A method and system for dynamic regulation of battery charging power

Abstract

The application relates to the technical field of battery charging control, in particular to a dynamic adjustment method and system for battery charging power, which comprises the following steps: detecting a zero-current relaxation stage starting moment and converting the same into a voltage rebound discrete sequence, performing a first-order difference operation on the sequence to build a first-order derivative sequence and calculating a polarization rebound rate, comparing the rate with a threshold value to generate a current amplitude adjustment instruction, generating a second-order derivative sequence by differentiating the first-order derivative sequence and identifying a zero-crossing point feature, generating a relaxation time adjustment instruction according to whether the zero-crossing point feature exists, combining the current and time instructions to build a pulse charging control parameter set, and adjusting the pulse width modulation signal duty ratio and frequency according to the parameter set. In the application, the battery polarization state is accurately evaluated by monitoring the voltage rebound characteristics in real time, the charging current amplitude and the relaxation time are dynamically optimized, the battery polarization phenomenon is effectively inhibited while the charging efficiency is ensured, and therefore the service life of the battery is significantly prolonged.

Description

Technical Field

[0001] This invention relates to the field of battery charging control technology, and in particular to a method and system for dynamically adjusting battery charging power. Background Technology

[0002] The field of battery charging control technology mainly covers the use of electronic circuit devices to replenish the power of batteries or battery packs, and the management of voltage and current states during the charging process by adjusting circuit parameters. A traditional method for dynamic adjustment of battery charging power involves connecting a current sampling resistor in series and a voltage divider resistor in parallel in the main charging circuit. The power management chip acquires the analog electrical signal at the sampling point through an analog-to-digital converter interface, logically compares this signal with a fixed reference threshold stored in the chip's internal register, and adjusts the duty cycle of the pulse width modulation signal based on the comparison result. This, in turn, controls the switching frequency of the metal-oxide-semiconductor field-effect transistor in the buck or boost converter circuit to output power according to a preset constant current or constant voltage curve.

[0003] Existing technologies rely solely on preset fixed reference thresholds to logically compare sampled voltage and current signals and output power according to a constant curve. This fails to detect changes in the electrochemical polarization state inside the battery in real time and ignores the differences in the battery's actual accepting capacity at different charging stages. As a result, the polarization voltage accumulates severely during long-term charging, which not only affects the accuracy of determining when the battery is fully charged, but also easily leads to lithium plating or gas generation side reactions due to the mismatch between charging parameters and the battery's internal state. This results in low energy conversion efficiency and severely shortens the battery's cycle life. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and to propose a method and system for dynamically adjusting battery charging power.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for dynamically adjusting battery charging power, comprising the following steps: S1: Detect the start time of the zero current relaxation stage, collect the voltage rebound analog signal using a voltage sensor, and convert it into a voltage rebound discrete sequence through an analog-to-digital converter; S2: Perform a first-order difference operation on the voltage rebound discrete sequence to construct a voltage rebound first-order derivative sequence, calculate the arithmetic mean of the voltage rebound first-order derivative sequence to generate a polarization rebound rate, generate a current amplitude reduction command for the polarization rebound rate being greater than a reference polarization rate threshold, and generate a current amplitude increase command for the polarization rebound rate being less than the reference polarization rate threshold. S3: Perform discrete numerical differentiation on the voltage rebound first derivative sequence to generate the voltage rebound second derivative sequence, scan the voltage rebound second derivative sequence to identify zero-crossing features, generate an extended relaxation time instruction for the presence of the zero-crossing feature, and generate a shortened relaxation time instruction for the absence of the zero-crossing feature. S4: Combine the current amplitude reduction command or the current amplitude increase command with the relaxation time extension command or the relaxation time shortening command to construct a pulse charging control parameter set, and adjust the duty cycle and frequency of the pulse width modulation signal according to the pulse charging control parameter set.

[0006] As a further aspect of the present invention, step S1 specifically comprises: S11: Real-time monitoring of the instantaneous current change rate in the charging circuit; if the monitored instantaneous current change rate exceeds a preset current cutoff slope threshold, determine that the current moment is the start moment of the zero current relaxation stage, and generate a synchronous trigger acquisition signal. S12: In response to the synchronous trigger acquisition signal, the voltage sensor is activated to continuously acquire the terminal voltage data at both ends of the battery within a preset relaxation observation window period, and a voltage rebound simulation signal is generated. S13: The analog-to-digital converter samples and quantizes the voltage rebound analog signal at equal intervals at a preset sampling frequency. After filtering out high-frequency noise interference, the quantized voltage values ​​are arranged in time order to generate the voltage rebound discrete sequence.

[0007] As a further aspect of the present invention, step S2 specifically comprises: S21: Obtain the voltage rebound discrete sequence generated in S1, calculate the difference between the voltage values ​​of two adjacent sampling points in the sequence and divide it by the sampling time interval, and construct a voltage rebound first derivative sequence including multiple instantaneous rate of change values ​​in time order. S22: Perform an accumulation operation on all elements in the voltage rebound first derivative sequence and divide by the total number of elements to obtain an average value that reflects the concentration polarization elimination rate inside the battery, and generate the polarization rebound rate. S23: Obtain a preset reference polarization rate threshold, compare the polarization rebound rate with the reference polarization rate threshold, generate a decrease current amplitude instruction to reduce the charging current in the next cycle if the comparison result shows that the former value is larger, and generate an increase current amplitude instruction to increase the charging current in the next cycle if the comparison result shows that the former value is smaller.

[0008] As a further aspect of the present invention, step S3 specifically comprises: S31: Obtain the voltage rebound first derivative sequence generated in S2, perform difference calculation on adjacent derivative values ​​in the sequence to obtain a set of values ​​characterizing voltage change acceleration information, and generate the voltage rebound second derivative sequence. S32: Traverse each data point in the voltage rebound second derivative sequence, detect whether the sign of adjacent data points changes abruptly from positive to negative or from negative to positive, mark the position as a zero-crossing point for the detected sign change, and generate the zero-crossing point feature; S33: Count the number of zero-crossing features identified in the current relaxation cycle. If the number is greater than zero, determine that the electrochemical reaction has not been fully balanced and generate the instruction to extend the relaxation time. If the number is equal to zero, determine that the polarization has been fully eliminated and generate the instruction to shorten the relaxation time.

[0009] As a further aspect of the present invention, step S4 specifically comprises: S41: Parse the instruction to reduce current amplitude or the instruction to increase current amplitude to extract the target current adjustment step size, parse the instruction to extend relaxation time or the instruction to shorten relaxation time to extract the target time adjustment step size, and establish the pulse charging control parameter set including the current setting value and the relaxation time setting value. S42: Calculate the corresponding power switch conduction time ratio according to the current setting value in the pulse charging control parameter set, calculate the total duration of the pulse period and the corresponding switching frequency according to the relaxation time setting value, and generate a pulse width modulation signal adjustment scheme. S43: Write the pulse width modulation signal adjustment scheme into the microcontroller's register, and output the updated drive waveform through the drive circuit to adjust the duty cycle and frequency of the pulse width modulation signal.

[0010] As a further aspect of the present invention, the process of generating the polarization rebound rate in S22 specifically includes: Obtain the voltage rebound first derivative sequence and sequence length value, and calculate the rate index that can characterize the overall rebound trend by using the cumulative summation and division operation based on the polarization elimination dynamic averaging model, thereby generating the polarization rebound rate. The formula for calculating the polarization rebound rate is: ; in, Represents the polarization rebound rate, This represents the total number of sampling points in the voltage rebound discrete sequence. Representing the The voltage quantization value of each sampling point Represents the time interval between adjacent sampling points. This represents the weighted compensation coefficient used to correct sensor sampling errors.

[0011] As a further aspect of the present invention, the zero-crossing feature identification process described in S32 specifically includes: Obtain the voltage rebound second derivative sequence, set a noise tolerance band for determining the stability of the numerical sign, calculate the product of two adjacent second derivative values ​​in the sequence one by one, and determine the sign jump that can reflect the polarization inflection point at the position if the product result is negative and the absolute values ​​of the two second derivative values ​​are both greater than the noise tolerance band, and generate the zero-crossing feature. If no product result satisfying the above conditions is found after traversing the entire sequence, an empty feature signal representing the monotonic change of the voltage curve is output, and the command to shorten the relaxation time is generated.

[0012] As a further aspect of the present invention, the generation process of the pulse width modulation signal adjustment scheme in S42 specifically includes: The target current value and target relaxation time are obtained from the pulse charging control parameter set. Combined with the current battery terminal voltage feedback value and power input voltage value, the target duty cycle of the next charging cycle is calculated using the principle of energy conservation, and the duty cycle control word is generated. Based on the target relaxation time and the preset constant current charging time, the length of the complete pulse cycle is calculated and its reciprocal is taken to determine the switching frequency, and a frequency control word is generated. By combining the duty cycle control word with the frequency control word, a pulse width modulation signal adjustment scheme is constructed that can directly control the switching action of the hardware circuit.

[0013] As a further aspect of the present invention, the process of obtaining the reference polarization rate threshold in S23 specifically includes: The system detects the current state of charge (SOC) of the battery and the ambient temperature, queries a preset multidimensional mapping table of electrochemical impedance characteristics, and matches the reference value of the optimal polarization elimination rate at the current temperature and SOC. The historical data of the actual polarization rebound rate of the previous charging cycle is obtained, and its weighted moving average is calculated as a historical trend correction factor. The optimal polarization elimination rate reference value is dynamically fine-tuned using the factor to generate the benchmark polarization rate threshold.

[0014] A dynamic adjustment system for battery charging power, the system being used to implement the aforementioned dynamic adjustment method for battery charging power, the system comprising: The signal acquisition and processing module is used to detect the start time of the zero current relaxation stage. It uses a voltage sensor to acquire the voltage rebound analog signal and converts it into a voltage rebound discrete sequence through an analog-to-digital converter. The current amplitude adjustment module is used to perform a first-order difference operation on the voltage rebound discrete sequence to construct a voltage rebound first-order derivative sequence, calculate the arithmetic mean of the voltage rebound first-order derivative sequence to generate a polarization rebound rate, generate a current amplitude reduction command when the polarization rebound rate is greater than a reference polarization rate threshold, and generate a current amplitude increase command when the polarization rebound rate is less than the reference polarization rate threshold. The relaxation time control module is used to perform discrete numerical differentiation on the voltage rebound first derivative sequence to generate the voltage rebound second derivative sequence, scan the voltage rebound second derivative sequence to identify zero-crossing features, generate an extended relaxation time instruction for the presence of the zero-crossing feature, and generate a shortened relaxation time instruction for the absence of the zero-crossing feature. The pulse parameter execution module is used to combine the current amplitude reduction instruction or the current amplitude increase instruction with the relaxation time extension instruction or the relaxation time shortening instruction to construct a pulse charging control parameter set, and to adjust the duty cycle and frequency of the pulse width modulation signal according to the pulse charging control parameter set.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by acquiring voltage rebound signals during the zero-current relaxation phase and constructing a discrete sequence, the polarization rebound rate is obtained by calculating the first derivative to dynamically adjust the current amplitude. The zero-crossing feature of the second derivative is combined to identify the internal chemical reaction equilibrium state to optimize the relaxation time. This achieves real-time matching between pulse charging parameters and battery electrochemical characteristics, effectively eliminating the effects of concentration polarization and ohmic polarization. While ensuring that the battery maximizes the acceptance of electrical energy, it avoids side reactions such as lithium plating, significantly improving charging efficiency and safety and extending the overall battery life. Attached Figure Description

[0016] Figure 1 This is a flowchart of the battery charging power dynamic adjustment method of the present invention; Figure 2 This is a flowchart of the voltage rebound sequence acquisition and generation process of the present invention; Figure 3 This is a flowchart illustrating the current amplitude command generation process of the present invention. Figure 4 This is a flowchart of the relaxation time instruction generation process of the present invention; Figure 5 This is a flowchart of the pulse width modulation signal adjustment process of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the software-based technical solution is described in detail below with reference to system architecture diagrams and embodiments. It should be understood that the specific embodiments described herein are only for explaining the technical solutions of this invention and do not constitute a limitation on the scope of protection.

[0018] In the description of this invention, the system architecture relationships or data processing flows indicated by terms such as "layer," "module," "interface," "data flow," "client," and "server" are all defined based on the architecture diagram or flowchart corresponding to the embodiments. This way of describing is only used to clearly illustrate the logical relationships between the elements in the technical solution, and not to limit the physical deployment form. The term "multiple" includes two or more technical units, including but not limited to multiple data nodes, processing threads, service instances, or functional components and other scalable elements. The specific number is determined according to the actual business scenario and needs to be specifically specified.

[0019] Please see Figure 1 and Figure 2 This invention provides a technical solution: a method for dynamically adjusting battery charging power, comprising the following steps: S1: Detect the start time of the zero current relaxation stage, collect the voltage rebound analog signal using a voltage sensor, and convert it into a voltage rebound discrete sequence through an analog-to-digital converter; The specific steps of S1 are as follows: S11: Real-time monitoring of the instantaneous current change rate in the charging circuit. If the monitored instantaneous current change rate exceeds the preset current cutoff slope threshold, the current moment is determined to be the start moment of the zero current relaxation stage, and a synchronous trigger acquisition signal is generated. S12: In response to the synchronous trigger acquisition signal, activate the voltage sensor to continuously acquire the terminal voltage data at both ends of the battery within the preset relaxation observation window period, and generate a voltage rebound simulation signal. S13: The analog voltage rebound signal is sampled and quantized at equal intervals using an analog-to-digital converter at a preset sampling frequency. After filtering out high-frequency noise interference, the quantized voltage values ​​are arranged in time order to generate a discrete voltage rebound sequence.

[0020] During the operation of the battery charging management system, the main control unit establishes connections with the current sensor and voltage sensor through an integrated high-precision analog-to-digital converter interface. When executing step S11, the system first initializes the current monitoring interrupt service routine, setting the current sampling frequency to 200kHz, i.e., the sampling period. The time interval is 5 microseconds. The main control unit reads the analog voltage output of the current sensor in the charging circuit in real time and converts it into the corresponding instantaneous current value. The processor allocates a first-in-first-out (FIFO) buffer queue in its internal registers to store the current values ​​of the two most recent sampling cycles. and The processor calls the Arithmetic Logic Unit (ALU) to perform the subtraction operation. And divide the difference by the time interval. The instantaneous current rate of change was obtained. The system's preset current cutoff slope threshold is... The threshold is set based on the turn-off characteristic curve of the power switch (such as MOSFET), and 50% of the slope of its turn-off edge is taken as the judgment criterion.

[0021] For example, at time The detected current value is 40.0A, at time... The current value was detected to drop rapidly to 38.5A. The processor calculated the rate of change: The processor will calculate the result. With preset threshold Comparison, because Less than (That is, the absolute value of the rate of change exceeds the absolute value of the threshold), the processor determines that the current moment is the start moment of the zero current relaxation phase. Once the determination condition is met, the processor immediately sends a synchronous trigger acquisition signal to the direct memory access (DMA) controller and sets the status flag register.

[0022] In step S12, the voltage acquisition subsystem responds to the synchronous trigger acquisition signal. The main control unit activates the high-impedance differential voltage amplifier circuit connected to the battery terminals, conditioning the battery terminal voltage signal to the input range of the analog-to-digital converter (e.g., 0-3.3V). Simultaneously, the processor starts a dedicated hardware timer for the relaxation phase, setting the counting period to match the preset relaxation observation window. During this window, because the external charging current is cut off, the battery exhibits the physical characteristic of gradually diminishing polarization voltage, and the terminal voltage shows a rebound trend. Driven by the timer, the analog-to-digital converter continuously converts the conditioned voltage rebound analog signal.

[0023] In step S13, the analog-to-digital converter is configured to 12-bit resolution at a sampling frequency of 1 kHz (i.e., time interval). The analog voltage signal is sampled and quantized at equal intervals. The quantization process maps the analog voltage to a digital code from 0 to 4095. The processor reads the quantized raw data and performs digital filtering to remove high-frequency switching noise and electromagnetic interference. This embodiment uses a 5th-order moving average filtering algorithm, which takes the arithmetic mean of the current sampling point and the four sampling points before it as the final voltage value. The filtered voltage values ​​are sequentially stored in designated address blocks in random access memory (RAM) according to time sequence, thereby generating a discrete voltage rebound sequence.

[0024] Table 1 shows the voltage data records of the first few sampling points after the start of the zero-current relaxation phase in an actual data acquisition process.

[0025] Table 1. Sample data of voltage rebound during relaxation phase Refer to Table 1. The data in the table reflects the slight recovery of the battery terminal voltage after the moment of power failure. The filtered voltage values ​​are... This eliminated some of the fluctuations in random noise, providing a stable data foundation for subsequent calculations.

[0026] Please see Figure 1 and Figure 3 S2: Perform a first-order difference operation on the voltage rebound discrete sequence to construct the voltage rebound first-order derivative sequence, calculate the arithmetic mean of the voltage rebound first-order derivative sequence to generate the polarization rebound rate, generate a current amplitude reduction command for polarization rebound rate greater than the reference polarization rate threshold, and generate a current amplitude increase command for polarization rebound rate less than the reference polarization rate threshold. The specific steps of S2 are as follows: S21: Obtain the discrete voltage rebound sequence generated by S1, calculate the difference between the voltage values ​​of two adjacent sampling points in the sequence and divide it by the sampling time interval, and construct a voltage rebound first derivative sequence including multiple instantaneous rate of change values ​​in time order. S22: Perform an accumulation operation on all elements in the voltage rebound first derivative sequence and divide by the total number of elements to obtain the average value reflecting the concentration polarization elimination rate inside the battery, and generate the polarization rebound rate. The generation process of the polarization rebound rate of S22 specifically includes: Obtain the voltage rebound first derivative sequence and sequence length value. Based on the polarization elimination kinetic averaging model, use the summation and division operations to calculate the rate index that can characterize the overall rebound trend and generate the polarization rebound rate. The formula for calculating the polarization rebound rate is: ; in, Represents the polarization rebound rate. The total number of sampling points representing the discrete sequence of voltage rebound. Representing the The voltage quantization value of each sampling point Represents the time interval between adjacent sampling points. This represents the weighted compensation coefficient used to correct sensor sampling errors; S23: Obtain a preset reference polarization rate threshold, compare the polarization rebound rate with the reference polarization rate threshold, generate a current reduction instruction to decrease the charging current in the next cycle if the comparison result shows that the former value is larger, and generate an current increase instruction to increase the charging current in the next cycle if the comparison result shows that the former value is smaller. The process of obtaining the reference polarization rate threshold of S23 specifically includes: The system detects the current state of charge (SOC) of the battery and the ambient temperature, queries a preset multidimensional mapping table of electrochemical impedance characteristics, and matches the reference value of the optimal polarization elimination rate at the current temperature and SOC. Historical data on the actual polarization rebound rate of the previous charging cycle are obtained, and its weighted moving average is calculated as a historical trend correction factor. The factor is used to dynamically fine-tune the reference value of the optimal polarization elimination rate to generate a benchmark polarization rate threshold.

[0027] The processor retrieves the voltage rebound discrete sequence generated in step S1 from RAM and begins executing step S21. The processor initializes the floating-point unit and sets a loop counter to iterate through the voltage rebound discrete sequence. In each loop, the processor reads the voltage values ​​from two adjacent sampling points. and The subtraction operation is performed to calculate the voltage increment, and then the increment is divided by the sampling time interval. (In this embodiment, the value is fixed at 0.001s). The processor stores each calculated instantaneous rate of change value into a floating-point array according to its time index, constructing a sequence of the first derivative of voltage rebound. Taking the 4th and 5th sampling points in Table 1 as examples, the calculation process is as follows: This numerical sequence reflects the rate of voltage recovery at each moment during the relaxation process.

[0028] In step S22, the processor invokes the polarization rebound rate generation algorithm. The core of this algorithm lies in calculating the weighted absolute average of the voltage rebound first derivative sequence to quantitatively characterize the overall elimination dynamics of concentration polarization within the battery.

[0029] The formula for calculating the polarization rebound rate is: ; in, Represents polarization rebound rate, measured in volts per second (V / s). This represents the total number of difference points involved in the calculation within the discrete sequence of voltage rebound. Representing the The filtered voltage values ​​at each sampling point are in volts (V). Representing the The filtered voltage values ​​at each sampling point are in volts (V). This represents the time interval between adjacent sampling points, in seconds (s). This represents the weighted compensation coefficient, used to correct systematic measurement errors caused by temperature sensor response lag or line contact resistance. Its value typically ranges from 0.95 to 1.05.

[0030] The above weighted compensation coefficient The setup process is as follows: Under a constant temperature environment of 25℃, a high-precision benchtop digital multimeter (accuracy 0.001V) and the onboard voltage acquisition circuit are used to synchronously measure the relaxation voltage curve of a standard battery pack. The ratio of the mean of the first derivatives obtained from both is calculated as... The set value. In this embodiment, the measured value of the onboard circuit, obtained through calibration, is slightly higher than the standard value, and the set value is... .

[0031] Assuming that based on Table 1 and subsequent data collection, a total of [data missing] were obtained. The processor sums the absolute values ​​of these 100 samples, taking the first derivative values ​​from each sample point. Assume the summation result is... Substitute the numerical values ​​into the formula to perform the calculation: The calculated result of 34.3 V / s is the current polarization rebound rate.

[0032] In step S23, the processor needs to determine the baseline polarization rate threshold. The processor reads the current battery pack surface temperature as 30°C using a temperature sensor, and estimates the current battery state of charge (SOC) to be 80% using coulomb integration combined with open-circuit voltage correction. The processor then accesses a multidimensional mapping table of electrochemical impedance characteristics stored in non-volatile memory, which records the optimal polarization elimination rate under different temperature and SOC combinations.

[0033] Table 2. Multidimensional mapping table of electrochemical impedance characteristics (fragment) Referring to Table 2, the processor matches the optimal polarization elimination rate reference value of 33.5V / s under the current conditions (30℃, 80% SOC). The processor reads the historical data of the actual polarization rebound rate calculated in the previous charging cycle (set to 34.0V / s). The processor applies a weighted moving average algorithm to calculate the historical trend correction factor, setting the weight of the current reference value to 0.7 and the weight of the historical data to 0.3. The baseline polarization rate threshold is then calculated. .

[0034] The processor will use the currently calculated polarization rebound rate Compared with the reference polarization rate threshold Perform a numerical comparison. The comparison logic is as follows: If... This indicates that the current polarization rebound rate is too fast, and the internal polarization accumulation of the battery is too heavy, requiring a reduction in current. If This indicates that the polarization rebound is slow, the battery still has excess charging capacity, and the current can be increased. In this example, The comparison results show that the former value is larger. Based on this, the processor generates a "reduce current amplitude instruction" and writes the instruction into the charging strategy control register, instructing the charging current to be reduced in the next cycle.

[0035] Please see Figure 1 and Figure 4 S3: Perform discrete numerical differentiation on the first derivative sequence of voltage rebound to generate the second derivative sequence of voltage rebound, scan the second derivative sequence of voltage rebound to identify zero-crossing features, generate an extended relaxation time instruction for those with zero-crossing features, and generate a shortened relaxation time instruction for those without zero-crossing features. The specific steps for S3 are as follows: S31: Obtain the voltage rebound first derivative sequence generated by S2, perform difference calculation on adjacent derivative values ​​in the sequence to obtain a set of values ​​characterizing the voltage change acceleration information, and generate the voltage rebound second derivative sequence. S32: Traverse each data point in the voltage rebound second derivative sequence, detect whether the sign of adjacent data points changes abruptly from positive to negative or from negative to positive, mark the position as a zero-crossing point for the detected sign change, and generate zero-crossing point features; The process of identifying the zero-crossing feature of S32 specifically includes: Obtain the voltage rebound second derivative sequence, set a noise tolerance band for determining the stability of the numerical sign, calculate the product of two adjacent second derivative values ​​in the sequence one by one, and determine the sign jump at the position that can reflect the inflection point of polarization state if the product result is negative and the absolute values ​​of the two second derivative values ​​are both greater than the noise tolerance band, and generate zero-crossing feature. If no product result satisfying the above conditions is found after traversing the entire sequence, an empty feature signal representing the monotonic change of the voltage curve is output, and a command to shorten the relaxation time is generated. S33: Count the number of zero-crossing features identified in the current relaxation cycle. If the number is greater than zero, it is determined that the electrochemical reaction has not been fully balanced and an instruction to extend the relaxation time is generated. If the number is equal to zero, it is determined that the polarization has been fully eliminated and an instruction to shorten the relaxation time is generated.

[0036] The processor calls the voltage rebound first derivative sequence generated in step S2 and executes step S31. The processor performs discrete numerical differentiation on the first derivative sequence, that is, calculates the difference between two adjacent derivative values ​​in the sequence. Assume the values ​​of a segment in the first derivative sequence are as follows: (Unit: V / s). Processor calculates the difference: ; ; These differences constitute the second derivative sequence of voltage rebound, which physically represents the acceleration during the voltage recovery process, with units of... .

[0037] In step S32, the processor scans the voltage rebound second derivative sequence point by point to identify zero-crossing features. The processor first sets a noise margin band parameter, which is used to filter out minute numerical fluctuations caused by sampling quantization errors. In this embodiment, the noise margin band is set to [value missing]. During the scan, the processor sequentially extracts two adjacent data points from the second derivative sequence. and The decision logic contains two sub-conditions: Condition 1: (That is, A and B have opposite signs, and there is a zero-crossing crossing); Condition 2: and (That is, the numerical amplitude on both sides of the crossing point exceeds the noise floor).

[0038] Suppose that a certain point in the sequence is scanned. Calculate the product: (Condition 1 is met); Inspection scope: , (Condition 2 is met). The processor determines that a valid zero-crossing feature has been detected at this position and increments the zero-crossing counter by 1. If the counter value remains 0 after traversing the entire sequence, it indicates that the voltage rebound curve is smooth and monotonous, and no inflection point has appeared. At this time, the processor generates a "shorten relaxation time instruction".

[0039] In step S33, the processor checks the final value of the zero-crossing counter. If the counter value is greater than 0 (e.g., one zero-crossing was detected in this example), it indicates that the electrochemical diffusion process inside the battery has not yet reached equilibrium, ion redistribution is still underway, and the voltage curve fluctuates. Based on this, the processor generates an "extend relaxation time instruction," intended to increase the charging pause time in the next cycle to allow the chemical reaction to reach equilibrium more fully. If the counter value is equal to 0, it indicates that the polarization voltage has decayed exponentially to a stable state, and continuing to wait will reduce charging efficiency. Based on this, the processor generates a "shorten relaxation time instruction."

[0040] Please see Figure 1 and Figure 5 S4: Combine the instruction to decrease or increase the current amplitude with the instruction to extend or shorten the relaxation time to construct a pulse charging control parameter set, and adjust the duty cycle and frequency of the pulse width modulation signal according to the pulse charging control parameter set.

[0041] The specific steps for S4 are as follows: S41: Parse the instruction to decrease the current amplitude or increase the current amplitude to extract the target current adjustment step size, parse the instruction to extend the relaxation time or shorten the relaxation time to extract the target time adjustment step size, and establish a pulse charging control parameter set including the current set value and the relaxation time set value. S42: Calculate the corresponding power switch conduction time ratio based on the current set value in the pulse charging control parameter set, calculate the total duration of the pulse period and the corresponding switching frequency based on the relaxation time set value, and generate a pulse width modulation signal adjustment scheme. The generation process of the pulse width modulation signal adjustment scheme of S42 specifically includes: The target current value and target relaxation time are obtained from the pulse charging control parameter set. Combined with the current battery terminal voltage feedback value and power input voltage value, the target duty cycle of the next charging cycle is calculated using the principle of energy conservation, and the duty cycle control word is generated. Based on the target relaxation time and the preset constant current charging time, the length of the complete pulse cycle is calculated and its reciprocal is taken to determine the switching frequency, and a frequency control word is generated. By combining the duty cycle control word with the frequency control word, a pulse width modulation signal adjustment scheme can be constructed that can directly control the switching action of hardware circuits. S43: Write the pulse width modulation signal adjustment scheme into the microcontroller's register, and output the updated drive waveform through the drive circuit to adjust the duty cycle and frequency of the pulse width modulation signal.

[0042] The processor combines the current adjustment instructions from step S2 and the time adjustment instructions from step S3, and executes step S41.

[0043] The processor reads the charging parameters currently stored in the system status register: Current setting current Current relaxation period Parsing the "reduce current amplitude instruction": The processor retrieves the preset current adjustment step size parameter (e.g., 1.5A). It then calculates the new target current value. Parsing the "Extend Relaxation Time Instruction": The processor extracts the preset time adjustment step size parameter (e.g., 15ms). It then calculates the new target relaxation time. The processor will calculate the result. and The parameters are combined and stored in the pulse charging control parameter set structure.

[0044] In step S42, the processor calculates the adjustment scheme for the pulse width modulation (PWM) signal based on the updated parameter set.

[0045] First, the duty cycle is calculated. The system is based on a Buck converter topology and utilizes the real-time acquired power input voltage. and battery terminal voltage Perform feedforward calculations.

[0046] Assuming the current , Target current The adjustment value output by the PID control algorithm is .

[0047] The formula for calculating duty cycle is: .

[0048] in It is the equivalent internal resistance of the circuit.

[0049] Substitute numerical estimation (ignoring PID fine-tuning terms): .

[0050] The processor converts the duty cycle of 0.7267 into a value in the PWM generator's compare register.

[0051] Assuming the PWM carrier frequency is 20kHz and the counting period is 2500, the value written to the compare register is... .

[0052] Next, the switching frequency (i.e., the frequency of the pulse period) is calculated. The system is preset to determine the duration of the constant current charging phase. The value is fixed at 885ms. Updated total pulse period duration. The corresponding pulse repetition frequency This frequency corresponds to the macroscopic charging / charging off switching control.

[0053] Table 3 shows a comparison of the system's control state before and after parameter adjustment.

[0054] Table 3 Comparison of pulse charging control parameters before and after adjustment See Table 3. The update of this parameter set directly reflects the system's response to the battery polarization state.

[0055] In step S43, the processor writes the calculated PWM adjustment scheme (including the new duty cycle register value of 1817 and the new state machine switching time of 115ms) into the microcontroller's shadow register. At the end of the current pulse cycle, the data in the shadow register is automatically loaded into the active register, and the drive circuit then outputs the updated waveform. The hardware circuit controls the power switch to output 38.5A of current during conduction based on the new duty cycle, and controls the switch to remain off for 115ms in each cycle based on the new timing logic, thus achieving dynamic adjustment of the charging power at the physical level.

[0056] A dynamic adjustment system for battery charging power, the system being used to execute the aforementioned dynamic adjustment method for battery charging power, the system comprising: The signal acquisition and processing module is used to detect the start time of the zero current relaxation stage. It uses a voltage sensor to acquire the voltage rebound analog signal and converts it into a voltage rebound discrete sequence through an analog-to-digital converter. The current amplitude adjustment module is used to perform first-order difference operation on the voltage rebound discrete sequence to construct the voltage rebound first derivative sequence, calculate the arithmetic mean of the voltage rebound first derivative sequence to generate the polarization rebound rate, generate a current amplitude reduction command for the polarization rebound rate being greater than the reference polarization rate threshold, and generate a current amplitude increase command for the polarization rebound rate being less than the reference polarization rate threshold. The relaxation time control module is used to perform discrete numerical differentiation on the first derivative sequence of voltage rebound to generate the second derivative sequence of voltage rebound, scan the second derivative sequence of voltage rebound to identify zero-crossing features, generate an instruction to extend the relaxation time for those with zero-crossing features, and generate an instruction to shorten the relaxation time for those without zero-crossing features. The pulse parameter execution module is used to combine instructions to decrease or increase the current amplitude with instructions to extend or shorten the relaxation time to construct a pulse charging control parameter set, and to adjust the duty cycle and frequency of the pulse width modulation signal according to the pulse charging control parameter set.

[0057] The above embodiments illustrate preferred embodiments of the present invention. Any equivalent adjustments to the technical solution based on software engineering methods are within the scope of protection, including but not limited to: implementing algorithm logic using different programming languages, refactoring functional modules into services, adjusting data interaction protocols, and optimizing resource scheduling strategies. Any implementation scheme derived from reasonable modifications to the data processing flow, service call chain, or system architecture layer without departing from the core technology of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A method for dynamically adjusting battery charging power, characterized in that, Includes the following steps: S1: Detect the start time of the zero current relaxation stage, collect the voltage rebound analog signal using a voltage sensor, and convert it into a voltage rebound discrete sequence through an analog-to-digital converter; S2: Perform a first-order difference operation on the voltage rebound discrete sequence to construct a voltage rebound first-order derivative sequence, calculate the arithmetic mean of the voltage rebound first-order derivative sequence to generate a polarization rebound rate, generate a current amplitude reduction command for the polarization rebound rate being greater than a reference polarization rate threshold, and generate a current amplitude increase command for the polarization rebound rate being less than the reference polarization rate threshold. S3: Perform discrete numerical differentiation on the voltage rebound first derivative sequence to generate the voltage rebound second derivative sequence, scan the voltage rebound second derivative sequence to identify zero-crossing features, generate an extended relaxation time instruction for the presence of the zero-crossing feature, and generate a shortened relaxation time instruction for the absence of the zero-crossing feature. S4: Combine the current amplitude reduction command or the current amplitude increase command with the relaxation time extension command or the relaxation time shortening command to construct a pulse charging control parameter set, and adjust the duty cycle and frequency of the pulse width modulation signal according to the pulse charging control parameter set.

2. The method for dynamically adjusting battery charging power according to claim 1, characterized in that, The specific steps of S1 are as follows: S11: Real-time monitoring of the instantaneous current change rate in the charging circuit; if the monitored instantaneous current change rate exceeds a preset current cutoff slope threshold, determine that the current moment is the start moment of the zero current relaxation stage, and generate a synchronous trigger acquisition signal. S12: In response to the synchronous trigger acquisition signal, the voltage sensor is activated to continuously acquire the terminal voltage data at both ends of the battery within a preset relaxation observation window period, and a voltage rebound simulation signal is generated. S13: The analog-to-digital converter samples and quantizes the voltage rebound analog signal at equal intervals at a preset sampling frequency. After filtering out high-frequency noise interference, the quantized voltage values ​​are arranged in time order to generate the voltage rebound discrete sequence.

3. The method for dynamically adjusting battery charging power according to claim 1, characterized in that, The specific steps of S2 are as follows: S21: Obtain the voltage rebound discrete sequence generated in S1, calculate the difference between the voltage values ​​of two adjacent sampling points in the sequence and divide it by the sampling time interval, and construct a voltage rebound first derivative sequence including multiple instantaneous rate of change values ​​in time order. S22: Perform an accumulation operation on all elements in the voltage rebound first derivative sequence and divide by the total number of elements to obtain an average value that reflects the concentration polarization elimination rate inside the battery, and generate the polarization rebound rate. S23: Obtain a preset reference polarization rate threshold, compare the polarization rebound rate with the reference polarization rate threshold, generate a decrease current amplitude instruction to reduce the charging current in the next cycle if the comparison result shows that the former value is larger, and generate an increase current amplitude instruction to increase the charging current in the next cycle if the comparison result shows that the former value is smaller.

4. The method for dynamically adjusting battery charging power according to claim 1, characterized in that, The specific steps of S3 are as follows: S31: Obtain the voltage rebound first derivative sequence generated in S2, perform difference calculation on adjacent derivative values ​​in the sequence to obtain a set of values ​​characterizing voltage change acceleration information, and generate the voltage rebound second derivative sequence. S32: Traverse each data point in the voltage rebound second derivative sequence, detect whether the sign of adjacent data points changes abruptly from positive to negative or from negative to positive, mark the position as a zero-crossing point for the detected sign change, and generate the zero-crossing point feature; S33: Count the number of zero-crossing features identified in the current relaxation cycle. If the number is greater than zero, determine that the electrochemical reaction has not been fully balanced and generate the instruction to extend the relaxation time. If the number is equal to zero, determine that the polarization has been fully eliminated and generate the instruction to shorten the relaxation time.

5. The method for dynamically adjusting battery charging power according to claim 1, characterized in that, The specific steps of S4 are as follows: S41: Parse the instruction to reduce current amplitude or the instruction to increase current amplitude to extract the target current adjustment step size, parse the instruction to extend relaxation time or the instruction to shorten relaxation time to extract the target time adjustment step size, and establish the pulse charging control parameter set including the current setting value and the relaxation time setting value. S42: Calculate the corresponding power switch conduction time ratio according to the current setting value in the pulse charging control parameter set, calculate the total duration of the pulse period and the corresponding switching frequency according to the relaxation time setting value, and generate a pulse width modulation signal adjustment scheme. S43: Write the pulse width modulation signal adjustment scheme into the microcontroller's register, and output the updated drive waveform through the drive circuit to adjust the duty cycle and frequency of the pulse width modulation signal.

6. The method for dynamically adjusting battery charging power according to claim 3, characterized in that, The process of generating the polarization rebound rate described in S22 specifically includes: Obtain the voltage rebound first derivative sequence and sequence length value, and calculate the rate index that can characterize the overall rebound trend by using the cumulative summation and division operation based on the polarization elimination dynamic averaging model, thereby generating the polarization rebound rate. The formula for calculating the polarization rebound rate is: ； in, Represents the polarization rebound rate, This represents the total number of sampling points in the voltage rebound discrete sequence. Representing the The voltage quantization value of each sampling point Represents the time interval between adjacent sampling points. This represents the weighted compensation coefficient used to correct sensor sampling errors.

7. The method for dynamically adjusting battery charging power according to claim 4, characterized in that, The zero-crossing feature identification process described in S32 specifically includes: Obtain the voltage rebound second derivative sequence, set a noise tolerance band for determining the stability of the numerical sign, calculate the product of two adjacent second derivative values ​​in the sequence one by one, and determine the sign jump that can reflect the polarization inflection point at the position if the product result is negative and the absolute values ​​of the two second derivative values ​​are both greater than the noise tolerance band, and generate the zero-crossing feature. If no product result satisfying the above conditions is found after traversing the entire sequence, an empty feature signal representing the monotonic change of the voltage curve is output, and the command to shorten the relaxation time is generated.

8. The method for dynamically adjusting battery charging power according to claim 5, characterized in that, The generation process of the pulse width modulation signal adjustment scheme described in S42 specifically includes: The target current value and target relaxation time are obtained from the pulse charging control parameter set. Combined with the current battery terminal voltage feedback value and power input voltage value, the target duty cycle of the next charging cycle is calculated using the principle of energy conservation, and the duty cycle control word is generated. Based on the target relaxation time and the preset constant current charging time, the length of the complete pulse cycle is calculated and its reciprocal is taken to determine the switching frequency, and a frequency control word is generated. By combining the duty cycle control word with the frequency control word, a pulse width modulation signal adjustment scheme is constructed that can directly control the switching action of the hardware circuit.

9. The method for dynamically adjusting battery charging power according to claim 3, characterized in that, The process of obtaining the reference polarization rate threshold mentioned in S23 specifically includes: The system detects the current state of charge (SOC) of the battery and the ambient temperature, queries a preset multidimensional mapping table of electrochemical impedance characteristics, and matches the reference value of the optimal polarization elimination rate at the current temperature and SOC. The historical data of the actual polarization rebound rate of the previous charging cycle is obtained, and its weighted moving average is calculated as a historical trend correction factor. The optimal polarization elimination rate reference value is dynamically fine-tuned using the factor to generate the benchmark polarization rate threshold.

10. A dynamic adjustment system for battery charging power, characterized in that, The system is used to implement the dynamic adjustment method for battery charging power according to any one of claims 1-9, the system comprising: The signal acquisition and processing module is used to detect the start time of the zero current relaxation stage. It uses a voltage sensor to acquire the voltage rebound analog signal and converts it into a voltage rebound discrete sequence through an analog-to-digital converter. The current amplitude adjustment module is used to perform a first-order difference operation on the voltage rebound discrete sequence to construct a voltage rebound first-order derivative sequence, calculate the arithmetic mean of the voltage rebound first-order derivative sequence to generate a polarization rebound rate, generate a current amplitude reduction command when the polarization rebound rate is greater than a reference polarization rate threshold, and generate a current amplitude increase command when the polarization rebound rate is less than the reference polarization rate threshold. The relaxation time control module is used to perform discrete numerical differentiation on the voltage rebound first derivative sequence to generate the voltage rebound second derivative sequence, scan the voltage rebound second derivative sequence to identify zero-crossing features, generate an extended relaxation time instruction for the presence of the zero-crossing feature, and generate a shortened relaxation time instruction for the absence of the zero-crossing feature. The pulse parameter execution module is used to combine the current amplitude reduction instruction or the current amplitude increase instruction with the relaxation time extension instruction or the relaxation time shortening instruction to construct a pulse charging control parameter set, and to adjust the duty cycle and frequency of the pulse width modulation signal according to the pulse charging control parameter set.

Images