Fault state determination method and device, storage medium and electronic device

Abstract

The invention discloses a fault state determination method and device, a storage medium and an electronic device, and the method comprises the steps: collecting the real-time temperature data of a plurality of battery clusters in a battery cabin within a preset monitoring time, and obtaining a plurality of data sets; performing battery compartment average temperature calculation processing on the multiple groups of data sets to obtain a first time data sequence; performing battery cluster relative temperature calculation processing on the multiple groups of data sets to obtain a second time data sequence; according to the sequence fluctuation of the first time data sequence and / or the second time data sequence, whether the first-class thermal management system and the second-class thermal management system in the battery compartment are in a fault state or not is determined, each battery cluster corresponds to one second-class thermal management system, and the first-class thermal management system is formed by the multiple second-class thermal management systems. The problem that faults of a thermal management system in a battery energy storage power station are difficult to monitor and identify in time is solved, and the safety and efficiency of the energy storage power station are improved.

Description

Technical Field

[0001] The present application relates to the field of energy storage technology, and in particular to a method and device for determining a fault state, a storage medium, and an electronic device. Background Art

[0002] Lithium-ion battery energy storage technology occupies an important position in domestic energy storage power stations. However, with the rapid growth of the scale of energy storage power stations, the safety problems of lithium-ion battery energy storage stations have gradually emerged. Battery thermal runaway is one of the main causes of safety accidents in energy storage systems, so thermal management is crucial to preventing battery runaway. At present, there are many technical routes and design schemes for energy storage thermal management systems. Among them, the air cooling system uses air as a medium for heat dissipation, which has the advantages of simple structure and low cost. It is currently widely used in the field of energy storage power stations. Typical air cooling systems usually use air conditioning for cooling, and at the same time, guide air ducts and guide fans are arranged above the battery compartment to divert cold air to the top of each battery cluster. A battery compartment is usually equipped with a large number of guide fans. Due to space limitations, the operating status of the fan is difficult to detect. If the fan fails, it will affect the battery cooling effect, thereby reducing battery performance and even triggering an overtemperature fault.

[0003] With regard to the problem in related technologies that failures of thermal management systems in battery energy storage power stations are difficult to monitor and identify in a timely manner, no effective solution has been proposed so far.

[0004] Therefore, it is necessary to improve the related technology to overcome the above-mentioned defects in the related technology. Summary of the invention

[0005] The embodiments of the present application provide a method and device for determining a fault status, a storage medium, and an electronic device, so as to at least solve the problem that faults of a thermal management system in a battery energy storage power station are difficult to monitor and identify in a timely manner.

[0006] According to one aspect of an embodiment of the present application, a method for determining a fault state is provided, including: collecting real-time temperature data of multiple battery clusters in a battery compartment within a preset monitoring time to obtain multiple data sets; performing battery compartment average temperature calculation processing on the multiple data sets to obtain a first time data series; performing battery cluster relative temperature calculation processing on the multiple data sets to obtain a second time data series; determining whether a first-class thermal management system and a second-class thermal management system in the battery compartment are in a fault state based on sequence fluctuations of the first time data series and / or the second time data series, wherein each battery cluster corresponds to a second-class thermal management system, and multiple second-class thermal management systems constitute a first-class thermal management system.

[0007] In an exemplary embodiment, determining whether a first type of thermal management system and a second type of thermal management system in a battery compartment are in a fault state is performed based on sequence fluctuations of a first time data series and / or a second time data series, including: obtaining a first monitoring threshold preset for the battery compartment, wherein the first monitoring threshold is a maximum temperature fluctuation value of a compartment-level average temperature corresponding to the battery compartment allowed for safe operation; determining that the first type of thermal management system is in a fault state when the difference between any two consecutive temperature data in the first time data series is greater than the first monitoring threshold, wherein the first type of thermal management system is a thermal management system at the battery compartment level; determining that the first type of thermal management system is in a non-fault state when the difference between any two consecutive temperature data in the first time data series is less than or equal to the first monitoring threshold, and sending a prompt message to the management object of the battery compartment that the battery compartment is operating normally.

[0008] In an exemplary embodiment, determining whether a first type of thermal management system and a second type of thermal management system in a battery compartment are in a fault state is performed based on sequence fluctuations of a first time data series and / or a second time data series, including: obtaining a second monitoring threshold preset for the battery compartment, wherein the second monitoring threshold is a maximum temperature fluctuation value of cluster-level relative temperatures corresponding to different battery clusters allowed for safe operation; determining that the second type of thermal management system is in a fault state when the difference between any two consecutive temperature data in the second time data series is greater than the second monitoring threshold, wherein the second type of thermal management system is a cluster-level thermal management system; determining that the second type of thermal management system is in a non-fault state when the difference between any two consecutive temperature data in the second time data series is less than or equal to the second monitoring threshold, and generating status information that the second type of thermal management system is operating normally.

[0009] In an exemplary embodiment, after determining whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a faulty state based on the sequence fluctuations of the first time data series and / or the second time data series, the above method also includes: when there are multiple battery compartments in the energy storage area at the same time, recording a first number of faulty battery compartments; when the first number is greater than a preset value, determining that there is an energy storage abnormality in the current energy storage area, and the power transmission line of the battery compartment needs to be inspected.

[0010] In an exemplary embodiment, after determining whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state based on the sequence fluctuations of the first time data series and / or the second time data series, the above method also includes: acquiring structural data of the battery compartment; determining the location and component type of components used for heat dissipation in the battery compartment based on the structural data; determining the real-time operating status of each component type; and determining whether the fault state is caused by hardware abnormality of the heat dissipation component based on the real-time operating status.

[0011] In an exemplary embodiment, determining whether a fault state is caused by a hardware abnormality of a heat dissipation component is based on the real-time operating status, including: in the case where it is determined based on the real-time operating status that a fault state is caused by a hardware abnormality of a heat dissipation component, collecting the abnormal position of the abnormal component; sending the component type and the abnormal position of the abnormal component to the management object of the battery compartment; and prompting the management object to replace components in the battery compartment.

[0012] According to another aspect of an embodiment of the present application, a device for determining a fault status is also provided, including: an acquisition module, used to acquire real-time temperature data of multiple battery clusters in a battery compartment within a preset monitoring time to obtain multiple data sets; a first calculation module, used to perform battery compartment average temperature calculation processing on the multiple data sets to obtain a first time data series; a second calculation module, used to perform battery cluster relative temperature calculation processing on the multiple data sets to obtain a second time data series; a determination module, used to determine whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state according to the sequence fluctuation of the first time data series and / or the second time data series, wherein each battery cluster corresponds to a second type of thermal management system, and multiple second type of thermal management systems constitute the first type of thermal management system.

[0013] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program is configured to execute the above-mentioned method for determining the fault state when running.

[0014] According to another aspect of an embodiment of the present application, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the method for determining the fault state through the computer program.

[0015] According to another aspect of the embodiments of the present application, a computer program product is provided, including a computer program, and a method for determining the above-mentioned fault state when the computer program is executed by a processor.

[0016] Through this application, real-time temperature data of multiple battery clusters in the battery compartment within a preset monitoring time are collected to obtain multiple data sets; the battery compartment average temperature calculation process is performed on the multiple data sets to obtain a first time data sequence; the battery cluster relative temperature calculation process is performed on the multiple data sets to obtain a second time data sequence; according to the sequence fluctuations of the first time data sequence and / or the second time data sequence, it is determined whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a faulty state, wherein each battery cluster corresponds to a second type of thermal management system, and multiple second type of thermal management systems constitute the first type of thermal management system. The above technical solution is adopted to solve the problem that the failure of the thermal management system in the battery energy storage power station is difficult to monitor and identify in time. Furthermore, by monitoring the temperature data of the battery cluster in the battery compartment and analyzing the sequence changes of the average temperature of the battery compartment and the relative temperature of the battery cluster, the thermal management system failure is diagnosed, thereby improving the safety and efficiency of the energy storage power station. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0019] Figure 1 It is a hardware structure block diagram of a computer terminal of a method for determining a fault state according to an embodiment of the present application;

[0020] Figure 2 is a flow chart of a method for determining a fault state according to an embodiment of the present application;

[0021] Figure 3 It is a flow chart of a fault diagnosis method of a thermal management system of a battery energy storage power station according to an embodiment of the present application;

[0022] Figure 4 is a battery compartment average temperature monitoring curve diagram according to an embodiment of the present application;

[0023] Figure 5 is a relative temperature monitoring curve diagram of a battery cluster according to an embodiment of the present application;

[0024] Figure 6 It is a structural block diagram of determining a fault state according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] The method embodiments provided in the embodiments of the present application can be executed in a computer terminal, a mobile terminal or a similar computing device. Taking running on a computer terminal as an example, Figure 1 FIG. 1 is a hardware structure block diagram of a computer terminal of a method for determining a fault state according to an embodiment of the present application. Figure 1 As shown, the computer terminal may include one or more ( Figure 1 The computer terminal includes a processor 102 (only one is shown in the figure) (the processor 102 may include but is not limited to a processing device such as a microprocessor (Central Processing Unit, CPU) or a programmable logic device (Field Programmable Gate Array, FPGA)) and a memory 104 for storing data, wherein the computer terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above-mentioned computer terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0028] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the method for determining the fault state in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0029] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0030] In this embodiment, a method for determining a fault state is provided. Figure 2 is a flow chart of a method for determining a fault state according to an embodiment of the present application, such as Figure 2 As shown, the process includes the following steps S202-S208:

[0031] Step S202: collecting real-time temperature data of multiple battery clusters in the battery compartment within a preset monitoring time to obtain multiple sets of data;

[0032] Step S204: performing battery compartment average temperature calculation processing on the plurality of data sets to obtain a first time data sequence;

[0033] Step S206: performing battery cluster relative temperature calculation processing on the plurality of data sets to obtain a second time data series;

[0034] Step S208: Determine whether the first-type thermal management system and the second-type thermal management system in the battery compartment are in a fault state based on the sequence fluctuations of the first time data series and / or the second time data series, wherein each battery cluster corresponds to a second-type thermal management system, and multiple second-type thermal management systems constitute a first-type thermal management system.

[0035] The above steps collect real-time temperature data of multiple battery clusters in the battery compartment within a preset monitoring time to obtain multiple data sets; perform battery compartment average temperature calculation processing on the multiple data sets to obtain a first time data series; perform battery cluster relative temperature calculation processing on the multiple data sets to obtain a second time data series; determine whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state based on the sequence fluctuations of the first time data series and / or the second time data series, wherein each battery cluster corresponds to a second type of thermal management system, and multiple second type of thermal management systems constitute the first type of thermal management system. The above technical solution solves the problem that the failure of the thermal management system in the battery energy storage power station is difficult to monitor and identify in time. Furthermore, by monitoring the temperature data of the battery cluster in the battery compartment and analyzing the sequence changes of the average temperature of the battery compartment and the relative temperature of the battery cluster, the thermal management system failure is diagnosed, thereby improving the safety and efficiency of the energy storage power station.

[0036] In an exemplary embodiment, determining whether a first type of thermal management system and a second type of thermal management system in a battery compartment are in a fault state is performed based on sequence fluctuations of a first time data series and / or a second time data series, including: obtaining a first monitoring threshold preset for the battery compartment, wherein the first monitoring threshold is a maximum temperature fluctuation value of a compartment-level average temperature corresponding to the battery compartment allowed for safe operation; determining that the first type of thermal management system is in a fault state when the difference between any two consecutive temperature data in the first time data series is greater than the first monitoring threshold, wherein the first type of thermal management system is a thermal management system at the battery compartment level; determining that the first type of thermal management system is in a non-fault state when the difference between any two consecutive temperature data in the first time data series is less than or equal to the first monitoring threshold, and sending a prompt message to the management object of the battery compartment that the battery compartment is operating normally.

[0037] In a battery energy storage power station, if the monitoring threshold of the average temperature of the battery compartment is set to 5℃, it means that in any charging or discharging cycle, if the average temperature of the battery compartment changes by more than 5℃ between two consecutive monitoring points, the battery compartment-level thermal management system is considered to be in a faulty state. For example, when a battery compartment is operating normally, the average temperature fluctuates between 25℃ and 30℃, which is within a safe range. If during the day, the system monitors that the average temperature of the battery compartment is 28℃ at the 10th monitoring point, and suddenly rises to 35℃ at the 11th monitoring point, that is, the temperature change is 7℃. Since 7℃ exceeds the preset 5℃ monitoring threshold, the system immediately determines that the battery compartment-level thermal management system may be in a faulty state. On the contrary, if the average temperature of the battery compartment is 28℃ at the 10th monitoring point, and changes to 29℃ at the 11th monitoring point, that is, the temperature change is only 1℃, which does not exceed the 5℃ monitoring threshold, the system will determine that the battery compartment-level thermal management system is in a non-faulty state. At this time, a prompt message that the battery compartment is operating normally is sent to the management object of the battery compartment, avoiding unnecessary alarms and ensuring the stable operation of the system. In this way, not only can the detection efficiency of thermal management system faults in battery energy storage power stations be improved, but the fault type and location can also be effectively located, greatly improving the safety and operation and maintenance efficiency of the energy storage system.

[0038] In an exemplary embodiment, determining whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state based on the sequence fluctuation of the first time data series and / or the second time data series includes: obtaining a second monitoring threshold preset for the battery compartment, wherein the second monitoring threshold is the maximum temperature fluctuation value of the cluster-level relative temperature corresponding to different battery clusters allowed for safe operation; determining that the second type of thermal management system is in a fault state when the difference between any two consecutive temperature data in the second time data series is greater than the second monitoring threshold, wherein the second type of thermal management system is a cluster-level thermal management system; determining that the second type of thermal management system is in a non-fault state when the difference between any two consecutive temperature data in the second time data series is less than or equal to the second monitoring threshold, and generating status information indicating that the second type of thermal management system is operating normally.

[0039] Optionally, in a battery energy storage power station, the second monitoring threshold is set to 0.2, which means that when the temperature fluctuation between different battery clusters exceeds 20%, the system will consider that there may be a battery cluster-level thermal management system failure. For example, during a certain monitoring cycle, the system records the characteristic temperature of the battery cluster at the 10th monitoring point and the 11th monitoring point. At the 10th monitoring point, the characteristic temperature distribution of all battery clusters is relatively uniform, with an average value of 0.6. However, at the 11th monitoring point, the system detects that the characteristic temperature of one of the battery clusters suddenly rises to 0.9, while the characteristic temperatures of other battery clusters remain at around 0.6. Since the relative change in the characteristic temperature of the battery cluster is 0.3, that is, from 0.6 to 0.9, the fluctuation exceeds the set second monitoring threshold of 0.2, and the system determines that the thermal management system corresponding to the battery cluster may be in a faulty state. If the characteristic temperature fluctuations of all battery clusters do not exceed the second monitoring threshold from the 10th monitoring point to the 11th monitoring point, the system will determine that the second type of thermal management system is in a non-faulty state, and then generate status information that the battery cluster-level thermal management system is operating normally, ensuring the normal operation of the system and avoiding unnecessary inspections and maintenance. Through this method, not only can the efficient operation of the thermal management system be ensured, but the risk of battery thermal runaway can also be effectively reduced, thereby improving the overall safety and operation and maintenance efficiency of the energy storage power station.

[0040] In an exemplary embodiment, after determining whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a faulty state based on the sequence fluctuations of the first time data series and / or the second time data series, the above method also includes: when there are multiple battery compartments in the energy storage area at the same time, recording a first number of faulty battery compartments; when the first number is greater than a preset value, determining that there is an energy storage abnormality in the current energy storage area, and the power transmission line of the battery compartment needs to be inspected.

[0041] Optionally, 20 battery compartments are deployed in an energy storage area, and each battery compartment is equipped with the above-mentioned thermal management system fault diagnosis method. The preset fault battery compartment threshold in the area is 3, that is, when more than 3 battery compartments report thermal management system faults at the same time, the system will judge it as a regional energy storage anomaly, and the transmission lines in the entire area need to be checked. For example, during one day's operation, the system detected that at the 20th monitoring point, 3 battery compartments reported thermal management system faults: battery compartment A, battery compartment B, and battery compartment C. The average temperature of battery compartment A suddenly rose from 28°C to 35°C, the relative temperature of a battery cluster in battery compartment B rose from 0.6 to 0.9, and the average temperature of battery compartment C also fluctuated abnormally. Since 3 battery compartments reported faults at the same time, exceeding the preset threshold, the system immediately judged that there was an energy storage anomaly in the current energy storage area and automatically triggered a regional alarm. Timely discovery and handling of regional-level faults effectively controlled the chain effect of faults and ensured the stable operation of the energy storage area.

[0042] In an exemplary embodiment, after determining whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state based on the sequence fluctuations of the first time data series and / or the second time data series, the above method also includes: acquiring structural data of the battery compartment; determining the location and component type of components used for heat dissipation in the battery compartment based on the structural data; determining the real-time operating status of each component type; and determining whether the fault state is caused by hardware abnormality of the heat dissipation component based on the real-time operating status.

[0043] Optionally, in a battery energy storage power station, the battery compartment adopts an air-cooled heat dissipation design, which includes multiple heat dissipation components such as air conditioning units, guide fans and heat sinks. The system first obtains the structural data of the battery compartment and determines that the air conditioning unit is located on one side of the battery compartment, there are two guide fans above each battery cluster, and the heat sinks are distributed around the battery cluster. During a routine inspection, the system detected that the temperature in a certain area in the battery compartment increased significantly, and the speed data of the guide fan above the battery cluster in this area was abnormally low, lower than the speed during normal operation. At the same time, the cooling capacity and energy consumption data of the air conditioning unit were also within the normal range, indicating that the air conditioning unit was operating normally. Based on these real-time operating status data, the system determined that the cause of the temperature increase in this area may be a hardware failure of the guide fan, such as a fan blade blockage or a motor problem. By obtaining the battery compartment structural data and monitoring the real-time operating status of the heat dissipation components, hardware faults can be accurately identified and located, providing support for fast and effective fault resolution, while also avoiding unnecessary inspection and maintenance of components that are operating normally, saving operation and maintenance costs.

[0044] In an exemplary embodiment, determining whether a fault state is caused by a hardware abnormality of a heat dissipation component is based on the real-time operating status, including: in the case where it is determined based on the real-time operating status that a fault state is caused by a hardware abnormality of a heat dissipation component, collecting the abnormal position of the abnormal component; sending the component type and the abnormal position of the abnormal component to the management object of the battery compartment; and prompting the management object to replace components in the battery compartment.

[0045] Optionally, in a battery energy storage power station, the system detects that the temperature of a certain area in the battery compartment is abnormally increased. After further analysis, it is found that the guide fan above the battery cluster is operating abnormally, and its speed is much lower than the normal value. After determining that the fault state is caused by the abnormal hardware of the heat dissipation component, the system collects the specific location information of the abnormal guide fan. For example, it is determined that the faulty fan is located above the second battery cluster in the third row of the battery compartment, numbered F3_2. Subsequently, the system sends this information, including the type of abnormal component (guide fan) and the abnormal location (F3_2) to the management object of the battery compartment. After receiving this information, the management object can quickly locate the specific location of the faulty fan and conduct an on-site inspection. The faulty fan is replaced in time to ensure the normal operation of other fans. The above embodiment shows an efficient processing flow after determining the hardware failure of the heat dissipation component based on the real-time operating status. From fault diagnosis to information transmission, and then to on-site replacement, each link is accurately and timely executed, which not only quickly solves the fault, but also avoids the waste of resources caused by inaccurate information, and ensures the stable operation and safety performance of the battery energy storage power station.

[0046] Obviously, the embodiments described above are only some embodiments of the present application, not all embodiments. In order to better understand the above method, the above process is described below in conjunction with the embodiments, but it is not intended to limit the technical solutions of the embodiments of the present application, specifically:

[0047] The optional embodiment of the present application provides a method for diagnosing faults in the thermal management system of a battery energy storage power station to solve the problem that it is difficult to monitor and identify faults in the thermal management system in a battery energy storage power station in a timely manner. The method determines the location of each battery cluster, i.e., the number of batteries, according to the integrated structure of the battery compartment; monitors the temperature of all batteries in each battery cluster, and calculates the average and maximum temperature of the battery cluster, and normalizes the temperature as the characteristic temperature of the battery cluster; calculates the characteristic temperature of each battery cluster, and when the characteristic temperature of the battery cluster increases significantly, it is determined that the guide fan corresponding to the cluster is faulty and needs to be inspected and confirmed.

[0048] Optional, Figure 3 This is a flow chart of a fault diagnosis method for a thermal management system of a battery energy storage power station according to an embodiment of the present application; it specifically includes the following steps:

[0049] Step 1: Data acquisition. Determine the temperature measurement points of each battery cluster. Taking a typical air-cooled battery compartment as an example, the battery compartment contains several battery clusters, denoted as S1, S2, …, S m , determine that each battery cluster contains temperature measurement points, such as S m The temperature measurement points are [t m,1 ,t m,2 ,…,t m,n ], where m is the number of battery clusters contained in the battery compartment, and n is the number of battery clusters Sm The number of temperature sensors included. Collect the required temperature data from the energy storage BMS system, PCS system or EMS system according to the measurement point data.

[0050] Step 2: Calculate the average temperature of the battery compartment. Calculate the average temperature of the battery cluster. Take a charge or discharge cycle of the battery cell as the calculation time interval. In the charge or discharge cycle, the battery cluster is not required to be fully charged and discharged, but it is required to meet a certain charge and discharge amount to ensure that the investigated interval meets the calculation requirements. For example, the battery cluster investigation interval is required to meet SOC = [20,90]. In this time interval, record all temperature data of each battery cluster. For example, for battery cluster S m Temperature data is [t m,1 ,t m,2 ,…,t m,n ]1,[t m,1 ,t m,2 ,…,t m,n ]2,…,[t m,1 ,t m,2 ,…,t m,n ]k, where k is the temperature acquisition time. Then the average temperature of the battery cluster in the investigated time interval is:

[0051]

[0052] Calculate the average temperature of all battery clusters, respectively t = [t 1,mean , t 2,mean ,…,t m,mean ] Calculate the average temperature of the battery compartment:

[0053]

[0054] Step 3: Calculate the relative temperature of the battery cluster. Take a charge or discharge cycle of the battery cell as the calculation time interval. In the charge or discharge cycle, the battery cluster is not required to be fully charged and discharged, but a certain charge and discharge amount is required to ensure that the thermal management system is put into operation within the investigated interval. According to step 2, calculate the average temperature of all battery clusters in turn, which are t = [t 1,mean , t 2,mean ,…,t m,mean ]. Normalize the battery cluster temperature:

[0055]

[0056] Among them, t sn is the normalized battery cluster S m Average temperature, as the battery cluster S m Characteristic temperature. After normalization, the characteristic temperature of the battery cluster is distributed in the interval [0, 1].

[0057] Step 4: Monitor the average temperature of the battery compartment. Specifically include:

[0058] (1) Temperature time series calculation. For the battery compartment, its average temperature time series table data T mean =[t mean,1 ,t mean,2 ,…,t mean,c ], where t mean,c is the cth average temperature of the battery compartment.

[0059] (2) Average temperature threshold setting. For example, if the battery compartment average temperature threshold is set to 5°C, when T mean A certain value in the interior fluctuates significantly, that is, |T mean,c+1 -T mean,c |≥5 means that the heat dissipation state in the battery compartment has changed significantly. Figure 4 As shown, Figure 4 is a battery compartment average temperature monitoring curve diagram according to an embodiment of the present application; Figure 4 It can be seen that the average temperature of the battery compartment at the 8th monitoring point is 30, and starting from the 9th monitoring temperature, the average temperature of the battery compartment rises to 38, which means that starting from the 9th monitoring temperature, there may be a failure in the overall thermal management system of the battery compartment, such as a failure of the air conditioner compressor or external fan, which needs to be investigated in detail.

[0060] Step 5: Battery cluster relative temperature monitoring. Specifically including:

[0061] (1) Temperature time series calculation. For a battery cluster, its average temperature time series data T m.s =[t m,s,1 ,t m,s,2 ,…,t m,s,c ], where t m,s,c is the cth relative temperature of battery cluster m.

[0062] (2) Relative temperature threshold setting. For example, if the relative temperature threshold is set to 0.2, when T m,s A certain value in the interior fluctuates significantly, that is, |T m,s,c+1 -T m,s,c When |≥0.2, it means that the heat dissipation state of the battery cluster has changed significantly. Figure 5 As shown, Figure 5 is a relative temperature monitoring curve diagram of a battery cluster according to an embodiment of the present application, from Figure 5 It can be seen that the relative temperature of a battery cluster at the 8th monitoring point is 0.6, and starting from the 9th monitoring temperature, the relative temperature of the battery cluster rises to 0.9, which means that starting from the 9th monitoring temperature, the thermal management system components corresponding to the battery cluster may be faulty, such as the guide fan above the battery cluster, which needs to be checked in detail.

[0063] It should be noted that when determining the location and number of batteries of each battery cluster according to the integrated structure of the battery compartment, the accuracy and real-time nature of the data must be ensured. If the battery compartment structure changes or the number of batteries is adjusted, the location and quantity information in the system must be updated in a timely manner, otherwise the characteristic temperature calculation may be wrong, affecting the accuracy of fault diagnosis. When calculating the average and maximum values ​​of the battery cluster temperature, it is necessary to ensure the correctness of the data processing logic to avoid misjudgment caused by data anomalies or processing errors. The normalization process is equally important. It needs to be based on a certain time window and a reasonable temperature range to ensure that the normalized characteristic temperature can accurately reflect the temperature state of the battery cluster. To determine whether the characteristic temperature of the battery cluster has increased significantly, a reasonable threshold needs to be set. The setting of the threshold needs to comprehensively consider the battery operating temperature range, the normal temperature fluctuation range, and the working characteristics of the thermal management system. Too high or too low thresholds may lead to false alarms or missed alarms, affecting the accuracy and timeliness of fault diagnosis. The significant increase in the characteristic temperature of the battery cluster is not necessarily entirely due to the failure of the guide fan, but may also be affected by other factors, such as problems with the battery itself, blockage of the heat exchanger, etc. Therefore, when determining that the guide fan is faulty, it is necessary to conduct a comprehensive analysis in combination with other data and information to avoid misjudgment.

[0064] In summary, the optional embodiments of the present application calculate the average temperature of the battery compartment under the required working conditions as the characteristic temperature of the battery compartment. When the overall average temperature of the battery compartment increases significantly, it is judged that there may be a fault in the battery compartment-level thermal management system, which requires timely maintenance. At the same time, the normalized temperature of the battery cluster is calculated as the characteristic temperature of the battery cluster. When the relative temperature of a battery cluster increases significantly, it is judged that there may be a fault in the corresponding thermal management system component, which requires timely maintenance. This method does not require system hardware modification and can simultaneously identify battery compartment-level and battery cluster-level thermal management system faults, which helps to improve power station operating efficiency and reduce the risk of thermal runaway.

[0065] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.

[0066] In this embodiment, a device for determining a fault state is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0067] Figure 6 is a structural block diagram of a device for determining a fault state according to an embodiment of the present application, the device comprising:

[0068] The acquisition module 62 is used to acquire real-time temperature data of multiple battery clusters in the battery compartment within a preset monitoring time to obtain multiple sets of data;

[0069] A first calculation module 64 is used to perform battery compartment average temperature calculation processing on the plurality of data sets to obtain a first time data sequence;

[0070] A second calculation module 66, configured to perform battery cluster relative temperature calculation processing on the plurality of data sets to obtain a second time data series;

[0071] A determination module 68 is used to determine whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state based on the sequence fluctuation of the first time data series and / or the second time data series, wherein each battery cluster corresponds to a second type of thermal management system, and multiple second type of thermal management systems constitute a first type of thermal management system.

[0072] The above device collects real-time temperature data of multiple battery clusters in the battery compartment within a preset monitoring time to obtain multiple data sets; performs battery compartment average temperature calculation processing on the multiple data sets to obtain a first time data series; performs battery cluster relative temperature calculation processing on the multiple data sets to obtain a second time data series; determines whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state based on the sequence fluctuations of the first time data series and / or the second time data series, wherein each battery cluster corresponds to a second type of thermal management system, and multiple second type of thermal management systems constitute the first type of thermal management system. The above technical solution solves the problem that the failure of the thermal management system in the battery energy storage power station is difficult to monitor and identify in time. Furthermore, by monitoring the temperature data of the battery cluster in the battery compartment and analyzing the sequence changes of the average temperature of the battery compartment and the relative temperature of the battery cluster, the thermal management system failure is diagnosed, thereby improving the safety and efficiency of the energy storage power station.

[0073] In an exemplary embodiment, the above-mentioned determination module is also used to obtain a first monitoring threshold preset for the battery compartment, wherein the first monitoring threshold is the maximum temperature fluctuation value of the compartment-level average temperature corresponding to the battery compartment allowed for safe operation; when the difference between any two consecutive temperature data in the first time data sequence is greater than the first monitoring threshold, it is determined that the first type of thermal management system is in a fault state, wherein the first type of thermal management system is a thermal management system at the battery compartment level; when the difference between any two consecutive temperature data in the first time data sequence is less than or equal to the first monitoring threshold, it is determined that the first type of thermal management system is in a non-fault state, and a prompt information that the battery compartment is operating normally is sent to the management object of the battery compartment.

[0074] In an exemplary embodiment, the above-mentioned determination module is also used to obtain a second monitoring threshold preset for the battery compartment, wherein the second monitoring threshold is the maximum temperature fluctuation value of the cluster-level relative temperature corresponding to different battery clusters allowed for safe operation; when the difference between any two consecutive temperature data in the second time data sequence is greater than the second monitoring threshold, it is determined that the second type of thermal management system is in a fault state, wherein the second type of thermal management system is a cluster-level thermal management system; when the difference between any two consecutive temperature data in the second time data sequence is less than or equal to the second monitoring threshold, it is determined that the second type of thermal management system is in a non-fault state, and status information indicating that the second type of thermal management system is operating normally is generated.

[0075] In an exemplary embodiment, the above-mentioned device also includes: a recording module, which is used to determine whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a faulty state based on the sequence fluctuation of the first time data series and / or the second time data series, and then record the first number of faulty battery compartments when there are multiple battery compartments in the energy storage area at the same time; when the first number is greater than a preset value, it is determined that there is an energy storage abnormality in the current energy storage area, and the power transmission line of the battery compartment needs to be inspected.

[0076] In an exemplary embodiment, the above-mentioned device also includes: a determination module, which is used to determine whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state based on the sequence fluctuations of the first time data series and / or the second time data series, and then obtain the structural data of the battery compartment; determine the location and component type of components used for heat dissipation in the battery compartment based on the structural data; determine the real-time operating status of each component type; and determine whether the fault state is caused by abnormal hardware of the heat dissipation component based on the real-time operating status.

[0077] In an exemplary embodiment, the above-mentioned determination module is also used to collect the abnormal position of the abnormal component when it is determined based on the real-time operating status that a fault state is caused by abnormal hardware of the heat dissipation component; send the component type and abnormal position of the abnormal component to the management object of the battery compartment; and prompt the management object to replace the components of the battery compartment.

[0078] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when run.

[0079] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0080] S1. Collecting real-time temperature data of multiple battery clusters in a battery compartment within a preset monitoring time to obtain multiple sets of data;

[0081] S2, performing battery compartment average temperature calculation processing on the multiple data sets to obtain a first time data sequence;

[0082] S3, performing battery cluster relative temperature calculation processing on the plurality of data sets to obtain a second time data series;

[0083] S4. Determine whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state based on the sequence fluctuation of the first time data series and / or the second time data series, wherein each battery cluster corresponds to a second type of thermal management system, and multiple second type of thermal management systems constitute a first type of thermal management system.

[0084] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0085] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

[0086] An embodiment of the present application further provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps in any one of the above method embodiments are performed.

[0087] An embodiment of the present application further provides another computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0088] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0089] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0090] S1. Collecting real-time temperature data of multiple battery clusters in a battery compartment within a preset monitoring time to obtain multiple sets of data;

[0091] S2, performing battery compartment average temperature calculation processing on the multiple data sets to obtain a first time data sequence;

[0092] S3, performing battery cluster relative temperature calculation processing on the plurality of data sets to obtain a second time data series;

[0093] S4. Determine whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state based on the sequence fluctuation of the first time data series and / or the second time data series, wherein each battery cluster corresponds to a second type of thermal management system, and multiple second type of thermal management systems constitute a first type of thermal management system.

[0094] In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0095] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

[0096] Obviously, those skilled in the art should understand that the above modules or steps of the present application can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

[0097] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for determining a fault state, characterized in that: include: Collecting real-time temperature data of multiple battery clusters in the battery compartment within a preset monitoring time to obtain multiple sets of data; Executing battery compartment average temperature calculation processing on the plurality of data sets to obtain a first time data sequence; Executing battery cluster relative temperature calculation processing on the plurality of data sets to obtain a second time data series; Based on the sequence fluctuation of the first time data series and / or the second time data series, determine whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state, wherein each battery cluster corresponds to a second type of thermal management system, and multiple second type of thermal management systems constitute a first type of thermal management system.

2. The method according to claim 1, characterized in that Determining whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state according to the sequence fluctuation of the first time data series and / or the second time data series includes: Obtaining a first monitoring threshold preset for the battery compartment, wherein the first monitoring threshold is a maximum temperature fluctuation value of a compartment-level average temperature corresponding to the battery compartment allowed for safe operation; When the difference between any two consecutive temperature data in the first time data sequence is greater than the first monitoring threshold, determining that the first type of thermal management system is in a fault state, wherein the first type of thermal management system is a thermal management system at the battery compartment level; When the difference between any two consecutive temperature data in the first time data sequence is less than or equal to the first monitoring threshold, it is determined that the first type of thermal management system is in a non-fault state, and a prompt message indicating that the battery compartment is operating normally is sent to the management object of the battery compartment.

3. The method according to claim 1, characterized in that Determining whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state according to the sequence fluctuation of the first time data series and / or the second time data series includes: Acquire a second monitoring threshold preset for the battery compartment, wherein the second monitoring threshold is a maximum temperature fluctuation value of cluster-level relative temperatures corresponding to different battery clusters allowed for safe operation; When the difference between any two consecutive temperature data in the second time data sequence is greater than the second monitoring threshold, determining that the second type of thermal management system is in a fault state, wherein the second type of thermal management system is a cluster-level thermal management system; When the difference between any two consecutive temperature data in the second time data series is less than or equal to the second monitoring threshold, it is determined that the second type of thermal management system is in a non-fault state, and status information indicating that the second type of thermal management system is operating normally is generated.

4. The method according to claim 1, characterized in that: After determining whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state according to the sequence fluctuation of the first time data series and / or the second time data series, the method further includes: When there are multiple battery compartments in the energy storage area at the same time, the first number of faulty battery compartments is recorded; when the first number is greater than a preset value, it is determined that there is energy storage abnormality in the current energy storage area, and the power transmission line of the battery compartment needs to be repaired.

5. The method according to claim 1, characterized in that After determining whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state according to the sequence fluctuation of the first time data series and / or the second time data series, the method further includes: Acquiring structural data of the battery compartment; Determine the location and type of components used for heat dissipation in the battery compartment according to the structural data; Determine the real-time operational status of each component type; Based on the real-time operating status, it is determined whether a fault state is generated due to hardware abnormality of the heat dissipation component.

6. The method according to claim 5, characterized in that Determining whether a fault state is caused by hardware abnormality of a heat dissipation component based on the real-time operating state includes: In the case where it is determined based on the real-time operating status that a fault state is caused by hardware abnormality of a heat dissipation component, collecting an abnormal position of the abnormal component; Sending the component type of the abnormal component and the abnormal position to the management object of the battery compartment; The management object is prompted to replace components of the battery compartment.

7. A device for determining a fault state, characterized in that: include: A collection module is used to collect real-time temperature data of multiple battery clusters in the battery compartment within a preset monitoring time to obtain multiple sets of data; A first calculation module, configured to perform battery compartment average temperature calculation processing on the plurality of data sets to obtain a first time data sequence; A second calculation module, used for performing battery cluster relative temperature calculation processing on the plurality of data sets to obtain a second time data series; A determination module is used to determine whether the first type of thermal management system and the second type of thermal management system in the battery compartment are in a fault state based on the sequence fluctuation of the first time data series and / or the second time data series, wherein each battery cluster corresponds to a second type of thermal management system, and multiple second type of thermal management systems constitute a first type of thermal management system.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 6 when executed.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 6 through the computer program.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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