Method and device for artificial intelligence monitoring and battery efficiency protection

Abstract

The invention discloses a method for monitoring and protecting battery efficiency by artificial intelligence. The method comprises the following steps of: judging whether the temperature and the current of a battery core in a battery pack are within a limit specification or not; obtaining a maximum current power when the temperature and the current of the battery cell are within the limit specifications; and performing an operation on the battery cell according to the maximum current power.

Description

Technical Field

[0001] The present disclosure relates to the field of battery technology, and more particularly to a method and device for artificial intelligence monitoring and protecting battery performance. Background Art

[0002] Today's society has increasingly higher requirements for energy conservation and environmental protection, and optimizing battery energy efficiency is one of the keys to achieving energy conservation and environmental protection. With the continuous advancement of battery technology, the application of battery management system (BMS) is becoming more and more extensive.

[0003] Battery management systems usually have the function of measuring battery voltage to prevent or avoid abnormal conditions such as over-discharge, over-charge, and over-temperature. General battery management systems usually use protection mechanisms such as over-current protection (OCP) and over-temperature protection (OTP) to manage batteries. However, the above protection mechanisms all use fixed thresholds to protect the battery from current and over-temperature, but cannot optimize the battery energy efficiency.

[0004] Therefore, there is a need for a method and device for artificial intelligence monitoring and protecting battery performance, which can optimize battery energy efficiency, ensure the normal operation of the battery and extend the battery life. Summary of the invention

[0005] The following disclosures are exemplary only and are not intended to be limiting in any way. In addition to the illustrative aspects, embodiments, and features, other aspects, embodiments, and features will also be apparent by reference to the accompanying drawings and the following detailed description. That is, the following disclosures are provided to introduce concepts, key points, benefits, and novel and non-obvious technical advantages described herein. Selected, but not all, embodiments will be further described in detail as follows. Therefore, the following disclosures are not intended to be essential features of the claimed subject matter, nor are they intended to be used in determining the scope of the claimed subject matter.

[0006] Therefore, the main purpose of the present disclosure is to provide a method and device for artificial intelligence monitoring and protecting battery performance, which uses a maximum current power to optimize battery energy efficiency, ensure the normal operation of the battery and extend the life of the battery pack.

[0007] The present disclosure proposes an artificial intelligence method for monitoring and protecting battery performance, including: determining whether a temperature and a current of a battery cell in a battery pack are within a limit specification; when the temperature and the current of the battery cell are within the limit specification, obtaining a maximum current power; and performing an operation according to the maximum current power.

[0008] In some embodiments, the maximum current power is obtained according to a relative state of charge (RSOC) of the battery pack, a voltage, a system impedance value, an optimization parameter, and a battery impedance value.

[0009] In some embodiments, the maximum current power (MCP) is expressed by the following formula:

[0010]

[0011] Wherein B is the above-mentioned remaining capacity percentage, D is the above-mentioned voltage, E is the above-mentioned system impedance value, F is the above-mentioned optimization parameter and G is the above-mentioned battery impedance value.

[0012] In some embodiments, the optimization parameters are generated by a large language model or a large data model.

[0013] In some embodiments, the step of determining whether the temperature and the current of the battery cell are within the limit specifications also includes determining whether the temperature of the battery cell is within an operating temperature range, whether the current has not reached an over current protection (OCP) operating limit and has not reached a short circuit protection operating limit.

[0014] In some embodiments, the step of performing the above operation according to the above maximum current power also includes: when an indicator corresponding to the above maximum current power is lower than a threshold, sending a notification message to a processor to notify the above processor of a power condition that the above battery cell can currently support.

[0015] In some embodiments, the method further includes: when the temperature and the current of the battery cell are not within the limit specifications, performing a protection operation on the battery cell.

[0016] The present disclosure proposes an artificial intelligence monitoring and protection device for battery performance, comprising: a battery pack, including: a battery cell; and a controller; wherein the controller performs: determining whether a temperature and a current of the battery cell are within a limit specification; when the temperature and the current of the battery cell are within the limit specification, obtaining a maximum current power; and performing an operation according to the maximum current power. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of a system for artificial intelligence monitoring and protecting battery performance according to an embodiment of the present disclosure.

[0018] Figure 2 The figure shows the internal structure of a battery pack according to an embodiment of the present disclosure.

[0019] Figure 3 The present invention is a flowchart of a method for artificial intelligence monitoring and protecting battery performance according to an embodiment of the present invention.

[0020] Figure 4 The table shows experimental data of obtaining maximum current power and status indicators according to an embodiment of the present disclosure.

[0021] Figure 5 It is a schematic diagram showing the discharge of a battery pack according to an embodiment of the present disclosure.

[0022] Figure 6 The diagram is a schematic diagram showing the relationship between the maximum current power (MCP) and the remaining capacity percentage (RSOC) according to an embodiment of the present disclosure.

[0023] Figure 7 It is a schematic diagram showing the relationship between the maximum current power (MCP) and time according to an embodiment of the present disclosure.

[0024]

Explanation of symbols

[0025] 100: System

[0026] 110: Power supply

[0027] 120: Power selector

[0028] 130: Main power supply unit

[0029] 140:Battery Charger

[0030] 150:Battery pack

[0031] 160: Processor

[0032] 170: Power Management Unit

[0033] 180 warning device

[0034] 210:Battery cell

[0035] 220: Controller

[0036] 230: Secondary protection IC

[0037] 240: Thermal resistor

[0038] 250: Inductive resistor

[0039] 260: Self-cut protector

[0040] 272: Thermal fuse

[0041] 274:Discharge Field Effect Transistor

[0042] 276: Charging Field Effect Transistor

[0043] 280: Positive terminal

[0044] 282: Negative terminal

[0045] 284: Data line

[0046] 286: Clock line

[0047] 300: Methods

[0048] S305, S310, S315, S320: Steps DETAILED DESCRIPTION

[0049] In the following, various aspects of the present disclosure will be described more fully with reference to the accompanying drawings. However, the present disclosure can be embodied in many different forms and should not be construed as being limited to any specific structure or function presented throughout the present disclosure. On the contrary, providing these aspects will make the present disclosure comprehensive and complete, and the present disclosure will fully convey the scope of the present disclosure to those skilled in the art. Based on the content taught herein, those skilled in the art will appreciate that, whether it is implemented alone or in combination with any other aspect of the present disclosure, any aspect disclosed herein is implemented, and the scope of the present disclosure is intended to cover any aspect disclosed herein. For example, any number of devices or execution methods proposed herein can be used to implement. In addition, in addition to the multiple aspects of the present disclosure proposed herein, the scope of the present disclosure is more intended to cover devices or methods implemented using other structures, functions, or structures and functions. It should be understood that any aspect disclosed herein can be embodied by one or more elements of the claims.

[0050] The word "exemplary" is used herein to mean "serving as an example, instance, or illustration." Any aspect of the disclosure or design described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other aspects of the disclosure or design. In addition, like numbers refer to like elements throughout the several figures, and the articles "a," "an," and "above" include plural references unless otherwise specified in the description.

[0051] It is understood that when an element is referred to as being "connected" or "coupled" to another element, the element may be directly connected or coupled to the other element or there may be an intermediate element. Conversely, when the element is referred to as being "directly connected" or "directly coupled" to another element, there are no intermediate elements. Other words used to describe the relationship between elements should be interpreted in a similar manner (e.g., "between" versus "directly between," "adjacent" versus "directly adjacent," etc.).

[0052] The disclosed embodiments provide a method and device for artificial intelligence monitoring and protecting battery performance, which uses a maximum current power to optimize battery energy efficiency, ensure the normal operation of the battery, and extend the life of the battery pack.

[0053] Figure 1 FIG. 1 is a schematic diagram of a system 100 for monitoring and protecting battery performance using artificial intelligence according to an embodiment of the present disclosure. The system 100 includes a power supply 110 , a power selector 120 , a main power device 130 , a battery charger 140 , a battery pack 150 , a processor 160 , a power management unit 170 , and an alarm device 180 .

[0054] The power supply 110 may be an adapter or a Universal Serial Bus (USB). The power selector 120 is coupled to the power supply 110, the main power device 130, and the battery charger 140. The power selector 120 selects the DC / AC as the main power source when there is DC / AC. Otherwise, the power selector 120 selects the battery as the power source.

[0055] The main power supply device 130 can be a system end, for example, any type of device such as 3C products, notebook computers, tablet computers, robots, and car batteries. The battery charger 140 is coupled to the power selector 120 and the battery pack 150, and has a charge / discharge circuit. The battery pack 150 can include multiple combinations of battery packs, for example, single series, multiple series, single parallel, multiple parallel, and other combinations.

[0056] The processor 160 is coupled to the battery pack 150, the power management unit 170, and the warning device 180. The processor 160 may be any processor suitable for executing instructions, such as instructions from a memory (not shown). Accordingly, the processor 160 may be, for example, a central processing unit (CPU), a microprocessor, or other similar processors.

[0057] The power management unit 170 is coupled to the main power device 130 and the processor 160 , and can provide basic power protection for the system 100 .

[0058] The warning device 180 may be a display, an LED or other output element with a warning function.

[0059] Figure 2The figure shows the internal structure of the battery pack 150 according to an embodiment of the present disclosure. The battery pack 150 may include, but is not limited to, a battery cell 210, a controller 220, a secondary protection IC 230, a thermal resistor 240, a sensing resistor 250, a self-cutoff protector 260, a thermal fuse 272, a discharge field-effect transistor (FET) 274, and a charge field-effect transistor 276.

[0060] The controller 220 may be a general purpose processor, a microcontroller unit (MCU), an application processor, etc. It includes various circuits for providing data processing and computing functions, and controls the battery cell 210 to communicate with the battery cell 210. Figure 1 The microprocessor 160 and the battery charger 140 communicate with each other.

[0061] The controller 220 is coupled to the battery cell 210, the secondary protection IC 230, the thermal resistor 240, and the sensing resistor 250. The controller 220 can support a wide range of first-level and second-level battery safety features. The first-level safety features include: cell-level overvoltage / undervoltage protection, charge and discharge overcurrent protection, short circuit protection, and over-temperature protection. The second-level safety features are used to indicate more serious faults and may cause the series fuse (e.g., thermal fuse 272) to blow, thereby permanently disabling the battery cell 210. The second-level safety features include: safety overvoltage, battery imbalance, safety overcurrent, safety overtemperature, thermistor 240 open circuit, charging FET 274 and discharge FET 276 failure, fuse blown fault detection, etc.

[0062] In addition, the controller 220 can also trigger the self-cut protector 260 coupled to the battery cell 210 with the secondary protection IC 230 to start the protection mechanism of the battery cell 210. The controller 220 can obtain the temperature 242 of the battery cell 210 through the thermal resistor 240, and obtain the current of the battery cell 210 through the sensing resistor 250. The controller 220 can track the capacity change, battery impedance, voltage, current, temperature and other key operating parameters of the battery cell 210 in real time, and obtain a maximum current power. In one embodiment, the controller 220 can generate certain control signals according to the maximum current power to start appropriate safety precautions for the battery cell 210.

[0063] exist Figure 2 In the embodiment, the battery pack 150 has a positive terminal 280 and a negative terminal 282 to be connected to the battery charger 140 for charging. The controller 220 uses the Smart Battery Bus (SMBus) protocol to communicate with the battery charger 140. Figure 1communicates with the central processor 160. The SMBus consists of a data line (SMD) 284 and a clock line (SMC) 286, and the processor 160 communicates with each other through the data line 284 and the clock line 286.

[0064] In another embodiment, the battery pack 150 may include a memory (not shown in the figure), which can store instructions associated with the operation of the battery pack 150, and the above instructions are executed by the controller 220. The controller 220 can also execute programs and instructions in the memory to present the actions and steps described in the embodiments of the present disclosure, or other descriptions in the specification.

[0065] In yet another embodiment, the controller 220 can implement a large language model (LLM) or a big data model based on a neural network, and use the above large language model or big data model to generate relevant parameters in the battery pack.

[0066] It should be noted that although the number of battery cells 210 is exemplified by a single battery in Figure 2 the battery cells can be expanded into other combinations (such as two in series, two in series and one in parallel, etc.), so the present disclosure is not limited to Figure 2 the embodiments shown.

[0067] Figure 3 is a flowchart of a method 300 for artificial intelligence monitoring and protecting battery performance according to an embodiment of the present disclosure. This method 300 is executed by the controller 220 of the battery pack 150 as shown in Figure 2 the figure.

[0068] In step S305, the controller determines whether the temperature and current of a battery cell in a battery pack are within a limit specification. More specifically, the controller can determine whether the temperature of the battery cell is within an operating temperature range, whether the current does not reach an over current protection (OCP) operating limit and does not reach a short circuit protection operating limit.

[0069] When the temperature and the current of the battery cell are within the limit specifications (“Yes” in step S305), in step S310, the controller obtains a maximum current power (MCP), wherein the maximum current power is obtained according to a residual capacity percentage (Relative State Of Charge, RSOC) of the battery cell, a voltage, a system impedance value, an optimization parameter and a battery impedance value. In more detail, the system impedance value is the impedance value of the system 100, and the battery impedance value is the impedance value of the battery cell 210. The optimization parameter is a value generated by the controller using a large language model or a large data model, wherein the value is mainly to make the relationship between the maximum current power and the residual capacity percentage close to a preset curve. For example, this optimization parameter can make the relationship between the maximum current power and the residual capacity percentage close to a 45-degree curve, such as Figure 6 As shown. The maximum current power can be expressed by the following formula:

[0070]

[0071] Wherein B is the above-mentioned remaining capacity percentage, D is the above-mentioned voltage, E is the above-mentioned system impedance value, F is the above-mentioned optimization parameter and G is the above-mentioned battery impedance value.

[0072] In step S315, the controller performs an operation according to the above-mentioned maximum current power. In one embodiment, the value of the maximum current power can display the current energy consumption power state of the battery pack through a status indicator. The status indicator can be represented by a value of 0-5, 1-10 or other values. The higher the value, the better the power state that the battery cell can support. The lower the value, the worse the power state that the battery cell can support. For example, the status indicator is represented by a value of 1-10. A status indicator of 0 indicates that the power state that the battery cell can support is very low, and a status indicator of 9 or 10 indicates that the power state that the battery cell can support is very good and can be operated under heavy load.

[0073] When the status indicator is lower than a threshold, the controller may send a notification message to a processor or a user to inform the processor of the power condition that the battery cell can currently support. For another example, when the status indicator is lower than a threshold 3, the controller may send a notification message to a processor or a user to inform the processor that the power condition that the battery cell can currently support is not good. After receiving the notification message, the processor may extend the battery cell usage time by adjusting the load to improve system energy efficiency.

[0074] Return to step S305. When the temperature and current of the above battery cell are not within the above limit specifications (the "No" in step S305), in step S320, the controller performs a protection operation on the above battery cell. For example, when the controller determines that the temperature of the battery pack is not within an operating temperature range or the current has reached one of the overcurrent protection operation limit and the short-circuit protection operation limit, the controller stops using the above battery cell.

[0075] Figure 4 It shows the experimental data table 400 for obtaining the maximum current power and status indicators according to an embodiment of the present disclosure. In Figure 4 the battery pack adopts a combination of two series and one parallel, and the normal current is 3.5 amperes. The status indicators are divided into 0 to 5 values according to the maximum current power.

[0076] As shown in Table 400, the battery impedance value is related to the operating cycle. The more operating cycles, the higher the battery impedance value. And the maximum current power (MCP) is related to the remaining capacity percentage (RSOC), the battery pack voltage, the system impedance value, the optimization parameters, and the battery impedance value. In other words, the maximum current power is an estimated value that is not a fixed value, which can estimate how much electrical energy the battery cell can provide currently, and the maximum current power will change with differences in the number of uses, aging conditions, capacity, etc. of the battery pack.

[0077] Figure 5 It shows a schematic diagram of the battery pack discharging according to an embodiment of the present disclosure, and refer to Figure 4 .

[0078] The battery pack operates by combining a 7-ampere current discharge for 10 seconds and a 14-ampere current discharge for 10 milliseconds. As shown in the figure, the operating current does not exceed the overcurrent protection (OCP) operation limit (using 8.75 amperes for continuous discharge for 5 to 8 seconds) and the short-circuit protection operation limit (using 17.5 amperes for discharge for more than 3 milliseconds). Discharging with this current combination, the relationship between the maximum current power (MCP) and the remaining capacity percentage (RSOC) can be as Figure 6 shown, and the relationship between the maximum current power (MCP) and time can be as Figure 7 shown. It should be noted that in Figure 6 and Figure 7 the maximum current power is plotted as a negative value (-) for discharging.

[0079] From Figure 6 it can be seen that during the discharging process, the operating trend of the maximum current power not only has no unexpected peaks, but also conforms to a 45-degree curve and finally returns to zero. And in Figure 7 the curve of the maximum current power of the battery pack also has no peak during the discharging process and returns to zero after about 300 minutes.

[0080] As described above, the method and device for artificial intelligence monitoring and protecting battery performance disclosed in the present invention use the maximum current power to determine the current power state of the battery, which can optimize the interaction between the battery and the load to ensure the stability and efficiency of the battery power supply and improve the energy utilization of the battery.

[0081] The data structures and program codes described in this specific embodiment are generally stored on a computer-readable storage medium, which can be any device or medium that can store program codes and / or data for use by a computer system. Computer-readable storage media include, but are not limited to, volatile memory, non-volatile memory, magnetic and optical storage devices, such as disk drives, tapes, CDs (compact disks), DVDs (digital versatile disks), or other media capable of storing computer-readable media now known or later developed.

[0082] The methods and processes described in the detailed description may be embodied as program code and / or data, which may be stored in a computer-readable storage medium as described above. When a computer system reads and executes the program code and / or data stored on a computer-readable storage medium, the computer system executes the methods and processes embodied as data structures and program code and stored in the computer-readable storage medium.

[0083] In addition, the above methods and processes may be included in hardware devices or apparatuses. For example, hardware devices or apparatuses may include, but are not limited to, application specific integrated circuit (ASIC) chips, field programmable gate arrays (FPGAs), dedicated or shared processors that execute specific software programs or program codes at specific times, and other programmable logic devices now known or later developed. When the hardware devices or apparatuses are started, these hardware modules or apparatuses execute the methods and processes included therein.

[0084] Any specific order or hierarchy of steps in the process disclosed herein is purely by way of example. Based on design preferences, it should be understood that any specific order or hierarchy of steps in the process may be rearranged within the scope of this document. The accompanying method claims present elements of various steps in an exemplary order and therefore should not be limited to the specific order or hierarchy shown.

[0085] The use of ordinal numbers such as "first", "second", "third", etc. to modify elements in the claims does not in itself imply any priority, precedence, sequence between elements, or order of steps performed by the method, but is only used as an identifier to distinguish different elements with the same name (with different ordinal numbers).

[0086] Although the present disclosure has been disclosed as above by way of implementation examples, it is not intended to limit the present application. Anyone familiar with this technology may make some changes and modifications without departing from the spirit and scope of the present disclosure. Therefore, the scope of protection of the present application shall be determined by the definition of the appended claims.

Claims

1. A method for artificial intelligence monitoring and protecting battery performance, include: Determining whether a temperature and a current of a battery cell in a battery pack are within a limit specification; When the temperature and the current of the battery cell are within the limit specifications, a maximum current power is obtained; and An operation is performed according to the maximum current power.

2. The method for artificial intelligence monitoring and protecting battery performance as described in claim 1, wherein the maximum current power is obtained based on a residual capacity percentage (Relative State Of Charge, RSOC) of the battery pack, a voltage, a system impedance value, an optimization parameter and a battery impedance value.

3. The method for monitoring and protecting battery performance by artificial intelligence as claimed in claim 2, wherein the maximum current power (MCP) is expressed by the following formula: Wherein B is the above-mentioned remaining capacity percentage, D is the above-mentioned voltage, E is the above-mentioned system impedance value, F is the above-mentioned optimization parameter and G is the above-mentioned battery impedance value.

4. The method for artificial intelligence monitoring and protecting battery performance as described in claim 2, wherein the above-mentioned optimization parameters are generated by a large language model or a large data model.

5. The method for monitoring and protecting battery performance using artificial intelligence as claimed in claim 1, wherein the step of determining whether the temperature and the current of the battery cell are within the limit specifications further comprises: include: It is determined whether the temperature of the battery cell is within an operating temperature range and whether the current has not reached an over current protection (OCP) operating limit and a short circuit protection operating limit.

6. The method for artificial intelligence monitoring and protecting battery performance as claimed in claim 1, wherein the step of performing the above operation according to the above maximum current power is further include: When an indicator corresponding to the maximum current power is lower than a threshold, a notification message is sent to a processor to notify the processor of a power condition that the battery cell can currently support.

7. The method of artificial intelligence monitoring and protecting battery performance as claimed in claim 1, further comprising: include: When the temperature and the current of the battery cell are not within the limit specifications, a protection operation is performed on the battery cell.

8. An artificial intelligence device for monitoring and protecting battery performance, include: A battery pack comprising: a battery cell; and a controller; The controller executes: Determining whether a temperature and a current of the battery cell are within a limit specification; When the temperature and the current of the battery cell are within the limit specifications, a maximum current power is obtained; and An operation is performed according to the maximum current power.

9. The device for monitoring and protecting battery performance by artificial intelligence as described in claim 8, wherein the maximum current power is obtained based on a residual capacity percentage (Relative State Of Charge, RSOC) of the battery cell, a voltage, a system impedance value, an optimization parameter and a battery impedance value.

10. The artificial intelligence monitoring and battery performance protection device as claimed in claim 9, wherein the maximum current power (MCP) is expressed by the following formula: Wherein B is the above-mentioned remaining capacity percentage, D is the above-mentioned voltage, E is the above-mentioned system impedance value, F is the above-mentioned optimization parameter and G is the above-mentioned battery impedance value.

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