WO2021249269A1 - 预警方法、装置、设备及存储介质 - Google Patents

预警方法、装置、设备及存储介质 Download PDF

Info

Publication number
WO2021249269A1
WO2021249269A1 PCT/CN2021/098055 CN2021098055W WO2021249269A1 WO 2021249269 A1 WO2021249269 A1 WO 2021249269A1 CN 2021098055 W CN2021098055 W CN 2021098055W WO 2021249269 A1 WO2021249269 A1 WO 2021249269A1
Authority
WO
WIPO (PCT)
Prior art keywords
battery
temperature
maximum
sampling
cell voltage
Prior art date
Application number
PCT/CN2021/098055
Other languages
English (en)
French (fr)
Inventor
张頔
刘轶鑫
齐睿
荣常如
于春洋
王书洋
Original Assignee
中国第一汽车股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 中国第一汽车股份有限公司 filed Critical 中国第一汽车股份有限公司
Priority to EP21823006.8A priority Critical patent/EP4102615A4/en
Publication of WO2021249269A1 publication Critical patent/WO2021249269A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/4207—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells for several batteries or cells simultaneously or sequentially
    • 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
    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/389—Measuring internal impedance, internal conductance or related variables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/05—Accumulators with non-aqueous electrolyte
    • H01M10/052—Li-accumulators
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • H01M10/482—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte for several batteries or cells simultaneously or sequentially
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • H01M10/486—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte for measuring temperature
    • 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
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/54—Drive Train control parameters related to batteries
    • B60L2240/545—Temperature
    • 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
    • B60L2240/00—Control parameters of input or output; Target parameters
    • B60L2240/40—Drive Train control parameters
    • B60L2240/54—Drive Train control parameters related to batteries
    • B60L2240/547—Voltage
    • 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
    • B60L2250/00—Driver interactions
    • B60L2250/10—Driver interactions by alarm
    • 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
    • B60L2260/00—Operating Modes
    • B60L2260/40—Control modes
    • B60L2260/50—Control modes by future state prediction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/28—Testing of electronic circuits, e.g. by signal tracer
    • G01R31/282—Testing of electronic circuits specially adapted for particular applications not provided for elsewhere
    • G01R31/2829—Testing of circuits in sensor or actuator systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R35/00—Testing or calibrating of apparatus covered by the other groups of this subclass
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
    • H01M2010/4271—Battery management systems including electronic circuits, e.g. control of current or voltage to keep battery in healthy state, cell balancing
    • 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
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries
    • 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

Definitions

  • This application relates to the field of automobile technology, such as an early warning method, device, equipment, and storage medium.
  • This application provides an early warning method, device, equipment, and storage medium, which can accurately warn of battery thermal runaway and give a warning to the user.
  • An embodiment of the present application provides an early warning method, including:
  • An embodiment of the present application also provides an early warning device, which includes:
  • Collection module set to collect battery cell voltage and battery module temperature in real time
  • the calculation module is configured to calculate the battery characteristic parameters according to the battery cell voltage and the battery module temperature
  • the early warning module is configured to perform an early warning if the battery characteristic parameters meet preset conditions.
  • An embodiment of the present application also provides a computer device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the above warning method when the program is executed.
  • An embodiment of the present application also provides a computer-readable storage medium having a computer program stored on the computer-readable storage medium, and when the program is executed by a processor, the foregoing early warning method is implemented.
  • FIG. 1A is a flowchart of an early warning method in Embodiment 1 of the present application.
  • FIG. 1B is a schematic diagram of a thermal runaway device of a pool management system in Embodiment 1 of the present application;
  • FIG. 1C is a schematic diagram of the topology structure of the battery management system in Embodiment 1 of the present application.
  • Figure 2 is a schematic structural diagram of an early warning device in the second embodiment of the present application.
  • Fig. 3 is a schematic structural diagram of a computer device in the third embodiment of the present application.
  • Figure 1A is a flow chart of an early warning method provided in Embodiment 1 of this application. This embodiment can be applied to an early warning situation. The method can be executed by the early warning device in the embodiment of this application. As shown in Figure 1A, the method specifically includes the following steps:
  • the battery cell voltage and battery module temperature are collected in real time.
  • the battery characteristic parameters are calculated according to the battery cell voltage and the battery module temperature.
  • the method further includes: determining the line condition according to the battery characteristic parameter.
  • an early warning is performed, including: if the battery characteristic parameter and the line condition meet the preset condition, an early warning is performed.
  • the battery characteristic parameters include: maximum battery module temperature, minimum battery module temperature, sampling points corresponding to the maximum and minimum battery module temperature, maximum battery cell voltage, and battery cell
  • the line conditions include: battery cell voltage sampling line open circuit failure, temperature sensor sampling line open circuit failure, temperature sensor sampling line short circuit failure, sampling board communication line failure, sampling board power supply line failure, sampling board failure At least one of the abnormalities in the communication response identification.
  • the line conditions include line normal and line faults.
  • Line faults include: battery cell voltage sampling line open fault, temperature sensor sampling line open fault, temperature sensor sampling line short circuit fault, sampling board communication line failure, sampling board power supply line At least one of faults and abnormalities in the communication response identification of the sampling board;
  • the normal conditions of the circuit include: the battery cell voltage sampling line is normal, the temperature sensor sampling line is normal, the sampling board communication line is normal, the sampling board power supply line is normal, and the sampling board communication The response identifies at least one of normal.
  • the foregoing situation in this embodiment is not limited.
  • determining the line condition according to the battery characteristic parameters includes: if the difference between the maximum value of the battery cell voltage and the minimum value of the battery cell voltage is greater than the voltage difference threshold of the open fault of the cell voltage sampling line, and the battery The difference between the sampling point position number corresponding to the maximum cell voltage and the sampling point position number corresponding to the minimum battery cell voltage is equal to 1, that is, the maximum voltage sampling point and the minimum sampling point are adjacent, then the battery is determined
  • the sampling line at the middle of the sampling point corresponding to the maximum cell voltage and the sampling point corresponding to the minimum battery cell voltage has an open circuit fault, and the maximum position number of the sampling point is the number of sampling points.
  • the voltage difference threshold of the open fault of the single voltage sampling line may be set by the system or manually, which is not limited in this embodiment.
  • determining the line condition according to the battery characteristic parameter includes: if the voltage value of the temperature sensor is greater than the voltage threshold, determining that the temperature sensor sampling line is open or short-circuited; wherein, the voltage threshold may be set by the system, It can also be set manually, which is not limited in this embodiment. Collect the voltage value of the temperature sensor. If the voltage value of the temperature sensor is greater than the voltage threshold, it is determined that the temperature sensor sampling line is open or short-circuited.
  • determining the line condition according to the battery characteristic parameters includes: if at least one of the battery cell voltage and module temperature data uploaded by the sampling board is not updated, and the communication response identifier of the sampling board is abnormal, then determining the sampling board At least one of the communication line and the power supply line is faulty.
  • an early warning is performed, including if the maximum battery module temperature is greater than the abnormal battery temperature threshold for battery thermal runaway, and the minimum battery cell voltage is less than the battery thermal runaway.
  • Battery cell voltage abnormal threshold the difference between the minimum battery cell voltage in the current sampling period and the minimum battery cell voltage in the previous sampling period is greater than the first threshold, and the sampling point and battery cell corresponding to the maximum battery module temperature If the sampling point corresponding to the minimum voltage is in the same battery module, an early warning is performed, wherein the first threshold is the ratio of the minimum rate of change of the battery cell voltage to a preset multiple of the battery cell voltage data sampling period.
  • the preset multiple can be set according to requirements, and for the current solution, the preset multiple can be set to 1-5 times.
  • an early warning is performed, including if the maximum value of the battery module temperature is greater than the abnormal maximum value of the battery temperature for thermal runaway of the battery, the sampling point corresponding to the maximum temperature value of the current detection cycle The difference between the temperature value of and the temperature value of the sampling point corresponding to the maximum temperature value of the previous sampling detection period is greater than the second threshold, and within the preset multiple of the battery module temperature data sampling period, the maximum battery module temperature and the battery If the difference between the average module temperature is greater than the difference change threshold between the maximum battery module temperature and the average battery module temperature, an early warning is performed, wherein the second threshold is the ratio of the rate of change threshold to the determination period of the rate of change.
  • the preset multiple can be set according to requirements, and the preset multiple can be set to 10-20 times for this solution.
  • the change threshold of the difference between the maximum value of the temperature and the average value may be 20°C-25°C.
  • the rate of change includes at least one of a rapid rate of change and an extremely rapid rate of change
  • the determination period of the rapid rate of change is a battery module temperature data sampling period of a first preset multiple
  • the determination period of the rapid rate of change The battery module temperature data sampling period of the second preset multiple.
  • the first preset multiple may be 20-30 times
  • the second preset multiple may be 10-20 times.
  • an early warning is performed, including if the maximum battery module temperature is greater than the abnormal battery temperature threshold for battery thermal runaway, the adjacent temperature value of the maximum temperature value of the current sampling period The difference between the adjacent temperature value and the maximum temperature value of the previous sampling period is greater than the second threshold, and the difference between the previous adjacent temperature value or the next adjacent temperature value of the maximum battery module temperature and the average battery module temperature If the value is greater than the maximum value of the battery module temperature, the difference between the adjacent temperature value and the battery module temperature average value change threshold, then an early warning is given.
  • the adjacent temperature value of the maximum temperature value may be the previous adjacent temperature value of the maximum temperature value, or may be the adjacent temperature value after the maximum temperature value, and may also include the previous phase of the maximum temperature value.
  • the adjacent temperature value also includes the next adjacent temperature value of the maximum temperature value, which is not limited in this embodiment.
  • the adjacent temperature value of the maximum temperature value is the next adjacent temperature value after the maximum temperature value.
  • the sampling point corresponding to the adjacent temperature of the maximum temperature value is the sampling point corresponding to the previous adjacent temperature value of the maximum temperature point.
  • the change threshold of the difference between the adjacent temperature point of the maximum temperature point and the average value may be 10°C-25°C.
  • an early warning is performed, including: if the maximum value of the battery module temperature is greater than the abnormal maximum value of the battery temperature due to battery thermal runaway, the battery cell voltage If the sampling line is open fault, the maximum temperature sampling point of the battery module and the open fault point of the battery cell voltage sampling line are in the same module, and the temperature sensor is in a normal working state, an early warning is given.
  • an early warning is performed, including: if the maximum value of the battery module temperature is greater than the abnormal maximum value of the battery temperature due to thermal runaway of the battery, the temperature sensor is in a normal state Working status, the sampling board communication response identification is abnormal, the maximum battery module temperature sampling point location and the sampling board communication response identification abnormal point location are in the same module, and the maximum battery module temperature is greater than the maximum abnormal battery temperature for battery thermal runaway The time before the sampling board communication response identifier is abnormal, an early warning will be given.
  • an early warning is given, including: sampling if the temperature value of the sampling point corresponding to the maximum temperature value of the current detection cycle corresponds to the maximum temperature value of the previous sampling detection cycle.
  • the difference between the temperature value of the point is greater than the second threshold, and the difference between the maximum value of the battery module temperature and the average value of the battery module temperature in the battery module temperature data collection period of the preset multiple is greater than the maximum value of the battery module temperature and the battery
  • the difference change threshold of the average temperature of the module the temperature sensor fails, the temperature change precedes the temperature sensor failure, the battery cell voltage sampling line is open, and the minimum battery cell voltage is less than the abnormal maximum value of the battery cell voltage for thermal runaway of the battery.
  • the difference between the minimum value of the battery cell voltage in the current sampling period and the minimum value of the battery cell voltage in the previous sampling period is greater than the first threshold, where the first threshold is the minimum change rate threshold of the battery cell voltage
  • the second threshold is the ratio of the change rate threshold to the judgment period of the change rate.
  • This embodiment is based on the daisy chain-based battery management system topology, which can use the change characteristics of the maximum value of the battery temperature and the method for locating the electrical fault of the battery management system caused by the thermal runaway of the battery, and accurately warn the thermal runaway of the battery, and The instrument provides early warning to the user, and at the same time, the fault information can be uploaded to the big data monitoring platform.
  • the technical solution of the present application can diagnose the fault location where thermal runaway occurs, which can provide reference information for subsequent vehicle maintenance and fault analysis, and also contribute to the design improvement of the battery system structure and layout.
  • Step 1 Collect battery cell voltage and battery module temperature data in real time through the battery management system sampling slave board, and the battery management system main control board will monitor the battery cell voltage, Establish an array of battery module temperature data and perform value processing: battery cell voltage data array: CellVol[n], battery module temperature data array: ModuleTemp[m], where n is the number of battery system cell voltage sampling points; m is The number of temperature sampling points of the battery module of the battery system.
  • Step 5 Calculate the rate of change of adjacent temperature values of the maximum battery module temperature in the same battery module, taking into account that when the battery is thermally out of control, due to the heating of the faulty battery cell, the adjacent temperature sampling points will also have a rapid temperature rise At the same time, it also eliminates the interference of the sensor sampling abnormality of the maximum temperature of the battery module.
  • Step 6 Identify the maximum temperature of the battery module and the characteristics of the difference between the adjacent temperature value and the average temperature of the battery module.
  • the battery module temperature is adopted The maximum value and the difference change characteristics between the adjacent temperature value and the average temperature of the battery module are identified.
  • Vrt is the abnormal maximum value of cell voltage for battery thermal runaway, and the abnormal maximum value of battery temperature for Trt battery thermal runaway;
  • V1 is the minimum change rate threshold of battery cell voltage, ranging from 1V to 4V;
  • t4 is battery cell voltage 1 to 5 times the data sampling period.
  • Condition 2 is to ensure the accuracy of the recognition of the maximum rate of change, taking into account the impact of battery energy density on the rate of temperature rise, the rapidity and extremeness of the temperature change of the battery module, and the maximum temperature change of the battery module Features perform dual-rate recognition.
  • ⁇ Tmax1 is fast
  • T1 is the threshold of rapid change rate
  • the range is 1°C ⁇ 3°C
  • t1 is the judgment period of rapid change rate
  • the range is 20-30 times of the battery module temperature data sampling period
  • ⁇ Tmax2 is the extreme speed
  • T2 It is the extreme speed change rate threshold
  • the range is 2°C ⁇ 5°C
  • t2 is the judgment period of the extreme fast change rate
  • the range is 5-10 times of the battery module temperature data sampling period.
  • T3 is the change threshold of the difference between the maximum value of the battery module temperature and the average value of the battery module, ranging from 20°C to 25°C
  • t3 is the retention time of the difference between the maximum value of the battery module temperature and the average value of the battery module , The range is 10 to 20 times of the battery module temperature data sampling period.
  • T4 is the change threshold of the difference between the temperature value adjacent to the maximum temperature and the average value, and the range is 10°C to 25°C.
  • any thermal runaway warning flag of working conditions 1 to 3 is set to 1, and the battery management system sends a battery thermal runaway warning signal. If the thermal runaway warning flag of working conditions 1 to 3 is not set to 1, it will enter the battery characteristic change and battery management system Electrical fault joint identification and battery thermal runaway diagnosis process.
  • battery thermal runaway When battery thermal runaway occurs, it may affect the cell voltage and temperature data sampling circuit of the battery management system, causing the sampled data to be abnormal, and the accuracy of the sampled data cannot be ensured; at the same time, the battery thermal runaway may also affect the data transmission and communication of the battery management system
  • the power supply circuit of the circuit and the sampling board has an impact. The electrical failure of these battery management systems will cause the data to be unable to update in time, or even block the data transmission, and there is a risk of fault misreport and omission.
  • the data sampling circuit, communication circuit, and sampling board power supply circuit of the battery management system are identified, and combined with the aforementioned change characteristics of battery cell voltage and temperature maximum point and abnormal location identification and verification methods, The location of the thermal runaway of the battery system is more accurately identified, and the accuracy of the warning for the thermal runaway of the battery is also improved.
  • identifying and verifying the change characteristics and abnormal positions of the battery cell voltage and temperature maximum point includes the following steps: Step 10: Identify the battery cell according to the voltage change and pressure difference of adjacent battery cells The voltage sampling line is open-circuit fault, and the fault location is identified.
  • V2 is the voltage difference threshold of the open fault of the single voltage sampling line.
  • Step 20 Determine the range based on the maximum battery module temperature and the minimum battery module temperature sampling value, identify the temperature sensor sampling line open circuit or short circuit fault, and identify the fault location at the same time. If the maximum battery module temperature and the minimum battery module temperature exceed the temperature sensor sampling temperature range, it is determined that the temperature sensor sampling line is open or short-circuited at the temperature sampling point outside the range.
  • Step 30 When the communication line and power supply line failure of the sampling board of the battery management system occurs, it is reflected that the battery cell voltage and module temperature data uploaded by the abnormal sampling board are no longer updated, and the communication response identification of the sampling board is abnormal. The abnormality of these data and response marks can identify the location of the fault.
  • Step 40 Combining the temperature change of the battery module, the cell voltage change and the conditions in steps 10-30 to jointly locate the thermal runaway fault.
  • Condition 3 The communication response identifier of the sampling board is abnormal
  • any thermal runaway warning flag in working conditions 4 ⁇ 5 is set to 1, the battery management system will issue a battery thermal runaway warning signal. If the thermal runaway warning flag in working conditions 4 ⁇ 5 is not set to 1, then it will re-enter the battery characteristic change to identify battery heat. Out-of-control diagnosis process.
  • the battery management system will control the high-voltage circuit to disconnect, report the meter battery thermal runaway fault, prompt the user to stay away from the vehicle immediately, and the battery management system will simultaneously upload the fault information to the big data monitoring platform.
  • the battery management system 1 includes a master control board and 6 slave control boards.
  • the slave control board is connected through the sampling line of the battery management system
  • the battery module and the battery module are connected through the copper bar between the battery modules
  • the main control board and the slave control board or the slave control board and the slave control board are connected through the battery management system communication line Connected, set the judgment values of the battery thermal runaway judgment conditions 1 to 6 for the above-mentioned battery management system topology structure:
  • Condition 3 The communication response identifier of the sampling board is abnormal
  • Trt can be 65°C, 85°C, or 100°C
  • Vrt can be 1V, 1.5V, or 2V
  • V1 can be 1V, 2V, or 4V
  • T1 can be 1°C, 2°C, or 3°C
  • T2 can be 2°C, 3°C or 5°C
  • T3 can be 20°C, 23°C or 25°C
  • T4 can be 10°C, 15°C or 20°C
  • t1 can be 2s, 2.5s or 3s
  • t2 can be 500ms, 800ms Or 1000ms
  • t3 can be 1s, 1.5s, or 2s
  • t4 can be 100ms, 300ms, or 500ms.
  • the battery thermal runaway judgment conditions 4 and 5 can also report the battery thermal runaway fault, and the technical solution disclosed in this embodiment can accurately locate the battery thermal runaway fault.
  • This embodiment takes into account the battery temperature change characteristics caused by the battery thermal runaway and the impact on the battery cells of the same battery module, which can avoid the misdiagnosis of thermal runaway caused by abnormal sampling of one of the temperature sensors.
  • the method for locating the electrical fault of the battery management system caused by the battery thermal runaway involved in the present application can avoid the misdiagnosis of the thermal runaway caused by separately judging the battery temperature change trend, and improve the accuracy of positioning the battery thermal runaway location.
  • the topology of the battery management system in this embodiment includes, but is not limited to, a distributed topology, and can also be implemented in a centralized manner.
  • This embodiment uses the characteristics of the battery management system topology based on the daisy chain to diagnose and locate the battery thermal runaway fault, without adding other gas and pressure sensors; using the adjacent temperature point of the battery module that is the same as the battery thermal runaway temperature maximum point Variation characteristics of sampling value and identification method of variation characteristics of the difference with battery temperature average value, to verify the maximum temperature caused by battery thermal runaway, improve the accuracy of temperature maximum recognition, and eliminate failures caused by abnormal sampling of a single temperature sensor False positives.
  • the method for identifying the characteristics of rapid and extremely rapid changes in the maximum value of battery thermal runaway temperature can better cover the thermal runaway conditions of high-energy density batteries.
  • battery thermal runaway Using battery thermal runaway, battery module temperature maximum change, cell voltage maximum change, and battery management system sampling faults, and communication faults for joint diagnosis and positioning, can reduce battery management system electrical faults caused by data failure to update in time, data transmission resistance The risk of false alarms and omissions caused by faults.
  • battery thermal runaway troubleshooting measures not only the current high-voltage disconnection operation and instrument warning prompts are considered, but also the fault information can be simultaneously uploaded to the big data monitoring platform, which has a positive effect on after-sales maintenance, big data analysis, and battery system design improvement. .
  • this embodiment proposes a combination of battery temperature change feature identification and battery management system electrical fault location detection caused by battery thermal runaway.
  • the battery is determined based on temperature change features and fault location. Early warning of thermal runaway.
  • This embodiment uses the characteristics of the battery management system topology based on the daisy chain to diagnose and locate the battery thermal runaway fault. It does not add other gas and pressure sensors, which has an advantage in cost; it uses the same battery module as the maximum temperature of the battery thermal runaway.
  • the characteristic identification method of the change characteristics of the sampling value of the adjacent temperature points and the difference between the average value of the battery temperature and the battery temperature.
  • Thermal runaway fault handling measures not only consider the current high-voltage disconnection operation and instrument warning prompts, but also upload fault information to the big data monitoring platform simultaneously, which has a positive effect on after-sales maintenance, big data analysis, and battery system design improvement.
  • the technical solution of this embodiment collects battery cell voltage and battery module temperature in real time; calculates battery characteristic parameters based on the battery cell voltage and battery module temperature; if the battery characteristic parameters meet preset conditions, Early warning can accurately warn of battery thermal runaway.
  • Fig. 2 is a schematic structural diagram of an early warning device provided in the second embodiment of the application. This embodiment can be applied to an early warning situation.
  • the device can be implemented in either software or hardware.
  • the device can be integrated in any equipment that provides early warning functions.
  • the early warning device is specifically Including: an acquisition module 210, a calculation module 220, and an early warning module 230.
  • the collection module is set to collect battery cell voltage and battery module temperature in real time
  • a calculation module configured to calculate battery characteristic parameters based on the battery cell voltage and the battery module temperature
  • the early warning module is configured to perform an early warning when the battery characteristic parameters meet preset conditions.
  • the above-mentioned product can execute the method provided in any embodiment of the present application, and has corresponding functional modules and beneficial effects for the execution method.
  • the technical solution of this embodiment collects battery cell voltage and battery module temperature in real time; calculates battery characteristic parameters based on the battery cell voltage and battery module temperature; if the battery characteristic parameters meet preset conditions, Early warning can accurately warn of battery thermal runaway.
  • FIG. 3 is a schematic structural diagram of a computer device in the third embodiment of this application.
  • FIG. 3 shows a block diagram of a computer device 12 suitable for implementing this embodiment.
  • the computer device 12 shown in FIG. 3 is only an example, and should not bring any limitation to the function and scope of use of the embodiments of the present application.
  • the computer device 12 is represented in the form of a general-purpose computing device.
  • the components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the system memory 28 and the processing unit 16).
  • the bus 18 represents one or more of several types of bus structures, including a memory bus or a memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any bus structure among multiple bus structures.
  • these architectures include but are not limited to industry standard architecture (ISA) bus, microchannel architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and peripheral component interconnection ( PCI) bus.
  • ISA industry standard architecture
  • MAC microchannel architecture
  • VESA Video Electronics Standards Association
  • PCI peripheral component interconnection
  • the computer device 12 includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and nonvolatile media, removable and non-removable media.
  • the system memory 28 may include a computer system readable medium in the form of a volatile memory, such as at least one of a random access memory (RAM) 30 and a cache memory 32.
  • the computer device 12 may also include other removable or non-removable, volatile or non-volatile computer system storage media.
  • the storage system 34 may be used to read and write non-removable, non-volatile magnetic media (not shown in FIG. 3, and generally referred to as a "hard drive").
  • a disk drive for reading and writing to removable non-volatile disks such as "floppy disks"
  • a removable non-volatile optical disk such as CD-ROM, DVD-ROM
  • other optical media read and write optical disc drives.
  • each drive can be connected to the bus 18 through one or more data media interfaces.
  • the memory 28 may include at least one program product, the program product having a set (for example, at least one) program modules, and these program modules are configured to perform the functions of each embodiment of the present application.
  • a program or utility 40 having a set of (at least one) program module 42 may be stored in, for example, the memory 28.
  • Such program module 42 includes but is not limited to an operating system, one or more application programs, other program modules, and program data At least one of these examples of the program module 42 may include a network environment.
  • the program module 42 usually executes one of the functions and methods in the embodiments described in this application.
  • the computer device 12 can also communicate with one or more external devices 14 (such as keyboards, pointing devices, displays 24, etc.), and can also communicate with one or more devices that enable a user to interact with the computer device 12, or communicate with
  • the computer device 12 can communicate with any device (such as a network card, modem, etc.) that can communicate with one or more other computing devices. This communication can be performed through an input/output (I/O) interface 22.
  • the display 24 does not exist as an independent entity, but is embedded in a mirror surface. When the display surface of the display 24 is not displayed, the display surface of the display 24 and the mirror surface are visually integrated.
  • the computer device 12 may also communicate with one or more networks (for example, at least one of a local area network (LAN), a wide area network (WAN), and a public network, such as the Internet) through the network adapter 20.
  • the network adapter 20 communicates with other modules of the computer device 12 through the bus 18.
  • at least one of other hardware and software modules can be used in conjunction with the computer device 12.
  • Other hardware and software modules include but are not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives or data backup storage systems, etc.
  • the processing unit 16 executes a variety of functional applications and data processing by running programs stored in the system memory 28, for example, realizes the early warning method provided by the embodiments of the present application: real-time collection of battery cell voltage and battery module temperature; The battery cell voltage and the battery module temperature are calculated to obtain battery characteristic parameters; if the battery characteristic parameters meet a preset condition, an early warning is performed.
  • the fourth embodiment of the present application provides a computer-readable storage medium with a computer program stored on the computer-readable storage medium.
  • the program is executed by a processor, the early warning method provided in all embodiments of the present application is realized: real-time collection of battery cells.
  • the body voltage and the temperature of the battery module; the battery characteristic parameters are calculated according to the battery cell voltage and the battery module temperature; if the battery characteristic parameters meet the preset conditions, an early warning is given.
  • the computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium.
  • the computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or a combination of any of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), Erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above.
  • a computer-readable storage medium may be any tangible medium that contains or stores a program, and the program may be used by an instruction execution system, apparatus, or device, or used in combination with the program.
  • the computer-readable signal medium may include a data signal propagated in baseband or as a part of a carrier wave, and the data signal carries computer-readable program code. This propagated data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • the computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium.
  • the computer-readable medium may be sent, propagated, or transmitted for use by an instruction execution system, apparatus, or device or for use with the computer-readable medium. The program used in conjunction with the medium.
  • the program code contained on the computer-readable medium can be transmitted by any suitable medium, including but not limited to wireless, wire, optical cable or RF, etc., or any suitable combination of the above.
  • the computer program code used to perform the operations of the present application can be written in one or more programming languages or a combination thereof.
  • the programming languages include object-oriented programming languages such as Java, Smalltalk or C++, as well as conventional Procedural programming language, such as "C" language or similar programming language.
  • the program code can be executed entirely on the user's computer, partly on the user's computer, executed as an independent software package, partly on the user's computer and partly executed on a remote computer, or entirely executed on the remote computer or server.
  • the remote computer can be connected to the user's computer through any kind of network or it can be connected to an external computer.
  • the network includes a local area network (LAN) or a wide area network (WAN).
  • the external computer can use an Internet service provider to Connect via the Internet).

Landscapes

  • Engineering & Computer Science (AREA)
  • General Chemical & Material Sciences (AREA)
  • Electrochemistry (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Chemical & Material Sciences (AREA)
  • Manufacturing & Machinery (AREA)
  • Power Engineering (AREA)
  • General Physics & Mathematics (AREA)
  • Physics & Mathematics (AREA)
  • Mechanical Engineering (AREA)
  • Transportation (AREA)
  • Sustainable Energy (AREA)
  • Sustainable Development (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • Secondary Cells (AREA)
  • Charge And Discharge Circuits For Batteries Or The Like (AREA)

Abstract

本发明公开了一种预警方法、装置、设备及存储介质。该方法包括：实时采集电池单体电压和电池模组温度；根据所述电池单体电压和电池模组温度计算得到电池特征参数；及若所述电池特征参数满足预设条件，则进行预警。

Description

预警方法、装置、设备及存储介质
本申请要求申请日为2020年06月08日、申请号为202010511835.9的中国专利申请的优先权，该申请的全部内容通过引用结合在本申请中。
技术领域
本申请涉及汽车技术领域，例如涉及一种预警方法、装置、设备及存储介质。
背景技术
安全问题是妨碍锂离子电池在电动汽车中大规模应用的主要障碍。随着锂离子电池能量密度的不断提高，提高锂离子电池安全性对电动汽车的发展日益迫切。热失控是电池安全研究中的一个关键问题，也是电池管理系统对电池故障预警的重点和难点。相关技术中，电池管理系统对电池热失控的预警方法通常都集中在温度变化速率的判断，或增加烟雾传感器、气体传感器等设备进行安全预防。但上述方法从温度变化维度判断容易受温度传感器采样精度和特性影响，有误报风险；而增设烟雾传感器、气体传感器的措施，虽然可从多维度保证预警的准确性，但也增加了系统潜在功能失效风险和系统成本。
发明内容
本申请提供了一种预警方法、装置、设备及存储介质，能够实现能够准确预警电池热失控，并对用户进行预警提示。
本申请一实施例提供了一种预警方法，包括：
实时采集电池单体电压和电池模组温度；
根据所述电池单体电压和电池模组温度计算得到电池特征参数；及
若所述电池特征参数满足预设条件，则进行预警。
本申请一实施例还提供了一种预警装置，该装置包括：
采集模块，设置为实时采集电池单体电压和电池模组温度；
计算模块，设置为根据所述电池单体电压和电池模组温度计算得到电池特征参数；及
预警模块，设置为若所述电池特征参数满足预设条件，则进行预警。
本申请一实施例还提供了一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其中，所述处理器执行所述程序时实现上述预警方法。
本申请一实施例还提供了一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机程序，所述程序被处理器执行时实现上述预警方法。
附图说明
图1A是本申请实施例一中的一种预警方法的流程图；
图1B是本申请实施例一中的池管理系统热失控装置示意图；
图1C是本申请实施例一中的电池管理系统拓扑结构示意图；
图2是本申请实施例二中的一种预警装置的结构示意图；
图3是本申请实施例三中的一种计算机设备的结构示意图。
具体实施方式
在以下实施例中应注意到：相似的标号和字母在下面的附图中表示类似项，因此，一旦一项在一个附图中被定义，则在随后的附图中不需要对该项进行进一步定义和解释。同时，在本申请的描述中，术语“第一”、“第二”等仅用于区分描述，而不能理解为指示或暗示相对重要性。
实施例一
图1A为本申请实施例一提供的一种预警方法的流程图，本实施例可适用于预警的情况，该方法可以由本申请实施例中的预警装置来执行，该装置可采用软件和硬件中的至少一种方式实现，如图1A所示，该方法具体包括如下步骤：
S110中，实时采集电池单体电压和电池模组温度。
S120中，根据所述电池单体电压和电池模组温度计算得到电池特征参数。
S130中，若所述电池特征参数满足预设条件，则进行预警。
在一实施例中，若所述电池特征参数满足预设条件，则进行预警之前，还包括：根据所述电池特征参数确定线路情况。
若所述电池特征参数满足预设条件，则进行预警，包括：若所述电池特征参数和所述线路情况满足预设条件，则进行预警。
在一实施例中，所述电池特征参数包括：电池模组温度最大值，电池模组温度最小值，电池模组温度最大值和最小值对应的采样点，电池单体电压最大 值，电池单体电压最小值以及电池单体电压最大值和最小值对应的采样点，电池模组温度平均值，电池模组温度最值的相邻温度对应的采样点的温度值，电池模组温度最大值变化速率，同一电池模组内电池模组温度最大值的相邻温度值的变化速率，电池模组温度最大值与电池模组温度平均值的差值，电池模组温度最大值对应的采样点的相邻采样点的温度值与电池模组温度平均值的差值以及电池单体电压最小值变化速率中的至少一种。
在一实施例中，所述线路情况包括：电池单体电压采样线开路故障、温度传感器采样线开路故障、温度传感器采样线短路故障、采样板通讯线路故障、采样板供电线路故障、采样板的通讯响应标识异常中的至少一种。
其中，所述线路情况包括线路正常和线路故障，线路故障包括：电池单体电压采样线开路故障、温度传感器采样线开路故障、温度传感器采样线短路故障、采样板通讯线路故障、采样板供电线路故障、采样板的通讯响应标识异常中的至少一种；线路正常情况包括：电池单体电压采样线路正常、温度传感器采样线路正常、采样板通讯线路正常、采样板供电线路正常以及采样板的通讯响应标识正常中的至少一种。本实施例上述情况不进行限制。
在一实施例中，根据所述电池特征参数确定线路情况包括：若电池单体电压最大值和电池单体电压最小值的差值大于单体电压采样线开线故障的压差阈值，且电池单体电压最大值对应的采样点位置编号与电池单体电压最小值对应的采样点位置编号的差值等于1，即，电压最大值采样点和最小值采样点是相邻的，则确定电池单体电压最大值对应的采样点与电池单体电压最小值对应的采样点的中间位置的采样线发生开路故障，采样点的最大位置编号为采样点的点数。其中，所述单体电压采样线开线故障的压差阈值可以为系统设定，也可以为人为设定，本实施例对此不进行限制。
在一实施例中，根据所述电池特征参数确定线路情况包括：若温度传感器的电压值大于电压阈值，则确定温度传感器采样线开路或者短路故障；其中，所述电压阈值可以为系统设定，也可以为人为设定，本实施例对此不进行限制。采集温度传感器的电压值，若温度传感器的电压值大于电压阈值，则确定温度传感器采样线开路或者短路故障。
在一实施例中，根据所述电池特征参数确定线路情况包括：若采样板上传的电池单体电压和模组温度数据中的至少一个不更新，且采样板通信响应标识异常，则确定采样板通讯线路和供电线路中的至少一个故障。
在一实施例中，若所述电池特征参数满足预设条件，则进行预警，包括若电池模组温度最大值大于电池热失控的电池温度异常阈值，电池单体电压最小值小于电池热失控的电池单体电压异常阈值，当前采样周期电池单体电压最小值和上一采样周期电池单体电压最小值的差值大于第一阈值，且电池模组温度最大值对应的采样点和电池单体电压最小值对应的采样点在同一电池模组内，则进行预警，其中，所述第一阈值为电池单体电压最小值变化速率阈值与预设倍数的电池单体电压数据采样周期的比值。
其中，所述预设倍数可以根据需求进行设定，针对当前方案，预设倍数可以设定为1-5倍。
在一实施例中，若所述电池特征参数满足预设条件，则进行预警，包括若电池模组温度最大值大于电池热失控的电池温度异常最值，当前检测周期最大温度值对应的采样点的温度值与上一采样检测周期最大温度值对应的采样点的温度值的差值大于第二阈值，且在预设倍数的电池模组温度数据采样周期内，电池模组温度最大值与电池模组温度均值的差值大于电池模组温度最大值与电池模组温度均值的差值变化阈值，则进行预警，其中，所述第二阈值为变化速率阈值与变化速率的判断周期的比值。
其中，所述预设倍数可以根据需求进行设定，针对本方案预设倍数可以设定为10-20倍。
其中，所述温度最大值与均值的差值变化阈值可以为20℃-25℃。
其中，所述变化速率包括快速变化速率和极速变化速率中的至少一个，所述快速变化速率的判断周期为第一预设倍数的电池模组温度数据采样周期，所述极速变化速率的判断周期为第二预设倍数的电池模组温度数据采样周期。其中，所述第一预设倍数可以为20-30倍，第二预设倍数可以为10-20倍。
在一实施例中，若所述电池特征参数满足预设条件，则进行预警，包括若电池模组温度最大值大于电池热失控的电池温度异常阈值，当前采样周期最大温度值的相邻温度值与上一采样周期最大温度值的相邻温度值的差值大于第二阈值，且电池模组温度最大值的前一相邻温度值或者后一相邻温度值与电池模组温度均值的差值大于电池模组温度最大值的相邻温度值与电池模组温度均值的差值变化阈值，则进行预警。
其中，所述最大温度值的相邻温度值可以为最大温度值的前一相邻温度值，也可以为最大温度值的后一相邻温度值，还可以既包括最大温度值的前一相邻 温度值，又包括最大温度值的后一相邻温度值，本实施例对此不进行限制。
在一实施例中，在电池模组温度最大值对应的采样点位置编号等于1时，最大温度值的相邻温度值为最大温度值的后一相邻温度值，在电池模组温度最大值对应的采样点位置编号等于电池模组温度采样点数时，最大温度值的相邻温度对应的采样点为最大温度值点的前一相邻温度值对应的采样点。其中，所述温度最大值点相邻温度点与均值的差值变化阈值可以为10℃-25℃。
在一实施例中，若所述电池特征参数和所述线路情况满足预设条件，则进行预警，包括：若电池模组温度最大值大于电池热失控的电池温度异常最值，电池单体电压采样线开路故障，电池模组温度最大值采样点和电池单体电压采样线开路故障点在同一模组，且温度传感器处于正常工作状态，则进行预警。
在一实施例中，若所述电池特征参数和所述线路情况满足预设条件，则进行预警，包括：若电池模组温度最大值大于电池热失控的电池温度异常最值，温度传感器处于正常工作状态，采样板通信响应标识异常，电池模组温度最大值采样点位置和采样板通信响应标识异常点位置在同一模组，且电池模组温度最大值大于电池热失控的电池温度异常最值的时间先于采样板通信响应标识异常，则进行预警。
或者，若所述电池特征参数和所述线路情况满足预设条件，则进行预警，包括：若当前检测周期最大温度值对应的采样点的温度值与上一采样检测周期最大温度值对应的采样点的温度值的差值大于第二阈值，且在预设倍数的电池模组温度数据采集周期内电池模组温度最大值与电池模组温度均值的差值大于电池模组温度最大值与电池模组温度均值的差值变化阈值，温度传感器故障，温度变化先于温度传感器故障，电池单体电压采样线开路正常，电池单体电压最小值小于电池热失控的电池单体电压异常最值，且当前采样周期电池单体电压最小值和上一采样周期电池单体电压最小值的差值大于第一阈值，则进行预警，其中，所述第一阈值为电池单体电压最小值变化速率阈值与预设倍数的电池单体电压数据采样周期的比值，其中，所述第二阈值为变化速率阈值与变化速率的判断周期的比值。
本实施例是在基于菊花链的电池管理系统拓扑结构下，能够运用电池温度最值的变化特征和因电池热失控导致的电池管理系统电气故障的定位方法，准确预警电池热失控，并在车辆仪表上对用户进行预警提示，同时可以将故障信息上传大数据监控平台。如图1B所示，通过本申请的技术方案可以诊断出发生 热失控的故障位置，能够对后续的车辆维修、故障分析提供参考信息，也有助于电池系统结构、布置的设计改进。首先需要对电池单体电压、温度数据进行实时采集，并对电池单体电压、温度最值点的变化特征和异常位置进行识别及校验，其中，对电池单体电压、温度最值点的变化特征和异常位置进行识别及校验包括如下步骤：步骤1：通过电池管理系统采样从板实时采集电池单体电压、电池模组温度数据，由电池管理系统主控板对电池单体电压、电池模组温度数据建立数组并进行赋值处理：电池单体电压数据数组：CellVol[n]，电池模组温度数据数组：ModuleTemp[m]，其中，n为电池系统单体电压采样点数；m为电池系统电池模组温度采样点数。步骤2：实时对电池单体电压数据数组和电池模组温度数据数组进行数据处理，计算出电池单体电压最小值、最大值及对应采样点和电池模组温度最小值、最大值及对应采样点，以及电池模组温度平均值：f[Vmin，NumVmin]＝Min(CellVol[n])，f[Vmax，NumVmax]＝Max(CellVol[n])，f[Tmin，NumTmin]＝Min(ModuleTemp[m])，f[Tmax，NumTmax]＝Max(ModuleTemp[m])，Tavg＝Sum(ModuleTemp[m])/m，其中，Vmin为电池单体电压最小值，NumVmin为电池单体电压最小值采样点位置；Tmax为电池模组温度最大值，NumTmax为电池模组温度最大值采样点位置；Tavg为电池模组温度平均值。步骤3：计算电池模组温度最值点相邻温度采样点的值；Tmaxf＝ModuleTemp[NumTmax-1],Tmaxb＝ModuleTemp[NumTmax+1]，其中，Tmaxf为电池模组温度最大值前一个采样点的温度,Tmaxb为电池模组温度最大值后一个采样点的温度。如果NumTmax＝1,Tmaxf＝Tmax；如果NumTmax＝m，Tmaxb＝Tmax。步骤4：计算电池模组温度最大值变化速率，为保证对电池模组温度最大值的变化速率识别的准确性，考虑到电池能量密度对温升速率的影响，以及电池模组温度变化的快速性和极速性,计算电池模组温度最大值变化速率：快速变化速率：ΔTmax1＝Tmax(i)-Tmax(i-1)，极速变化速率：ΔTmax2＝Tmax(j)-Tmax(j-1)，其中，Tmax(i)、Tmax(j)为当前检测周期最大温度值对应的采样点的温度值，Tmax(i-1)、Tmax(j-1)为上一检测周期最大温度值对应的采样点的温度值；ΔTmax1的检测周期大于ΔTmax1。步骤5：计算同一电池模组内电池模组温度最大值的相邻温度值变化速率，考虑到电池发生热失控时，由于故障电池单体发热影响，相邻温度采样点也会有快速温升变化，同时也排除电池模组温度最大值采样点传感器采样异常的干扰，计算同一电池模组内温度最大值的相邻温度值变化速率为：ΔTmaxf＝Tmaxf(k)-Tmaxf(k-1)，ΔTmaxb＝Tmaxb(k)-Tmaxb(k-1)；其中，Tmaxf(k) 和Tmaxb(k)为当前采样周期相邻采样点的温度值，Tmaxf(k-1)和Tmaxb(k-1)为上一采样周期相邻采样点的温度值。步骤6：对电池模组温度最大值以及相邻温度值与电池模组温度平均值的差值变化特征进行识别，考虑到电池热失控可能由其中一个单体异常引起，所以采用电池模组温度最大值以及相邻温度值与电池模组温度平均值的差值变化特征进行识别，该差值计算如下：ΔT＝Tmax-Tavg，ΔTf＝Tmaxf-Tavg，ΔTb＝Tmaxb-Tavg；其中，ΔT是电池模组温度最大值与电池模组温度平均值的差值，ΔTf是电池模组温度最大值前一相邻温度值与平均值的差值，ΔTb是电池模组温度最大值后一相邻温度值与平均值的差值。步骤7：除考虑电池热失控对电池温度特征的影响，对电池单体电压变化的影响也进行了识别。计算电池单体电压最小值变化速率：ΔVmin＝Vmin(k)Vmin(k-1)；其中，Vmin(k)为当前采样周期单体电压最小值，Vmin(k-1)为上一采样周期单体电压最小值。步骤8：综合步骤4～7的计算数据进行电池热失控预警：
电池热失控判定工况1：
条件①Vmin<Vrt
条件②ΔVmin>V1/t4
条件③Tmax>Trt
条件④NumTmax和NumVmin在同一电池模组内
条件①～④全部满足，热失控预警标识1置为1。
其中，Vrt为电池热失控的单体电压异常最值，Trt电池热失控的电池温度异常最值；V1为电池单体电压最小值变化速率阈值，范围为1V～4V；t4为电池单体电压数据采样周期的1～5倍。
电池热失控判定工况2：
条件①Tmax>Trt
条件②ΔTmax1>T1/t1或ΔTmax2>T2/t2
条件③ΔT>T3，且保持时间>t3
条件①～③全部满足，热失控预警标识2置为1。
条件②中，是为保证对最大值的变化速率识别的准确性，考虑到电池能量密度对温升速率的影响，电池模组温度变化的快速性和极速性，对电池模组温度最大值变化特征进行双速率识别。其中，ΔTmax1为快速，T1为快速变化速率阈值，范围为1℃～3℃，t1为快速变化速率的判断周期，范围为电池模组温度数据采样周期的20～30倍；ΔTmax2为极速，T2为极速变化速率阈值，范围为 2℃～5℃，t2为极速变化速率的判断周期，范围为电池模组温度数据采样周期的5～10倍。
条件③中，T3为电池模组温度最大值与电池模组均值的差值变化阈值，范围为20℃～25℃，t3为电池模组温度最大值与电池模组均值的差值的保持时间，范围为电池模组温度数据采样周期的10倍～20倍。
电池热失控判定工况3：
条件①Tmax>Trt
条件②ΔTmaxf>T1/t1或ΔTmaxb>T1/t1
条件③ΔTf>T4或ΔTb>T4，且保持时间>t3
条件①～③全部满足，热失控预警标识3置为1。
其中，T4为温度最大值相邻温度值与均值的差值变化阈值，范围为10℃～25℃。
考虑到电池发生热失控时，由于故障电池单体发热影响，相邻温度对应的采样点也会有快速温升变化，同时也排除电池模组温度最大值采样点传感器采样异常的干扰，对电池模组温度最大值所在同一电池模组内的相邻温度点变化特征进行快速率识别。也可根据单个电池模组温度采样点数，选择采用ΔTmaxf和ΔTmaxb中的至少一个。如果NumTmax＝1，只采用ΔTmaxb的判断结果；如果NumTmax＝m，只采用ΔTmaxf的判断结果。
判定工况1至3任一热失控预警标识置为1，电池管理系统发出电池热失控预警信号，若工况1至3热失控预警标识未置为1，则进入电池特性变化和电池管理系统电气故障联合识别电池热失控诊断流程。
当发生电池热失控时可能影响电池管理系统的单体电压、温度数据采样线路，使采样数据发生异常，不能确保采样数据的精准性；同时电池热失控也可能对电池管理系统的数据传输、通讯线路、采样板供电线路产生影响，这些电池管理系统电气故障会导致数据不能及时更新，甚至阻断数据传输，存在故障误报、漏报的风险。考虑到上述情况，对电池管理系统的数据采样线路、通讯线路、采样板供电线路进行识别，并结合前述的电池单体电压、温度最值点的变化特征和异常位置识别及校验方法，对电池系统发生热失控的位置进行更精准的识别，同时也提高了对电池热失控预警的准确性。
在一实施例中，对电池单体电压、温度最值点的变化特征和异常位置进行识别及校验包括如下步骤：步骤10：根据相邻电池单体电压变化和压差识别出 电池单体电压采样线开路故障，并识别出故障位置。
ΔV＝Vmax-Vmin
单体压差识别：ΔV＞V2
压差位置识别：|NumVmax-NumVmin|＝1
其中，V2为单体电压采样线开线故障的压差阈值。
满足上述条件，判断出单体电压最大值采样点与最小值采样点中间位置的采样线发生开路故障。
步骤20：根据电池模组温度最大值及电池模组温度最小值采样值进行范围判断，识别出温度传感器采样线开路或短路故障，同时识别出故障位置。如果电池模组温度最大值及电池模组温度最小值超出温度传感器采样温度范围，则判断超出范围的温度采样点发生温度传感器采样线开路或短路故障。
步骤30：当发生电池管理系统采样板通讯线路、供电线路故障时，体现出的是异常采样板上传的电池单体电压、模组温度数据不再更新，以及采样板的通讯响应标识异常，从这些数据及响应标识的异常，可以识别出故障位置。
步骤40：结合电池模组温度变化、单体电压变化与步骤10～30中的条件联合定位热失控故障。
电池热失控判定工况4：
条件①Tmax>Trt
条件②有电池单体电压采样线开路故障
条件③NumTmax和电池单体电压采样线开路故障点在同一模组
条件④无温度传感器故障
条件①～④全部满足，热失控预警标识4置为1。
电池热失控判定工况5：
条件①Tmax>Trt
条件②无温度传感器故障
条件③采样板通讯响应标识异常
条件④NumTmax和采样板通讯响应标识异常点在同一模组
条件⑤Tmax>Trt时间先于采样板通讯响应标识异常
条件①～⑤全部满足，热失控预警标识5置为1。
电池热失控判定工况6：
条件①ΔTmax>T1/t1或ΔTmax>T2/t2
条件②ΔT>T3，且保持时间>t3
条件③有温度传感器故障
条件④温度变化先于温度传感器故障
条件⑤无电池单体电压采样线开路故障
条件⑥Vmin<Vrt
条件⑦ΔVmin>V1/t4
条件①～⑦全部满足，热失控预警标识6置为1。
判定工况4～5任一热失控预警标识置为1，电池管理系统发出电池热失控预警信号，若工况4～5热失控预警标识未置为1，则重新进入电池特性变化识别电池热失控诊断流程。
经过上述方法诊断出电池热失控故障后，电池管理系统会控制高压回路断开，上报仪表电池热失控故障，提示用户立即远离车辆，电池管理系统同步上传故障信息至大数据监控平台。
在一实施例中，如图1C所示，图中，电池管理系统1包括一个主控板和6个从控板，电池系统正极2和电池系统负极3分别设置，电池模组与主控板或者从控板通过电池管理系统采样线路连接，电池模组与电池模组通过电池模组间连接铜排相连，主控板与从控板或者从控板与从控板通过电池管理系统通讯线路相连，针对上述电池管理系统拓扑结构，设置电池热失控判定工况1～6的判定值：
电池热失控判定工况1：
条件①Vmin<Vrt
条件②ΔVmin>V1/t4
条件③Tmax>Trt
条件④NumTmax和NumVmin在同一电池模组内
条件①～④全部满足，热失控预警标识1置为1。
电池热失控判定工况2：
条件①Tmax>Trt
条件②ΔTmax1>T1/t1或ΔTmax2>T2/t2
条件③ΔT>T3，且保持时间>t3
条件①～③全部满足，热失控预警标识2置为1。
电池热失控判定工况3：
条件①Tmax>Trt
条件②ΔTmaxf>T1/t1或ΔTmaxb>T1/t1
条件③ΔTf>T4或ΔTb>T4，且保持时间>t3
条件①～③全部满足，热失控预警标识3置为1。
电池热失控判定工况4：
条件①Tmax>Trt
条件②有电池单体电压采样线开路故障
条件③NumTmax和电池单体电压采样线开路故障点在同一模组
条件④无温度传感器故障
条件①～④全部满足，热失控预警标识4置为1。
电池热失控判定工况5：
条件①Tmax>Trt
条件②无温度传感器故障
条件③采样板通讯响应标识异常
条件④NumTmax和采样板通讯响应标识异常点在同一模组
条件⑤Tmax>Trt时间先于采样板通讯响应标识异常
条件①～⑤全部满足，热失控预警标识5置为1。
电池热失控判定工况6：
条件①ΔTmax>T1/t1或ΔTmax>T2/t2
条件②ΔT>T3，且保持时间>t3
条件③有温度传感器故障
条件④温度变化先于温度传感器故障
条件⑤无电池单体电压采样线开路故障
条件⑥Vmin<Vrt
条件⑦ΔVmin>V1/t4
条件①～⑦全部满足，热失控预警标识6置为1。
本实施例中，Trt可以为65℃、85℃或100℃，Vrt可以为1V、1.5V或2V，V1可以为1V、2V或4V，T1可以为1℃、2℃或3℃，T2可以为2℃、3℃或5℃，T3可以为20℃、23℃或25℃，T4可以为10℃、15℃或20℃，t1可以为2s、2.5s或3s，t2可以为500ms、800ms或1000ms，t3可以为1s、1.5s或2s，t4可以为100ms、300ms或500ms。根据实验结果报警后的数据变化分析可得，电池热失控判定工况4和5 同样可报出电池热失控故障，且本实施例公开的技术方案可以准确进行电池热失控故障定位。
本实施例考虑了电池热失控导致的电池温度变化特征，以及对同电池模组电池单体的影响，可以避免由其中一个温度传感器发生采样异常导致的热失控误诊断。本申请所涉及的由电池热失控引起的电池管理系统电气故障的定位方法，可以避免因单独判断电池温度变化趋势导致的热失控误诊断，提高对电池热失控的位置定位的准确性。本实施例中的电池管理系统拓扑结构包括但不限于分布式拓扑结构，也能通过集中式实现。
本实施例运用基于菊花链的电池管理系统拓扑结构的特点进行电池热失控故障诊断定位，不增设其他气体、压力传感器；运用与电池热失控温度最值点相同电池模组的相邻温度点的采样值的变化特征以及与电池温度均值差值的变化特征识别方法，对电池热失控导致的温度最值进行校验，提高温度最值识别的准确性，排除因单一温度传感器采样异常引起的故障误报。电池热失控温度最值的快速、极速变化特征的识别方法与其他相关技术用温度单一速率比较，更能覆盖高能量密度电池的热失控工况。用电池热失控电池模组温度最值变化、单体电压最值变化与电池管理系统采样故障、通讯故障进行联合诊断定位，能够降低电池管理系统电气故障引发的因数据不能及时更新、数据传输阻断导致的故障误报、漏报的风险。在电池热失控故障处理措施方面不仅考虑当前的高压断开操作、仪表预警提示，还能够将故障信息同步上传至大数据监控平台，对售后维修、大数据分析、电池系统设计改进都有积极作用。
本实施例是为了在纯电动汽车上有效检测电池热失控，提出了一种结合电池温度变化特征识别和因电池热失控导致的电池管理系统电气故障定位检测，根据温度变化特征和故障定位对电池热失控进行预警。本实施例运用基于菊花链的电池管理系统拓扑结构的特点进行电池热失控故障诊断定位，不增设其他气体、压力传感器，在成本上有优势；运用与电池热失控温度最值点相同电池模组的相邻温度点的采样值的变化特征以及与电池温度均值差值的变化特征识别方法，对电池热失控导致的温度最值进行校验，提高温度最值识别可靠性；用电池热失控温度最值的快速、极速变化特征的识别方法与其他相关技术中采用温度单一速率进行比较，更能覆盖高能量密度电池的热失控工况；用电池热失控电池模组温度最值变化、单体电压最值变化与电池管理系统采样故障、通讯故障进行联合诊断定位，能够降低电池管理系统电气故障引发的因数据不能 及时更新、数据传输阻断导致的故障误报、漏报的风险；在电池热失控故障处理措施方面不仅考虑当前的高压断开操作、仪表预警提示，还可以将故障信息同步上传至大数据监控平台，对售后维修、大数据分析、电池系统设计改进都有积极作用。
本实施例的技术方案，通过实时采集电池单体电压和电池模组温度；根据所述电池单体电压和电池模组温度计算得到电池特征参数；若所述电池特征参数满足预设条件，则进行预警，能够准确预警电池热失控。
实施例二
图2为本申请实施例二提供的一种预警装置的结构示意图。本实施例可适用于预警的情况，该装置可采用软件和硬件中的任一种方式实现，该装置可集成在任何提供预警的功能的设备中，如图2所示，所述预警装置具体包括：采集模块210、计算模块220和预警模块230。
其中，采集模块，设置为实时采集电池单体电压和电池模组温度；
计算模块，设置为根据所述电池单体电压和电池模组温度计算得到电池特征参数；
预警模块，设置为当所述电池特征参数满足预设条件时，则进行预警。
上述产品可执行本申请任意实施例所提供的方法，具备执行方法相应的功能模块和有益效果。
本实施例的技术方案，通过实时采集电池单体电压和电池模组温度；根据所述电池单体电压和电池模组温度计算得到电池特征参数；若所述电池特征参数满足预设条件，则进行预警，能够准确预警电池热失控。
实施例三
图3为本申请实施例三中的一种计算机设备的结构示意图。图3示出了适于用来实现本实施方式的计算机设备12的框图。图3显示的计算机设备12仅仅是一个示例，不应对本申请实施例的功能和使用范围带来任何限制。
如图3所示，计算机设备12以通用计算设备的形式表现。计算机设备12的组件可以包括但不限于：一个或者多个处理器或者处理单元16，系统存储器28，连接不同系统组件(包括系统存储器28和处理单元16)的总线18。
总线18表示几类总线结构中的一种或多种，包括存储器总线或者存储器控 制器，外围总线，图形加速端口，处理器或者使用多种总线结构中的任意总线结构的局域总线。举例来说，这些体系结构包括但不限于工业标准体系结构(ISA)总线，微通道体系结构(MAC)总线，增强型ISA总线、视频电子标准协会(VESA)局域总线以及外围组件互连(PCI)总线。
计算机设备12包括多种计算机系统可读介质。这些介质可以是任何能够被计算机设备12访问的可用介质，包括易失性和非易失性介质，可移动的和不可移动的介质。
系统存储器28可以包括易失性存储器形式的计算机系统可读介质，例如随机存取存储器(RAM)30和高速缓存存储器32中的至少一种。计算机设备12还可以包括其它可移动或不可移动的、易失性或非易失性计算机系统存储介质。仅作为举例，存储系统34可以用于读写不可移动的、非易失性磁介质(图3未显示，通常称为“硬盘驱动器”)。尽管图3中未示出，可以提供用于对可移动非易失性磁盘(例如“软盘”)读写的磁盘驱动器，以及对可移动非易失性光盘(例如CD-ROM,DVD-ROM或者其它光介质)读写的光盘驱动器。在这些情况下，每个驱动器可以通过一个或者多个数据介质接口与总线18相连。存储器28可以包括至少一个程序产品，该程序产品具有一组(例如至少一个)程序模块，这些程序模块被配置为执行本申请每个实施例的功能。
具有一组(至少一个)程序模块42的程序或实用工具40，可以存储在例如存储器28中，这样的程序模块42包括但不限于操作系统、一个或者多个应用程序、其它程序模块以及程序数据，程序模块42的这些示例中的至少一种可能包括网络环境。程序模块42通常执行本申请所描述的实施例中的功能和方法中的一种。
计算机设备12也可以与一个或多个外部设备14(例如键盘、指向设备、显示器24等)通信，还可与一个或者多个使得用户能与该计算机设备12交互的设备通信，或与使得该计算机设备12能与一个或多个其它计算设备进行通信的任何设备(例如网卡，调制解调器等等)通信。这种通信可以通过输入/输出(I/O)接口22进行。另外，本实施例中的计算机设备12，显示器24不是作为独立个体存在，而是嵌入镜面中，在显示器24的显示面不予显示时，显示器24的显示面与镜面从视觉上融为一体。并且，计算机设备12还可以通过网络适配器20与一个或者多个网络(例如局域网(LAN)，广域网(WAN)和公共网络中的至少一种，例如因特网)通信。如图3所示，网络适配器20通过总线18与计算机设备12的其 它模块通信。尽管图中未示出，可以结合计算机设备12使用其它硬件和软件模块中的至少一种，其它硬件和软件模块包括但不限于：微代码、设备驱动器、冗余处理单元、外部磁盘驱动阵列、RAID系统、磁带驱动器或数据备份存储系统等。
处理单元16通过运行存储在系统存储器28中的程序，从而执行多种功能应用以及数据处理，例如实现本申请实施例所提供的预警方法：实时采集电池单体电压和电池模组温度；根据所述电池单体电压和电池模组温度计算得到电池特征参数；若所述电池特征参数满足预设条件，则进行预警。
实施例四
本申请实施例四提供了一种计算机可读存储介质，该计算机可读存储介质上存储有计算机程序，该程序被处理器执行时实现如本申请所有实施例提供的预警方法：实时采集电池单体电压和电池模组温度；根据所述电池单体电压和电池模组温度计算得到电池特征参数；若所述电池特征参数满足预设条件，则进行预警。
可以采用一个或多个计算机可读的介质的任意组合。计算机可读介质可以是计算机可读信号介质或者计算机可读存储介质。计算机可读存储介质例如可以是但不限于电、磁、光、电磁、红外线或半导体的系统、装置或器件，或者任意以上的组合。计算机可读存储介质的更具体的例子(非穷举的列表)包括：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本申请中，计算机可读存储介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与该程序结合使用。
计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号，该数据信号承载了计算机可读的程序代码。这种传播的数据信号可以采用多种形式，包括但不限于电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读存储介质以外的任何计算机可读介质，该计算机可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与该计算机可读介质结合使用的程序。
计算机可读介质上包含的程序代码可以用任何适当的介质传输，包括但不 限于无线、电线、光缆或RF等等，或者上述的任意合适的组合。
可以以一种或多种程序设计语言或其组合来编写用于执行本申请操作的计算机程序代码，所述程序设计语言包括面向对象的程序设计语言，诸如Java、Smalltalk或C++，还包括常规的过程式程序设计语言，诸如“C”语言或类似的程序设计语言。程序代码可以完全地在用户计算机上执行、部分地在用户计算机上执行、作为一个独立的软件包执行、部分在用户计算机上部分在远程计算机上执行、或者完全在远程计算机或服务器上执行。在涉及远程计算机的情形中，远程计算机可以通过任意种类的网络连接到用户计算机或者，可以连接到外部计算机，该网络包括局域网(LAN)或广域网(WAN)，外部计算机可以利用因特网服务提供商来通过因特网连接)。

Claims (10)

  1. 一种预警方法，包括：
    实时采集电池单体电压和电池模组温度；
    根据所述电池单体电压和电池模组温度计算得到电池特征参数；及
    若所述电池特征参数满足预设条件，则进行预警。
  2. 根据权利要求1所述的方法，其中，所述若所述电池特征参数满足预设条件，则进行预警之前，还包括：根据所述电池特征参数确定线路情况；
    若所述电池特征参数满足预设条件，则进行预警，包括：若所述电池特征参数和所述线路情况满足预设条件，则进行预警。
  3. 根据权利要求1或2所述的方法，其中，所述电池特征参数包括：电池模组温度最大值，电池模组温度最小值，电池模组温度最大值和最小值对应的采样点，电池单体电压最大值，电池单体电压最小值，电池单体电压最小值和最小值对应的采样点，电池模组温度平均值，电池模组温度最值相邻温度值，电池模组温度最大值变化速率，同一电池模组内电池模组温度最大值的相邻温度值变化速率，电池模组温度最大值与电池模组温度均值的差值，电池模组温度最大值对应的采样点的相邻采样点的温度值与电池模组温度均值的差值以及电池单体电压最小值变化速率中的至少一种。
  4. 根据权利要求2所述的方法，其中，所述线路情况包括：电池单体电压采样线开路故障、温度传感器采样线开路故障、温度传感器采样线短路故障、采样板通讯线路故障、采样板供电线路故障、采样板的通讯响应标识异常中的至少一种。
  5. 根据权利要求2所述的方法，其中，所述根据所述电池特征参数确定线路情况包括以下情况中的一种：
    若电池单体电压最大值和电池单体电压最小值的差值大于单体电压采样线开线故障的压差阈值，且电池单体电压最大值采样点位置编号与电池单体电压最小值采样点位置编号的差值等于1，则确定电池单体电压最大值、最小值采样点中间位置的采样线发生开路故障；
    若温度传感器的电压值大于电压阈值，则确定所述温度传感器采样线开路或者短路故障；及
    若采样板上传的电池单体电压和模组温度数据中至少一个不更新，且采样板通信响应标识异常，则确定采样板通讯线路和供电线路故障中的至少一种情况。
  6. 根据权利要求1所述的方法，其中，所述若所述电池特征参数满足预设条件，则进行预警，包括以下情况中的一种：
    若电池模组温度最大值大于电池热失控的电池温度异常阈值，电池单体电压最小值小于电池热失控的电池单体电压异常阈值，当前采样周期电池单体电压最小值和上一采样周期电池单体电压最小值的差值大于第一阈值，且电池模组温度最大值对应的采样点的位置和电池单体电压最小值对应的采样点的位置在同一电池模组内，则进行预警，其中，所述第一阈值为电池单体电压最小值变化速率阈值与预设倍数的电池单体电压数据采样周期的比值；
    若电池模组温度最大值大于电池热失控的电池温度异常最值，当前检测周期最大温度值对应的采样点的温度值与上一采样检测周期最大温度值对应的采样点的温度值的差值大于第二阈值，且在预设倍数的电池模组温度数据采样周期内，电池模组温度最大值与电池模组温度均值的差值大于所述温度最大值与所述平均值的差值变化阈值，则进行预警，其中，所述第二阈值为变化速率阈值与变化速率的判断周期的比值；及
    若电池模组温度最大值大于电池热失控的电池温度异常阈值，当前采样周期最大温度值点的相邻温度值与上一采样周期最大温度值的相邻温度值的差值大于第二阈值，且电池模组温度最大值的前一相邻温度值或者后一相邻温度值与所述电池模组温度均值的差值大于所述电池模组温度最大值的相邻温度值与所述电池模组温度均值的差值变化阈值，则进行预警。
  7. 根据权利要求2所述的方法，其中，所述若所述电池特征参数和所述线路情况满足预设条件，则进行预警，包括以下情况中的任一种：
    若电池模组温度最大值大于电池热失控的电池温度异常最值，电池单体电压采样线开路故障，电池模组温度最大值采样点位置和电池单体电压采样线开路故障点在同一模组，且温度传感器处于正常工作状态，则进行预警；
    若电池模组温度最大值大于电池热失控的电池温度异常最值，所述温度传感器处于正常工作状态，采样板通信响应标识异常，电池模组温度最大值采样点和采样板通信响应标识异常点在同一模组，且电池模组温度最大值大于电池热失控的电池温度异常最值的时间先于采样板通信响应标识异常，则进行预警；及
    若当前检测周期最大温度值对应采样点的温度值与上一采样检测周期最大温度值对应采样点的温度值的差值大于第二阈值，且在预设倍数的电池模组温 度数据采集周期内电池模组温度最大值与电池模组温度均值的差值大于电池模组温度最大值与电池模组温度均值的差值变化阈值，温度传感器故障，温度变化先于温度传感器故障，电池单体电压采样线开路正常，电池单体电压最小值小于电池热失控的电池单体电压异常最值，且当前采样周期电池单体电压最小值和上一采样周期电池单体电压最小值的差值大于第一阈值，则进行预警，其中，所述第一阈值为电池单体电压最小值变化速率阈值与预设倍数的电池单体电压数据采样周期的比值，其中，所述第二阈值为变化速率阈值与变化速率的判断周期的比值。
  8. 一种预警装置，包括：
    采集模块，设置为实时采集电池单体电压和电池模组温度；
    计算模块，设置为根据所述电池单体电压和电池模组温度计算得到电池特征参数；及
    预警模块，设置为若所述电池特征参数满足预设条件，则进行预警。
  9. 一种计算机设备，包括存储器、处理器及存储在存储器上并可在处理器上运行的计算机程序，其中，所述处理器执行所述程序时实现如权利要求1-7中任一所述的方法。
  10. 一种计算机可读存储介质，其中，所述计算机可读存储介质存储有计算机程序，所述程序被处理器执行时实现如权利要求1-7中任一所述的方法。
PCT/CN2021/098055 2020-06-08 2021-06-03 预警方法、装置、设备及存储介质 WO2021249269A1 (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP21823006.8A EP4102615A4 (en) 2020-06-08 2021-06-03 EARLY WARNING METHOD AND APPARATUS, DEVICE AND STORAGE MEDIUM

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202010511835.9 2020-06-08
CN202010511835.9A CN111653840B (zh) 2020-06-08 2020-06-08 一种预警方法、装置、设备及存储介质

Publications (1)

Publication Number Publication Date
WO2021249269A1 true WO2021249269A1 (zh) 2021-12-16

Family

ID=72351294

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/098055 WO2021249269A1 (zh) 2020-06-08 2021-06-03 预警方法、装置、设备及存储介质

Country Status (3)

Country Link
EP (1) EP4102615A4 (zh)
CN (1) CN111653840B (zh)
WO (1) WO2021249269A1 (zh)

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114464906A (zh) * 2022-02-10 2022-05-10 重庆金康动力新能源有限公司 动力电池预警方法和装置
CN114487836A (zh) * 2022-01-26 2022-05-13 上海玫克生智能科技有限公司 基于电压和温度的电池状态分析方法、系统及终端
CN115084685A (zh) * 2022-08-22 2022-09-20 新能动力(北京)智慧能源科技有限公司 一种对电池包进行动态调整的方法、装置以及存储介质
CN115320385A (zh) * 2022-07-28 2022-11-11 重庆金康赛力斯新能源汽车设计院有限公司 车辆电池的热失控预警方法、装置、设备和存储介质
CN115825790A (zh) * 2022-01-29 2023-03-21 宁德时代新能源科技股份有限公司 电池绝缘故障的预警方法、装置、系统和计算机设备
CN115840157A (zh) * 2022-12-08 2023-03-24 斯润天朗(合肥)科技有限公司 基于eof分析的锂电池电性能指标协调性分析系统
CN116106758A (zh) * 2023-03-23 2023-05-12 华能新能源股份有限公司山西分公司 基于数据驱动的电池故障诊断方法及系统
CN117169733A (zh) * 2023-11-01 2023-12-05 车城智能装备(武汉)有限公司 一种动力电池监控方法、系统、设备及存储介质
CN117214741A (zh) * 2023-11-09 2023-12-12 杭州高特电子设备股份有限公司 一种电池采集温度异常的诊断方法和电池系统
WO2024045502A1 (zh) * 2022-08-31 2024-03-07 岚图汽车科技有限公司 电池电压采集故障预警方法及系统

Families Citing this family (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111653840B (zh) * 2020-06-08 2021-07-09 中国第一汽车股份有限公司 一种预警方法、装置、设备及存储介质
CN112180282B (zh) * 2020-09-24 2023-05-12 蜂巢能源科技股份有限公司 电池热失控概率的预测方法、装置、介质、系统及车辆
CN112172528B (zh) * 2020-09-29 2021-11-05 蜂巢能源科技有限公司 识别车辆电芯热失控的误报的方法、装置、存储介质及车辆
CN112363061A (zh) * 2020-11-11 2021-02-12 上海电享信息科技有限公司 一种基于大数据的热失控风险评估方法
CN112345943B (zh) * 2020-11-13 2022-03-18 东风汽车集团有限公司 一种电池热失控预警方法及装置
CN112581715B (zh) * 2020-12-10 2022-03-04 珠海格力电器股份有限公司 电池高温报警方法、装置及系统
CN112785821A (zh) * 2021-01-05 2021-05-11 四川天辰智联科技有限公司 一种住宅智能安防报警方法、系统及计算机可读存储介质
CN112909363A (zh) * 2021-02-05 2021-06-04 北京车和家信息技术有限公司 电池系统内短路预警方法、装置、介质、车载系统和车辆
CN112937303B (zh) * 2021-02-08 2022-10-04 重庆长安新能源汽车科技有限公司 一种电池过热后实时在线预警方法及系统
CN113022378B (zh) * 2021-03-01 2023-03-07 中国第一汽车股份有限公司 温度一致性预测方法、装置、预测设备及存储介质
CN113119737B (zh) * 2021-04-28 2023-02-21 中国第一汽车股份有限公司 一种动力电池热失控监控装置、方法及动力电池系统
CN113341332A (zh) * 2021-05-25 2021-09-03 三一重机有限公司 电池热失控预警方法、装置、作业机械及电子设备
CN113904008A (zh) * 2021-09-27 2022-01-07 江西昌河汽车有限责任公司 一种汽车动力电池热失控预警系统
CN116068423A (zh) * 2021-10-29 2023-05-05 宁德时代新能源科技股份有限公司 电池热失控检测方法、装置、系统、车辆及存储介质
CN114184973A (zh) * 2021-11-18 2022-03-15 安徽锐能科技有限公司 锂电池包充电过程中潜在不良的诊断方法及系统
CN114274778A (zh) * 2021-12-16 2022-04-05 奇瑞新能源汽车股份有限公司 动力电池的失效预警方法、装置、车辆及存储介质
CN115219900B (zh) * 2022-06-24 2024-06-04 阿理新能源科技(昆山)有限公司 一种锂离子电池系统的状态监测方法及装置
CN115649005A (zh) * 2022-09-21 2023-01-31 岚图汽车科技有限公司 电池温度采样故障预警方法、系统、电子设备及存储介质
CN115267589B (zh) * 2022-09-26 2023-01-06 陕西汽车集团股份有限公司 一种电动汽车电池故障多参数联合诊断方法

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN207274442U (zh) * 2017-08-23 2018-04-27 北京智行鸿远汽车有限公司 电动汽车电池过温保护系统
CN108736079A (zh) * 2018-04-08 2018-11-02 江西优特汽车技术有限公司 一种动力电池热失控扩散预警系统及方法
US20190302188A1 (en) * 2018-03-28 2019-10-03 Yokogawa Electric Corporation Electronic device, battery life judgment method, and battery life judgment program
CN110370984A (zh) * 2019-06-26 2019-10-25 清华大学 动力电池热失控预警方法
CN110967642A (zh) * 2019-04-30 2020-04-07 宁德时代新能源科技股份有限公司 热失控检测电路及方法
CN111653840A (zh) * 2020-06-08 2020-09-11 中国第一汽车股份有限公司 一种预警方法、装置、设备及存储介质

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
UA82129C2 (uk) * 2006-05-03 2008-03-11 Институт Транспортных Систем И Технологий Национальной Академии Наук Украины "Трансмаг" Електричний спосіб контролю технічного стану свинцево-кислотних акумуляторних батарей
KR101629648B1 (ko) * 2015-04-03 2016-06-13 태성이엘이씨 주식회사 배터리 관리기능을 갖는 부표용 축전장치
CN210442486U (zh) * 2019-04-30 2020-05-01 宁德时代新能源科技股份有限公司 热失控检测电路

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN207274442U (zh) * 2017-08-23 2018-04-27 北京智行鸿远汽车有限公司 电动汽车电池过温保护系统
US20190302188A1 (en) * 2018-03-28 2019-10-03 Yokogawa Electric Corporation Electronic device, battery life judgment method, and battery life judgment program
CN108736079A (zh) * 2018-04-08 2018-11-02 江西优特汽车技术有限公司 一种动力电池热失控扩散预警系统及方法
CN110967642A (zh) * 2019-04-30 2020-04-07 宁德时代新能源科技股份有限公司 热失控检测电路及方法
CN110370984A (zh) * 2019-06-26 2019-10-25 清华大学 动力电池热失控预警方法
CN111653840A (zh) * 2020-06-08 2020-09-11 中国第一汽车股份有限公司 一种预警方法、装置、设备及存储介质

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP4102615A4 *

Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114487836A (zh) * 2022-01-26 2022-05-13 上海玫克生智能科技有限公司 基于电压和温度的电池状态分析方法、系统及终端
CN115825790A (zh) * 2022-01-29 2023-03-21 宁德时代新能源科技股份有限公司 电池绝缘故障的预警方法、装置、系统和计算机设备
CN115825790B (zh) * 2022-01-29 2023-10-17 宁德时代新能源科技股份有限公司 电池绝缘故障的预警方法、装置、系统和计算机设备
CN114464906A (zh) * 2022-02-10 2022-05-10 重庆金康动力新能源有限公司 动力电池预警方法和装置
CN115320385A (zh) * 2022-07-28 2022-11-11 重庆金康赛力斯新能源汽车设计院有限公司 车辆电池的热失控预警方法、装置、设备和存储介质
CN115320385B (zh) * 2022-07-28 2024-04-30 重庆金康赛力斯新能源汽车设计院有限公司 车辆电池的热失控预警方法、装置、设备和存储介质
CN115084685A (zh) * 2022-08-22 2022-09-20 新能动力(北京)智慧能源科技有限公司 一种对电池包进行动态调整的方法、装置以及存储介质
WO2024045502A1 (zh) * 2022-08-31 2024-03-07 岚图汽车科技有限公司 电池电压采集故障预警方法及系统
CN115840157A (zh) * 2022-12-08 2023-03-24 斯润天朗(合肥)科技有限公司 基于eof分析的锂电池电性能指标协调性分析系统
CN115840157B (zh) * 2022-12-08 2023-08-22 斯润天朗(合肥)科技有限公司 基于eof分析的锂电池电性能指标协调性分析系统
CN116106758A (zh) * 2023-03-23 2023-05-12 华能新能源股份有限公司山西分公司 基于数据驱动的电池故障诊断方法及系统
CN116106758B (zh) * 2023-03-23 2024-01-30 华能新能源股份有限公司山西分公司 基于数据驱动的电池故障诊断方法及系统
CN117169733A (zh) * 2023-11-01 2023-12-05 车城智能装备(武汉)有限公司 一种动力电池监控方法、系统、设备及存储介质
CN117214741A (zh) * 2023-11-09 2023-12-12 杭州高特电子设备股份有限公司 一种电池采集温度异常的诊断方法和电池系统
CN117214741B (zh) * 2023-11-09 2024-05-28 杭州高特电子设备股份有限公司 一种电池采集温度异常的诊断方法和电池系统

Also Published As

Publication number Publication date
CN111653840A (zh) 2020-09-11
EP4102615A4 (en) 2024-03-13
EP4102615A1 (en) 2022-12-14
CN111653840B (zh) 2021-07-09

Similar Documents

Publication Publication Date Title
WO2021249269A1 (zh) 预警方法、装置、设备及存储介质
CN111361454B (zh) 动力电池热管理系统的诊断方法、装置、设备和存储介质
CN101499544B (zh) 电池装置、保护电路、温度监控方法、温度传感器布置方法
WO2023273267A1 (zh) 故障诊断方法、装置、电子设备及存储介质
Sun et al. An online data-driven fault diagnosis and thermal runaway early warning for electric vehicle batteries
WO2023273971A1 (zh) 电池包泄露检测的方法、装置、电子设备及存储介质
WO2023050614A1 (zh) 电动汽车的充电检测方法、装置及系统
CN112034358A (zh) 一种锂电池热失控检测系统及方法
CN110609491B (zh) 电动汽车整车控制器半实物仿真事故鉴定方法及系统
CN111506048B (zh) 车辆故障预警方法及相关设备
WO2023237123A1 (zh) 混合动力车辆的故障提示方法和车辆
CN104076808A (zh) 工控设备的故障诊断系统和方法
WO2023221595A1 (zh) 电动汽车绝缘检测功能的失效诊断系统、方法及设备
CN112327733A (zh) 一种船舶机舱智能监控系统
CN112285478A (zh) 车辆静态电流的检测方法和装置、介质、设备、车辆
US12009490B2 (en) Method and apparatus for determining status of battery temperature sensor, medium, vehicle, and server
CN104914376A (zh) 一种数字量电路状态检测电路和方法
CN112462744A (zh) 一种坦克火控系统状态评估与故障诊断系统
CN109948937B (zh) 人工智能自学习的安全隐患检测方法、系统、设备及介质
WO2023028850A1 (zh) 一种动力电池热失控的控制方法、装置及动力电池
KR102172012B1 (ko) 철도차량 안전부품 진단장치
KR20230089895A (ko) 제어 신호를 이용한 빅데이터 기반의 엘이디 디스플레이 장치의 모니터링 시스템
CN113723625A (zh) 基于网关的故障区域识别方法、装置、智能网关和介质
CN112988445A (zh) 一种计算机板卡故障诊断方法、系统及计算机板卡
CN111367765A (zh) 接口响应性能的监控方法、装置、服务器和存储介质

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21823006

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2021823006

Country of ref document: EP

Effective date: 20220909

NENP Non-entry into the national phase

Ref country code: DE