CN116278758A - Method, system and computer readable storage medium for diagnosing power battery fault - Google Patents
Method, system and computer readable storage medium for diagnosing power battery fault Download PDFInfo
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- CN116278758A CN116278758A CN202310277749.XA CN202310277749A CN116278758A CN 116278758 A CN116278758 A CN 116278758A CN 202310277749 A CN202310277749 A CN 202310277749A CN 116278758 A CN116278758 A CN 116278758A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
- B60L3/0023—Detecting, eliminating, remedying or compensating for drive train abnormalities, e.g. failures within the drive train
- B60L3/0046—Detecting, eliminating, remedying or compensating for drive train abnormalities, e.g. failures within the drive train relating to electric energy storage systems, e.g. batteries or capacitors
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/10—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
Abstract
The invention discloses a method, a system and a computer readable storage medium for diagnosing power battery faults, wherein the method comprises the following steps: acquiring the current value of each monitoring index detected by a battery control system of the vehicle; predicting the current power battery state of the vehicle according to the correlation between the current value and the historical value of the monitoring index; and determining a fault type based on the current value when the power battery state is a fault state. The method and the device can monitor whether the power battery fails in real time in the running process of the vehicle, and determine the failure type of the power battery when predicting that the power battery is likely to fail, so that a corresponding failure processing strategy can be determined as soon as possible, and the driving safety is improved.
Description
Technical Field
The present invention relates to the field of vehicle safety management technologies, and in particular, to a method and a system for diagnosing a power battery fault, and a computer readable storage medium.
Background
Currently, the battery control system on the vehicle is mostly composed of a CMU (Cell Monitor Unit, cell monitoring unit) and a BMS (Battery management System ). The single monitoring unit is responsible for collecting data such as voltage, current, temperature and the like of the power battery. The battery management system is responsible for fault diagnosis of the data transmitted by the single monitoring unit. In the related art, after a vehicle fails, data of a power battery is collected for fault diagnosis and corresponding fault types are determined. Based on the control principle of the battery control system, the battery control system can only determine the fault type after the fault occurs, and response time is needed between the occurrence of the fault and the determination of the fault type, so that hysteresis exists in fault processing, and driving safety is not facilitated.
Disclosure of Invention
The embodiment of the application aims to realize fault monitoring and fault diagnosis of a power battery and improve driving safety by providing a method, a system and a computer readable storage medium for diagnosing faults of the power battery.
The embodiment of the application provides a power battery fault diagnosis method applied to a cloud platform, which comprises the following steps:
acquiring the current value of each monitoring index detected by a battery control system of the vehicle;
predicting the current power battery state of the vehicle according to the correlation between the current value and the historical value of the monitoring index;
and determining a fault type based on the current value when the power battery state is a fault state.
Optionally, the monitoring index includes a battery cell index and a battery module index, and the step of predicting the current power battery state of the vehicle according to the correlation between the current value and the historical value of the monitoring index includes:
and when the current value of the battery cell index is not associated with the historical value of the battery cell index and the current value of the battery module index is not associated with the historical value of the battery module index, determining that the current power battery state of the vehicle is a fault state.
Optionally, when the power battery state is a fault state, the step of determining the fault type based on the current value includes:
when the power battery state is a fault state, matching the current value of the monitoring index with a preset value corresponding to the monitoring index in a preset fault database;
when the current value is matched with the preset value, taking a preset fault type corresponding to the matched preset value as the fault type of the power battery, wherein the preset fault type comprises the following steps: one of an overcharge fault type, an overheat fault type, and a short circuit fault type.
Optionally, after the step of determining the fault type based on the current value when the power battery state satisfies a fault condition, the method further includes:
and determining a fault processing strategy corresponding to the vehicle according to the fault type.
Optionally, the step of determining the fault handling policy corresponding to the vehicle according to the fault type includes:
determining a fault grade corresponding to the fault type;
acquiring a preset fault processing strategy corresponding to the fault level;
and determining the preset fault processing strategy as a fault processing strategy corresponding to the vehicle.
Optionally, the step of obtaining a preset fault handling policy corresponding to the fault level includes:
generating fault early warning information of the power battery when the fault level is a primary fault;
when the fault level is a secondary fault, the corresponding fault handling strategy at least comprises: setting a first discharge limit value, setting a first feedback current limit value and generating a work suspension instruction of a failed battery cell/module;
when the fault level is a three-level fault, the corresponding fault handling strategy at least comprises: setting a second discharge limit value, setting a second feedback current limit value, and sending monitoring indexes and power battery states needing early warning to a controller for arbitration.
Optionally, after the step of predicting the current power battery state of the vehicle according to the correlation between the current value and the historical value of the monitoring index, the method includes:
when the state of the power battery is a normal state, determining the physical examination condition of the power battery according to the health degree, the state of charge and the power state of the power battery;
and determining a corresponding control strategy according to the physical examination condition.
Optionally, the physical examination condition includes a health condition and a sub-health condition, and the step of determining the corresponding control strategy according to the physical examination condition includes:
when the physical examination condition of the power battery is the health condition, sending prompt information that the physical examination condition of the power battery is the health condition to terminal equipment;
and when the physical examination condition of the power battery is a sub-health condition, executing a control strategy at least comprising:
sending prompt information that the physical examination condition of the power battery is sub-health condition to the terminal equipment, and/or,
and determining the physical examination frequency of the power battery and a preset diagnosis optimization program of the power battery, and performing self-checking on the power battery based on the physical examination frequency and the preset diagnosis optimization program.
In addition, to achieve the above object, the present invention also provides a system for diagnosing a power battery fault, including:
the acquisition module is used for acquiring the current value of each monitoring index detected by the battery control system of the vehicle;
the prediction module is used for predicting the current power battery state of the vehicle according to the correlation between the current value and the historical value of the monitoring index;
and the determining module is used for determining the fault type based on the current value when the power battery state is a fault state.
In addition, in order to achieve the above object, the present invention also provides a computer-readable storage medium having stored thereon a diagnosis program of a power battery failure, which when executed by a processor, implements the steps of the above-described diagnosis method of a power battery failure.
According to the technical scheme of the power battery fault diagnosis method, system and computer readable storage medium, the cloud platform is adopted for fault monitoring and fault diagnosis, and the cloud platform acquires the current value of each monitoring index detected by the battery control system in the vehicle running process in real time, and compares the detected current value of the monitoring index with the historical value to determine the correlation between the current value and the historical value, so that the power battery state is predicted according to the correlation. When the power battery state is a fault state, the fault type of the current power battery may be determined in advance based on the current value. The method and the device can monitor whether the power battery fails in real time in the running process of the vehicle, and determine the failure type of the power battery when predicting that the power battery is likely to fail, so that a corresponding failure processing strategy can be determined as soon as possible, and the driving safety is improved.
Drawings
FIG. 1 is a flow chart of a first embodiment of a method for diagnosing a power battery failure according to the present invention;
FIG. 2 is a flow chart of a second embodiment of a method for diagnosing a power battery failure according to the present invention;
FIG. 3 is a flow chart of a third embodiment of a method for diagnosing a power battery failure according to the present invention;
fig. 4 is a functional block diagram of a power battery failure diagnosis system of the present invention.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to embodiments, with reference to the accompanying drawings, which are only illustrations of one embodiment, but not all of the inventions.
Detailed Description
A battery control system on a vehicle includes a cell monitoring unit and a battery management system. The single monitoring unit is responsible for collecting data such as voltage, current, temperature and the like of the power battery, and transmitting the collected data to the battery management system. The battery management system is responsible for carrying out fault diagnosis and data management on the data transmitted by the single monitoring unit, and making corresponding battery protection strategies for different faults. After the vehicle breaks down, data of the power battery are collected for fault diagnosis and corresponding fault types are determined. Because the fault type is determined after the fault occurs, and response time is needed between the occurrence of the fault and the determination of the fault type, hysteresis exists in the processing of the subsequent fault, and driving safety is not facilitated.
Therefore, the application provides a power battery fault diagnosis method, fault monitoring and fault diagnosis are carried out by adopting a cloud platform, and as the cloud platform can acquire the current value of each monitoring index detected by a battery control system in the vehicle running process in real time, the detected current value of the monitoring index is compared with a historical value uploaded to the cloud platform in a historical manner to determine the correlation between the current value and the historical value, and then the power battery state is predicted according to the correlation. When the power battery state is a fault state, the fault type of the current power battery may be determined in advance based on the current value. The method and the device can monitor whether the power battery fails in real time in the running process of the vehicle, and determine the possible failure type of the power battery in advance when predicting the possible failure of the power battery, so as to determine the corresponding failure processing strategy as soon as possible and improve the driving safety.
In order that the above-described aspects may be better understood, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
First embodiment.
As shown in fig. 1, in the first embodiment of the present application, the method for diagnosing a power battery fault of the present application may be applied to a cloud platform, and may also be applied to an edge node, a vehicle, or the like. The power battery fault diagnosis method comprises the following steps:
step S110, a current value of each monitoring index detected by a battery control system of the vehicle is acquired.
In this embodiment, the battery control system includes a cell monitoring unit and a battery management system. The single monitoring unit is responsible for collecting data such as voltage, current, temperature and the like of the power battery, and transmitting the collected data to the battery management system. The battery management system is responsible for carrying out fault diagnosis and data management on the data transmitted by the single monitoring unit, and making corresponding battery protection strategies for different faults.
Alternatively, the current values of the respective monitoring indicators may be obtained in real time by a battery control system of the vehicle. Or, the battery control system can also send the obtained current values of the monitoring indexes to the cloud database for storage, and when the data are needed to be used, the cloud platform directly obtains the current values of the monitoring indexes from the cloud database for fault diagnosis. Or the battery control system can also send the obtained current value of each monitoring index to the edge node or the vehicle machine, and fault diagnosis is directly carried out on the edge node or the vehicle machine, so that network connection limitation is avoided, response speed is improved, and data transmission cost is reduced.
Optionally, the monitoring metrics include, but are not limited to: cell index and battery module index. Current values of the cell index include, but are not limited to: voltage, current, temperature, internal resistance, health, open/short circuit parameters, etc. Current values of battery module indicators include, but are not limited to: voltage, current, temperature, internal resistance, health, open/short circuit parameters, etc.
Step S120, predicting the current power battery state of the vehicle according to the correlation between the current value and the historical value of the monitoring index.
In the present embodiment, the power battery state includes a normal state and a failure state. And predicting that the current power battery state of the vehicle is a fault state when the current value of the battery cell index is not associated with the historical value of the battery cell index and the current value of the battery module index is not associated with the historical value of the battery module index. Wherein, determining whether the current value is associated with the historical value may be: when the current value is not matched with the historical value, the current value is not associated with the historical value, or when the current value is not in the range set by the historical value, the current value is not associated with the historical value.
Optionally, when the correlation between the current value of the battery cell indicator and the historical value of the battery cell indicator is lower than a preset threshold, and the correlation between the current value of the battery module indicator and the historical value of the battery module indicator is lower than the preset threshold, predicting that the current power battery state of the vehicle is a fault state. And predicting that the current power battery state of the vehicle is a fault state when the correlation between the current value of the battery cell index and the historical value of the battery cell index is higher than a preset threshold value and the correlation between the current value of the battery module index and the historical value of the battery module index is higher than the preset threshold value.
Optionally, the current power battery state of the vehicle can be predicted according to the comparison relation between the current value of the monitoring index and the preset value of the monitoring index. Specifically, when all the monitoring indexes are determined to meet the conditions according to the current value of the monitoring index and the preset value of the monitoring index, determining that the current power battery state of the vehicle is in a normal state, and if not, when one of the monitoring indexes is determined to not meet the conditions according to the current value of the monitoring index and the preset value of the monitoring index, predicting that the current power battery state of the vehicle is in a fault state.
For example, taking the cell index as an example, when the voltage, current, temperature, internal resistance, health and open/short of the circuit of the cell meet the conditions, the current power battery state of the vehicle is predicted to be a normal state. And when one of the voltage, the current, the temperature, the internal resistance, the health degree and the open circuit/short circuit of the battery core does not meet the conditions, predicting that the current power battery state of the vehicle is a fault state. And when the temperature of the monitoring index is larger than the preset temperature and other monitoring indexes do not meet the conditions, determining that the current power battery state of the vehicle is a fault state.
And step S130, when the power battery state is a fault state, determining a fault type based on the current value.
In this embodiment, when the power battery state is a failure state, it indicates that risk prediction is required. And determining the fault type based on the current value when the risk pre-judgment is required. The fault type may be one of an overcharge fault type, an overheat fault type, and a short circuit fault type, among others.
Optionally, when the state of the power battery is a fault state, matching the current value of the monitoring index with a preset value corresponding to the monitoring index in a preset fault database; and when the current value is matched with the preset value, taking the preset fault type corresponding to the matched preset value as the fault type of the power battery. Wherein, the preset fault type includes: one of an overcharge fault type, an overheat fault type, and a short circuit fault type. The overcharge risk fault is a fault caused by charge protection failure; if overheat risk faults such as acceleration of temperature rise, pre-judging whether the faults occur due to insolation or heating system faults; the short-circuit risk fault is a fault caused by a fault of the battery cell circuit.
According to the technical scheme, the cloud platform can acquire the current value of each monitoring index detected by the battery control system in the vehicle running process in real time, and the detected current value of the monitoring index is compared with the historical value uploaded to the cloud platform in a historical manner to determine the correlation between the current value and the historical value, so that the state of the power battery is predicted according to the correlation. When the power battery state is a fault state, the fault type of the current power battery may be determined in advance based on the current value. The method and the device can monitor whether the power battery fails in real time in the running process of the vehicle, and determine the possible failure type of the power battery in advance when predicting the possible failure of the power battery, so as to determine the corresponding failure processing strategy as soon as possible and improve the driving safety.
Second embodiment.
As shown in fig. 2, in a second embodiment of the present application, the diagnosis method of the power battery failure of the present application includes the steps of:
step S110, obtaining the current value of each monitoring index detected by a battery control system of the vehicle;
step S120, predicting the current power battery state of the vehicle according to the correlation between the current value and the historical value of the monitoring index;
step S130, when the power battery state is a fault state, determining a fault type based on the current value;
and step S210, determining a fault processing strategy corresponding to the vehicle according to the fault type.
In this embodiment, the fault types include, but are not limited to: an overcharge failure type, an overheat failure type, a short-circuit failure type, and the like. One or even more fault handling strategies can be preset for each fault type, so that the adaptive fault handling strategy can be quickly found under each fault type, and the fault handling efficiency is improved.
In an embodiment, in order to improve the fault handling efficiency and match to an accurate fault handling policy, a fault level corresponding to a current fault type may be determined, a preset fault handling policy corresponding to the fault level is obtained, and the preset fault handling policy is determined as a fault handling policy corresponding to a vehicle. Wherein, a corresponding fault level may be set in advance for each fault type, and a corresponding fault handling policy may be set for each fault level.
Optionally, determining the fault level corresponding to the current fault type may be: comparing the current fault type with all preset fault types in a preset fault state, determining a preset fault grade corresponding to the fault type from all the preset fault types, and determining the preset fault grade as the fault grade corresponding to the current fault type. Thereby accurately positioning the fault grade corresponding to the current fault type.
Alternatively, the number of levels of the fault level may be divided according to actual conditions, for example, a primary fault, a secondary fault, and a tertiary fault. The priority of each fault level can be set according to the actual situation, for example, the priority of the primary fault is lower than the priority of the secondary fault, and the priority of the secondary fault is lower than the priority of the tertiary fault.
Optionally, the cloud platform may upload fault types, fault states, and corresponding fault handling policies shared by various power cell vendors/users. The preset fault handling policy may be determined based on fault types, fault states, and corresponding fault handling policies shared by various power cell vendors/users provided on the cloud platform.
Specifically, the obtaining the preset fault handling policy corresponding to the fault level may be: when the fault level is a first-level fault, generating fault early warning information of the power battery, wherein the normal discharge of the battery is not influenced by only performing fault early warning under the first-level fault;
when the fault level is a secondary fault, the corresponding fault handling strategy at least comprises: setting a first discharge limit and a first feedback current limit and generating a work suspension instruction of a failed cell/module. The first discharging limit value and the first feedback current limit value under the secondary fault can be set according to practical situations, for example, the first discharging limit value is set to 50%, and the first feedback current limit value is set to 50%, so as to ensure normal operation and cut off the work of the battery core/module in the fault. When the current discharge exceeds 50% and the current feedback current exceeds 50%, the fault of the battery core/module can be judged, and the work of the battery core/module in the fault is cut off.
When the fault level is a three-level fault, the corresponding fault handling strategy at least comprises: setting a second discharge limit value, setting a second feedback current limit value, and sending monitoring indexes and power battery states needing early warning to a controller for arbitration. The second discharging limit value is smaller than the first discharging limit value, and the second feedback current limit value is smaller than the first feedback current limit value. The second discharge limit and the second feedback current limit in the three-stage fault may be set according to practical situations, for example, the second discharge limit is set to 0% and the second feedback current limit is set to 0%. Such as which monitored parameters and conditions need to be pre-warned; such as thermal runaway countermeasures and power-off protection measures; the early warning or protection is sent to the controller at the upper layer for arbitration, and finally, the warning or protection device finally reminds a driver to estimate the mileage of the whole vehicle which can be safely and continuously driven, so that the driver can reach the nearest maintenance point to avoid the situation of anchoring the roadside, and if the user is required to be suggested or forced to replace the battery to ensure the safety and the improvement performance.
Alternatively, after determining the fault handling policy, the fault handling policy may be sent to the vehicle controller, such that the vehicle controller executes the fault handling policy after receiving the fault handling policy.
According to the technical scheme, the cloud platform can acquire the current value of each monitoring index detected by the battery control system in the vehicle running process in real time, and the detected current value of the monitoring index is compared with the historical value uploaded to the cloud platform in a historical manner to determine the correlation between the current value and the historical value, so that the state of the power battery is predicted according to the correlation. When the power battery state is a fault state, the fault type of the current power battery can be determined in advance based on the current value, and a corresponding fault handling strategy is determined. The method and the device can monitor whether the power battery fails in real time in the running process of the vehicle, and determine the possible failure type of the power battery in advance when predicting the possible failure of the power battery, so as to determine the corresponding failure processing strategy as soon as possible and improve the driving safety.
Third embodiment.
As shown in fig. 3, in a third embodiment of the present application, the diagnosis method of the power battery fault of the present application includes the steps of:
step S110, obtaining the current value of each monitoring index detected by a battery control system of the vehicle;
step S120, predicting the current power battery state of the vehicle according to the correlation between the current value and the historical value of the monitoring index;
step S310, when the state of the power battery is a normal state, determining the physical examination state of the power battery according to the health degree, the state of charge and the power state of the power battery;
step S320, corresponding control strategies are determined according to the physical examination conditions.
In the present embodiment, the power battery state includes a normal state and a failure state, but may be other states. Physical examination conditions include health conditions and sub-health conditions. Besides countermeasures for potential risks, the cloud platform also can carry out periodic physical examination on the power battery system, and compares the collected health degree, state of charge and power state of the power battery with corresponding preset thresholds, so that whether the battery core/module of the power battery is in a healthy state or a sub-healthy state is judged. Corresponding preset thresholds can be set for the health degree, the charge state and the power state according to actual conditions. And determining that the power battery is in a sub-health state when the health degree, the state of charge and the power state of the power battery do not meet the set corresponding preset thresholds.
After the physical examination condition of the power battery is determined, control strategies corresponding to different physical examination conditions may be determined. When the physical examination condition of the power battery is the health condition, sending prompt information that the physical examination condition of the power battery is the health condition to terminal equipment; and when the physical examination condition of the power battery is the sub-health condition, sending prompt information that the physical examination condition of the power battery is the sub-health condition to a terminal device, and/or determining the physical examination frequency of the power battery and a preset diagnosis optimization program of the power battery, and performing self-examination on the power battery based on the physical examination frequency and the preset diagnosis optimization program. The preset diagnosis optimization program can be set according to actual conditions.
According to the technical scheme, the embodiment sets a physical examination period for the battery without potential faults; for sub-healthy batteries, a preset diagnosis optimization program is set in a battery management unit, the physical examination frequency is improved, and a driver is synchronously informed of the actual state of the battery and the number of the battery is counted; for healthy batteries, the driver is reported the health status, and the driver is relieved.
Embodiments of the present invention provide embodiments of a method of diagnosing a power battery fault, it being noted that although a logic sequence is shown in the flow chart, in some cases, the steps shown or described may be performed in a different order than that shown or described herein.
As shown in fig. 4, the present application provides a diagnosis system for power battery failure, the diagnosis system comprising:
an acquisition module 10 for acquiring the current values of the respective monitoring indexes detected by the battery control system of the vehicle;
a prediction module 20, configured to predict a current power battery state of the vehicle according to a correlation between the current value and a historical value of the monitoring index.
In an embodiment, the prediction module 20 is configured to determine that the current power battery state of the vehicle is a fault state when the current value of the battery cell indicator is not associated with the historical value of the battery cell indicator and the current value of the battery module indicator is not associated with the historical value of the battery module indicator.
A determining module 30 is configured to determine a fault type based on the current value when the power battery state is a fault state.
In an embodiment, the determining module 30 is configured to match, when the power battery state is a fault state, a current value of the monitoring indicator with a preset value corresponding to the monitoring indicator in a preset fault database; when the current value is matched with the preset value, taking a preset fault type corresponding to the matched preset value as the fault type of the power battery, wherein the preset fault type comprises the following steps: one of an overcharge fault type, an overheat fault type, and a short circuit fault type.
In an embodiment, a fault handling policy determining module is further connected to the determining module 30, where the fault handling policy determining module is configured to determine a fault handling policy corresponding to the vehicle according to the fault type.
In an embodiment, the fault handling policy determining module is configured to determine a fault level corresponding to the fault type; acquiring a preset fault processing strategy corresponding to the fault level; and determining the preset fault processing strategy as a fault processing strategy corresponding to the vehicle.
In an embodiment, the fault handling policy determining module is configured to generate fault early warning information of the power battery when the fault level is a primary fault; when the fault level is a secondary fault, the corresponding fault handling strategy at least comprises: setting a first discharge limit value, setting a first feedback current limit value and generating a work suspension instruction of a failed battery cell/module; when the fault level is a three-level fault, the corresponding fault handling strategy at least comprises: setting a second discharge limit value, setting a second feedback current limit value, and sending monitoring indexes and power battery states needing early warning to a controller for arbitration.
In an embodiment, after the prediction module 20, a physical examination module is further connected, where the physical examination module is configured to determine, when the state of the power battery is a normal state, a physical examination condition of the power battery according to the health degree, the state of charge, and the power state of the power battery; and determining a corresponding control strategy according to the physical examination condition.
In an embodiment, the physical examination module is further configured to send a prompt message that the physical examination condition of the power battery is a health condition to a terminal device when the physical examination condition of the power battery is a health condition; and when the physical examination condition of the power battery is a sub-health condition, executing a control strategy at least comprising: and sending prompt information that the physical examination condition of the power battery is a sub-health condition to a terminal device, and/or determining the physical examination frequency of the power battery and a preset diagnosis optimization program of the power battery, and performing self-test on the power battery based on the physical examination frequency and the preset diagnosis optimization program.
The specific implementation manner of the power battery fault diagnosis system is basically the same as that of each embodiment of the power battery fault diagnosis method, and is not repeated herein.
Based on the same inventive concept, the embodiments of the present application further provide a computer readable storage medium, where the computer readable storage medium stores a power battery fault diagnosis program, where each step of the power battery fault diagnosis method described above is implemented when the power battery fault diagnosis program is executed by a processor, and the same technical effects can be achieved, so that repetition is avoided, and no further description is given here.
Because the storage medium provided in the embodiments of the present application is a storage medium used for implementing the method in the embodiments of the present application, based on the method described in the embodiments of the present application, a person skilled in the art can understand the specific structure and the modification of the storage medium, and therefore, the description thereof is omitted herein. All storage media used in the methods of the embodiments of the present application are within the scope of protection intended in the present application.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, a television, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. A method for diagnosing a power battery fault, applied to a cloud platform, the method comprising:
acquiring the current value of each monitoring index detected by a battery control system of the vehicle;
predicting the current power battery state of the vehicle according to the correlation between the current value and the historical value of the monitoring index;
and determining a fault type based on the current value when the power battery state is a fault state.
2. The method of claim 1, wherein the monitoring indicator comprises a battery cell indicator and a battery module indicator, and wherein predicting the current power battery state of the vehicle based on a correlation between the current value and a historical value of the monitoring indicator comprises:
and when the current value of the battery cell index is not associated with the historical value of the battery cell index and the current value of the battery module index is not associated with the historical value of the battery module index, determining that the current power battery state of the vehicle is a fault state.
3. The method of claim 2, wherein the step of determining a fault type based on the current value when the power battery state is a fault state comprises:
when the power battery state is a fault state, matching the current value of the monitoring index with a preset value corresponding to the monitoring index in a preset fault database;
when the current value is matched with the preset value, taking a preset fault type corresponding to the matched preset value as the fault type of the power battery, wherein the preset fault type comprises the following steps: one of an overcharge fault type, an overheat fault type, and a short circuit fault type.
4. The method of claim 1, wherein after the step of determining a fault type based on the current value when the power battery state satisfies a fault condition, further comprising:
and determining a fault processing strategy corresponding to the vehicle according to the fault type.
5. The method of claim 4, wherein the step of determining the corresponding fault handling policy for the vehicle based on the fault type comprises:
determining a fault grade corresponding to the fault type;
acquiring a preset fault processing strategy corresponding to the fault level;
and determining the preset fault processing strategy as a fault processing strategy corresponding to the vehicle.
6. The method of claim 5, wherein the step of obtaining the preset fault handling policy corresponding to the fault level comprises:
generating fault early warning information of the power battery when the fault level is a primary fault;
when the fault level is a secondary fault, the corresponding fault handling strategy at least comprises: setting a first discharge limit value, setting a first feedback current limit value and generating a work suspension instruction of a failed battery cell/module;
when the fault level is a three-level fault, the corresponding fault handling strategy at least comprises: setting a second discharge limit value, setting a second feedback current limit value, and sending monitoring indexes and power battery states needing early warning to a controller for arbitration.
7. The method of claim 1, wherein said step of predicting a current power battery state of said vehicle based on a correlation between said current value and a historical value of said monitored indicator, comprises, after said step of:
when the state of the power battery is a normal state, determining the physical examination condition of the power battery according to the health degree, the state of charge and the power state of the power battery;
and determining a corresponding control strategy according to the physical examination condition.
8. The method of claim 7, wherein the physical examination condition comprises a health condition and a sub-health condition, the step of determining a corresponding control strategy based on the physical examination condition comprising:
when the physical examination condition of the power battery is the health condition, sending prompt information that the physical examination condition of the power battery is the health condition to terminal equipment;
and when the physical examination condition of the power battery is a sub-health condition, executing a control strategy at least comprising:
sending prompt information that the physical examination condition of the power battery is sub-health condition to the terminal equipment, and/or,
and determining the physical examination frequency of the power battery and a preset diagnosis optimization program of the power battery, and performing self-checking on the power battery based on the physical examination frequency and the preset diagnosis optimization program.
9. A diagnostic system for a power battery fault, the diagnostic system comprising:
the acquisition module is used for acquiring the current value of each monitoring index detected by the battery control system of the vehicle;
the prediction module is used for predicting the current power battery state of the vehicle according to the correlation between the current value and the historical value of the monitoring index;
and the determining module is used for determining the fault type based on the current value when the power battery state is a fault state.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a diagnosis program of a power battery failure, which when executed by a processor, implements the steps of the power battery failure diagnosis method of any one of claims 1 to 8.
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| CN202310277749.XA CN116278758A (en) | 2023-03-20 | 2023-03-20 | Method, system and computer readable storage medium for diagnosing power battery fault |
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