A parameter identification method and device of a battery equivalent circuit and a battery cell

Abstract

The application discloses a parameter identification method and device of a battery equivalent circuit and a battery unit, belongs to the technical field of battery models, is suitable for a second-order RC equivalent circuit of a battery, and comprises the following steps: performing electrochemical impedance spectrum (EIS) test on the battery at a target temperature and a target SOC, obtaining electrochemical impedance spectrum under high-frequency excitation, and identifying an accurate value of the internal resistance R0 of the battery; performing hybrid pulse power characteristic (HPPC) test on the battery at the target temperature and the target SOC, obtaining voltage and current response data under short-time pulse current excitation and long-time pulse current excitation respectively, and identifying accurate parameter values of polarization RC branches and diffusion RC branches. The weighted identification method comprises the following steps: obtaining multiple sets of accurate parameter values by using the parameter identification method and performing weighted summation to obtain final accurate parameter values. The application has the characteristics of high precision, simple calculation and strong working condition adaptability.

Description

Technical Field

[0001] This invention relates to the field of battery modeling technology, and in particular to a method, device and battery cell for identifying parameters of a battery equivalent circuit. Background Technology

[0002] Accurate battery models are fundamental for battery state-of-the-art (SOC, SOH) estimation and energy management. A second-order RC equivalent circuit model of a battery is shown below. Figure 1 As shown, it is widely used due to its good balance between accuracy and complexity. The model parameters (ohmic internal resistance R0, polarization resistance and polarization capacitance R1 / C1, diffusion resistance and diffusion capacitance R2 / C2) will change with factors such as temperature, SOC, and aging degree, so they need to be accurately identified.

[0003] Existing parameter identification technologies have the following main shortcomings:

[0004] 1. Only applicable to specific operating conditions: HPPC testing is mainly for pulse current conditions ranging from several seconds to tens of seconds, which cannot accurately reflect the low-frequency response characteristics of the battery during long-term charging and discharging, resulting in inaccurate identification of R2 / C2 parameters.

[0005] 2. Parameter Aliasing Issue: In HPPC testing, due to the time-scale coupling between the response of R0 (milliseconds) and the responses of R1 and R2 (seconds to hundreds of seconds), the identified value of R0 actually includes some unattenuated mid-to-high frequency polarization resistance, rather than pure ohmic resistance, introducing a systematic error. This error will propagate and affect the identification accuracy of R1, C1, R2, and C2.

[0006] 3. Limitations of online identification algorithms: Although online identification algorithms based on recursive least squares (RLS) and extended Kalman filter (EKF) can update parameters in real time, they are complex, computationally expensive, and require high computing power from microcontrollers (MCUs), which increases the hardware cost and software complexity of the BMS. They also have convergence and stability issues.

[0007] 4. Poor adaptability to operating conditions: The parameters identified by traditional offline methods under specific short-term pulse conditions are difficult to accurately describe the low-frequency characteristics of the battery during long-term charging and discharging (such as constant current charging and actual driving conditions), resulting in a decrease in the prediction accuracy of the model under complex operating conditions.

[0008] Therefore, there is an urgent need for a parameter identification method that is highly accurate, computationally simple, and adaptable to various working conditions. Summary of the Invention

[0009] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method, device and battery cell for identifying parameters of battery equivalent circuit, thereby solving the technical problems of low accuracy, high complexity and weak adaptability of existing parameter identification methods.

[0010] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0011] In a first aspect, the present invention provides a parameter identification method for a battery equivalent circuit, adaptable to a second-order RC equivalent circuit of a battery, wherein the second-order RC equivalent circuit of the battery includes a battery internal resistance R0 connected in series, a polarized RC branch, and a diffused RC branch; the parameter identification method includes:

[0012] Electrochemical impedance spectroscopy (EIS) was performed on the battery at the target temperature and target SOC to obtain the electrochemical impedance spectrum under high-frequency excitation.

[0013] Based on the electrochemical impedance spectroscopy, the precise value of the battery internal resistance R0 at the target temperature and target SOC was identified.

[0014] At the target temperature and target SOC, the battery was subjected to hybrid pulse power characteristic HPPC test to obtain voltage and current response data under short-time pulse current excitation and long-time pulse current excitation, respectively.

[0015] Based on the voltage and current response data, the precise parameter values ​​of the polarized RC branch and the diffused RC branch at the target temperature and target SOC are identified.

[0016] The parameter identification method provided by this invention utilizes the characteristic that the polarization circuit has not yet responded under high-frequency excitation, ensuring the purity of the battery internal resistance R0 and avoiding the mixing of mid- and low-frequency polarization internal resistance, thus obtaining the accurate value of the battery internal resistance R0. Based on the voltage change curve during the pulse duration, a function fitting method is used to obtain the accurate parameter values ​​of the polarization RC branch and the diffusion RC branch. The overall method features high accuracy, simple calculation, and strong adaptability to operating conditions.

[0017] Optionally, the battery is pretreated before the electrochemical impedance spectroscopy (EIS) test and the hybrid pulse power characteristic (HPPC) test. The pretreatment includes placing the battery in a constant temperature environment at the target temperature, charging / discharging it to the target SOC with a constant current, and letting it stand for a predetermined time.

[0018] Preprocessing ensures the battery is in a stable state before testing, improving the accuracy of test results and thus guaranteeing the precision of subsequent identification calculations.

[0019] Optionally, obtaining the electrochemical impedance spectroscopy under high-frequency excitation includes:

[0020] An AC excitation signal is applied in the high-frequency region to ensure that the battery is in a linear response state, and the corresponding electrochemical impedance spectrum is obtained.

[0021] The high-frequency region has a frequency range of 1 kHz to 5 kHz, and the amplitude of the AC excitation signal is ≤10mV.

[0022] In the high-frequency region, the polarization effect of the battery can be ignored. At this time, the impedance is mainly composed of the battery internal resistance R0, which ensures the purity of the R0 value and avoids the mixing of mid- and low-frequency polarization internal resistance, which would affect the identification accuracy of the battery internal resistance R0.

[0023] Optionally, the precise value of the battery internal resistance R0 is the impedance value at the intersection of the high-frequency region and the real axis in the Nyquist plot of the electrochemical impedance spectrum.

[0024] In the high-frequency region, the polarization effect of the battery can be ignored. At this time, the impedance is mainly composed of the battery's internal resistance R0. Therefore, the impedance value at the intersection of the high-frequency region and the real axis in the Nyquist plot can be extracted as the battery's internal resistance R0.

[0025] Optionally, the duration of the short-time pulse current excitation is 10s to 60s, and the duration of the long-time pulse current excitation is 5min to 1h.

[0026] The purpose of short-time pulsed current excitation is to capture the voltage jump at the moment of pulse loading, and to roughly identify the parameter values ​​of the polarization RC branch and the diffusion RC branch. Therefore, applying a pulsed current on the order of several seconds to tens of seconds is sufficient. The purpose of long-time pulsed current excitation is to apply a long-term charge-discharge condition. Under this condition, the mid-frequency polarization process has basically reached a steady state, while the low-frequency ion diffusion process is fully manifested, thus allowing for precise identification of the parameter values ​​of the diffusion RC branch. Therefore, applying a pulsed current on the order of several minutes to one hour is necessary. By simulating the actual operating conditions of the battery, the test results are made closer to actual operating conditions, improving the accuracy of subsequent parameter identification.

[0027] Optionally, identifying the precise parameter values ​​of the polarized RC branch and the diffused RC branch at the target temperature and target SOC based on the voltage and current response data includes:

[0028] Construct corresponding response curves based on voltage and current response data under short-time pulse current excitation and long-time pulse current excitation;

[0029] A second-order exponential fit is performed on the zero-input response segment of the response curve under short-time pulse current excitation to calculate the rough parameter values ​​of the polarized RC branch and the diffused RC branch.

[0030] A second-order exponential fit is performed on the zero-input response segment of the response curve under long-term pulse current excitation. The coarse parameter values ​​of the polarized RC branch are added as known quantities to the fitting process to calculate the precise parameter values ​​of the diffused RC branch.

[0031] A second-order exponential fit is performed on the zero-input response segment of the response curve under short-time pulse current excitation. The precise parameter values ​​of the diffused RC branch are added as known quantities to the fitting process to calculate the precise parameter values ​​of the polarized RC branch.

[0032] Under short-time pulsed current excitation, the coarse parameter values ​​of the polarization RC branch and the diffusion RC branch are identified by the voltage jump at the moment of pulse loading. Then, using the coarse parameter value of the polarization RC branch as a known quantity, the precise parameter value of the diffusion RC branch is identified separately under long-time pulsed current excitation. Under this condition, the mid-frequency polarization process has basically reached a steady state, while the low-frequency ion diffusion process is fully manifested. Therefore, the precise parameter value of the diffusion RC branch is highly accurate. Then, using the precise parameter value of the diffusion RC branch as a known quantity, the precise parameter value of the polarization RC branch is re-identified under short-time pulsed current excitation, thus improving its identification accuracy.

[0033] Optionally, the fitting formula for the second-order exponential fit is:

[0034]

[0035] In the formula, For the coordinate points on the response curve, These are the start and end times of the zero-input response segment, respectively. These are the fitting coefficients. For constant terms;

[0036] The formula for the zero-input response segment is:

[0037]

[0038] In the formula, The voltage value of the zero-input response segment. Let R1 be the resistance value and C1 be the capacitance value in the polarized RC branch. Let R2 be the resistance value and C2 be the capacitance value in the diffused RC branch. The time within the zero input response segment, This is the current value of the pulse current. This is the battery open-circuit voltage;

[0039] Combine the fitting equation and the operational equation for the zero-input response segment, and then apply the fitting coefficients... Calculate the parameter values ​​for the polarized RC branch and the diffused RC branch:

[0040]

[0041] .

[0042] The main advantage of second-order exponential fitting lies in its ability to precisely characterize dynamic processes at different time scales, balancing the model's accuracy and practicality. Compared to first-order models, it more accurately describes the voltage relaxation process; compared to higher-order models or intelligent algorithms, its mathematical form is relatively simple, its computational burden is lighter, and it is beneficial for implementation in embedded systems (such as BMS).

[0043] Secondly, the present invention provides a parameter weighting identification method for a battery equivalent circuit, comprising:

[0044] Using the target temperature and target SOC as a baseline, adjust the target temperature and target SOC to obtain the neighboring temperature and neighboring SOC;

[0045] Construct a neighbor group of the benchmark group based on the neighboring temperature and the target SOC, and the target temperature and the neighboring SOC;

[0046] Using the parameter identification method described above, the accurate parameter values ​​of the battery internal resistance R0, polarized RC branch, and diffused RC branch in the reference group and adjacent group are obtained.

[0047] The precise parameter values ​​of the baseline group and the neighboring group are weighted and summed to obtain the final precise parameter values ​​of the battery internal resistance R0, the polarized RC branch, and the diffused RC branch at the target temperature and the target SOC.

[0048] The parameter weighted identification method provided by this invention can integrate the parameter values ​​of the benchmark group and the neighboring group, reducing the random error of single-point identification. At the same time, it can construct the functional relationship between parameters and SOC and temperature more smoothly and accurately, rather than just the mean of discrete points, thus improving the engineering application value of the final parameters.

[0049] Thirdly, the present invention provides a parameter identification device for a battery equivalent circuit, adapted to a second-order RC equivalent circuit of a battery, wherein the second-order RC equivalent circuit of the battery includes a battery internal resistance R0 connected in series, a polarized RC branch, and a diffused RC branch; the parameter identification device includes:

[0050] The EIS test module is configured to perform electrochemical impedance spectroscopy (EIS) tests on the battery at the target temperature and target SOC to obtain the electrochemical impedance spectrum under high-frequency excitation.

[0051] An internal resistance determination module is configured to identify the precise value of the battery internal resistance R0 at the target temperature and target SOC based on the electrochemical impedance spectroscopy.

[0052] The HPPC test module is configured to perform hybrid pulse power characteristic HPPC tests on the battery at the target temperature and target SOC, and to acquire voltage and current response data under short-time pulse current excitation and long-time pulse current excitation, respectively.

[0053] The branch determination module is configured to identify the precise parameter values ​​of the polarized RC branch and the diffused RC branch at the target temperature and target SOC based on the voltage and current response data.

[0054] Optionally, the precise value of the battery internal resistance R0 is the impedance value at the intersection of the high-frequency region and the real axis in the Nyquist plot of the electrochemical impedance spectrum.

[0055] Optionally, the branch determination module is specifically configured as follows:

[0056] Construct corresponding response curves based on voltage and current response data under short-time pulse current excitation and long-time pulse current excitation;

[0057] A second-order exponential fit is performed on the zero-input response segment of the response curve under short-time pulse current excitation to calculate the rough parameter values ​​of the polarized RC branch and the diffused RC branch.

[0058] A second-order exponential fit is performed on the zero-input response segment of the response curve under long-term pulse current excitation. The coarse parameter values ​​of the polarized RC branch are added as known quantities to the fitting process to calculate the precise parameter values ​​of the diffused RC branch.

[0059] A second-order exponential fit is performed on the zero-input response segment of the response curve under short-time pulse current excitation. The precise parameter values ​​of the diffused RC branch are added as known quantities to the fitting process to calculate the precise parameter values ​​of the polarized RC branch.

[0060] Fourthly, the present invention provides a battery cell, including one or more of a battery module, a battery pack, or an energy storage battery, wherein the battery cell uses the parameter identification device, the parameter identification method, or the parameter weighting identification method described above to identify the parameters of the battery equivalent circuit.

[0061] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0062] This invention provides a parameter identification method, device, and battery cell for a battery equivalent circuit. The parameter identification method and device utilize the characteristic that the polarization stage has not yet responded under high-frequency excitation, ensuring the purity of the battery's internal resistance R0 and avoiding the mixing of mid-to-low-frequency polarization internal resistances, thus obtaining an accurate value for the battery's internal resistance R0. Based on the voltage change curve during the pulse duration, a function fitting method is used to obtain accurate parameter values ​​for the polarization RC branch and the diffusion RC branch. The overall method features high accuracy, simple calculation, and strong adaptability to operating conditions. The weighted identification method can integrate parameter values ​​from the benchmark group and neighboring groups, reducing random errors in single-point identification. Simultaneously, it can more smoothly and accurately construct the functional relationship between parameters and SOC and temperature, rather than simply the mean of discrete points, enhancing the engineering application value of the final parameters. In summary, this invention significantly improves the accuracy of model parameters and the overall prediction accuracy of the model by employing strategies such as time-scale decoupling, step-by-step parameter iteration, moving window mean filtering, and temperature interval identification for second-order RC equivalent circuits, while maintaining the advantages of offline algorithms such as simple computation and ease of engineering deployment. Attached Figure Description

[0063] Figure 1 This is a schematic diagram of the second-order RC equivalent circuit of the battery provided by the present invention;

[0064] Figure 2 This is a flowchart illustrating the parameter identification method provided by the present invention;

[0065] Figure 3 These are the electrochemical impedance spectra of the lithium battery provided by this invention at 10% and 20% SOC.

[0066] Figure 4 This is a flowchart of parameter identification for the polarized RC branch and the diffused RC branch provided by the present invention;

[0067] Figure 5 This is a schematic diagram of the response curve of the HPPC test provided by the present invention;

[0068] Figure 6 This is a flowchart illustrating the parameter weighting identification method provided by the present invention. Detailed Implementation

[0069] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0070] Example 1

[0071] like Figure 1 As shown, this embodiment of the invention provides a parameter identification method for a battery equivalent circuit, applicable to a second-order RC equivalent circuit of a battery, such as... Figure 1As shown, the second-order RC equivalent circuit of the battery includes the battery internal resistance R0 connected in series, the polarized RC branch (resistor R1 and capacitor C1 in parallel), and the diffused RC branch (resistor R2 and capacitor C2 in parallel).

[0072] like Figure 2 As shown, the parameter identification method includes the following steps:

[0073] Step S1: At the target temperature and target SOC, perform electrochemical impedance spectroscopy (EIS) on the battery to obtain the electrochemical impedance spectrum under high-frequency excitation.

[0074] Electrochemical impedance spectroscopy (EIS) tests were performed on the battery using an electrochemical workstation. A small AC excitation signal with an amplitude ≤10mV was applied in the high-frequency region (e.g., 1kHz-5kHz) to ensure the battery was in a linear response state. The corresponding electrochemical impedance spectrum was then obtained. The frequency and amplitude can be adjusted by the operator as needed. In the high-frequency region, the battery polarization effect can be ignored, and the impedance is mainly composed of the battery's internal resistance R0.

[0075] Step S2: Identify the precise value of the battery internal resistance R0 at the target temperature and target SOC based on electrochemical impedance spectroscopy.

[0076] The impedance value at the intersection of the high-frequency region and the real axis in the Nyquist plot of the electrochemical impedance spectroscopy is extracted and used as the accurate value of the battery's internal resistance R0. This method utilizes the characteristic that the polarization circuit has not yet responded under high-frequency excitation, ensuring the purity of the R0 value and avoiding the incorporation of mid- and low-frequency polarization internal resistance.

[0077] like Figure 3 The figure shows the electrochemical impedance spectroscopy of a lithium battery at 10% and 20% SOC. The ultra-high frequency part (such as 1kHz-5kHz and above) represents the internal resistance of the battery. The points where the imaginary part is 0 in the figure are the values ​​of R0.

[0078] Step S3: At the target temperature and target SOC, perform hybrid pulse power characteristic (HPPC) tests on the battery to obtain voltage and current response data under short-time pulse current excitation and long-time pulse current excitation, respectively.

[0079] Under target temperature and target SOC, the battery is subjected to HPPC (hybrid pulse power characterization) testing, applying pulse current conditions ranging from several seconds to tens of seconds (e.g., 0.2C-2C pulse current, lasting 10-60 seconds). During the HPPC test, the battery's voltage and current response data under short-term pulse current excitation are recorded.

[0080] Under target temperature and target SOC, the battery is subjected to HPPC (hybrid pulse power characterization) testing, applying pulse current conditions ranging from several minutes to one hour (e.g., 0.1C-1C pulse current, lasting 5-60 minutes). During the HPPC test, the voltage and current response data of the battery under long-term pulse current excitation are recorded.

[0081] The purpose of short-time pulsed current excitation is to capture the voltage jump at the moment of pulse loading, and to roughly identify the parameter values ​​of the polarization RC branch and the diffusion RC branch. Therefore, applying a pulsed current on the order of several seconds to tens of seconds is sufficient. The purpose of long-time pulsed current excitation is to apply a long-term charge-discharge condition. Under this condition, the mid-frequency polarization process has basically reached a steady state, while the low-frequency ion diffusion process is fully manifested, thus allowing for precise identification of the parameter values ​​of the diffusion RC branch. Therefore, applying a pulsed current on the order of several minutes to one hour is necessary. By simulating the actual operating conditions of the battery, the test results are made closer to actual operating conditions, improving the accuracy of subsequent parameter identification.

[0082] Step S4: Identify the precise parameter values ​​of the polarized RC branch and the diffused RC branch at the target temperature and target SOC based on the voltage and current response data.

[0083] like Figure 4 As shown, the specific process includes:

[0084] Step S4.1: Construct the corresponding response curves based on the voltage and current response data under short-time pulse current excitation and long-time pulse current excitation.

[0085] like Figure 5 The figure shows a schematic diagram of the response curve for an HPPC test. The voltage jumps between U1 and U2 and between U3 and U4 are related to the battery's internal resistance R0.

[0086]

[0087] The gradual voltage change process from U2 to U3 and from U4 to U5 is related to R1 / C1 / R2 / C2. According to circuit principles, the current-voltage relationship of an RC circuit is divided into zero-state response and zero-input response. The U2-U3 segment can be considered as the zero-state response, and the U4-U5 segment can be considered as the zero-input response.

[0088] In this embodiment, RC parameter identification is performed using the U4-U5 segment (zero-input response) as an example, and the calculation formula for the zero-input response segment is constructed:

[0089]

[0090] In the formula, The voltage value of the zero-input response segment. Let R1 be the resistance value and C1 be the capacitance value in the polarized RC branch. Let R2 be the resistance value and C2 be the capacitance value in the diffused RC branch. The time within the zero input response segment, This is the current value of the pulse current. This is the battery open-circuit voltage.

[0091] Step S4.2: Perform second-order exponential fitting on the zero-input response segment of the response curve under short-time pulse current excitation, and calculate the rough parameter values ​​of the polarized RC branch and the diffused RC branch.

[0092] A second-order exponential fit is performed on the U4-U5 segment (zero input response).

[0093] The fitting formula is:

[0094]

[0095] In the formula, For the coordinate points on the response curve, These are the start and end times of the zero-input response segment, respectively. These are the fitting coefficients. This is a constant term.

[0096] The main advantage of second-order exponential fitting lies in its ability to precisely characterize dynamic processes at different time scales, balancing the model's accuracy and practicality. Compared to first-order models, it more accurately describes the voltage relaxation process; compared to higher-order models or intelligent algorithms, its mathematical form is relatively simple, its computational burden is lighter, and it is beneficial for implementation in embedded systems (such as BMS).

[0097] The fitting coefficients are obtained through fitting calculations. Then, by combining the fitting equation and the operational equation, the parameter values ​​of the polarized RC branch and the diffused RC branch are calculated:

[0098]

[0099] .

[0100] Step S4.3: Perform second-order exponential fitting on the zero-input response segment of the response curve under long-term pulse current excitation, and add the coarse parameter values ​​of the polarized RC branch as known quantities to the fitting process to calculate the precise parameter values ​​of the diffused RC branch.

[0101] The second-order exponential fitting here is the same as in step S4.2, except that the fitting coefficients in step S4.2 are... As known quantities, refit the fitting coefficients. .

[0102] Step S4.4: Perform second-order exponential fitting on the zero-input response segment of the response curve under short-time pulse current excitation, and add the accurate parameter values ​​of the diffused RC branch as known quantities to the fitting process to calculate the accurate parameter values ​​of the polarized RC branch.

[0103] The second-order exponential fitting here is the same as in step S4.2, except that the fitting coefficients in step S4.3 are... As known quantities, only the fitting coefficients are used. .

[0104] In this embodiment, under short-time pulsed current excitation, the coarse parameter values ​​of the polarization RC branch and the diffusion RC branch are identified by the voltage jump at the moment of pulse loading. Then, using the coarse parameter value of the polarization RC branch as a known quantity, the precise parameter value of the diffusion RC branch is identified separately under long-time pulsed current excitation. Under this condition, the mid-frequency polarization process has basically reached a steady state, while the low-frequency ion diffusion process is fully manifested. Therefore, the precise parameter value of the diffusion RC branch is highly accurate. Then, using the precise parameter value of the diffusion RC branch as a known quantity, the precise parameter value of the polarization RC branch is re-identified under short-time pulsed current excitation, thereby improving its identification accuracy.

[0105] Furthermore, both the electrochemical impedance spectroscopy (EIS) test and the hybrid pulse power characteristic (HPPC) test require pretreatment of the battery. Pretreatment involves placing the battery in a constant-temperature environment at the target temperature, charging / discharging it to the target state of charge (SOC) with a constant current, and then allowing it to stand for a predetermined time. This pretreatment stabilizes the battery before testing, improving the accuracy of the test results and ensuring the precision of subsequent identification calculations.

[0106] In summary, the parameter identification method provided by this invention utilizes the characteristic that the polarization circuit has not yet responded under high-frequency excitation, ensuring the purity of the battery internal resistance R0 and avoiding the mixing of mid- and low-frequency polarization internal resistances, thus obtaining an accurate value for the battery internal resistance R0. Based on the voltage change curve during the pulse duration phase, a function identification method is used to obtain the accurate parameter values ​​of the polarization RC branch and the diffusion RC branch. The overall method features high accuracy, simple calculation, and strong adaptability to operating conditions.

[0107] Taking the parameter identification of a certain 32Ah lithium iron phosphate battery at 25℃ and 50% SOC as an example, the implementation process of this invention is illustrated as follows:

[0108] 1. Battery pretreatment

[0109] Place the battery in a constant temperature chamber and set the temperature to the target temperature range (25°C). Charge and discharge the battery at a constant current (0.33C) to the target SOC point (50%), and let it stand for 2 hours to allow the battery to reach a stable state.

[0110] 2. High-frequency EIS testing and R0 identification

[0111] The battery was subjected to EIS testing using an electrochemical workstation with a frequency range of 1kHz to 5kHz and an excitation signal amplitude of 5mV. In the high-frequency region (>1kHz), electrochemical impedance spectroscopy was acquired, and the internal resistance of the battery was determined to be R0 = 0.012Ω by identifying the impedance data.

[0112] 3. Short-term HPPC operating conditions and preliminary identification of R1 / C1

[0113] The battery was subjected to HPPC testing under constant temperature conditions at the target temperature (25°C):

[0114] Discharge at 1C for 30 seconds

[0115] Let stand for 1 minute

[0116] Charge at 0.75C for 30 seconds

[0117] Let stand for 1 minute

[0118] Voltage and current data during the HPPC test were recorded at a sampling frequency of 100Hz. Based on R0=0.012Ω, a second-order RC model equation was constructed, and the exponential function was initially identified for the short-time HPPC data, yielding rough values ​​of R1=0.015Ω and C1=2400F.

[0119] 4. Accurate identification of long-term HPPC operating conditions and R2 / C2

[0120] The battery was subjected to HPPC testing under constant temperature conditions at the target temperature (25°C):

[0121] Discharge at 0.5C for 10 minutes

[0122] Let stand for 1 hour

[0123] Charge at 0.25C for 20 minutes

[0124] Let stand for 1 hour

[0125] Record voltage and current data during long-term operation. Based on the approximate values ​​of R0=0.012Ω, R1=0.015Ω, and C1=2400F, identify the long-term HPPC data to obtain the precise values ​​of R2=0.0015Ω and C2=2400F.

[0126] 5. Iterative optimization and accurate R1 / C1 identification

[0127] Substituting R0=0.012Ω, R2=0.0015Ω, and C2=2400F back into the short-time HPPC data, we constructed an updated second-order RC model equation. By re-identifying the short-time HPPC data, we obtained the precise values ​​of R1=0.014Ω and C1=2350F.

[0128] Using the parameter identification method provided in this embodiment, the impedance parameters of the battery equivalent circuit under different temperatures (0℃ / 10℃ / 25℃ / 40℃) and different SOCs (0% / 10% / 20% / 30% / 40% / 50% / 60% / 70% / 80% / 90% / 100%) are obtained, as shown in Table 1.

[0129] Table 1: Impedance parameters of the battery equivalent circuit

[0130]

[0131] Table 1 provides a mapping relationship between the parameters of the equivalent circuit and temperature and SOC, thereby improving the temperature adaptability of the model.

[0132] Example 2

[0133] like Figure 6 As shown, this embodiment of the invention provides a parameter weighting identification method for a battery equivalent circuit, including the following steps:

[0134] Step S11: Using the target temperature and target SOC as a reference group, adjust the target temperature and target SOC to obtain the neighboring temperature and neighboring SOC.

[0135] Taking a target temperature of 25℃ and a target SOC of 50% as an example, the adjusted neighboring temperatures are 24℃ and 26℃, and the adjusted neighboring SOCs are 49% and 51%. Staff can set these values ​​according to actual needs.

[0136] Step S12: Construct a neighboring group of the baseline group based on the neighboring temperature and the target SOC, and the target temperature and the neighboring SOC.

[0137] Taking the target temperature of the benchmark group as 25℃ and the target SOC as 50% as an example, examples of the benchmark group and neighboring groups are shown in Table 2.

[0138] Table 2: Examples of baseline and neighboring groups

[0139]

[0140] Step S13: Using the parameter identification method provided in Embodiment 1 above, obtain the accurate parameter values ​​of the battery internal resistance R0, the polarized RC branch, and the diffused RC branch in the reference group and the adjacent group.

[0141] The precise parameter values ​​of the reference group are denoted as: R0, R1, C1, R2, C2.

[0142] The precise parameter values ​​of neighboring group 1 are denoted as: R0_1, R1_1, C1_1, R2_1, C2_1.

[0143] The precise parameter values ​​of neighboring group 2 are denoted as: R0_2, R1_2, C1_2, R2_2, C2_2.

[0144] The precise parameter values ​​of neighboring group 3 are denoted as: R0_3, R1_3, C1_3, R2_3, C2_3.

[0145] The precise parameter values ​​of neighboring group 4 are denoted as: R0_4, R1_4, C1_4, R2_4, C2_4.

[0146] Step S14: Weighted summation of the precise parameter values ​​under the benchmark group and the neighboring group to obtain the final precise parameter values ​​of the battery internal resistance R0, the polarized RC branch and the diffused RC branch at the target temperature and the target SOC.

[0147] A moving window weighted average algorithm is used, with the center of the window receiving the highest weight and the edges receiving lower weights, such as 0.4, 0.15, 0.15, 0.15, 0.15. The target SOC is 50%, and the final parameters of the cell's equivalent circuit at a target temperature of 25℃ are:

[0148] R0_final = R0*0.4 + R0_1*0.15 + R0_2*0.15 + R0_3*0.15 + R0_4*0.15

[0149] R1_final = R1*0.4 + R1_1*0.15 + R1_2*0.15 + R1_3*0.15 + R1_4*0.15

[0150] C1_final = C1*0.4 + C1_1*0.15 + C1_2*0.15 + C1_3*0.15 + C1_4*0.15

[0151] R2_final = R2*0.4 + R2_1*0.15 + R2_2*0.15 + R2_3*0.15 + R2_4*0.15

[0152] C2_final = C2*0.4 + C2_1*0.15 + C2_2*0.15 + C2_3*0.15 + C2_4*0.15

[0153] The parameter weighting identification method provided in this invention can integrate the parameter values ​​of the benchmark group and the neighboring group, reducing the random error of single-point identification. At the same time, it can construct a smoother and more accurate functional relationship between parameters and SOC and temperature, rather than just the mean of discrete points, thus improving the engineering application value of the final parameters.

[0154] Using the parameter weighting identification method provided in this embodiment, the impedance parameters of the battery equivalent circuit under different temperatures (0℃ / 10℃ / 25℃ / 40℃) and different SOCs (0% / 10% / 20% / 30% / 40% / 50% / 60% / 70% / 80% / 90% / 100%) can be obtained. A mapping table of the parameters of the equivalent circuit with temperature and SOC can be established to improve the temperature adaptability of the model.

[0155] Example 3

[0156] This invention provides a parameter identification device for a battery equivalent circuit, adapted to a second-order RC equivalent circuit of a battery. The second-order RC equivalent circuit of a battery includes a battery internal resistance R0, a polarized RC branch, and a diffused RC branch connected in series. The parameter identification device includes:

[0157] The EIS test module is configured to perform electrochemical impedance spectroscopy (EIS) tests on the battery at the target temperature and target SOC to obtain the electrochemical impedance spectrum under high-frequency excitation.

[0158] The internal resistance determination module is configured to identify the precise value of the battery internal resistance R0 at the target temperature and target SOC based on the electrochemical impedance spectroscopy. Specifically, the precise value of the battery internal resistance R0 is the impedance value at the intersection of the high-frequency region and the real axis in the Nyquist plot of the electrochemical impedance spectroscopy.

[0159] The HPPC test module is configured to perform hybrid pulse power characteristic HPPC tests on the battery at the target temperature and target SOC, and to acquire voltage and current response data under short-time pulse current excitation and long-time pulse current excitation, respectively.

[0160] The branch determination module is configured to identify the precise parameter values ​​of the polarized RC branch and the diffused RC branch at the target temperature and target SOC based on voltage and current response data, specifically:

[0161] Construct corresponding response curves based on voltage and current response data under short-time pulse current excitation and long-time pulse current excitation;

[0162] A second-order exponential fit is performed on the zero-input response segment of the response curve under short-time pulse current excitation to calculate the rough parameter values ​​of the polarized RC branch and the diffused RC branch.

[0163] A second-order exponential fit is performed on the zero-input response segment of the response curve under long-term pulse current excitation. The coarse parameter values ​​of the polarized RC branch are added as known quantities to the fitting process to calculate the precise parameter values ​​of the diffused RC branch.

[0164] A second-order exponential fit is performed on the zero-input response segment of the response curve under short-time pulse current excitation. The precise parameter values ​​of the diffused RC branch are added as known quantities to the fitting process to calculate the precise parameter values ​​of the polarized RC branch.

[0165] Example 4

[0166] This invention provides a battery unit, including one or more of a battery module, a battery pack, or an energy storage battery. The battery unit uses the parameter identification device provided in Embodiment 3 above, or the parameter identification method provided in Embodiment 1 above, or the parameter weighted identification method provided in Embodiment 2 above to identify the parameters of the battery equivalent circuit.

[0167] Power batteries (battery modules, battery packs) are power supply devices that provide power to electric vehicles, electric trains, electric ships, etc. The main types include lead-acid batteries and lithium iron phosphate batteries; nickel-metal hydride batteries are also used in hybrid vehicles. By accurately identifying the parameters of the battery equivalent circuit of the battery pack, a battery model can be accurately constructed, enabling accurate estimation of battery state (such as SOC and SOH) and energy management.

[0168] Energy storage batteries are key devices for storing electrical energy in renewable energy systems, primarily used in solar and wind power generation equipment. Product types include lead-acid batteries (including vented, valve-regulated, and gel types) and lithium-ion batteries (represented by lithium iron phosphate). By accurately identifying the parameters of the battery's equivalent circuit, a battery model can be accurately constructed, enabling accurate battery state estimation and energy management.

[0169] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0170] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0171] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0172] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0173] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A parameter identification device for a battery equivalent circuit, adapted to a second-order RC equivalent circuit of a battery, wherein the second-order RC equivalent circuit of the battery includes a battery internal resistance R0, a polarized RC branch, and a diffused RC branch connected in series; characterized in that, The parameter identification device includes: The EIS test module is configured to perform electrochemical impedance spectroscopy (EIS) tests on the battery at the target temperature and target SOC to obtain the electrochemical impedance spectrum under high-frequency excitation. An internal resistance determination module is configured to identify the precise value of the battery internal resistance R0 at the target temperature and target SOC based on the electrochemical impedance spectroscopy. The HPPC test module is configured to perform hybrid pulse power characteristic HPPC tests on the battery at the target temperature and target SOC, and to acquire voltage and current response data under short-time pulse current excitation and long-time pulse current excitation, respectively. The branch determination module is configured to identify precise parameter values ​​of the polarized RC branch and the diffused RC branch at the target temperature and target SOC based on the voltage and current response data, including: Construct corresponding response curves based on voltage and current response data under short-time pulse current excitation and long-time pulse current excitation; A second-order exponential fit is performed on the zero-input response segment of the response curve under short-time pulse current excitation to calculate the rough parameter values ​​of the polarized RC branch and the diffused RC branch. A second-order exponential fit is performed on the zero-input response segment of the response curve under long-term pulse current excitation. The coarse parameter values ​​of the polarized RC branch are added as known quantities to the fitting process to calculate the precise parameter values ​​of the diffused RC branch. A second-order exponential fit is performed on the zero-input response segment of the response curve under short-time pulse current excitation. The precise parameter values ​​of the diffused RC branch are added as known quantities to the fitting process to calculate the precise parameter values ​​of the polarized RC branch. The fitting formula for the second-order exponential fit is: ； In the formula, For the coordinate points on the response curve, These are the start and end times of the zero-input response segment, respectively. These are the fitting coefficients. For constant terms; The formula for the zero-input response segment is: ； In the formula, The voltage value of the zero-input response segment. Let R1 be the resistance value and C1 be the capacitance value in the polarized RC branch. Let R2 be the resistance value and C2 be the capacitance value in the diffused RC branch. The time within the zero input response segment, This is the current value of the pulse current. This is the battery open-circuit voltage; Combine the fitting equation and the operational equation for the zero-input response segment, and then apply the fitting coefficients... Calculate the parameter values ​​for the polarized RC branch and the diffused RC branch: ； 。 2. The parameter identification device for the battery equivalent circuit according to claim 1, characterized in that, The precise value of the battery internal resistance R0 is the impedance value at the intersection of the high-frequency region and the real axis in the Nyquist plot of the electrochemical impedance spectrum.

3. A method for parameter identification of a battery equivalent circuit, applicable to a second-order RC equivalent circuit of a battery, wherein the second-order RC equivalent circuit of the battery includes a battery internal resistance R0 connected in series, a polarized RC branch, and a diffused RC branch; characterized in that, The parameter identification method includes: Electrochemical impedance spectroscopy (EIS) was performed on the battery at the target temperature and target SOC to obtain the electrochemical impedance spectrum under high-frequency excitation. Based on the electrochemical impedance spectroscopy, the precise value of the battery internal resistance R0 at the target temperature and target SOC was identified. At the target temperature and target SOC, the battery was subjected to hybrid pulse power characteristic HPPC test to obtain voltage and current response data under short-time pulse current excitation and long-time pulse current excitation, respectively. Based on the voltage and current response data, the precise parameter values ​​of the polarized RC branch and the diffused RC branch at the target temperature and target SOC are identified, including: Construct corresponding response curves based on voltage and current response data under short-time pulse current excitation and long-time pulse current excitation; A second-order exponential fit is performed on the zero-input response segment of the response curve under short-time pulse current excitation to calculate the rough parameter values ​​of the polarized RC branch and the diffused RC branch. A second-order exponential fit is performed on the zero-input response segment of the response curve under long-term pulse current excitation. The coarse parameter values ​​of the polarized RC branch are added as known quantities to the fitting process to calculate the precise parameter values ​​of the diffused RC branch. A second-order exponential fit is performed on the zero-input response segment of the response curve under short-time pulse current excitation. The precise parameter values ​​of the diffused RC branch are added as known quantities to the fitting process to calculate the precise parameter values ​​of the polarized RC branch. The fitting formula for the second-order exponential fit is: ； In the formula, For the coordinate points on the response curve, These are the start and end times of the zero-input response segment, respectively. These are the fitting coefficients. For constant terms; The formula for the zero-input response segment is: ； In the formula, The voltage value of the zero-input response segment. Let R1 be the resistance value and C1 be the capacitance value in the polarized RC branch. Let R2 be the resistance value and C2 be the capacitance value in the diffused RC branch. The time within the zero input response segment, This is the current value of the pulse current. This is the battery open-circuit voltage; Combine the fitting equation and the operational equation for the zero-input response segment, and then apply the fitting coefficients... Calculate the parameter values ​​for the polarized RC branch and the diffused RC branch: ； 。 4. The parameter identification method for the battery equivalent circuit according to claim 3, characterized in that, Before both the electrochemical impedance spectroscopy (EIS) test and the hybrid pulse power characteristic (HPPC) test, the battery is pretreated. The pretreatment includes placing the battery in a constant temperature environment at the target temperature, charging / discharging it to the target state of charge (SOC) with a constant current, and then letting it stand for a predetermined time.

5. The parameter identification method for the battery equivalent circuit according to claim 3, characterized in that, The acquisition of electrochemical impedance spectroscopy under high-frequency excitation includes: An AC excitation signal is applied in the high-frequency region to ensure that the battery is in a linear response state and the corresponding electrochemical impedance spectrum is obtained; wherein, the frequency range of the high-frequency region is 1 kHz to 5 kHz, and the amplitude of the AC excitation signal is ≤10 mV; The precise value of the battery internal resistance R0 is the impedance value at the intersection of the high-frequency region and the real axis in the Nyquist plot of the electrochemical impedance spectrum.

6. The parameter identification method for the battery equivalent circuit according to claim 3, characterized in that, The duration of the short-time pulse current excitation is 10s to 60s, and the duration of the long-time pulse current excitation is 5min to 1h.

7. A parameter weighting identification method for a battery equivalent circuit, characterized in that, include: Using the target temperature and target SOC as a baseline, adjust the target temperature and target SOC to obtain the neighboring temperature and neighboring SOC; Construct a neighbor group of the benchmark group based on the neighboring temperature and the target SOC, and the target temperature and the neighboring SOC; Using the parameter identification method as described in any one of claims 3-6, the accurate parameter values ​​of the battery internal resistance R0, the polarized RC branch, and the diffused RC branch under the reference group and the adjacent group are obtained; The precise parameter values ​​of the baseline group and the neighboring group are weighted and summed to obtain the final precise parameter values ​​of the battery internal resistance R0, the polarized RC branch, and the diffused RC branch at the target temperature and the target SOC.

8. A battery cell, characterized in that, The battery unit includes one or more of battery modules, battery packs, or energy storage batteries, and the battery unit uses the parameter identification device as described in any one of claims 1-2, the parameter identification method as described in any one of claims 3-6, or the parameter weighting identification method as described in claim 7 to identify the parameters of the battery equivalent circuit.

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