Power battery power estimation method and electronic equipment

Abstract

The invention provides a power battery power estimation method and electronic equipment, and the method comprises the steps: determining observation parameters participating in the calculation of the polarization state of a power battery according to HPPC test data; substituting the direct-current internal resistance into a polarization state calculation formula to determine the polarization state of the power battery; constructing a power state prediction model corresponding to the power battery according to the polarization state of the power battery and the direct-current internal resistance and the time constant after the preset time period is given; and according to the power state prediction model, predicting to obtain the peak power of the power battery, and according to the peak power of the power battery, performing damping control taking the dynamic voltage as a target. The power of the battery is predicted by combining the polarization state of the power battery with the first-order RC model, the prediction process is simplified, the estimation precision is improved, voltage balance regulation and control based on the predicted power are provided, the power limitation is smoother, and the battery capability is ensured to be exerted.

Description

Technical Field

[0001] This application relates to the field of power battery power prediction technology, and in particular to a power battery power estimation method and electronic device. Background Technology

[0002] In a battery management system (BMS), state of power (SOP) estimation is a core function that directly affects the safety, performance, and lifespan of the battery system. Currently, the mainstream power estimation methods include those based on charge / discharge time or energy integral to select the power MAP, as well as model-based power estimation methods. All of these approaches have certain limitations, specifically: Power estimation methods based on charge / discharge time or energy integral selection power MAP are often conservative in their power estimation to adapt to complex operating conditions. This can easily lead to undervoltage triggering power limits and affect driving smoothness.

[0003] Model-based power estimation methods suffer from problems such as sensitivity to battery parameters, high calibration difficulty, and high model complexity. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide at least one power battery power estimation method and electronic device, which combines the power battery polarization state and a first-order RC model to predict battery power, simplifying the prediction process while improving the estimation accuracy, and providing voltage balance regulation based on the predicted power, making power limiting smoother and ensuring the battery's capacity is fully utilized.

[0005] This application mainly includes the following aspects: In a first aspect, embodiments of this application provide a method for estimating the power of a power battery. The method includes: conducting a hybrid pulse power characteristic test on the power battery to obtain experimental data; determining observation parameters for calculating the polarization state of the power battery based on the experimental data, including the instantaneous DC internal resistance of a single cell, the equivalent DC internal resistance after a prediction period, and the time constant corresponding to the first-order RC model of the single cell; substituting the DC internal resistance into the polarization state calculation formula to determine the polarization state of the power battery; constructing a power state prediction model for the power battery based on the power battery polarization state and the DC internal resistance and time constant after a given preset time period; predicting the peak power of the power battery based on the power state prediction model and performing damping control with dynamic voltage as the target based on the peak power of the power battery.

[0006] In one possible implementation, the polarization state calculation formula is as follows:

[0007] In this formula, This represents the polarization voltage, which reflects the polarization state of a single cell at time t. This represents the open-circuit voltage of a single cell at time t corresponding to its state of charge (SOC). This represents the instantaneous DC internal resistance of a single cell. This represents the current of a single cell at time t. This represents the terminal voltage of a single cell at time t.

[0008] In one possible implementation, the power state prediction model for the power battery is constructed as follows: The polarization state of a single battery cell is rate-wave processed using a preset filtering model to obtain the filtered target polarization state; a target curve of the open-circuit voltage of the single battery cell changing with the state of charge is extracted from experimental data, and the derivative of the target curve is used to determine the rate of change of the open-circuit voltage of the single battery cell with respect to the state of charge; the sum of the discharge cutoff voltage of the single battery cell and the preset voltage tolerance is determined as the lower limit of the discharge voltage; a single-cell peak current prediction model for the power battery cell is constructed based on the equivalent DC internal resistance, time constant, target polarization state, rate of change, and lower limit of the discharge voltage; and a power state prediction model is constructed based on the single-cell peak current prediction model, the number of power battery cells, and the lower limit of the discharge voltage.

[0009] In one possible implementation, the preset filtering model is:

[0010] in, This represents the target polarization voltage of a single cell at time t. This represents the polarization voltage of the power battery at time t. This represents the preset filter coefficients. express The target polarization voltage at any given time.

[0011] In one possible implementation, the single-cell peak current prediction model is as follows:

[0012] in, Indicates the forecast period The predicted peak current of a single cell in the rear power battery. Indicates the individual cell at t+ The corresponding open-circuit voltage OCV at any given time is the state of charge (SOC). Indicates the lower limit of the discharge voltage. This represents the target polarization state at time t. Represents the time constant. Indicates the rate of change. This represents the equivalent DC internal resistance. This indicates the capacity of a single battery cell.

[0013] In one possible implementation, the instantaneous DC internal resistance, equivalent DC internal resistance, and time constant are determined as follows: based on the current and terminal voltage changes of the individual cell described by experimental data, the current change, instantaneous voltage change, and voltage change after a predicted period are determined; a first ratio between the instantaneous voltage change and the current change is calculated, and this first ratio is determined as the instantaneous DC internal resistance; a second ratio between the voltage change and the current change after the predicted period is calculated, and this second ratio is determined as the equivalent DC internal resistance; a first-order RC model combined with the instantaneous DC internal resistance is fitted with the experimental data to obtain the time constant of the first-order RC model corresponding to the individual cell.

[0014] In one possible implementation, the power state prediction model is as follows:

[0015] in, Indicates the forecast period Predicted power output of the rear battery Indicates the forecast period The predicted peak current of a single cell in the rear power battery. Indicates the lower limit of the discharge voltage. This indicates the number of individual power battery cells.

[0016] In one possible implementation, the peak power of the power battery is predicted according to a power state prediction model, and damping control targeting dynamic voltage is performed based on the peak power. This includes: using the peak power of the power battery as the allowable power of the power battery; comparing the minimum single-cell voltage corresponding to the power battery with the allowable power; if the minimum single-cell voltage is greater than or equal to the lower limit of the discharge voltage corresponding to the single-cell battery, then continuing to use the peak power of the power battery as the allowable power of the power battery; if the minimum single-cell voltage is less than the lower limit of the discharge voltage corresponding to the single-cell battery, then determining whether the allowable power is greater than the actual upper limit of the power battery, where the actual upper limit is the power battery's... The sum of the actual power and the preset power increase; if the allowable power is less than or equal to the upper limit of the actual power, the power battery voltage is regulated according to the allowable power; if the allowable power is greater than the upper limit of the actual power, the actual power is assigned to the target control power of the power battery; the allowable power of the power battery is controlled to decrease to the target control power at a given decreasing rate; it is determined whether the allowable power of the power battery is equal to the target control power. If the allowable power is equal to the target control power, the power battery voltage is regulated according to the allowable power; if the allowable power is greater than the target control power, the process returns to control the allowable power of the power battery to decrease to the target control power at a given decreasing rate.

[0017] In one possible implementation, the step of regulating the power battery voltage according to the allowable power includes: setting the single-cell control voltage of the power battery equal to the lower limit of the discharge voltage corresponding to the single-cell battery; determining whether the minimum single-cell voltage is less than the lower limit of the discharge voltage; if the minimum single-cell voltage is less than the lower limit of the discharge voltage, regulating the single-cell control voltage of the power battery and updating the allowable power according to a first strategy; if the minimum single-cell voltage is greater than or equal to the lower limit of the discharge voltage, regulating the single-cell control voltage of the power battery and updating the allowable power according to a second strategy; after the single-cell control voltage and allowable power are updated, determining whether the minimum single-cell voltage is greater than the lower limit of the discharge voltage; if the minimum single-cell voltage is determined to be greater than the lower limit of the discharge voltage, returning to the step of setting the single-cell control voltage of the power battery equal to the lower limit of the discharge voltage corresponding to the single-cell battery; if the minimum single-cell voltage is determined to be less than or equal to the lower limit of the discharge voltage, returning to the step of determining whether the minimum single-cell voltage is less than the lower limit of the discharge voltage.

[0018] In one possible implementation, the first strategy includes: updating the individual cell control voltage to the minimum individual cell voltage; looking up a preset power control table to determine the target regulated power corresponding to the individual cell control voltage; and determining the difference between the allowable power and the target regulated power as the updated allowable power.

[0019] In one possible implementation, the second strategy includes keeping the individual control voltage and allowable power constant.

[0020] Secondly, embodiments of this application also provide an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate through the bus. The machine-readable instructions are executed by the processor to perform the steps of the power battery power estimation method provided in any of the above embodiments.

[0021] This application provides a power battery power estimation method and electronic device. The method includes: conducting a hybrid pulse power characteristic test on the power battery to obtain experimental data; determining the observation parameters involved in the power battery polarization state calculation based on the experimental data, including the instantaneous DC internal resistance of a single cell, the equivalent DC internal resistance after a prediction period, and the time constant corresponding to the first-order RC model of the single cell; substituting the DC internal resistance into the polarization state calculation formula to determine the power battery polarization state; constructing a power state prediction model for the power battery based on the power battery polarization state and the DC internal resistance and time constant after a given preset time period; predicting the peak power of the power battery based on the power state prediction model and performing damping control with dynamic voltage as the target based on the peak power of the power battery. By combining the power battery polarization state and the first-order RC model for battery power prediction, the prediction process is simplified while the estimation accuracy is improved, and voltage balance regulation based on the predicted power is provided, making power limiting smoother and ensuring the battery's capacity is fully utilized.

[0022] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A flowchart of a power battery power estimation method provided in an embodiment of this application is shown; Figure 2 This illustration shows a schematic diagram of the current and terminal voltage changes of a single cell under HPPC according to an embodiment of this application; Figure 3 This illustration shows a schematic diagram of fitting HPPC experimental data and first-order RC model calculation results according to an embodiment of this application; Figure 4 A schematic diagram illustrating the power state prediction model construction process provided in an embodiment of this application is shown. Figure 5 This document illustrates one of the flowcharts for dynamic voltage control based on predicted peak power of the power battery, according to an embodiment of this application. Figure 6 This document illustrates a second flowchart of a dynamic voltage control method based on predicted peak power of a power battery, according to an embodiment of this application. Figure 7 This paper illustrates a functional block diagram of a power battery power estimation device provided in an embodiment of this application. Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the drawings in this application are for illustrative and descriptive purposes only and are not intended to limit the scope of protection of this application. Furthermore, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of this application. It should be understood that the operations in the flowcharts may not be implemented in sequence, and steps without logical contextual relationships may be reversed or implemented simultaneously. In addition, those skilled in the art, guided by the content of this application, may add one or more other operations to the flowcharts, or remove one or more operations from the flowcharts.

[0026] Furthermore, the described embodiments are merely some, not all, of the embodiments of this application. The components of the embodiments of this application described and illustrated herein can typically be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0027] In a battery management system (BMS), State of Power (SOP) estimation is a core function, directly impacting the safety, performance, and lifespan of the battery system. Currently, mainstream power estimation methods include those based on charge / discharge time or energy integral power selection (lookup table method), as well as model-based methods. All these approaches have certain limitations, such as: Power estimation methods based on charge / discharge time or energy integral selection (lookup table method) tend to be conservative in power estimation to adapt to complex operating conditions, which can easily lead to undervoltage triggering power limits and affect driving smoothness.

[0028] Model-based power estimation methods (such as those addressing model errors, sensor noise, and rapid battery aging) suffer from issues such as sensitivity to battery parameters, high calibration difficulty, and high model complexity.

[0029] Based on this, embodiments of this application provide a power battery power estimation method and electronic device. The method combines the power battery polarization state with a first-order RC model to predict battery power, simplifying the prediction process while improving estimation accuracy. Furthermore, it provides voltage balance regulation based on the predicted power, making power limiting smoother and ensuring optimal battery performance. Specifically, as follows: Please see Figure 1 , Figure 1 A flowchart illustrating a power battery power estimation method provided in an embodiment of this application is shown. Figure 1 As shown, the method provided in this application embodiment includes the following steps: S100: Perform hybrid pulse power characteristic tests on the power battery to obtain test data.

[0030] S200. Based on the test data, determine the observation parameters involved in the calculation of the polarization state of the power battery.

[0031] The observed parameters include the instantaneous DC internal resistance of a single cell, the equivalent DC internal resistance after the prediction period, and the time constant of the first-order RC model of the single cell.

[0032] S300. Substitute the DC internal resistance into the polarization state calculation formula to determine the polarization state of the power battery.

[0033] S400: Based on the polarization state of the power battery and the DC internal resistance and time constant after a given preset time period, construct a power state prediction model corresponding to the power battery.

[0034] S500: Based on the power state prediction model, the peak power of the power battery is predicted, and damping control with dynamic voltage as the target is performed based on the peak power of the power battery.

[0035] In steps S100 to S500 provided in this application, a power state prediction model is constructed based on the predicted polarization state of the power battery to achieve accurate estimation of the power state (i.e., peak power). When the estimation fails and overvoltage / undervoltage occurs, the voltage is quickly balanced in the redundant range through the damping control of the dynamic voltage target to ensure maximum power output capability while maintaining power smoothness.

[0036] In a preferred embodiment, in step S100, the hybrid pulse power characteristic test (HPPC) is performed on a single cell. A short-duration, high-intensity charge-discharge pulse is applied to the single cell in the power battery, and the changes in the terminal voltage and current of the single cell are measured to obtain test data.

[0037] In step S200, the DC internal resistance is essentially the ratio of the voltage change to the current change. Therefore, this application obtains the instantaneous DC internal resistance of a single cell based on the terminal voltage and current changes described in the experimental data. After the prediction period The equivalent DC internal resistance after And the time constant Tao corresponding to the first-order RC model.

[0038] In a preferred embodiment, please refer to Figure 2 , Figure 2 This diagram illustrates the current and terminal voltage changes of a single battery cell under HPPC according to an embodiment of this application. Figure 2 As shown, step S200 includes: Based on the current and terminal voltage changes of the individual cells described in the experimental data, determine the current change ∆I, the instantaneous voltage change ∆V0, and the voltage change after the predicted period. The voltage change ∆V1 is used to calculate the first ratio between the instantaneous voltage change ∆V0 (the voltage change during the process of the terminal voltage rising from its lowest instantaneous value to a gradual increase) and the current change ∆I. This first ratio is then determined as the instantaneous DC internal resistance. ,Right now:

[0039] Calculate the second ratio between the voltage change ∆V1 and the current change ∆I, and determine the second ratio as the equivalent DC internal resistance. ,Right now:

[0040] By combining the instantaneous DC internal resistance with the first-order RC model corresponding to a single cell, and fitting it with the experimental data, the time constant Tao of the first-order RC model corresponding to a single cell is obtained.

[0041] In a preferred embodiment, the first-order RC model corresponding to a single cell is used to calculate the terminal voltage of the single cell. Specifically, the first-order RC model is formed by the following formulas (1) and (2): (1) (2) In formula (1), This represents the terminal voltage of a single cell at time t. This represents the open-circuit voltage of a single cell at time t corresponding to its state of charge (SOC). This represents the current of a single cell at time t. This represents the polarization voltage of a single cell at time t. Indicates that a single cell is in Polarization voltage at time , To predict periodic variables, Let represent the polarization internal resistance of a single cell. Substituting formula (2) into formula (1) yields the calculation model for the terminal voltage of a single cell, namely the first-order RC model.

[0042] In one specific embodiment, please refer to Figure 3 , Figure 3 This illustration shows a schematic diagram of fitting HPPC experimental data with the calculation results of a first-order RC model, as provided in an embodiment of this application. Figure 3 As shown, the horizontal axis represents the number of terminal voltage sampling points corresponding to a single cell, and the vertical axis represents the terminal voltage corresponding to a single cell. Figure 3 L1 in the figure represents the terminal voltage sampling curve of a single cell during HPPC testing. The terminal voltage is directly acquired, and during the terminal voltage acquisition process, the corresponding voltage of the large single cell is also acquired. and Set the initial polarization voltage to 0, and then set the terminal voltage indicated by the L1 curve... , Initial polarization voltage and calculated instantaneous DC internal resistance Substituting the above formulas (1) and (2) into the fit, we obtain the parameters corresponding to the first-order RC model, namely the time constant Tao and the polarization resistance. Ultimately, the result is as follows Figure 3 The terminal voltage curve of the first-order RC model shown in L2.

[0043] In one specific embodiment, step S300 includes: To reduce model parameters (time constant Tao and polarization resistance) The polarization state calculation formula is as follows, considering the influence of errors: (3) In a preferred embodiment, please refer to Figure 4 , Figure 4 This diagram illustrates a power state prediction model construction process provided in an embodiment of this application. Figure 4 As shown, step S400 includes: S4001. The polarization state of a single battery cell is processed by a preset filtering model to obtain the filtered polarization state of the target power battery.

[0044] S4002. Extract the target curve of the open-circuit voltage of a single cell as a function of state of charge from the experimental data, differentiate the target curve, and determine the rate of change of the open-circuit voltage of the single cell with respect to the state of charge.

[0045] S4003. The sum of the discharge cutoff voltage corresponding to the power battery and the preset voltage tolerance is determined as the lower limit of the discharge voltage.

[0046] S4004. Based on the equivalent DC internal resistance, time constant, target polarization state, rate of change, and lower limit of discharge voltage, construct a single-cell peak current prediction model for the power battery.

[0047] S4005. Based on the single-cell peak current prediction model, the number of power battery cells, and the lower limit of discharge voltage, construct a power state prediction model.

[0048] In a preferred embodiment, considering that the false alarm process is relatively slow, in order to avoid polarization voltage caused by terminal voltage jumps... The rapid changes require... The filtering process is performed; specifically, the preset filtering model in step S4001 is as follows: (4) In the preset filtering model described by formula (4), This represents the target polarization voltage of a single cell at time t. The polarization voltage of a single cell at time t is determined by the polarization state calculation formula described in formula (3). This represents the preset filter coefficients. express The target polarization voltage at any given time.

[0049] In step S4002, the derivative of the target curve with the state of charge (SOC) of a single cell as the abscissa and the open-circuit voltage of the single cell as the ordinate is calculated to obtain the rate of change of the open-circuit voltage of the single cell with respect to the state of charge. .

[0050] In step S4003, the discharge cutoff voltage (pre-given) corresponding to a single cell can be predetermined based on the power battery model. Based on this discharge cutoff voltage, and according to actual needs, the discharge cutoff voltage is increased by a preset capacitance difference (for example, the preset capacitance difference can be set to 0.4V) to obtain the lower limit of the discharge voltage. .

[0051] In step S4004, this application uses a predicted period Using the peak power of the subsequent power battery as the target, and combining the above formulas (1) and (2), the prediction period is determined. The formula for calculating the terminal voltage of a single cell is as follows: (5) (6) Combining formulas (5) and (6) above, the prediction cycle is... Then, when the terminal voltage of a single cell... Lower limit of discharge voltage hour, Peak current of a single unit Thus, the peak current of a single cell is obtained. The calculation formula is as follows: (7) In formula (7), Indicates the forecast period The predicted peak current corresponding to the next single cell, The forecast period is indicated by C, and the single cell capacity is indicated by C.

[0052] The polarization voltage in formula (7) Replace with the filtered target polarization voltage in formula (4) ,get: (8) In formula (8), Replace with prediction period The equivalent DC internal resistance of the next single cell The equivalent DC internal resistance obtained offline through the above steps Time constant Tao, target polarization state The rate of change of open-circuit voltage of a single cell with respect to its state of charge and lower limit of discharge voltage The following prediction model for the peak current of a single power battery cell is constructed: (9) In the single-unit peak current prediction model described by formula (9), This indicates the predicted lifespan of a single cell within the power battery. The predicted peak current, i.e., the single-cell peak current prediction model described by formula (9), can determine the peak current of a single cell in the power battery during the prediction cycle. The peak current of the subsequent single cell .

[0053] In step S4005, the power state prediction model is: (10) In the power state prediction model described by formula (10), Indicating the forecast period Then, the predicted power of the power battery, This represents the predicted peak current of a single cell within the power battery, specifically substituted into the model described by formula (9). This indicates the lower limit of the discharge voltage. This indicates the number of individual power battery cells.

[0054] In a preferred embodiment, please refer to Figure 5 , Figure 5 This illustration shows one of the flowcharts for dynamic voltage control based on predicted peak power of the power battery, according to an embodiment of this application. Figure 5 As shown, step S500 includes: S501, the peak power of the power battery is taken as the allowable power of the power battery.

[0055] S502, the minimum single-cell voltage corresponding to the power battery With discharge voltage lower limit Compare them.

[0056] If the minimum single-cell voltage ≥ Lower limit of discharge voltage corresponding to a single cell If so, return to step S501.

[0057] S503, If the minimum single-unit voltage <Lower discharge voltage limit corresponding to a single cell Then it is determined whether the allowable power is greater than the actual power limit Pactm of the power battery.

[0058] The actual power limit is the sum of the actual power Pact of the power battery and the preset power increase. The sum between them, for example, a preset power increase. A 5KW (kilowatt) power supply is available.

[0059] If the allowable power is less than or equal to the actual power limit, then step S507 is executed to regulate the voltage according to the allowable power.

[0060] S504. If the allowable power is greater than the actual power limit, then the actual power is assigned to the target control power of the power battery.

[0061] S505, control the allowable power of the power battery to decrease to the target control power according to the given decrease rate v1.

[0062] S506. Determine whether the allowable power is equal to the target control power.

[0063] If the allowable power is equal to the target control power, then proceed to step S507.

[0064] If the allowed power is greater than the target control power, then return to step S505.

[0065] In one specific embodiment, in steps S503 to S506, when the minimum single-cell voltage... <Lower discharge voltage limit corresponding to a single cell When the voltage drops, it indicates that the power battery is in an undervoltage state. At this time, if the allowable power is greater than the upper limit of the actual power, the allowable power is controlled to decrease to the target control power (i.e., the actual power Pact) at a given rate of decrease v1. That is, while the power battery is undervoltage, the allowable power of the power battery is controlled to decrease synchronously, so that the allowable power of the power battery is always within a safe range, and the actual power is avoided from being exceeded to ensure the safe operation of the power battery.

[0066] Please see Figure 6 , Figure 6 This illustration shows a second flowchart of a dynamic voltage control method based on predicted peak power of a power battery, according to an embodiment of this application. Figure 6 As shown, step S507 includes: S5071, Controlling the voltage of individual power battery cells =Lower discharge voltage limit for a single cell .

[0067] S5072, Determine the minimum unit voltage Is it less than the lower limit of discharge voltage? .

[0068] S5073, If the minimum single-unit voltage Less than the lower limit of discharge voltage Then execute: Adjust the individual unit control voltage Updated to minimum unit voltage Locate the preset power control table and determine the target regulating power corresponding to the individual unit control voltage. .

[0069] S5074, If the minimum single-unit voltage Greater than or equal to the lower limit of discharge voltage Then execute: Set the individual control voltage =Single unit control voltage To enable target power regulation .

[0070] S5075, The allowable power is compared with the target controlled power. The difference between them is determined as the updated allowable power. S5076, Determine the minimum unit voltage Is it greater than the lower limit of discharge voltage? .

[0071] If it is determined that the minimum single-cell voltage is greater than the lower limit of the discharge voltage (specifically, if...) > + , For example, to preset the individual cell voltage capacitance value, If 0.2V can be taken, then return to step S5071.

[0072] If the minimum single-cell voltage is determined Less than or equal to the lower limit of discharge voltage If so, return to step S5072.

[0073] As can be seen from step S507 above, the activation condition for step S507 (i.e., the damping control process based on the single-cell control voltage) is the minimum single-cell voltage. <Discharge voltage lower limit The exit condition for step S507 is the minimum single-cell voltage. > ( Furthermore, the duration of the slow charging feedback discharge process is greater than or equal to 1 second.

[0074] In the power battery power estimation provided above, the terminal voltage of the power battery will deviate from the off-circuit voltage (OCV) during charging and discharging. This deviation is mainly caused by DC internal resistance voltage division and polarization voltage division. Usually, DC internal resistance voltage division can be calculated by offline measurement of DC impedance and real-time current. Polarization state reflects the degree of dynamic response inside the power battery and is a key internal state affecting the instantaneous output capability of the battery. It can be calculated by open-circuit voltage and DC internal resistance voltage division.

[0075] Traditional power battery power estimation (such as the lookup table method) is based on static mapping relationships (such as SOC-internal resistance-voltmeter). It cannot reflect the instantaneous voltage changes inside the power battery caused by polarization effect in real time. Therefore, a large safety margin must be reserved to avoid exceeding the limit.

[0076] The technical solution provided in this application abandons the simple lookup table method. It combines the battery polarization state and the battery DC impedance and adopts a forward prediction model to accurately estimate the power of the power battery. The model as a whole is implemented using a first-order RC model, which avoids the problems of battery parameter sensitivity, high calibration difficulty, and high model complexity faced by traditional machine learning prediction.

[0077] Furthermore, since any estimation model may be inaccurate (such as model error, sensor noise, rapid battery aging, etc.), once it fails, the power battery voltage may actually reach its safety limit (overvoltage or undervoltage). Therefore, this application combines the predicted peak power of the power battery and performs further damping control with voltage balance as the goal. Specifically, when overvoltage or undervoltage occurs, the control goal of this application is to keep the voltage in a balanced state (if the voltage continues to drop rapidly, the allowable power is reduced; conversely, if the voltage rebounds, the allowable power is increased), thereby ensuring the maximum power output capability and smoothness of the power battery.

[0078] In summary, the advantages of the technical solution provided in this application are: (1) By combining the polarization state of the power battery to predict the peak power of the power battery, the dynamic perception capability of the battery state is improved. The current polarization state of the power battery can be estimated in real time, thereby improving the dynamic power estimation capability and making the operating conditions more adaptable.

[0079] (2) By combining the prediction model of polarization state, the redundancy of power estimation in the lookup table scheme is reduced, the estimation is more accurate, and the battery capacity is fully utilized.

[0080] (3) By using the dynamic voltage target damping control method, the voltage can be quickly balanced within the safe range. Compared with the traditional scheme, the power limitation is smoother while ensuring the full utilization of the battery capacity.

[0081] Based on the same application concept, this application also provides a power battery power estimation device corresponding to the power battery power estimation method provided in the above embodiments. Since the principle of the device in this application is similar to the power battery power estimation method in the above embodiments of this application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0082] Please see Figure 7 , Figure 7 This diagram illustrates a functional block diagram of a power battery power estimation device provided in an embodiment of this application. Figure 7 As shown, the device includes: Test module 600 is used to test the hybrid pulse power characteristics of power batteries and obtain test data; The parameter calculation module 610 is used to determine the observation parameters involved in the calculation of the polarization state of the power battery based on the test data. The observation parameters include the instantaneous DC internal resistance of the single cell, the equivalent DC internal resistance after the prediction period, and the time constant of the first-order RC model of the single cell. The determination module 620 is used to input the DC internal resistance into the polarization state calculation formula to determine the polarization state of the power battery. Module 630 is used to construct a power state prediction model for the power battery based on the polarization state of the power battery and the DC internal resistance and time constant after a given preset time period. The predictive control module 640 is used to predict the peak power of the power battery based on the power state prediction model and to perform damping control with dynamic voltage as the target based on the peak power of the power battery.

[0083] Based on the same application concept, please refer to Figure 8 , Figure 8 This diagram illustrates the structure of an electronic device according to an embodiment of this application. Figure 8As shown, the electronic device 70 includes a processor 701, a memory 702, and a bus 703. The memory 702 stores machine-readable instructions that can be executed by the processor 701. When the electronic device 70 is running, the processor 701 and the memory 702 communicate through the bus 703. The machine-readable instructions are executed by the processor 701 to perform the steps of the power battery power estimation method of any of the above embodiments.

[0084] Based on the same concept, this application also provides a computer-readable storage medium storing a computer program, which, when run by a processor, executes the steps of the power battery power estimation method provided in the above embodiments.

[0085] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection may be through some communication interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0086] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0087] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0088] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0089] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for estimating the power of a power battery, characterized in that, The method includes: The hybrid pulse power characteristics of the power battery were tested to obtain experimental data; Based on the experimental data, the observation parameters for calculating the polarization state of the power battery are determined. The observation parameters include the instantaneous DC internal resistance of the single cell, the equivalent DC internal resistance after the prediction period, and the time constant of the first-order RC model of the single cell. The DC internal resistance is substituted into the polarization state calculation formula to determine the polarization state of the power battery. Based on the polarization state of the power battery and the DC internal resistance and time constant after a given preset time period, a power state prediction model corresponding to the power battery is constructed. Based on the power state prediction model, the peak power of the power battery is predicted, and damping control with dynamic voltage as the target is performed based on the peak power of the power battery.

2. The method according to claim 1, characterized in that, The formula for calculating the polarization state is: In this formula, This represents the polarization voltage, which reflects the polarization state of a single cell at time t. This represents the open-circuit voltage of a single cell at time t corresponding to its state of charge (SOC). This represents the instantaneous DC internal resistance corresponding to a single cell. This represents the current of a single cell at time t. This represents the terminal voltage of a single cell at time t.

3. The method according to claim 1, characterized in that, The power state prediction model for the power battery is constructed using the following method: The polarization state of a single cell is processed by rate-wave processing using a preset filtering model to obtain the filtered target polarization state. Extract the target curve of the open-circuit voltage of a single cell as a function of state of charge from the experimental data, and determine the rate of change of the open-circuit voltage of the single cell with respect to the state of charge by taking the derivative of the target curve. The sum of the discharge cutoff voltage of a single cell and the preset voltage tolerance is determined as the lower limit of the discharge voltage. Based on the equivalent DC internal resistance, time constant, target polarization state, rate of change, and lower limit of discharge voltage, a single-cell peak current prediction model for the power battery is constructed. Based on the single-cell peak current prediction model, the number of power battery cells, and the lower limit of discharge voltage, a power state prediction model is constructed.

4. The method according to claim 3, characterized in that, The preset filtering model is: in, This represents the target polarization voltage of a single cell at time t. This represents the polarization voltage of the power battery at time t. This represents the preset filter coefficients. express The target polarization voltage at any given time.

5. The method according to claim 3, characterized in that, The single-unit peak current prediction model is as follows: in, Indicates the forecast period The predicted peak current of a single cell in the rear power battery. Indicates the individual cell at t+ The corresponding open-circuit voltage OCV at any given time is the state of charge (SOC). This indicates the lower limit of the discharge voltage. This represents the target polarization state at time t. This represents the time constant. This represents the rate of change. This represents the equivalent DC internal resistance. This indicates the capacity of a single battery cell.

6. The method according to claim 1, characterized in that, The instantaneous DC internal resistance, the equivalent DC internal resistance, and the time constant are determined in the following manner: Based on the current and terminal voltage changes of the individual cells described in the test data, determine the current change, instantaneous voltage change, and voltage change after the predicted period. Calculate a first ratio between the instantaneous voltage change and the current change, and determine the first ratio as the instantaneous DC internal resistance; Calculate a second ratio between the voltage change and the current change after the prediction period, and use the second ratio to determine the equivalent DC internal resistance; By using a first-order RC model combined with the instantaneous DC internal resistance and fitting it with the experimental data, the time constant of the first-order RC model corresponding to a single cell is obtained.

7. The method according to claim 3, characterized in that, The power state prediction model is as follows: in, Indicates the forecast period Predicted power output of the rear battery Indicates the forecast period The predicted peak current of a single cell in the rear power battery. This indicates the lower limit of the discharge voltage. This indicates the number of individual power battery cells.

8. The method according to claim 1, characterized in that, Based on the power state prediction model, the peak power of the power battery is predicted, and damping control targeting dynamic voltage is performed based on the peak power of the power battery, including: The peak power of the power battery is taken as the allowable power of the power battery; Compare the minimum single-cell voltage of the power battery with the allowable power; If the minimum single-cell voltage is greater than or equal to the lower limit of the discharge voltage corresponding to the single cell, then the peak power of the power battery will continue to be used as the allowable power of the power battery. If the minimum single-cell voltage is less than the lower limit of the discharge voltage corresponding to the single cell, then it is determined whether the allowable power is greater than the upper limit of the actual power of the power battery. The upper limit of the actual power is the sum of the actual power of the power battery and the preset power increase. If the allowable power is less than or equal to the actual power limit, the power battery voltage is regulated according to the allowable power. If the allowable power is greater than the actual power limit, then the actual power is assigned to the target control power of the power battery. The allowable power of the control battery is reduced to the target control power at a given rate of decrease; Determine whether the allowable power of the power battery is equal to the target control power. If the allowable power is equal to the target control power, then regulate the power battery voltage according to the allowable power. If the allowable power is greater than the target control power, then return to control the allowable power of the power battery to decrease to the target control power at a given decreasing rate.

9. The method according to claim 8, characterized in that, The step of regulating the power battery voltage according to the allowable power includes: Set the control voltage of the single cell of the power battery to be equal to the lower limit of the discharge voltage of the single cell; Determine whether the minimum single-cell voltage is less than the lower limit of the discharge voltage; If the minimum single cell voltage is less than the lower limit of the discharge voltage, the single cell control voltage of the power battery is adjusted and the allowable power is updated according to the first strategy. If the minimum single-cell voltage is greater than or equal to the lower limit of the discharge voltage, then the single-cell control voltage of the power battery is adjusted and the allowable power is updated according to the second strategy; After the cell control voltage and the allowable power are updated, determine whether the minimum cell voltage is greater than the lower limit of the discharge voltage; If it is determined that the minimum single cell voltage is greater than the lower limit of the discharge voltage, then return to execute the command to make the single cell control voltage of the power battery equal to the lower limit of the discharge voltage of the single cell. If it is determined that the minimum cell voltage is less than or equal to the lower limit of the discharge voltage, then return to the step of determining whether the minimum cell voltage is less than the lower limit of the discharge voltage.

10. The method according to claim 9, characterized in that, The first strategy includes: Update the individual cell control voltage to the minimum individual cell voltage; Locate the preset power control table to determine the target regulating power corresponding to the control voltage of the individual unit; The difference between the allowable power and the target control power is determined as the updated allowable power.

11. The method according to claim 9, characterized in that, The second strategy includes: The control voltage and allowable power of the individual unit remain unchanged.

12. An electronic device, characterized in that, include: The device includes a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor communicates with the memory via the bus. The machine-readable instructions are executed by the processor to perform the steps of the power battery power estimation method as described in any one of claims 1 to 11.

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