Method for measuring optimal charging temperature interval of sodium ion battery cell

Abstract

The invention relates to a method for measuring an optimal charging temperature interval of sodium ion cells, which comprises the following steps of: placing a plurality of cells of the same batch in battery test cabinets at different temperatures in a gradient manner for constant volume, eliminating a gradient preselection item with a relatively large difference with a preset rated capacity, and further screening the residual gradient cells to obtain the optimal charging temperature interval of the sodium ion cells. Carrying out 1C cycle test at different temperatures, recording the capacity retention ratio, the DC internal resistance of the battery cell and the charging and discharging efficiency when the battery cell circulates to a stable state, balancing the index proportion, carrying out mathematical modeling, and adopting a quadratic regression model to obtain the optimal charging temperature interval of the sodium ion battery cell. According to the method for rapidly determining the optimal charging temperature interval of the sodium-ion battery, the optimal charging temperature interval of the sodium-ion battery can be conveniently, rapidly and accurately obtained through the method, the performance loss and waste of the sodium-ion battery can be reduced, the charging and discharging efficiency of the battery is improved, and the service life of the battery is prolonged.

Description

Technical Field

[0001] The present invention belongs to the technical field of analyzing battery performance by testing electrochemical variables, and particularly relates to a method for determining the optimal charging temperature range of a sodium-ion battery cell. Background Art

[0002] A sodium-ion battery is a secondary battery in which the charging and discharging processes are achieved by continuously embedding and de-embedding Na + in the positive and negative electrodes of the battery. The positive electrode material of the sodium-ion battery mainly consists of layered transition metal oxides, polyanion-type compounds or Prussian blue compounds, which are important factors affecting the cell voltage and cycle stability. During the charging process, sodium ions will be removed from the positive electrode material, flow through the electrolyte, and be embedded in the negative electrode. The negative electrode material of the sodium-ion battery is mainly hard carbon or titanium-based material. During the discharging process, sodium ions will flow back into the positive electrode from the negative electrode, and electrons form an electric current through the external circuit.

[0003] The sodium-ion battery has a wider charging temperature adaptation range than the lithium-ion battery. At low temperatures, since the Stokes radius of sodium ions in the sodium-ion battery is smaller, the migration resistance of sodium ions in the electrolyte will be reduced, and the conductivity will also be better. Therefore, the capacity retention rate of the sodium-ion battery is often better than that of the lithium-ion battery at low temperatures. At high temperatures, the thermal decomposition temperature of the commonly used positive electrode material of the sodium-ion battery is also higher, and the chemical properties of sodium also make it less likely to undergo side reactions at high temperatures. That is, the sodium-ion battery has better high-temperature stability than the lithium-ion battery.

[0004] The sodium-ion battery has obvious advantages over the lithium-ion battery in terms of low-temperature performance and high-temperature safety. However, for its optimal charging temperature, due to the diversity of its material system and reaction kinetics, the prior art does not give a definite optimal charging temperature range, nor a method for determining the optimal charging temperature range. With the maturity of sodium-ion battery technology and the advancement of research results, it is found that the capacity, efficiency, and internal resistance of the battery at different temperatures have a crucial impact on the battery performance. Studying its optimal battery charging temperature range is beneficial to reducing the loss and waste of battery performance and extending the service life of the battery. Summary of the Invention

[0005] The present invention discloses a method for determining the optimal charging temperature range of a sodium-ion battery cell, which can obtain the optimal charging temperature of the sodium-ion battery during cycling at different temperatures, thereby determining the optimal charging temperature range and realizing the improvement of the performance of the sodium-ion battery.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is as follows: A method for determining the optimal charging temperature range of a sodium-ion battery cell, comprising the following steps: Step 1: Constantly volume the sodium-ion battery cells with the same consistency at different temperatures to obtain the actual capacities of the sodium-ion battery cells at different temperatures; Step 2: Screen out the corresponding temperatures within the preset rated capacity deviation range of the actual capacity. Perform charge and discharge cycle tests on the sodium-ion battery cells at the screened temperatures respectively. After they cycle to a stable state, record the capacity retention rate, the DC internal resistance of the battery cell, and the charge and discharge efficiency of the sodium-ion battery cells at each temperature; Step 3: Mathematically model the best charging performance index F(T) based on the capacity retention rate, the DC internal resistance of the battery cell, and the charge and discharge efficiency. Assume that there is a quadratic function relationship between F(T) and the temperature T. Fit the quadratic model, calculate the coefficients of the quadratic function, substitute the calculated coefficients into the original quadratic function, and take the derivative of the quadratic function. Let the derivative be 0 to solve for the best charging temperature T; Step 4: Use the R 2 value to verify the quadratic regression model; Step 5: After passing the verification, expand the temperature range of the obtained best charging temperature T to obtain the best charging temperature range of the sodium-ion battery cells.

[0007] Furthermore, in the above Step 1, there are multiple sodium-ion battery cells at each temperature and the number is the same. The actual capacity at each temperature is averaged.

[0008] Furthermore, in the above Step 1, the different temperatures are specifically selected as the following temperatures: -20°C, -10°C, 0°C, 10°C, 15°C, 20°C, 25°C, 30°C, 35°C, 40°C, 50°C, 60°C.

[0009] Furthermore, in the above Step 2, screen out the corresponding temperatures within the range of ±3% of the rated capacity of the actual capacity.

[0010] Furthermore, in the above Step 2, when the sodium-ion battery cell cycles to the same number of weeks and satisfies that the change rate compared with the previous cycle is less than 0.05%, it enters the stable state.

[0011] Furthermore, in the above Step 2, the sodium-ion battery cells are subjected to 1C discharge current cycle tests at different temperatures.

[0012] Furthermore, in the above Step 2, the data of the capacity retention rate, the DC internal resistance of the battery cell, and the charge and discharge efficiency are obtained in the following manner: Capacity retention rate calculation formula: Capacity retention rate = (ending capacity / initial capacity) × 100% Charge and discharge efficiency calculation formula: Charge and discharge efficiency = [(discharge current × time to discharge to cut-off voltage) / (charging current × charging time)] × 100% The method for measuring the DC internal resistance of the battery cell is as follows: 1): Use the 50% SOC and 20% SOC of the sodium-ion battery cells at each temperature as calibration points; 2): Select to measure the DC internal resistance when the battery cell cycle enters the stable state; 3): When measuring the DC internal resistance of the sodium-ion battery cell, select a current of 2C and a time point of 2S; 4): The calculation formula for the DC internal resistance is as follows: , where DcIR is the DC internal resistance, V1 is the voltage value during 2C discharge for 2S, and V0 is the static voltage value at 50% SOC or 20% SOC.

[0013] Further, in step 3), F(T) = ω1 × capacity retention rate + ω2 × charge-discharge efficiency - ω3 × [(DC internal resistance / reference internal resistance) - 1], where ω1 is the weight coefficient of the battery cell capacity retention rate, ω2 is the weight coefficient of the battery cell charge-discharge efficiency, ω3 is the weight coefficient of the battery cell DC internal resistance, and the reference internal resistance is the set standard value of the internal resistance of the sodium-ion battery cell; The quadratic relationship expression between F(T) and temperature T is: y = aT² + bT + c. Use the least squares method for fitting, calculate the linear regression equation, calculate the values of a, b, and c, substitute the calculated values of a, b, and c into y = aT² + bT + c, take the derivative and set the derivative to 0 to obtain .

[0014] Further, in step 4), the formula for R² is as follows:

[0015] In the above formula, SS E is the sum of squared residuals, that is, the sum of the squares of the differences between the actual values and the model predicted values; SS T is the total sum of squared deviations, that is, the sum of the squares of the differences between the actual values and the actual mean values.

[0016] Further, in step 5), take T ± 5°C as the optimal charging temperature range of the sodium-ion battery cell.

[0017] The present invention provides a method for quickly determining the optimal charging temperature range of a sodium-ion battery. Through this method, the optimal charging temperature range of the sodium-ion battery can be obtained conveniently, quickly, and accurately, which helps to reduce the performance loss and waste of the sodium-ion battery and improve the charge-discharge efficiency and service life of the battery. Description of the Drawings

[0018] Figure 1 is a flowchart of the method for determining the optimal charging temperature range of the sodium-ion battery cell of the present invention. Detailed Embodiments

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0020] This embodiment discloses a method for determining the optimal charging temperature range of a sodium-ion battery cell. As shown in Figure 1 the following, this method includes the following steps: Step 1: Take multiple sodium-ion battery cells of the same batch with the same consistency, and place them in a battery test cabinet at different temperatures in gradients for constant volume to obtain the actual capacity of the battery cells.

[0021] Specifically, in this embodiment, sodium-ion batteries with the model 33140 are selected for testing. The rated capacity of this battery is 10 Ah, and the temperature gradient is designed as follows: -20°C, -10°C, 0°C, 10°C, 15°C, 20°C, 25°C, 30°C, 35°C, 40°C, 50°C, 60°C. For this test, 3 battery cells are taken at each temperature, and a total of 36 battery cells are used at 12 temperatures. The above battery cells are placed in a battery test cabinet with a range of 5V 30Ah for constant volume, and the battery cells with abnormal capacity are excluded to obtain the average actual capacity data of the battery cells at each temperature. The average actual capacity data obtained from this test is shown in Table 1: Table 1

[0022] Step 2: Exclude the temperature pre-options with a large difference between the actual capacity and the preset rated capacity. Perform 1C charge and discharge cycle tests on the sodium-ion battery cells at the selected temperatures respectively. After they cycle to a stable state, record the capacity retention rate, the DC internal resistance of the battery cells, and the charge and discharge efficiency at each temperature.

[0023] Specifically, based on the data in Table 1, during this screening, the corresponding temperatures with the average actual capacity within ±3% of the rated capacity are retained, and the temperatures that do not meet the above requirements are excluded. That is, the temperature range selected for this test is 10°C to 40°C (subsequent tests are carried out at 10°C, 15°C, 20°C, 25°C, 30°C, 35°C, 40°C respectively). During the cycle test of the battery cells, when the sodium-ion battery cells cycle to the same number of weeks (350 weeks are selected in this case) and meet that the change rate is less than 0.05% compared with the previous cycle, they enter a stable state. Then record the capacity retention rate, the DC internal resistance of the battery cells, and the charge and discharge efficiency at each temperature.

[0024] Among them, the capacity retention rate of the battery cell is the ratio of the remaining capacity to the initial capacity under certain conditions. In sodium-ion battery cells, controlling capacity decay and maintaining the stability of the electrode is the path to enhance the capacity retention rate of the battery cell, and its proportion in the battery cell performance is 30% to 40%. The calculation formula of the capacity retention rate is as follows: Capacity retention rate = (Ending capacity / Initial capacity) × 100% The charge-discharge efficiency of the battery cell is the ratio of the output energy to the input energy during the charge-discharge process of the battery cell, which can intuitively reflect the proportion of energy conversion loss and is a crucial indicator representing the performance of the battery cell. Its proportion in the battery cell performance is 40% - 50%. The calculation formula for the charge-discharge efficiency is as follows: Charge-discharge efficiency = [(Discharge current × Time to discharge cut-off voltage) / (Charge current × Charge time)] × 100% The DC internal resistance of the battery cell refers to the resistance to current inside the battery, which is an important indicator affecting the charge-discharge efficiency and temperature of the battery cell. Its proportion in the battery cell performance is 10% - 20%. The DC internal resistance of the battery cell at each temperature is measured as follows: 1): Take 50% SOC and 20% SOC of the sodium-ion battery cell at each temperature as the calibration points; 2): Select to measure the DC internal resistance when the battery cell is cycled to 350 weeks; 3): When measuring the DC internal resistance of the sodium-ion battery cell, select a current of 2C and a time point of 2S; 4): The calculation formula for the DC internal resistance is as follows: , where DcIR is the DC internal resistance, V1 is the voltage value during 2C discharge for 2S, and V0 is the static voltage value at 50% SOC or 20% SOC.

[0025] After the test in this step, the data in Table 2 is obtained: Table 2 In the above Table 2, the data of the capacity retention rate, charge-discharge efficiency, and internal resistance ratio are all the corresponding average values. The internal resistance ratio is the average ratio of the actual DC internal resistance of the battery cell to the reference internal resistance. For the battery cells tested this time, the reference internal resistance is 2.20 mΩ, and the reference internal resistance is the internal resistance setting standard value of this production batch of the battery cell.

[0026] Step 3: Let F(T) be the optimal charging performance index, and let F(T) = ω1 × Capacity retention rate + ω2 × Charge-discharge efficiency - ω3 × [(DC internal resistance / Reference internal resistance) - 1], where ω1 is the weight coefficient of the capacity retention rate of the battery cell, ω2 is the weight coefficient of the charge-discharge efficiency of the battery cell, and ω3 is the weight coefficient of the DC internal resistance of the battery cell. In this test, ω1 = 0.3, ω2 = 0.5, and ω3 = 0.2. Substitute the data in Table 2 into the F(T) expression, and the data in Table 3 can be obtained: Table 3 Step 4: Establish a quadratic regression equation, fit its parameters, use the least squares method to fit the quadratic model, calculate its linear regression equation, calculate the coefficients a, b, c, and take the derivative of the quadratic function. Set the derivative to 0, and you can solve the optimal charging temperature T. .

[0027] Establish a quadratic model: y=aT²+bT+c, and use the least squares method to list the following normal equations:

[0028] In the above formula, n is the number of variables with different temperatures T as independent variables; y is the best charging performance index obtained at different temperatures according to the experimental data in step 3 above. By combining the above equations, we can get constants a=-0.0000662, b=0.003062, c=0.7440. Substituting the above constants a, b, and c into the quadratic function relationship, we can get: y=-0.0000662T 2 +0.003062T+0.7440, differentiate the quadratic function, set the derivative y=0, and you can get the optimal charging temperature T=23.127℃, that is, the derived value T is the optimal charging temperature value of the battery cell.

[0029] Step 5: Use R 2 The quadratic regression model was validated.

[0030]

[0031] The formula for R² is:

[0032] SS E is the residual sum of squares, that is, the sum of squares of the differences between the actual values ​​and the values ​​predicted by the model.

[0033] SS T is the total sum of squared deviations, that is, the sum of squares of the differences between the actual values ​​and the actual mean.

[0034]

[0035] In this test, , Based on the above formula, the data shown in Table 4 can be obtained: Table 4

[0036] According to the data in Table 4 and the above expression, we can get:

[0037] The closer the R² value is to 1, the better the model fitting degree. Generally, R2≥0.65 represents that the model has a high fitting degree. The R² value in this test already meets the above requirements, indicating that the model of the present invention has a high fitting degree.

[0038] Step Six: Through the above verification, it is known that the model of the present invention meets the requirements. In order to more conveniently control the optimal charging temperature in practice, the temperature range can be appropriately expanded according to the obtained optimal charging temperature T. In this embodiment, take T±5℃ as the optimal charging temperature range of the sodium-ion battery cell, that is, the optimal temperature range is 18℃~28℃.

[0039] Step Seven: Verify the obtained optimal temperature range of 18℃~28℃ through the embodiment. Continue to cycle the battery cells in this test to 500 weeks and record their capacity retention rate. After cycling 500 weeks, the capacity retention rate data of the battery cells are shown in Table 5: Table 5

[0040] The data in Table 5 above show that when the charging temperature is between 18 and 28℃, the capacity retention rate of the battery cell is the best. Therefore, through this verification, 18~28℃ is the optimal charging temperature range of the experimental battery cell, which also indicates that the determination method given by the present invention is feasible.

[0041] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for determining the optimal charging temperature range of a sodium-ion battery cell, characterized in that: It includes the following steps: Step 1: Constantly volume the sodium-ion battery cells with the same consistency at different temperatures to obtain the actual capacities of the sodium-ion battery cells at different temperatures. Step 2: Screen out the corresponding temperatures within the preset rated capacity deviation range of the actual capacity. Perform charge and discharge cycle tests on the sodium-ion battery cells at the screened temperatures respectively. After they cycle to a stable state, record the capacity retention rate, the DC internal resistance of the battery cell, and the charge and discharge efficiency of the sodium-ion battery cells at each temperature. Step 3: Mathematically model the best charging performance index F(T) based on the capacity retention rate, the DC internal resistance of the battery cell, and the charge and discharge efficiency. Assume that there is a quadratic function relationship between F(T) and temperature T. Fit the quadratic model, calculate the coefficients of the quadratic function, substitute the calculated coefficients into the original quadratic function, and take the derivative of the quadratic function. Let the derivative be 0, then the best charging temperature T can be solved. Step 4: Use the R 2 value to verify the quadratic regression model; Step 5: After passing the verification, expand the temperature range of the obtained best charging temperature T to obtain the best charging temperature range of the sodium-ion battery cells.

2. The method for determining the optimal charging temperature range of a sodium-ion battery cell according to claim 1, wherein: In the above Step 1, there are multiple sodium-ion battery cells at each temperature and the number is the same. The actual capacity at each temperature is averaged.

3. The method for determining the optimal charging temperature range of a sodium ion battery cell according to claim 1, wherein: In the above Step 1, the different temperatures are specifically selected as follows: -20°C, -10°C, 0°C, 10°C, 15°C, 20°C, 25°C, 30°C, 35°C, 40°C, 50°C, 60°C.

4. The method for determining the optimal charging temperature range of a sodium-ion battery cell according to claim 1, characterized in that: In the above Step 2, screen out the corresponding temperatures within the range of ±3% of the rated capacity of the actual capacity.

5. The method for determining the optimal charging temperature range of a sodium-ion battery cell according to claim 1, wherein: In the above Step 2, when the sodium-ion battery cells cycle to the same number of weeks and satisfy that the change rate is less than 0.05% compared with the previous cycle, it enters the stable state.

6. The method for determining the optimal charging temperature range of a sodium ion battery cell according to claim 1, characterized in that: In the above Step 2, the sodium-ion battery cells are subjected to 1C discharge current cycle tests at different temperatures.

7. The method for determining the optimal charging temperature range of a sodium ion battery cell according to claim 1, wherein: In the above Step 2, the data of the capacity retention rate, the DC internal resistance of the battery cell, and the charge and discharge efficiency are obtained in the following manner: Capacity retention rate calculation formula: Capacity retention rate = (ending capacity / initial capacity) × 100% Charge and discharge efficiency calculation formula: Charge and discharge efficiency = [(discharge current × discharge time to cut-off voltage) / (charge current × charge time)] × 100% The method for measuring the DC internal resistance of the battery cell is as follows: 1): Take 50% SOC and 20% SOC of the sodium-ion battery cells at each temperature as the calibration points. 2): Select to measure the DC internal resistance when the battery cell cycles into the stable state. 3): When measuring the DC internal resistance of the sodium-ion battery cells, select a current of 2C and a time point of 2S. 4): The calculation formula for the DC internal resistance is as follows: , where DcIR is the DC internal resistance, V1 is the voltage value during 2C discharge for 2S, and V0 is the static voltage value at 50% SOC or 20% SOC.

8. A method for determining the optimal charging temperature range of a sodium-ion battery cell according to claim 1, characterized in that: In the above Step 3, F(T) = ω1 × capacity retention rate + ω2 × charge and discharge efficiency - ω3 × [(DC internal resistance / reference internal resistance) - 1], where ω1 is the weight coefficient of the capacity retention rate of the battery cell, ω2 is the weight coefficient of the charge and discharge efficiency of the battery cell, ω3 is the weight coefficient of the DC internal resistance of the battery cell, and the reference internal resistance is the set standard value of the internal resistance of the sodium-ion battery cell. The quadratic relationship expression between F(T) and temperature T is: y = aT² + bT + c. The least squares method is used for fitting to calculate the linear regression equation, and the values of a, b, and c are calculated. Substitute the calculated values of a, b, and c into y = aT² + bT + c, take the derivative and set the derivative to 0 to obtain .

9. The method for determining the optimal charging temperature range of a sodium ion battery cell according to claim 1, characterized in that: In the above Step 4, the formula for R² is as follows: ， In the above formula, SS E is the sum of squared residuals, that is, the sum of the squares of the differences between the actual values and the model predicted values; SS T is the total sum of squared deviations, that is, the sum of the squares of the differences between the actual values and the actual mean.

10. The method for determining the optimal charging temperature range of a sodium ion battery cell according to claim 1, wherein: In the above Step 5, take T ± 5°C as the best charging temperature range of the sodium-ion battery cells.

Images