Battery cell temperature sensor temperature outlier detection method and apparatus
Patent Information
- Application Number
- CN202611122795.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-07-27
- Publication Date
- 2026-11-03
AI Technical Summary
Existing technologies in the power battery systems of new energy vehicles have problems such as misjudgment when the sampling link is abnormal, missed detection of thermal runaway, lack of cross-driving cycle management and insufficient engineering adaptability in the identification of abnormal temperature sensors, dynamic effectiveness management and safety diagnosis.
By setting a sampling validity identifier for each cell temperature sampling value, calculating an average temperature reference benchmark, and combining a multi-condition coupled continuous verification mechanism to identify high-temperature and low-temperature outlier sensors, and performing setting, freezing, or recovery operations according to the voltage sampling fault time window, the system achieves refined management and safety protection of abnormal temperatures.
Significantly reduces the false alarm rate of temperature faults, improves the reliability and safety of thermal runaway diagnosis, enables refined classification and scenario-based management of temperature anomalies, enhances the robustness and fault tolerance of the BMS to sensor anomalies, and optimizes the balance between safety and vehicle availability.
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Figure CN123028722A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of battery management system (BMS) technology for new energy vehicles, and in particular to a method and device for detecting temperature outliers of cell temperature sensors based on multi-scenario fusion, sampling link anomaly perception and state machine management. It is applicable to anomaly identification, dynamic validity management and safety diagnosis of cell temperature sensors (NTC). Background Technology
[0002] In the power battery system of new energy vehicles, multiple temperature sensors (NTCs) are usually arranged on the surface of the battery module or cell to monitor the battery temperature status in real time. The collected temperature data is mainly used for the following functions: (1) Battery over-temperature and under-temperature protection; (2) Charging and discharging power limiting and thermal management control; (3) Correction of battery state estimation (SOC, SOH); (4) Thermal runaway early warning and safety protection.
[0003] To avoid the impact of a single temperature sensor malfunction on system control and safety assessments, related technologies generally incorporate a "temperature outlier detection" mechanism. This mechanism involves statistically analyzing multi-point temperature data to identify and remove or mark abnormal temperature points that significantly deviate from the overall distribution. For example, a related patent discloses a temperature anomaly detection method based on multi-temperature point statistical analysis. The main steps of this method include: (1) Acquire temperature data from multiple temperature sensors; (2) Sort the temperature data; (3) Calculate the difference between adjacent temperature values; (4) Determine whether there are abnormal temperature points based on the preset difference threshold; (5) Treat or remove abnormal temperature points as outliers.
[0004] This type of technical solution can identify obviously abnormal temperature sampling points to a certain extent, avoiding interference from extreme values on temperature control and fault diagnosis. However, it still has the following obvious shortcomings in practical engineering applications: (1) The timing effect of sampling link abnormality is not considered. The existing technology does not distinguish whether the temperature abnormality is caused by the failure of the sensor body or by link abnormalities such as the sampling chip, daisy-chain communication or voltage sampling line disconnection. It is easy to misjudge outliers before and after link jitter or disconnection. (2) Lack of collaborative logic between outlier temperature points and thermal runaway diagnosis. Existing solutions usually directly remove outlier points without considering that outlier temperature points may be real high temperature signals in some scenarios. Direct removal may lead to missed diagnosis of thermal runaway. (3) Lack of state retention mechanism across driving cycles Existing technologies typically only handle outlier states during a single power-on or single operating cycle, and cannot continuously track and manage abnormal temperature sensors in subsequent driving cycles; (4) Insufficient engineering adaptability: Existing technologies are not adaptable to complex working conditions (such as low temperature start-up, uneven heat dissipation, and differences between different vehicle models and platforms), which can easily lead to false alarms or missed alarms. Summary of the Invention
[0005] This application provides a method and apparatus for detecting outliers in a battery cell temperature sensor, in order to address how to avoid misjudgments of temperature outliers before and after sampling link anomalies or disconnections; how to reasonably eliminate outlier temperature points while ensuring no missed detection of thermal runaway; how to continuously manage outlier temperature sensors across driving cycles; and how to improve the robustness and reliability of temperature anomaly diagnosis in practical engineering applications.
[0006] The first aspect of this application provides a method for detecting temperature outliers using a battery cell temperature sensor, comprising the following steps: Set a sampling validity flag for each cell temperature sampling value, and limit the functional participation permissions of that temperature data through the sampling validity flag; Based on all currently sampled temperature values that are marked as valid, the average temperature reference baseline of the battery pack is calculated. Based on the average temperature reference benchmark, high-temperature outlier sensors and low-temperature outlier sensors are identified and marked through a multi-condition coupled continuous verification mechanism. Based on the time window of voltage sampling failure, perform set, freeze, or restore operations on outlier sensors; The high-temperature outlier sensor, the low-temperature outlier sensor, and the temperature over-limit sensor are all included in the anomaly set count, so that different levels of temperature sensor fault warnings and corresponding protection strategies are triggered based on the number in the anomaly set.
[0007] Optionally, the sampling validity identifier is divided into a valid state and an invalid state. In the valid state, the data can participate in the full temperature function calculation, while in the invalid state, the data is only used for data recording and fault tracing.
[0008] Optionally, before initiating the temperature distribution deviation determination, the availability of the sampling link and the sampling hardware is verified.
[0009] Optionally, the step of identifying and marking high-temperature outliers and low-temperature outliers based on the average temperature reference benchmark through a multi-condition coupled continuous verification mechanism includes: When any cell temperature sampling value meets the preset high temperature deviation condition relative to the average temperature reference benchmark, and the adjacent temperature difference meets the distribution change condition and continues for more than the first preset duration, it is marked as the high temperature outlier sensor. When any cell temperature sampling value meets the preset low temperature deviation condition relative to the average temperature reference benchmark and continues for more than the second preset duration, it is marked as the low temperature outlier sensor.
[0010] Optionally, it also includes: If the duration does not reach the first preset duration or the second preset duration, the validity flag of the current cell temperature sampling value is temporarily set to invalid in order to perform de-jitter processing.
[0011] Optionally, when any cell temperature sampling value satisfies a preset high-temperature deviation condition relative to the average temperature reference, and the adjacent temperature differences satisfy a distribution abrupt change condition and continue for more than a first preset duration, it is marked as the high-temperature outlier sensor, including: If the difference between any cell temperature sample value and the average temperature reference is greater than or equal to a first preset threshold, and all valid temperature sample values are sorted in descending order, and the maximum difference between any two adjacent temperature sample values is greater than or equal to a second preset threshold, and the duration reaches the first preset duration, then the sensor is marked as the high-temperature outlier sensor.
[0012] Optionally, the step of marking any cell temperature sampling value as the low-temperature outlier sensor when it meets a preset low-temperature deviation condition relative to the average temperature reference and continues for more than a second preset duration includes: If the difference between any cell temperature sampling value and the average temperature reference is greater than or equal to a third preset threshold, and the duration reaches the second preset duration, then the sensor is marked as the low-temperature outlier sensor.
[0013] A second aspect of this application provides a temperature outlier detection device for a battery cell temperature sensor, comprising: The limiting module is used to set a sampling validity identifier for each cell temperature sampling value, and to limit the functional participation permissions of the temperature data through the sampling validity identifier. The calculation module is used to calculate the average temperature reference of the battery pack based on all currently sampled temperature sample values that are marked as valid. The identification module is used to identify and mark high-temperature outlier sensors and low-temperature outlier sensors respectively based on the average temperature reference benchmark and through a multi-condition coupled continuous verification mechanism. The differentiated control module is used to perform set, freeze, or restore operations on outlier sensors based on the time window of voltage sampling fault occurrence; The early warning and protection module is used to include the high temperature outlier sensor, the low temperature outlier sensor and the temperature over-limit sensor into the anomaly set count, so as to trigger different levels of temperature sensor fault warning and corresponding protection strategies according to the number in the anomaly set.
[0014] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the temperature outlier detection method for a battery cell temperature sensor as described in the above embodiments.
[0015] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for detecting temperature outliers in a battery cell temperature sensor.
[0016] The temperature outlier detection method and apparatus for a battery cell temperature sensor proposed in this application have the following beneficial effects: (1) Significantly reduces the false alarm rate of temperature faults; (2) Improve the reliability and safety of thermal runaway diagnosis; (3) To achieve refined classification and scenario-based management of temperature anomalies; (4) Enhance the robustness and fault tolerance of the BMS to sensor anomalies; (5) Achieving a better balance between safety and vehicle availability.
[0017] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description
[0018] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein: Figure 1 This is a flowchart of a method for detecting temperature outliers using a battery cell temperature sensor according to an embodiment of this application; Figure 2 This is a block diagram of a temperature outlier detection device for a battery cell temperature sensor according to an embodiment of this application; Figure 3This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.
[0019] Explanation of reference numerals in the attached figures: 20. Temperature outlier detection device for battery cell temperature sensor, 201-limiting module, 202-calculation module, 203-identification module, 204-differentiated control module, 205-early warning and protection module, 301-memory, 302-processor, 303-communication interface. Detailed Implementation
[0020] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.
[0021] The following description, with reference to the accompanying drawings, describes a method and apparatus for detecting temperature outliers in a battery cell temperature sensor according to an embodiment of this application.
[0022] Figure 1 This is a flowchart of a method for detecting temperature outliers using a battery cell temperature sensor according to an embodiment of this application.
[0023] like Figure 1 As shown, the temperature outlier detection method of this battery cell temperature sensor includes the following steps: In step S101, a sampling validity identifier is set for each cell temperature sampling value, and the functional participation permission of the temperature data is limited by the sampling validity identifier.
[0024] In some embodiments, the sampling validity identifier is divided into valid state and invalid state. In the valid state, the data can participate in the full temperature function calculation, while in the invalid state, the data is only used for data recording and fault tracing.
[0025] It should be noted that the battery management system is applied to the power battery system of new energy vehicles. The power battery system includes several cell temperature sensors, which are negative temperature coefficient thermistors (NTCs) arranged on the top of the cells to collect the real-time temperature value of the corresponding cells. The battery management system periodically collects the temperature data of each cell temperature sensor through a sampling chip and completes data aggregation and processing through an internal communication link.
[0026] In actual implementation, a dedicated temperature sensor is independently deployed at each temperature measurement point corresponding to each cell of the power battery. This sensor is not affected by the sampling logic of other temperature measurement channels and periodically and synchronously collects the real-time raw temperature data of the corresponding cell, ensuring that each temperature sampling value has an independent acquisition link. A dedicated sampling validity identifier is configured for each cell temperature sampling value. The status of this identifier can be dynamically updated by the BMS system based on the health of the sampling link and the results of the judgment logic operation. This identifier clearly and explicitly defines the boundary range of functional modules that can access the corresponding temperature data, thus avoiding the risk of invalid or abnormal temperature values flowing into incompatible functional modules and causing calculation deviations from the data access level.
[0027] Furthermore, when the sampling validity flag is valid, the temperature sample value has full computational participation rights and can participate normally in all temperature data-based functional module calculations, such as temperature extreme value calculation, over-temperature / under-temperature protection, temperature difference diagnosis, and thermal runaway diagnosis. This provides accurate and reliable data source support for various temperature-related control logics of the battery management system, ensuring the normal operation of functions such as power battery thermal management and safety protection. When the sampling validity flag is invalid, the temperature sample value will be removed from the computational data source of regular temperature-related functions and will not participate in regular functional module calculations except for information recording and fault tracing. It will only be used for information sending and recording to avoid abnormal sampling values interfering with normal control logic. At the same time, its original sampling data will be completely stored in the system log, providing traceable original evidence for subsequent technicians to trace the cause of sampling anomalies, troubleshoot sensor hardware failures, and sort out the entire process of vehicle thermal events.
[0028] In step S102, the average temperature reference of the battery pack is calculated based on all currently sampled temperature sample values that are marked as valid.
[0029] In some embodiments, before initiating the temperature distribution deviation determination, the availability of the sampling link and the sampling hardware is verified.
[0030] In actual execution, before initiating the temperature outlier detection logic, two prerequisites must be checked first: First, verify whether the vehicle's internal communication link, on which the battery cell temperature sampling data transmission depends, is in normal operation with no packet loss, no delay, and no communication errors. Second, verify whether the dedicated sampling chip responsible for temperature data acquisition has issues such as sampling accuracy deviation, hardware communication failure, or power supply abnormalities that affect the reliability of the sampling results. Only when all the above prerequisites are verified and the underlying operating environment of the current sampling data source is confirmed to be completely reliable, can the subsequent temperature outlier detection process be formally initiated.
[0031] When the above two prerequisites are met, all temperature sampling values with valid identifiers are selected to calculate the average temperature reference benchmark of the battery pack. This benchmark is used to determine the degree of deviation of the temperature of each cell relative to the overall distribution. It can accurately reflect the true temperature distribution level of the current battery pack as a whole and eliminate the interference of invalid sampling values on the overall benchmark. Subsequently, using this benchmark as the core reference, the difference between the temperature sampling value of each cell and the benchmark is calculated one by one to realize the quantitative comparison of the temperature deviation of each cell in the entire group.
[0032] If any of the prerequisites are not met, the temperature outlier determination process will be paused directly to avoid generating incorrect outlier determination results based on abnormal data sources.
[0033] In step S103, based on the average temperature reference, the high-temperature outlier sensor and the low-temperature outlier sensor are identified and marked through a multi-condition coupled continuous verification mechanism.
[0034] In some embodiments, based on an average temperature reference, a continuous verification mechanism using multi-condition coupling is used to identify and label high-temperature outliers and low-temperature outliers, including: When any cell temperature sampling value meets the preset high temperature deviation condition relative to the average temperature reference, and the adjacent temperature difference meets the distribution change condition and continues to exceed the first preset duration, it is marked as a high temperature outlier sensor. When any cell temperature sampling value meets the preset low temperature deviation condition relative to the average temperature reference and continues for more than the second preset duration, it is marked as a low temperature outlier sensor.
[0035] In some embodiments, it also includes: If the duration does not reach the first preset duration or the second preset duration, the validity flag of the current cell temperature sampling value is temporarily set to invalid in order to perform de-jitter processing.
[0036] In some embodiments, when any cell temperature sampling value meets a preset high-temperature deviation condition relative to the average temperature reference, and the adjacent temperature difference meets a distribution abrupt change condition and continues for more than a first preset duration, it is marked as a high-temperature outlier sensor, including: If the difference between any cell temperature sample value and the average temperature reference is greater than or equal to a first preset threshold, and all valid temperature sample values are sorted in descending order, and the maximum difference between any two adjacent temperature sample values is greater than or equal to a second preset threshold, and the duration reaches a first preset duration, then the sensor is marked as a high-temperature outlier sensor.
[0037] In some embodiments, when any cell temperature sampling value meets a preset low-temperature deviation condition relative to an average temperature reference and continues for more than a second preset duration, it is marked as a low-temperature outlier sensor, including: If the difference between any cell temperature sample value and the average temperature reference is greater than or equal to a third preset threshold, and the duration reaches a second preset duration, then the sensor is marked as a low-temperature outlier sensor.
[0038] In actual execution, the triggering condition for the high temperature outlier judgment logic is as follows: the positive difference between any cell temperature sampling value and the average temperature of the entire group is greater than or equal to the first preset threshold, and the difference clearly points to the deviation characteristic of the single sampling value being abnormally high; after sorting all the valid temperature sampling values in the entire group in descending order of value, the difference between each group of adjacent temperature values is calculated by traversing the sorted sequence, and the maximum value among all adjacent differences is taken. This maximum difference is greater than or equal to the second preset threshold, thereby eliminating the misjudgment of single-channel temperature difference caused by the overall synchronous rise of the temperature of the entire group, and ensuring that the outlier point is an isolated high point that is significantly deviated from the overall temperature distribution; The two judgment conditions mentioned above must be met simultaneously for a duration that reaches the first preset duration to avoid misidentification caused by instantaneous sampling interference and transient temperature fluctuations. During the de-jittering phase when the conditions have not been met for the preset duration, the validity flag of the temperature sampling value will be temporarily set to invalid to prevent the suspected outlier from flowing into the regular temperature control related functional modules and causing the strategy to be falsely triggered. After the duration of the simultaneous satisfaction of the two conditions has been fully met, the corresponding sensor will be officially marked as a high-temperature outlier sensor to complete the final confirmation of the outlier identity.
[0039] The trigger condition for the low-temperature outlier determination logic is: the positive difference between any cell temperature sampling value and the average temperature of the entire group is greater than or equal to a preset third preset threshold. This difference represents the low-temperature deviation of a single sampling value relative to the overall average temperature of the battery pack, and is used to filter out low-temperature abnormal sampling points that are significantly lower than the overall temperature distribution. The above-mentioned low-temperature deviation determination condition must be continuously and stably established, and the duration must reach the pre-calibrated second preset duration to avoid misjudgment caused by occasional factors such as normal fluctuations in cell temperature and instantaneous interference during sampling. During the de-jittering stage when the condition does not reach the preset duration, a formal outlier determination conclusion will not be generated directly. Instead, the validity flag of the temperature sampling value will be temporarily set to invalid, and the sampling value will be suspended from participating in the calculation of regular temperature-related functional modules. After the duration of the abnormal state fully meets the standard and it is confirmed that the low-temperature deviation is a stable and non-occasional abnormality, the sensor will be officially marked as a low-temperature outlier sensor.
[0040] In step S104, the outlier sensor is set, frozen, or restored according to the time window of the voltage sampling fault.
[0041] In actual implementation, this step involves setting the identifier of outlier temperature sensors and performing refined scenario-based control logic for their full lifecycle state recovery, forming a closed-loop mechanism throughout the entire process, as detailed below: During normal operation when no voltage sampling-related faults are detected, outlier flags are allowed to be set normally for sampling points that meet the judgment criteria. At the moment when a voltage sampling-related fault is detected and throughout the subsequent period, the setting operation of adding outlier flags should be stopped immediately to avoid generating incorrect outlier judgment results due to temperature reference offset caused by voltage sampling abnormalities. The time window boundary for voltage sampling faults is determined. For outlier sensors that have been marked within the preset time interval before the fault occurs, the current state of their temperature sampling links is checked one by one. Differentiated operations of mark recovery or state freezing are performed respectively. Among them, the sampling data of outlier sensors that have completed mark recovery can only participate in the calculation of specific safety functions such as thermal runaway diagnosis, and do not participate in other functional modules other than thermal runaway diagnosis. From the mechanism level, the interference of abnormal sampling data on core functions such as vehicle thermal management and conventional over-temperature and under-temperature protection is avoided. For temperature sensors that are officially identified as temperature outliers, the following rules apply: Under normal operating conditions, the temperature outlier sensor does not participate in thermal runaway diagnosis; If no thermal runaway event occurs during the current operating cycle, the temperature outlier sensor will be permanently disabled at the start of the next operating cycle. Temperature sensors that have been permanently disabled will no longer participate in any functional modules and will not be restored.
[0042] Temperature outlier sensors do not participate in the calculations or judgments of the following functional modules: calculation of temperature extreme values, over-temperature protection and under-temperature protection, temperature difference abnormality diagnosis, and other functional modules that rely on temperature sampling values. Meanwhile, the BMS counts high-temperature outlier sensors and low-temperature outlier sensors separately, and limits the total number of allowed outlier temperature sensors to no more than a preset upper limit.
[0043] In step S105, the high-temperature outlier sensor, the low-temperature outlier sensor, and the temperature over-limit sensor are all included in the anomaly set count, so as to trigger different levels of temperature sensor fault warnings and corresponding protection strategies based on the number in the anomaly set.
[0044] In actual implementation, outlier temperature sensors that have been officially marked and temperature over-limit sensors identified by independent temperature over-limit judgment logic are uniformly collected into the abnormal temperature sensor set for full counting. The total number of abnormal sensors in the set is counted in real time, and the corresponding level of temperature sensor abnormality fault warning is triggered by matching the preset multi-gradient number threshold. At the same time, the warning signal is synchronously transmitted to the vehicle control unit, and the vehicle safety protection strategies such as power reduction operation, limiting charging power, and graded power-off are strictly matched with the warning level.
[0045] It should be noted that the temperature outlier detection logic and the temperature over-limit detection logic operate independently of each other. The two detection processes do not interfere with each other, and the abnormal results generated by each are uniformly summarized into the abnormal temperature sensor set.
[0046] In addition, the battery management system transmits the number of outlier sensors, the corresponding sampling point number information, and the actual sampling temperature value of each temperature sensor to the outside world through the vehicle communication network. At the same time, it reserves a calibrable temperature compensation interface to support the dynamic correction and optimization of temperature extreme values through parameter calibration.
[0047] The temperature outlier detection method for a battery cell temperature sensor proposed in this application has the following advantages: (1) Significantly reduces the false alarm rate of temperature faults; (2) Improve the reliability and safety of thermal runaway diagnosis; (3) To achieve refined classification and scenario-based management of temperature anomalies; (4) Enhance the robustness and fault tolerance of the BMS to sensor anomalies; (5) Achieving a better balance between safety and vehicle availability.
[0048] Next, with reference to the accompanying drawings, a temperature outlier detection device for a battery cell temperature sensor according to an embodiment of this application is described.
[0049] Figure 2 This is a block diagram of a temperature outlier detection device for a battery cell temperature sensor according to an embodiment of this application.
[0050] like Figure 2 As shown, the temperature outlier detection device 20 of the battery cell temperature sensor includes: a limiting module 201, a calculation module 202, an identification module 203, a differential control module 204, and an early warning and protection module 205.
[0051] The module 201 is used to set a sampling validity identifier for each cell temperature sampling value and to limit the functional participation permissions of that temperature data through the sampling validity identifier. The calculation module 202 is used to calculate the average temperature reference benchmark of the battery pack based on all currently valid temperature sampling values. The identification module 203 is used to identify and mark high-temperature outlier sensors and low-temperature outlier sensors respectively through a multi-condition coupled continuous verification mechanism based on the average temperature reference benchmark. The differentiated management module 204 is used to perform set, freeze, or restore operations on outlier sensors according to the occurrence time window of voltage sampling faults. The early warning and protection module 205 is used to include high-temperature outlier sensors, low-temperature outlier sensors, and temperature over-limit sensors into an anomaly set count, so as to trigger different levels of temperature sensor fault early warnings and corresponding protection strategies based on the number in the anomaly set.
[0052] In some embodiments, the sampling validity identifier is divided into valid state and invalid state. In the valid state, the data can participate in the full temperature function calculation, while in the invalid state, the data is only used for data recording and fault tracing.
[0053] In some embodiments, before initiating the temperature distribution deviation determination, the availability of the sampling link and the sampling hardware is verified.
[0054] In some embodiments, the identification module 203 includes: The first identification unit is used to mark any cell temperature sampling value as a high temperature outlier sensor when the average temperature reference benchmark meets the preset high temperature deviation condition and the adjacent temperature difference meets the distribution change condition and continues to exceed the first preset duration. The second identification unit is used to mark any cell temperature sampling value as a low-temperature outlier sensor if it meets a preset low-temperature deviation condition relative to the average temperature reference and continues for more than a second preset duration.
[0055] In some embodiments, the identification module 203 further includes: The de-jitter unit is used to temporarily invalidate the validity flag of the current cell temperature sampling value when the duration has not reached the first preset duration or the second preset duration, so as to perform de-jitter processing.
[0056] In some embodiments, the first identification unit includes: If the difference between any cell temperature sample value and the average temperature reference is greater than or equal to a first preset threshold, and all valid temperature sample values are sorted in descending order, and the maximum difference between any two adjacent temperature sample values is greater than or equal to a second preset threshold, and the duration reaches a first preset duration, then the sensor is marked as a high-temperature outlier sensor.
[0057] In some embodiments, the second identification unit includes: If the difference between any cell temperature sample value and the average temperature reference is greater than or equal to a third preset threshold, and the duration reaches a second preset duration, then the sensor is marked as a low-temperature outlier sensor.
[0058] It should be noted that the foregoing explanation of the embodiment of the temperature outlier detection method for the cell temperature sensor also applies to the temperature outlier detection device for the cell temperature sensor in this embodiment, and will not be repeated here.
[0059] The temperature outlier detection device for a battery cell temperature sensor proposed in the embodiments of this application has the following beneficial effects: (1) Significantly reduces the false alarm rate of temperature faults; (2) Improve the reliability and safety of thermal runaway diagnosis; (3) To achieve refined classification and scenario-based management of temperature anomalies; (4) Enhance the robustness and fault tolerance of the BMS to sensor anomalies; (5) Achieving a better balance between safety and vehicle availability.
[0060] Figure 3 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.
[0061] The electronic device may include: a memory 301, a processor 302, and a computer program stored in the memory 301 and executable on the processor 302. When the processor 302 executes the program, it implements the temperature outlier detection method for the battery cell temperature sensor provided in the above embodiments.
[0062] Furthermore, electronic devices also include: Communication interface 303 is used for communication between memory 301 and processor 302.
[0063] The memory 301 is used to store computer programs that can run on the processor 302.
[0064] The memory 301 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.
[0065] If the memory 301, processor 302, and communication interface 303 are implemented independently, then the communication interface 303, memory 301, and processor 302 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.
[0066] Optionally, in a specific implementation, if the memory 301, processor 302, and communication interface 303 are integrated on a single chip, then the memory 301, processor 302, and communication interface 303 can communicate with each other through an internal interface.
[0067] Processor 302 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.
[0068] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method for detecting temperature outliers of a battery cell temperature sensor.
[0069] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.
[0070] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.
[0071] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.
[0072] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.
[0073] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.
[0074] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.
[0075] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.
[0076] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.
Claims
1. A method for detecting temperature outliers using a battery cell temperature sensor, characterized in that, Includes the following steps: Set a sampling validity flag for each cell temperature sampling value, and limit the functional participation permissions of that temperature data through the sampling validity flag; Based on all currently sampled temperature values that are marked as valid, the average temperature reference baseline of the battery pack is calculated. Based on the average temperature reference benchmark, high-temperature outlier sensors and low-temperature outlier sensors are identified and marked through a multi-condition coupled continuous verification mechanism. Based on the time window of voltage sampling failure, perform set, freeze, or restore operations on outlier sensors; The high-temperature outlier sensor, the low-temperature outlier sensor, and the temperature over-limit sensor are all included in the anomaly set count, so that different levels of temperature sensor fault warnings and corresponding protection strategies are triggered based on the number in the anomaly set.
2. The method for detecting temperature outliers using a battery cell temperature sensor according to claim 1, characterized in that, The sampling validity identifier is divided into valid and invalid states. In the valid state, the data can participate in the full temperature function calculation, while in the invalid state, the data is only used for data recording and fault tracing.
3. The method for detecting temperature outliers using a battery cell temperature sensor according to claim 1, characterized in that, Before initiating the temperature distribution deviation determination, the availability of the sampling link and the sampling hardware is verified.
4. The method for detecting temperature outliers using a battery cell temperature sensor according to claim 1, characterized in that, The step of identifying and marking high-temperature outliers and low-temperature outliers based on the average temperature reference benchmark through a multi-condition coupled continuous verification mechanism includes: When any cell temperature sampling value meets the preset high temperature deviation condition relative to the average temperature reference benchmark, and the adjacent temperature difference meets the distribution change condition and continues for more than the first preset duration, it is marked as the high temperature outlier sensor. When any cell temperature sampling value meets the preset low temperature deviation condition relative to the average temperature reference benchmark and continues for more than the second preset duration, it is marked as the low temperature outlier sensor.
5. The method for detecting temperature outliers using a battery cell temperature sensor according to claim 4, characterized in that, Also includes: If the duration does not reach the first preset duration or the second preset duration, the validity flag of the current cell temperature sampling value is temporarily set to invalid in order to perform de-jitter processing.
6. The method for detecting temperature outliers using a battery cell temperature sensor according to claim 4, characterized in that, When any cell temperature sampling value meets a preset high-temperature deviation condition relative to the average temperature reference, and the adjacent temperature differences meet a distribution change condition and persist for more than a first preset duration, it is marked as the high-temperature outlier sensor, including: If the difference between any cell temperature sample value and the average temperature reference is greater than or equal to a first preset threshold, and all valid temperature sample values are sorted in descending order, and the maximum difference between any two adjacent temperature sample values is greater than or equal to a second preset threshold, and the duration reaches the first preset duration, then the sensor is marked as the high-temperature outlier sensor.
7. The method for detecting temperature outliers using a battery cell temperature sensor according to claim 4, characterized in that, When any cell temperature sampling value meets a preset low-temperature deviation condition relative to the average temperature reference benchmark and continues for more than a second preset duration, it is marked as the low-temperature outlier sensor, including: If the difference between any cell temperature sampling value and the average temperature reference is greater than or equal to a third preset threshold, and the duration reaches the second preset duration, then the sensor is marked as the low-temperature outlier sensor.
8. A temperature outlier detection device for a battery cell temperature sensor, characterized in that, include: The limiting module is used to set a sampling validity identifier for each cell temperature sampling value, and to limit the functional participation permissions of the temperature data through the sampling validity identifier. The calculation module is used to calculate the average temperature reference of the battery pack based on all currently sampled temperature values that are marked as valid. The identification module is used to identify and mark high-temperature outlier sensors and low-temperature outlier sensors respectively based on the average temperature reference benchmark and through a multi-condition coupled continuous verification mechanism. The differentiated control module is used to perform set, freeze, or restore operations on outlier sensors based on the time window of voltage sampling fault occurrence; The early warning and protection module is used to include the high temperature outlier sensor, the low temperature outlier sensor and the temperature over-limit sensor into the anomaly set count, so as to trigger different levels of temperature sensor fault warning and corresponding protection strategies according to the number in the anomaly set.
9. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the temperature outlier detection method for a cell temperature sensor as described in any one of claims 1-7.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the temperature outlier detection method for the cell temperature sensor as described in any one of claims 1-7.