Method and device for joint estimation of soc and soh of lithium-ion battery
By combining current data, SOC values, and SOH values with an equivalent circuit model and an optimized model, the method for estimating the state of charge (SOC) and state of OH of lithium-ion batteries has solved the problem of low accuracy in estimating the SOC and achieved higher-precision real-time estimation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- GUANGDONG POWER GRID CO LTD
- Filing Date
- 2023-01-18
- Publication Date
- 2026-07-21
AI Technical Summary
Existing lithium-ion battery state-of-charge estimation algorithms suffer from low accuracy, particularly in estimating the SOC and SOH of lithium-ion batteries, which hinders their application development.
A joint estimation method for SOC and SOH of lithium-ion batteries is adopted. Based on the current data of the lithium battery at the current moment, the SOC value and SOH value at the previous moment, and combined with the equivalent circuit model of the lithium battery, the prior SOC estimate, the optimal SOH estimate and the posterior SOC estimate are determined by the optimization model, realizing an alternating estimation optimization process.
It improves the accuracy of lithium-ion battery state of charge estimation, takes into account the coupling relationship between SOC and SOH, simplifies the calculation steps, is suitable for real-time online estimation, and improves the accuracy and efficiency of estimation.
Smart Images
Figure CN116008818B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of energy storage technology, and in particular to a method and apparatus for jointly estimating the SOC and SOH of a lithium-ion battery. Background Technology
[0002] Lithium-ion battery energy storage is currently the most widely used form of electrochemical energy storage system, and it is widely applied in power grids, electric vehicles, and other fields. The actual state of charge (SOC) of a lithium-ion battery is one of the most significant factors affecting its output. For lithium-ion batteries, the SOC is a core physical variable that exists but cannot be directly measured and is difficult to accurately estimate. The complex electrochemical processes within the battery and the coupling effects of factors such as temperature, aging, charge / discharge rate, and self-discharge rate are key reasons why its accurate estimation is challenging. Currently, SOC estimation for lithium-ion batteries remains a critical factor limiting its development and is a focus of attention for experts and scholars in the industry. Therefore, developing high-precision SOC estimation algorithms for lithium-ion batteries is of great significance.
[0003] Currently, research on the state of charge (SOC) estimation of lithium-ion batteries mainly focuses on two aspects: SOC influencing factor analysis and SOC estimation itself. SOC influencing factor analysis can also serve as a preliminary step in improving SOC estimation methods. Regarding SOC estimation, common methods include empirical formulas based on experiments and data, SOC estimation methods based on battery equivalent circuit models (such as Kalman filtering and its improvements, particle filtering, etc.), and artificial intelligence methods based on big data science (such as neural networks and their improvements, support vector machines, etc.). Empirical formula methods and artificial intelligence methods based on data have high requirements for the quality of lithium-ion battery data, and the coupling relationships between multiple factors are difficult to determine. While SOC estimation methods based on equivalent circuit models have lower requirements for data quality, the accuracy of the equivalent circuit model is significantly affected, and the coupling of numerous influencing factors causes nonlinearity in the model. Therefore, research on lithium-ion battery SOC estimation methods driven by a hybrid data and model approach, and the development of more accurate and efficient lithium-ion battery SOC estimation algorithms, is a current research hotspot. Summary of the Invention
[0004] This application provides a method and apparatus for jointly estimating the SOC and SOH of lithium-ion batteries, in order to solve the technical problem of low estimation accuracy in existing lithium-ion battery state-of-charge estimation algorithms.
[0005] To address the aforementioned technical problems, in a first aspect, this application provides a method for jointly estimating the SOC and SOH of a lithium-ion battery, comprising:
[0006] Based on the current data of the lithium battery at the current moment, the SOC value and SOH value at the previous moment, the prior SOC estimate of the lithium battery at the current moment is determined;
[0007] Based on the prior SOC estimate, and combined with the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values, the output voltage of the lithium battery equivalent circuit model is determined.
[0008] Using an optimization model between the output voltage and the measured voltage of the lithium battery, the optimal estimated value of the SOH of the lithium battery at the current moment is determined;
[0009] Using the equivalent circuit model of the lithium battery, and based on the optimal SOH estimate, the posterior SOC estimate of the lithium battery at the current moment is calculated.
[0010] In some implementations, determining the prior SOC estimate of the lithium battery based on the current data of the lithium battery at the current moment, the SOC value and SOH value at the previous moment includes:
[0011] Using the ampere-hour integration method, based on the current data of the lithium battery at the current moment and the SOC value at the previous moment, the prior SOC estimate of the lithium battery at the current moment is determined. The expression for the ampere-hour integration method is:
[0012] ;
[0013] in, This represents the prior SOC estimate of a lithium battery. Indicates that lithium batteries are Current data at any given time. Indicates that lithium batteries are SOC value at time t, Indicates that lithium batteries are SOH value at time 10:00 This indicates the nominal capacity of the lithium battery. This indicates the charging efficiency of the lithium battery. This indicates the discharge efficiency of the lithium battery; This represents the self-discharge coefficient of a lithium-ion battery. This indicates that the lithium battery is charging. This indicates that the lithium battery is discharging.
[0014] In some implementations, determining the output voltage of the lithium battery equivalent circuit model based on the prior SOC estimate and the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values includes:
[0015] Based on the historical data of the lithium battery, the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values is determined.
[0016] Based on the prior SOC estimate and functional relationship, the output voltage of the lithium battery equivalent circuit model is determined.
[0017] In some implementations, the expression for the equivalent circuit model of the lithium battery is:
[0018] ;
[0019] in, This represents the output voltage of the equivalent circuit model of a lithium battery. This represents the output current of the equivalent circuit model of a lithium battery. These represent the model parameters of the equivalent circuit model of a lithium battery. Indicates that lithium batteries are SOC value at time t, Indicates that lithium batteries are The SOH value at time 10:00. Represents a time function.
[0020] In some implementations, determining the optimal estimate of the SOH of the lithium battery at the current moment using an optimization model between the output voltage and the measured voltage of the lithium battery includes:
[0021] Based on the output voltage and the measured voltage, establish the objective function and constraints of the optimization model;
[0022] Using an optimization algorithm, based on the objective function and constraints, the optimal estimated value of the state of harmonics (SOH) of the lithium battery at the current moment is determined; the expressions for the objective function and constraints are:
[0023] ;
[0024] in, Indicates that lithium batteries are Output voltage at any given time Indicates that lithium batteries are Voltage measured at time, Indicates that lithium batteries are The SOH value at time 10:00. Indicates that lithium batteries are The SOH value at time 10:00. Indicates that lithium batteries are The SOH value at time t.
[0025] In some implementations, the step of using the equivalent circuit model of the lithium battery to calculate the posterior SOC estimate of the lithium battery at the current time based on the optimal SOH estimate includes:
[0026] Substituting the optimal SOH estimate into the lithium battery equivalent circuit model, the target equivalent circuit model is obtained;
[0027] Using a state estimation algorithm, based on the target equivalent circuit model and the measured voltage, the posterior SOC estimate of the lithium battery at the current moment is calculated.
[0028] In some implementations, the expression for the target equivalent circuit model is:
[0029] ;
[0030] in, This represents the posterior SOC estimate of the lithium battery at the current moment. This represents the optimal estimate of the SOH of the lithium battery at the current moment.
[0031] Secondly, this application also provides a device for jointly estimating the SOC and SOH of a lithium-ion battery, comprising:
[0032] The first determining module is used to determine the prior SOC estimate of the lithium battery at the current moment based on the current data of the lithium battery at the current moment, the SOC value and SOH value at the previous moment;
[0033] The second determining module is used to determine the output voltage of the lithium battery equivalent circuit model based on the prior SOC estimate and the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values.
[0034] The third determining module is used to determine the optimal estimated value of the SOH of the lithium battery at the current moment by using an optimization model between the output voltage and the measured voltage of the lithium battery;
[0035] The calculation module is used to calculate the posterior SOC estimate of the lithium battery at the current time based on the optimal SOH estimate using the equivalent circuit model of the lithium battery.
[0036] Thirdly, this application also provides a computer device, including a processor and a memory, the memory being used to store a computer program, which, when executed by the processor, implements the joint estimation method for SOC and SOH of a lithium-ion battery as described in the first aspect.
[0037] Fourthly, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the joint estimation method for SOC and SOH of a lithium-ion battery as described in the first aspect.
[0038] Compared with the prior art, this application has at least the following beneficial effects:
[0039] By using the current data of the lithium battery at the current moment, and the SOC and SOH values at the previous moment, the prior SOC estimate of the lithium battery at the current moment is determined. Based on the prior SOC estimate, and combining the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values, the output voltage of the lithium battery equivalent circuit model is determined. Using an optimized model between the output voltage and the measured voltage of the lithium battery, the optimal SOH estimate of the lithium battery at the current moment is determined. Using the lithium battery equivalent circuit model, and based on the optimal SOH estimate, the posterior SOC estimate of the lithium battery at the current moment is calculated. This approach considers the coupling problem between the actual lithium battery SOC and SOH estimation processes. Through an alternating estimation and optimization process, the prior SOC estimate of the lithium battery is combined with the lithium battery equivalent circuit model to optimize the current SOH of the lithium battery. Then, the optimized lithium battery equivalent model is used to complete the final SOC estimate of the lithium battery. Compared to existing independent estimation methods for SOC and SOH of lithium batteries, this application fully considers the coupling relationship between the two and applies optimization and numerical simulation combination methods to further improve the estimation accuracy. Compared to existing joint estimation methods for SOC and SOH, the steps in this application are simpler to implement and have less computational load, making it more suitable for real-time online estimation of lithium batteries. Attached Figure Description
[0040] Figure 1 This is a schematic flowchart illustrating the joint estimation method of SOC and SOH for lithium-ion batteries in an embodiment of this application.
[0041] Figure 2 This is a schematic diagram of the structure of a first-order Thevenin equivalent circuit shown in an embodiment of this application;
[0042] Figure 3 This is a schematic diagram of the structure of the joint estimation device for SOC and SOH of a lithium-ion battery shown in the embodiments of this application;
[0043] Figure 4 This is a schematic diagram of the structure of a computer device shown in an embodiment of this application. Detailed Implementation
[0044] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.
[0045] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a joint estimation method for SOC and SOH of a lithium-ion battery provided in an embodiment of this application. The joint estimation method for SOC and SOH of a lithium-ion battery in this application can be applied to computer devices, including but not limited to smartphones, laptops, tablets, desktop computers, physical servers, and cloud servers. Figure 1 As shown, the joint estimation method for SOC and SOH of lithium-ion batteries in this embodiment includes steps S101 to S104, which are detailed below:
[0046] Step S101: Based on the current data of the lithium battery at the current moment, the SOC value and SOH value at the previous moment, determine the prior SOC estimate of the lithium battery at the current moment.
[0047] Step S102: Based on the prior SOC estimate, and combined with the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values, determine the output voltage of the lithium battery equivalent circuit model.
[0048] Step S103: Using the optimization model between the output voltage and the measured voltage of the lithium battery, determine the optimal estimated value of the SOH of the lithium battery at the current moment.
[0049] Step S104: Using the equivalent circuit model of the lithium battery, calculate the posterior SOC estimate of the lithium battery at the current moment based on the optimal SOH estimate.
[0050] In this embodiment, the coupling problem between the actual lithium battery SOC and SOH estimation processes is considered. An alternating estimation and optimization process is used, combining the prior estimate of the lithium battery SOC with a lithium battery equivalent circuit model to optimize the current SOH. Then, the optimized lithium battery equivalent model is used to complete the final estimation of the lithium battery SOC. Compared to existing independent estimation methods for lithium battery SOC and SOH, this application fully considers the coupling relationship between the two and applies optimization and a combination of numerical and analog methods to further improve estimation accuracy. Compared to existing joint estimation methods for SOC and SOH, the steps in this application are simpler to implement and have less computational load, making it more suitable for real-time online estimation of lithium batteries.
[0051] In some embodiments, step S101 includes:
[0052] Using the ampere-hour integration method, based on the current data of the lithium battery at the current moment and the SOC value at the previous moment, the prior SOC estimate of the lithium battery at the current moment is determined. The expression for the ampere-hour integration method is:
[0053] ;
[0054] in, This represents the prior SOC estimate of a lithium battery. Indicates that lithium batteries are Current data at any given time. Indicates that lithium batteries are SOC value at time t, Indicates that lithium batteries are SOH value at time 10:00 This indicates the nominal capacity of the lithium battery. This indicates the charging efficiency of the lithium battery. This indicates the discharge efficiency of the lithium battery; This represents the self-discharge coefficient of a lithium-ion battery. This indicates that the lithium battery is charging. This indicates that the lithium battery is discharging.
[0055] In this embodiment, a power sensor is used to measure the lithium-ion battery. Current value at time and according to Lithium-ion batteries as well as The ampere-hour integral method was used to calculate Prior SOC estimate of lithium-ion battery at time .
[0056] In some embodiments, step S102 includes:
[0057] Based on the historical data of the lithium battery, the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values is determined.
[0058] Based on the prior SOC estimate and functional relationship, the output voltage of the lithium battery equivalent circuit model is determined.
[0059] In this embodiment, an equivalent circuit model of lithium-ion batteries is established, and based on historical experimental test data, the functional relationship between the model parameters and the SOC and SOH of the lithium-ion battery is tuned. Combined with the prior SOC estimate, the output voltage expression based on the equivalent circuit model is obtained, which is a function with the current SOH as the variable.
[0060] Optionally, the expression for the equivalent circuit model of the lithium battery is:
[0061] ;
[0062] in, This represents the output voltage of the equivalent circuit model of a lithium battery. This represents the output current of the equivalent circuit model of a lithium battery. These represent the model parameters of the equivalent circuit model of a lithium battery. Indicates that lithium batteries are SOC value at time t, Indicates that lithium batteries are The SOH value at time 10:00. Represents a time function.
[0063] For example, an equivalent circuit model of a lithium-ion battery is established based on the equivalent circuit method, so as to... Figure 2 Taking the first-order Thevenin equivalent circuit shown as an example, its mathematical model is as follows:
[0064] ;
[0065] in, , , as well as These represent the open-circuit voltage (V), internal resistance (Ω), polarization resistance (Ω), and polarization capacitance (F) of a lithium-ion battery, respectively. These battery parameters are time-varying. and The function.
[0066] If the open circuit voltage of a lithium-ion battery and and To establish a cubic function relationship, based on laboratory test data and historical data (cycle aging tests and hybrid power pulse experiments, etc.) of lithium-ion batteries, the function coefficients are tuned using least squares and its improved methods to establish the functional relationship between lithium-ion battery parameters and battery SOC and SOH. Finally, based on the prior SOC estimate of the lithium-ion battery at time t calculated in step S101, the relationship is further defined. Based on the equivalent circuit model, the output voltage expression based on the lithium-ion battery equivalent circuit can be represented as follows:
[0067] ;
[0068] visible, The output voltage of the battery model at any given time is characterized as that of a lithium-ion battery. The function.
[0069] In some embodiments, step S103 includes:
[0070] Based on the output voltage and the measured voltage, establish the objective function and constraints of the optimization model;
[0071] Using an optimization algorithm, the optimal estimated value of the SOH of the lithium battery at the current moment is determined based on the objective function and constraints.
[0072] In this embodiment, an optimization model is established with the goal of minimizing the sum of squared residuals between the output voltage based on the equivalent circuit model and the measured battery voltage. An optimization algorithm is then used to solve for the optimal estimate of the SOH of the lithium-ion battery at the current moment.
[0073] based on( The measured voltage of the lithium-ion battery and the output voltage of the battery model within the specified time period define the lithium-ion battery. The objective function of the optimal estimate The constraints are as follows:
[0074] ;
[0075] in, Indicates that lithium batteries are Output voltage at any given time Indicates that lithium batteries are Voltage measured at time, Indicates that lithium batteries are The SOH value at time 10:00. Indicates that lithium batteries are The SOH value at time 10:00. Indicates that lithium batteries are The SOH value at time 10:00. This represents the length of the time window. It should be noted that... It is obtained from the prior SOC value calculated in step S101 at time t. function, and It is from step S104 in The posterior SOC value calculated at time 1 Obtained function.
[0076] According to the objective function Given the constraints, the optimization algorithm is used to calculate ( Lithium-ion batteries during the period Then define time The optimization result is Optimal estimate of SOH of lithium-ion battery at time .
[0077] In some embodiments, step S104 includes:
[0078] Substituting the optimal SOH estimate into the lithium battery equivalent circuit model, the target equivalent circuit model is obtained;
[0079] Using a state estimation algorithm, based on the target equivalent circuit model and the measured voltage, the posterior SOC estimate of the lithium battery at the current moment is calculated.
[0080] In this embodiment, the optimal SOH estimate obtained in step S103 is input into the equivalent circuit model of the lithium battery. Combined with the measured battery voltage, the posterior estimate of the SOC of the lithium-ion battery at the current moment is calculated using a state estimation algorithm, which is the final estimation result.
[0081] In some embodiments, the expression for the target equivalent circuit model is:
[0082] ;
[0083] in, This represents the posterior SOC estimate of the lithium battery at the current moment. This represents the optimal estimate of the SOH of the lithium battery at the current moment.
[0084] Optionally, based on the aforementioned target equivalent circuit model, existing mature state estimation algorithms, such as Kalman filtering and its improved algorithms, can be applied to obtain the posterior SOC estimate of the lithium-ion battery. That is, the final SOC estimation result. Then, based on the lithium-ion battery circuit and voltage measured at time t+1, the SOC and SOH of the lithium-ion battery at time t+1 are estimated.
[0085] To implement the joint estimation method for SOC and SOH of lithium-ion batteries corresponding to the above method embodiments, and to achieve the corresponding functional and technical effects, see [link to documentation]. Figure 3 , Figure 3 This diagram illustrates a structural block diagram of a joint SOC and SOH estimation device for a lithium-ion battery according to an embodiment of this application. For ease of explanation, only the parts relevant to this embodiment are shown. The joint SOC and SOH estimation device for a lithium-ion battery provided in this embodiment includes:
[0086] The first determining module 301 is used to determine the prior SOC estimate of the lithium battery at the current moment based on the current data of the lithium battery at the current moment, the SOC value and SOH value at the previous moment.
[0087] The second determining module 302 is used to determine the output voltage of the lithium battery equivalent circuit model based on the prior SOC estimate and the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values.
[0088] The third determining module 303 is used to determine the optimal estimated value of the SOH of the lithium battery at the current moment by using an optimization model between the output voltage and the measured voltage of the lithium battery.
[0089] The calculation module 304 is used to calculate the posterior SOC estimate of the lithium battery at the current moment based on the optimal SOH estimate using the equivalent circuit model of the lithium battery.
[0090] In some embodiments, the first determining module 301 is specifically used for:
[0091] Using the ampere-hour integration method, based on the current data of the lithium battery at the current moment and the SOC value at the previous moment, the prior SOC estimate of the lithium battery at the current moment is determined. The expression for the ampere-hour integration method is:
[0092] ;
[0093] in, This represents the prior SOC estimate of a lithium battery. Indicates that lithium batteries are Current data at any given time. Indicates that lithium batteries are SOC value at time t, Indicates that lithium batteries are SOH value at time 10:00 This indicates the nominal capacity of the lithium battery. This indicates the charging efficiency of the lithium battery. This indicates the discharge efficiency of the lithium battery; This represents the self-discharge coefficient of a lithium-ion battery. This indicates that the lithium battery is charging. This indicates that the lithium battery is discharging.
[0094] In some embodiments, the second determining module 302 is specifically used for:
[0095] Based on the historical data of the lithium battery, the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values is determined.
[0096] Based on the prior SOC estimate and functional relationship, the output voltage of the lithium battery equivalent circuit model is determined.
[0097] In some embodiments, the expression for the lithium battery equivalent circuit model is:
[0098] ;
[0099] in, This represents the output voltage of the equivalent circuit model of a lithium battery. This represents the output current of the equivalent circuit model of a lithium battery. These represent the model parameters of the equivalent circuit model of a lithium battery. Indicates that lithium batteries are SOC value at time t, Indicates that lithium batteries are The SOH value at time 10:00. Represents a time function.
[0100] In some embodiments, the third determining module 303 is specifically used for:
[0101] Based on the output voltage and the measured voltage, establish the objective function and constraints of the optimization model;
[0102] Using an optimization algorithm, based on the objective function and constraints, the optimal estimated value of the state of harmonics (SOH) of the lithium battery at the current moment is determined; the expressions for the objective function and constraints are:
[0103] ;
[0104] in, Indicates that lithium batteries are Output voltage at any given time Indicates that lithium batteries are Voltage measured at time, Indicates that lithium batteries are The SOH value at time 10:00. Indicates that lithium batteries are The SOH value at time 10:00. Indicates that lithium batteries are The SOH value at time t.
[0105] In some embodiments, the computing module 304 is specifically used for:
[0106] Substituting the optimal SOH estimate into the lithium battery equivalent circuit model, the target equivalent circuit model is obtained;
[0107] Using a state estimation algorithm, based on the target equivalent circuit model and the measured voltage, the posterior SOC estimate of the lithium battery at the current moment is calculated.
[0108] In some embodiments, the expression for the target equivalent circuit model is:
[0109] ;
[0110] in, This represents the posterior SOC estimate of the lithium battery at the current moment. This represents the optimal estimate of the SOH of the lithium battery at the current moment.
[0111] The aforementioned joint SOC and SOH estimation device for lithium-ion batteries can implement the joint SOC and SOH estimation method for lithium-ion batteries described in the above method embodiments. The options in the above method embodiments are also applicable to this embodiment and will not be detailed here. The remaining content of this application embodiment can be referred to the content of the above method embodiments, and will not be repeated in this embodiment.
[0112] Figure 4 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Figure 4 As shown, the computer device 4 in this embodiment includes: at least one processor 40 ( Figure 4 (Only one is shown in the diagram) a processor, a memory 41, and a computer program 42 stored in the memory 41 and executable on the at least one processor 40, wherein the processor 40 executes the computer program 42 to implement the steps in any of the above method embodiments.
[0113] The computer device 4 can be a smartphone, tablet, desktop computer, cloud server, or other computing device. This computer device may include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art will understand that... Figure 4 The computer device 4 is merely an example and does not constitute a limitation on the computer device 4. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, etc.
[0114] The processor 40 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.
[0115] In some embodiments, the memory 41 may be an internal storage unit of the computer device 4, such as a hard disk or memory of the computer device 4. In other embodiments, the memory 41 may be an external storage device of the computer device 4, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 4. Furthermore, the memory 41 may include both internal and external storage units of the computer device 4. The memory 41 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 41 can also be used to temporarily store data that has been output or will be output.
[0116] In addition, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in any of the above method embodiments.
[0117] This application provides a computer program product that, when run on a computer device, enables the computer device to execute the steps described in the various method embodiments above.
[0118] In the several embodiments provided in this application, it will be understood that each block in the flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the figures. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved.
[0119] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.
[0120] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above descriptions are merely specific embodiments of this application and are not intended to limit the scope of protection of this application. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application for those skilled in the art.
Claims
1. A method for jointly estimating the SOC and SOH of a lithium-ion battery, characterized in that, include: Based on the current data of the lithium battery at the current moment, the SOC value and SOH value at the previous moment, the prior SOC estimate of the lithium battery at the current moment is determined; Based on the prior SOC estimate, and combined with the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values, the output voltage of the lithium battery equivalent circuit model is determined. Using an optimization model between the output voltage and the measured voltage of the lithium battery, the optimal estimated value of the SOH of the lithium battery at the current moment is determined; Using the equivalent circuit model of the lithium battery, and based on the optimal SOH estimate, the posterior SOC estimate of the lithium battery at the current moment is calculated. The step of using an optimization model between the output voltage and the measured voltage of the lithium battery to determine the optimal estimate of the SOH of the lithium battery at the current moment includes: Based on the output voltage and the measured voltage, establish the objective function and constraints of the optimization model; Using an optimization algorithm, based on the objective function and constraints, the optimal estimated value of the state of harmonics (SOH) of the lithium battery at the current moment is determined; the expressions for the objective function and constraints are: ； in, Indicates that lithium batteries are Output voltage at any given time Indicates that lithium batteries are Voltage measured at time, Indicates that lithium batteries are The SOH value at time 10:
00. Indicates that lithium batteries are The SOH value at time 10:
00. Indicates that lithium batteries are The SOH value at time t.
2. The method for jointly estimating the SOC and SOH of a lithium-ion battery as described in claim 1, characterized in that, The determination of the prior SOC estimate of the lithium battery based on the current data of the lithium battery at the current moment, the SOC value and SOH value at the previous moment, includes: Using the ampere-hour integration method, based on the current data of the lithium battery at the current moment and the SOC value at the previous moment, the prior SOC estimate of the lithium battery at the current moment is determined. The expression for the ampere-hour integration method is: ； in, This represents the prior SOC estimate of a lithium battery. Indicates that lithium batteries are Current data at any given time. Indicates that lithium batteries are SOC value at time t, Indicates that lithium batteries are SOH value at time 10:00 This indicates the nominal capacity of the lithium battery. This indicates the charging efficiency of the lithium battery. This indicates the discharge efficiency of the lithium battery; This represents the self-discharge coefficient of a lithium-ion battery. This indicates that the lithium battery is charging. This indicates that the lithium battery is discharging.
3. The method for jointly estimating SOC and SOH of a lithium-ion battery as described in claim 1, characterized in that, The step of determining the output voltage of the lithium battery equivalent circuit model based on the prior SOC estimate and the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values includes: Based on the historical data of the lithium battery, the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values is determined. Based on the prior SOC estimate and functional relationship, the output voltage of the lithium battery equivalent circuit model is determined.
4. The method for jointly estimating SOC and SOH of a lithium-ion battery as described in claim 3, characterized in that, The expression for the equivalent circuit model of the lithium battery is: ； in, This represents the output voltage of the equivalent circuit model of a lithium battery. This represents the output current of the equivalent circuit model of a lithium battery. These represent the model parameters of the equivalent circuit model of a lithium battery. Indicates that lithium batteries are SOC value at time t, Indicates that lithium batteries are The SOH value at time 10:
00. Represents a time function.
5. The method for jointly estimating SOC and SOH of a lithium-ion battery as described in claim 4, characterized in that, The step of using the equivalent circuit model of the lithium battery to calculate the posterior SOC estimate of the lithium battery at the current moment based on the optimal SOH estimate includes: Substituting the optimal SOH estimate into the lithium battery equivalent circuit model, the target equivalent circuit model is obtained; Using a state estimation algorithm, based on the target equivalent circuit model and the measured voltage, the posterior SOC estimate of the lithium battery at the current moment is calculated.
6. The method for jointly estimating SOC and SOH of a lithium-ion battery as described in claim 5, characterized in that, The expression for the target equivalent circuit model is: ; in, This represents the posterior SOC estimate of the lithium battery at the current moment. This represents the optimal estimate of the SOH (State of Harm) of the lithium battery at the current moment. Indicates that lithium batteries are Current data at any given time. Indicates that lithium batteries are SOC value at time 10:00 This indicates the nominal capacity of the lithium battery. This indicates the charging efficiency of the lithium battery. This indicates the discharge efficiency of the lithium battery; This represents the self-discharge coefficient of a lithium-ion battery. This indicates that the lithium battery is charging. This indicates that the lithium battery is discharging.
7. A device for jointly estimating the SOC and SOH of a lithium-ion battery, characterized in that, include: The first determining module is used to determine the prior SOC estimate of the lithium battery at the current moment based on the current data of the lithium battery at the current moment, the SOC value and SOH value at the previous moment; The second determining module is used to determine the output voltage of the lithium battery equivalent circuit model based on the prior SOC estimate and the functional relationship between the model parameters of the lithium battery equivalent circuit model and the SOC and SOH values. The third determining module is used to determine the optimal estimated value of the SOH of the lithium battery at the current moment by using an optimization model between the output voltage and the measured voltage of the lithium battery; The calculation module is used to calculate the posterior SOC estimate of the lithium battery at the current moment based on the optimal SOH estimate using the equivalent circuit model of the lithium battery. The third determining module is specifically used for: Based on the output voltage and the measured voltage, establish the objective function and constraints of the optimization model; Using an optimization algorithm, based on the objective function and constraints, the optimal estimated value of the state of harmonics (SOH) of the lithium battery at the current moment is determined; the expressions for the objective function and constraints are: ； in, Indicates that lithium batteries are Output voltage at any given time Indicates that lithium batteries are Voltage measured at time, Indicates that lithium batteries are The SOH value at time 10:
00. Indicates that lithium batteries are The SOH value at time 10:
00. Indicates that lithium batteries are The SOH value at time t.
8. A computer device, characterized in that, It includes a processor and a memory, the memory being used to store a computer program, which, when executed by the processor, implements the joint estimation method for SOC and SOH of a lithium-ion battery as described in any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the joint estimation method for SOC and SOH of a lithium-ion battery as described in any one of claims 1 to 6.