Apparatus and method for processing communication with battery module
By designing the battery module communication processing device and identifying and determining the communication protocol of the battery module, the problem of battery module recycling complexity caused by different manufacturers using different communication protocols is solved, and higher compatibility and lower recycling costs are achieved.
Patent Information
- Application Number
- CN202410280152.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Priority Date
- 2023-10-25
- Filing Date
- 2024-03-12
- Publication Date
- 2025-04-25
AI Technical Summary
In the prior art, different manufacturers of electric vehicle battery modules use different communication protocols and data transmission methods, resulting in complex battery module recycling process and increasing cost and difficulty.
A battery module communication processing device is designed to connect to the communication port of the battery module through a connector, and to use the processor to identify the number of pins of the connector and the transmitted data to determine the communication protocol of the battery module, thereby establishing effective communication.
Improves compatibility between various communication protocols used by battery modules, promotes recycling of battery modules, reduces the cost and difficulty of recycling, while allowing flexible adjustment of battery modules to improve utilization and is compatible with cloud environments to improve energy storage capacity utilization.
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Figure CN119892939A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to an apparatus and method for handling communications with a battery module. Background Art
[0002] Although electric vehicles are energy-efficient means of transportation, their batteries have a limited lifespan.
[0003] During the life of the car, the battery must be replaced at least once. However, the battery may have sufficient energy storage capacity and can be recycled into an energy storage system (ESS) or the like.
[0004] However, each electric vehicle manufacturer or battery module manufacturer has its own communication protocol and data transmission method for its battery management system. Such different communication protocols increase the complexity of the battery module recycling process and increase the cost and difficulty of recycling.
[0005] This section is intended only to provide a better understanding of the background of the invention and therefore may contain information that is not necessarily prior art. Summary of the invention
[0006] Embodiments of the present disclosure provide an apparatus and method for processing communications with a battery module, which can facilitate recycling of battery modules while reducing the cost and difficulty of recycling by improving compatibility between various communication protocols used by the battery modules.
[0007] The above and other aspects and features of the present invention will become apparent from the following description of embodiments of the present invention.
[0008] According to one aspect of the present disclosure, a battery module communication processing device includes: a connector connected to a communication port of a battery module; and a processor that establishes communication of the battery module by determining the communication protocol of the battery module based on the number of pins of the connector connected to the communication port and data of the battery module transmitted through the connector.
[0009] According to the present disclosure, the battery module communication processing device improves the compatibility between various communication protocols used by the battery module, thereby facilitating the recycling of the battery module while reducing the cost and difficulty of recycling.
[0010] According to the present disclosure, the battery module communication processing device can flexibly change the number of battery modules according to user needs, thereby improving the utilization rate of the battery modules.
[0011] According to the present disclosure, a battery module communication processing device is compatible with a cloud environment to be able to improve utilization of energy storage capacity.
[0012] However, aspects and features of the present invention are not limited to the above-mentioned contents, and other aspects and features not mentioned will be clearly understood by those skilled in the art from the detailed description given below. BRIEF DESCRIPTION OF THE DRAWINGS
[0013] The following drawings attached to this specification illustrate embodiments of the present invention and, together with the detailed description of the present invention, further describe aspects and features of the present invention. Therefore, the present invention should not be interpreted as being limited to the drawings:
[0014] Figure 1 is a block diagram of a battery module communication processing device according to an embodiment of the present invention;
[0015] Figure 2 is a flow chart showing a battery module communication processing method according to one embodiment of the present invention;
[0016] Figure 3 A training processor for a machine learning model according to one embodiment of the present invention is shown;
[0017] Figure 4 is a flow chart illustrating a communication protocol determination process according to one embodiment of the present invention;
[0018] Figure 5 is a flow chart illustrating a process of generating a communication protocol preset according to one embodiment of the present invention;
[0019] Figure 6 The figure shows a parallel data stream processing process according to an embodiment of the present invention. DETAILED DESCRIPTION
[0020] Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. The terms or words used in this specification and claims should not be interpreted as limited to the usual or dictionary meanings, but should be interpreted as having meanings and concepts consistent with the technical ideas of the present invention, based on the principle that the inventor can be his / her own lexicon compiler to appropriately define the concept of the term, so as to explain his / her invention in the best way. The embodiments described in this specification and the configurations shown in the accompanying drawings are only some embodiments of the present invention and do not represent all technical ideas, aspects and features of the present invention. Therefore, it should be understood that when filing this application, there may be various equivalents and modifications to replace or modify the embodiments described herein. It will also be understood that the terms "include", "including", "comprises" and / or "comprising" when used in this specification specify the presence of stated features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof. In addition, when describing embodiments of the present invention, the use of "may" refers to "one or more embodiments of the present invention"
[0021] In the drawings, the sizes of various elements, layers, etc. may be exaggerated for clarity of illustration. The same reference numerals denote the same elements.
[0022] Reference to two compared elements, features, etc. as being "the same" may mean that they are "substantially the same." Thus, the phrase "substantially the same" may include situations with what is considered in the art to be low deviations, e.g., 5% or less. In addition, when a parameter is referred to as being uniform in a given area, this may mean that it is uniform with respect to an average value.
[0023] It should be understood that although the terms first, second, third, etc. can be used to describe various elements, components, regions, layers and / or parts here, these elements, components, regions, layers and / or parts should not be limited by these terms. These terms are used to distinguish an element, component, region, layer or part from another element, component, region, layer or part. Therefore, without departing from the teaching of the exemplary embodiment, the first element, component, region, layer or part discussed below can be referred to as a second element, component, region, layer or part.
[0024] Throughout the specification, unless otherwise specified, each element may be in the singular or in the plural.
[0025] When any element is referred to as being disposed (or positioned or placed) "above" (or "below") or "on" (or "under") a component, this may mean that the arbitrary element is placed in contact with the upper (or lower) surface of the component, and may also mean that another component may be inserted between the component and any element disposed (or positioned or placed) above (or under) the component.
[0026] Furthermore, it should be understood that when an element is referred to as being "coupled," "linked," or "connected" to another element, the elements may be directly "coupled," "linked," or "connected" to each other, or there may be an intermediate element between them through which the element may be "coupled," "linked," or "connected" to another element. Furthermore, when a part is referred to as being "electrically coupled" to another part, the part may be directly connected to the other part, or there may be an intermediate part between them so that the part and the other part are indirectly connected to each other.
[0027] Throughout the specification, unless otherwise specified, when "A and / or B" is stated, it means A, B, or A and B. That is, "and / or" includes any or all combinations of the listed multiple items. Unless otherwise specified, when "C to D" is stated, it means C or more and D or less.
[0028] Figure 1 is a block diagram of a battery module communication processing device according to an embodiment of the present invention.
[0029] Reference Figure 1 , a battery module communication processing device 100 according to an embodiment of the present invention may include a connector 110 and a processor 120 .
[0030] The battery module communication processing device 100 can be implemented by a terminal, a computer system, a server, etc.
[0031] The connector 110 may be physically connected to a communication port of the battery module 10 .
[0032] The battery pack may include at least one battery module 10 .
[0033] The battery module 10 may include a plurality of battery cells and a module housing.
[0034] The battery cells may be stacked and housed in a module housing. The battery cells may be provided with cathode leads and anode leads. Depending on the shape of the battery, the battery cells may be round, prismatic or pouch-type battery cells.
[0035] The connector 110 may transmit the number of pins connected to the battery module 10 to the processor 120 .
[0036] The connector 110 may transmit data of the battery module 10 to the processor 120 through a communication port of the battery module 10 .
[0037] The size, type, or shape of the connector 110 is not particularly limited as long as the connector 110 can be connected to the communication port of the battery module 10 .
[0038] A plurality of connectors 110 may be provided. In this case, each connector 110 may be connected to the battery module 10 one-to-one.
[0039] In this embodiment, one connector 110 is connected to one battery module 10 as an example.
[0040] The external device 20 may be connected to the battery module communication processing device 100 through various communication networks to communicate with the battery module 10 through the battery module communication processing device 100 .
[0041] The communication network may adopt 3GPP (3rd Generation Partnership Project), LTE (Long Term Evolution), 5G (5G), WIMAX (Worldwide Interoperability for Microwave Access), wired or wireless Internet, LAN (Local Area Network), wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area Network), Bluetooth, Wi-Fi (Wireless Fidelity), etc., but are not limited to these.
[0042] The external device 20 may control the battery module 10 through the battery module communication processing apparatus 100. The external device 20 may be a central processing unit, a battery management system (BMS) or an energy storage system (ESS), and various application devices, but is not limited thereto.
[0043] The external device 20 may exist in the form of a cloud server, and may have various structures capable of controlling the battery module communication processing device 100. Therefore, the battery module communication processing device 100 may be compatible with a cloud environment to be able to improve utilization of energy storage capacity.
[0044] When the connector 110 is connected to the communication port, the processor 120 may recognize the number of pins of the connector 110 connected to the communication port, and may receive data of the battery module 10 through the connector 110 .
[0045] Based on the number of pins of the identified connector 110 and the data of the battery module 10 , the processor 120 may determine a communication protocol of the battery module 10 .
[0046] The processor 120 may establish communication of the battery module 10 according to the communication protocol to allow communication to be performed between the battery module 10 and the external device 20. In this case, the processor 120 may determine whether the communication protocol is a pre-registered communication protocol. If the communication protocol is a pre-registered communication protocol, the processor 120 may establish communication according to the communication protocol. If the communication protocol is not a pre-registered communication protocol, the processor 120 may establish a new communication protocol preset using the communication protocol and the data format to establish communication.
[0047] The pre-registered communication protocol may be a communication protocol between the battery module 10 and the external device 20. The pre-registered communication protocol may be set according to the manufacturer of the electric vehicle, the manufacturer of the battery module 10, etc. By pre-storing the communication protocol of each electric vehicle manufacturer or each battery module manufacturer, the processor 120 may determine whether the extracted communication protocol is a pre-registered communication protocol.
[0048] The processor 120 may manage the battery module 10 and the communication protocol using the directory as a data structure.
[0049] The module directory for managing the battery modules 10 may store item information of the battery modules 10. For example, the module directory may store a unique identifier, a communication protocol used, a communication rate, and a data format for each battery module 10. The information stored in the module directory is not particularly limited.
[0050] The communication protocol directory for managing communication protocols may store information about the communication protocol of the battery module 10. For example, the communication protocol directory may store information about the communication protocol for converting and interpreting data of the battery module 10. The information stored in the communication protocol directory is not particularly limited.
[0051] When the battery module 10 is connected to the processor 120 through the connector 110, the processor 120 may determine the communication protocol and add a new item to the module directory.
[0052] When the battery module 10 is disconnected from the connector 110 , the processor 120 may delete the corresponding entry from the module directory.
[0053] When collecting data from the battery module 10 , the processor 120 may convert the data according to a communication protocol and transmit it to the external device 20 .
[0054] The processor 120 can use multiple parallel streams to simultaneously process data of multiple battery modules 10. As a result, data of many battery modules 10 can be processed in real time. This parallel processing method can support communication with many battery modules 10 at the same time.
[0055] Therefore, according to this embodiment, it is easy to add or delete data on the battery module 10 using different communication protocols, and it is easy to increase or reduce the battery modules 10.
[0056] The processor 120 may be connected to a memory (not shown) that may store instructions for performing operations, steps, etc. according to embodiments of the present invention. Here, the memory may include a magnetic storage medium or a flash memory medium, in addition to a volatile storage device that requires power to maintain stored information, but is not limited thereto.
[0057] In addition, the processor 120 can be configured to perform different functions divided at the hardware, software or logic level. In this case, dedicated hardware can be used to perform each function. To this end, the processor 120 can be implemented by or include at least one of an application specific integrated circuit (ASIC), a digital signal processor (DSP), a programmable logic device (PLD), a field programmable gate array (FPGA), a central processing unit (CPU), a microcontroller and / or a microprocessor.
[0058] The processor 120 may be implemented by a central processing unit (CPU) or a system on chip (SoC), and may run an operating system or an application to control a plurality of hardware or software components connected to the processor 120, and may perform various data processing and calculations. The processor 120 may be configured to execute at least one instruction stored in a memory, and store data generated by the execution in the memory.
[0059] Figure 2 is a flowchart illustrating a battery module communication processing method according to an embodiment of the present invention.
[0060] Reference Figure 2 When the communication port of the battery module 10 is connected to the connector 110 , data of the battery module 10 is transmitted to the processor 120 through the connector 110 .
[0061] The processor 120 may identify the number of pins of the connector 110 connected to the communication port. In addition, the processor 120 may receive data of the battery module 10 through the connector 110 (S100).
[0062] The processor 120 may analyze the number and data of the pins of the identified connector 110 to extract the communication protocol of the battery module 10 based on the machine learning model (S200). The machine learning model will be described below.
[0063] The processor 120 may determine whether the communication protocol is a pre-registered communication protocol (S300).
[0064] As a result of the determination in step S300 , when it is determined that the communication protocol is a pre-registered communication protocol, the processor 120 may establish communication according to the communication protocol ( S500 ) to allow communication to be performed between the battery module 10 and the external device 20 .
[0065] As a result of the determination in step S300, when it is determined that the communication protocol is not a pre-registered communication protocol, the processor 120 may analyze the rules and data format of the extracted communication protocol to generate a new communication protocol preset (S400).
[0066] The processor 120 establishes communication according to a preset new communication protocol to allow communication to be performed between the battery module 10 and the external device 20 ( S500 ).
[0067] Next, the battery module communication processing method will be described in more detail.
[0068] Figure 3 A training processor for a machine learning model according to one embodiment of the present invention is shown.
[0069] refer to Figure 3 , the machine learning model can be a random forest model.
[0070] Random forest is an ensemble learning method that trains multiple decision trees and combines the predictions of the decision trees to reach a final conclusion. Each decision tree is trained on a subset of the data, eliminating the problem of overfitting.
[0071] The training process of the random forest model is as follows.
[0072] The random forest model can preprocess the collected data to fit the random forest model and can perform feature selection. During this process, the random forest model can select important variables or remove unnecessary variables to improve model performance.
[0073] The random forest model can divide the data into training dataset, validation dataset and test dataset.
[0074] The random forest model can be trained using the training dataset. Here, hyperparameters such as the maximum depth of the data tree can be set.
[0075] Specifically, the random forest model first performs bootstrap sampling.
[0076] While training each decision tree, the Random Forest model can draw bootstrap samples from the training data. Bootstrap samples are datasets generated through sampling that create an exact representation of the original data.
[0077] The random forest model can generate decision trees. The decision tree is trained based on the bootstrap sample, and at each node, some features are randomly selected to determine the best split. This configuration can prevent overfitting while increasing the diversity of the model.
[0078] The random forest model can combine the predictions of decision trees. When making predictions on the test data, the random forest model can produce the final result by combining the predictions of all the trained decision trees.
[0079] The random forest model can use the average of the predicted values for regression problems, and can use a voting method to select the most frequently predicted class as the final result for classification problems.
[0080] Through this process, the random forest model can achieve better performance and generalization ability than a single decision tree, and can improve robustness to noise and outliers.
[0081] Next, the communication protocol determination process will be described.
[0082] Figure 4 is a flow chart illustrating a communication protocol determination process according to one embodiment of the present invention;
[0083] Reference Figure 4 When the connector 110 is connected to the communication port of the battery module 10, the data flow is started, and the processor 120 can collect data packets within a set time period. An example of the collected data flow is as follows.
[0084] 0x7E 0x81 0xA2 0x7E 0x20 0x30 0x7E
[0085] The processor 120 may pre-process the collected data ( S210 ).
[0086] In this case, the processor 120 may divide the collected data into a set number of bits based on the communication protocol. The set number of bits may be 8 bits, 16 bits, or 32 bits, but is not limited thereto.
[0087] The processor 120 may identify the start, middle, and end identifiers of each packet. For example, the processor 120 may identify the start of a frame, the end of a frame, and the like.
[0088] The processor 120 may classify the packet using at least one of the bit pattern, the bit length, and the payload.
[0089] An example of packet classification of the above data stream is as follows.
[0090] Group 1: 0x7E 0x81 0xA2 0x7E
[0091] Group 2: 0x20 0x30 0x7E
[0092] Next, the processor 120 may extract features ( S220 ).
[0093] In this case, the processor 120 may set the bit length, header, payload, and cyclic redundancy check (CRC) of each packet as features. In addition, the processor 120 may further extract a timestamp and an inter-packet interval. These features are not limited to the above-described embodiments.
[0094] The results of feature extraction are as follows.
[0095] Packet 1: Length = 4, Header = 0x7E, Payload = 0x81 0xA2, CRC = 0x7E
[0096] Packet 2: Length = 3, Header = 0x20, Payload = 0x30, CRC = 0x7E
[0097] The processor 120 may apply the features of the grouping to a machine learning model to classify the communication protocol (S230).
[0098] That is, the processor 120 can train the learning model by marking the communication protocol to be classified (supervised learning) and applying the features as input values to the machine learning model. In addition, the processor 120 can apply the trained model to the data in real time to classify the communication protocol.
[0099] The results of classifying the communication protocols are as follows.
[0100] Group 1: Protocol A
[0101] Group 2: Protocol B
[0102] Next, the process of generating a communication protocol preset will be described.
[0103] Figure 5 is a flow chart illustrating a process of generating a communication protocol preset according to one embodiment of the present invention.
[0104] Reference Figure 5 , the processor 120 may analyze the collected packets to determine the existing structure (S410). For example, the processor 120 may determine the header, payload, and CRC of each packet.
[0105] The processor 120 may detect a pattern of each group, that is, a repetitive element in each group (S420).
[0106] The processor 120 may extract characteristic information from each packet (S430). The characteristic information of each packet may include packet length, a bit pattern between a header and a payload, and an end byte. The characteristics of the packet are not particularly limited.
[0107] Based on the extracted characteristic information of the packet, the processor 120 may classify which communication protocol the packet belongs to (S440). In this case, the processor 120 may use a machine learning model or a rule-based system.
[0108] The processor 120 may generate a communication protocol preset for the communication protocol based on the packet classification result (S450).
[0109] The communication protocol presets may include header information, payload length, use of CRC, and communication timing, but are not limited thereto.
[0110] On the other hand, the processor 120 can receive data from each of the plurality of battery modules 10 and input the data into the machine learning model to perform parallel data stream processing to determine the communication protocol in real time and send the communication protocol to the external device 20. This will refer to Figure 6 Give a description.
[0111] Figure 6 The figure shows a parallel data stream processing process according to an embodiment of the present invention.
[0112] Reference Figure 6 , when the connector 110 is connected to the communication port of each of the battery modules 10 , the processor 120 may collect data from each of the battery modules 10 .
[0113] The processor 120 may convert the data into tasks to be processed, and insert the converted data into a task queue that can be processed in parallel ( S510 ).
[0114] The processor 120 may identify a communication protocol by inputting the data inserted into the task queue into a machine learning model (S520).
[0115] The processor 120 may convert the format of the data according to the identified communication protocol (S530), and merge the converted data into a single unified data stream (S540).
[0116] The processor 120 may transmit the merged data stream to the external device 20 (S550).
[0117] In this way, according to an embodiment of the present invention, the battery module communication processing device 100 can promote the recycling of the battery module 10 while reducing complexity by improving the compatibility between various communication protocols used by the battery module 10.
[0118] In addition, according to the embodiment of the present invention, the battery module communication processing device 100 can flexibly change the number of battery modules 10 according to user needs, thereby improving the utilization of the battery modules 10 .
[0119] Furthermore, according to an embodiment of the present invention, the battery module communication processing device 100 is compatible with a cloud environment to allow improved utilization of energy storage capacity.
[0120] Although the present invention has been described with reference to some embodiments and drawings showing aspects thereof, the present invention is not limited thereto. Those skilled in the art to which the present invention pertains may make various modifications and changes within the technical spirit of the present invention and the scope of the claims and their equivalents.
Claims
1. A battery module communication processing device, comprising: a connector connected to a communication port of the battery module; and A processor establishes communication of the battery module by determining a communication protocol of the battery module using the number of pins of the connector connected to the communication port and data of the battery module transmitted through the connector.
2. The battery module communication processing device according to claim 1, wherein: The processor establishes communication of the battery modules according to whether the communication protocol is a pre-registered communication protocol.
3. The battery module communication processing device according to claim 2, wherein: When it is determined that the communication protocol is a pre-registered communication protocol, the processor converts and transmits data between the battery module and an external device according to the communication protocol.
4. The battery module communication processing device according to claim 2, wherein: When it is determined that the communication protocol is not a pre-registered communication protocol, the processor generates a new communication protocol preset by analyzing a rule of the communication protocol and a format of the data.
5. The battery module communication processing device according to claim 4, wherein: The processor converts and transmits data between the battery module and the external device according to the communication protocol preset.
6. The battery module communication processing device according to claim 4, wherein: The processor extracts characteristic information of the data packets, classifies the packets based on the characteristic information, and generates the communication protocol preset based on the classification results, the characteristic information of each packet including at least one of the length, the bit pattern between the header and the payload, and the end byte thereof.
7. The battery module communication processing device according to claim 4, wherein: The communication protocol preset includes at least one of header information, payload length, use of CRC (Cyclic Redundancy Check), and communication timing.
8. The battery module communication processing device according to claim 2, wherein: The processor applies features of the grouping classified from the data to a machine learning model to determine whether the communication protocol is a pre-registered communication protocol.
9. The battery module communication processing device according to claim 8, wherein: The machine learning model is trained based on the features of the packets as input values, and the features of each packet include at least one of a bit length, a header, a payload, a cyclic redundancy check (CRC), a timestamp, and an interval between packets thereof.
10. The battery module communication processing device according to claim 1, wherein: The processor has a directory for managing the battery modules and a directory for managing the communication protocol of the battery modules, project information of the battery modules is stored in the directory for managing the battery modules, and information about the communication protocol of the battery modules is stored in the directory for managing the communication protocol.
11. The battery module communication processing device according to claim 1, wherein: The processor converts each of the data transmitted from each battery module according to the communication protocol, merges the converted data into a data stream, and transmits the data stream to an external device.
12. A battery module communication processing method, comprising: When a communication port of a battery module is connected to a connector, a processor identifies the number of pins of the connector connected to the communication port, and determines a communication protocol of the battery module using the number of pins of the connector and data of the battery module transmitted through the connector; determining, by the processor, whether the communication protocol is a pre-registered communication protocol; and The processor establishes communication of the battery modules according to whether the communication protocol is a pre-registered communication protocol.
13. The battery module communication processing method according to claim 12, wherein: In establishing the communication of the battery module, when it is determined that the communication protocol is a pre-registered communication protocol, the processor converts and transmits data between the battery module and an external device according to the communication protocol.
14. The battery module communication processing method according to claim 12, wherein: In establishing the communication of the battery module, when it is determined that the communication protocol is not a pre-registered communication protocol, the processor generates a new communication protocol preset by analyzing a rule of the communication protocol and a format of the data.
15. The battery module communication processing method according to claim 14, wherein: In establishing communication of the battery module, the processor converts and transmits data between the battery module and an external device according to the communication protocol preset.
16. The battery module communication processing method according to claim 14, wherein: In establishing the communication of the battery module, the processor extracts characteristic information of the grouping of the data, classifies the grouping based on the characteristic information, and generates the communication protocol preset based on the classification result, The characteristic information of each packet includes at least one of a length, a bit pattern between a header and a payload, and an end byte thereof.
17. The battery module communication processing method according to claim 14, wherein: The communication protocol preset includes at least one of header information, payload length, use of CRC (Cyclic Redundancy Check), and communication timing.
18. The battery module communication processing method according to claim 12, wherein: In determining whether the communication protocol is a pre-registered communication protocol, the processor applies features of the grouping classified from the data to a machine learning model to determine whether the communication protocol is a pre-registered communication protocol.
19. The battery module communication processing method according to claim 18, wherein: The machine learning model is trained based on the features of the packets as input values, and the features of each packet include at least one of a bit length, a header, a payload, a cyclic redundancy check (CRC), a timestamp, and an interval between packets thereof.
20. The battery module communication processing method according to claim 12, wherein: In establishing the communication of the battery modules, the processor converts each of the data transmitted from each battery module according to the communication protocol, merges the converted data into a data stream, and transmits the data stream to an external device.