack which is fully charged is immediately replaced. The battery replacement can be completed within a few minutes, and then the new energy vehicle can run again without waiting. The battery replacement mode of the new energy vehicle gradually becomes an important charging solution, and is rapidly developed. The battery replacement platform calculates the amount of money to be paid by the user according to the loss of the battery pack, such as electric quantity consumption, so that quick electric quantity supplement is provided for the user. By means of the block chain 20 technology, the battery swapping platform can realize an efficient service mode that all data sharing and business transactions are automatically completed on line, and the use experience of users is further improved.
Currently, the new energy battery replacement is generally performed by adopting an automatic battery replacement platform. The battery replacement platform not only controls the battery replacement equipment to disassemble and assemble the battery pack, but also generates corresponding order information for the battery replacement user and completes payment wage of capital. A chain swapping platform by means of a block chain 20 is currently present. The on-chain battery replacement platform has the obvious advantages that the ordinary battery replacement platform does not have, and has higher reliability and data security.
The service data and the fund data of the common battery swapping platform are stored in a background server of the battery swapping platform, so that the possibility of data loss, tampering and counterfeiting exists, the reliability is low, and the expansion of a service mode is not facilitated. The block chain 20 has natural credibility, so that credible data storage service can be provided, the reality and the safety of business data and fund data are guaranteed, and the electricity exchanging business can be smoothly carried out.
The block chain 20 is able to provide proof of trust because the block chain 20 is a chain of blocks one after another. Each block holds certain information, which are linked in a chain according to a respective generated time sequence. This chain is maintained among all servers, and as long as one server is operational throughout the system, the entire blockchain 20 is secure. These servers, referred to as nodes in the blockchain 20 system, provide storage space and computational support for the entire blockchain 20 system. If the information in the blockchain 20 is to be modified, more than half of the nodes must be certified to agree and modify the information in all the nodes, which are usually held in different hands of the subject, so it is extremely difficult to tamper with the information in the blockchain 20.
The battery replacement by the block chain 20 can fix the data directly related to the charge calculation, such as the residual electric quantity of the battery pack, the SoC of the battery pack, the mileage subtotal and the like, in the battery replacement data by the block chain 20, so that the transaction dispute can be effectively avoided. Meanwhile, the data of the voltage, the current, the temperature and the like of the battery pack can be fixed by the block chain 20. Thus forming the accumulation of data and providing a data base for the data analysis and mining in the future. According to the residual electric quantity of the battery pack, the SoC of the battery pack, the mileage subtotal and the like, the charge of the battery replacement at this time needs to be calculated by the battery replacement platform on the chain, and relevant order information is generated. The functions and service logics of the on-chain battery swapping platform are different in size or larger according to different operators. Before the on-chain battery swapping platform is operated on line, the function and the service logic of the on-chain battery swapping platform need to be tested. The reliability of the work of the battery replacement platform on the chain is guaranteed. The existing test method has the condition that the source of test data is limited or the test data is separated from the actual service, so that the test of the function and the service logic of the on-chain battery swapping platform is influenced. Therefore, it is necessary to research a generation scheme of the test data to improve the quantity and quality of the test data. The embodiment provides a method for constructing test data of a chain swapping platform, referring to fig. 1, including the following steps:
step A01) randomly generating a vehicle message;
step A02) receiving a vehicle message, account and battery information, wherein the vehicle message comprises at least one vehicle state data;
step A03) using the vehicle state data verification model to verify the vehicle message, eliminating the vehicle message which is not verified to pass, verifying whether at least one vehicle state data is matched with the vehicle state data verification model, if so, verifying to pass, and if not, verifying to fail;
step A04) associating the vehicle message with the corresponding account and battery information of the uploading personnel, generating transaction information and uploading the transaction information to a block chain 20 for storage;
step A05), inquiring a block chain 20, and downloading the inquired transaction information containing the vehicle message;
step A06), extracting a vehicle message in the transaction information, and sending the vehicle message to a to-be-tested on-chain battery replacement platform;
step A07) periodically generating reward transaction, and transferring the corresponding pass of the downloaded times to the account of the corresponding uploading personnel.
The vehicle message contains vehicle state data to be used in the test, and the vehicle state data is one or more of battery pack SoC, battery pack residual capacity, odometer or vehicle alarm code. The mileage is counted as the mileage traveled by the battery of the vehicle, the battery information includes the BMU number of the vehicle corresponding to the battery pack, the uploading module 21 receives the vehicle registration information sent by the uploading personnel, and the registered vehicle is assigned with the unique BMU number. And providing the vehicle message to the on-chain battery replacement platform, wherein the on-chain battery replacement platform performs battery replacement according to the vehicle message, generates order information, and records the amount of money to be paid by the battery replacement user.
In this embodiment, the battery SoC, the remaining battery capacity, and the vehicle alarm code in the vehicle message are used as the basis for charging. The charge required to be paid for battery replacement is calculated and obtained by the product of the residual electric quantity of the battery pack and a preset first coefficient, the product of the consumption of the SoC of the battery pack and a preset second coefficient and the charge amount corresponding to the vehicle alarm code. The loss amount of the SoC of the battery pack is calculated as follows: and using the ratio of the current residual capacity of the battery pack to the nominal capacity of the battery as the reference SoC. And subtracting the SoC of the current battery pack from the reference SoC to serve as the loss amount of the SoC of the battery pack. The loss amount of the SoC of the battery pack mainly represents the loss reduction degree of the maximum available power of the battery pack. When the battery pack is newer, the SoC will be smaller for the same remaining power. If the battery pack is used, the battery pack is over-discharged, the SoC loss of the battery pack is large, and meanwhile, the battery pack can send out a power alarm. Therefore, extra cost is increased through two items of the loss amount and the electric quantity alarm of the SoC of the battery pack, and the loss of the battery pack caused by over-discharge of the battery pack is made up. And meanwhile, the user is encouraged to reasonably use the power battery.
The SoC of the battery pack is used to indicate that the remaining capacity of the battery is in the range of 0% to 100%. In the constructed vehicle information test message, the value exists in a 16-ary format, and therefore, a certain data format conversion process is required.
The remaining battery capacity of the battery pack refers to the remaining capacity of the primary battery before battery replacement. This value has a strong correlation with the battery SoC value, and is generally proportional. The value is greater than 0 and exists in 16 system, and the 10 system numerical value which can be understood by the user needs to be converted into a corresponding message format.
The odometer records the mileage of a new battery in the vehicle. This value is greater than 0 and is usually present in 16 or 2 systems, requiring the user-understandable 10 system value to be converted into the corresponding message format.
The vehicle alarm code is represented by a WarnCode, and includes dozens of kinds of alarm information such as voltage, current, temperature, electric quantity, fire and the like. The vehicle alarm code required in the embodiment at least comprises a voltage alarm, a temperature alarm and a remaining capacity alarm.
The battery pack SoC, the battery pack residual capacity, the mileage subtotal and the vehicle alarm code in the vehicle state data have a correlation relationship. The generating module 22 randomly generates a vehicle message, and gives a random value to the battery pack SoC, the battery pack residual capacity, the mileage subtotal and the vehicle alarm code. A problem of mismatch between the vehicle state data will be caused. Therefore, the vehicle state data verification model is required to perform verification. And deleting the unmatched vehicle messages, namely deleting the vehicle messages which fail to be verified. If the SoC value of the battery pack is 80%, the residual electric quantity of the battery pack is 0.2kWh, the mileage is counted down to 900 kilometers, and the vehicle alarm code is an abnormal code. When the SoC value of the battery pack is 80%, it indicates that the remaining capacity of the battery pack is sufficient and the driving range of the vehicle using the current battery pack is small. And the residual capacity of the battery pack is 0.2kWh, and the mileometer is 900 kilometers and is not matched with the SoC of the battery pack. Such vehicle messages cannot complete the test of the on-chain battery swapping platform, and therefore need to be deleted.
On the other hand, when the SoC value of the battery pack is 0.1%, the remaining battery capacity of the battery pack is 0.02kWh, the mileage is small and the number is 650 kilometers, and the vehicle alarm code is the abnormal code. Such a vehicle message also has no practical significance, so that the SoC of the battery pack is extremely low, and an electric quantity alarm is necessarily triggered to generate an electric quantity alarm code. However, since no vehicle alarm code exists in the vehicle message, charging is carried out according to the electric quantity consumption of the battery pack and the SoC loss of the battery pack when the battery is replaced, and charging is not carried out on the condition of generating alarm information, so that the service logic is not accordant with the expectation. The on-chain battery replacement platform cannot be accurately tested. The vehicle state data verification model can remove the unmatched vehicle messages, so that test data with higher quality and closer to the actual situation are obtained, and the accuracy of the on-chain battery replacement platform test is improved.
The on-chain battery replacement platform can also record other information contained in the order information, wherein the other information comprises an order number, a primary battery code, the residual electric quantity of the primary battery, battery replacement time, a battery replacement station position, a battery code after battery replacement, the electric quantity of the battery after battery replacement and the amount of money to be paid after battery replacement. And the on-chain battery replacement platform uploads the hash value of the order information to the block chain 20 for storage to form a storage certificate of the order information. And storing the order information locally as a basis for collecting money for the user. The trueness of the order information generated by the on-chain battery replacement platform can be ensured through the deposit of the block chain 20 on the order information, and disputes can be avoided. Meanwhile, the order information is encrypted and uploaded to the block chain 20, and the order amount can be automatically settled through an intelligent contract.
In particular, settlement intelligence contracts are issued on the blockchain 20. The user submits at least one pass to a temporary storage account of the settlement intelligent contract for registration, and declares that the settlement intelligent contract is allowed to be settled. The on-chain battery replacement encrypts the order information by using a preset secret key and uploads the encrypted order information to the block chain 20. And the intelligent contract is settled, the block chain 20 is inquired, and the order information is obtained through decryption. And generating transaction information which is consistent with the amount of money to be paid for battery replacement, transferring the evidence submitted by the user in advance from the temporary storage account to the account of the on-chain battery replacement platform, and completing the automatic payment process.
In the technical scheme provided by the embodiment, the vehicle state data verification model has a key role. The embodiment specifically provides a method for establishing a vehicle state data verification model, which specifically comprises the following steps: and setting a numerical value filtering rule, recording the value taking rule of the battery pack SoC, the residual electric quantity of the battery pack, the mileage subtotal and the vehicle alarm code by the numerical value filtering rule, and verifying that the vehicle state data which does not conform to the value taking rule does not pass.
By setting the value-taking rule, the vehicle message which does not conform to the value-taking rule is deleted, and the quality of the vehicle message for testing is improved. The setting of the value-taking rule is determined according to the relationship between the vehicle state data. This embodiment provides an example of a specific value rule:
value rule 1: and if the difference value exceeds a preset threshold value, the vehicle message is represented to be not in accordance with the value-taking rule.
Value rule 2: when the SoC of the battery pack is lower than a preset threshold or the remaining battery capacity of the battery pack is lower than a preset threshold, the vehicle alarm code is an electric quantity alarm code, and if no electric quantity alarm code exists, the value rule is not met.
Value rule 3: the product of the absolute value of the difference between the battery pack SoC and 100% and a preset mileage coefficient and the difference between the battery pack SoC and the mileage subtotal are within a preset range, and if the difference exceeds a preset threshold, the vehicle message is represented to be not in accordance with a value-taking rule.
Value rule 4: and if the difference value exceeds a preset threshold value, the vehicle message is represented to be not in accordance with the value-taking rule.
Most of the non-conforming vehicle messages can be removed through the 4 value-taking rules. However, this embodiment cannot exhaust all value-taking rules, and those skilled in the art can add a new value-taking rule according to actual situations.
On the other hand, the embodiment also provides a scheme that the vehicle state data verification model further comprises an exclusion rule. The exclusion rule can be used independently or in combination with the value-taking rule as a vehicle state data verification model. When the vehicle state data verification model is used in combination with the value-taking rule and is used as a vehicle state data verification model, only the vehicle messages which accord with the value-taking rule and do not accord with the exclusion rule can be reserved and used for testing the battery replacement platform on the chain.
Referring to fig. 2, the method for establishing the exclusion rule includes:
step B01) enumerating numerical range intervals of the battery pack SoC, the residual electric quantity of the battery pack and the mileage subtotal;
step B02) dividing the numerical range interval into at least one value interval, associating interval identification codes for the value interval, and regarding the battery pack SoC, the battery pack residual capacity and the mileage subtotal as interval identification codes corresponding to numerical values, and regarding the vehicle alarm codes as the interval identification codes;
step B03) establishing an exclusion entry, wherein when the exclusion entry records an interval identification code in which other vehicle state data cannot fall when one vehicle state data falls into the interval identification code;
step B04) establishes the exclusion entry a plurality of times so that the exclusion entry covers each section identification code of each vehicle state data.
The numerical range interval of the battery pack SoC is [0,100% ], the numerical range interval of the battery pack SoC is equally divided into 5 intervals, and interval identification codes are respectively associated with each interval and are respectively A1 to A5. In this embodiment, if the nominal capacity of the battery pack is 50kWh, the range of the remaining battery capacity is [0,50], and the unit is kWh. The numerical range interval of the residual electric quantity of the battery pack is divided into 5 intervals, namely [0,10 ], [10,20 ], [20,30 ], [30,40 ] and [40,50], and interval identification codes are respectively associated with each interval and are respectively B1 to B5. The range of the mileage subtotal numerical value is [0,1000], the range of the mileage subtotal numerical value is equally divided into 10 intervals, the interval identification codes are respectively associated with each interval, and the interval identification codes are respectively C1 to C10. The vehicle alarm codes are regarded as section identification codes, and the vehicle alarm codes are 9011 to 9013.
Then, one generated exclusion entry is (A1, B5, C1, ALL), that is, when the value of the battery SoC is in the interval [0,10%), the value interval of the remaining battery capacity falls into [40,50], the subtotal value of the mileage falls into [0,100 ], and the exclusion entry is matched with the exclusion entry regardless of whether the vehicle alarm code exists. I.e. the vehicle message should be excluded. Actually, there should be an exclusion entry (A1, B2-B4, C1, ALL), that is, when the value of the battery SoC is in the interval [0,10%) and the interval identification code of the remaining battery capacity is B2-B4, ALL the exclusion entries should be excluded, and ALL the exclusion entries will form the exclusion rule.
Furthermore, a plurality of docking modules of different types of SDKs are established, and vehicle messages, account and battery information are received through the docking modules.
In another aspect, the present embodiment provides a computer system, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the computer program is executed by the processor, the computer program implements a test data constructing method for a chain swapping platform as described above.
As shown in fig. 3, the computer system includes: a processor 13, a memory 11 and a computer program 12 stored in the memory 11 and operable on the processor 13, the steps of the proposed consensus execution method in the above-described embodiments being implemented by the processor 13 executing the computer program 12.
The computer system 10 may be a general purpose computer system or a special purpose computer system. In particular implementations, computer system 10 may be a server cluster including a plurality of servers. Those skilled in the art will appreciate that fig. 3 is merely exemplary of computer system 10 and does not constitute a limitation of computer system 10 and may include more or fewer components than shown, or some of the components may be combined, or different components, such as input output devices, network access devices, etc.
The Processor 13 may be a Central Processing Unit (CPU), and the Processor 13 may also be other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or any conventional processor.
The storage 11 may be an internal storage unit of the computer system 10 in some embodiments, such as a hard disk or a memory of the computer system 10. The memory 11 may also be an external storage device of the computer system 10 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), etc. provided on the computer system 10. Further, the memory 11 may also include both an internal storage unit and an external storage device of the computer system 10. The memory 11 is used for storing an operating system, an application program, a Boot Loader (Boot Loader), data, and other programs. The memory 11 may also be used to temporarily store data that has been output or is to be output.
In another aspect, the present embodiment provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the computer program implements a test data constructing method of a chain swapping platform as described above.
On the other hand, the embodiment provides a test data construction system of a chain swapping platform, which is used for executing the test data construction method of the chain swapping platform, please refer to fig. 4, the test data construction system includes a generation module 22, an upload module 21 and a download module 23, the generation module 22 randomly generates a vehicle message, the upload module 21 receives the vehicle message uploaded by an upload person or generated by the generation module 22, the account and battery information, the vehicle message includes at least one vehicle state data, the upload module 21 verifies the vehicle message using a vehicle state data verification model, eliminates the vehicle message that fails to be verified, the vehicle state data verification model is pre-established and stored in the upload module 21, the vehicle state data verification model verifies whether at least one vehicle state data is matched with each other, if so, the vehicle state data passes the verification, if not, the vehicle state data does not pass the verification, the upload module 21 associates the vehicle message with the account and battery information of the upload person, generates transaction information and uploads the transaction information to the block chain 20 for storage; the downloading module 23 queries the block chain 20, downloads the queried transaction information containing the vehicle messages, extracts the vehicle messages in the transaction information, sends the vehicle messages to the on-chain battery replacement platform to be tested, periodically generates reward transactions, and transfers the certificates corresponding to the downloaded times to the account of an uploading person.
The generation module 22 randomly generates vehicle message data, and the uploading module 21 receives the vehicle message randomly generated by the generation module 22 and also receives the vehicle message uploaded by the uploading personnel and related account and battery information.
The uploading module 21 uses the vehicle state data verification model to verify the vehicle messages, eliminates the vehicle messages which are not verified to pass, and uploads the residual vehicle messages to the block for storage after the residual vehicle messages are associated with the account and the battery information. The generation module 22 has a fixed account and a fictitious battery information.
The downloading module 23 downloads the corresponding vehicle message from the blockchain 20, i.e. obtains the test data meeting the test requirements. Therefore, test data can be provided for the on-chain power swapping platform, and the service logic test of the on-chain power swapping platform is realized.
On the other hand, this embodiment further provides a scheme that the upload module 21 includes at least one docking module, the at least one docking module supports different SDK types, and upload personnel are connected to the corresponding docking module. The uploading staff may be manually connected to the uploading module 21, specifically, the uploading staff provides a manual interaction interface for the uploading module 21, and the vehicle messages, the account and the battery information are manually filled by the uploading staff and then submitted to the uploading module 21. On the other hand, the uploading module 21 can also be in butt joint with an automatic system owned by an uploading person to realize automatic uploading of vehicle messages, accounts and battery information. The upload personnel may have different programming languages for the automation system and the upload module 21 provides SDKs in different language types for interfacing with the automation systems of different upload personnel. The uploading module 21 provides an uploading interface for vehicle messages, accounts and battery information, and an automatic system of uploading personnel uploads data by using the uploading interface. Uploading personnel of different SDK types are used in butt joint through the butt joint module, the uploading personnel can conveniently upload vehicle messages, and the range of the uploading module 21 capable of receiving vehicle state data is enlarged.
The beneficial technical effects of the embodiment include: test data which are not easy to generate in the real vehicle test are generated by means of the generation module 22, so that the test of the on-chain battery replacement platform is more comprehensive, and the stability and the reliability of the operation of the on-chain battery replacement platform are guaranteed; the uploading module 21 is used for receiving vehicle state data of a real vehicle uploaded by an uploading person, so that the real vehicle state can be obtained, a vehicle state data verification model is established according to the vehicle state data of the real vehicle, unreasonable vehicle state data are removed from vehicle messages screened by the vehicle state data verification model, the quality of test data is improved, and meanwhile, the test efficiency is improved; the vehicle message is stored by means of the block chain 20, authenticity of the vehicle message can be guaranteed, the using times of the vehicle message are recorded through the downloading module 23, the uploading personnel are rewarded based on the using times, enthusiasm of the uploading personnel can be stimulated, and more real vehicle data are uploaded to the block chain 20.
Example two:
the embodiment provides a new improvement on a method for establishing a vehicle state data verification model on the basis of the first embodiment. Referring to fig. 5, in the present embodiment, the method for establishing the vehicle state data verification model includes:
step C01) reading at least one vehicle message, and associating the verification result of the vehicle message as sample data;
step C02) randomly generating a vehicle message, comparing the randomly generated vehicle message with the rejection rule, marking the vehicle message as not passing the verification if the vehicle message is matched with the rejection item, and marking the vehicle message as passing the verification if the vehicle message is not matched with the rejection item;
step C03), bringing the marked randomly generated vehicle message into sample data;
step C04) establishing a neural network model, wherein the input layer neurons of the neural network model correspond to the vehicle state data contained in the vehicle message, and the output of the neural network model is the distribution probability of the verification result;
and C05) training and testing the neural network model by using the sample data until the accuracy of the neural network model reaches a preset threshold value, wherein the neural network model is a vehicle state data verification model.
The embodiment provides a method for establishing a vehicle state data verification model when the method is used in combination with the exclusion rule on the basis of the first embodiment, and provides more accurate vehicle state data verification by means of a neural network model.
The neural network model is a classification model and belongs to a machine learning technology. The neural network model is trained through the sample data, and classification of data except the sample data can be achieved. The neural network model includes an input layer, at least one intermediate layer, and an output layer. The output layer can output the class distribution probability to which the input data belongs, using the softmax function as an activation function.
Generally, the data input into the neural network model is normalized data, so that the neural network model can be converged more quickly. In this embodiment, the SoC of the battery pack is normalized data. And the ratio of the residual electric quantity of the battery pack to the nominal electric quantity of the battery pack is used for representing the residual electric quantity of the battery pack, so that the normalization of the residual electric quantity of the battery pack can be completed. And expressing the ratio of the mileage subtotal to the preset maximum mileage by the mileage subtotal, namely normalizing the mileage subtotal. At least one constant value is set in the [0,1] interval to respectively represent the vehicle alarm codes, and then the normalized representation of the vehicle alarm codes can be realized.
And manually marking the verification result of the vehicle message as sample data. The cost of manual labeling is high, and the efficiency is low. At this time, the vehicle message is randomly generated in the step C02), the randomly generated vehicle message is compared with the rejection rule, the vehicle message matched with the rejection item is marked as not passing the verification, and the vehicle message not matched with the rejection item is marked as passing the verification, so that the number of sample data can be increased rapidly, and the workload of manual marking is reduced. If the value of the SoC of the battery pack is 5%, the value of the residual electric quantity of the battery pack is 45kWh, the value of the mileage subtotal falls into 65, and if no vehicle alarm code exists, the vehicle alarm code is matched with the rejection item, so that the vehicle message is marked as fail to pass the verification. The value of the SoC of the battery pack is 5%, the value of the residual electric quantity of the battery pack is 7kWh, the value of the mileage subtotal falls into 365, and if no vehicle alarm code exists, the vehicle message is not matched with any exclusive item, so that the vehicle message is marked as passing the verification. In this way a large amount of sample data can be provided.
On the other hand, the vehicle message which is randomly generated and marked by the exclusion rule is used for training the neural network model, and then the manually marked sample data is used for testing, so that a better effect can be achieved.
The embodiment provides a vehicle state data verification model based on a neural network model on the basis of the first embodiment, and a verification rule can be quickly established by the neural network model by means of sample data. There is no need to exhaust the value rules and exclusion rules. Although in this embodiment, the exhaustive exclusion rule helps to improve the accuracy of the neural network model, as long as the neural network model can pass the test of the manually labeled sample data, even if the exclusion rule is incomplete or incorrect, the quality of the final test data will not be affected. Therefore, a large amount of work of exhausting the value-taking rule and the exclusion rule is saved, and the efficiency of generating the test data is improved.
Example three:
the embodiment provides a new improvement on a method for establishing a vehicle state data verification model on the basis of the first embodiment. Referring to fig. 6, in the present embodiment, the method for establishing the vehicle state data verification model includes:
step D01) reading at least one vehicle message, and associating the verification result of the vehicle message as sample data;
step D02) establishing a neural network model, wherein the input layer neurons of the neural network model correspond to vehicle state data contained in the vehicle message, and the output of the neural network model is the distribution probability of a verification result;
and D03) training and testing the neural network model by using the sample data until the accuracy of the neural network model reaches a preset threshold value, wherein the neural network model is the vehicle state data verification model.
Compared with the second embodiment, the second embodiment specifically explains the method for establishing the vehicle state data verification model based on the neural network model when the rejection rule is not used for assisting in generating the sample data. In the embodiment, all sample data is uploaded by an uploading person, read in the step D01), and then the verification result is manually marked. Although the sample data used in the embodiment has higher acquisition cost, the sample data has extremely high accuracy, and a more accurate vehicle state data verification model can be provided.
The beneficial technical effects of the embodiment include: the check rule can be quickly established by means of sample data through the neural network model. There is no need to exhaust the value rules and exclusion rules.
While the invention has been described with reference to specific embodiments thereof, it will be understood by those skilled in the art that the invention is not limited thereto, and may be embodied in many different forms without departing from the spirit and scope of the invention as set forth in the following claims. Any modification which does not depart from the functional and structural principles of the present invention is intended to be included within the scope of the claims.
Claims (10)
1. A test data construction method of a chain swapping platform is characterized in that,
the method comprises the following steps:
randomly generating a vehicle message;
receiving the vehicle message, the account and the battery information, wherein the vehicle message comprises at least one piece of vehicle state data;
the vehicle message is verified by using a vehicle state data verification model, the vehicle message which is not verified is removed, the vehicle state data verification model verifies whether at least one vehicle state data is matched with each other, if so, the vehicle state data passes the verification, and if not, the vehicle state data is not verified;
after the vehicle message is associated with the account of the uploading personnel and the battery information, transaction information is generated and uploaded to a block chain for storage;
the inquiry block chain downloads the inquired transaction information containing the vehicle message;
extracting a vehicle message in the transaction information which is downloaded and inquired, and sending the vehicle message to a chain battery replacement platform to be tested;
and periodically generating reward transactions, and transferring the corresponding pass of the downloaded times into the account of the corresponding uploading personnel.
2. The method for constructing test data of a chain swapping platform of claim 1,
the vehicle state data comprises a battery pack SoC, battery pack residual capacity, a mileage subtotal or a vehicle alarm code, the mileage subtotal is the mileage of the battery of the vehicle, the battery information comprises BMU numbers of the vehicle corresponding to the battery pack, the uploading module receives vehicle registration information sent by an uploading person, and the registered vehicle is assigned with a unique BMU number.
3. The method for constructing test data of a chain swapping platform of claim 2,
the method for establishing the vehicle state data verification model comprises the following steps:
setting a numerical value filtering rule, wherein the numerical value filtering rule records the value taking rules of the battery pack SoC, the battery pack residual capacity, the mileage subtotal and the vehicle alarm code, and the vehicle state data which does not conform to the value taking rules are not checked and checked.
4. The method for constructing test data of a chain swapping platform of claim 3,
the vehicle state data verification model further comprises an exclusion rule, and the method for establishing the exclusion rule comprises the following steps:
enumerating numerical range intervals of the SoC of the battery pack, the residual electric quantity of the battery pack and the mileage subtotal;
dividing the numerical range interval into at least one value interval as a value interval association interval identification code, and regarding the battery pack SoC, the battery pack residual capacity and the mileage subtotal as interval identification codes corresponding to numerical values, and regarding the vehicle alarm codes as interval identification codes;
establishing an exclusion entry, wherein the exclusion entry records an interval identification code into which other vehicle state data cannot fall when one vehicle state data falls into the interval identification code;
the exclusion entry is established a plurality of times so that the exclusion entry covers each section identification code of each vehicle state data.
5. The method for constructing test data of a chain swapping platform of claim 4,
the method for establishing the vehicle state data verification model comprises the following steps:
reading at least one vehicle message, and associating a verification result of the vehicle message as sample data;
randomly generating a vehicle message, comparing the randomly generated vehicle message with the exclusion rule, if the vehicle message is matched with the exclusion item, the vehicle message is checked to be not passed, and if the vehicle message is not matched with the exclusion item, the vehicle message is checked to be passed;
bringing the marked vehicle message into sample data;
establishing a neural network model, wherein an input layer neuron of the neural network model corresponds to vehicle state data contained in the vehicle message, and the output of the neural network model is the distribution probability of a verification result;
and training and testing the neural network model by using the sample data until the accuracy of the neural network model reaches a preset threshold value, wherein the neural network model is a vehicle state data verification model.
6. The method for constructing test data of a chain swapping platform according to claim 1 or 2,
the method for establishing the vehicle state data verification model comprises the following steps:
reading at least one vehicle message, and associating a verification result of the vehicle message as sample data;
establishing a neural network model, wherein an input layer neuron of the neural network model corresponds to vehicle state data contained in the vehicle message, and the output of the neural network model is the distribution probability of a verification result;
and training and testing the neural network model by using the sample data until the accuracy of the neural network model reaches a preset threshold value, wherein the neural network model is a vehicle state data verification model.
7. The method for constructing test data of a chain swapping platform according to any one of claims 1 to 4,
establishing a plurality of docking modules of different types of SDKs, and receiving vehicle messages, account and battery information through the docking modules.
8. A computer system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program when executed by the processor implementing a method of test data construction for a chain swap platform according to any of claims 1-7.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements a method of test data construction for a chaining conversion platform as claimed in any one of claims 1 to 7.
10. A test data construction system of a chain swapping platform for performing a test data construction method of a chain swapping platform as claimed in any of claims 1 to 7,
the system comprises a generation module, an uploading module and a downloading module, wherein the generation module randomly generates vehicle messages, the uploading module receives the vehicle messages, accounts and battery information generated by uploading personnel, the vehicle messages comprise at least one piece of vehicle state data, the uploading module uses a vehicle state data verification model to verify the vehicle messages, the vehicle messages which do not pass the verification are removed, the vehicle state data verification model verifies whether at least one piece of vehicle state data are matched with one another, if the vehicle state data are matched, the vehicle messages pass the verification, if the vehicle state data are not matched, the vehicle messages do not pass the verification, and after the vehicle messages are associated with the accounts and the battery information of the uploading personnel, the uploading module generates transaction information and uploads the transaction information to a block chain for storage;
the downloading module inquires a block chain, downloads the inquired transaction information containing the vehicle messages, extracts the vehicle messages in the transaction information, sends the vehicle messages to a chain battery replacement platform to be tested, periodically generates reward transactions, and transfers the corresponding certificates corresponding to the downloaded times to the account of the corresponding uploading personnel.
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