A battery system performance evaluation method based on boundary construction

Abstract

This invention discloses a battery system performance evaluation method based on boundary construction. The method includes: A. Performing single-cell testing on a target model battery cell to construct cycle decay curves for the target model battery cell at different temperatures; B. Obtaining the factory parameters of the target model battery cell; C. Determining the upper and lower boundaries of the short-board cell within a set confidence interval using probability statistics; D. Obtaining the temperature field distribution of the desired system and determining the short-board cell temperature of the target model battery cell; E. Obtaining the initial capacity retention rate of the short-board cell and obtaining the cycle decay curve at the short-board cell temperature; obtaining a specific cycle decay curve for the short-board cell; and evaluating the performance of the desired system composed of the target model battery cell based on the specific cycle decay curve. This method, on the one hand, summarizes multiple influencing factors, improving the accuracy of prediction; on the other hand, it can be adjusted for specific target model battery cells, improving prediction flexibility.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery system performance prediction, and in particular relates to a battery system performance evaluation method based on boundary construction. Background Art

[0002] The performance of energy storage batteries will experience irreversible aging as they are used, which directly affects the performance and use value of energy storage products. During the use of existing energy storage battery systems, status monitoring and life prediction can be carried out to diagnose the situation, determine the best maintenance or replacement time or change the operation strategy, thereby extending the battery life, improving the use value of energy storage products, and bringing intuitive economic value.

[0003] SOH characterizes the ability of a battery to store electrical energy and energy relative to a new battery, and is an indicator that quantitatively describes the performance status of a battery. As charging and discharging proceed, SOH shows a downward trend. At present, the research ideas for SOH mainly include three categories: 1. From the perspective of battery aging mechanism, describe the battery capacity decay and impedance increase; 2. From an experimental perspective, describe the relationship between battery capacity decay and impedance increase; 3 Based on the battery model, use algorithms such as least squares and KF to identify parameters such as capacitance and resistance of the battery equivalent model. Current technical parties mostly start from battery system data and make system-level predictions, but when encountering large system integration that is difficult to conduct actual testing, predictions are difficult to make.

[0004] The battery system is composed of battery cells and has a "barrel effect". This solution uses the "barrel effect" and recursively infers the capacity retention rate of the battery system by using the capacity retention rate of the battery cells in boundary operation. It is proposed to start from the perspective of battery cells and realize convenient and fast performance evaluation of the battery system composed of specific battery models by evaluating the overall performance of specific battery cells. This evaluation method will not cause problems that are difficult to evaluate and predict due to the large size of the system. Summary of the invention

[0005] The purpose of the present invention is to address the above-mentioned problems and provide a battery system performance evaluation method based on boundary construction, which utilizes the barrel effect to propose a life prediction method from battery cells to systems, which can overcome the limitations of system scale and also ensure better prediction and evaluation effects for large-scale systems.

[0006] A battery system performance evaluation method based on boundary construction, the method comprising:

[0007] A. Conduct single-cell tests on the target model battery cells, construct cycle attenuation curves of the target model battery cells at different temperatures, and characterize the capacity retention rate of the battery cells as the number of cycles changes;

[0008] B. Obtain the factory parameters of the target model battery, including initial capacity difference and residual capacity tolerance;

[0009] C. Obtain the upper and lower boundaries of the short board of the target model battery cell in the set confidence interval based on probability statistics;

[0010] D. Obtain the temperature field distribution of the desired system, and determine the short board cell temperature of the target model cell based on the temperature field distribution;

[0011] E. Obtain the initial capacity retention rate of the short-board battery cell based on the upper boundary and the lower boundary of the short board;

[0012] According to the temperature of the short-board battery cell, the cycle attenuation curve at that temperature is obtained;

[0013] The specific cycle decay curve of the short-board battery cell is obtained by combining the initial capacity retention rate and the cycle decay curve;

[0014] The performance of the desired system composed of target model batteries is evaluated according to the specific cycle attenuation curve.

[0015] In the above-mentioned battery system performance evaluation method based on boundary construction, in E, the initial capacity retention rate is used as the initial value of the cycle decay curve at the corresponding temperature to draw the cycle decay curve to obtain the specific cycle decay curve of the short-board battery cell.

[0016] The above scheme proposes to evaluate the performance of the desired system based on the performance of the battery cells. On the one hand, it improves the accuracy of the prediction by summarizing various influencing factors. On the other hand, it can adjust the evaluation of various desired systems according to specific target signal batteries to improve the flexibility of prediction and evaluation. On the other hand, since it starts from the battery cells, the performance evaluation results are obtained by analyzing the temperature field of the desired system under extreme conditions, so it can realize the evaluation of systems of various sizes.

[0017] In the above-mentioned battery system performance evaluation method based on boundary construction, in E, the specific cycle decay curve is recursively derived as the cycle decay curve of the desired system;

[0018] The performance evaluation result includes the capacity retention rate of the desired system at a specific moment.

[0019] In the above-mentioned battery system performance evaluation method based on boundary construction, the upper boundary of the short board is the lower limit of the maximum chargeable capacity of the target model battery cell, and the lower boundary of the short board is the upper limit of the maximum dischargeable capacity of the target model battery cell;

[0020] In E, based on the input cycle number, the capacity retention rate of the desired system after the corresponding number of cycles is output according to the specific cycle decay curve.

[0021] In the above-mentioned battery system performance evaluation method based on boundary construction, the upper boundary of the short board is the lower limit and upper limit of the maximum chargeable capacity of the target model battery cell, and the lower boundary of the short board is the upper limit and lower limit of the maximum dischargeable capacity of the target model battery cell;

[0022] In E, based on the input number of cycles, the capacity retention rate range of the desired system after the corresponding number of cycles is output according to the specific cycle attenuation curve.

[0023] The above scheme proposes the upper and lower limits of battery cell performance, and regards the upper limit battery cell and the lower limit battery cell as the short board battery cell that becomes the short board of the system due to the highest temperature, thereby realizing the system performance range prediction based on the barrel effect.

[0024] In the above-mentioned battery system performance evaluation method based on boundary construction, the upper limit of the maximum chargeable capacity and the lower limit of the maximum dischargeable capacity constitute the maximum initial capacity retention rate;

[0025] The lower limit of the maximum chargeable capacity and the upper limit of the maximum dischargeable capacity constitute the minimum initial capacity retention rate;

[0026] In E, the first specific cycle decay curve of the short-board battery cell is obtained according to the maximum initial capacity retention rate and the cycle decay curve, and the maximum capacity retention rate is obtained according to the number of cycles;

[0027] According to the minimum initial capacity retention rate and the cycle attenuation curve, a second specific cycle attenuation curve of the short-board battery cell is obtained, and the minimum capacity retention rate is obtained according to the number of cycles;

[0028] From this, the capacity retention rate range after the corresponding number of cycles is obtained.

[0029] In the above-mentioned battery system performance evaluation method based on boundary construction, A specifically includes:

[0030] A1. Perform a single cell test on the target battery cell to obtain the cycle attenuation curves of the target battery cell at at least two different temperatures;

[0031] A2. Construct the cycle decay curves of the target battery cell at various temperatures based on the cycle decay curves at at least two different temperatures.

[0032] In the above-mentioned battery system performance evaluation method based on boundary construction, in A2, the Arrhenius equation is used to construct the cycle decay curves of the target battery cell at various temperatures based on the cycle decay curves at at least two different temperatures.

[0033] The above technical solution constructs the cycle attenuation curve of the target model battery cell at various temperatures by using the Arrhenius formula, and then obtains the cycle attenuation curve of the short-board battery cell according to the temperature field distribution of the desired system, thereby realizing the performance prediction of the desired system.

[0034] In the above-mentioned battery system performance evaluation method based on boundary construction, in A1, multiple groups of charge and discharge cycle comparison test experiments are carried out on the target battery cell under the same constant working conditions, and data at the beginning and end of the charge and discharge cycle under at least two groups of temperature conditions are collected to fit the change curve of the battery cell capacity retention rate with the number of cycles, that is, the cycle attenuation curve.

[0035] In the above-mentioned battery system performance evaluation method based on boundary construction, in A, a long-term static experiment is performed on the target battery cell at room temperature, the change of the battery cell capacity retention rate at room temperature with time is collected, and the change curve of the battery cell capacity retention rate with the static time is obtained by fitting, that is, the static attenuation curve;

[0036] In E, the capacity retention rate or capacity retention rate range of the desired system is output according to the specific cycle attenuation curve and static attenuation curve of the short-board battery cell as well as the input number of cycles and static time.

[0037] The advantages of the present invention are:

[0038] 1) On the one hand, this solution summarizes a variety of influencing factors, including the initial conditions of the target model battery cell, the cycle attenuation conditions of the target model battery cell, the static attenuation conditions, and the temperature field distribution of the desired system, etc., which improves the accuracy of the prediction; on the other hand, since it is a performance prediction based on the battery cell, it can adjust the prediction of the desired system with the same process and the same structure for the specific target model battery cell, thereby improving the flexibility of the prediction;

[0039] 2) This scheme obtains the upper and lower boundary values ​​of the target model battery cell capacity by using probability statistics to find the confidence interval, and obtains the limit conditions of the target model battery cell. At the same time, the cycle attenuation curve and static attenuation curve of the target model battery cell are obtained through single-cell testing. When evaluating the performance of the battery system using the target model battery cell, the limit conditions of the target model battery cell itself and the temperature field distribution of the desired system are comprehensively considered. Through the short-board effect, the capacity retention rate of the desired system is recursively deduced from the short-board battery cell that considers the limit of the battery cell model itself and the limit temperature of the desired system, thereby realizing the performance evaluation of the battery system starting from the battery cell, with higher prediction and evaluation efficiency and prediction and evaluation capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a flow chart of a battery system performance evaluation method based on boundary construction in Embodiment 1 of the present invention;

[0041] Figure 2 This is a comparison diagram of evaluation results of different levels of a battery system according to the battery system performance evaluation method based on boundary construction in Embodiment 1 of the present invention;

[0042] Figure 3 This is a flow chart of a battery system performance evaluation method based on boundary construction in Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0043] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0044] Embodiment 1

[0045] The present invention provides a battery system performance evaluation method based on boundary construction, such as Figure 1 As shown, the method includes:

[0046] A. Carry out multiple groups of charge and discharge cycle comparison test experiments under the same constant working conditions on the target model battery cell, collect data at the beginning and end of the charge and discharge cycle under at least two groups of temperature conditions, for example, three or four groups of data can also be collected, and after pre-processing, fit to obtain the curve of the change of battery cell capacity retention rate with the number of cycles, that is, the cycle attenuation curve. Several groups of data will obtain several cycle attenuation curves, and then the cycle attenuation curves at any different temperatures are calculated through algorithms. The specific method will be described in detail below;

[0047] B. Perform probability distribution calculation based on the initial capacity difference, residual capacity tolerance and other indicators of the target model announced or provided by the battery manufacturer to obtain the upper and lower boundaries of the short board of the 99% confidence interval of the target model battery. The initial capacity difference of the battery refers to the maximum difference between the upper and lower limits of the maximum chargeable capacity, and the upper limit of the maximum chargeable capacity is regarded as 100%. The residual capacity tolerance refers to the maximum difference between the upper and lower limits of the maximum dischargeable capacity, and the lower limit of the maximum dischargeable capacity is regarded as 0%.

[0048] The upper boundary of the short board is the lower limit of the maximum chargeable capacity of the target model battery cell, and the lower boundary of the short board is the upper limit of the maximum dischargeable capacity of the target model battery cell, representing a battery cell under extreme conditions.

[0049] D. Obtain the temperature field distribution of the desired system, and determine the short board battery cell temperature of the target model battery cell based on the temperature field distribution; since the higher the temperature, the faster the battery cell decays, according to the barrel effect, the highest temperature of the desired system is used as the operating temperature of the system, which is also the operating temperature of the short board battery cell of the desired system;

[0050] E. Place the battery cell of the extreme case in B at the operating temperature to obtain the initial capacity retention rate of the short-board battery cell, and obtain the cycle attenuation curve at the temperature according to the operating temperature obtained above;

[0051] The initial capacity retention rate is taken as the initial value of the cycle decay curve at the corresponding temperature to draw a cycle decay curve to obtain a specific cycle decay curve of the short-board battery cell;

[0052] The specific cyclic decay curve is recursively derived as the cyclic decay curve of the desired system;

[0053] The performance of the desired system composed of target model batteries is evaluated according to the specific cycle attenuation curve, and the capacity retention rate of the desired system at a specific moment can be determined based on the input and output.

[0054] When put into use, the user inputs the number of cycles for the desired system, and the system outputs the capacity retention rate of the desired system after the corresponding number of cycles based on the input number of cycles and the specific cycle decay curve. Since the battery cell in the extreme case used above has the worst performance among the target models within the confidence interval, that is, the battery cell with the lowest initial capacity retention rate, it is placed at the highest temperature. Combining the two extremes, the initial retention rate is the lowest and the decay is the fastest, so this embodiment obtains the lower limit of the performance of the desired system.

[0055] Barrel effect: A barrel is made of several wooden boards, and the amount of water it can hold is also determined by these boards. If one of the boards is very short, the amount of water that can be held in the barrel will be limited, and the short board will become the "limiting factor" (or "short board effect") of the amount of water that can be held in the barrel. If you want to increase the amount of water that can be held in the barrel, you can only replace the short board or lengthen it. People have summarized this rule as the "barrel principle", or "barrel law", also known as the "short board theory".

[0056] Furthermore, a long-term static test is conducted on the target battery cell at room temperature. The ambient temperature has little effect on static decay, so here we only test the static decay change at room temperature of 25 degrees Celsius, collect the change of battery cell capacity retention rate over time at room temperature, and fit the change curve of battery cell capacity retention rate over static time, that is, static decay curve.

[0057] In practical applications, if there are conditions to conduct long-term static experiments at more temperatures to measure the static attenuation changes at different temperatures, of course, the ambient temperature of the location can also be taken into account according to the system. For example, the static attenuation changes under four groups of temperatures can be measured to correspond to spring, summer, autumn, and winter, respectively, and different static attenuation curves can be assigned according to time changes. For example, different static attenuation curves can also be assigned to the system based on different geographical locations and the characteristics of temperature changes in the four seasons.

[0058] At this time, in E, the performance evaluation result of the desired system is output according to the specific cycle attenuation curve and static attenuation curve of the short-board battery cell and the input number of cycles and static time.

[0059] Furthermore, A specifically includes:

[0060] A1. Perform single-cell tests on the target battery model to obtain the cycle attenuation curves of the target battery model at at least two different temperatures;

[0061] A2. Based on the cycle decay curves at at least two different temperatures, use the Arrhenius equation to construct the cycle decay curves of the target model battery cells at various temperatures.

[0062] The specific method is as follows: first, the Arrhenius equation is improved.

[0063] The modified Arrhenius formula is as follows:

[0064] ln(Q loss )=ln(B)-ln(Ea / RT)+zln(Ah)

[0065] Then according to the Arrhenius equivalent equation, ln(Q loss ) can be regarded as a linear function with the same slope about ln(Ah); z is the slope, ln(B)-ln(Ea / RT) is a constant, and z is obtained by fitting different temperature curves;

[0066] According to the values ​​of ln(B)-ln(Ea / RT) at different temperatures, a set of linear equations with two variables was constructed and the values ​​of Ea and B were obtained by solving them; Ea is the experimental activation energy, T is the absolute temperature, and R is the molar gas constant.

[0067] A complete cyclic decay curve at any different temperature can be constructed based on the three Arrhenius parameters obtained.

[0068] Specifically, the derivation of the attenuation calculation formula for different battery cell temperatures includes the logarithmic process and the parameter decomposition process, as follows:

[0069]

[0070] Q loss is the attenuation capacity; D is DOD, DOD is the depth of discharge; Ncycle is the number of cycles; Q0 is the unit discharge capacity; Ah is the cumulative discharge capacity; Crate is the charge and discharge rate;

[0071] k, represents the reaction rate constant at temperature T;

[0072] A, represents the prefactor, i.e. the Arrhenius constant, and its unit is the same as k;

[0073] Ea, experimental activation energy, is a temperature-independent constant with units of J·mol -1 or J.mol -1 ·K-1 ;

[0074] e, the base of natural logarithm.

[0075] In the above example, the desired system can be a battery system, or a battery pack or battery cluster in a battery system. In this embodiment, the performance lower limit is obtained by the above method for any single cell CELL, battery pack PACK, battery cluster RACK and battery system SYSTEM of a battery system, respectively. In units of years, the tester inputs data based on the parameters such as the usual number of cycles and rest time of the desired system in each year for prediction. The results are as follows: Figure 2 As shown, Figure 2 In the figure, the top curve corresponds to the single cell, followed by the battery pack, battery cluster and battery system. It can be seen that the predicted results for the battery pack, battery cluster and battery system of the same system are very close, indicating that the performance evaluation of the system by this scheme is almost unaffected by the scale of the system. By taking the battery cell as the basis, it is possible to evaluate the system of any scale composed of the corresponding type of battery cells.

[0076] Embodiment 2

[0077] This embodiment is similar to the first embodiment, except that this embodiment outputs the interval for the desired system performance indicator, specifically:

[0078] like Figure 3 As shown, in this embodiment, the upper boundary of the short board is the lower limit and upper limit of the maximum chargeable capacity of the target model battery cell, and the lower boundary of the short board is the upper limit and lower limit of the maximum dischargeable capacity of the target model battery cell.

[0079] In E, based on the input number of cycles (or number of cycles and rest time), the capacity retention rate interval of the desired system at the corresponding number of cycles (or number of cycles and rest time) is output according to the specific cycle attenuation curve (or specific cycle attenuation curve and rest attenuation curve).

[0080] Specifically, the upper limit of the maximum chargeable capacity and the lower limit of the maximum dischargeable capacity constitute the maximum initial capacity retention rate, and the lower limit of the maximum chargeable capacity and the upper limit of the maximum dischargeable capacity constitute the minimum initial capacity retention rate.

[0081] In E, the first specific cycle decay curve of the short-board battery cell is obtained according to the maximum initial capacity retention rate and the cycle decay curve, and the maximum capacity retention rate is obtained according to the number of cycles;

[0082] According to the minimum initial capacity retention rate and the cycle attenuation curve, a second specific cycle attenuation curve of the short-board battery cell is obtained, and the minimum capacity retention rate is obtained according to the number of cycles;

[0083] From this, the capacity retention rate range after the corresponding number of cycles is obtained.

[0084] Similarly, if the static time and the static decay curve are involved, the output capacity retention interval is obtained after taking the static time and the static decay curve into consideration. At this time, the performance interval of the desired system is obtained.

[0085] The specific embodiments described herein are merely examples of the spirit of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in similar ways, but they will not deviate from the spirit of the present invention or exceed the scope defined by the appended claims.

Claims

1. A battery system performance evaluation method based on boundary construction, characterized in that: The method includes: A. Conduct single-cell tests on the target battery model, construct cycle attenuation curves of the target battery model at different temperatures, and characterize the capacity retention rate of the battery model as the number of cycles changes; B. Obtain the factory parameters of the target model battery, including initial capacity difference and residual capacity tolerance; C. Obtain the upper and lower boundaries of the short board of the target model battery cell within the set confidence interval based on probability statistics; D. Obtain the temperature field distribution of the desired system, and determine the short board cell temperature of the target model cell based on the temperature field distribution; E. Obtain the initial capacity retention rate of the short-board battery cell based on the upper boundary and the lower boundary of the short board; According to the temperature of the short-board battery cell, the cycle attenuation curve at that temperature is obtained; The initial capacity retention rate is used as the initial value of the cycle decay curve at the corresponding temperature to draw a cycle decay curve to obtain a specific cycle decay curve of the short-board battery cell, and the specific cycle decay curve is recursively deduced as the cycle decay curve of the desired system; The performance of the desired system composed of target model batteries is evaluated according to the specific cycle attenuation curve.

2. The battery system performance evaluation method based on boundary construction according to claim 1, characterized in that: The result of the performance evaluation includes the capacity retention rate of the desired system at a specific moment.

3. The battery system performance evaluation method based on boundary construction according to claim 2 is characterized in that: The upper boundary of the short board is the lower limit of the maximum chargeable capacity of the target model battery cell, and the lower boundary of the short board is the upper limit of the maximum dischargeable capacity of the target model battery cell; In E, based on the input cycle number, the capacity retention rate of the desired system after the corresponding number of cycles is output according to the specific cycle decay curve.

4. The battery system performance evaluation method based on boundary construction according to claim 2, characterized in that: The upper boundary of the short board is the lower limit and upper limit of the maximum chargeable capacity of the target model battery cell, and the lower boundary of the short board is the upper limit and lower limit of the maximum dischargeable capacity of the target model battery cell; In E, based on the input number of cycles, the capacity retention rate range of the desired system after the corresponding number of cycles is output according to the specific cycle attenuation curve.

5. The battery system performance evaluation method based on boundary construction according to claim 4 is characterized in that: The upper limit of the maximum chargeable capacity and the lower limit of the maximum dischargeable capacity constitute the maximum initial capacity retention rate; The lower limit of the maximum chargeable capacity and the upper limit of the maximum dischargeable capacity constitute the minimum initial capacity retention rate; In E, the first specific cycle decay curve of the short-board battery cell is obtained according to the maximum initial capacity retention rate and the cycle decay curve, and the maximum capacity retention rate is obtained according to the number of cycles; According to the minimum initial capacity retention rate and the cycle attenuation curve, a second specific cycle attenuation curve of the short-board battery cell is obtained, and the minimum capacity retention rate is obtained according to the number of cycles; From this, the capacity retention rate range after the corresponding number of cycles is obtained.

6. The battery system performance evaluation method based on boundary construction according to any one of claims 2 to 5, characterized in that: A specifically includes: A1. Perform a single cell test on the target battery cell to obtain the cycle attenuation curves of the target battery cell at at least two different temperatures; A2. Construct the cycle decay curves of the target battery cell at various temperatures based on the cycle decay curves at at least two different temperatures.

7. The battery system performance evaluation method based on boundary construction according to claim 6, characterized in that: In A2, the Arrhenius equation is used to construct the cycle decay curves of the target battery cell at various temperatures based on the cycle decay curves at at least two different temperatures.

8. The battery system performance evaluation method based on boundary construction according to claim 7 is characterized in that: In A1, multiple groups of charge and discharge cycle comparison test experiments are carried out on the target battery cell under the same constant working conditions, and data from the beginning and end of the charge and discharge cycle under at least two groups of temperature conditions are collected to fit the curve of the change of battery cell capacity retention rate with the number of cycles, that is, the cycle attenuation curve.

9. The battery system performance evaluation method based on boundary construction according to claim 8, characterized in that: In A, a long-term static experiment is performed on the target battery cell at room temperature, and the change of the battery cell capacity retention rate at room temperature over time is collected, and a curve of the change of the battery cell capacity retention rate over the static time is obtained by fitting, that is, the static attenuation curve; In E, the capacity retention rate or capacity retention rate range of the desired system is output according to the specific cycle attenuation curve and static attenuation curve of the short-board battery cell as well as the input number of cycles and static time.

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