Electric drive platform BMS intelligent battery management control method and system

Abstract

According to the electric drive platform BMS intelligent battery management control method and system, communication lines related to a CAN bus in an electric drive platform are accurately recognized and analyzed, high-speed and high-bandwidth communication lines are calculated and marked according to the requirements of a BMS intelligent battery management system, and the electric drive platform BMS intelligent battery management control system is obtained through real-time measurement and waveform distortion analysis. The communication signal integrity and tolerance of the lines are evaluated, electromagnetic shielding is added to the high-sensitivity line according to the evaluation result, and finally, the evaluation frequency and the energy management strategy of the battery health state are dynamically adjusted by performing evaluation feedback on the data transmission accuracy after shielding. It is ensured that the BMS can stably and reliably operate in a complex electromagnetic environment, the service life of the battery is prolonged, system safety is improved, and the overall performance of the electric drive platform is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent battery management, and in particular to a BMS intelligent battery management control method and system for an electric drive platform. Background Art

[0002] A BMS (Battery Management System) is a technology specifically designed to monitor and control battery pack performance. It precisely measures battery voltage, current, temperature, and other parameters to ensure each cell operates within a safe range. The BMS intelligent battery management system communicates with other control systems via the electric drive platform's CAN bus, coordinating with the vehicle's entire operation. It provides data to users and higher-level systems to ensure the battery pack remains synchronized with the overall vehicle's operation.

[0003] However, since the high-power components of the electric drive platform (such as electric motors and inverters) will generate strong electromagnetic interference during operation, this interference may affect the communication of the CAN bus under certain specific frequencies and conditions; and if the sensitivity of the communication line is too high, it may easily cause hidden communication errors, which may cause occasional errors in the battery data transmitted by the BMS, such as slight deviations in voltage or temperature; such deviations may not immediately cause system alarms or failures, but will accumulate and affect the battery's health status assessment and energy management decisions, and in the long run may cause abnormal aging or sudden failure of the battery. Summary of the Invention

[0004] The present disclosure provides a BMS intelligent battery management control method and system for an electric drive platform to address the above-mentioned deficiencies.

[0005] The electric drive platform BMS intelligent battery management control method provided in the present disclosure mainly includes the following steps:

[0006] S1: Identify all CAN bus-related communication lines in the electric drive platform, calculate the data rate and bandwidth requirements of each communication line based on the communication requirements of the BMS intelligent battery management system, and mark high-speed and high-bandwidth communication lines;

[0007] S2: For the marked communication lines, perform real-time measurements on the communication signals in the lines, determine the waveform distortion of the signals under different working conditions, and evaluate the integrity of the communication signals on the lines;

[0008] S3: Monitor the electromagnetic interference data generated by the high-power components of the electric drive platform during operation, analyze the frequency of changes in the communication error rate of the marked communication lines under different interference intensities and frequencies, and evaluate the line's tolerance under various interference conditions;

[0009] S4: Evaluate the sensitivity of the marked communication line based on the integrity of the communication signal and its tolerance under various interference conditions;

[0010] S5, marking highly sensitive communication lines based on the evaluation result of step S4;

[0011] S6: Add electromagnetic shielding to highly sensitive communication lines, evaluate and provide feedback on the accuracy of BMS battery data transmitted through the communication lines after adding electromagnetic shielding, and dynamically adjust the battery health status assessment time and energy management decisions based on the feedback results.

[0012] The BMS intelligent battery management control system for an electric drive platform using the above method mainly includes: a communication management module, a signal monitoring module, an electromagnetic interference analysis module, a sensitivity assessment module, a sensitivity classification module, and a control management module; wherein:

[0013] Communication management module: used to identify all CAN bus-related communication lines in the electric drive platform, calculate the data rate and bandwidth requirements of each communication line according to the communication needs of the BMS intelligent battery management system, and mark high-speed and high-bandwidth communication lines;

[0014] Signal monitoring module: used to measure the communication signal of the marked communication line in real time, determine the waveform distortion of the signal under different working conditions, and evaluate the integrity of the communication signal of the marked communication line;

[0015] Electromagnetic Interference Analysis Module: This module is used to monitor the electromagnetic interference data generated by the high-power components of the electric drive platform during operation, analyze the frequency of changes in the communication error rate of the tag communication line under different interference intensities and frequencies, and evaluate the tolerance of the tag communication line under various interference conditions;

[0016] Sensitivity assessment module: used to assess the sensitivity of the marked communication lines based on the integrity of the communication signals and their tolerance under various interference conditions; based on the assessment results, highly sensitive communication lines are marked;

[0017] Control and management module: After adding electromagnetic shielding to highly sensitive communication lines, it is used to evaluate and provide feedback on the accuracy of BMS battery data transmitted through the electromagnetic shielded communication lines, and dynamically adjust the battery health status assessment time and energy management decisions based on the feedback results.

[0018] Compared with the existing technology, the beneficial effects of the present invention are: 1. By comprehensively identifying and analyzing the communication lines related to the CAN bus in the electric drive platform, combined with the needs of the BMS intelligent battery management system, high-speed and high-bandwidth communication lines are marked, and through signal measurement and electromagnetic interference monitoring, the signal integrity and interference tolerance of these lines under different working conditions are deeply evaluated; 2. By adding electromagnetic shielding to highly sensitive communication lines, and combining real-time data analysis and feedback mechanisms, the assessment frequency of the battery health status and energy management decisions are dynamically adjusted to ensure the stability and reliability of the system in a complex electromagnetic environment; 3. The anti-interference ability of the communication line is effectively improved, the impact of hidden communication errors on BMS transmission data is reduced, and abnormal battery aging or failure caused by the accumulation of small data deviations is avoided; 4. Precise control and optimization of the battery management system is achieved, which extends the battery life and ensures the safety and performance of the entire vehicle, while reducing the overall load of the system and improving the efficiency of energy management. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and other objects, features and advantages of the present disclosure will become more apparent through a more detailed description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present disclosure.

[0020] Figure 1 is a flow chart of a method according to an exemplary embodiment;

[0021] Figure 2 is a system module diagram according to an exemplary embodiment. DETAILED DESCRIPTION

[0022] The preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although preferred embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0023] The present disclosure provides a BMS intelligent battery management control method and system for an electric drive platform. In an exemplary embodiment, the battery management control method according to the present disclosure is as shown in the attached Figure 1 As shown, the following steps are included:

[0024] 1: Identify all CAN bus-related communication lines in the electric drive platform, calculate the data rate and bandwidth requirements of each communication line based on the communication requirements of the BMS intelligent battery management system, and mark high-speed and high-bandwidth communication lines;

[0025] 2: For the marked communication lines, use a signal analyzer to measure the communication signals of the marked communication lines in real time, determine the waveform distortion of the communication signals under different working conditions, and evaluate the integrity of the communication signals of the marked communication lines;

[0026] 3: Monitor the electromagnetic interference data generated by the high-power components of the electric drive platform during operation, analyze the frequency of changes in the communication error rate of the marker communication line under different interference intensities and frequencies, and evaluate the tolerance of the marker communication line under various interference conditions;

[0027] 4: Evaluate the sensitivity of the tag communication line based on the integrity of the tag communication line's communication signal and its tolerance to various interference conditions;

[0028] 5: Based on the evaluation results, the sensitivity of the marked communication lines is divided into different sensitivity levels, namely high-sensitivity marked lines and low-sensitivity marked lines;

[0029] 6: Add electromagnetic shielding to highly sensitive communication lines, evaluate and provide feedback on the accuracy of battery data transmitted by the BMS on the added electromagnetic shielding communication lines, and dynamically adjust the battery health status assessment time and energy management decisions based on the feedback results.

[0030] The above scheme is further described as follows:

[0031] 1. Step 1

[0032] Identify all CAN bus-related communication lines in the electric drive platform. Based on the communication requirements of the BMS intelligent battery management system, calculate the data rate and bandwidth requirements of each communication line, and mark high-speed and high-bandwidth communication lines. Specifically:

[0033] Obtain an electrical system diagram for the electric drive platform: Obtain a detailed electrical system diagram (E / E diagram) from the electric drive platform manufacturer. This diagram should include all electrical components and their connected network structure, including the topology of all CAN buses. Determine which components and systems are connected to the CAN bus and identify the specific lines on each CAN bus.

[0034] Identify CAN nodes: In the architecture diagram, identify all nodes connected to the CAN bus. These nodes typically include the BMS, powertrain control unit (PCU), charging control unit (CCU), sensors, and other electronic control units (ECUs). Determine the devices connected to each CAN bus and their functions, and distinguish between communication lines with different functions.

[0035] Draw a communication diagram: Based on the identified nodes, draw a detailed communication diagram, marking the CAN bus connections between each node. Visualize all CAN bus-related communication lines to facilitate subsequent analysis.

[0036] Check the wiring harness and actual wiring: Compare the wiring harness diagram of the electric drive platform with the actual wiring to ensure that all identified CAN bus lines are consistent with the diagram during actual installation to avoid omissions or incorrect markings. Verify the consistency of the theoretical design and actual wiring to ensure that the identified lines are complete and correct.

[0037] According to the functional requirements of the BMS intelligent battery management system, list all data types that need to be transmitted through the CAN bus (such as voltage, temperature, current, SOC status, fault information, etc.).

[0038] Determine the packet size (in bits) for each data type. For example, voltage data might be 16 bits, and temperature data might be 12 bits. If the data type is multi-byte (such as a floating-point number or long integer), determine the number of bits in the packet based on its length.

[0039] Based on system requirements, determine the refresh rate (i.e., how many times per second) each data type should be updated. For example, voltage data might need to be updated 100 times per second, while temperature data might need to be updated 50 times per second. Understanding the transmission frequency required for each data type during operation will help you accurately calculate the total data volume.

[0040] Calculate the data rate for each data type transmitted on each CAN bus. Multiply the packet size of each data type by its refresh rate to get the bit rate of that data type. Add the bit rates of all data types to get the total data rate of the CAN bus. The specific calculation expression is: data rate = ∑(packet size (bits) × refresh rate (Hz));

[0041] Based on the calculated data rate, a safety margin factor (usually 1.2 to 2 times) is multiplied to cope with fluctuations and multi-task loads that may occur in actual operation. The expression is: Bandwidth = Data Rate × Safety Margin Factor.

[0042] Based on the overall design standards of the electric drive platform, data rate and bandwidth requirements are defined as reference thresholds for high speed and high bandwidth, respectively. The real-time calculated data rate is compared with the data rate threshold. If the real-time data rate is greater than or equal to the data rate threshold, the communication line is marked as a high-speed communication line. The real-time calculated bandwidth data is compared with the bandwidth data threshold. If the real-time bandwidth data is greater than or equal to the bandwidth data threshold, the communication line is marked as a high-bandwidth communication line. Communication lines with data rates greater than or equal to the data rate threshold and bandwidth data greater than or equal to the bandwidth data threshold are marked as high-speed and high-bandwidth communication lines.

[0043] Mark high-speed communication lines: On the communication line diagram, mark all high-speed communication lines with a special symbol or color (such as red). Use a legend to indicate the meaning of each color or symbol. This visual marking allows you to quickly identify communication lines in the system that require high speeds, allowing you to focus on and optimize them.

[0044] Marking high-bandwidth communication lines: Similarly, high-bandwidth communication lines should be marked. Different colors (such as blue) or symbols can be used to distinguish them. Communication lines marked with two different colors indicate that they require both high speed and high bandwidth. This ensures that these lines with higher bandwidth requirements are prioritized in cabling and interference protection design.

[0045] Generate Marker Report: Create a communication line marking report that lists detailed information on all marked high-speed and high-bandwidth lines, including their location, connected nodes, data rates, and bandwidth requirements. This provides detailed reference documentation for subsequent engineering design, testing, and optimization.

[0046] 2. Step 2

[0047] For the marked communication lines, the communication signals of the marked communication lines are measured in real time by a signal analyzer, and the waveform distortion of the communication signals under different working conditions is judged to evaluate the integrity of the communication signals of the marked communication lines.

[0048] Select a suitable signal analyzer based on the communication rate and bandwidth requirements of the CAN bus. The analyzer should have the following functions:

[0049] Supports CAN bus signal analysis and is capable of capturing high-frequency signals. It features real-time waveform display, enabling analysis of signal integrity and waveform distortion. It supports multi-channel monitoring for simultaneous analysis of signals from multiple lines.

[0050] Connect the signal analyzer: Connect the signal analyzer to the marked CAN bus communication line correctly. Use appropriate probes to ensure that the line does not affect the normal operation.

[0051] Configure the signal analyzer: Set the sampling rate to capture all signal details (typically 10 times the CAN rate or higher). Set trigger conditions, such as triggering sampling when a specific signal level changes, to capture key events. Set the channels as needed to monitor multiple lines simultaneously.

[0052] Turn on the signal analyzer and start collecting real-time signal data on the marked communication line. Obtain the communication signals on the CAN bus during actual operation for subsequent analysis.

[0053] Record initial signal waveforms: When the electric drive platform is stationary or under low load, record the initial waveforms of each marked communication line. These waveforms will serve as a baseline for comparison under subsequent operating conditions.

[0054] Repeat measurements under varying operating conditions: Measure under varying operating conditions, such as acceleration, deceleration, steering, charging, and varying temperature conditions. Record the communication line waveform in real time under each operating condition. Capture and store the waveform in real time for subsequent analysis.

[0055] Compare the waveforms recorded under different working conditions with the initial reference waveform to observe whether the waveform is distorted. Common distortions include: Waveform spikes: unexpected high-frequency spike signals, which may be caused by electromagnetic interference. Signal jitter: The rise time and fall time of the signal are unstable or jittery, which may cause data decoding errors. Signal reflection: Echoes or multiple reflections that should not exist appear in the waveform, usually caused by line impedance mismatch. Signal attenuation: The waveform amplitude decreases, which may cause the receiver to be unable to correctly identify the signal. Use the automatic measurement functions of the signal analyzer (such as eye diagram analysis and jitter analysis) to quantitatively evaluate the degree of waveform distortion.

[0056] Record and annotate the waveform distortion in detail for each operating condition, including the type of distortion, the conditions under which it occurred, and the possible causes. Use the signal analyzer's annotation function to directly mark the distortion location on the waveform graph.

[0057] The signal waveform distortion index is generated according to the waveform distortion of the communication signal under different working conditions to evaluate the integrity of the communication signal of the communication line. The method for obtaining the signal waveform distortion index is as follows:

[0058] The time domain waveform data of the collected signal under different working conditions is recorded as x(t). The time domain signal x(t) is subjected to discrete Fourier transform using the fast Fourier transform algorithm. The expression is: Where X(k) is the value of the frequency domain signal at the kth frequency point, x(n) is the value of the time domain signal at the nth sample point, N is the total number of signal sample points, and e -j2πkt / N is the kernel function of the Fourier transform, where j is the imaginary unit, which extracts the amplitude from the complex frequency domain signal X(k). Among them, Re(X(k)) 2 is the real part of X(k), IM(X(k)) 2 is the imaginary part of X(k), and the signal waveform distortion index is calculated. The expression is: In the formula, |X(k i )| is the amplitude of the i-th harmonic, |X(k1)| is the amplitude of the fundamental frequency, and THD is the signal waveform distortion index.

[0059] The obtained signal waveform distortion index is compared with the preset signal waveform distortion index reference threshold. If the signal waveform distortion index is greater than or equal to the preset signal waveform distortion index reference threshold, it means that the degree of communication signal waveform distortion under different working conditions is more serious, that is, the integrity of the communication signal of the communication line is low, and a communication signal distortion signal is generated at this time; if the signal waveform distortion index is less than the preset signal waveform distortion index reference threshold, it means that the degree of communication signal waveform distortion under different working conditions is less serious, that is, the integrity of the communication signal of the communication line is high, and no communication signal distortion signal is generated at this time.

[0060] 3. Step 3

[0061] The electromagnetic interference data generated by the high-power components of the electric drive platform during operation is monitored, the changing frequency of the communication error rate of the marker communication line under different interference intensities and frequencies is analyzed, and the tolerance of the marker communication line under various interference conditions is evaluated.

[0062] Use appropriate EMI monitoring equipment, such as a spectrum analyzer, electromagnetic field probe, or oscilloscope. These devices should be able to measure the intensity of electromagnetic interference within a specific frequency range. Before starting the measurement, ensure that the equipment is properly calibrated to ensure accurate measurement results.

[0063] Identify and document the locations of key high-power components in the electric drive platform, such as the motor, inverter, and charger. Collect information on the operating conditions of these components under different operating modes (e.g., full load, partial load, no load, etc.). Ensure that the measurement environment minimizes external electromagnetic interference to avoid influencing measurement results. Place electromagnetic field probes or antennas in strategic locations near high-power components to ensure that the probes can capture the strongest interference signals.

[0064] Start the electric drive platform and operate the high-power components under different load conditions, gradually increasing from low to high load. Under each load condition, use a spectrum analyzer to measure the EMI intensity at different frequencies. Record the interference frequency range (e.g., kHz to GHz) and interference intensity (e.g., dBμV / m or dBm) for each load condition. Use the spectrum analyzer's save function to store the EMI spectrum for each operating condition.

[0065] Using the collected data, plot the EMI spectrum under different operating conditions to show how the interference intensity changes with frequency. Identify and mark the main interference frequency bands and corresponding intensities generated by high-power components in different operating states.

[0066] While monitoring EMI, a signal analyzer is used to simultaneously collect and mark data packet transmission on the communication line, recording any communication errors (such as packet loss, bit flips, timeouts, etc.) that occur during actual transmission. A data logging system is used to synchronously record the error rate of each communication line with the corresponding time stamp for subsequent analysis.

[0067] Align the EMI measurement data and communication error rate data by timestamp to ensure they correspond. Compare the intensity changes in different interference frequency bands and analyze how the communication error rate of the marked communication line changes in these frequency bands.

[0068] The error rate in each time period is calculated to obtain the communication error rate change frequency in each frequency band, and the tolerance of the communication line under various interference conditions is evaluated. The error rate fluctuation index is obtained as follows:

[0069] The bit error rate under different working conditions within a time period t is obtained in real time, and a bit error rate time series {BER(t)} is constructed. All local maxima and local minima in the bit error rate time series are connected using spline curves to obtain the upper envelope U(t) and lower envelope L(t) of the bit error rate time series. The average value m(t) of the upper and lower envelopes is calculated using the formula: Subtract the local mean m(t) from the original bit error rate signal to obtain the first component h1(t), which is expressed as: h1(t) = BER(t) - m(t); treat h1(t) as new data and continue to calculate h1(t) until h1(t) meets the intrinsic mode function of the IMF condition, and record this IMF as IMF1(t); subtract IMF1(t) from the original data, which is expressed as: r1(t) = BER(t) - IMF1(t); repeatedly calculate r1(t) until the remaining data rn(t) can no longer be decomposed into IMFs. The bit error rate time series BER(t) is decomposed into several IMFs and a residual trend term. All IMFs are obtained, and several IMFs representing different frequency components of the bit error rate and a residual term are obtained.

[0070] For each IMFi(t), calculate its Hilbert transform IMF^i(t), which is expressed as: Where PV represents the principal value integral, τ is time, and π is pi. For each IMFi(t), its instantaneous amplitude Ai(t) is calculated, and the expression is: Calculate the energy spectral density Ei(t) of each IMF, which reflects the energy distribution at each instantaneous frequency. The expression is: Ei(t) = Ai(t) 2 ; Calculate the total energy Etotal of all IMFs, the expression is: n is the total number of IMFs. The bit error rate fluctuation index is calculated as follows: Where SD is the bit error rate fluctuation index.

[0071] The obtained bit error rate fluctuation index is compared with the preset bit error rate tolerance. If the bit error rate fluctuation index is greater than or equal to the preset bit error rate tolerance, it means that the higher the frequency of change of the communication error rate of the marked communication line under different interference intensities and frequencies, the lower the tolerance of the marked communication line under various interference conditions. At this time, a communication line abnormal signal is generated; if the bit error rate fluctuation index is less than the preset bit error rate tolerance, it means that the lower the frequency of change of the communication error rate of the marked communication line under different interference intensities and frequencies, the higher the tolerance of the marked communication line under various interference conditions. At this time, a communication line normal signal is generated.

[0072] 4. Step 4

[0073] The sensitivity of the communication line is evaluated based on the integrity of the communication signal and its tolerance to various interference conditions. Since the integrity of the communication signal is expressed by the waveform distortion index and the tolerance is expressed by the bit error rate fluctuation index, the sensitivity evaluation method of the communication line specifically includes:

[0074] The signal waveform distortion index (indicating integrity) and the bit error rate fluctuation index (indicating tolerance) are converted into the first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model uses the sensitivity analysis value label of the communication line predicted by each group of first eigenvectors as the prediction target, and minimizes the sum of the prediction errors of the sensitivity analysis value labels of all communication lines as the training target. The machine learning model is trained until the sum of the prediction errors reaches convergence, and the model training is stopped. The sensitivity analysis value of the communication line is determined according to the model output results.

[0075] The sensitivity analysis value of the communication line is obtained by obtaining the corresponding function expression from the first eigenvector training data of the trained machine learning model: CM = f1(THD, SD); where f1 is the output function of the model, THD is the signal waveform distortion index, SD is the bit error rate fluctuation index, and CM is the sensitivity analysis value of the communication line.

[0076] 5. Step 5

[0077] According to the evaluation results, the sensitivity of the marked communication lines is divided into different sensitivity levels, namely high-sensitivity marked lines and low-sensitivity marked lines.

[0078] The acquired sensitivity analysis value of the communication line is compared with the preset sensitivity analysis value reference threshold of the communication line. If the sensitivity analysis value of the communication line is greater than or equal to the preset sensitivity analysis value reference threshold of the communication line, it is classified as a high-sensitivity marked line and a high-sensitivity signal is generated; if the sensitivity analysis value of the communication line is less than the preset sensitivity analysis value reference threshold of the communication line, it is classified as a low-sensitivity marked line and a low-sensitivity signal is generated.

[0079] These signals can be highlighted with different color markers, specific codes, or by different treatment methods in system design. For example, a high-sensitivity line can be marked red or annotated as "High Sensitivity" on the circuit diagram. A low-sensitivity line can be marked green or annotated as "Low Sensitivity."

[0080] Record the sensitivity levels of all circuits and generate a detailed report. This report should include each circuit's sensitivity analysis value, corresponding threshold, and the final sensitivity classification. Feedback this information to the system design team for design optimization, such as strengthening shielding or adjusting routing for highly sensitive circuits.

[0081] 6. Step 6

[0082] Add electromagnetic shielding to highly sensitive communication lines, evaluate and feedback the accuracy of battery data transmitted by the BMS on the electromagnetic shielded communication lines, and dynamically adjust the battery health status assessment time and energy management decisions based on the feedback results.

[0083] Examine existing wiring and shielding measures for highly sensitive communication lines. Select appropriate electromagnetic shielding materials and methods based on the line's operating frequency, environmental conditions, and the type of interference source. Shielding materials include copper, aluminum foil, braided wire, ferrite beads, etc. Shielding methods include shielded cables, shielded enclosures, grounded shields, or adding a ground plane to the PCB.

[0084] Shield highly sensitive communication lines to ensure they are fully covered and well grounded. Use EMI testing equipment to test the shielded lines to confirm they are effective.

[0085] After the shielding modification is completed, the BMS system is started to collect battery data transmitted on the shielded communication line, including key parameters such as voltage, current, temperature, and SOC (State of Charge).

[0086] After adding electromagnetic shielding to highly sensitive communication lines, the sensitivity analysis values of the communication lines generated in subsequent fixed time periods are collected, and a data set is established. The mean and standard deviation of the data set are calculated. After analysis, the accuracy of the battery data transmitted by the BMS of the communication line is evaluated and fed back. The battery health status assessment time and energy management decisions are dynamically adjusted based on the feedback results.

[0087] If the mean sensitivity analysis value within the data set is greater than or equal to the reference threshold for the mean sensitivity analysis value, and the standard deviation of the sensitivity analysis value is less than the reference threshold for the standard deviation of the sensitivity analysis value, it indicates that the sensitivity of the communication line is high and stable, and there is persistent slight interference. In this case, a level 2 warning signal is generated, and relevant personnel need to further strengthen shielding measures and optimize line design, increase the frequency of battery health assessment, and ensure timely response to possible interference;

[0088] If the sensitivity analysis value mean is greater than or equal to the reference threshold for the sensitivity analysis value mean, and the sensitivity analysis value standard deviation is greater than or equal to the reference threshold for the sensitivity analysis value standard deviation, it indicates that the communication line performance is inconsistent in different time periods and there is unstable strong interference. In this case, a level 1 warning signal is generated, and relevant personnel need to conduct in-depth interference source analysis. It may be necessary to redesign the shielding or take additional anti-interference measures. It is necessary to further increase the frequency of battery health assessment and closely monitor the system status.

[0089] If the sensitivity analysis value mean is less than the reference threshold for the sensitivity analysis value mean, and the sensitivity analysis value standard deviation is greater than or equal to the reference threshold for the sensitivity analysis value standard deviation, it indicates that the line performs normally most of the time, but is occasionally subject to significant interference. In this case, a Level 3 warning signal is generated, and relevant personnel need to investigate the source of occasional interference, strengthen monitoring within a specific time period, and dynamically adjust the assessment frequency. If an anomaly is found, the frequency should be increased, and otherwise the frequency should be maintained at a lower level.

[0090] If the sensitivity analysis value mean is less than the reference threshold for the sensitivity analysis value mean, and the sensitivity analysis value standard deviation is less than the reference threshold for the sensitivity analysis value standard deviation, it indicates that the communication line is stable and insensitive most of the time. In this case, no warning signal is generated. Consider reducing the frequency of battery health status assessment, reducing the system load, and maintaining the existing energy management strategy without further adjustment.

[0091] It should be noted here that the importance of the first-level warning signal is greater than that of the second-level warning signal, and the importance of the second-level warning signal is greater than that of the third-level warning signal. Relevant personnel can take corresponding adjustment measures according to different warning signal levels.

[0092] The dynamic adjustment of battery health status assessment time and energy management decision is as follows:

[0093] 1) Adjust the battery health status assessment time:

[0094] Increase the assessment frequency: When it is found that the line is highly sensitive and fluctuates greatly, increase the assessment frequency and shorten the time interval between each assessment.

[0095] Reduce the evaluation frequency: When the line performance is stable and the sensitivity is low, the evaluation frequency can be appropriately reduced to reduce the system calculation burden.

[0096] Ensure that the battery health assessment matches the current communication line conditions.

[0097] 2) Adjust energy management strategy:

[0098] Optimize charge and discharge control: Under high-sensitivity and high-volatility conditions, adjust the charge or discharge rate in real time to avoid excessive battery consumption and extend battery life.

[0099] Adjusting fault detection thresholds: Dynamically adjust fault detection thresholds based on the real-time sensitivity of the line to reduce false positives and missed alarms. Optimize energy management strategies based on changes in line sensitivity to improve overall system efficiency and safety.

[0100] Continuous Monitoring and Optimization: We will continue to regularly collect sensitivity analysis values and conduct rolling analysis based on new data. We will dynamically adjust battery health assessment time and energy management strategies based on the latest assessment feedback to maintain the system's adaptability and ensure optimal performance under various operating conditions.

[0101] In this embodiment, all CAN bus-related communication lines in the electric drive platform are identified. Based on the communication requirements of the BMS intelligent battery management system, the data rate and bandwidth requirements of each communication line are calculated, and high-speed and high-bandwidth communication lines are marked. For the marked communication lines, the communication signals of the marked communication lines are measured in real time using a signal analyzer, and the waveform distortion of the communication signals under different operating conditions is determined to evaluate the integrity of the communication signals of the marked communication lines. The electromagnetic interference data generated by the high-power components of the electric drive platform during operation is monitored, and the frequency of changes in the communication error rate of the marked communication lines under different interference intensities and frequencies is analyzed to evaluate the tolerance of the marked communication lines under various interference conditions. The sensitivity of the marked communication lines is evaluated based on the integrity of the communication signals of the marked communication lines and their tolerance under various interference conditions. Based on the evaluation results, the sensitivity of the marked communication lines is divided into different sensitivity levels, namely high-sensitivity marked lines and low-sensitivity marked lines. Electromagnetic shielding is added to the highly sensitive communication lines, and the accuracy of the battery data transmitted by the BMS on the electromagnetically shielded communication lines is evaluated and feedback is provided. The battery health status assessment time and energy management decisions are dynamically adjusted based on the feedback results. It effectively improves the data transmission accuracy and stability of the BMS system, ensures the accuracy and timeliness of battery health status assessment and energy management decisions, thereby improving the reliability and safety of the overall electric drive platform system and extending the battery life.

[0102] The BMS intelligent battery management control system for electric drive platform using the above method is shown in the attached Figure 2 As shown, it includes: communication management module, signal monitoring module, electromagnetic interference analysis module, sensitivity assessment module, sensitivity classification module and control management module;

[0103] Communication management module: Identifies all CAN bus-related communication lines in the electric drive platform, calculates the data rate and bandwidth requirements of each communication line based on the communication needs of the BMS intelligent battery management system, and marks high-speed and high-bandwidth communication lines;

[0104] Signal monitoring module: For the marked communication lines, the signal analyzer is used to measure the communication signals of the marked communication lines in real time, and the waveform distortion of the communication signals under different working conditions is determined to evaluate the integrity of the communication signals of the marked communication lines.

[0105] Electromagnetic Interference Analysis Module: This module monitors the electromagnetic interference data generated by the high-power components of the electric drive platform during operation, analyzes the frequency of changes in the communication error rate of the marker communication line under different interference intensities and frequencies, and evaluates the tolerance of the marker communication line under various interference conditions.

[0106] Sensitivity assessment module: assesses the sensitivity of the marker communication line based on the integrity of the marker communication line's communication signal and its tolerance under various interference conditions;

[0107] Sensitivity classification module: Based on the evaluation results, the sensitivity of the marked communication lines is divided into different sensitivity levels, namely high-sensitivity marked lines and low-sensitivity marked lines;

[0108] Control and management module: Add electromagnetic shielding to highly sensitive communication lines, evaluate and provide feedback on the accuracy of battery data transmitted by the BMS on the added electromagnetic shielding communication lines, and dynamically adjust the battery health status assessment time and energy management decisions based on the feedback results.

[0109] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0110] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0111] The above technical solutions are only exemplary embodiments of the present invention. For those skilled in the art, it is easy to make various types of improvements or modifications based on the application methods and principles disclosed in the present invention, and are not limited to the methods described in the above specific embodiments of the present invention. Therefore, the methods described above are only preferred and do not have a restrictive meaning.

Claims

1. A BMS intelligent battery management control method for an electric drive platform, comprising the following steps: S1: Identify all CAN bus-related communication lines in the electric drive platform, calculate the data rate and bandwidth requirements of each communication line based on the communication requirements of the BMS intelligent battery management system, and mark high-speed and high-bandwidth communication lines; S2: For the marked communication lines, perform real-time measurements on the communication signals in the lines, determine the waveform distortion of the signals under different working conditions, and evaluate the integrity of the communication signals on the lines; S3: Monitor the electromagnetic interference data generated by the high-power components of the electric drive platform during operation, analyze the frequency of changes in the communication error rate of the marked communication lines under different interference intensities and frequencies, and evaluate the line's tolerance under various interference conditions; S4: Evaluate the sensitivity of the marked communication line based on the integrity of the communication signal and its tolerance under various interference conditions; S5, marking highly sensitive communication lines based on the evaluation result of step S4; S6: Add electromagnetic shielding to highly sensitive communication lines, evaluate and provide feedback on the accuracy of BMS battery data transmitted through the communication lines after adding electromagnetic shielding, and dynamically adjust the battery health status assessment time and energy management decisions based on the feedback results.

2. The method according to claim 1, characterized in that The step S1 specifically includes: Calculate the data rate and bandwidth for all data types transmitted on each CAN bus; Based on the overall design standards of the electric drive platform, reference thresholds for high data rate and high bandwidth are defined. Comparing the data rate calculated in real time with a data rate threshold, and marking it as a high-speed communication line if the real-time data rate is greater than or equal to the data rate threshold; Compare the bandwidth data calculated in real time with the bandwidth data threshold. If the real-time bandwidth data is greater than or equal to the bandwidth data threshold, mark it as a high-bandwidth communication line. Communication lines with a data rate greater than or equal to a data rate threshold and a bandwidth data greater than or equal to a bandwidth data threshold are marked as high-speed and high-bandwidth communication lines.

3. The method according to claim 1, characterized in that The step S2 specifically includes: S21, calculating the waveform distortion index of the marked communication line communication signal under different working conditions: Collect the time domain waveform data of the signal under different working conditions and record it as x(t); Perform discrete Fourier transform on the time domain signal x(t): Where X(k) is the value of the frequency domain signal at the kth frequency point, x(n) is the value of the time domain signal at the nth sample point, N is the total number of signal sample points, and e -j2πkt / N is the kernel function of the Fourier transform, where j is the imaginary unit; Extract the amplitude from the complex frequency domain signal X(k): Among them, Re(X(k)) 2 is the real part of X(k), IM(X(k)) 2 is the imaginary part of X(k); Calculate the signal waveform distortion index: In the formula, |X(k i )| is the amplitude of the i-th harmonic, |X(k1)| is the amplitude of the fundamental frequency, and THD is the signal waveform distortion index; S22, comparing the obtained signal waveform distortion index with a preset corresponding threshold value, and if the index is greater than or equal to the threshold value, marking the integrity of the communication signal of the communication line as low; Otherwise, the integrity of the communication signal of the marking communication line is high.

4. The method according to claim 3, characterized in that The specific method of step S3 includes: S31, calculate the bit error rate fluctuation index in each time period: Obtain the bit error rate under different working conditions in time period t in real time and construct the bit error rate time series {BER(t)}; Connect all local maxima and local minima in the bit error rate time series with spline curves to obtain the upper envelope U(t) and lower envelope L(t) of the bit error rate time series. Calculate the average value m(t) of the upper and lower envelopes: Subtract the local mean m(t) from the original bit error rate signal to obtain the first component h1(t): h1(t) = BER(t) - m(t); Treat h1(t) as new data and continue to calculate h1(t) until h1(t) meets the IMF intrinsic mode function, and record this IMF as IMF1(t); Subtract IMF1(t) from the original bit error rate data, denoted as: r1(t) = BER(t) - IMF1(t); Repeat the calculation of r1(t) until the remaining data rn(t) can no longer be decomposed into IMFs; The bit error rate time series BER(t) is thus decomposed into several IMFs and a residual trend term. The IMFs represent the different frequency components of the bit error rate. For each IMFi(t), calculate its Hilbert transform IMF^i(t): Where PV represents the principal value integral, τ is time, and π is pi; For each IMFi(t) calculate its instantaneous amplitude Ai(t): Calculate the energy spectral density Ei(t) of each IMF: Ei(t) = Ai(t) 2 ; Calculate the total energy Etotal of all IMFs: n is the total number of IMFs; Calculate the bit error rate fluctuation index: Where, SD is the bit error rate fluctuation index; S32, comparing the obtained bit error rate fluctuation index with a preset bit error rate tolerance. If the bit error rate exceeds the tolerance, it is marked that the communication line has low tolerance under various interference conditions; otherwise, it is marked that the communication line has high tolerance under various interference conditions.

5. The method according to claim 4, characterized in that In step S4, the method for evaluating the sensitivity of the communication line specifically includes: The signal waveform distortion index and the bit error rate fluctuation index are converted into a first eigenvector, and the first eigenvector is used as the input of the machine learning model. The machine learning model uses the sensitivity analysis value label of the communication line predicted by each group of first eigenvectors as a prediction target, and uses minimizing the sum of the prediction errors of the sensitivity analysis value labels of all communication lines as a training target. The machine learning model is trained until the sum of the prediction errors reaches convergence, and the model training is stopped. The sensitivity analysis value of the communication line is determined according to the model output result; The sensitivity analysis value of the communication line is obtained by obtaining the corresponding function expression from the first eigenvector training data of the trained machine learning model: CM = f1(THD, SD); where f1 is the output function of the model, THD is the signal waveform distortion index, SD is the bit error rate fluctuation index, and CM is the sensitivity analysis value of the communication line.

6. The method according to any one of claims 1 to 5, characterized in that: The step S6 specifically includes: Electromagnetic shielding is added to the highly sensitive communication line. Then, battery data transmitted on the shielded communication line is collected, and the sensitivity analysis value of the communication line is collected. A data set is established, and the mean and standard deviation of the data set are calculated. After analyzing the data set, the battery health status assessment time and energy management decision are dynamically adjusted according to the analysis results, including: If the mean of the sensitivity analysis values within the data set is greater than or equal to its corresponding threshold, and the standard deviation of the sensitivity analysis values is less than its corresponding threshold, a secondary warning signal is generated to further enhance shielding measures and optimize circuit design, thereby increasing the frequency of battery health status assessments. If the mean of the sensitivity analysis value is greater than or equal to its corresponding threshold, and the standard deviation of the sensitivity analysis value is greater than or equal to its corresponding threshold, a level 1 warning signal is generated, and the shielding is redesigned and additional anti-interference measures are taken to further increase the frequency of battery health status assessment and monitor system status; If the mean value of the sensitivity analysis value is less than its corresponding threshold value, and the standard deviation of the sensitivity analysis value is greater than or equal to its corresponding threshold value, a third-level warning signal is generated to check for sporadic interference sources and dynamically adjust the evaluation frequency. If an anomaly is found, the evaluation frequency is increased, otherwise it is maintained at a low frequency. If the mean value of the sensitivity analysis value is less than its corresponding threshold value, and the standard deviation of the sensitivity analysis value is less than its corresponding threshold value, no warning signal is generated, the assessment frequency of the battery health status is reduced, the system load is reduced, and the existing energy management strategy is maintained.

7. An electric drive platform BMS intelligent battery management control system using the method according to any one of claims 1 to 6, characterized in that: include: Communication management module, signal monitoring module, electromagnetic interference analysis module, sensitivity assessment module, sensitivity classification module and control management module; among which: Communication management module: Identifies all CAN bus-related communication lines in the electric drive platform, calculates the data rate and bandwidth requirements of each communication line based on the communication needs of the BMS intelligent battery management system, and marks high-speed and high-bandwidth communication lines; Signal monitoring module: used to measure the communication signal of the marked communication line in real time, determine the waveform distortion of the signal under different working conditions, and evaluate the integrity of the communication signal of the marked communication line; Electromagnetic Interference Analysis Module: This module is used to monitor the electromagnetic interference data generated by the high-power components of the electric drive platform during operation, analyze the frequency of changes in the communication error rate of the tag communication line under different interference intensities and frequencies, and evaluate the tolerance of the tag communication line under various interference conditions; Sensitivity assessment module: used to assess the sensitivity of the marked communication lines based on the integrity of the communication signals and their tolerance under various interference conditions; based on the assessment results, highly sensitive communication lines are marked; Control and management module: After adding electromagnetic shielding to highly sensitive communication lines, it is used to evaluate and provide feedback on the accuracy of BMS battery data transmitted through the electromagnetic shielded communication lines, and dynamically adjust the battery health status assessment time and energy management decisions based on the feedback results.

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