Storage battery pack operation state determination method and system

Abstract

The embodiment of the invention discloses a method and system for determining the operation state of a storage battery pack, the operation state parameter of the storage battery pack is obtained, the operation state of the storage battery pack is determined according to the state value corresponding to the operation state parameter, manual operation state detection is not needed, the detection efficiency of the operation state of the storage battery pack can be improved, and the detection efficiency is improved. And errors caused by manual detection can be avoided. The operation state of the storage battery pack is determined according to the state value related to the operation state of the storage battery pack, so that the accuracy of the determined operation state of the storage battery pack is ensured. According to the technical scheme, not only can the current operation state be determined, but also the operation state of the future prediction time period can be determined, under the condition that the current operation state is determined to be the fault state or the fault state can occur in the future prediction time period, the storage battery pack is maintained in time, the service life of the storage battery pack is prolonged, and the maintenance efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of battery health status detection, and in particular to a method and system for determining the operating status of a battery pack. Background Art

[0002] The battery pack is an independent and reliable power source. Due to its stability, low cost and excellent performance, it plays a particularly important role in the normal operation of the substation.

[0003] At present, the battery pack discharge test is mainly carried out manually to detect the operating status of the battery. However, this method has the problems of large amount of operation and long time consumption. The current maintenance work lacks more convenient and advanced monitoring methods, resulting in the inability to more accurately monitor the real-time status of the battery, and it is also impossible to eliminate the potential safety hazards.

[0004] Therefore, how to improve the efficiency and accuracy of battery pack operating status detection has become an urgent problem to be solved. Summary of the invention

[0005] The present invention provides a method and system for determining the operating state of a battery pack, so as to improve the efficiency and accuracy of detecting the operating state of the battery pack, thereby maintaining the battery pack and extending the service life of the battery pack.

[0006] According to one aspect of the present invention, a method for determining an operating state of a battery pack is provided, comprising:

[0007] Acquiring operating state parameters of the battery pack, the operating state parameters including at least one of the current capacity, current charge and discharge times, internal temperature, internal gas content, and deformation of the battery pack;

[0008] Determine the corresponding state value according to the operating state parameter and the determination rule corresponding to the operating state parameter;

[0009] The operating state of the battery pack is determined according to the state value, where the operating state includes a current operating state and / or an operating state in a future predicted period.

[0010] Optionally, determining the operating state of the battery pack according to the state value includes:

[0011] When at least one state value exceeds the corresponding preset state value range, determining that the current operating state is a fault state;

[0012] When each state value does not exceed the corresponding preset state value range, it is determined that the current operating state is a normal state.

[0013] Optionally, determining the operating state of the battery pack according to the state value includes:

[0014] The state value and the corresponding current running state, as well as the state values ​​and the corresponding historical running states at multiple moments in a preset historical period are used as samples;

[0015] A neural network model is used to train multiple samples to obtain a state prediction model of the operating state in the future prediction period;

[0016] The operating status of the future prediction period is predicted based on the status prediction model.

[0017] Optionally, the neural network model includes an input layer, an output layer, and one or at least two intermediate layers; the neural network model is used to train multiple samples to obtain a state prediction model of the operating state in the future prediction period, including:

[0018] In the process of training multiple samples using a neural network model, the number of neurons in the middle layer is adjusted to reduce the error, so as to obtain a state prediction model of the operating state in the future prediction period.

[0019] Optionally, in the process of training multiple samples using a neural network model, the number of neurons in the middle layer is adjusted to reduce the error, so as to obtain a state prediction model of the operating state in the future prediction period, including:

[0020] In the process of training multiple samples using a neural network model, the number of neurons in the middle layer is adjusted, and the number of neurons with the smallest error is determined as the final number of neurons corresponding to the middle layer, so as to obtain a state prediction model for the operating state of the future prediction period.

[0021] Optionally, in the process of training multiple samples using a neural network model, the number of neurons in the middle layer is adjusted to reduce the error, so as to obtain a state prediction model of the operating state in the future prediction period, including:

[0022] Adjust the number of neurons in the middle layer according to the following formula:

[0023] y=(n+m) 1 / 2 +k·b;

[0024] Among them, y is the number of neurons in the middle layer, n and m are the number of neurons in the output layer and input layer respectively, b is a constant value, and k is a variable weight.

[0025] Optionally, determining a corresponding state value according to the running state parameter and a determination rule corresponding to the running state parameter includes:

[0026] Determining a first state value according to a ratio of a current capacity to a factory capacity of the battery pack, wherein the test temperatures of the current capacity and the factory capacity are the same;

[0027] The current charge and discharge times include the current cumulative charge times and the current cumulative discharge times; the second state value is determined according to the ratio of the sum of the current cumulative charge times and the current cumulative discharge times to the rated charge and discharge times;

[0028] Determine a third state value according to a ratio of a difference between a change in oxygen content and a change in hydrogen in a first set period before the current moment to a change in oxygen content;

[0029] Determine a fourth state value according to the change amount of the internal temperature within a second set period before the current moment;

[0030] The fifth state value is determined according to the ratio of the deformation amount of the battery pack at the current moment to the factory size of the battery pack.

[0031] According to another aspect of the present invention, there is provided a system for determining the operating state of a battery pack, comprising: an operating state parameter acquisition module and a processing module;

[0032] The operating state parameter acquisition module is connected to the processing module and is used to acquire the operating state parameters of the battery pack, the operating state parameters including at least one of the current capacity of the battery pack, the current charge and discharge times, the internal temperature, the internal gas content, and the deformation amount;

[0033] The processing module is used to determine the corresponding state value according to the operating state parameters obtained from the operating state parameter acquisition module and the determination rules corresponding to the operating state parameters; determine the operating state of the battery pack according to the state value, and the operating state includes the current operating state and / or the operating state of the future predicted period.

[0034] Optionally, the operating status parameter acquisition module includes at least one of a current capacity acquisition unit, a charge and discharge times acquisition unit, a gas content acquisition unit, an internal temperature acquisition unit, and a deformation acquisition unit; the current capacity acquisition unit, the charge and discharge times acquisition unit, the gas content acquisition unit, the internal temperature acquisition unit, and the deformation acquisition unit are respectively connected to the processing module; the current capacity acquisition unit is used to acquire the current capacity of the battery pack; the charge and discharge times acquisition unit is used to acquire the current charge and discharge times of the battery pack; the gas content acquisition unit is used to acquire the oxygen content and hydrogen content inside the battery pack; the internal temperature acquisition unit is used to acquire the temperature inside the battery pack; and the deformation acquisition unit is used to acquire the current size of the battery pack.

[0035] Optionally, it also includes at least one of a communication module, an alarm module and an input module; the communication module, the alarm module and the input module are respectively connected to the processing module, and the processing module is used to send a prompt message through the communication module when it is determined that the operating state includes a fault state, or send an alarm message through the alarm module; the input module is used to receive a preset state value range corresponding to the state value, and the processing module is used to determine that the current operating state is a fault state when at least one state value exceeds the corresponding preset state value range; when all state values ​​do not exceed the corresponding preset state value range, determine that the current operating state is a normal state.

[0036] The method and system for determining the operating state of a battery pack according to the embodiment of the present invention obtains the operating state parameters of the battery pack, determines the corresponding state value according to the operating state parameters and the determination rules corresponding to the operating state parameters, and determines the operating state of the battery pack according to the state value. The operating state includes the current operating state and / or the operating state of the future prediction period. There is no need to manually detect the operating state, which can improve the detection efficiency of the operating state of the battery pack and avoid errors introduced by manual detection. In addition, by determining the operating state of the battery pack according to the state value related to the operating state of the battery pack, the accuracy of the determined operating state of the battery pack is guaranteed. Moreover, in the embodiment of the present invention, not only the current operating state can be determined, but also the operating state of the future prediction period can be determined. Then, when it is determined that the current operating state is a fault state or a fault state will occur in the future prediction period, the battery pack can be maintained in time to extend the service life of the battery pack and improve the maintenance efficiency.

[0037] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 is a flow chart of a method for determining the operating status of a battery pack provided by an embodiment of the present invention;

[0040] Figure 2 It is a structural schematic diagram of a battery pack operating state determination system provided by an embodiment of the invention;

[0041] Figure 3is a flow chart of another method for determining the operating state of a battery pack provided by an embodiment of the present invention;

[0042] Figure 4 It is a schematic diagram of the neural network structure;

[0043] Figure 5 It is a structural schematic diagram of another battery pack operating status determination system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0045] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention 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 interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0046] Figure 1 The present invention provides a flowchart of a method for determining the operating state of a battery pack provided by an embodiment of the present invention. The method for determining the operating state of a battery pack is applied to a system for determining the operating state of a battery pack, wherein the battery pack can be applied to a substation. Figure 2 is a schematic diagram of a battery pack operating status determination system provided by an embodiment of the invention, with reference to Figure 2 The battery pack state operation system includes an operation state parameter acquisition module 10 and a processing module 20. The operation state parameter acquisition module 10 is connected to the processing module 20. The operation state parameter acquisition module 10 can acquire the operation state parameters of the battery pack. The processing module 20 can be used to execute the battery pack operation state determination method of any embodiment of the present invention. Figure 1 , the method for determining the operating state of the battery pack includes:

[0047] S110, obtaining operating status parameters of the battery pack, where the operating status parameters include at least one of the current capacity of the battery pack, the current number of charge and discharge times, the internal temperature, the internal gas content, and the deformation amount.

[0048] Specifically, the processing module 20 can obtain the operating state parameters of the battery pack from the operating state parameter acquisition module 10. The operating state acquisition module may include an acquisition unit for acquiring the operating state parameters. Considering that the operating state of the battery pack is related to the charging and discharging characteristics, capacity characteristics, internal temperature change characteristics, and internal gas content change characteristics of the battery pack, the operating state parameter acquisition module 10 is set to include at least one of a current capacity acquisition unit, a charging and discharging times acquisition unit, a gas content acquisition unit, an internal temperature acquisition unit, and a deformation acquisition unit; the current capacity acquisition unit, the charging and discharging times acquisition unit, the gas content acquisition unit, the internal temperature acquisition unit, and the deformation acquisition unit are respectively connected to the processing module 20; the current capacity acquisition unit is used to acquire the current capacity of the battery pack; the charging and discharging times acquisition unit is used to acquire the current charging and discharging times of the battery pack; the gas content acquisition unit is used to acquire the oxygen content and hydrogen content inside the battery pack; the internal temperature acquisition unit is used to acquire the temperature inside the battery pack; the deformation acquisition unit is used to acquire the current size of the battery pack; the processing module 20 is used to determine the deformation amount according to the current size and the factory size of the battery.

[0049] S120. Determine a corresponding state value according to the operating state parameter and a determination rule corresponding to the operating state parameter.

[0050] In this step, the state values ​​corresponding to different operating state parameters can be calculated by different determination rules. Among them, the determination rules of the state values ​​corresponding to the operating state parameters can be pre-stored and set, and the determination rules can be a calculation formula, or a lookup table of the corresponding relationship between the operating state parameters and the state values, or other forms of determination rules, which are not specifically limited in the embodiment of the present invention. Exemplarily, the first state value corresponding to the current capacity is determined according to the current capacity of the battery pack and the first determination rule; the second state value is determined according to the current number of charge and discharge times and the second determination rule; the third state value is determined according to the internal temperature and the third determination rule; the fourth state value is determined according to the internal gas content and the fourth determination rule; the fifth state value is determined according to the deformation and the fifth determination rule. The first determination rule, the second determination rule, the third determination rule, the fourth determination rule and the fifth determination rule can be stored and set in the processing module 20 in advance. After the processing module 20 obtains the operating state parameters, the corresponding state values ​​can be determined according to the operating state parameters and the corresponding determination rules. In this step, the corresponding state value is determined according to the operating state parameters related to the operating state of the battery pack as a quantitative indicator for determining the operating state of the battery pack.

[0051] S130. Determine an operating state of the battery pack according to the state value, where the operating state includes a current operating state and / or an operating state in a future predicted period.

[0052] Since the state value is determined based on the operating state parameters, the operating state parameters are related to the operating state of the battery pack. In this step, the operating state of the battery pack can be determined based on the state value. The operating state can be the current operating state, that is, the operating state at the current moment; it can also be the operating state of the future prediction period. Among them, the current operating state includes a normal operating state and a fault state, and the operating state of the future prediction period also includes a normal operating state and a fault state. In this step, not only can the current operating state of the battery pack be determined based on the state value, but also the operating state of the battery pack in the future prediction period can be predicted. Among them, when predicting the operating state of the battery pack in the future prediction period, the state values ​​at multiple moments in a set period of time before the state value at the current moment can be combined with the machine learning algorithm to perform model training to obtain the corresponding prediction model, and then the operating state of the future set period is predicted based on the prediction model.

[0053] The method for determining the operating state of a battery pack in an embodiment of the present invention obtains the operating state parameters of the battery pack, determines the corresponding state value according to the operating state parameters and the determination rules corresponding to the operating state parameters, and determines the operating state of the battery pack according to the state value. The operating state includes the current operating state and / or the operating state of the future prediction period. There is no need to manually detect the operating state, which can improve the detection efficiency of the operating state of the battery pack and avoid errors introduced by manual detection. In addition, in this embodiment, the operating state of the battery pack is determined according to the state value related to the operating state of the battery pack, so as to ensure the accuracy of the determined operating state of the battery pack. Moreover, in this embodiment, not only the current operating state can be determined, but also the operating state of the future prediction period can be determined. Then, when it is determined that the current operating state is a fault state or a fault state will occur in the future prediction period, the battery pack can be maintained in time to extend the service life of the battery pack and improve the maintenance efficiency.

[0054] In some optional embodiments of the present invention, the above S130 includes: when at least one state value exceeds the corresponding preset state value range, determining that the current operating state is a fault state; when all state values ​​do not exceed the corresponding preset state value range, determining that the current operating state is a normal state.

[0055] Before S110, a preset state value range corresponding to each state value may be preset, wherein the preset state value range is the state value range of the battery pack under normal working state. When at least one state value exceeds the corresponding preset state value range, it indicates that the battery pack is abnormal at the current moment, and the current operating state is determined to be a fault state, so that the battery pack is maintained in time.

[0056] In some optional embodiments, S120 includes: determining a first state value according to a ratio of a current capacity to a factory capacity of the battery pack, wherein the test temperatures of the current capacity and the factory capacity are the same.

[0057] In order to better ensure the output performance of the battery pack, it is necessary to timely understand the life of the battery pack. Its capacity change is one of the verification factors. Therefore, it is proposed to use the first state value determined by the ratio of the current capacity of the battery to the initial healthy state capacity (that is, the factory capacity) as a quantitative indicator for operating state evaluation. The first state value ΔS is calculated according to the following formula:

[0058]

[0059] Among them, S(T,I,K) is the capacity released by the battery when it is in a certain health state K and temperature T, with a load current I from full charge and discharge to the termination voltage; S(T,I) represents the factory capacity, that is, the capacity released by the battery when it is produced at temperature T, with a load current I from full charge and discharge to the termination voltage.

[0060] In some optional embodiments, the current charge and discharge times include the current cumulative charge times and the current cumulative discharge times; S120 includes: determining the second state value according to the ratio of the sum of the current cumulative charge times and the current cumulative discharge times to the rated charge and discharge times.

[0061] Specifically, the battery pack has a rated number of charge and discharge times, so the number of charge and discharge times is also one of the factors affecting the health status of the battery pack. The second state value ΔP is calculated according to the following formula:

[0062]

[0063] Among them, C is the current cumulative number of charges; D is the current cumulative number of discharges; and H is the rated number of charges and discharges specified for the battery pack.

[0064] In some optional embodiments, S120 includes: determining a third state value according to a ratio of a difference between a change in oxygen content and a change in hydrogen within a first set period before the current moment to a change in oxygen content.

[0065] Specifically, when charging is about 90% complete, the negative electrode begins to produce hydrogen. There are two other sources of hydrogen generation: (1) during overcharging, it is produced in the side reaction of water electrolysis; (2) during open circuit storage. Therefore, the operating condition of the battery pack can be determined by the gas sensor detecting the gas. The third state value ΔQ is calculated according to the following formula:

[0066]

[0067] Among them, Q 氧气 Indicates the change in oxygen content during the first set period, Q 氧气 represents the change in hydrogen content within the first set period, and Δt represents the duration of the first set period, wherein the first set period is continuous with the current moment.

[0068] In some optional embodiments, S120 includes: determining a fourth state value according to a change in the internal temperature within a second set period before the current moment.

[0069] Specifically, a large temperature difference inside the battery will also have a certain impact on the service life of the battery pack. Therefore, the influence of the internal temperature of the battery pack is considered here, and an optical fiber temperature sensor is used for measurement. The following is the relationship between the optical fiber wavelength drift and the temperature change:

[0070] Δλ B =K T ΔT;

[0071] where Δλ B K is the wavelength drift of the optical fiber when only the temperature changes. T is the FBG temperature sensitivity coefficient, and ΔT is the temperature change. According to the above formula, the change in the internal temperature of the battery pack in the second time period can be determined as the fourth state value according to the drift of the optical fiber wavelength. The second set time period is continuous with the current moment, and in some optional embodiments of the present invention, the second set time period is the same as the first set time period.

[0072] In some optional embodiments, S120 includes: determining a fifth state value according to a ratio of a deformation amount of the battery pack at a current moment to a factory size of the battery pack.

[0073] Specifically, after running for a period of time, the battery pack may be deformed, such as bulging or other surface deformation phenomena. Therefore, the displacement sensor is used to detect the surface displacement change of the battery pack.

[0074]

[0075] Wherein, L2 is the size of the battery pack at time t+1; L is the size of the battery pack at time t, and L0 is the reference size of the battery pack (i.e., the factory size). The size of the battery pack includes the length and / or width of the battery pack. The difference between t+1 and t is equal to the sampling interval time for the processing module 20 to obtain the operating status parameter from the displacement sensor.

[0076] Figure 3 is a flowchart of another method for determining the operating status of a battery pack provided by an embodiment of the present invention, referring to Figure 3 Optionally, the method for determining the operating state of the battery pack includes:

[0077] S210, obtaining operating status parameters of the battery pack, where the operating status parameters include at least one of the current capacity of the battery pack, the current number of charge and discharge times, the internal temperature, the internal gas content, and the deformation amount.

[0078] S220: Determine a corresponding state value according to the operating state parameter and a determination rule corresponding to the operating state parameter.

[0079] S230: Take the state value and the corresponding current running state, as well as the state values ​​and the corresponding historical running states at multiple moments in a preset historical period as samples.

[0080] The data training sample set E is as follows:

[0081] E={(x1,y1),(x2,y2)……(x n ,y n )};

[0082] x i ∈R N ,y i ∈{0,1},i=1,2……n.

[0083] where x i is a sample (data regularly acquired by the processing module 20 through the state parameter module), yi is a category (such as 1 for normal state, 0 for fault state, requiring on-site inspection), R N is an N-dimensional Gaussian feature space, and n is the number of samples.

[0084] S240: training multiple samples using a neural network model to obtain a state prediction model for the operating state of a future prediction period.

[0085] Figure 4 This is a schematic diagram of the neural network structure, refer to Figure 4The neural network structure has at least three layers, an input layer, one or more intermediate layers (hidden layers) and an output layer. The training process includes the forward propagation of input data and the back propagation of errors. The neural network training and learning process is the process of continuously correcting the thresholds and weights, so that the final output results are more consistent with expectations.

[0086] Optionally, S240 includes adjusting the number of neurons in the middle layer to reduce errors during the training of multiple samples using a neural network model, so as to obtain a state prediction model for the operating state of the future prediction period.

[0087] Specifically, during the training of the neural network model, the initial value of the number of neurons in the middle layer can be set first, and then the initial value can be adjusted. The adjustment direction of the initial value can be an increase direction or a decrease direction to reduce the error. In this way, the improved neural network model with a variable number of neurons in the middle layer is used to train the samples to obtain the state prediction model, thereby ensuring the accuracy of the determined state prediction model.

[0088] In some embodiments, during the process of training multiple samples using a neural network model, the number of neurons in the middle layer is adjusted, and the number of neurons with the smallest error is determined as the final corresponding number of neurons in the middle layer to obtain a state prediction model for the operating state of the future prediction period.

[0089] In some other embodiments, the number of neurons in the middle layer is adjusted according to the following formula:

[0090] y=(n+m) 1 / 2 +k·b;

[0091] Among them, y is the number of neurons in the middle layer, n and m are the number of neurons in the output layer and input layer respectively, b is a constant value, and k is a variable weight. The number of neurons in the middle layer can be adjusted by adjusting the size of the variable modulation k.

[0092] Optionally, the number of neurons in the middle layer can be trained with a smaller number of neurons in the middle layer first, and then gradually increased until the number of neurons in the middle layer corresponding to the minimum error is found. Training is performed as follows:

[0093] s t =Ux t +Wh t-1

[0094] h t =f((n+m) 1 / 2 +k·b)

[0095] o t =g(Vh t )

[0096] where x t is an n-dimensional vector, and the input of the recurrent network will be a whole sequence, that is, x = [x1,...,x t-1 ,x t ,x t+1 ,...x T ];h t represents the hidden state at time t; o t represents the output at time t; U represents the weight from the input layer to the hidden layer; W represents the weight from the hidden layer to the hidden layer; V represents the weight from the hidden layer to the output layer. n and m are the number of neurons in the output layer and the input layer respectively, b is a constant value, and k is a variable weight.

[0097] S250: predicting the operating status of a future prediction period according to the status prediction model.

[0098] Continue to refer Figure 2 The embodiment of the present invention further provides a battery pack operating state determination system, which includes: an operating state parameter acquisition module 10 and a processing module 20; the operating state parameter acquisition module 10 is connected to the processing module 20, and is used to acquire the operating state parameters of the battery pack, and the operating state parameters include at least one of the current capacity of the battery pack, the current number of charge and discharge times, the internal temperature, the internal gas content, and the deformation amount; the processing module 20 is used to determine the corresponding state value according to the operating state parameters obtained from the operating state parameter acquisition module 10 and the determination rules corresponding to the operating state parameters; the operating state of the battery pack is determined according to the state value, and the operating state includes the current operating state and / or the operating state of the future prediction period.

[0099] The battery pack operating state determination system of this embodiment automatically collects the operating state parameters of the battery pack through the operating state parameter acquisition module 10, and does not need to manually detect the operating state, which can improve the detection efficiency of the battery pack operating state and avoid errors introduced by manual detection. The processing module determines the operating state of the battery pack according to the state value related to the operating state of the battery pack to ensure the accuracy of the determined operating state of the battery pack. In addition, in this embodiment, not only the current operating state can be determined, but also the operating state of the future predicted period can be determined. Then, when it is determined that the current operating state is a fault state or a fault state will occur in the future predicted period, the battery pack can be maintained in time to extend the service life of the battery pack and improve the maintenance efficiency.

[0100] Figure 5 is a schematic diagram of another battery pack operating status determination system provided by an embodiment of the present invention, with reference to Figure 5Optionally, the operating status parameter acquisition module 10 includes at least one of a current capacity acquisition unit 11, a charge and discharge times acquisition unit 12, a gas content acquisition unit 13, an internal temperature acquisition unit 14, and a deformation acquisition unit 15; the current capacity acquisition unit 11, the charge and discharge times acquisition unit 12, the gas content acquisition unit 13, the internal temperature acquisition unit 14, and the deformation acquisition unit 15 are respectively connected to the processing module 20; the current capacity acquisition unit 11 is used to acquire the current capacity of the battery pack; the charge and discharge times acquisition unit 12 is used to acquire the current charge and discharge times of the battery pack; the gas content acquisition unit 13 is used to acquire the oxygen content and hydrogen content inside the battery pack; the internal temperature acquisition unit 14 is used to acquire the temperature inside the battery pack; the deformation acquisition unit 15 is used to acquire the current size of the battery pack.

[0101] Among them, the gas content acquisition unit 13 may include a gas sensor, and the gas sensor may be arranged inside the battery pack. The internal temperature acquisition unit 14 may include an optical fiber sensor, and the light sensor may be arranged inside the battery pack. The deformation acquisition unit 15 may include a displacement sensor, and the displacement sensor may be arranged on the surface of the battery pack. In some embodiments, the current capacity acquisition unit 11 may receive the current capacity input from the outside, and the charge and discharge times acquisition unit 12 may receive the charge and discharge times input from the outside.

[0102] Continue to refer Figure 5 Optionally, the battery pack operating status determination system also includes at least one of a communication module 30, an alarm module 40 and an input module 50; the communication module 30, the alarm module 40 and the input module 50 are respectively connected to the processing module 20, and the processing module 20 is used to send a prompt message through the communication module 30 when determining that the operating status includes a fault state, or to send an alarm message through the alarm module 40; the input module 50 is used to receive a preset state value range corresponding to the state value, and the processing module 20 is used to determine that the current operating state is a fault state when at least one state value exceeds the corresponding preset state value range; when all state values ​​do not exceed the corresponding preset state value range, determine that the current operating state is a normal state.

[0103] Among them, the communication module 30 can adopt a wired communication method or a wireless communication method. The alarm module 40 includes but is not limited to a buzzer, an indicator light, etc. By setting the battery pack operation status determination system to include a communication module 30 and / or an alarm module 40, maintenance personnel can receive prompt information or alarm information in time when the battery pack is in a fault state, and then maintain the battery pack in time, which is beneficial to extend the service life of the battery pack and improve the safety and reliability of the use of the battery pack. The battery pack operation status system also includes an input module 50, which can be a button or a touch panel, and the embodiment of the present invention is not specifically limited here.

[0104] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0105] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for determining the operating state of a battery pack, characterized in that: include: Acquiring operating state parameters of the battery pack, wherein the operating state parameters include at least one of the current capacity, current charge and discharge times, internal temperature, internal gas content, and deformation amount of the battery pack; Determine a corresponding state value according to the operating state parameter and a determination rule corresponding to the operating state parameter; The operating state of the battery pack is determined according to the state value, where the operating state includes a current operating state and / or an operating state in a future predicted period.

2. The method according to claim 1, characterized in that: Determining the operating state of the battery pack according to the state value includes: In the case where at least one of the state values ​​exceeds the corresponding preset state value range, determining that the current operating state is a fault state; When each of the state values ​​does not exceed the corresponding preset state value range, it is determined that the current operating state is a normal state.

3. The method according to claim 1 or 2, characterized in that: Determining the operating state of the battery pack according to the state value includes: The state value and the corresponding current running state, as well as the state values ​​and the corresponding historical running states at multiple moments in a preset historical period are taken as samples; Training the plurality of samples using a neural network model to obtain a state prediction model of the operating state of the future prediction period; The operating state of the future prediction period is predicted according to the state prediction model.

4. The method according to claim 3, characterized in that The neural network model includes an input layer, an output layer and one or at least two intermediate layers; the neural network model is used to train the plurality of samples to obtain a state prediction model of the running state in the future prediction period, including: In the process of training the plurality of samples using a neural network model, the number of neurons in the intermediate layer is adjusted to reduce errors, so as to obtain a state prediction model of the operating state of the future prediction period.

5. The method according to claim 4, characterized in that In the process of training the plurality of samples using a neural network model, the number of neurons in the intermediate layer is adjusted to reduce the error, so as to obtain a state prediction model of the operating state in the future prediction period, including: In the process of training the multiple samples using the neural network model, the number of neurons in the middle layer is adjusted, and the number of neurons with the smallest error is determined as the final number of neurons corresponding to the middle layer, so as to obtain a state prediction model of the operating state of the future prediction period.

6. The method according to claim 4, characterized in that In the process of training the plurality of samples using a neural network model, the number of neurons in the intermediate layer is adjusted to reduce the error, so as to obtain a state prediction model of the operating state in the future prediction period, including: The number of neurons in the middle layer is adjusted according to the following formula: y=(n+m) 1 / 2 +k·b; Among them, y is the number of neurons in the middle layer, n and m are the number of neurons in the output layer and input layer respectively, b is a constant value, and k is a variable weight.

7. The method according to claim 1, characterized in that The determining the corresponding state value according to the operating state parameter and the determination rule corresponding to the operating state parameter includes: Determining a first state value according to a ratio of the current capacity to the factory capacity of the battery pack, wherein the test temperatures of the current capacity and the factory capacity are the same; The current charge and discharge times include the current cumulative charge times and the current cumulative discharge times; the second state value is determined according to the ratio of the sum of the current cumulative charge times and the current cumulative discharge times to the rated charge and discharge times; Determine a third state value according to a ratio of a difference between a change in oxygen content and a change in hydrogen in a first set period before the current moment to the change in oxygen content; Determine a fourth state value according to the change amount of the internal temperature within a second set period before the current moment; A fifth state value is determined according to a ratio of the deformation amount of the battery pack at the current moment to a factory size of the battery pack.

8. A system for determining the operating status of a battery pack, characterized in that: include: Operation status parameter acquisition module and processing module; The operating state parameter acquisition module is connected to the processing module and is used to acquire the operating state parameters of the battery pack, wherein the operating state parameters include at least one of the current capacity, current charge and discharge times, internal temperature, internal gas content, and deformation amount of the battery pack; The processing module is used to determine the corresponding state value according to the operating state parameter obtained from the operating state parameter acquisition module and the determination rule corresponding to the operating state parameter; The operating state of the battery pack is determined according to the state value, where the operating state includes a current operating state and / or an operating state in a future predicted period.

9. The battery pack operating state determination system according to claim 8, characterized in that: The operating state parameter acquisition module includes at least one of a current capacity acquisition unit, a charge and discharge times acquisition unit, a gas content acquisition unit, an internal temperature acquisition unit, and a deformation acquisition unit; the current capacity acquisition unit, the charge and discharge times acquisition unit, the gas content acquisition unit, the internal temperature acquisition unit, and the deformation acquisition unit are respectively connected to the processing module; The current capacity acquisition unit is used to acquire the current capacity of the battery pack; The charge and discharge times acquisition unit is used to acquire the current charge and discharge times of the battery pack; The gas content collection unit is used to collect the oxygen content and hydrogen content inside the battery pack; The internal temperature acquisition unit is used to acquire the temperature inside the battery pack; The deformation acquisition unit is used to acquire the current size of the battery pack.

10. The battery pack operating state determination system according to claim 8, characterized in that: Also includes at least one of a communication module, an alarm module and an input module; The communication module, the alarm module, and the input module are respectively connected to the processing module, and the processing module is used to send a prompt message through the communication module or send an alarm message through the alarm module when determining that the operating state includes a fault state; The input module is used to receive a preset state value range corresponding to the state value, and the processing module is used to determine that the current operating state is a fault state when at least one of the state values ​​exceeds the corresponding preset state value range; When each of the state values ​​does not exceed the corresponding preset state value range, it is determined that the current operating state is a normal state.

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