Multi-mode depolarization pulse sequence control method and system

Abstract

The invention relates to the technical field of battery charging, and particularly provides a multi-mode depolarization pulse sequence control method and system, and the method comprises the steps: monitoring the polarization impedance Rp (t) of a battery in real time, building a four-dimensional dynamic model containing the Rp (t), SOC, SOH and temperature T, and calculating a depolarization parameter; designing a multi-mode depolarization pulse sequence, and automatically switching a sine wave mode, a square wave mode or a compound wave mode according to polarization impedance; and a closed-loop feedback optimization mechanism is constructed based on the voltage recovery rate, and pulse parameters are optimized in real time in combination with fuzzy logic. Compared with the prior art, the service life of the battery can be prolonged, the cycle life is prolonged by 35%, and the risks of lithium precipitation and thermal runaway are reduced. Adaptability is enhanced, and dynamic parameter optimization of different battery types (LFP, NMC and the like) and aging states is supported.

Description

Technical Field

[0001] The present invention relates to the technical field of battery charging, and in particular provides a multi-modal depolarization pulse sequence control method and system. Background Art

[0002] Traditional pulse charging technology reduces battery polarization by periodically applying charging pulses and rest periods, but it has the following problems:

[0003] (1) Fixed depolarization parameters: The amplitude and duration of the depolarization pulse are not dynamically adjusted according to the real-time polarization state of the battery, resulting in insufficient depolarization effect in high-polarization scenarios. The waveform is single and relies only on a square wave depolarization pulse with a fixed amplitude, which cannot adapt to the differences in electrochemical characteristics of different battery types and aging levels.

[0004] (2) Lack of closed-loop feedback: The subsequent pulse parameters are not optimized in combination with the voltage recovery characteristics after depolarization, which can easily lead to excessive depolarization or residual polarization. Summary of the Invention

[0005] The present invention aims to overcome the above-mentioned deficiencies in the prior art and provides a multi-modal depolarization pulse sequence control method with strong practicality.

[0006] A further technical task of the present invention is to provide a multi-modal depolarization pulse sequence control system that is rationally designed, safe and applicable.

[0007] The technical solution adopted by the present invention to solve its technical problem is:

[0008] A multi-modal depolarization pulse sequence control method monitors the battery polarization impedance Rp(t) in real time, establishes a four-dimensional dynamic model including Rp(t), SOC, SOH, and temperature T, and calculates the depolarization parameters. The multi-modal depolarization pulse sequence is designed to automatically switch between sine wave, square wave, or composite wave modes according to the polarization impedance.

[0009] A closed-loop feedback optimization mechanism is constructed based on the voltage recovery rate, and the pulse parameters are optimized in real time by combining fuzzy logic.

[0010] Furthermore, a real-time monitoring and dynamic model of polarization impedance is established. Through multi-sinusoidal excitation and fast Fourier transform technology, a 10mHz-1MHz broadband signal is injected during the charging interval to obtain the battery polarization impedance Rp(t) in real time. A four-dimensional dynamic model including polarization impedance Rp(t), state of charge SOC(t), temperature T(t), and state of health SOH(t) is established to calculate the optimal depolarization parameters.

[0011] Furthermore, the four-dimensional dynamic model is:

[0012]

[0013] Among them, I depol is the depolarization current amplitude, t depol is the depolarization duration, f depol is the sinusoidal wave pulse frequency, k1~k5 are battery characteristic calibration coefficients, and L and C are battery equivalent circuit parameters.

[0014] Furthermore, when designing a multimodal depolarization pulse sequence, the positive wave mode is in the low polarization scene R p <R th Under the applied frequency f depol Sine wave pulses promote uniform diffusion of lithium ions;

[0015] The square wave mode is in the middle polarization scenario R th ≤R p <R th Under the condition of high current, short-term discharge is used to break the ion concentration gradient;

[0016] The composite wave mode is in the high polarization scenario R p ≥2R th Under the condition of sine wave and square wave pulses, active depolarization and natural recovery were combined.

[0017] According to the real-time polarization impedance R p (t) Automatically switch waveform mode and threshold R th Dynamically adjusted by battery type and aging state.

[0018] Furthermore, in the closed-loop feedback optimization mechanism, after each depolarization pulse, the voltage recovery curve V rec (t), calculate the voltage recovery rate:

[0019] ηrec=V o cv-Vrec(tstart)Vrec(tend)-Vrec(tstart);

[0020] Where V ocv is the open circuit voltage of the battery, if the recovery rate η rec <80%, increase the depolarizing current amplitude Idepol or prolong the duration t depol If η rec If the value is >95%, reduce the parameter to avoid excessive depolarization.

[0021] Furthermore, a fuzzy controller is designed with the input variable being the polarization impedance R p , voltage recovery rate η rec and temperature T, the output variables are the amplitude adjustment coefficient α and frequency adjustment coefficient β of the depolarization pulse, and the depolarization parameters are adjusted in real time through fuzzy reasoning to improve the control robustness and adaptability.

[0022] Furthermore, during operation, the battery BMS data is first read, the equivalent circuit parameters L and C are calibrated, the battery type calibration table is loaded, a multi-sine signal is injected every 50ms, and the polarization impedance R is obtained through FFT analysis. p (t), according to R p (t) Select the waveform mode and substitute it into the four-dimensional model to calculate I depol (t), t depol (t), f depol (t), drive the H-bridge circuit to output the corresponding waveform, synchronously monitor the voltage recovery curve, and calculate the voltage recovery rate η rec , adjust the parameters through fuzzy logic, and repeat the above until charging is completed.

[0023] A multi-modal depolarization pulse sequence control system includes a multi-modal pulse generation module, a polarization impedance measurement module, a fuzzy logic control module and a closed-loop feedback module;

[0024] The multi-modal pulse generation module is used to integrate an H-bridge circuit and supports sine wave, square wave and composite wave output;

[0025] The polarization impedance measurement module is used to implement 10ms-level impedance measurement using the AD7706 high-precision ADC in combination with multi-sine excitation technology;

[0026] The fuzzy logic control module is used to process sensor data in real time and generate control instructions based on the GD32F407 microcontroller;

[0027] The closed-loop feedback module is used to evaluate the depolarization effect in real time through a voltage monitoring circuit and dynamically adjust the pulse parameters.

[0028] Compared with the prior art, the multi-modal depolarization pulse sequence control method and system of the present invention have the following outstanding beneficial effects:

[0029] This invention improves depolarization efficiency, reducing polarization impedance by over 30% and shortening charging time by 15%-20% compared to traditional three-stage discharge. It also extends battery life, increasing cycle life (80% DOE) by 35%, and reducing the risks of lithium plating and thermal runaway. It also enhances adaptability and supports dynamic parameter optimization for different battery types (such as LFP and NMC) and aging states. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the solutions of the present invention, the present invention will be further described in detail below in conjunction with specific embodiments. Obviously, the embodiments described are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0031] A best embodiment is given below:

[0032] In this embodiment, a multi-modal depolarization pulse sequence control method monitors the battery polarization impedance Rp(t) in real time, establishes a four-dimensional dynamic model including Rp(t), SOC, SOH, and temperature T, and calculates depolarization parameters. A multi-modal depolarization pulse sequence is designed to automatically switch between sine wave, square wave, or composite wave modes according to the polarization impedance.

[0033] A closed-loop feedback optimization mechanism is constructed based on the voltage recovery rate, and the pulse parameters are optimized in real time by combining fuzzy logic.

[0034] Among them, a real-time monitoring and dynamic model of polarization impedance is established. Through multi-sinusoidal excitation and fast Fourier transform (FFT) technology, a 10mHz-1MHz broadband signal is injected during the charging interval to obtain the battery polarization impedance Rp(t) in real time. A four-dimensional dynamic model including polarization impedance Rp(t), state of charge SOC(t), temperature T(t), and state of health SOH(t) is established to calculate the optimal depolarization parameters.

[0035] The four-dimensional dynamic model is:

[0036]

[0037] Among them, I depol is the depolarization current amplitude, t depol is the depolarization duration, f depol is the sinusoidal wave pulse frequency, k1~k5 are battery characteristic calibration coefficients, and L and C are battery equivalent circuit parameters.

[0038] When designing a multimodal depolarization pulse sequence, the positive wave mode is used in the low polarization scene R p <R th Under the applied frequency f depol Sine wave pulses promote uniform diffusion of lithium ions;

[0039] Square wave mode is for the medium polarization scenario R th ≤R p <R th Under the condition of high current, short-term discharge (-2C to -5C) is used to break the ion concentration gradient.

[0040] The composite wave mode is in the high polarization scenario R p ≥2R th Under the condition of sine wave and square wave pulses, active depolarization and natural recovery were combined.

[0041] According to the real-time polarization impedance R p (t) Automatically switch waveform mode and threshold R thDynamically adjusted by battery type and aging state.

[0042] In the closed-loop feedback optimization mechanism, after each depolarization pulse, the voltage recovery curve V rec (t), calculate the voltage recovery rate:

[0043] ηrec=V o cv-Vrec(tstart)Vrec(tend)-Vrec(tstart);

[0044] Where V ocv is the open circuit voltage of the battery, if the recovery rate η rec <80%, increase the depolarizing current amplitude Idepol or prolong the duration t depol If η rec If the value is >95%, reduce the parameter to avoid excessive depolarization.

[0045] Design a fuzzy controller with the polarization impedance R as input variable p , voltage recovery rate η rec and temperature T, the output variables are the amplitude adjustment coefficient α and frequency adjustment coefficient β of the depolarization pulse, and the fuzzy rules are as follows:

[0046]

[0047] The depolarization parameters are adjusted in real time through fuzzy reasoning to improve the control robustness and adaptability.

[0048] At runtime:

[0049] (1) Initialization: Read the battery BMS data, calibrate the equivalent circuit parameters L and C, and load the battery type calibration table.

[0050] (2) Real-time impedance measurement: Inject multiple sinusoidal signals every 50ms and obtain the polarization impedance R through FFT analysis p (t);

[0051] (3) Mode selection and parameter calculation: According to R p (t) Select the waveform mode and substitute it into the four-dimensional model to calculate I depol (t), t depol (t), f depol (t);

[0052] (4) Pulse sequence generation: driving the H-bridge circuit to output the corresponding waveform and synchronously monitoring the voltage recovery curve;

[0053] (5) Closed-loop optimization: Calculation of voltage recovery rate η rec , adjust the parameters through fuzzy logic, and repeat steps (2) to (5) above until charging is completed.

[0054] Based on the above method, a multi-modal depolarization pulse sequence control system in this embodiment includes a multi-modal pulse generation module, a polarization impedance measurement module, a fuzzy logic control module and a closed-loop feedback module;

[0055] Among them, the multi-modal pulse generation module is used to integrate the H-bridge circuit and supports sine wave, square wave and composite wave output;

[0056] The polarization impedance measurement module uses the AD7706 high-precision ADC and multi-sine excitation technology to achieve 10ms-level impedance measurement.

[0057] The fuzzy logic control module is used to process sensor data in real time and generate control instructions based on the GD32F407 microcontroller;

[0058] The closed-loop feedback module is used to evaluate the depolarization effect in real time through the voltage monitoring circuit and dynamically adjust the pulse parameters.

[0059] The above-mentioned specific implementation methods are only specific cases of the present invention. The patent protection scope of the present invention includes but is not limited to the above-mentioned specific implementation methods. Any technical solutions that conform to the above-mentioned specific implementation methods of the present invention and any appropriate changes or substitutions made thereto by ordinary technicians in the relevant technical field shall fall within the patent protection scope of the present invention.

[0060] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A multi-modal depolarization pulse sequence control method, characterized in that: Real-time monitoring of battery polarization impedance Rp(t), establishment of a four-dimensional dynamic model including Rp(t), SOC, SOH, and temperature T, and calculation of depolarization parameters; design of a multi-modal depolarization pulse sequence, automatically switching between sine wave, square wave, or composite wave modes according to polarization impedance; A closed-loop feedback optimization mechanism is constructed based on the voltage recovery rate, and the pulse parameters are optimized in real time by combining fuzzy logic.

2. A multi-modal depolarization pulse sequence control method according to claim 1, characterized in that: A real-time monitoring and dynamic model of polarization impedance is established. Through multi-sine excitation and fast Fourier transform technology, a 10mHz-1MHz broadband signal is injected during the charging interval to obtain the battery polarization impedance Rp(t) in real time. A four-dimensional dynamic model including polarization impedance Rp(t), state of charge SOC(t), temperature T(t), and state of health SOH(t) is established to calculate the optimal depolarization parameters.

3. A multi-modal depolarization pulse sequence control method according to claim 2, characterized in that: The four-dimensional dynamic model is: Among them, I depol is the depolarization current amplitude, t depol is the depolarization duration, f depol is the sinusoidal wave pulse frequency, k1~k5 are battery characteristic calibration coefficients, and L and C are battery equivalent circuit parameters.

4. A multi-modal depolarization pulse sequence control method according to claim 3, characterized in that: When designing a multimodal depolarization pulse sequence, the positive wave pattern is in the low polarization scene R p <R th Under the applied frequency f depol Sine wave pulses promote uniform diffusion of lithium ions; The square wave mode is in the middle polarization scenario R th ≤R p <R th Under the condition of high current, short-term discharge is used to break the ion concentration gradient; The composite wave mode is in the high polarization scenario R p ≥2R th Under the condition of sine wave and square wave pulses, active depolarization and natural recovery were combined. According to the real-time polarization impedance R p (t) Automatically switch waveform mode and threshold R th Dynamically adjusted by battery type and aging state.

5. A multi-modal depolarization pulse sequence control method according to claim 4, characterized in that: In the closed-loop feedback optimization mechanism, after each depolarization pulse, the voltage recovery curve V rec (t), calculate the voltage recovery rate: ηrec=V o cv-Vrec(tstart)Vrec(tend)-Vrec(tstart); Where V ocv is the open circuit voltage of the battery, if the recovery rate η rec <80%, increase the depolarizing current amplitude Idepol or prolong the duration t depol If η rec If the value is >95%, reduce the parameter to avoid excessive depolarization.

6. A multi-modal depolarization pulse sequence control method according to claim 5, characterized in that: Design a fuzzy controller with the polarization impedance R as input variable p , voltage recovery rate η rec and temperature T, the output variables are the amplitude adjustment coefficient α and frequency adjustment coefficient β of the depolarization pulse, and the depolarization parameters are adjusted in real time through fuzzy reasoning to improve the control robustness and adaptability.

7. A multi-modal depolarization pulse sequence control method according to claim 6, characterized in that: During operation, the battery BMS data is first read, the equivalent circuit parameters L and C are calibrated, the battery type calibration table is loaded, a multi-sine signal is injected every 50ms, and the polarization impedance R is obtained through FFT analysis. p (t), according to R p (t) Select the waveform mode and substitute it into the four-dimensional model to calculate I depol (t), t depol (t), f depol (t), drive the H-bridge circuit to output the corresponding waveform, synchronously monitor the voltage recovery curve, and calculate the voltage recovery rate η rec , adjust the parameters through fuzzy logic, and repeat the above until charging is completed.

8. A multi-modal depolarization pulse sequence control system, characterized in that: It includes a multi-modal pulse generation module, a polarization impedance measurement module, a fuzzy logic control module and a closed-loop feedback module; The multi-modal pulse generation module is used to integrate an H-bridge circuit and supports sine wave, square wave and composite wave output; The polarization impedance measurement module is used to implement 10ms-level impedance measurement using the AD7706 high-precision ADC in combination with multi-sine excitation technology; The fuzzy logic control module is used to process sensor data in real time and generate control instructions based on the GD32F407 microcontroller; The closed-loop feedback module is used to evaluate the depolarization effect in real time through a voltage monitoring circuit and dynamically adjust the pulse parameters.

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