A DSP-based multi-segment intelligent charging strategy switching system

Abstract

This invention discloses a DSP-based multi-segment intelligent charging strategy switching system, relating to the field of battery charging control technology. It addresses the problem of adaptively controlling current switching during multi-segment constant current charging to prevent voltage over-limit interruptions while minimizing switching time to improve charging efficiency. The system includes: acquiring the battery's reference impedance, sampled current, and sampled voltage during the current switching cycle; determining the linear voltage change of the battery during the current control cycle based on the change in sampled current and the reference impedance, and determining the polarization voltage component of the battery during the current control cycle based on the change in sampled current; determining a virtual impedance index based on the polarization voltage component, sampled voltage, and charging cutoff voltage threshold; and determining the allowable charging current adjustment step size during the current control cycle based on a preset voltage fluctuation budget value and the virtual impedance index, and updating the target charging current command accordingly.

Description

Technical Field

[0001] This invention relates to the field of battery charging control technology, and more specifically to a multi-segment intelligent charging strategy switching system based on DSP. Background Technology

[0002] In fields such as new energy vehicles and energy storage systems, the fast charging capability and operational safety of power batteries are core performance indicators. Multi-stage constant current charging, as a common strategy, aims to balance charging speed and battery safety by gradually reducing the current during charging. Existing technologies typically rely on fixed-slope control based on voltage feedback or threshold comparison methods to achieve current switching. However, these methods have limitations in handling the complex dynamic response of battery terminal voltage, making it difficult to achieve a good balance between preventing unexpected interruptions in the charging process and maximizing the use of the fast charging window, leading to a conflict between charging reliability and overall charging efficiency. Summary of the Invention

[0003] To address the technical challenge of adaptively controlling current switching to prevent voltage over-limit interruptions and minimize switching time to improve charging efficiency during multi-segment constant current charging, this invention aims to provide a DSP-based multi-segment intelligent charging strategy switching system. The specific technical solution adopted is as follows:

[0004] In a first aspect, the present invention provides a DSP-based multi-segment intelligent charging strategy switching system, comprising: a data acquisition module, a voltage component calculation module, an impedance evaluation module, an adjustment step size determination module, and a strategy update module; the data acquisition module is used to acquire the reference impedance of the battery in the current switching cycle, and the sampled current and sampled voltage of the battery in the current control cycle; the voltage component calculation module is used to determine the linear voltage change of the battery in the current control cycle based on the change in sampled current and the reference impedance, and to determine the polarization voltage component of the battery in the current control cycle based on the linear voltage change and the change in sampled current; wherein, the polarization voltage component is used to characterize the difference between the change in sampled voltage and the linear voltage change; the impedance evaluation module is used to determine a virtual impedance index based on the polarization voltage component, the sampled voltage, and the charging cutoff voltage threshold; wherein, the virtual impedance index is used to characterize the constraint degree of the current charging current adjustment; the adjustment step size determination module is used to determine the allowable charging current adjustment step size in the current control cycle based on a preset voltage fluctuation budget value and the virtual impedance index; the strategy update module is used to update the target charging current command based on the charging current adjustment step size.

[0005] Secondly, this invention provides a DSP-based multi-segment intelligent charging strategy switching method, comprising: acquiring the reference impedance of the battery in the current switching cycle, and the sampled current and sampled voltage of the battery in the current control cycle; determining the linear voltage change of the battery in the current control cycle based on the change in the sampled current and the reference impedance, and determining the polarization voltage component of the battery in the current control cycle based on the linear voltage change and the change in the sampled current; wherein the polarization voltage component is used to characterize the difference between the change in the sampled voltage and the linear voltage change; determining a virtual impedance index based on the polarization voltage component, the sampled voltage, and the charging cutoff voltage threshold; wherein the virtual impedance index is used to characterize the constraint degree of the current charging current adjustment; determining the allowable charging current adjustment step size in the current control cycle based on a preset voltage fluctuation budget value and the virtual impedance index; and updating the target charging current command based on the charging current adjustment step size.

[0006] Thirdly, the present invention provides an electronic device, comprising: a processor and a memory; wherein the memory is used to store one or more programs, the one or more programs including computer-executable instructions, and when the electronic device is running, the processor executes the computer-executable instructions stored in the memory to cause the electronic device to perform the DSP-based multi-segment intelligent charging strategy switching method as described in the first aspect and any possible implementation thereof.

[0007] This invention offers the following advantages: By identifying the battery's internal ohmic resistance online as a benchmark, the terminal voltage change is decoupled into a linear and a polarization component. A dynamic virtual impedance index is constructed using the polarization voltage component and the voltage safety boundary. Finally, the current adjustment step size is adaptively determined based on this index and the system voltage fluctuation budget. This method can detect and quantify the voltage rebound risk caused by electrochemical polarization in real time during the final stage of battery charging or high-current switching, dynamically constraining the rate of current decrease. This allows for faster current switching while preventing charging interruption due to battery voltage exceeding limits, effectively improving the reliability, safety, and overall charging efficiency of the multi-stage charging strategy. Attached Figure Description

[0008] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 This is a schematic diagram of the architecture of a DSP-based multi-segment intelligent charging strategy switching system provided in one embodiment of the present invention;

[0010] Figure 2 This is a flowchart illustrating a DSP-based multi-segment intelligent charging strategy switching method according to an embodiment of the present invention. Detailed Implementation

[0011] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the specific implementation methods, structures, features, and effects of the present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0012] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0013] In all division and logarithmic operations involved in this invention, a smoothing mechanism is employed to prevent computer program crashes or invalid values ​​from being generated due to a zero denominator or zero input. Specifically, a correction factor ε, which is a very small positive number, is superimposed on the denominator term of the division operation or the argument term of the logarithmic function, for example, a value of 10 to the power of negative 5, thereby ensuring the robustness and feasibility of the algorithm under extreme conditions.

[0014] Unless otherwise specified, the normalization function Norm() mentioned in this invention uses maximum and minimum value normalization. The maximum and minimum values ​​are preset empirical extreme values ​​derived from a large amount of historical experimental data. If the calculation result exceeds the [0, 1] interval, it is restricted to the [0, 1] range by a truncation function (i.e., if the result is less than 0, it is taken as 0; if it is greater than 1, it is taken as 1) to eliminate the influence of outliers on the evaluation index.

[0015] The following description, in conjunction with the accompanying drawings, details a specific solution for a DSP-based multi-segment intelligent charging strategy switching system provided by the present invention.

[0016] For example, such as Figure 1 The diagram shown is an architectural schematic of a DSP-based multi-segment intelligent charging strategy switching system (hereinafter referred to as the strategy switching system) according to an embodiment of the present invention. The strategy switching system 10 includes: a data acquisition module 11, a voltage component calculation module 12, an impedance evaluation module 13, an adjustment step size determination module 14, and a strategy update module 15. The modules are described below in sequence:

[0017] (1) Data acquisition module 11.

[0018] The data acquisition module 11 is responsible for collecting real-time electrical signals of the battery system and obtaining, through specific processing, a reference impedance characterizing the internal ohmic properties of the battery and sampled values ​​for control calculations, providing an accurate, multi-rate data foundation for the entire adaptive control process.

[0019] Optionally, the data acquisition module 11 is used to acquire the reference impedance of the battery in the current switching cycle, as well as the sampled current and sampled voltage of the battery in the current control cycle.

[0020] Specifically, the data acquisition module 11 first performs high-frequency sampling to obtain the reference impedance: at the peak and trough of the pulse width modulation (PWM) switching signal, it triggers the analog-to-digital converter to acquire the battery terminal voltage and loop current, respectively, to obtain the peak sampling voltage, peak sampling current, trough sampling voltage, and trough sampling current. Then, the data acquisition module 11 calculates the voltage ripple amplitude based on the difference between the peak and trough sampling voltages, and calculates the current ripple amplitude based on the difference between the peak and trough sampling currents. Furthermore, when the current ripple amplitude is greater than or equal to a preset ripple threshold, the data acquisition module 11 calculates the ratio of the voltage ripple amplitude to the current ripple amplitude to obtain the instantaneous impedance, and performs low-pass filtering on this instantaneous impedance, finally outputting a smooth reference impedance.

[0021] Simultaneously, the data acquisition module 11 samples the battery terminal voltage and loop current multiple times within each low-frequency control cycle, and averages the sampled voltage and current values ​​to obtain the average sampled voltage and average sampled current used to characterize the current state. The data acquisition module 11 synchronously outputs the calculated reference impedance, sampled current, and sampled voltage to the subsequent voltage component calculation module 12 and impedance evaluation module 13.

[0022] (2) Voltage component calculation module 12.

[0023] The voltage component calculation module 12 is responsible for receiving the reference impedance and sampling current from the data acquisition module 11. Through decoupling analysis, it separates the ohmic voltage drop part and the electrochemical polarization part in the battery terminal voltage response, thereby extracting the key polarization state information.

[0024] Optionally, the voltage component calculation module 12 is used to determine the linear voltage change of the battery in the current control cycle based on the change in the sampled current and the reference impedance, and to determine the polarization voltage component of the battery in the current control cycle based on the linear voltage change and the change in the sampled current. The polarization voltage component is used to characterize the difference between the change in the sampled voltage and the linear voltage change.

[0025] Specifically, the voltage component calculation module 12 first determines the change in the sampling current based on the difference between the current sampling current and the historical sampling current of the previous cycle. Then, the voltage component calculation module 12 multiplies the change in the sampling current by the reference impedance to obtain the linear voltage change caused by the change in pure internal resistance.

[0026] Next, the voltage component calculation module 12 calculates the difference between the current sampled voltage and the historical sampled voltage to obtain the change in the sampled voltage. The voltage component calculation module 12 then calculates the absolute value of the difference between the change in the sampled voltage and the linear voltage change. Finally, the voltage component calculation module 12 determines whether the absolute value of this difference is less than a preset polarization noise threshold; if yes, the polarization voltage component is set to zero; if no, the absolute value of the difference is determined as the polarization voltage component.

[0027] The voltage component calculation module 12 outputs the calculated polarization voltage component to the impedance evaluation module 13.

[0028] (3) Impedance assessment module 13.

[0029] Impedance assessment module 13 is responsible for integrating the real-time voltage state of the battery with the extracted polarization information to construct a dynamic virtual impedance index. This index quantifies the comprehensive constraints faced when adjusting the current at the current moment.

[0030] Optionally, the impedance evaluation module 13 is used to determine a virtual impedance index based on the polarization voltage component, the sampling voltage, and the charging cutoff voltage threshold. The virtual impedance index characterizes the degree of constraint on the current charging current regulation.

[0031] Specifically, the impedance assessment module 13 first calculates the difference between the charging cutoff voltage threshold and the sampling voltage to obtain the remaining voltage space. Then, the impedance assessment module 13 determines whether the remaining voltage space is less than a preset protection threshold; if so, it sets the value of the remaining voltage space to the protection threshold. Furthermore, the impedance assessment module 13 determines the polarization weighting coefficient based on the ratio of the polarization voltage component to the charging cutoff voltage threshold. Simultaneously, the impedance assessment module 13 determines the safety adjustment term based on the ratio of the preset safety gain reference voltage to the remaining voltage space.

[0032] Finally, the impedance assessment module 13 calculates the virtual impedance index based on the reference impedance, polarization weighting coefficient, and safety adjustment term. The value of this index is positively correlated with the polarization voltage component and negatively correlated with the remaining voltage space. The impedance assessment module 13 outputs the virtual impedance index to the adjustment step size determination module 14.

[0033] (4) Adjust step size determination module 14.

[0034] The step size determination module 14 is responsible for calculating a safe and efficient charging current adjustment amount within the current control cycle based on the system's allowable voltage fluctuation budget and the real-time evaluated virtual impedance.

[0035] Optionally, the step size determination module 14 is used to determine the allowable charging current adjustment step size under the current control cycle based on the preset voltage fluctuation budget value and virtual impedance index.

[0036] Specifically, the step size determination module 14 internally stores a preset voltage fluctuation budget value, which defines the range of voltage fluctuations the system can tolerate in response to dynamic changes. The step size determination module 14 uses the received virtual impedance index as a measure of the "resistance" for the current current regulation. Then, by dividing the voltage fluctuation budget value by the virtual impedance index, the step size determination module 14 calculates the allowable charging current adjustment step size for the current control cycle. This step size is output to the strategy update module 15 as the direct basis for instruction updates.

[0037] (5) Strategy update module 15.

[0038] The strategy update module 15, as the final decision-making and output unit of the system, is responsible for generating and outputting new target charging current commands based on the adaptively calculated adjustment step size or safety control conditions, thereby realizing the control of the power stage circuit.

[0039] Optionally, the strategy update module 15 is used to adjust the step size according to the charging current and update the target charging current command.

[0040] Specifically, the strategy update module 15 first determines whether the sampled voltage is greater than or equal to the charging cutoff voltage threshold, or whether the remaining voltage space is less than a preset protection threshold. If the determination is yes, the strategy update module 15 executes safety control logic, directly updating the target charging current command to the preset target stage charging current value. If the determination is no, the strategy update module 15 executes normal adaptive update logic: first, it obtains the charging current command from the previous control cycle; then, based on the charging current command and charging current adjustment step size from the previous control cycle, it determines the candidate charging current command for the current control cycle; finally, it compares the candidate charging current command with the preset target stage charging current value, and determines the larger of the two as the updated target charging current command. The strategy update module 15 outputs the finally determined target charging current command to an external current loop controller to drive the power switching devices.

[0041] Optionally, the strategy switching system 10 also includes an initialization module 16 (not shown in the figure). The initialization module 16 is used to perform initialization operations during the first control cycle of charging control at system startup. Specifically, the initialization operations include setting the historical sampled voltage value to the current measured sampled voltage value and setting the historical sampled current value to the current measured sampled current value to ensure that the difference calculation in the first control cycle has a correct initial reference.

[0042] The above describes the policy switching system 10 and its included modules.

[0043] For example, such as Figure 2 The diagram shown is a flowchart illustrating a DSP-based multi-segment intelligent charging strategy switching method according to an embodiment of the present invention, comprising the following steps:

[0044] S201. Obtain the reference impedance of the battery in the current switching cycle, as well as the sampled current and sampled voltage of the battery in the current control cycle.

[0045] In this embodiment of the invention, system operation involves two key and distinct time bases: the current switching cycle and the current control cycle, which will be described below:

[0046] Switching cycle: Specifically refers to a single switching cycle of a pulse-width modulation (PWM) signal in a power stage circuit. Its duration (e.g., 20 microseconds, corresponding to a switching frequency of 50kHz) is determined by the hardware circuit design. This scheme performs synchronous sampling at specific moments (peaks and troughs) within this cycle to extract high-frequency ripple signals for calculating the reference impedance. This cycle serves as the time base for high-frequency signal processing; the current switching cycle mentioned below refers to the switching cycle analyzed in real time.

[0047] Control cycle: Specifically refers to the main loop cycle of the digital controller (such as a DSP) executing the adaptive control algorithm described in this invention, the duration of which (e.g., 1 millisecond) is set by software. Within this cycle, the system completes core logic such as state observation, evaluation calculation, and instruction update. This cycle serves as the time base for low-frequency control decisions; the current control cycle mentioned below refers to the control cycle for real-time analysis.

[0048] For example, this step can be performed by the data acquisition module 11 in the policy switching system 10 described above, and specifically includes the following steps:

[0049] (1) At the peak and trough of the pulse width modulation (PWM) switching signal, the battery terminal voltage and loop current are collected respectively to obtain the peak sampling voltage, peak sampling current, trough sampling voltage and trough sampling current.

[0050] Specifically, at the peak of the power switching device's conduction, the data acquisition module 11 triggers the analog-to-digital converter to synchronously acquire the terminal voltage and loop current of the primary battery, recording them as peak sampling voltage and peak sampling current, respectively. At the trough of the power switching device's turn-off, acquisition is triggered again to obtain trough sampling voltage and trough sampling current. These two sets of instantaneous values ​​together form the basis for calculating high-frequency impedance ripple.

[0051] (2) Determine the voltage ripple amplitude based on the difference between the peak sampling voltage and the trough sampling voltage.

[0052] Specifically, the data acquisition module 11 calculates the difference between the peak sampling voltage and the trough sampling voltage, and takes the absolute value of the difference to obtain the fluctuation amplitude of the battery terminal voltage within one PWM switching cycle, i.e., the voltage ripple amplitude.

[0053] (3) Determine the current ripple amplitude based on the difference between the peak sampling current and the trough sampling current.

[0054] Specifically, the data acquisition module 11 calculates the difference between the peak sampling current and the trough sampling current, and takes the absolute value of the difference to obtain the fluctuation amplitude of the charging circuit current within the same PWM switching cycle, i.e., the current ripple amplitude.

[0055] (4) Determine the reference impedance based on the voltage ripple amplitude and the current ripple amplitude.

[0056] Specifically, the data acquisition module 11 first determines whether the calculated current ripple amplitude is greater than or equal to a preset ripple threshold to ensure signal validity. When the condition is met, the data acquisition module 11 divides the voltage ripple amplitude by the current ripple amplitude to calculate a ratio reflecting the instantaneous internal resistance, i.e., the instantaneous impedance. Then, the data acquisition module 11 performs low-pass filtering on this instantaneous impedance to smooth fluctuations caused by switching noise, ultimately outputting a reference impedance that stably characterizes the battery's ohmic internal resistance.

[0057] (5) Perform low-pass filtering on the instantaneous impedance to obtain the reference impedance.

[0058] Specifically, after calculating the instantaneous impedance, the data acquisition module 11 does not directly use it as the reference impedance. To suppress the influence of switching noise and accidental interference on the impedance measurement and to obtain a parameter that smoothly and stably reflects the changes in the battery's internal resistance, the data acquisition module 11 performs a first-order low-pass digital filter on the instantaneous impedance. This filtering process is implemented using the following recursive formula: Reference Impedance (Current) = (1 - Filter Coefficient) × Reference Impedance (Previous Cycle) + Filter Coefficient × Instantaneous Impedance. Here, the filter coefficient is a decimal between 0 and 1, and its value determines the filter's time constant and cutoff frequency. By appropriately setting the filter coefficient (for example, corresponding to a cutoff frequency of 10Hz), high-frequency noise much higher than the frequency of battery internal resistance changes can be effectively filtered out, while simultaneously tracking the slow changes in battery internal resistance caused by temperature or state of charge, ultimately outputting a quasi-static, reliable reference impedance for subsequent modules.

[0059] (6) In each control cycle, the battery terminal voltage and loop current are sampled and averaged multiple times to obtain the sampled voltage and sampled current.

[0060] Specifically, the high-frequency sampling and reference impedance calculation described in steps (1) to (4) above are performed based on the PWM switching cycle (e.g., 20 microseconds). Simultaneously, to perform state calculations for this control cycle (e.g., 1 millisecond), the data acquisition module 11 also needs to acquire sampled voltage and sampled current to characterize the average electrical state within a control cycle. Therefore, in each control cycle, the data acquisition module 11 continuously and uniformly samples the battery terminal voltage and loop current signals multiple times at a rate much higher than the control frequency (e.g., 100 samples within 1 millisecond). Then, the data acquisition module 11 performs an arithmetic average of all the original voltage sample values ​​acquired within this control cycle to obtain the sampled voltage for that cycle; similarly, it performs an arithmetic average of all the original current sample values ​​to obtain the sampled current for that cycle. This averaging process effectively smooths the switching ripple and suppresses random interference, obtaining voltage and current values ​​that better represent the battery's steady-state operating point within the control cycle, providing accurate low-frequency state quantities for subsequent voltage change calculations, polarization state decoupling, etc.

[0061] Therefore, the data acquisition module 11 synchronously collects electrical signals at the peaks and troughs of the switching cycle, extracts and calculates the ripple amplitude of voltage and current, and then identifies the reference impedance of the battery online. At the same time, by averaging multiple samples within the control cycle, a stable sampling current and sampling voltage are obtained, providing a precise and multi-rate data foundation for subsequent state decoupling and evaluation.

[0062] S202. Based on the change in sampling current and the reference impedance, determine the linear voltage change of the battery in the current control cycle, and based on the linear voltage change and the change in sampling current, determine the polarization voltage component of the battery in the current control cycle. The polarization voltage component characterizes the difference between the change in sampling voltage and the linear voltage change.

[0063] For example, this step can be performed by the voltage component calculation module 12 in the strategy switching system 10 described above. Specifically, the voltage component calculation module 12 first calculates the change in the sampling current based on the sampling current of the current control cycle and the historical sampling current of the previous control cycle. Then, the voltage component calculation module 12 multiplies the change in the sampling current by the reference impedance to obtain the linear voltage change caused by the pure Ohmic effect. Furthermore, the voltage component calculation module 12 compares the difference between the actual change in the sampling voltage and the calculated linear voltage change, and makes a judgment based on a preset noise threshold, ultimately determining the polarization voltage component characterizing the electrochemical polarization state. It should be noted that the specific process of the aforementioned sub-steps is described in S301-S303 below, and will not be repeated here.

[0064] In another possible implementation, when determining the linear voltage change of the battery in the current control cycle, the voltage component calculation module 12 can also use the sampled current sequence of multiple recent control cycles to fit the change curve, predict the current change in the current cycle, and then multiply it with the reference impedance to obtain the linear voltage change, so as to cope with the scenario of drastic current fluctuations and improve the robustness of the linear part estimation.

[0065] In another possible implementation, when determining the polarization voltage component of the battery in the current control cycle, the voltage component calculation module 12 can also dynamically adjust the preset polarization noise threshold based on the real-time temperature of the battery when comparing the difference between the sampled voltage change and the linear voltage change, thereby more accurately distinguishing the real polarization voltage from the measurement noise over a wide temperature range.

[0066] Thus, the voltage component calculation module 12 decouples the total change in the sampled voltage into a linear part and a nonlinear (polarization) part, accurately separating the polarization voltage component dominated by the dynamics of the internal electrochemical reaction of the battery, providing a key intermediate state quantity for subsequent quantification of current regulation constraints.

[0067] S203. Determine the virtual impedance index based on the polarization voltage component, sampling voltage, and charging cutoff voltage threshold. The virtual impedance index characterizes the degree of constraint on the current charging current regulation.

[0068] For example, this step can be performed by the impedance evaluation module 13 in the strategy switching system 10 described above. Specifically, the impedance evaluation module 13 first calculates the difference between the charging cutoff voltage threshold and the current sampled voltage to obtain the remaining voltage space, and then performs safety limiting processing on it. Next, based on the squeezing effect of the polarization voltage component on the remaining voltage space, the impedance evaluation module 13 calculates a polarization weighting coefficient; simultaneously, based on the relative relationship between the system safety gain requirement and the remaining voltage space, it calculates a safety adjustment term. Finally, the impedance evaluation module 13 integrates the reference impedance, the polarization weighting coefficient, and the safety adjustment term to generate a virtual impedance index through fusion calculation. The larger the value of this index, the stronger the overall "resistance" or constraint faced by the current reduction in charging current. It should be noted that the specific process of the aforementioned sub-steps is described in S401-S403 below, and will not be repeated here.

[0069] In another possible implementation, when determining the virtual impedance index, the impedance evaluation module 13 can also quantize the polarization voltage component and the remaining voltage space into different fuzzy levels (such as "large", "medium" and "small"). By querying a preset fuzzy rule table that reflects expert experience, the corresponding virtual impedance index level or value can be directly output. This is suitable for application scenarios that are sensitive to computing resources or where model parameters are uncertain.

[0070] Therefore, the impedance assessment module 13 creatively combines the polarization voltage component, which reflects the dynamic polarization state of the battery, with the residual voltage space, which reflects the static voltage boundary, to construct a dynamic virtual impedance index. This index is not the actual physical impedance, but a core control parameter used to quantify the ease or difficulty of current regulation at the current moment.

[0071] S204. Based on the preset voltage fluctuation budget value and virtual impedance index, determine the allowable charging current adjustment step size under the current control cycle.

[0072] For example, this step can be performed by the adjustment step size determination module 14 in the policy switching system 10 described above.

[0073] Specifically, the step size determination module 14 stores a preset voltage fluctuation budget value, which defines the maximum safe range of battery terminal voltage fluctuation allowed to maintain system stability within a single control cycle.

[0074] The step size adjustment module 14 uses the received virtual impedance index as the denominator and the preset voltage fluctuation budget value as the numerator, performing a division operation. The calculation formula is intuitively expressed as: Charging current adjustment step size = Voltage fluctuation budget value / Virtual impedance index. The core idea of ​​this calculation is to allocate the system's tolerable voltage fluctuation "budget" according to the magnitude of the current adjustment "resistance" (virtual impedance). When the resistance is high, the allowable current adjustment step size is small to prevent voltage overshoot; when the resistance is low, the allowable adjustment step size can be increased accordingly to speed up the switching speed. The calculated charging current adjustment step size serves as the maximum allowable change in the current command for the current cycle.

[0075] Thus, the step size determination module 14 transforms the abstract constraint index output by the evaluation module into a specific current adjustment quantity that can be directly used for control execution through a simple and effective mapping relationship, thereby realizing the connection from state evaluation to control quantity generation.

[0076] S205. Adjust the step size according to the charging current and update the target charging current command.

[0077] For example, this step can be executed by the strategy update module 15 in the strategy switching system 10 described above. Specifically, the strategy update module 15 first performs a safety condition judgment. If the sampled voltage has reached the cutoff threshold or the remaining voltage space is insufficient, it skips the adaptive adjustment logic and directly executes the safety control operation, forcibly updating the target charging current command to the target value of the next stage. If the safety control conditions are not met, the strategy update module 15 executes the normal command update process: it calculates a candidate command value based on the command value of the previous cycle and the adjustment step size calculated in the current cycle, and compares the candidate value with the preset final target stage current value, taking the larger one as the new target charging current command output. It should be noted that the specific process of the aforementioned sub-steps is described in S501-S503 below, and will not be repeated here.

[0078] In another possible implementation, when updating the target charging current command, the strategy update module 15 may not directly use the calculated value when updating the command according to the adjustment step size, but instead perform a weighted average with the command of the previous cycle, so that the output target charging current command changes more smoothly, which helps to further suppress the impact of sudden changes in current command on the power system.

[0079] Therefore, the strategy update module 15, as the final decision-making and output unit, integrates safety control logic and adaptive adjustment logic to generate and output the target charging current command for each control cycle, thereby realizing real-time, smooth and safe strategy switching control for the multi-segment constant current charging process.

[0080] Based on the above technical solution, this invention uses online identification of the battery's ohmic internal resistance as a benchmark to decouple the terminal voltage change into a linear and a polarization component. It then constructs a dynamic virtual impedance index using the polarization voltage component and the voltage safety boundary. Finally, it adaptively determines the current adjustment step size based on this index and the system voltage fluctuation budget. This method can detect and quantify the voltage rebound risk caused by electrochemical polarization in real time during the final stage of battery charging or when switching to high current, dynamically constraining the rate of current decrease. This allows for faster current switching as much as possible while preventing charging interruption due to battery voltage exceeding limits, effectively improving the reliability, safety, and overall charging efficiency of the multi-stage charging strategy.

[0081] For example, in another DSP-based multi-segment intelligent charging strategy switching method provided in one embodiment of the present invention, the linear voltage change of the battery in the current control cycle is determined according to the change in the sampled current and the reference impedance, specifically including the following steps:

[0082] S301. If the absolute value of the difference between the change in the sampled voltage and the change in the linear voltage is less than the preset polarization noise threshold, the polarization voltage component is determined to be zero.

[0083] In this step, the voltage component calculation module 12 first receives the reference impedance from the data acquisition module 11 and the sampling current of the current control cycle and the previous control cycle. , Calculate the change in the sampled current. .in, This represents the sampled current for the current control cycle. This represents the historical sampled current from the previous control cycle. Used to characterize the change in charging current command within a control cycle.

[0084] Then, the voltage component calculation module 12 calculates the linear voltage change according to Ohm's law. .in, This represents the reference impedance obtained from data acquisition module 11. It can be understood that this calculation reflects the current variation assuming the battery is a purely resistive load. The resulting change in terminal voltage.

[0085] Simultaneously, the voltage component calculation module 12 calculates the change in the sampled voltage. .in, The sampled voltage for the current control cycle. This is the historical sampled voltage from the previous control cycle. This is the total change in battery terminal voltage actually observed. Finally, the voltage component calculation module 12 calculates... The absolute value of the difference between the linear voltage change and the linear voltage change.

[0086] Subsequently, the voltage component calculation module 12 compares the absolute value of the difference with a preset polarization noise threshold. When it is determined that the absolute value of the difference is less than the polarization noise threshold, the voltage component calculation module 12 considers that the current voltage change is mainly contributed by the Ohmic effect and measurement noise, and the electrochemical polarization effect is insignificant or has been submerged by noise. Therefore, the polarization voltage component under the current control cycle is determined to be zero. This judgment logic effectively avoids misjudging measurement noise as polarization voltage, ensuring the robustness of state observation.

[0087] For example, the polarization noise threshold value mentioned above is determined based on the system's analog-to-digital converter (ADC) resolution, sensor measurement accuracy, and statistical analysis of the battery system's voltage measurement noise under steady state. A typical value could be 5mV, used to effectively filter out minute voltage fluctuations caused by thermal noise and quantization errors in the measurement circuit.

[0088] S302. When the absolute value of the difference between the change in the sampled voltage and the change in the linear voltage is greater than or equal to the polarization noise threshold, the absolute value of the difference is determined as the polarization voltage component.

[0089] Specifically, after calculating and comparing the absolute value of the difference with the polarization noise threshold, the voltage component calculation module 12 determines that if the absolute value of the difference is greater than or equal to the polarization noise threshold, then the difference contains a non-negligible, real electrochemical polarization voltage component. In this case, the voltage component calculation module 12 no longer sets the difference to zero, but directly determines its absolute value as the polarization voltage component under the current control cycle.

[0090] It can be understood that, after deducting the linear change caused by the ohmic internal resistance (i.e., the linear voltage change) from the observed total voltage change, the remaining voltage change is attributed to the electrochemical polarization kinetics process inside the battery.

[0091] In this way, the voltage component calculation module 12 can extract key physical quantities characterizing the battery polarization state in real time and quantitatively, thereby ultimately determining the value of the polarization voltage component. This process effectively decouples the voltage response caused by current changes, separating the linear ohmic part from the nonlinear polarization part.

[0092] Based on the above technical solution, this embodiment of the invention sets a preset polarization noise threshold to judge the calculated voltage change residual (i.e., the difference between the sampled voltage change and the linear voltage change). When the residual is less than the threshold, the polarization effect is considered negligible, and the polarization voltage component is set to zero, effectively filtering out the interference of measurement noise. When the residual is greater than or equal to the threshold, a significant polarization voltage is considered to have occurred, and the absolute value of the residual is directly used as the polarization voltage component. This method achieves accurate and robust online observation of the battery polarization state, providing a reliable input for subsequent evaluation of current regulation constraints, while avoiding misjudgments caused by noise and enhancing the stability of the system under complex operating conditions.

[0093] For example, in another DSP-based multi-segment intelligent charging strategy switching method provided in one embodiment of the present invention, the virtual impedance index is calculated based on the reference impedance, the polarization voltage component, and the remaining voltage space, specifically including the following steps:

[0094] S401. Determine the remaining voltage space based on the difference between the charging cutoff voltage threshold and the sampling voltage.

[0095] In this step, the impedance evaluation module 13 first reads the preset charging cutoff voltage threshold from the system configuration. This threshold is set by the battery management system based on the battery chemistry and represents the highest safe limit for the battery terminal voltage allowed during charging (e.g., 4.25V for a certain type of lithium-ion battery). Simultaneously, the impedance assessment module 13 receives the sampled voltage from the data acquisition module 11 for the current control cycle. Then, the impedance assessment module 13 performs a subtraction operation to calculate the remaining voltage space. It is understandable that the above calculations intuitively reflect the remaining "buffer" space between the current battery terminal voltage and the hardware safety boundary. The smaller the value, the closer the battery voltage is to the upper limit, the smaller the allowable voltage fluctuation margin when the system adjusts the current (especially downward adjustment), and the more conservative the control strategy needs to be.

[0096] S402. If the remaining voltage space is less than the preset protection threshold, set the value of the remaining voltage space to the protection threshold.

[0097] Specifically, the impedance evaluation module 13 calculates the remaining voltage space. Then, it will be compared with a preset protection threshold. Compare. Protection threshold. The settings are primarily based on a comprehensive consideration of the system voltage sampling noise floor, the analog-to-digital converter (ADC) resolution, and the numerical stability requirements of the control algorithm. The aim is to prevent measurement noise or minute fluctuations from causing problems when the voltage is very close to the cutoff threshold. The calculated value approaches zero, which can cause division by zero errors or numerical overflow in subsequent calculations. A typical example is a value of 10mV (i.e., 0.01V). If the condition is met... Then the impedance evaluation module 13 will force the remaining voltage space value used for subsequent calculations to be set to That is, execution .like If the original calculated value is retained, then this step provides numerical safety for the entire virtual impedance calculation.

[0098] S403. Calculate the virtual impedance index based on the reference impedance, polarization voltage components, and remaining voltage space. The value of the virtual impedance index is positively correlated with the polarization voltage components and negatively correlated with the remaining voltage space.

[0099] Optionally, the impedance evaluation module 13 performs S403 specifically by including the following steps:

[0100] (1) Determine the polarization weighting coefficient based on the polarization voltage component and the charging cutoff voltage threshold.

[0101] First, the impedance evaluation module 13 receives the polarization voltage component from the voltage component calculation module 12. And read the charging cutoff voltage threshold. Then, the polarization weighting coefficients are calculated using the following formula. : In the above formula, Represents the polarization voltage component. Indicates the charging cutoff voltage threshold. β This represents a preset sensitivity adjustment coefficient (e.g., 0.005). It can be understood that the above formula normalizes the polarization voltage component, scaling it proportionally to the voltage threshold to obtain a dimensionless weighting coefficient. When the polarization voltage component... When it is zero or very small, A value close to 1 indicates a weak polarization effect; as... Increase The linear increase is used to amplify the virtual impedance in subsequent calculations to reflect the increased difficulty of current regulation when polarization is severe.

[0102] (2) Determine the safety adjustment items based on the preset safety gain reference voltage and the remaining voltage space.

[0103] Then, the impedance evaluation module 13 reads a preset safety gain reference voltage. (For example, 1% of the battery's rated voltage, such as 0.05V, can be used), and the remaining voltage space after processing by S402 is obtained. The safety adjustment item is calculated using the following formula. : In the above formula, This represents the safety gain reference voltage, used to adjust the system's sensitivity to voltage approaching the safety boundary; This represents the remaining voltage space. It should be noted that the above formula includes a term inversely proportional to the remaining voltage space. When the remaining voltage space... When it is very large, The value is very small, and its impact on the overall situation is negligible; when As the charging process progresses, the temperature gradually decreases. The value increases rapidly, thus introducing a strong "barrier" effect into the virtual impedance, forcing the system to significantly slow down current changes as the voltage approaches its upper limit.

[0104] (3) Determine the virtual impedance index based on the reference impedance, polarization weighting coefficient and safety adjustment term.

[0105] For example, the impedance evaluation module 13 finally synthesizes the virtual impedance index using the following formula. : in, This represents the reference impedance (battery internal resistance in ohms) obtained from the data acquisition module 11, which serves as the physical dimension basis for the virtual impedance. This represents the polarization weighting coefficient, which reflects the dynamic influence of the polarization state; The term is a safety gain factor that includes a safety adjustment term. It can be understood that the above formula uses physical internal resistance as the basis for the calculation. Based on this, firstly through A coefficient greater than or equal to 1 is applied to penalize polarization; then, a safety factor is applied that increases nonlinearly as the remaining voltage space decreases, thus synthesizing the final virtual impedance index. . The numerical values ​​and polarization voltage components (via The voltage is positively correlated with the residual voltage space (characterized by the denominator term) and negatively correlated with the residual voltage space (characterized by the denominator term).

[0106] Based on the above technical solution, this embodiment of the invention quantifies the safety margin by calculating the remaining voltage space and introduces a protection threshold to ensure numerical stability. Furthermore, it creatively combines the polarization weighting coefficient, which characterizes the dynamics inside the battery, with a safety adjustment term reflecting external voltage boundary constraints, fusing them based on physical internal resistance to dynamically generate a virtual impedance index. This index comprehensively quantifies the current regulation "resistance" constituted by electrochemical polarization and voltage approximation effects, providing precise and adaptive constraint input for subsequent adaptive determination of the current adjustment step size, thereby achieving a balance between preventing overvoltage and improving efficiency at the algorithm level.

[0107] For example, in another DSP-based multi-segment intelligent charging strategy switching method provided in one embodiment of the present invention, the target charging current command is updated according to the step size adjustment based on the charging current, specifically including the following steps:

[0108] S501, Obtain the charging current command from the previous control cycle.

[0109] In this step, before calculating the new current instruction, the policy update module 15 needs to obtain the historical control state as the starting point for the update. Specifically, the policy update module 15 reads the previous control cycle (i.e., the [number]th control cycle) from its internal registers or shared memory. The target charging current command that has been determined and output at the end of each control cycle is denoted as... This instruction value is the final result of the adaptive control or safety management logic in the previous cycle, representing the current control objective for the power stage circuit. Obtaining this historical instruction value provides the necessary initial reference for instruction recursion calculation in the current cycle.

[0110] S502. Based on the charging current command and charging current adjustment step size of the previous control cycle, determine the candidate charging current command for the current control cycle.

[0111] Furthermore, the strategy update module 15 receives the current control cycle (the number of cycles) calculated by the adjustment step size determination module 14. Allowable charging current adjustment step size under (per cycle) This step size quantifies the maximum allowable current reduction within the current cycle, based on the voltage fluctuation budget and virtual impedance constraints. Subsequently, the strategy update module 15 calculates the candidate charging current command for the current control cycle using the following formula: in, This indicates the charging current command from the previous control cycle. This indicates the allowable charging current adjustment step size under the current control cycle (provided by the adjustment step size determination module 14). It should be noted that the above formula performs a monotonically decreasing update: subtracting the safety adjustment step size calculated in the current cycle from the command value of the previous cycle, thus obtaining a "tentative" and lower candidate current command value. This step ensures that during the current switching process in multi-stage charging, the current command always changes in the direction of decreasing, meeting the basic requirement of switching from a high rate to a low rate.

[0112] S503. The larger of the candidate charging current command and the preset target stage charging current value is determined as the updated target charging current command.

[0113] Specifically, the strategy update module 15 calculates the candidate charging current command. Subsequently, it was not directly used as the final output. To avoid the current command being "over-adjusted" (i.e., lower than the preset constant current value for the next stage) due to excessive single-step adjustment or excessive cumulative adjustment, the strategy update module 15 introduced a lower limit comparison mechanism to read the preset target stage charging current value from the system configuration. This value is the constant current value set for the next stage (the stage to which the user will switch) in a multi-stage charging strategy (e.g., when switching from 3C to 1C). This refers to the current value corresponding to 1C (e.g., 10A). Afterwards, the strategy update module 15 will... and The comparison is performed, and the final target charging current command for this cycle is determined by taking the maximum value. The decision-making logic can be expressed by the following formula: In the above formula, This indicates the candidate charging current command calculated in the current cycle. This indicates the preset target charging current value. This indicates that the larger of the two values ​​is taken. It should be noted that the above formula implements lower limit clamping protection: if the candidate instruction... Still above the target value This indicates that the switching process is not yet complete, and the instruction update for this cycle is... The current will continue to decrease; if the candidate instruction The target value has been reached or fallen below the calculated value. If this indicates that the target stage has been reached or slightly exceeded, then the instruction will be clamped at this point. This ensures that the switching process is accurately terminated and the system proceeds to the next stage of constant current charging. This mechanism guarantees that the current command converges smoothly and stably to the target value without oscillation or falling below the target value.

[0114] Based on the above technical solution, this embodiment of the invention achieves robust updates to the target charging current command by acquiring historical commands, calculating candidate commands based on a safety step size, and comparing them with the target stage current value at a lower limit and taking the larger value. This method ensures the monotonicity and controllability of the current switching process. It fully utilizes the safety adjustment space of each control cycle to gradually reduce the current, and effectively prevents command over-adjustment through final target value clamping. This ensures that the current can transition accurately and smoothly to the next charging stage, thereby efficiently completing the switching of charging strategies while adhering to safety constraints.

[0115] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0116] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A DSP-based multi-section intelligent charging strategy switching system, characterized in that, The system includes: a data acquisition module, a voltage component calculation module, an impedance evaluation module, an adjustment step size determination module, and a strategy update module; The data acquisition module is used to acquire the reference impedance of the battery in the current switching cycle, as well as the sampling current and sampling voltage of the battery in the current control cycle. The voltage component calculation module is used to determine the linear voltage change of the battery in the current control cycle based on the change in the sampling current and the reference impedance, and to determine the polarization voltage component of the battery in the current control cycle based on the linear voltage change and the change in the sampling current; wherein, the polarization voltage component is used to characterize the difference between the change in the sampling voltage and the linear voltage change. The impedance evaluation module is used to determine a virtual impedance index based on the polarization voltage component, the sampling voltage, and the charging cutoff voltage threshold; wherein the virtual impedance index is used to characterize the degree of constraint of the current charging current regulation. The adjustment step size determination module is used to determine the allowable charging current adjustment step size under the current control cycle based on the preset voltage fluctuation budget value and the virtual impedance index. The strategy update module is used to adjust the step size according to the charging current and update the target charging current command.

2. The DSP-based multi-stage intelligent charging strategy switching system according to claim 1, characterized in that, When determining the linear voltage change of the battery in the current control cycle based on the change in the sampled current and the reference impedance, the voltage component calculation module is specifically used for: If the absolute value of the difference between the change in the sampled voltage and the change in the linear voltage is less than a preset polarization noise threshold, the polarization voltage component is determined to be zero. If the absolute value of the difference between the change in the sampled voltage and the change in the linear voltage is greater than or equal to the polarization noise threshold, the absolute value of the difference is determined as the polarization voltage component.

3. The DSP-based multi-stage intelligent charging strategy switching system according to claim 2, characterized in that, When determining the virtual impedance index based on the polarization voltage component, the sampling voltage, and the charging cutoff voltage threshold, the impedance evaluation module is specifically used for: The remaining voltage space is determined based on the difference between the charging cutoff voltage threshold and the sampling voltage; If the remaining voltage space is less than a preset protection threshold, the value of the remaining voltage space is set to the protection threshold. The virtual impedance index is calculated based on the reference impedance, the polarization voltage component, and the remaining voltage space; wherein the value of the virtual impedance index is positively correlated with the polarization voltage component and negatively correlated with the remaining voltage space.

4. The DSP-based multi-stage intelligent charging strategy switching system according to claim 3, characterized in that, When calculating the virtual impedance index based on the reference impedance, the polarization voltage component, and the remaining voltage space, the impedance evaluation module is specifically used for: The polarization weighting coefficients are determined based on the polarization voltage components and the charging cutoff voltage threshold. The safety adjustment item is determined based on the preset safety gain reference voltage and the remaining voltage space; The virtual impedance index is determined based on the reference impedance, the polarization weighting coefficient, and the safety adjustment term.

5. The DSP-based multi-stage intelligent charging strategy switching system according to claim 1, wherein, When the strategy update module adjusts the step size according to the charging current and updates the target charging current command, it is specifically used for: Obtain the charging current command from the previous control cycle; Based on the charging current command of the previous control cycle and the charging current adjustment step size, determine the candidate charging current command for the current control cycle. The larger of the candidate charging current command and the preset target stage charging current value is determined as the updated target charging current command.

6. The DSP-based multi-stage intelligent charging strategy switching system according to claim 3, wherein, Before the strategy update module adjusts the step size according to the charging current and updates the target charging current command, it is specifically used for: If the sampled voltage is greater than or equal to the charging cutoff voltage threshold, or the remaining voltage space is less than the preset protection threshold, then the target charging current command is updated to the preset target stage charging current value. Otherwise, the target charging current command is updated according to the charging current adjustment step size.

7. The DSP-based multi-stage intelligent charging strategy switching system of claim 1, wherein, The system also includes: an initialization module; The initialization module is used to perform an initialization operation during the first control cycle of charging control at system startup; wherein the initialization operation includes setting the historical sampled voltage value to the current measured sampled voltage value and setting the historical sampled current value to the current measured sampled current value.

8. The DSP-based multi-stage intelligent charging strategy switching system according to any one of claims 1-7, characterized in that, When acquiring the reference impedance of the battery in the current switching cycle, and the sampled current and sampled voltage of the battery in the current control cycle, the data acquisition module is specifically used for: At the peak and trough of the pulse width modulation (PWM) switching signal, the terminal voltage and loop current of the battery are collected respectively to obtain the peak sampling voltage, peak sampling current, trough sampling voltage and trough sampling current. The voltage ripple amplitude is determined based on the difference between the peak sampling voltage and the trough sampling voltage. The current ripple amplitude is determined based on the difference between the peak sampling current and the trough sampling current. The reference impedance is determined based on the voltage ripple amplitude and the current ripple amplitude.

9. The DSP-based multi-segment intelligent charging strategy switching system according to claim 8, characterized in that, When determining the reference impedance based on the voltage ripple amplitude and the current ripple amplitude, the data acquisition module is specifically used for: When the current ripple amplitude is greater than or equal to a preset ripple threshold, the ratio of the voltage ripple amplitude to the current ripple amplitude is determined as the instantaneous impedance. The instantaneous impedance is low-pass filtered to obtain the reference impedance.

10. The DSP-based multi-segment intelligent charging strategy switching system according to claim 8, characterized in that, The data acquisition module is also used to sample the terminal voltage and loop current of the battery multiple times in each control cycle. The data acquisition module is also used to average the voltage values ​​sampled multiple times to obtain the sampled voltage; The data acquisition module is also used to average the current values ​​sampled multiple times to obtain the sampled current.

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