A mobile battery cabin continuous power supply method and system based on voltage phase prediction

Abstract

This application discloses a method and system for continuous power supply of mobile battery compartments based on voltage phase prediction, belonging to the field of continuous power supply technology. The method includes: acquiring the operating status of the current mobile battery compartment and candidate mobile battery compartments, and determining the switching judgment result; if switching is required, continuously acquiring the voltage signals of the two mobile battery compartments at a preset sampling frequency to generate a phase difference sequence; determining the frequency difference data between the two mobile battery compartments based on the phase difference sequence; determining a safety window based on the frequency difference data and the phase difference change rate; sending a disconnection command to the contactor of the current mobile battery compartment within the safety window and calculating the dead time; after the dead time ends, issuing a closing command to the contactor of the candidate mobile battery compartment, making the candidate mobile battery compartment a power source. This solution does not rely on inter-device communication and synchronization functions, but achieves millisecond-level seamless switching by real-time monitoring and coordinated control of two independent voltage sources through upper-level control.

Description

Technical Field

[0001] This application belongs to the field of continuous power supply technology, specifically relating to a method and system for continuous power supply of a mobile battery compartment based on voltage phase prediction. Background Technology

[0002] Mobile energy storage systems are critical power sources for emergency power supply, providing power to remote areas, and temporary operations. To ensure longer power supply with a single deployment, the current mainstream approach is to use standardized, quickly replaceable battery compartment modules. A typical mobile energy storage system architecture generally consists of a fixed discharge compartment that integrates control and converter units, and multiple mobile battery compartments that contain only the battery system.

[0003] In traditional mobile battery compartment switching operations, workers use a multimeter and an internal resistance tester. First, they connect the multimeter probes to the battery electrodes sequentially to measure and record the voltage. Then, they operate the internal resistance tester correctly, setting and calibrating it, connecting the battery, and reading and recording the internal resistance value. After collecting all battery data, they assess the battery's charge level and health based on experience and parameters. Finally, they select batteries in good condition for installation, successfully completing the switch and providing power for the equipment's operation.

[0004] However, manually operating instruments to measure battery data is cumbersome, time-consuming, and prone to errors. Furthermore, reliance on manual operation results in low automation, making it difficult to handle large-scale switching and incurring high labor costs. Because the entire process cannot involve real-time power connection and switching, the load cannot obtain stable power during data acquisition and battery selection, thus hindering continuous power supply. Summary of the Invention

[0005] To overcome the aforementioned shortcomings, this invention is proposed to provide a solution, or at least a partial solution, to the technical problem of manually operating instruments to measure battery data in the prior art. This process is cumbersome, time-consuming, and prone to errors. Furthermore, it relies on manual operation, has low automation, struggles to handle large-scale switching, and incurs high labor costs. Because the entire process cannot be connected and switched to power in real time, the load cannot obtain stable power during data acquisition and battery selection, thus failing to achieve continuous power supply.

[0006] In a first aspect, the present invention provides a method for continuous power supply of a mobile battery compartment based on voltage phase prediction, the method comprising: The first operating state of the current mobile battery compartment and the second operating state of the candidate mobile battery compartment are obtained. Based on the first operating state and the second operating state, the switching utility is evaluated to obtain the switching judgment result. If the switching judgment result indicates that switching is required, the first voltage signal connected to the AC output terminal of the PCS connected to the current mobile battery compartment and the second voltage signal connected to the AC output terminal of the PCS connected to the candidate mobile battery compartment are continuously acquired at a preset sampling frequency, and a phase difference sequence is generated based on the continuously acquired first voltage signal and second voltage signal. Short-term trend fitting is performed based on the phase difference sequence to predict the phase difference change trend, obtain the phase difference change rate, and calculate the frequency difference data between the current mobile battery compartment and the candidate mobile battery compartment based on the phase difference change rate. The duration of the safety window is calculated based on frequency difference data, and the center of the safety window is predicted based on the rate of change of phase difference. The safety window is then determined based on the duration and center of the safety window. Send a disconnect command to the first contactor of the current mobile battery compartment within the safety window, obtain the first effective value of the first load current and the first power factor angle of the current mobile battery compartment, and calculate the dead time based on the first effective value of the load current, the first power factor angle and the preset dead time calculation formula. During the dead time, maintain electrical isolation between the current mobile battery compartment and the load side, and after the dead time ends, issue a closing command to the second contactor of the candidate mobile battery compartment to make the candidate mobile battery compartment a power source and realize continuous power supply to the load.

[0007] In a second aspect, the present invention provides a continuous power supply system for a mobile battery compartment based on voltage phase prediction, the system comprising: The evaluation module is used to obtain the first operating state of the current mobile battery compartment and the second operating state of the candidate mobile battery compartment, and to evaluate the switching utility based on the first operating state and the second operating state to obtain the switching judgment result. The phase difference sequence generation module is used to continuously acquire the first voltage signal connected to the AC output terminal of the PCS connected to the current mobile battery compartment and the second voltage signal connected to the AC output terminal of the PCS connected to the candidate mobile battery compartment at a preset sampling frequency if the switching judgment result is that switching is required, and generate a phase difference sequence based on the continuously acquired first voltage signal and second voltage signal. The prediction module is used to perform short-term trend fitting based on the phase difference sequence to predict the phase difference change trend, obtain the phase difference change rate, and calculate the frequency difference data between the current mobile battery compartment and the candidate mobile battery compartment based on the phase difference change rate. The safety window determination module is used to calculate the duration of the safety window based on frequency difference data, predict the center of the safety window based on the phase difference change rate, and determine the safety window based on the duration and center of the safety window. The dead time calculation module is used to send a disconnection command to the first contactor of the current mobile battery compartment within the safety window, obtain the first effective value of the first load current and the first power factor angle of the current mobile battery compartment, and calculate the dead time based on the first effective value of the load current, the first power factor angle and the preset dead time calculation formula. The switching module is used to maintain electrical isolation between the current mobile battery compartment and the load side during the dead time, and after the dead time ends, it sends a closing command to the second contactor of the candidate mobile battery compartment, so that the candidate mobile battery compartment becomes the power supply and realizes continuous power supply to the load.

[0008] In a third aspect, an electronic device is provided, comprising a processor, a memory, and a program or instructions stored in the memory and executable on the processor, the program or instructions being loaded and run by the processor to perform the steps of the aforementioned method for continuous power supply of a mobile battery compartment based on voltage phase prediction.

[0009] In a fourth aspect, a computer-readable storage medium is provided, wherein a plurality of program codes are stored therein, the program codes being adapted to be loaded and run by a processor to perform the steps of the above-described method for continuous power supply of a mobile battery compartment based on voltage phase prediction.

[0010] The above-described technical solutions of the present invention have at least one or more of the following beneficial effects: 1. Breaking away from the traditional technical approach that relies on the advanced synchronization functions of the PCS itself, a new architecture of "external monitoring-phase prediction-active control" led by the system-level upper-level controller (EMS) is creatively proposed. This architecture decouples the complex synchronization judgment from the PCS, eliminating the need for expensive inter-synchronization communication and phase-locked loop functions, thereby significantly reducing system hardware costs and compatibility barriers.

[0011] 2. Achieved true seamless electrical switching. By predicting the phase difference trend with high precision, the system dynamically captures the optimal synchronization window and executes sub-cycle-level (millisecond-level) "break-before-connect" timing control within this window, resulting in minimal load-side voltage fluctuations (e.g., <2%), fundamentally avoiding inrush currents and power outages caused by voltage asynchrony.

[0012] 3. It combines high reliability and high adaptability. As a higher-level control strategy independent of the PCS, its algorithm complexity is concentrated in the EMS, without interfering with the stable network operation of the PCS itself, thus improving the overall system reliability. At the same time, mechanisms such as dynamic dead time enable it to intelligently adapt to different load conditions. Attached Figure Description

[0013] The disclosure of this invention will become more readily understood with reference to the accompanying drawings. It will be readily understood by those skilled in the art that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this invention. Furthermore, similar numbers in the drawings are used to denote similar components, wherein:

[0014] Figure 1 This is a schematic flowchart of the first main steps of a mobile battery compartment continuous power supply method based on voltage phase prediction according to an embodiment of the present invention. Figure 2 This is a schematic flowchart of the second main steps of a mobile battery compartment continuous power supply method based on voltage phase prediction according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the main structure of a mobile battery compartment continuous power supply system based on voltage phase prediction according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0015] Some embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0016] In the description of this invention, "module" and "processor" can include hardware, software, or a combination of both. A module can include hardware circuitry, various suitable sensors, communication ports, memory, and may also include software components, such as program code, or a combination of software and hardware. A processor can be a central processing unit, microprocessor, image processor, digital signal processor, or any other suitable processor. The processor has data and / or signal processing capabilities. The processor can be implemented in software, in hardware, or a combination of both. Non-transitory computer-readable storage media include any suitable medium capable of storing program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc. The term "A and / or B" means all possible combinations of A and B, such as only A, only B, or A and B. The terms "at least one A or B" or "at least one of A and B" have a similar meaning to "A and / or B" and can include only A, only B, or A and B. The singular terms "a" or "this" can also include plural forms.

[0017] See appendix Figure 1 , Figure 1 This is a schematic flowchart of the first main steps of a continuous power supply method for a mobile battery compartment based on voltage phase prediction, according to an embodiment of the present invention. Figure 1As shown, a method for continuous power supply of a mobile battery compartment based on voltage phase prediction in an embodiment of the present invention mainly includes the following steps S101-S106.

[0018] Step S101: Obtain the first operating state of the current mobile battery compartment and the second operating state of the candidate mobile battery compartment, evaluate the switching utility based on the first operating state and the second operating state, and obtain the switching judgment result.

[0019] The current mobile battery compartment is a mobile battery compartment that is currently in operation, connected to the load side or the grid side, and is undertaking the task of power supply. It continuously outputs electrical energy to external loads through its own energy storage battery and power conversion system, and is in an actual power supply working state. The current mobile battery compartment can be implemented in the form of a vehicle, forming a mobile battery vehicle, relying on an onboard energy storage system and an onboard PCS (Power Conversion System, energy storage converter) to supply power to external systems.

[0020] A candidate mobile battery compartment is a mobile battery compartment that is in a state of standby during the current mobile battery compartment's power supply period, not yet supplying power to the load side or the grid side, but has the conditions to take over power supply. It meets the preset access feasibility requirements and is used to replace the current mobile battery compartment to perform power supply tasks when needed. The candidate mobile battery compartment can be implemented in the form of a vehicle, forming a mobile battery vehicle, which supplies power to external systems by relying on the vehicle-mounted energy storage system and the vehicle-mounted PCS.

[0021] The first operating state is the status information of the current mobile battery compartment's power supply capacity, operational stability, and access conditions at the current moment. It includes at least one of the mobile battery compartment's output capacity status, load matching status, and operational sustainability status, and is used to reflect the battery compartment's working performance in the current or potential power supply scenarios.

[0022] The second operating state is the status information of the candidate mobile battery compartment's power supply capacity, operational stability, and access conditions at the current moment, including at least one of the mobile battery compartment's output capacity status, load matching status, and operational sustainability status, which is used to reflect the battery compartment's working performance in the current or potential power supply scenarios.

[0023] The switching judgment result determines whether the control judgment result of switching the mobile battery compartment can be executed.

[0024] During system operation, the system utilizes its own sensors and measuring devices to collect real-time electrical parameters such as voltage, current, and output power of the current mobile battery compartment and candidate mobile battery compartments. It also simultaneously records load demand status, historical power supply stability characteristics, and battery health indicators. Based on this collected data, the system calculates the output capacity, load matching status, and operational sustainability status of the current and candidate mobile battery compartments under the current power supply scenario, forming corresponding first and second operating states. This comprehensively characterizes the performance of the two battery compartments under current and potential power supply scenarios. The Energy Management System (EMS) then uses these first and second operating states to extrapolate and calculate the changes in operational performance before and after the potential battery compartment switchover, thereby obtaining data on the potential positive utility of the switchover. Specifically, the system first combines the current output power, load matching status, and operational stability status of the current mobile battery compartment with the available capacity, health status, and access feasibility of the candidate mobile battery compartment to estimate the trend of power supply capacity changes after the switchover, thus obtaining a first benefit indicator to characterize the degree of improvement in power supply adaptability after the switchover. Simultaneously, based on the difference in sustainable power supply capacity between the current mobile battery compartment and the candidate mobile battery compartment, the change in the overall continuous operating time of the system after the switch is calculated, resulting in a second benefit indicator. Furthermore, based on the current health consumption status of the current mobile battery compartment and the health status of the candidate mobile battery compartment, the trend of health loss reduction in the current mobile battery compartment due to load release after the switch is estimated, resulting in a third benefit indicator. These multiple benefit indicators together constitute a switch benefit data set, reflecting the degree of operational performance improvement that a potential battery compartment switch can bring.

[0025] Even without actually performing a battery compartment switchover, the system still simulates the switchover process for potential battery compartments based on the first and second operating states, thereby predicting various cost factors that may be introduced during the switchover. Specifically, based on the differences in output voltage, frequency, and phase state between the current mobile battery compartment and the candidate mobile battery compartment, the system calculates the synchronization adjustment process required to perform the switchover operation and estimates the potential energy loss level during the switchover, obtaining energy cost data. Combining the current operating states and expected synchronization processes of the two mobile battery compartments, the system predicts the time span required to complete the switchover, obtaining time cost data. Simultaneously, based on the potential phase disturbances, power fluctuations, and transient instability risks that may occur during the switchover, the system estimates the potential impact of the switchover on system operational stability, obtaining stability cost data. These multiple cost data together constitute a switchover cost data set, which characterizes the cost required to switch potential battery compartments.

[0026] After acquiring the switching benefit data set and the switching cost data set, the system performs comparative calculations to determine whether a potential battery compartment switching has positive utility. Specifically, it compares the degree of operational performance improvement reflected in the switching benefit data set with the switching cost reflected in the switching cost data set. When the degree of improvement corresponding to the switching benefit meets the preset utility conditions and can cover the adverse effects of the switching cost, the system generates a switching judgment result indicating that the battery compartment switching should be performed; when the switching benefit is insufficient to offset the switching cost, the system generates a switching judgment result indicating that the current mobile battery compartment power supply status should be maintained.

[0027] Step S102: If the switching judgment result is that switching is required, continuously acquire the first voltage signal connected to the AC output terminal of the PCS connected to the current mobile battery compartment and the second voltage signal connected to the AC output terminal of the PCS connected to the candidate mobile battery compartment at a preset sampling frequency, and generate a phase difference sequence based on the continuously acquired first voltage signal and second voltage signal.

[0028] The preset sampling frequency is the sampling rate set in advance before the voltage signal is continuously acquired. It is used to determine the number of voltage signal samples acquired per second, ensuring the data accuracy required for phase difference calculation and frequency analysis.

[0029] The PCS AC output terminal is the port where the mobile battery compartment power conversion device outputs AC power, responsible for supplying power to the load or the power grid, and also providing voltage and current signals that can be used for measurement.

[0030] The first voltage signal is a sequence of instantaneous AC voltage values ​​continuously collected from the current mobile battery compartment PCS AC output terminal, used to reflect the current electrical state of the mobile battery compartment output terminal.

[0031] The second voltage signal is a sequence of instantaneous AC voltage values ​​continuously collected from the AC output terminal of the candidate mobile battery compartment PCS, used to reflect the electrical state of the candidate mobile battery compartment output terminal.

[0032] The phase difference sequence is a data sequence representing the real-time phase difference between the output voltages of the two PCS units. It is obtained by extracting the fundamental phase from the first and second voltage sequences using a sliding window discrete Fourier transform, and then subtracting the corresponding values ​​from each sequence. This sequence is used to analyze the synchronization of the output voltages of the two mobile battery compartments and to calculate the frequency difference.

[0033] If the determination indicates a switch is required, the EMS uses its built-in high-precision, multi-channel synchronous ADC (Analog-to-Digital Converter) to synchronously acquire voltage sensor signals directly connected to the AC output terminals of the PCS in both the current and candidate mobile battery compartments at a preset sampling frequency. The voltage sensors are rigidly connected to the independent channels of the ADC acquisition card via shielded cables. Based on the ADC sampling card's internal clock synchronization mechanism, microsecond-level time alignment accuracy is ensured for the acquisition of the two voltage signals, resulting in the first and second voltage signals.

[0034] After data acquisition, the first and second voltage signals are digitally low-pass filtered to remove high-frequency noise and smooth instantaneous voltage fluctuations, resulting in a first smoothed voltage sequence and a second smoothed voltage sequence. A sliding window discrete Fourier transform is then performed on both the smoothed first and second voltage sequences. The window length is set to 1 to 2 power frequency cycles. This transform directly extracts the fundamental phases of the first and second voltage signals corresponding to the center moment of each sliding window.

[0035] Subsequently, the two fundamental phase values ​​corresponding to the same moment are subtracted to obtain the instantaneous phase difference at that moment. This calculation is continued as the sliding window advances, resulting in a continuous, high-precision phase difference sequence. This sequence directly and accurately reflects the real-time phase relationship between the output voltages of the two PCS units and its trend over time, providing a reliable data foundation for subsequent synchronization analysis and safety window prediction.

[0036] Based on the above technical solution, optionally, a phase difference sequence is generated based on the continuously acquired first voltage signal and second voltage signal, including: Based on the continuously acquired first voltage signal and second voltage signal, a first voltage instantaneous value sequence and a second voltage instantaneous value sequence are generated; The first voltage instantaneous value sequence and the second voltage instantaneous value sequence are subjected to digital low-pass filtering to obtain the first voltage smoothed sequence and the second voltage smoothed sequence; The first voltage smoothing sequence and the second voltage smoothing sequence are subjected to sliding window Fourier transform to obtain the first fundamental phase and the second fundamental phase, respectively. The phase difference sequence is generated by subtracting the first fundamental phase sequence from the second fundamental phase sequence.

[0037] In this scheme, the first voltage instantaneous value sequence is a series of instantaneous voltage values ​​obtained by continuously collecting the voltage signal of the AC output terminal of the current mobile battery compartment and sorting it according to the sampling frequency. This can intuitively reflect the real-time changes of voltage over time.

[0038] The second voltage instantaneous value sequence is a series of instantaneous voltage values ​​obtained by continuously collecting the voltage signal of the AC output terminal of the candidate mobile battery compartment and organizing it according to the sampling frequency. It can intuitively reflect the real-time change of the battery compartment's output voltage over time.

[0039] The first voltage smoothing sequence is a sequence obtained by applying a digital low-pass filter to the first voltage instantaneous value sequence. It can effectively suppress high-frequency noise and highlight the fundamental component of the voltage.

[0040] The second voltage smoothing sequence is obtained by applying a digital low-pass filter to the second voltage instantaneous value sequence. It can effectively suppress high-frequency noise and highlight the fundamental component of the voltage.

[0041] The first fundamental phase is the fundamental component phase extracted after performing a sliding window Fourier transform on the first voltage smoothing sequence, and is used to accurately locate the fundamental position of the voltage waveform.

[0042] The second fundamental phase is the fundamental component phase extracted after performing a sliding window Fourier transform on the second voltage smoothing sequence, and is used to accurately locate the fundamental position of the voltage waveform.

[0043] The AC output voltage signals of the current and candidate mobile battery compartments are continuously acquired at a preset sampling frequency. The continuous voltage signals are discretized to form a sequence of instantaneous voltage values ​​that change over time, namely the first voltage instantaneous value sequence and the second voltage instantaneous value sequence. These two sets of sequences can accurately reflect the instantaneous state of the voltage waveform at each sampling point, while completely preserving the dynamic fluctuation information of the voltage.

[0044] To eliminate high-frequency noise and interference that may be introduced during the sampling process, the first and second instantaneous voltage value sequences are subjected to digital low-pass filtering to remove frequency components higher than the fundamental frequency, resulting in smoothed voltage sequences, namely the first smoothed voltage sequence and the second smoothed voltage sequence. These two sets of smoothed sequences highlight the fundamental characteristics of the voltage, providing accurate and stable data input for subsequent phase analysis.

[0045] A sliding window Fourier transform is performed on the first and second voltage smoothing sequences, using a sliding window of one to two power frequency cycles. For each transform window, the spectral line corresponding to the fundamental frequency is located, and the argument of its complex result is calculated, which is used as the fundamental phase at the center of that window. Subsequently, the two fundamental phase values ​​corresponding to the same timestamp are subtracted to obtain the instantaneous phase difference at that moment. This process is repeated for all continuously sliding windows, thus generating a continuous phase difference sequence. This sequence directly and accurately characterizes the dynamic changes in the phase relationship between the output voltages of the two PCS units.

[0046] In this scheme, the accuracy and stability of the phase difference measurement of the two voltage channels are improved by smoothing and precise phase extraction. The phase difference sequence accurately and continuously records the real-time phase offset and its changing trend between the output voltages of the two PCS, providing a unique data basis for subsequent safety window prediction.

[0047] Step S103: Perform short-time trend fitting based on the phase difference sequence to predict the phase difference change trend, obtain the phase difference change rate, and calculate the frequency difference data between the current mobile battery compartment and the candidate mobile battery compartment based on the phase difference change rate.

[0048] The phase difference change rate is calculated by fitting the phase difference changes of the most recent sampling points in a phase difference sequence using short-term trend fitting methods such as linear regression. The slope of the fitted result is the phase difference change rate, which characterizes the rate of change of the phase difference over time. This indicator can reflect the synchronous change trend of the voltage waveform between the current mobile battery compartment and the candidate mobile battery compartment.

[0049] The frequency difference data is calculated based on the phase difference change rate, combined with the physical relationship between phase and frequency, to obtain the instantaneous frequency difference between the current mobile battery compartment and the candidate mobile battery compartment.

[0050] Based on the phase difference sequence, a sliding window containing a preset number of sampling points is first constructed at the current sampling time. Short-term trend fitting is then performed on the phase difference data within the window. Specifically, a linear regression is performed on the phase difference sequence within the sliding window using the sampling point indices. The slope and intercept of the fitted line are calculated. The intercept represents the phase difference baseline at the starting point of the fitting window, while the slope characterizes the phase difference's change over time. In this way, the direction and rate of recent phase difference changes can be quantified, thereby constructing a fitted line that reflects the trend of phase difference changes.

[0051] Wherein, the sampling point number k and the physical time t are determined by a fixed sampling period. Related, satisfying in, The window starts at time; Let be the physical time corresponding to the k-th point. Therefore, the intercept... Represents the moment The phase difference benchmark is used, and the fitting slope S characterizes the phase difference as a function of sampling points, with the unit being degrees per sampling point (° / sampling point).

[0052] The slope of the fitted line is then converted into the phase difference change rate, which reflects the rate of change of the phase difference per unit time and can be used to predict the possible value of the phase difference at the next moment. The conversion follows a fixed method: phase difference change rate = fitted slope ÷ sampling period, where the sampling period is determined by a preset sampling frequency to ensure that the fitted slope corresponds accurately to the actual time scale.

[0053] Based on the obtained phase difference change rate, and combined with the physical relationship between phase and frequency, the frequency difference data between the current mobile battery compartment and the candidate mobile battery compartment is calculated. Specifically, the frequency difference equals the phase difference change rate divided by 360 degrees, thus obtaining the instantaneous frequency deviation between the AC output terminals of the two battery compartments. This frequency difference data can intuitively reflect the synchronization degree of the output waveforms of the two battery compartments, and at the same time provide a core basis for subsequent dead time calculation and switching safety window determination.

[0054] Based on the above technical solution, optionally, short-time trend fitting is performed on the phase difference sequence to predict the phase difference change trend and obtain the phase difference change rate, including: In the phase difference sequence, a sliding fitting window containing a preset number of sampling points is constructed based on the current sampling time, and linear regression fitting is performed on the sampling points within the sliding fitting window to obtain a fitted straight line; wherein, the equation of the fitted straight line is: ; in, represents the phase difference fitted value of the kth sampling point; k is the sampling point number within the sliding fitting window. This is the baseline value of the phase difference corresponding to the starting point of the sliding fitting window; The fitting slope is used to represent the trend of phase difference as a function of sampling points; The sampling period is determined based on a preset sampling frequency, and the phase difference change rate is calculated based on the fitting slope and the sampling period; the calculation process is as follows: ; in, The rate of change of phase difference; The slope is the fitted slope; The preset sampling period; The frequency difference between the current mobile battery compartment and the candidate mobile battery compartment is calculated based on the phase difference change rate; the calculation process is as follows: ; in, This is frequency difference data; This represents the rate of change of phase difference.

[0055] In this scheme, the unit of R is degrees per second (° / s).

[0056] The current sampling time is the latest sampling time point being processed in the phase difference sequence, which is used to accurately locate the placement of the sliding fitting window.

[0057] The preset number of sampling points is the number of consecutive sampling points included when constructing the sliding fitting window, providing a fixed-size sample base for trend fitting.

[0058] A sliding fitting window is a set of continuous sampling points extracted from the phase difference sequence with the current sampling time as the center or endpoint.

[0059] The fitted line is the linear equation obtained by performing linear regression on the sampling points within the sliding fitting window. It can accurately describe the change of phase difference over time and provide a basis for calculating the rate of change of phase difference.

[0060] The current sampling time is determined in the phase difference sequence, which is the time position corresponding to the latest sampling point being processed. Using this time as a reference, a continuous sequence containing a preset number of sampling points is extracted from the phase difference sequence. These sampling points cover and / or include the current time, thus constructing a sliding fitting window. The length of the sliding fitting window is defined by the preset number of samples, which can capture the local change trend of the phase difference within a short time range while avoiding excessive noise interference, ensuring fitting accuracy.

[0061] Using the sampling points within the sliding fitting window as input data, linear regression is performed. Specifically, with the time sequence number of each sampling point as the independent variable and the corresponding phase difference as the dependent variable, the least squares method is used to calculate the fitted line, ensuring that the line closely matches the variation patterns of all sampling points within the window. During the fitting process, data weighting or outlier removal can be applied to further improve the accuracy of short-term trend representation. The fitted line equation clearly characterizes the rate of change of phase difference and the initial reference point within the window time period, providing core foundational data for subsequent calculations of phase difference change rate and frequency difference.

[0062] This process is continuously executed by sliding along the phase difference sequence, updating the sliding fitting window each time with a new current sampling time, ensuring that a corresponding local fitting line can be generated at each time point, and providing real-time feedback on the short-term trend of phase difference changes.

[0063] The phase difference fitted value at the k-th sampling point is the predicted phase difference calculated by fitting a linear regression line to the k-th sampling point within a sliding fitting window. The linear regression line constructs a local trend model, and this fitted value is the output result of this line at the corresponding sampling point time position, which can accurately reflect the change pattern of the phase difference within a short time window.

[0064] The sliding window starts from the first sampling point, and the reference value is the phase difference at this starting point. The fitted value at the kth point is calculated based on this reference value and the fitting slope S.

[0065] The phase difference reference value corresponding to the starting point of the sliding fit window is the phase difference reference value corresponding to the first sampling point in the sliding fit window, which is the intercept of the fitted line at the starting point of the window. It represents the phase difference reference level at the beginning of the current window time period, and is used both to calculate the fitted values ​​of each sampling point within the window for linear fitting, and as a basic benchmark for subsequent predictive analysis or trend judgment.

[0066] The sampling period refers to the time interval between two adjacent sampling points when continuously acquiring signals; it is the reciprocal of the sampling frequency.

[0067] Step S104: Calculate the duration of the safety window based on the frequency difference data, predict the center of the safety window based on the phase difference change rate, and determine the safety window based on the duration of the safety window and the center of the safety window.

[0068] The safety window duration is the continuous time during which the output voltage phase difference between the current mobile battery compartment and the candidate mobile battery compartment remains within a preset safety phase threshold range, given the frequency difference. This duration is determined by both the frequency difference data and the safety phase threshold, reflecting the maximum time interval span allowed for battery compartment switching operations without excessive phase shift, and characterizing the permissible range of the switching operation in the time dimension.

[0069] The safety window center is determined by linearly fitting a real-time phase difference sequence to predict the moment when its future value will equal zero. This moment characterizes the point on the time axis where the AC output voltage waveforms of the two PCSs are about to synchronize, and serves as the time reference for calculating the entire safety switching window.

[0070] The safety window is a time interval defined on the time axis, with the center of the safety window as the time reference and the duration of the safety window as the width, that allows for the switching operation of the mobile battery compartment. Within this time interval, the phase difference of the output voltage of the two battery compartments meets the preset safety phase threshold requirement, and the risks of inrush current, arcing, or system instability during the switching process are all within a controllable range.

[0071] After acquiring the frequency difference data between the current mobile battery compartment and the candidate mobile battery compartment, this frequency difference is used as a rate constraint condition for the phase difference changing over time. Simultaneously, a preset safe phase threshold is introduced to limit the phase offset range allowed for switching operations. Specifically, the safe phase threshold is used to define the maximum allowable phase difference amplitude between the output voltages of the two battery compartments during the switching process. Its specific value needs to be preset based on the system's withstandable inrush current, arc risk, and the stability requirements of the parallel system.

[0072] Under conditions where the frequency difference remains constant or approximately constant for a short period, the phase difference exhibits a linear relationship with time, and the rate of change is directly determined by the frequency difference. Based on this linear relationship, the time required for the phase difference to change from a negative safety threshold to a positive safety threshold can be used as the total time span for allowing a handover operation, and the safety window duration can be calculated accordingly. This duration intuitively reflects the continuous duration for which the system can maintain the phase difference within a safe range under the current frequency difference conditions, providing a reliable timescale basis for planning subsequent handover sequences.

[0073] Using the phase difference value corresponding to the current sampling moment as the initial phase state, and combining it with the phase difference change rate, a linear extrapolation is performed along the time axis to predict the subsequent changes in the phase difference, progressively calculating the predicted phase difference values ​​for each future moment. When the extrapolation results show that the phase difference continuously decreases from the current value and reaches zero, the corresponding future moment is recorded. This moment is determined as the center of the safety window, used to indicate the position where the two voltages will reach phase synchronization in the future.

[0074] Based on the above principles, the center of the security window can be directly obtained using the following prediction formula: ; in, The center of the safety window is denoted by R, which represents the rate of change of phase difference. This formula is derived from the linear relationship Φ(t) = +R(t- Solving for Φ(t)=0 yields... ; where t is any physical time in the future (or past). It is a continuous variable representing the moment we want to predict; Φ(t) is the predicted phase difference of the output voltages of the two PCS units at the future time t. The unit is degrees (°). (Known parameters): The "current" reference time on which this prediction is based; (Known parameters): at the reference time The known value of the phase difference between the output voltages of the two PCS units.

[0075] The center of the security window should be selected based on the current time. The earliest possible synchronization moment in the future, based on this.

[0076] After obtaining the safe window duration and the safe window center, the time corresponding to the safe window center is used as the center point of the time axis. The safe window duration is then symmetrically expanded on both sides of the center point to define a continuous time interval on the time axis. The start time of this interval is half a safe window duration backward from the safe window center, and the end time is half a safe window duration forward from the safe window center.

[0077] Within this defined time interval, the phase difference remains within a preset safe phase threshold range, effectively reducing the risk of inrush current, arcing, and system instability during the switching process. This time interval is the safety window, used to clearly define the permissible execution time range for battery compartment switching operations.

[0078] Based on the above technical solution, optionally, the duration of the safety window can be calculated based on frequency difference data, including: The duration of the safety window is calculated based on frequency difference data; the calculation process is as follows: ; in, For the duration of the safety window; The preset phase difference threshold is used; This is frequency difference data.

[0079] In this solution, the preset phase difference threshold is a maximum allowable phase difference set in the system, used to determine whether the synchronization between two voltage sources or two mobile battery compartments is within a safe range. For example, during mobile battery compartment switching or grid connection operations, if the phase difference between the two power sources is less than or equal to the threshold, the switching or parallel operation is considered safe; if it exceeds the threshold, it may cause current surges or equipment damage, requiring a delay in switching or adjustment operations.

[0080] Step S105: Send a disconnect command to the first contactor of the current mobile battery compartment within the safety window, obtain the first effective value of the first load current and the first power factor angle of the current mobile battery compartment, and calculate the dead time based on the first effective value of the load current, the first power factor angle and the preset dead time calculation formula.

[0081] The first contactor is an electrical isolation and switching actuator installed between the current mobile battery compartment and the external load or AC bus, used to control the electrical connection status between the current mobile battery compartment and the load side. During normal power supply, the first contactor is in the closed state; during battery compartment switching, a disconnection operation is performed to achieve electrical isolation between the current mobile battery compartment and the load side.

[0082] The disconnection command is a control command issued to the first contactor. Its purpose is to drive the first contactor from the closed state to the open state, thereby cutting off the electrical connection between the currently moving battery compartment and the load side. The disconnection command usually includes a trigger time and action confirmation requirements to ensure that the contactor completes reliable disconnection within the expected time.

[0083] The first effective value of the load current is the root mean square value of the current obtained by measuring and calculating the AC current output from the current mobile battery compartment to the load before the first contactor disconnects. It is used to characterize the actual load current level carried by the current mobile battery compartment at the instant before switching.

[0084] The first power factor angle is the phase angle between the AC voltage and AC current output by the current mobile battery compartment before the first contactor disconnects. It is used to characterize the power factor characteristics of the load and the phase relationship between voltage and current.

[0085] Dead time is the time interval reserved between the first contactor completing its disconnection and the current moving battery compartment achieving electrical isolation from the load side, and before the candidate moving battery compartment contactor is allowed to perform a closing operation. Its function is to ensure that the arc is completely extinguished, the residual voltage is sufficiently decayed, and the system reaches transient stability.

[0086] Within the defined safety window, the current system operating status is first time-aligned, mapping the start, center, and end times of the safety window onto the control clock axis. Then, one or more control sampling times near the center of the safety window are selected as the execution times for the contactor operation. Before the selected execution time arrives, the current electrical connection between the mobile battery compartment and the load side is continuously maintained to ensure the continuity of power supply to the load.

[0087] When the control clock reaches the execution time, a disconnection control signal is sent to the first contactor corresponding to the current mobile battery compartment. This control signal drives the first contactor to change from a closed state to an open state. Within a preset short time interval before the disconnection control signal is sent, the output electrical parameters of the current mobile battery compartment are synchronously sampled to obtain the load characteristics at the moment of switching. Specifically, the instantaneous value of AC current collected by the current measuring device arranged in the output circuit of the current mobile battery compartment is continuously sampled. Within one complete power frequency cycle or multiple consecutive power frequency cycles, the root mean square (RMS) value of the instantaneous current is calculated to obtain the first effective value of the load current characterizing the load scale before switching.

[0088] Within the same sampling time interval, the AC voltage and AC current signals output by the current mobile battery compartment are simultaneously acquired, and their phase relationship is calculated. By extracting the fundamental component phases of the voltage and current, the angle between the voltage and current phases is determined, thus obtaining the first power factor angle, which reflects the load power factor characteristics. This first power factor angle is used to characterize the inductive or capacitive characteristics of the load at the moment of switching, providing a basis for the safe control of subsequent switching timing. After obtaining the first effective value of the load current and the first power factor angle, these two parameters are used as inputs and substituted into a pre-set calculation formula to obtain the dead time.

[0089] Based on the above technical solution, the optional preset dead time calculation formula includes: ; in, Dead time; To preset the basic arc extinguishing time; The preset current influence coefficient; This is the effective value of the first load current; This is the preset power factor influence coefficient; This is the first power factor angle.

[0090] In this scheme, the preset basic arc extinguishing time is the shortest time interval set to ensure that the generated arc is completely extinguished when switching the mobile battery compartment contactor.

[0091] The preset current influence coefficient is used to quantify the impact of load current on switching safety and dead time, accurately reflecting the potential impact and risk level of current changes on the switching process.

[0092] The preset power factor influence coefficient is used to characterize the effect of the inductive or capacitive properties of the load on switching safety and dead time.

[0093] Based on the above technical solution, optionally, after issuing a closing command to the second contactor of the candidate mobile battery compartment, the method further includes: Acquire the arc characteristic data of the current mobile battery compartment and the candidate mobile battery compartment at the moment of switching, and acquire the second effective value of the load current and the second power factor angle of the candidate mobile battery compartment after the switching is completed. Generate a load current characteristic record based on the first effective value of the load current and the second effective value of the load current. Power factor feature records are generated based on the first power factor angle and the second power factor angle; A switching feature dataset is generated based on load current characteristic records, power factor characteristic records, dead time, and arc characteristic data. The switching feature dataset, preset current influence coefficient, and preset power factor influence coefficient are input into the preset coefficient update model to update the preset current influence coefficient and preset power factor influence coefficient.

[0094] In this solution, the arc characteristic data is the arc-related characteristic data generated at the moment of switching of the mobile battery compartment, which covers the arc duration, current spike, energy release and fluctuation.

[0095] The second load current RMS value is the AC current RMS value when the candidate mobile battery compartment takes over the load after the switch is completed. It directly reflects the actual current scale of the load undertaken by the battery compartment after the switch.

[0096] The second power factor angle is the power factor angle when the candidate mobile battery compartment takes over the load after the switch is completed, which characterizes the phase relationship between the voltage and current of the load powered by the battery compartment.

[0097] Load current characteristic records are data records generated based on the effective values ​​of load current before and after switching, clearly showing the current changes during the switching process and their impact on the system.

[0098] The power factor characteristic record is a data record generated based on the power factor angle before and after the switching, reflecting the change in load characteristics and its impact on system switching.

[0099] The switching feature dataset is a comprehensive dataset that integrates load current feature records, power factor feature records, arc feature data, and dead time to fully characterize the dynamic impact of a single switching operation on the mobile battery compartment and the entire system.

[0100] The preset coefficient update model combines the switching feature dataset, preset current influence coefficient, and preset power factor influence coefficient for calculation and analysis, and dynamically updates the current and power factor influence coefficients.

[0101] During the switching process of the mobile battery compartment, the electrical output status of the current mobile battery compartment and the candidate mobile battery compartment is first monitored in real time. When the switching operation is about to start, the output terminals of the two battery compartments are sampled at high speed to capture the arc characteristics that may occur at the moment of switching, including transient current spikes, arc duration, and related energy fluctuations. By performing signal processing and feature extraction on these transient voltage and current signals, arc feature data is generated to reflect the impact of the switching moment on the system's safety and stability.

[0102] After the switchover is complete, the candidate mobile battery compartment officially takes over the load. At this point, its AC output current is measured in real time, and the effective value of the second load current is calculated. Simultaneously, the corresponding second power factor angle is obtained to reflect the battery compartment's power supply characteristics and load matching status after taking over the load. Subsequently, the effective value of the first load current before the switchover is compared and integrated with the effective value of the second load current after the switchover to generate a load current characteristic record, clearly depicting the current change trend and switching impact characteristics. Similarly, the first power factor angle and the second power factor angle are integrated to generate a power factor characteristic record, reflecting the load characteristics and changes in voltage and current phase.

[0103] Load current characteristic records, power factor characteristic records, arc characteristic data, and preset dead time are integrated to form a complete switching characteristic dataset. By unifying time series and event markers, the dynamic changes during the switching process are comprehensively characterized, forming a standardized dataset that can be used for subsequent analysis. Based on the preset coefficient update model, the switching characteristic dataset is analyzed and compared with existing preset current influence coefficients and preset power factor influence coefficients, and the current influence coefficients and power factor influence coefficients are updated accordingly.

[0104] The training process for the model with preset coefficients is as follows: The training process of the preset coefficient update model is based on historical switching data. First, complete records of the historical switching process are collected, covering arc characteristic data, the first effective value of the load current, the first power factor angle, the second effective value of the load current, the second power factor angle, dead time, and the corresponding preset current influence coefficient and preset power factor influence coefficient. Based on this, a training dataset is constructed. The input features of each data record consist of the load current, power factor, and arc characteristic data before and after the switching, while the labels are the preset current influence coefficient and preset power factor influence coefficient, which have been verified under the historical switching conditions.

[0105] The training data is then cleaned, standardized, and time-series aligned to ensure accurate correspondence between input features and labels at the moment of switching. Statistical regression or machine learning methods are then used to iteratively fit the training data, optimizing model parameters. This enables the model to predict the optimal current and power factor influence coefficients based on input load current characteristics, power factor characteristics, arc characteristics, and dead time. Once the model is trained, the preset current and power factor influence coefficients can be dynamically updated during subsequent real-time switching based on the real-time feature data of the current and candidate mobile battery compartments.

[0106] In this solution, dynamic updates can adjust the current and power factor coefficients based on real-time switching characteristics, improving the adaptability and safety of switching between mobile battery compartments; at the same time, it can reduce energy fluctuations and system disturbances caused by fixed coefficients, and improve the overall power supply stability.

[0107] Step S106: Maintain electrical isolation between the current mobile battery compartment and the load side during the dead time, and after the dead time ends, issue a closing command to the second contactor of the candidate mobile battery compartment to make the candidate mobile battery compartment a power source and realize continuous power supply to the load.

[0108] The load side is the electrical node or network located downstream of the mobile battery compartment's power supply circuit, where the electrical object receives and consumes electrical energy. It encompasses various power-related carriers such as electrical equipment, electrical systems, and distribution busbars electrically connected to the equipment. During battery compartment switching, the load side acts as the power supply object, and its electrical state is directly affected by the power supply switching behavior.

[0109] The second contactor is a controllable electrical connection device installed between the candidate mobile battery compartment and the load side, specifically used to control the electrical connection and disconnection between the candidate mobile battery compartment and the load side.

[0110] The closing command is a control signal used to switch the second contactor from the open state to the on state. Its function is to drive the second contactor to perform a closing action, thereby establishing an electrical connection between the candidate mobile battery compartment and the load side. This closing command is issued after the dead time has ended, enabling a smooth power supply switchover provided that the switching conditions are met.

[0111] After determining that a battery compartment switching operation is necessary, the electrical connection between the current mobile battery compartment and the load side is first controlled and disconnected according to a preset switching sequence. When the switching action is initiated, a disconnection control signal is sent to the first contactor corresponding to the current mobile battery compartment, driving the first contactor to switch from a conducting state to an open state, thereby cutting off the electrical path between the current mobile battery compartment and the load side. The open state of the first contactor needs to be confirmed by a feedback signal from its auxiliary contact to ensure that the current mobile battery compartment has achieved reliable electrical isolation from the load side. After confirming that the first contactor has completed disconnection, the system starts timing and enters a dead time interval.

[0112] During the dead time, the system maintains both the first and second contactors in an open state, keeping the load side in a passive power supply state and preventing the two mobile battery compartments from forming a parallel circuit or generating a reverse impact during the switching instant. During this period, the system combines the first effective value of the load current and the first power factor angle acquired before the switching, and calculates the dead time based on a preset dead time relationship to precisely control the dead time duration, ensuring that residual current fully decays and arc risk is completely released during the switching process, while also completely eliminating system transient oscillations. The dead time timing reference is provided by the system's internal time base and remains stable throughout the entire dead time interval, ensuring the accuracy of dead time execution.

[0113] When the dead timer expires, the system determines that the switching conditions have been met and immediately sends a closing control signal to the second contactor corresponding to the candidate mobile battery compartment. This drives the second contactor to switch from the open state to the closed state, establishing an electrical connection between the candidate mobile battery compartment and the load side. As the second contactor closes, the candidate mobile battery compartment begins to output power to the load side, gradually taking over the load power supply task. This completes the entire power supply switch from the current mobile battery compartment to the candidate mobile battery compartment. Because a dead time is set during the switching process, ensuring electrical isolation between the current mobile battery compartment and the load side, and simultaneously monitoring the phase difference and frequency difference in real time, precise closing timing control is achieved. The candidate mobile battery compartment can seamlessly take over the load power supply at the moment of closing, thus ensuring that the load continuously receives power throughout the entire switching process without interruption, achieving continuous power supply.

[0114] Based on steps S101-S106 above, by predicting the phase difference and frequency difference and calculating the safety window, the battery compartment is switched at a safe moment to ensure continuous power supply to the load, while reducing switching disturbances and energy consumption, and improving system stability. Furthermore, without relying on inter-device communication and synchronization functions, the upper-level control performs real-time monitoring and coordinated control of the two independent voltage sources, achieving millisecond-level seamless switching.

[0115] See appendix Figure 2 , Figure 2 This is a schematic flowchart of the second main step of a continuous power supply method for a mobile battery compartment based on voltage phase prediction according to an embodiment of the present invention. Figure 2 As shown, a method for continuous power supply of a mobile battery compartment based on voltage phase prediction in an embodiment of the present invention mainly includes the following steps S201-S210.

[0116] Step S201: Obtain the first operating state of the current mobile battery compartment and the second operating state of the candidate mobile battery compartment. Based on the first operating state and the second operating state, quantify the potential switching process of the mobile battery compartment to obtain various benefit indicators of the potential switching on the improvement of the operating performance of the mobile battery compartment.

[0117] The benefit indicators are specific values ​​obtained by quantifying the improvement in operational performance of the potential switching of the mobile battery compartment based on the first and second operating states. They are used to characterize the degree of improvement in energy supply capacity, system stability, and health consumption after the switch.

[0118] Step S202: Based on the weighted processing of each benefit indicator, obtain the switching benefit assessment value of the potential switching to improve the operating performance of the mobile battery compartment.

[0119] The switching benefit assessment value is a single quantitative value obtained by weighting multiple benefit indicators, and is used to comprehensively reflect the overall positive utility of the potential switching on the operational performance of the mobile battery compartment.

[0120] Step S203: Based on the first operating state and the second operating state, the potential switching process of the mobile battery compartment is deduced to obtain switching characteristic data characterizing the potential switching process of the mobile battery compartment.

[0121] The switching characteristic data is a set of values ​​obtained by extrapolating the potential battery compartment switching process based on the first and second operating states. It is used to characterize process characteristics such as time, load changes, energy consumption, and system disturbances during the switching process.

[0122] Step S204: Based on the handover feature data, perform quantitative analysis on the potential handover process impact represented in the handover feature data to obtain the corresponding handover cost assessment value.

[0123] The handover cost assessment value is a numerical value obtained by quantifying and analyzing potential handover influencing factors such as energy loss, time cost, and system disturbance risk reflected in the handover characteristic data. It is used to assess the cost required to perform the handover.

[0124] Step S205: Based on the switching benefit assessment value and the switching cost assessment value, a quantitative comparison is performed to obtain the switching judgment result.

[0125] Step S206: If the switching judgment result indicates that switching is required, continuously acquire the first voltage signal connected to the AC output terminal of the PCS connected to the current mobile battery compartment and the second voltage signal connected to the AC output terminal of the PCS connected to the candidate mobile battery compartment at a preset sampling frequency, and generate a phase difference sequence based on the continuously acquired first voltage signal and second voltage signal.

[0126] Step S207: Perform short-time trend fitting based on the phase difference sequence to predict the phase difference change trend, obtain the phase difference change rate, and calculate the frequency difference data between the current mobile battery compartment and the candidate mobile battery compartment based on the phase difference change rate.

[0127] Step S208: Calculate the duration of the safety window based on the frequency difference data, predict the center of the safety window based on the phase difference change rate, and determine the safety window based on the duration of the safety window and the center of the safety window.

[0128] Step S209: Send a disconnect command to the first contactor of the current mobile battery compartment within the safety window, obtain the first effective value of the first load current and the first power factor angle of the current mobile battery compartment, and calculate the dead time based on the first effective value of the load current, the first power factor angle and the preset dead time calculation formula.

[0129] Step S210: Maintain electrical isolation between the current mobile battery compartment and the load side during the dead time, and after the dead time ends, issue a closing command to the second contactor of the candidate mobile battery compartment to make the candidate mobile battery compartment a power source and realize continuous power supply to the load.

[0130] In this embodiment, the energy supply capacity and system response of the battery compartments before and after a potential switchover are numerically calculated by combining the current operating status of the mobile battery compartments, including output power, load matching, and operational stability, as well as the available capacity, health status, and access feasibility of candidate mobile battery compartments. By extrapolating the output power change trend when the second mobile battery compartment takes over the load after the switchover, the improvement in system load adaptability is calculated, yielding the first benefit indicator. Combining the differences in sustainable energy supply capacity between the two battery compartments, the change in continuous power supply time after the switchover is simulated, yielding the second benefit indicator. Furthermore, based on the current health consumption status of the first mobile battery compartment and the health status of the second mobile battery compartment, the trend of health loss reduction in the first mobile battery compartment due to load release after the switchover is extrapolated, yielding the third benefit indicator. The above process relies on numerical extrapolation driven by sampled data, linear or nonlinear trend calculations, and prediction algorithms based on historical performance data to generate various benefit indicators, forming a dataset reflecting the positive utility of the potential switchover.

[0131] After obtaining multiple benefit indicators, each indicator is weighted according to preset weights, and indicators such as improved energy supply capacity, extended sustainable energy supply time, and reduced health consumption are uniformly quantified into a single switchover benefit assessment value. In this process, each benefit indicator is converted into a comparable value through standardization, and then the comprehensive utility value is calculated using linear or nonlinear weighting formulas. Finally, the overall positive utility quantification result of the potential switchover's improvement on the operational performance of the mobile battery compartment is obtained.

[0132] Based on the current and candidate mobile battery compartment operating status, a time-series simulation of the potential switching process is conducted. Specifically, relying on real-time collected data on current, voltage, load distribution, and battery compartment health status, the simulation addresses instantaneous current changes, load redistribution processes, system response delays, and potential energy fluctuations during the switching operation. By recording the current, power flow, and system stability indicators at each time point, a complete sequence of switching characteristic data is formed, realistically reflecting the impact of the switching process on the system's dynamic behavior.

[0133] After obtaining the switching characteristic data, the impact of each recorded dynamic indicator, including current fluctuation amplitude, load distribution change, system response delay, and control operation step complexity, is calculated. For example, energy loss is obtained by integrating the current fluctuation at each time point, the operation delay is obtained by accumulating the load adjustment time, the deviation of the system response curve is quantified to obtain the stability disturbance index, and the number of control operation steps is counted to reflect the operation complexity.

[0134] Various quantitative indicators are weighted and summed or weighted averaged according to preset weights to obtain a comprehensive value, namely the switching cost assessment value, which represents the overall cost required to perform the potential switching. Simultaneously, historical switching experience data can be used to correct the weights or quantitative results of each indicator, improving the predictive accuracy and reliability of the switching cost assessment value. The switching benefit assessment value is compared with the switching cost assessment value to calculate the net benefit of the potential switching. When the switching benefit reaches or exceeds the cost, a switching is initiated, and the candidate mobile battery compartment takes over power supply; if the benefit is insufficient to cover the cost, the current battery compartment power supply status is maintained.

[0135] Based on the above steps S201-S210, by quantitatively analyzing the benefits and costs of potential switching, the switching decision-making is made more scientific and precise, improving the reliability and stability of the system's power supply, while reducing unnecessary energy loss and operational risks.

[0136] It should be noted that although the steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effects of the present invention, different steps do not necessarily have to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders, and these variations are all within the scope of protection of the present invention.

[0137] Furthermore, the present invention also provides a continuous power supply system for a mobile battery compartment based on voltage phase prediction.

[0138] See appendix Figure 3 , Figure 3 This is a main structural block diagram of a mobile battery compartment continuous power supply system based on voltage phase prediction according to an embodiment of the present invention. Figure 3 As shown, it specifically includes:

[0139] Evaluation module 301 is used to obtain the first operating state of the current mobile battery compartment and the second operating state of the candidate mobile battery compartment, and to evaluate the switching utility based on the first operating state and the second operating state to obtain the switching judgment result. The phase difference sequence generation module 302 is used to continuously acquire the first voltage signal connected to the AC output terminal of the PCS connected to the current mobile battery compartment and the second voltage signal connected to the AC output terminal of the PCS connected to the candidate mobile battery compartment at a preset sampling frequency if the switching judgment result is that switching is required, and generate a phase difference sequence based on the continuously acquired first voltage signal and second voltage signal. The prediction module 303 is used to perform short-term trend fitting based on the phase difference sequence to predict the phase difference change trend, obtain the phase difference change rate, and calculate the frequency difference data between the current mobile battery compartment and the candidate mobile battery compartment based on the phase difference change rate. The safety window determination module 304 is used to calculate the duration of the safety window based on the frequency difference data, predict the center of the safety window based on the phase difference change rate, and determine the safety window based on the duration of the safety window and the center of the safety window. The dead time calculation module 305 is used to send a disconnection command to the first contactor of the current mobile battery compartment within the safety window, obtain the first effective value of the first load current and the first power factor angle of the current mobile battery compartment, and calculate the dead time based on the first effective value of the load current, the first power factor angle and the preset dead time calculation formula. The switching module 306 is used to maintain electrical isolation between the current mobile battery compartment and the load side during the dead time, and after the dead time ends, it sends a closing command to the second contactor of the candidate mobile battery compartment, so that the candidate mobile battery compartment becomes a power source and realizes continuous power supply to the load.

[0140] The mobile battery compartment continuous power supply system based on voltage phase prediction provided in this application embodiment can achieve... Figure 1 The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0141] Those skilled in the art will understand that all or part of the processes in the method of the above embodiment of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable storage medium can include any entity or device capable of carrying the computer program code, a medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the content included in the computer-readable storage medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable storage medium does not include electrical carrier signals and telecommunication signals.

[0142] Furthermore, the present invention also provides an electronic device 400, including a processor 401, a memory 402, and a program or instructions stored in the memory 402 and executable on the processor 401. When the program or instructions are executed by the processor 401, they implement the various processes of the above-described embodiment of a method for continuous power supply of a mobile battery compartment based on voltage phase prediction and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0143] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0144] Furthermore, the present invention also provides a computer-readable storage medium. In one embodiment of the computer-readable storage medium according to the present invention, the computer-readable storage medium can be configured to store a program for executing a continuous power supply method for a mobile battery compartment based on voltage phase prediction according to the above-described method embodiments. This program can be loaded and run by a processor to implement the above-described continuous power supply method for a mobile battery compartment based on voltage phase prediction. For ease of explanation, only the parts related to the embodiments of the present invention are shown; for specific technical details not disclosed, please refer to the method section of the embodiments of the present invention. The computer-readable storage medium can be a storage device comprising various electronic devices. Optionally, in the embodiments of the present invention, the computer-readable storage medium is a non-transitory computer-readable storage medium.

[0145] Furthermore, it should be understood that since the various modules are only provided to illustrate the functional units of the device of the present invention, the physical devices corresponding to these modules may be the processor itself, or a part of the processor's software, hardware, or a combination of software and hardware. Therefore, the number of modules shown in the figures is merely illustrative.

[0146] Those skilled in the art will understand that the various modules in the device can be adaptively split or combined. Such splitting or combining of specific modules will not cause the technical solution to deviate from the principles of the present invention; therefore, the technical solutions after splitting or combining will fall within the protection scope of the present invention.

[0147] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for continuous power supply to a mobile battery compartment based on voltage phase prediction, characterized in that, The method includes: The first operating state of the current mobile battery compartment and the second operating state of the candidate mobile battery compartment are obtained. Based on the first operating state and the second operating state, the switching utility is evaluated to obtain the switching judgment result. If the switching judgment result indicates that switching is required, the first voltage signal connected to the AC output terminal of the PCS connected to the current mobile battery compartment and the second voltage signal connected to the AC output terminal of the PCS connected to the candidate mobile battery compartment are continuously acquired at a preset sampling frequency, and a phase difference sequence is generated based on the continuously acquired first voltage signal and second voltage signal. Short-term trend fitting is performed based on the phase difference sequence to predict the phase difference change trend, obtain the phase difference change rate, and calculate the frequency difference data between the current mobile battery compartment and the candidate mobile battery compartment based on the phase difference change rate. The duration of the safety window is calculated based on frequency difference data, and the center of the safety window is predicted based on the rate of change of phase difference. The safety window is then determined based on the duration and center of the safety window. Send a disconnect command to the first contactor of the current mobile battery compartment within the safety window, obtain the first effective value of the first load current and the first power factor angle of the current mobile battery compartment, and calculate the dead time based on the first effective value of the load current, the first power factor angle and the preset dead time calculation formula. During the dead time, maintain electrical isolation between the current mobile battery compartment and the load side, and after the dead time ends, issue a closing command to the second contactor of the candidate mobile battery compartment to make the candidate mobile battery compartment a power source and realize continuous power supply to the load.

2. The method for continuous power supply of a mobile battery compartment based on voltage phase prediction according to claim 1, characterized in that, in, Based on the first and second operating states, a handover utility evaluation is performed to obtain a handover judgment result, including: Based on the first and second operating states, the potential switching process of the mobile battery compartment is quantified to obtain various benefit indicators of the potential switching on the improvement of the mobile battery compartment's operating performance. We obtain the switching benefit assessment value for the potential improvement of the mobile battery compartment's operational performance by weighting the various benefit indicators. Based on the first and second operating states, the potential switching process of the mobile battery compartment is deduced to obtain switching characteristic data characterizing the potential switching process of the mobile battery compartment. Based on the handover feature data, the potential handover process impact represented in the handover feature data is quantitatively analyzed to obtain the corresponding handover cost assessment value. A quantitative comparison is made based on the switching benefit assessment value and the switching cost assessment value to obtain the switching judgment result.

3. The method for continuous power supply of a mobile battery compartment based on voltage phase prediction according to claim 1, characterized in that, in, A phase difference sequence is generated based on the continuously acquired first and second voltage signals, including: Based on the continuously acquired first voltage signal and second voltage signal, a first voltage instantaneous value sequence and a second voltage instantaneous value sequence are generated; The first voltage instantaneous value sequence and the second voltage instantaneous value sequence are subjected to digital low-pass filtering to obtain the first voltage smoothed sequence and the second voltage smoothed sequence; The first voltage smoothing sequence and the second voltage smoothing sequence are subjected to sliding window Fourier transform to obtain the first fundamental phase and the second fundamental phase, respectively. The phase difference sequence is generated by subtracting the first fundamental phase sequence from the second fundamental phase sequence.

4. The method for continuous power supply of a mobile battery compartment based on voltage phase prediction according to claim 1, characterized in that, in, Short-time trend fitting is performed based on the phase difference sequence to predict the phase difference change trend, and the phase difference change rate is obtained, including: In the phase difference sequence, a sliding fitting window containing a preset number of sampling points is constructed based on the current sampling time, and linear regression fitting is performed on the sampling points within the sliding fitting window to obtain a fitted straight line; wherein, the equation of the fitted straight line is: ； in, represents the phase difference fitted value of the kth sampling point; k is the sampling point number within the sliding fitting window. This is the baseline value of the phase difference corresponding to the starting point of the sliding fitting window; The fitting slope is used to represent the trend of phase difference as a function of sampling points; The sampling period is determined based on a preset sampling frequency, and the phase difference change rate is calculated based on the fitting slope and the sampling period; the calculation process is as follows: ； in, The rate of change of phase difference; The slope is the fitted slope; The preset sampling period; The frequency difference between the current mobile battery compartment and the candidate mobile battery compartment is calculated based on the phase difference change rate; the calculation process is as follows: ； in, This is frequency difference data; This represents the rate of change of phase difference.

5. A method for continuous power supply of a mobile battery compartment based on voltage phase prediction according to claim 1, characterized in that, in, The duration of the safety window is calculated based on frequency difference data, including: The duration of the safety window is calculated based on frequency difference data; the calculation process is as follows: ； in, For the duration of the safety window; The preset phase difference threshold is used; This is frequency difference data.

6. A method for continuous power supply of a mobile battery compartment based on voltage phase prediction according to claim 1, characterized in that, in, The preset dead time calculation formula includes: ； in, Dead time; To preset the basic arc extinguishing time; The preset current influence coefficient; This is the effective value of the first load current; This is the preset power factor influence coefficient; This is the first power factor angle.

7. A method for continuous power supply of a mobile battery compartment based on voltage phase prediction according to claim 6, characterized in that, in, After issuing a closing command to the second contactor of the candidate mobile battery compartment, the method further includes: Acquire the arc characteristic data of the current mobile battery compartment and the candidate mobile battery compartment at the moment of switching, and acquire the second effective value of the load current and the second power factor angle of the candidate mobile battery compartment after the switching is completed. Generate a load current characteristic record based on the first effective value of the load current and the second effective value of the load current. Power factor feature records are generated based on the first power factor angle and the second power factor angle; A switching feature dataset is generated based on load current characteristic records, power factor characteristic records, dead time, and arc characteristic data. The switching feature dataset, preset current influence coefficient, and preset power factor influence coefficient are input into the preset coefficient update model to update the preset current influence coefficient and preset power factor influence coefficient.

8. A continuous power supply system for a mobile battery compartment based on voltage phase prediction, characterized in that, The system includes: The evaluation module is used to obtain the first operating state of the current mobile battery compartment and the second operating state of the candidate mobile battery compartment, and to evaluate the switching utility based on the first operating state and the second operating state to obtain the switching judgment result. The phase difference sequence generation module is used to continuously acquire the first voltage signal connected to the AC output terminal of the PCS connected to the current mobile battery compartment and the second voltage signal connected to the AC output terminal of the PCS connected to the candidate mobile battery compartment at a preset sampling frequency if the switching judgment result is that switching is required, and generate a phase difference sequence based on the continuously acquired first voltage signal and second voltage signal. The prediction module is used to perform short-term trend fitting based on the phase difference sequence to predict the phase difference change trend, obtain the phase difference change rate, and calculate the frequency difference data between the current mobile battery compartment and the candidate mobile battery compartment based on the phase difference change rate. The safety window determination module is used to calculate the duration of the safety window based on frequency difference data, predict the center of the safety window based on the phase difference change rate, and determine the safety window based on the duration and center of the safety window. The dead time calculation module is used to send a disconnection command to the first contactor of the current mobile battery compartment within the safety window, obtain the first effective value of the first load current and the first power factor angle of the current mobile battery compartment, and calculate the dead time based on the first effective value of the load current, the first power factor angle and the preset dead time calculation formula. The switching module is used to maintain electrical isolation between the current mobile battery compartment and the load side during the dead time, and after the dead time ends, it sends a closing command to the second contactor of the candidate mobile battery compartment, so that the candidate mobile battery compartment becomes the power supply and realizes continuous power supply to the load.

9. An electronic device comprising a processor, a memory, and a program or instructions stored in the memory and executable on the processor, characterized in that, The program or instructions are adapted to be loaded and run by the processor to perform a method for continuous power supply of a mobile battery compartment based on voltage phase prediction, as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a plurality of program codes, characterized in that, The program code is adapted to be loaded and run by a processor to perform a method for continuous power supply of a mobile battery compartment based on voltage phase prediction, as described in any one of claims 1 to 7.

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