A Method and System for In-Situ Impedance Testing of Batteries Based on Adaptive Phase Compensation

Abstract

This invention relates to the field of in-situ impedance testing technology for energy storage batteries. To address the current difficulties in achieving rapid tracking of wideband excitation signals and the inaccurate identification and measurement of electrochemical parameters, it provides a battery in-situ impedance testing method and system based on adaptive phase compensation. The method includes acquiring the initial reference current and actual sampled current of the battery charging and testing system; iteratively calculating the real-time phase lag angle and generating a corrected reference current command accordingly; predicting the current response in two steps based on a discrete mathematical model of the full-bridge converter in continuous conduction mode; and optimizing the switching state corresponding to the voltage vector that minimizes the composite cost function to drive the switching transistors of the full-bridge converter. This method balances fast dynamic response with zero phase error tracking, meeting the high-precision requirements of in-situ EIS testing of energy storage batteries.

Description

Technical Field

[0001] This invention relates to the field of in-situ impedance testing technology for energy storage batteries, and in particular to a battery in-situ impedance testing method and system based on adaptive phase compensation. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Lithium-ion batteries, as core energy storage components, are widely used in large-capacity energy storage fields. Accurate sensing of battery state in energy storage battery charging systems relies on in-situ EIS impedance testing technology. As battery capacity continues to increase, the equivalent internal resistance of the battery pack continuously decreases, significantly weakening the minute impedance characteristics caused by internal state changes, thus posing new challenges to high-precision impedance measurement and state sensing technologies. Conventional in-situ EIS testing uses external superposition of AC and DC excitation equipment, actually measuring the equivalent impedance of the DC equipment and the battery, resulting in large measurement errors. Using a full-bridge bidirectional converter topology in the charging test system to directly output the AC / DC superimposed signal can fundamentally avoid impedance errors introduced by parallel connection of external equipment, and is expected to become a mainstream technology route to break through the limitations of traditional testing. However, traditional PI control methods are limited by the finite bandwidth gain product, making it difficult to achieve fast tracking of wide-bandwidth (0.01 Hz to 2 kHz) excitation signals. Furthermore, as the system switching frequency increases, the inherent sampling and calculation delays of the digital control system lead to phase errors, which in turn cause rotational distortion of the Nyquist curve, introducing spurious inductive or capacitive components, resulting in inaccurate identification and measurement of electrochemical parameters. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides a battery in-situ impedance testing method and system based on adaptive phase compensation, which can balance rapid dynamic response and zero phase error tracking, meeting the high-precision requirements of in-situ EIS testing of energy storage batteries.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] The first aspect of the present invention provides a method for in-situ impedance testing of a battery based on adaptive phase compensation.

[0007] In one or more embodiments, a method for testing the in-situ impedance of a battery based on adaptive phase compensation is provided, including:

[0008] The initial reference current and the actual sampled current of the battery charging and testing system are obtained, and the difference between the two is calculated as the error signal. The orthogonal component of the initial reference current is used as the gradient signal. The real-time phase lag angle is iteratively calculated by combining the least mean square adaptive algorithm and the stochastic gradient descent method.

[0009] The real-time phase lag angle is used as the feedforward compensation amount to perform phase pre-lead correction on the initial reference current and generate the corrected reference current command.

[0010] The discrete mathematical model of the full-bridge converter in continuous conduction mode based on the battery charging and testing system is used to calculate the current prediction value at time k+1 by combining the sampled current and switching state of the full-bridge converter at time k. Then, all possible voltage vectors in the full-bridge converter are traversed to predict the current response at time k+2; k is a positive integer greater than or equal to 1.

[0011] Using a pre-constructed composite cost function, the weighted sum of the deviations between the current response at time k+2 and the corrected reference current command is evaluated. The switching state corresponding to the voltage vector that minimizes the composite cost function is found, so as to drive the switching transistors of the full-bridge converter and simultaneously acquire the battery-side voltage and current response signals at this time.

[0012] The amplitude and phase information of the signal at different target frequencies are extracted from the synchronously acquired battery side voltage and current response signals. The amplitude and phase of the battery impedance are calculated in situ according to the impedance formula, and finally the battery impedance spectrum is generated.

[0013] As one implementation method, the process of generating the corrected reference current command is as follows:

[0014] Keeping the amplitude and frequency of the initial reference current unchanged, the real-time phase lag angle is superimposed on the phase parameter of the initial reference current to generate a sinusoidal signal with a pre-lead phase as the AC tracking target, and then superimposed on the DC charging command to obtain the corrected reference current command.

[0015] As one implementation method, the expression for iteratively calculating the real-time phase lag angle is:

[0016] ;

[0017] in, The phase lag angle at time k+1; Let be the phase lag angle at time k; Step size factor; This is an error signal; It is a gradient signal; The sampling period.

[0018] In one implementation, the initial reference current includes a DC charging command and a variable frequency sinusoidal AC disturbance command; the corrected initial reference current includes a constant DC charging command and a corrected variable frequency sinusoidal AC disturbance command; and the current response includes a predicted DC current component and an AC component.

[0019] As one implementation method, the calculation process of the composite cost function is as follows:

[0020] The first deviation is calculated by subtracting the modified variable frequency sinusoidal AC disturbance command from the predicted AC component.

[0021] The second deviation is calculated by subtracting the DC charging command from the predicted DC current component.

[0022] The composite cost function is obtained by weighted summation of the first and second biases.

[0023] As one implementation method, the expression for the predicted current value at time k+1 is:

[0024] ;

[0025] in, This is the predicted current value at time k+1; This refers to the parasitic resistance of the inductor. The sampling period; For filtering inductors; This is the filter inductor current; Let be the battery terminal voltage at time k; Let be the DC input voltage at time k; It is in the on / off state.

[0026] As one implementation method, the expression for the predicted current response at time k+2 is:

[0027] ;

[0028] in, The predicted current response at time k+2; This is the predicted current value at time k+1; This refers to the parasitic resistance of the inductor. The sampling period; For filtering inductors; This is the filter inductor current; Let be the battery terminal voltage at time k; Let be the DC input voltage at time k; It is in the on / off state.

[0029] A second aspect of the present invention provides a battery in-situ impedance test and control system based on adaptive phase compensation.

[0030] In one or more embodiments, a battery in-situ impedance test control system based on adaptive phase compensation includes:

[0031] The real-time phase lag angle calculation module is used to obtain the initial reference current and the actual sampled current of the battery charging and testing system and calculate the difference between the two as an error signal. The orthogonal component of the initial reference current is used as the gradient signal. The module combines the least mean square adaptive algorithm and the stochastic gradient descent method to iteratively calculate the real-time phase lag angle.

[0032] The reference current command correction module is used to use the real-time phase lag angle as the feedforward compensation amount to perform phase pre-lead correction on the initial reference current and generate the corrected reference current command.

[0033] The two-step current response prediction module is used for the discrete mathematical model of the full-bridge converter in continuous conduction mode based on the battery charging and testing system. It combines the sampled current and switching state of the full-bridge converter at time k to calculate the current prediction value at time k+1. Then, it traverses all possible voltage vectors in the full-bridge converter to predict the current response at time k+2; k is a positive integer greater than or equal to 1.

[0034] The composite cost function optimization module is used to evaluate the weighted sum of the deviations between the current response at time k+2 and the corrected reference current command using a pre-constructed composite cost function, and find the switching state corresponding to the voltage vector that minimizes the composite cost function, so as to drive the switching transistors of the full-bridge converter and simultaneously acquire the battery-side voltage and current response signals at this time.

[0035] The battery impedance spectrum generation module is used to extract the amplitude and phase information of the signal at different target frequencies from the synchronously acquired battery side voltage and current response signals, calculate the amplitude and phase of the battery impedance in situ according to the impedance formula, and finally generate the battery impedance spectrum.

[0036] A third aspect of the present invention provides a computer-readable storage medium.

[0037] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the above-described method for in-situ impedance testing of a battery based on adaptive phase compensation.

[0038] A fourth aspect of the present invention provides an electronic device.

[0039] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the above-described method for in-situ battery impedance testing based on adaptive phase compensation.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] This invention, based on the initial reference current and actual sampled current of a battery charging and testing system, combines the least mean square adaptive algorithm and stochastic gradient descent method to iteratively calculate the real-time phase lag angle and accordingly perform phase pre-lead correction on the initial reference current. Then, it combines a secondary current prediction method to predict the current response. Finally, using a pre-constructed composite cost function, it evaluates the weighted sum of the deviations between the current response and the corrected reference current command, and optimizes the switching state corresponding to the voltage vector that minimizes the composite cost function to drive the switching transistors of the full-bridge converter. This achieves adaptive phase estimation and correction, thereby enabling zero-phase-difference tracking and rapid tracking of high-frequency excitation signals for in-situ EIS testing of energy storage batteries. This effectively expands the measurement bandwidth of in-situ EIS, significantly improves the accuracy and reliability of the measured impedance spectrum, and provides accurate test data for energy storage battery state sensing. Attached Figure Description

[0042] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0043] Figure 1 This is a flowchart of the battery in-situ impedance testing method based on adaptive phase compensation according to an embodiment of the present invention;

[0044] Figure 2 This is the main circuit topology of the battery charging and testing system based on a full-bridge structure according to an embodiment of the present invention;

[0045] Figure 3 This is a block diagram of the minimum mean square adaptive phase compensator according to an embodiment of the present invention;

[0046] Figure 4 This is an overall control block diagram of the battery in-situ impedance testing method based on adaptive phase compensation according to an embodiment of the present invention;

[0047] Figure 5 The graph shows the output current tracking effect at different frequencies obtained by applying traditional PI control, traditional MPC control, and the battery in-situ impedance test control based on adaptive phase compensation according to the embodiment of the present invention. Detailed Implementation

[0048] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0049] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0050] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0051] In-situ electrochemical impedance spectroscopy (In-situ EIS) superimposes an AC excitation signal during DC charging and discharging, which can decouple key electrochemical parameters such as ohmic internal resistance, SEI film impedance, and charge transfer impedance inside the battery. This enables quantitative analysis of the microscopic electrochemical processes inside the battery and is expected to provide accurate quantitative basis for the health status assessment and consistency management of large-capacity battery systems.

[0052] The battery in-situ impedance testing method based on adaptive phase compensation according to this invention is applied to a battery charging and testing system. The battery charging and testing system adopts a full-bridge structure, and the main circuit structure is as follows: Figure 2 As shown, the battery charging and testing system is powered by a DC bus power supply. V in The system consists of switching transistors S1-S4, filter inductor L, filter capacitor C, and the lithium-ion battery pack under test. In the in-situ EIS test mode, the controller needs to operate at a DC charging current I... dc A variable-frequency sinusoidal disturbance current I is superimposed on top. ac This is used to stimulate the wide-frequency impedance response of the battery.

[0053] To achieve fast and effective tracking of the current of superimposed high-frequency excitation signals, combined with Figure 1 and Figure 4 As shown, this invention provides a method for in-situ impedance testing of a battery based on adaptive phase compensation, which may include the following steps 1 to 5. Steps 1 to 2 constitute the adaptive phase compensation part, the principle of which is as follows: Figure 3 As shown.

[0054] The specific implementation process of steps 1 to 5 is as follows:

[0055] Step 1: Obtain the initial reference current and the actual sampled current of the battery charging and testing system, and calculate the difference between the two as the error signal. Use the orthogonal component of the initial reference current as the gradient signal, and combine the least mean square adaptive algorithm and the stochastic gradient descent method to iteratively calculate the real-time phase lag angle.

[0056] In this embodiment of the invention, the initial reference current is the excitation current reference value of the in-situ EIS impedance test of the energy storage battery; the initial reference current includes a DC charging command and a variable frequency sinusoidal AC disturbance command.

[0057] First, define: at time k, the initial reference current. With the actual sampled current Error signals between The error signal is calculated in real time according to the following formula. :

[0058] (1);

[0059] To determine the direction of phase adjustment, the partial derivative of the reference signal with respect to the phase is calculated, and a gradient signal is generated. ( k The gradient signal is represented as:

[0060] (2);

[0061] in, The amplitude of the initial reference current; The frequency of the initial reference current; The sampling period.

[0062] It should be noted that, in a specific embodiment, the gradient signal can be calculated within the gradient calculation unit.

[0063] The phase lag angle is estimated by combining the least mean square adaptive algorithm and the stochastic gradient descent method. The expression for iteratively calculating the real-time phase lag angle is as follows:

[0064] (3);

[0065] in, The phase lag angle at time k+1; Let be the phase lag angle at time k; Step size factor; This is an error signal; It is a gradient signal; The sampling period is denoted by . The step size factor determines the convergence speed and steady-state accuracy of the algorithm.

[0066] Step 2: Use the real-time phase lag angle as the feedforward compensation amount to perform phase pre-lead correction on the initial reference current and generate the corrected reference current command.

[0067] In the specific implementation of step 2, the process of generating the corrected reference current command is as follows:

[0068] Keeping the amplitude and frequency of the initial reference current unchanged, the real-time phase lag angle is superimposed on the phase parameter of the initial reference current to generate a sinusoidal signal with a pre-lead phase as the AC tracking target, and then superimposed on the DC charging command to obtain the corrected reference current command.

[0069] Specifically, the expression for the revised reference current command is:

[0070] (4);

[0071] in, This is the corrected reference current command; DC charging command; The amplitude of the initial reference current; The frequency of the initial reference current; The sampling period; Let be the phase lag angle at time k.

[0072] Therefore, the corrected initial reference current includes a constant DC charging command and a corrected variable frequency sinusoidal AC disturbance command.

[0073] Step 3: Based on the discrete mathematical model of the full-bridge converter in continuous conduction mode of the battery charging and testing system, and combined with the sampled current and switching state of the full-bridge converter at time k, calculate the predicted current value at time k+1. Then, traverse all possible voltage vectors in the full-bridge converter to predict the current response at time k+2; k is a positive integer greater than or equal to 1. The current response includes the predicted DC current component and AC current component.

[0074] Based on Kirchhoff's voltage law, the continuous-time dynamic equation of inductor current can be described by the following equation:

[0075] (5);

[0076] in, For inductor parasitic resistance, V in DC input voltage, V bat This represents the battery terminal voltage. The switching state during each switching cycle... S The value ∈{0,1,2} determines the output voltage.

[0077] To adapt to the digital control implementation of the test control method in this embodiment of the invention, the forward Euler method is used to discretize equation (5), with a sampling period of . Assuming that at the sampling instant k, the current derivative is dIL / dt≈(IL(k+1)- IL(k)) / Ts, the expression for the predicted current value at time k+1 is:

[0078] (6);

[0079] in, This is the predicted current value at time k+1; This refers to the parasitic resistance of the inductor. The sampling period; For filtering inductors; This is the filter inductor current; Let be the battery terminal voltage at time k; Let be the DC input voltage at time k; It is in the on / off state.

[0080] To address the inherent time delay problem in digital control systems, a two-step prediction mechanism is introduced. Two-step Prediction ): Using system models to deduce k The current at +1 is used to compensate for the inherent one-step delay of the digital control system; then, based on this, all switching combinations are... S Unfolding the traversal to predict k Current response at time +2 I L p ( k+ 2).

[0081] The expression for the predicted current response at time k+2 is:

[0082] (7);

[0083] in, The predicted current response at time k+2; This is the predicted current value at time k+1; This refers to the parasitic resistance of the inductor. The sampling period; For filtering inductors; This is the filter inductor current; Let be the battery terminal voltage at time k; Let be the DC input voltage at time k; It is in the on / off state.

[0084] based on k The predicted value at time +1 is obtained by traversing the effective voltage vectors in the finite control set and using the deadbeat principle to solve for the value that enables... k At +2, the ideal duty cycle ensures accurate current tracking of the reference value. dideal Compare it with a fixed grid duty cycle d grid Together they form a candidate set.

[0085] Step 4: Using the pre-constructed composite cost function, evaluate the weighted sum of the deviations between the current response at time k+2 and the corrected reference current command. Optimize the switching state corresponding to the voltage vector that minimizes the composite cost function to drive the switching transistors of the full-bridge converter and simultaneously acquire the battery-side voltage and current response signals. This process yields the optimal vector that minimizes the cost function. x best and optimal duty cycle d best , used to drive the switching transistors of the full-bridge converter.

[0086] In step 4, the calculation process of the composite cost function is as follows:

[0087] The first deviation is calculated by subtracting the modified variable frequency sinusoidal AC disturbance command from the predicted AC component.

[0088] The second deviation is calculated by subtracting the DC charging command from the predicted DC current component.

[0089] The composite cost function is obtained by weighted summation of the first and second biases.

[0090] To achieve decoupled control of DC charging and AC disturbance, a weighted composite cost function J is constructed:

[0091] (8);

[0092] ;

[0093] ;

[0094] in, This is the first deviation; This is the second deviation; , These are the weights of the first deviation and the second deviation, respectively. This is the modified variable frequency sinusoidal AC disturbance command; The predicted AC component; DC charging command; This represents the predicted DC current component.

[0095] Step 5: Extract the amplitude and phase information of the signal at different target frequencies from the synchronously acquired battery-side voltage and current response signals. Calculate the amplitude and phase of the battery impedance in situ according to the impedance formula, and finally generate the battery impedance spectrum. The impedance formula is the ratio of voltage to current.

[0096] The battery in-situ impedance testing method based on adaptive phase compensation proposed in this invention has a simple implementation process and can be directly integrated into the full-bridge converter control unit of the energy storage battery charging and testing system. It can achieve in-situ EIS testing without adding an extra hardware excitation source, without increasing costs, and can be widely applied in battery testing systems.

[0097] The dynamic performance and adaptive phase correction capability of the proposed battery in-situ impedance testing method based on adaptive phase compensation were verified through software simulation. MATLAB / Simulink 2024a was used for simulation, and the simulation parameters are shown in Table 1.

[0098] Table 1 Simulation parameters;

[0099] <![CDATA[Input voltage V in > 1500 V <![CDATA[Battery voltage V bat > 400 V <![CDATA[Filter inductor L f1 、 L f2 > 1 mH <![CDATA[Filter capacitor C 2]]> 80F <![CDATA[Output inductance measurement L g > 30H <![CDATA[Switching frequency f sw > 100 kHz <![CDATA[Sampling frequency f s > 50 kHz Step size factor 0.5 Excitation signal frequency 0.01 Hz-2 kHz

[0100] The simulation results of the adaptive phase compensation battery in-situ impedance test control proposed in this invention are compared with those of the traditional PI control method and the traditional MPC control method.

[0101] MPC control, or Model Predictive Control, obtains the current control action at each sampling instant by solving a finite-time open-loop optimal control problem. The current state of the process serves as the initial state of the optimal control problem, and the resulting optimal control sequence only implements the first control action. This is its biggest difference from algorithms that use pre-computed control laws. Essentially, Model Predictive Control solves an open-loop optimal control problem. Its concept is independent of the specific model, but its implementation is model-dependent.

[0102] The battery in-situ impedance testing method based on adaptive phase compensation in this invention is a control method that combines the minimum mean square error algorithm with the model prediction algorithm.

[0103] Figure 5 Figures (a), (b), and (c) show the output current tracking performance under a 100 Hz excitation signal obtained by applying PI control, traditional MPC control, and the present invention. The solid line represents the reference value of the output current, with a magnitude of [80 + 10sin(200πt)] A, and the dashed line represents the actual value of the output current. It can be seen that when the frequency of the excitation signal is low, all three control methods can effectively track the excitation signal, but the response speed of MPC control and the present invention is significantly better than that of traditional PI control.

[0104] Figure 5 Figures (d), (e), and (f) show the output current tracking performance under a 1000Hz excitation signal obtained by applying PI control, traditional MPC control, and the present invention. The solid line represents the reference value of the output current, with a magnitude of [80 + 10sin(2000πt)] A, and the dashed line represents the actual value of the output current. It can be seen that when the frequency of the excitation signal is high, traditional PI control can no longer effectively track the excitation signal. Furthermore, traditional MPC control introduces a phase difference with the reference current during tracking, while the present invention can eliminate this phase difference in a short time.

[0105] Figure 5 Figures (g), (h), and (i) in the diagram represent the output current tracking performance under a 2000 Hz excitation signal obtained by applying PI control, traditional MPC control, and the present invention. It can be seen that as the frequency of the excitation signal increases, the phase difference between the actual output current and the reference current gradually increases, while the present invention can track and eliminate this phase difference in real time.

[0106] In summary, traditional PI control methods can effectively track excitation signals at low frequencies, but as the frequency of the excitation signal increases, traditional PI control methods struggle to achieve effective tracking within a short time. While traditional MPC control methods exhibit good dynamic performance at different frequencies, a phase difference exists between the actual output current and the reference current as the excitation signal frequency increases. This phase difference increases with frequency, leading to significant phase distortion of the impedance spectrum in EIS testing. Specifically, the Nyquist plot rotates in the complex plane, causing the identified high-frequency ohmic resistance value to deviate significantly from the true value and masking the weak inductive or SEI film impedance characteristics of the battery at high frequencies. The adaptive phase-compensated in-situ battery impedance testing control method of this invention maintains the good dynamic performance of the MPC algorithm while achieving zero-phase-difference tracking of the excitation signal, significantly expanding the bandwidth of in-situ EIS testing and ensuring the authenticity and reliability of the measured impedance spectrum.

[0107] In one or more embodiments, a battery in-situ impedance test and control system based on adaptive phase compensation is also provided, which can be implemented in software. The battery in-situ impedance test and control system based on adaptive phase compensation includes the following software modules:

[0108] The real-time phase lag angle calculation module is used to obtain the initial reference current and the actual sampled current of the battery charging and testing system and calculate the difference between the two as an error signal. The orthogonal component of the initial reference current is used as the gradient signal. The module combines the least mean square adaptive algorithm and the stochastic gradient descent method to iteratively calculate the real-time phase lag angle.

[0109] The reference current command correction module is used to use the real-time phase lag angle as the feedforward compensation amount to perform phase pre-lead correction on the initial reference current and generate the corrected reference current command.

[0110] The two-step current response prediction module is used for the discrete mathematical model of the full-bridge converter in continuous conduction mode based on the battery charging and testing system. It combines the sampled current and switching state of the full-bridge converter at time k to calculate the current prediction value at time k+1. Then, it traverses all possible voltage vectors in the full-bridge converter to predict the current response at time k+2; k is a positive integer greater than or equal to 1.

[0111] The composite cost function optimization module is used to evaluate the weighted sum of the deviations between the current response at time k+2 and the corrected reference current command using a pre-constructed composite cost function, and find the switching state corresponding to the voltage vector that minimizes the composite cost function, so as to drive the switching transistors of the full-bridge converter and simultaneously acquire the battery-side voltage and current response signals at this time.

[0112] The battery impedance spectrum generation module is used to extract the amplitude and phase information of the signal at different target frequencies from the synchronously acquired battery side voltage and current response signals, calculate the amplitude and phase of the battery impedance in situ according to the impedance formula, and finally generate the battery impedance spectrum.

[0113] It should be noted that each module in the battery in-situ impedance test control system based on adaptive phase compensation in this embodiment corresponds one-to-one with each step in the battery in-situ impedance test method based on adaptive phase compensation in the above embodiment, and their specific implementation processes are the same, so they will not be repeated here.

[0114] The structure of the electronic device according to embodiments of the present invention will be described in detail below. The electronic device provided in embodiments of the present invention includes: at least one processor, a memory, a user interface, and at least one network interface. The various components in the battery in-situ impedance test and control system based on adaptive phase compensation are coupled together through a bus system. It can be understood that the bus system is used to realize the connection and communication between these components. In addition to a data bus, the bus system also includes a power bus, a control bus, and a status signal bus. The user interface may include a display, keyboard, mouse, trackball, click wheel, buttons, a touchpad, or a touch screen, etc.

[0115] It is understood that the memory can be volatile memory or non-volatile memory, or both. The memory in this embodiment of the invention is capable of storing data to support the operation of the terminal. Examples of this data include any computer programs used to operate on the terminal, such as operating systems and applications. The operating system includes various system programs, such as the framework layer, core library layer, driver layer, etc., used to implement various basic services and handle hardware-based tasks. Applications can include various applications.

[0116] In some embodiments, the battery in-situ impedance test control system based on adaptive phase compensation provided in this invention can be implemented using a combination of hardware and software. As an example, the battery in-situ impedance test control system based on adaptive phase compensation provided in this invention can be a processor in the form of a hardware decoding processor, which is programmed to execute the battery in-situ impedance test method based on adaptive phase compensation provided in this invention. For example, the processor in the form of a hardware decoding processor can employ one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components.

[0117] As an example, a processor can be an integrated circuit chip with signal processing capabilities, such as a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., where a general-purpose processor can be a microprocessor or any conventional processor, etc.

[0118] As an example of the hardware implementation of the battery in-situ impedance test control system based on adaptive phase compensation provided in this embodiment of the invention, the device provided in this embodiment of the invention can be directly executed by a processor in the form of a hardware decoding processor. For example, it can be executed by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic components to implement the battery in-situ impedance test method based on adaptive phase compensation provided in this embodiment of the invention.

[0119] The memory in this embodiment of the invention is used to store various types of data to support the operation of the battery in-situ impedance test control system based on adaptive phase compensation, or to store data for execution. Figure 4 The program code for the method shown. Examples of this data include: any executable instructions for operation on a battery in-situ impedance test control system based on adaptive phase compensation, such as executable instructions that can be included in the executable instructions to implement the battery in-situ impedance test method based on adaptive phase compensation of the present invention.

[0120] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including functions for executing... Figure 4 The program code for the method shown. In such an embodiment, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by the central processing unit, it performs the various functions defined in the apparatus of this application.

[0121] 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, as well as 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. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0122] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A battery in-situ impedance test method based on adaptive phase compensation, characterized in that, include: The initial reference current and the actual sampled current of the battery charging and testing system are obtained, and the difference between the two is calculated as the error signal. The orthogonal component of the initial reference current is used as the gradient signal. The real-time phase lag angle is iteratively calculated by combining the least mean square adaptive algorithm and the stochastic gradient descent method. The real-time phase lag angle is used as the feedforward compensation amount to perform phase pre-lead correction on the initial reference current and generate the corrected reference current command. The discrete mathematical model of the full-bridge converter in continuous conduction mode based on the battery charging and testing system is used to calculate the current prediction value at time k+1 by combining the sampled current and switching state of the full-bridge converter at time k. Then, all possible voltage vectors in the full-bridge converter are traversed to predict the current response at time k+2; k is a positive integer greater than or equal to 1. Using a pre-constructed composite cost function, the weighted sum of the deviations between the current response at time k+2 and the corrected reference current command is evaluated. The switching state corresponding to the voltage vector that minimizes the composite cost function is found, so as to drive the switching transistors of the full-bridge converter and simultaneously acquire the battery-side voltage and current response signals at this time. From the synchronously acquired battery-side voltage and current response signals, the amplitude and phase information of the signals at different target frequencies are extracted. The amplitude and phase of the battery impedance are calculated in situ according to the impedance formula, and finally the battery impedance spectrum is generated. The expression for iteratively calculating the real-time phase lag angle is: ； wherein, is the phase-lag angle at time k+1; is the phase-lag angle at time k; is the step factor; is the error signal; is the gradient signal; is the sampling period; The expression for the predicted current value at time k+1 is: ； wherein, is the current prediction value at k+1 time instant; is the inductance parasitic resistance; is the sampling period; is the filtered inductance; is the filtered inductance current; is the battery terminal voltage at k time instant; is the DC input voltage at k time instant; is the switching state.

2. The battery in-situ impedance test method based on adaptive phase compensation of claim 1, wherein, The process of generating the corrected reference current command is as follows: Keeping the amplitude and frequency of the initial reference current unchanged, the real-time phase lag angle is superimposed on the phase parameter of the initial reference current to generate a sinusoidal signal with a pre-lead phase as the AC tracking target, and then superimposed on the DC charging command to obtain the corrected reference current command.

3. The battery in-situ impedance test method based on adaptive phase compensation of claim 1, wherein, The initial reference current includes a DC charging command and a variable frequency sinusoidal AC disturbance command; the corrected initial reference current includes a constant DC charging command and a corrected variable frequency sinusoidal AC disturbance command; the current response includes the predicted DC current component and AC component.

4. The battery in-situ impedance test method based on adaptive phase compensation of claim 3, wherein, The calculation process of the composite cost function is as follows: The first deviation is calculated by subtracting the modified variable frequency sinusoidal AC disturbance command from the predicted AC component. The second deviation is calculated by subtracting the DC charging command from the predicted DC current component. The composite cost function is obtained by weighted summation of the first and second biases.

5. The battery in-situ impedance test method based on adaptive phase compensation of claim 1, wherein, The expression for the predicted current response at time k+2 is: ； in, The predicted current response at time k+2; This is the predicted current value at time k+1; This refers to the parasitic resistance of the inductor. The sampling period; For filtering inductors; This is the filter inductor current; Let be the battery terminal voltage at time k; Let be the DC input voltage at time k; It is in the on / off state.

6. A battery in-situ impedance testing and control system based on adaptive phase compensation, characterized in that, The battery in-situ impedance testing method based on adaptive phase compensation as described in any one of claims 1-5 includes: The real-time phase lag angle calculation module is used to obtain the initial reference current and the actual sampled current of the battery charging and testing system and calculate the difference between the two as an error signal. The orthogonal component of the initial reference current is used as the gradient signal. The module combines the least mean square adaptive algorithm and the stochastic gradient descent method to iteratively calculate the real-time phase lag angle. The reference current command correction module is used to use the real-time phase lag angle as the feedforward compensation amount to perform phase pre-lead correction on the initial reference current and generate the corrected reference current command. The two-step current response prediction module is used for the discrete mathematical model of the full-bridge converter in continuous conduction mode based on the battery charging and testing system. It combines the sampled current and switching state of the full-bridge converter at time k to calculate the current prediction value at time k+1. Then, it traverses all possible voltage vectors in the full-bridge converter to predict the current response at time k+2; k is a positive integer greater than or equal to 1. The composite cost function optimization module is used to evaluate the weighted sum of the deviations between the current response at time k+2 and the corrected reference current command using a pre-constructed composite cost function, and find the switching state corresponding to the voltage vector that minimizes the composite cost function, so as to drive the switching transistors of the full-bridge converter and simultaneously acquire the battery-side voltage and current response signals at this time. The battery impedance spectrum generation module is used to extract the amplitude and phase information of the signal at different target frequencies from the synchronously acquired battery side voltage and current response signals, calculate the amplitude and phase of the battery impedance in situ according to the impedance formula, and finally generate the battery impedance spectrum.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the battery in-situ impedance testing method based on adaptive phase compensation as described in any one of claims 1-5.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the battery in-situ impedance testing method based on adaptive phase compensation as described in any one of claims 1-5.

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