An adaptive pulse heating control method based on low-temperature impedance characteristics of sodium-ion batteries

Abstract

The application discloses a kind of adaptive pulse heating control methods based on sodium ion battery low-temperature impedance characteristics.The method first establishes the electrochemical impedance spectrum database of sodium ion battery under different temperatures, SOC and SOH, determines the nonlinear mapping relationship between ohmic impedance and charge transfer impedance and temperature;In low-temperature environment, the electrochemical impedance spectrum of battery is measured in real time, and the ohmic impedance and charge transfer impedance value under the current state are extracted;According to the real-time impedance value, the optimal pulse heating parameters are dynamically calculated, including pulse frequency, current amplitude and duty cycle;During the heating process, continuously monitor the impedance and temperature change of battery, adjust the pulse parameters in real time until the battery temperature reaches the preset working temperature.The application solves the problems of low heating efficiency, poor temperature uniformity and easy damage to the battery in the prior art with fixed pulse parameters, and can adaptively adjust the heating strategy according to the real-time impedance characteristics of sodium ion battery, significantly improving the low-temperature heating efficiency.

Description

Technical Field

[0001] This invention relates to the field of battery thermal management technology, specifically to an adaptive pulse heating control method based on the low-temperature impedance characteristics of sodium-ion batteries. Background Technology

[0002] Sodium-ion batteries, with their advantages of abundant sodium resources, low cost, and high safety, have shown great application potential in fields such as grid energy storage, electric two-wheelers, low-speed electric vehicles, and communication base stations. However, the low-temperature performance bottleneck of sodium-ion batteries has always restricted their large-scale application in extreme environments. Currently, the capacity retention rate of mainstream sodium-ion batteries at -20℃ is generally below 60%, the rate performance drops by more than 50% compared to room temperature, and the cycle life is shortened to one-third of that at room temperature.

[0003] At low temperatures, the viscosity of the electrolyte increases dramatically (3-5 times that at room temperature at -20°C), and the ionic conductivity drops to less than 1 / 10 of that at room temperature. This leads to a significant increase in the interfacial impedance of the electrode materials (up to 5-8 times that at room temperature). Simultaneously, the diffusion rate of sodium ions during insertion / extraction slows down (the diffusion coefficient decreases by 2-3 orders of magnitude), and the SEI film ruptures due to repeated contraction / expansion, further exacerbating the loss of active materials and the occurrence of side reactions. These problems not only limit the market expansion of sodium-ion batteries but also make them less competitive in high-value application scenarios such as energy storage in northern winters and low-temperature starting of new energy vehicles.

[0004] In existing technologies, low-temperature heating of batteries mainly employs two methods: external heating and internal self-heating. External heating methods, such as PTC heating films and liquid cooling, suffer from drawbacks such as uneven heating, low energy utilization, high system complexity, and high cost. Internal self-heating methods primarily utilize the battery's internal resistance to generate Joule heat, among which pulse self-heating technology has attracted widespread attention due to its advantages such as fast heating speed and good temperature uniformity.

[0005] However, most existing pulse heating technologies use fixed pulse frequencies, amplitudes, and duty cycles, which cannot be dynamically adjusted based on the real-time impedance characteristics of sodium-ion batteries. Since the impedance of sodium-ion batteries exhibits a significant non-linear change with temperature, state of charge (SOC), and state of equilibrium (SOH), pulse heating with fixed parameters may result in insufficient current and low heating efficiency during the initial low-temperature phase when impedance is high, while excessive current, localized overheating, or even battery damage may occur as impedance decreases with rising temperatures. Furthermore, existing technologies rarely consider the impact of battery aging on heating performance, leading to inconsistent heating performance throughout the battery's lifespan.

[0006] Therefore, there is an urgent need to develop a heating control method that can adaptively adjust pulse parameters based on the real-time impedance characteristics of sodium-ion batteries in order to solve problems such as low heating efficiency, poor temperature uniformity, and easy damage to batteries in existing technologies. Summary of the Invention

[0007] The purpose of this invention is to provide an adaptive pulse heating control method based on the low-temperature impedance characteristics of sodium-ion batteries, so as to solve the problems mentioned above.

[0008] To achieve the above objectives, the present invention provides the following technical solution: an adaptive pulse heating control method based on the low-temperature impedance characteristics of sodium-ion batteries, comprising the following steps: S1: Establish an electrochemical impedance spectroscopy database for sodium-ion batteries at different temperatures, SOC, and SOH, and determine the nonlinear mapping relationship between ohmic impedance R0 and charge transfer impedance Rct and temperature, SOC, and SOH; S2: Real-time acquisition of the battery's ambient temperature, individual cell voltage, current, and SOC value to determine whether the low-temperature heating mode needs to be activated; S3: When heating is required, apply an AC excitation signal with a frequency range of 0.01Hz to 10kHz and an amplitude of 0.05C to 0.2C to the battery, measure the electrochemical impedance spectrum of the battery, and use Randle equivalent circuit fitting to extract the ohmic impedance R0 and charge transfer impedance Rct values ​​under the current state. S4: Calculate the optimal pulse heating parameters based on the real-time measured R0 and Rct values, including pulse frequency f, current amplitude I, and duty cycle D; S5: Apply a bidirectional pulse current to the battery according to the calculated optimal pulse parameters. The positive and negative pulses of the bidirectional pulse current have equal amplitudes and the same duration, and the average value of the pulse current is zero. Use the battery's internal resistance to generate Joule heat to achieve self-heating. S6: During the heating process, steps S3 and S4 are repeated every preset time interval to update the pulse heating parameters in real time; S7: Monitors the voltage and temperature of individual battery cells in real time during the heating process. If the voltage of any individual cell exceeds the upper limit threshold or falls below the lower limit threshold, or if the battery temperature exceeds the safety threshold, heating will be stopped immediately. S8: When the battery temperature reaches the preset operating temperature T0, stop pulse heating and switch to normal operating mode.

[0009] Furthermore, the method for establishing the electrochemical impedance spectroscopy database described in step S1 is as follows: Within the temperature range of -40℃ to 25℃, multiple temperature points are set at 5℃ intervals; At each temperature point, the electrochemical impedance spectroscopy of the battery was tested at different SOC states in 10% increments within the range of 0% to 100% SOC. The above tests were repeated on batteries with different aging levels to obtain a multidimensional database containing temperature, SOC, SOH, R0, and Rct. A third-order polynomial fitting method was used to establish nonlinear function models for R0(T,SOC,SOH) and Rct(T,SOC,SOH).

[0010] Furthermore, the activation conditions for the low-temperature heating mode described in step S2 are as follows: Ambient temperature T_env ≤ 0℃ and battery temperature T_bat ≤ 5℃; or The battery temperature T_bat ≤ 0℃ and a charging command has been received.

[0011] Furthermore, the AC excitation signal mentioned in step S3 is a sine wave signal.

[0012] Furthermore, the method for calculating the optimal pulse heating parameters in step S4 is as follows: The formula for calculating the pulse frequency f is: f = 1 / (2πRctCdl), where Cdl is the double-layer capacitance, which is obtained by fitting the electrochemical impedance spectroscopy. The formula for calculating the current amplitude I is: I = √[P_max / (R0+Rct)], where P_max is the maximum allowable heating power of the battery under the current state; The formula for calculating the duty cycle D is: D = (T0 - T_bat) × m × c / [I²・(R0 + Rct)・Δt], where m is the battery mass, c is the battery specific heat capacity, and Δt is the heating time interval; When the calculated duty cycle D > 1, take D = 100%.

[0013] Furthermore, the frequency range of the bidirectional pulse current in step S5 is 1 kHz to 50 kHz, and the current amplitude range is 0.1 C to 1 C.

[0014] Furthermore, the preset time interval mentioned in step S6 is 10s to 60s, and when the battery temperature change rate exceeds 1℃ / min, the time interval is shortened to 1 / 2 of the original interval, but not less than 5s.

[0015] Furthermore, step S7 also includes: Real-time monitoring of battery temperature uniformity; when the maximum temperature difference within the battery pack exceeds 5°C, reduce the pulse current amplitude or adjust the pulse frequency. The battery's state of equilibrium (SOH) is monitored in real time. When the SOH is below 80%, the maximum heating power P_max is reduced to 70% of the new battery's rated maximum heating power.

[0016] Furthermore, the preset operating temperature T0 mentioned in step S8 is 10°C to 25°C, and can be adjusted according to different application scenarios.

[0017] The present invention also provides a battery management system for implementing the above method, comprising: The data acquisition module is used to collect battery voltage, current, temperature, and SOC information; The impedance measurement module is used to apply an AC excitation signal with a frequency range of 0.01Hz to 10kHz and an amplitude of 0.05C to 0.2C to the battery and measure the electrochemical impedance spectrum of the battery. The ohmic impedance R0 and charge transfer impedance Rct values ​​are extracted by Randle equivalent circuit fitting. The control module has a built-in electrochemical impedance spectroscopy database and pulse parameter calculation algorithm, which is used to calculate the optimal pulse heating parameters based on the real-time impedance value and generate pulse control signals. The power conversion module adopts a bidirectional DC / DC converter topology to output bidirectional pulse current to the battery with equal positive and negative pulse amplitudes, the same duration, and zero average value, according to the pulse control signal. The safety protection module is used to immediately stop the heating operation in case of abnormal conditions such as overvoltage, undervoltage, overtemperature, excessive temperature difference, or excessively low SOH.

[0018] Equivalent Circuit Model Explanation: This invention employs the classic Randle equivalent circuit to fit the electrochemical impedance spectrum. This circuit consists of an ohmic impedance R0, a charge transfer impedance Rct, and a double-layer capacitance Cdl connected in series. R0 represents the ohmic resistance of the electrolyte, current collector, and electrode materials, exhibiting a weakly nonlinear relationship with temperature; Rct represents the charge transfer resistance at the electrode / electrolyte interface, exhibiting a strong exponential relationship with temperature and being a major component of the battery's internal resistance at low temperatures; Cdl represents the double-layer capacitance at the electrode / electrolyte interface, which changes relatively little with temperature and state of charge (SOC).

[0019] The theoretical basis for pulse frequency selection: This invention selects a pulse frequency f = 1 / (2πτ) that matches the time constant τ = RctCdl of the charge transfer process. At this frequency, the heating contribution of the charge transfer impedance Rct reaches its maximum value, which can significantly improve heating efficiency. Compared with fixed frequency heating, adaptive frequency heating can increase the heating power at low temperatures by more than 30%.

[0020] Compared with the prior art, the beneficial effects of the present invention are: (1) Based on the real-time impedance characteristics of sodium-ion batteries, the present invention dynamically adjusts the pulse heating parameters, which can always maintain the optimal heating efficiency. Experiments show that compared with fixed parameter pulse heating, the present invention increases the heating rate by more than 40% and reduces energy consumption by more than 25% in an environment of -20℃.

[0021] (2) The present invention uses bidirectional pulse current heating, and the average value of the pulse current is zero, which will not cause the battery to be overcharged or over-discharged. At the same time, it can generate periodic current fluctuations on the electrode surface, effectively suppressing the nucleation and growth of sodium dendrites and extending the battery life.

[0022] (3) The present invention takes into account the influence of battery SOC and SOH states on impedance characteristics, and can achieve stable heating performance throughout the battery life cycle, avoiding the decline in heating effect caused by battery aging.

[0023] (4) The present invention has multiple safety protection mechanisms that can monitor the battery voltage, temperature and SOH status in real time and stop heating immediately when an abnormal situation occurs, so as to ensure the safety of battery use. Detailed Implementation

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] Key parameter values: In this invention, the typical value of the battery specific heat capacity c is 1000 J / (kg·℃), the typical value of the thermal conductivity k is 0.85 W / (℃·kg), the battery safety temperature threshold is 45℃, the upper limit threshold of the single-cell voltage is 3.6V, and the lower limit threshold is 2.0V. SOC estimation uses the ampere-hour integration method combined with the open-circuit voltage method, with an estimation accuracy of ±3%; SOH estimation uses the capacity decay method, i.e., SOH = current actual capacity / rated capacity × 100%. Example

[0026] This embodiment provides an adaptive pulse heating control method based on the low-temperature impedance characteristics of sodium-ion batteries. The specific steps are as follows: Step 1: Establish an electrochemical impedance spectroscopy database A sodium vanadium phosphate-based sodium-ion battery, model NP-01, with a rated capacity of 50 Ah and a rated voltage of 3.2 V, was selected. Electrochemical impedance spectroscopy (EIS) of the battery at 11 state of charge (SOC) states (0%, 10%, 20%, ..., 100%) was measured in a high and low temperature test chamber at 14 temperature points: -40℃, -35℃, -30℃, -25℃, -20℃, -15℃, -10℃, -5℃, 0℃, 5℃, 10℃, 15℃, 20℃, and 25℃.

[0027] Impedance testing was performed using an electrochemical workstation with an AC excitation signal of 0.1C and a frequency range of 0.01Hz to 10kHz. The obtained impedance spectrum was fitted using a Randle equivalent circuit to extract the ohmic impedance R0, charge transfer impedance Rct, and double-layer capacitance Cdl for each state.

[0028] The above tests were repeated for batteries with different aging levels (SOH of 100%, 90%, 80%, and 70%) to obtain a multidimensional database containing temperature, SOC, SOH, R0, Rct, and Cdl. A third-order polynomial fitting method was used to establish nonlinear function models for R0(T,SOC,SOH) and Rct(T,SOC,SOH). R0(T,SOC,SOH)=a0+a1T+a2T²+a3T³+b1SOC+b2SOC²+b3SOC³+c1SOH+c2SOH²+c3SOH³ Rct(T,SOC,SOH)=d0+d1T+d2T²+d3T³+e1SOC+e2SOC²+e3SOC³+f1SOH+f2SOH²+f3SOH³ Among them, a0-a3, b1-b3, c1-c3, d0-d3, e1-e3, and f1-f3 are fitting coefficients.

[0029] Step 2: Determine whether to activate the low-temperature heating mode. The battery management system collects ambient temperature, battery temperature, individual cell voltage, current, and SOC value in real time. When the ambient temperature is detected to be -20℃, the battery temperature to be -18℃, and the SOC to be 50%, the low-temperature heating mode activation conditions are met (ambient temperature ≤0℃ and battery temperature ≤5℃), and the pulse heating program is activated.

[0030] Step 3: Measure battery impedance in real time A sinusoidal AC excitation signal with an amplitude of 0.1C and a frequency range of 0.01Hz to 10kHz was applied to the battery, and the electrochemical impedance spectrum of the battery was measured. By fitting the Randle equivalent circuit, the ohmic impedance R0 = 85mΩ, the charge transfer impedance Rct = 210mΩ, and the double-layer capacitance Cdl = 120μF were extracted for the current state.

[0031] Step 4: Calculate the optimal pulse heating parameters Calculate the optimal pulse heating parameters based on the real-time measured impedance values: Pulse frequency f = 1 / (2πRctCdl) = 1 / (2×3.14×210×10⁻³×120×10⁻ 6 ≈6300Hz The battery's maximum allowable heating power P_max = 100W, and the current amplitude I = √[P_max / (R0+Rct)] = √[100 / (0.085+0.210)] ≈ 18.5A (approximately 0.37C). The preset target temperature T0 = 15℃, battery mass m = 1.2kg, battery specific heat capacity c = 1000J / (kg・℃), and heating time interval Δt = 30s. Duty cycle D = (T0 - T_bat) × m × c / [I²・(R0 + Rct)・Δt] = [15 - (-18)] × 1.2 × 1000 / (18.5² × (0.085 + 0.210) × 30) ≈ 33 × 1200 / (342.25 × 0.295 × 30) ≈ 39600 / 3027 ≈ 1.31 Since the duty cycle cannot exceed 1, we take D=100%.

[0032] Step 5: Apply bidirectional pulse current The power conversion module applies a bidirectional pulse current to the battery according to the calculated pulse parameters (frequency 6300Hz, current amplitude 18.5A, duty cycle 100%). The forward and reverse pulses have equal amplitudes and the same duration, and the average pulse current is zero.

[0033] Step 6: Update pulse parameters in real time Steps 3 and 4 are repeated every 30 seconds to measure the battery impedance in real time and update the pulse heating parameters. When the battery temperature rises to -10℃, R0 = 42mΩ and Rct = 95mΩ are measured, and the following values ​​are recalculated: Pulse frequency f = 1 / (2π × 95 × 10⁻³ × 120 × 10⁻) 6 ≈14000Hz Current amplitude I = √[100 / (0.042+0.095)] ≈ 27.0A (approximately 0.54C) Duty cycle D = [15 - (-10)] × 1.2 × 1000 / (27.0² × (0.042 + 0.095) × 30) ≈ 25 × 1200 / (729 × 0.137 × 30) ≈ 30000 / 3000 ≈ 1.0, take D = 100% When the battery temperature rises to 0℃, the measured values ​​are R0 = 25mΩ and Rct = 45mΩ. The recalculated values ​​are: Pulse frequency f = 1 / (2π×45×10⁻³×120×10⁻) 6 ≈29500Hz Current amplitude I = √[100 / (0.025+0.045)] ≈ 37.8A (approximately 0.76C) Duty cycle D = (15-0) × 1.2 × 1000 / (37.8² × (0.025 + 0.045) × 30) ≈ 15 × 1200 / (1428.84 × 0.07 × 30) ≈ 18000 / 3000 ≈ 0.6, that is, D = 60%. Step 7: Safety Protection Throughout the heating process, the voltage, temperature, and temperature uniformity of each battery cell were monitored in real time. No abnormalities occurred in this embodiment, and the safety protection mechanisms were not triggered.

[0034] Step 8: Stop heating When the battery temperature rises to 15°C, pulse heating stops and switches to normal operating mode. The entire heating process takes about 12 minutes, with an average temperature rise rate of about 2.75°C / min and a maximum temperature difference of 3.2°C within the battery pack. Example

[0035] This embodiment provides a battery management system for implementing the above-described adaptive pulse heating control method, including: The data acquisition module includes voltage sensors, current sensors, temperature sensors, and a SOC estimation unit. The voltage sensors acquire the voltage of each individual battery cell with a measurement accuracy of ±1mV; the current sensors acquire the charging and discharging current of the battery pack with a measurement accuracy of ±0.5%; the temperature sensors, using NTC thermistors, are placed at multiple locations within the battery pack, with a measurement accuracy of ±0.5℃; the SOC estimation unit uses an ampere-hour integration method combined with the open-circuit voltage method to estimate the SOC, with an estimation accuracy of ±3%.

[0036] Impedance measurement module: includes an AC excitation source and an impedance analyzer. The AC excitation source can generate a sinusoidal AC excitation signal with a frequency range of 0.01Hz to 10kHz and an amplitude of 0.05C to 0.2C; the impedance analyzer can measure the impedance value of the battery at different frequencies and extract ohmic impedance, charge transfer impedance, and double-layer capacitance through Randle equivalent circuit fitting.

[0037] Control Module: Employs a 32-bit ARM microcontroller with a built-in electrochemical impedance spectroscopy database and pulse parameter calculation algorithm. The control module receives input signals from the data acquisition module and the impedance measurement module, calculates the optimal pulse heating parameters according to a preset algorithm, and generates corresponding pulse control signals.

[0038] Power conversion module: Adopting a bidirectional DC / DC converter topology, it is composed of IGBT power devices. The power conversion module can output bidirectional pulse current to the battery with a frequency range of 1kHz to 50kHz and a current amplitude range of 0.1C to 1C, based on the pulse control signal output by the control module. The forward and reverse pulses have equal amplitudes and durations, and the average value is zero.

[0039] Safety protection module: Includes overvoltage protection, undervoltage protection, overtemperature protection, temperature difference protection, and SOH protection unit. When any single cell voltage exceeds 3.6V or falls below 2.0V, the battery temperature exceeds 45℃, the maximum temperature difference within the battery pack exceeds 5℃, or the SOH falls below 70%, the heating operation will be stopped immediately and an alarm signal will be issued.

[0040] Comparative example: To verify the beneficial effects of the present invention, a comparative experiment was conducted using the optimal fixed-parameter pulse heating method optimized for the same type of battery in the prior art. The fixed pulse parameters were: frequency 10kHz, current amplitude 20A, and duty cycle 100%.

[0041] Under the same experimental conditions (ambient temperature -20℃, initial battery temperature -18℃, SOC=50%), it took about 17 minutes to heat to 15℃ using a fixed-parameter pulse heating method, with an average heating rate of about 1.94℃ / min, a maximum temperature difference within the battery pack of 6.8℃, and an energy consumption of about 28.3Wh.

[0042] The adaptive pulse heating control method of this invention takes approximately 12 minutes to heat, with an average temperature rise rate of approximately 2.75°C / min, a maximum temperature difference within the battery pack of 3.2°C, and energy consumption of approximately 21.1Wh. Compared to fixed-parameter pulse heating, this invention increases the heating rate by 41.8%, reduces energy consumption by 25.4%, and significantly improves temperature uniformity.

[0043] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0044] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An adaptive pulse heating control method based on the low-temperature impedance characteristics of sodium-ion batteries, characterized in that, Includes the following steps: S1: Establish an electrochemical impedance spectroscopy database for sodium-ion batteries at different temperatures, SOC, and SOH, and determine the nonlinear mapping relationship between ohmic impedance R0 and charge transfer impedance Rct and temperature, SOC, and SOH; S2: Real-time acquisition of the battery's ambient temperature, individual cell voltage, current, and SOC value to determine whether the low-temperature heating mode needs to be activated; S3: When heating is required, apply an AC excitation signal with a frequency range of 0.01Hz to 10kHz and an amplitude of 0.05C to 0.2C to the battery, measure the electrochemical impedance spectrum of the battery, and use Randle equivalent circuit fitting to extract the ohmic impedance R0 and charge transfer impedance Rct values ​​under the current state. S4: Calculate the optimal pulse heating parameters based on the real-time measured R0 and Rct values, including pulse frequency f, current amplitude I, and duty cycle D; S5: Apply a bidirectional pulse current to the battery according to the calculated optimal pulse parameters. The positive and negative pulses of the bidirectional pulse current have equal amplitudes and the same duration, and the average value of the pulse current is zero. Use the battery's internal resistance to generate Joule heat to achieve self-heating. S6: During the heating process, steps S3 and S4 are repeated every preset time interval to update the pulse heating parameters in real time; S7: Monitors the voltage and temperature of individual battery cells in real time during the heating process. If the voltage of any individual cell exceeds the upper limit threshold or falls below the lower limit threshold, or if the battery temperature exceeds the safety threshold, heating will be stopped immediately. S8: When the battery temperature reaches the preset operating temperature T0, stop pulse heating and switch to normal operating mode.

2. The adaptive pulse heating control method according to claim 1, characterized in that, The method for establishing the electrochemical impedance spectroscopy database described in step S1 is as follows: Within the temperature range of -40℃ to 25℃, multiple temperature points are set at 5℃ intervals; At each temperature point, the electrochemical impedance spectroscopy of the battery was tested at different SOC states in 10% increments within the range of 0% to 100% SOC. The above tests were repeated on batteries with different aging levels to obtain a multidimensional database containing temperature, SOC, SOH, R0, and Rct. A third-order polynomial fitting method was used to establish nonlinear function models for R0(T,SOC,SOH) and Rct(T,SOC,SOH).

3. The adaptive pulse heating control method according to claim 1, characterized in that, The conditions for starting the low-temperature heating mode in step S2 are as follows: Ambient temperature T_env ≤ 0℃ and battery temperature T_bat ≤ 5℃; or The battery temperature T_bat ≤ 0℃ and a charging command has been received.

4. The adaptive pulse heating control method according to claim 1, characterized in that, The AC excitation signal mentioned in step S3 is a sine wave signal.

5. The adaptive pulse heating control method according to claim 1, characterized in that, The specific method for calculating the optimal pulse heating parameters described in step S4 is as follows: The formula for calculating the pulse frequency f is: f = 1 / (2πRctCdl), where Cdl is the double-layer capacitance, which is obtained by fitting the electrochemical impedance spectroscopy. The formula for calculating the current amplitude I is: I = √[P_max / (R0+Rct)], where P_max is the maximum allowable heating power of the battery under the current state; The formula for calculating the duty cycle D is: D = (T0 - T_bat) × m × c / [I²・(R0 + Rct)・Δt], where m is the battery mass, c is the battery specific heat capacity, and Δt is the heating time interval; When the calculated duty cycle D > 1, take D = 100%.

6. The adaptive pulse heating control method according to claim 1, characterized in that, The frequency range of the bidirectional pulse current mentioned in step S5 is 1 kHz to 50 kHz, and the current amplitude range is 0.1 C to 1 C.

7. The adaptive pulse heating control method according to claim 1, characterized in that, The preset time interval mentioned in step S6 is 10s to 60s, and when the battery temperature change rate exceeds 1℃ / min, the time interval is shortened to 1 / 2 of the original interval, but not less than 5s.

8. The adaptive pulse heating control method according to claim 1, characterized in that, Step S7 also includes: Real-time monitoring of battery temperature uniformity; when the maximum temperature difference within the battery pack exceeds 5°C, reduce the pulse current amplitude or adjust the pulse frequency. The battery's state of equilibrium (SOH) is monitored in real time. When the SOH is below 80%, the maximum heating power P_max is reduced to 70% of the new battery's rated maximum heating power.

9. The adaptive pulse heating control method according to claim 1, characterized in that, The preset operating temperature T0 mentioned in step S8 is 10℃ to 25℃, and can be adjusted according to different application scenarios.

10. A battery management system implementing the method of any one of claims 1-9, characterized in that, include: The data acquisition module is used to collect battery voltage, current, temperature, and SOC information; The impedance measurement module is used to apply an AC excitation signal with a frequency range of 0.01Hz to 10kHz and an amplitude of 0.05C to 0.2C to the battery and measure the electrochemical impedance spectrum of the battery. The ohmic impedance R0 and charge transfer impedance Rct values ​​are extracted by Randle equivalent circuit fitting. The control module has a built-in electrochemical impedance spectroscopy database and pulse parameter calculation algorithm, which is used to calculate the optimal pulse heating parameters based on the real-time impedance value and generate pulse control signals. The power conversion module adopts a bidirectional DC / DC converter topology to output bidirectional pulse current to the battery with equal positive and negative pulse amplitudes, the same duration, and zero average value, according to the pulse control signal. The safety protection module is used to immediately stop the heating operation in case of abnormal conditions such as overvoltage, undervoltage, overtemperature, excessive temperature difference, or excessively low SOH.