An electric drive platform BMS intelligent battery management control method and system

Abstract

A kind of electric drive platform BMS intelligent battery management control method and system, by accurately identifying and analyzing the communication line related to CAN bus in electric drive platform, according to the demand of BMS intelligent battery management system, high speed and high bandwidth communication line is calculated and marked, through real-time measurement and waveform distortion analysis, the communication signal integrity and resistance of these lines are evaluated, and electromagnetic shielding is added to high sensitivity line according to the evaluation result, finally, through the evaluation feedback of the accuracy of data transmission after shielding, the evaluation frequency of battery health state and energy management strategy are dynamically adjusted, to ensure that BMS system can be stably and reliably operated in complex electromagnetic environment, improve battery life, system safety and overall performance of electric drive platform.

Description

Technical Field

[0001] This invention relates to the field of intelligent battery management technology, and in particular to a BMS intelligent battery management control method and system for electric drive platforms. Background Technology

[0002] A Battery Management System (BMS) is a technology specifically designed to monitor and control the performance of battery packs. It ensures that each battery cell operates within safe limits by precisely measuring parameters such as voltage, current, and temperature. The BMS intelligent battery management system can communicate with other control systems via the CAN bus of the electric drive platform, enabling coordinated operation with the entire vehicle and providing data to users and higher-level systems to ensure that the battery pack operates in sync with the overall vehicle operation.

[0003] However, the high-power components of the electric drive platform (such as motors and inverters) generate strong electromagnetic interference during operation. This interference may affect CAN bus communication under certain frequencies and conditions. If the communication lines are too sensitive, they may easily produce latent communication errors. These latent communication errors may cause occasional errors in the battery data transmitted by the BMS, such as slight deviations in voltage or temperature. These deviations may not immediately lead to system alarms or malfunctions, but they will accumulate and affect battery health assessment and energy management decisions. In the long run, this may lead to abnormal battery aging or sudden failure. Summary of the Invention

[0004] This disclosure provides a BMS intelligent battery management control method and system for electric drive platforms to address the aforementioned shortcomings.

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

[0006] S1: Identify all communication lines related to the CAN bus 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 the 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 operating conditions, and evaluate the integrity of the line communication signals;

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

[0009] S4: Assess the sensitivity of the marked communication lines based on the integrity of the communication signals and their tolerance to various interference conditions.

[0010] S5. Based on the evaluation results of step S4, mark the highly sensitive communication lines;

[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 and control system for an electric drive platform, applying 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 communication lines related to the CAN bus 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 signals of the marked communication lines in real time, determine the waveform distortion of the signals under different operating conditions, and evaluate the integrity of the communication signals of the marked communication lines;

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

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

[0017] Control and Management Module: After adding electromagnetic shielding to highly sensitive communication lines, it evaluates and provides feedback on the accuracy of BMS battery data transmitted through the electromagnetically shielded communication lines, and dynamically adjusts the battery health status assessment time and energy management decisions based on the feedback results.

[0018] Compared with existing technologies, the beneficial effects of this disclosure are: ① By comprehensively identifying and analyzing the communication lines related to the CAN bus in the electric drive platform, and combining the requirements of the BMS intelligent battery management system, high-speed and high-bandwidth communication lines are marked, and the signal integrity and interference tolerance of these lines under different operating conditions are thoroughly evaluated through signal measurement and electromagnetic interference monitoring; ② By adding electromagnetic shielding to highly sensitive communication lines and combining real-time data analysis and feedback mechanisms, the battery health status assessment frequency and energy management decisions are dynamically adjusted, thereby ensuring the stability and reliability of the system in complex electromagnetic environments; ③ The anti-interference capability of communication lines is effectively improved, the impact of implicit communication errors on BMS data transmission is reduced, and abnormal battery aging or failure due to the accumulation of small data deviations is avoided; ④ Precise control and optimization of the battery management system are achieved, extending battery life, ensuring the safety and performance of the entire vehicle, while reducing the overall load of the system and improving the efficiency of energy management. Attached Figure Description

[0019] The above and other objects, features and advantages of this disclosure will become more apparent from the more detailed description of exemplary embodiments of this disclosure taken in conjunction with the accompanying drawings, in which the same reference numerals generally represent the same components.

[0020] Figure 1 This is a flowchart of a method according to an exemplary embodiment;

[0021] Figure 2 This is a system block diagram according to an exemplary embodiment. Detailed Implementation

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

[0023] This disclosure provides a BMS intelligent battery management and control method and system for an electric drive platform. In one exemplary embodiment, the battery management and control method according to this disclosure is as follows: Figure 1 As shown, it includes the following steps:

[0024] 1. Identify all communication lines related to the CAN bus 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 the high-speed and high-bandwidth communication lines.

[0025] 2: 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 judged to 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 change of the communication error rate of the marked communication line under different interference intensities and frequencies, and evaluate the tolerance of the marked communication line under various interference conditions.

[0027] 4. Evaluate the sensitivity of the marked communication lines based on the integrity of the communication signals and their 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, classifying them into high-sensitivity marked lines and low-sensitivity marked lines.

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

[0030] The above plan is further explained in detail below:

[0031] 1. Step 1

[0032] Identify all communication lines related to the CAN bus 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 the electrical system architecture diagram of the electric drive platform: Obtain a detailed electrical system architecture diagram (E / E architecture diagram) from the electric drive platform manufacturer. This diagram should include all electrical components and their network structure, including the topology of all CAN buses. Determine which components and systems are connected to the CAN buses and identify the specific lines of 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, distinguishing communication lines with different functions.

[0035] Draw a communication line diagram: Based on the identified nodes, draw a detailed communication line diagram, marking the CAN bus connections between each node. Visualize all communication lines related to the CAN bus for easier 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 match the diagram during actual installation, avoiding omissions or incorrect markings. Verify the consistency between the theoretical design and the actual wiring to ensure that the identified lines are complete and error-free.

[0037] Based on the functional requirements of the BMS intelligent battery management system, list all data types that need to be transmitted via 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 floating-point numbers or long integers), determine the number of bits in the packet based on its length.

[0039] Based on system requirements, determine the refresh frequency for each type of data (e.g., how many times per second). For example, voltage data might need to be updated 100 times per second, and temperature data 50 times per second. Understand the transmission frequency required for each data type during operation to accurately calculate the total data volume.

[0040] Calculate the data rate for all data types transmitted on each CAN bus. Multiply the data packet size of each data type by its refresh rate to obtain the bit rate of that data type. Add the bit rates of all data types together to obtain the total data rate of the CAN bus. The specific calculation expression is: Data rate = ∑(data packet size (bit) × 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 possible fluctuations and multi-tasking loads 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, it 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, it is marked as a high-bandwidth communication line. Communication lines with both data rates and bandwidths 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, respectively.

[0043] Mark high-speed communication lines: On the communication line diagram, mark all high-speed communication lines with special symbols or colors (such as red). A legend can be used to explain the meaning of each color or symbol. Visual marking allows for quick identification of communication lines in the system with high speed requirements, enabling focused attention and optimization.

[0044] 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. Using two different colors to mark communication lines indicates that they have both high-speed and high-bandwidth requirements, ensuring that these high-bandwidth lines are prioritized in cabling and interference protection design.

[0045] Generate a tagging report: Create a communication line tagging report that lists detailed information about all tagged high-speed and high-bandwidth lines, including their location, connected nodes, data rates, and bandwidth requirements. This provides a detailed reference document 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 using a signal analyzer, and the waveform distortion of the communication signals under different operating 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] It supports CAN bus signal analysis and has the ability to capture high-frequency signals. It features real-time waveform display and can analyze signal integrity and waveform distortion. It supports multi-channel monitoring to simultaneously analyze signals from multiple lines.

[0050] Connect the signal analyzer: Connect the signal analyzer correctly to the marked CAN bus communication line. Use appropriate probes for connection, ensuring that the connection does not interfere with the normal operation of the line.

[0051] Configure the signal analyzer: Configure the sampling rate of the signal analyzer to ensure that all detailed signals can be captured (typically 10 times or more of the CAN rate). Set trigger conditions, such as setting sampling to be triggered when specific signal level changes, in order to capture critical events. Configure channels as needed to monitor multiple lines simultaneously.

[0052] Turn on the signal analyzer to begin real-time acquisition of signal data from the marked communication lines. Acquire the communication signals on the CAN bus during actual operation for subsequent analysis.

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

[0054] Changing operating conditions and repeating measurements: Measurements are performed under different operating conditions, such as acceleration, deceleration, steering, charging, and different temperature conditions of the electric drive platform. The waveform of the communication line is recorded in real time under each operating condition. The waveforms under each operating condition are captured and stored in real time for subsequent analysis.

[0055] Compare the waveforms recorded under different operating conditions with the initial reference waveform to observe whether waveform distortion occurs. Common distortions include: Waveform spikes: Unexpected high-frequency spikes, possibly caused by electromagnetic interference. Signal jitter: Instability or jitter in the rise and fall times of the signal, which may lead to data decoding errors. Signal reflections: Echoes or multiple reflections that should not be present in the waveform, usually caused by line impedance mismatch. Signal attenuation: Reduced waveform amplitude, which may prevent the receiver from correctly identifying the signal. Use the automatic measurement functions of a signal analyzer (such as eye diagram analysis and jitter analysis) to quantitatively assess the degree of waveform distortion.

[0056] The waveform distortion under each operating condition was recorded and annotated in detail, including the distortion type, the conditions under which it occurred, and the possible causes. The distortion location was directly marked on the waveform graph using the annotation function of the signal analyzer.

[0057] Based on the waveform distortion of communication signals under different operating conditions, a signal waveform distortion index is generated to evaluate the integrity of communication signals on marked communication lines. The method for obtaining the signal waveform distortion index is as follows:

[0058] The time-domain waveform data of the acquired signal under different operating conditions is recorded as x(t). A Discrete Fourier Transform (DFT) is performed on the time-domain signal x(t) using the Fast Fourier Transform (FFT) algorithm, and the expression is: Where X(k) is the value of the frequency domain signal at the k-th frequency point, x(n) is the value of the time domain signal at the n-th sample point, N is the total number of signal sample points, and e -j2πkt / N It is the kernel function of the Fourier transform, where j is the imaginary unit, and it extracts the amplitude from the frequency domain signal X(k) in complex form. Where, Re(X(k)) 2 It is the real part of X(k), IM(X(k)) 2 The imaginary part of X(k) is used to calculate the signal waveform distortion exponent, expressed as: In the formula, |X(k) i |X(k1)| 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 a 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 indicates that the degree of communication signal waveform distortion is more severe under different operating conditions, that is, the integrity of the communication signal of the marked communication line is low, and a communication signal distortion signal is generated. If the signal waveform distortion index is less than the preset signal waveform distortion index reference threshold, it indicates that the degree of communication signal waveform distortion is less severe under different operating conditions, that is, the integrity of the communication signal of the marked communication line is high, and no communication signal distortion signal is generated.

[0060] 3. Step 3

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

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

[0063] Identify and record 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). Ensure that external electromagnetic interference in the measurement environment is minimized to avoid affecting the measurement results. Position electromagnetic field probes or antennas at critical locations near high-power components, ensuring 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, EMI spectrum diagrams under different operating conditions are plotted to show how the interference intensity changes with frequency. The main interference frequency bands and corresponding intensities generated by high-power components under different operating conditions are identified and labeled.

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

[0067] Align EMI measurement data and communication error rate data by timestamp to ensure correspondence between the two sets of data. Analyze the changes in communication error rate of the marked communication lines across different interference frequency bands by comparing their intensity variations.

[0068] The error rate is calculated for each time period to obtain the frequency of communication error rate variation in each frequency band. The tolerance of the marked communication line under various interference conditions is evaluated. The method for obtaining the bit error rate fluctuation index is as follows:

[0069] The bit error rate (BER) under different operating conditions within a time period t is acquired in real time, and a BER time series {BER(t)} is constructed. All local maxima and minima in the BER time series are connected by spline curves to obtain the upper envelope U(t) and lower envelope L(t) of the BER time series. The average value m(t) of the upper and lower envelopes is calculated using the following formula: Subtracting the local average m(t) from the original bit error rate signal yields the first component h1(t), expressed as: h1(t) = BER(t) - m(t). Treating h1(t) as new data, h1(t) is continuously calculated until h1(t) satisfies the intrinsic mode function (IMF) condition. This IMF is recorded as IMF1(t). Subtracting IMF1(t) from the original data yields the expression: r1(t) = BER(t) - IMF1(t). Repeating 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 decomposed into several IMFs and a residual trend term, resulting in several IMFs representing different frequency components of the bit error rate, and a residual term.

[0070] For each IMFi(t), calculate its Hilbert transform IMF^i(t), expressed as: In the formula, 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) for each IMF, reflecting the energy distribution at each instantaneous frequency, expressed as: Ei(t) = Ai(t) 2 ; Calculate the total energy Etotal of all IMFs, the expression is: Let n be the total number of IMFs. The expression for calculating the bit error rate fluctuation index is: In the formula, 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 indicates that the communication error rate of the marked communication line changes more frequently under different interference intensities and frequencies, and the tolerance of the marked communication line under various interference conditions is low. At this time, an abnormal communication line signal is generated. If the bit error rate fluctuation index is less than the preset bit error rate tolerance, it indicates that the communication error rate of the marked communication line changes less frequently under different interference intensities and frequencies, and the tolerance of the marked communication line under various interference conditions is high. At this time, a normal communication line signal is generated.

[0072] 4. Step 4

[0073] The sensitivity of marked communication lines is assessed based on the integrity of the communication signal and their tolerance under various interference conditions. Since the integrity of the communication signal is represented by the waveform distortion index, and tolerance is represented by the bit error rate fluctuation index, the specific methods for assessing the sensitivity of communication lines include:

[0074] The signal waveform distortion index (representing integrity) and the bit error rate fluctuation index (representing tolerance) are converted into a first feature vector. The first feature vector is used as the input of the machine learning model. The machine learning model uses the prediction of the sensitivity analysis value label of the communication line for each set of first feature vectors as the prediction objective. The training objective is to minimize the sum of the prediction errors of the sensitivity analysis value labels of all communication lines. The machine learning model is trained until the sum of prediction errors converges, at which point the model training stops. The sensitivity analysis value of the communication line is determined based on the model output.

[0075] The method for obtaining the sensitivity analysis value of the communication line is as follows: from the training data of the first feature vector of the trained machine learning model, obtain the corresponding function expression: 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] Based on the assessment results, the sensitivity of the marked communication lines was divided into different sensitivity levels, namely, high-sensitivity marked lines and low-sensitivity marked lines.

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

[0079] These signals can be highlighted using different colors, specific codes, or different processing methods employed in the system design. For example, high-sensitivity lines can be marked in red or annotated "HighSensitivity" on the circuit diagram. Low-sensitivity lines can be marked in green or annotated "Low Sensitivity".

[0080] Record the sensitivity level of all lines and generate a detailed report. The report should include the sensitivity analysis value, corresponding threshold, and final sensitivity classification result for each line. Feedback the results to the system design team for design optimization, such as strengthening the shielding of high-sensitivity lines or adjusting wiring.

[0081] 6. Step 6

[0082] Electromagnetic shielding is added to highly sensitive communication lines. The accuracy of battery data transmitted by the BMS through the electromagnetically shielded communication lines is evaluated and feedback is provided. Based on the feedback results, the battery health status assessment time and energy management decisions are dynamically adjusted.

[0083] Inspect the existing wiring and shielding measures for highly sensitive communication lines. Based on the line's operating frequency, environmental conditions, and the type of interference source, select appropriate electromagnetic shielding materials and methods. Shielding materials: copper, aluminum foil, braided wire, ferrite beads, etc. Shielding methods: use shielded cables, shielded shells, grounding shielding, or add a grounding plane to the PCB board.

[0084] The highly sensitive communication lines were modified with shielding to ensure that the shielding layer completely covered the target line and that the shielding layer was properly grounded. EMI testing equipment was used to test the shielded lines to confirm the effectiveness of the shielding measures.

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

[0086] After adding electromagnetic shielding to highly sensitive communication lines, sensitivity analysis values ​​of the communication lines generated at fixed time intervals are collected and a dataset is established. The mean and standard deviation of the dataset are calculated and analyzed to evaluate the accuracy of battery data transmitted by the BMS of the communication lines. Based on the feedback results, the battery health status assessment time and energy management decisions are dynamically adjusted.

[0087] If the mean of the sensitivity analysis values ​​in the dataset is greater than or equal to the reference threshold of the mean of the sensitivity analysis values, and the standard deviation of the sensitivity analysis values ​​is less than the reference threshold of the standard deviation of the sensitivity analysis values, it indicates that the communication line is highly sensitive and stable, and there is a persistent slight interference. At this time, a level 2 warning signal is generated, and relevant personnel need to further enhance shielding measures and optimize line design, increase the frequency of battery health status assessment, and ensure timely response to possible interference.

[0088] If the mean value of the sensitivity analysis is greater than or equal to the reference threshold of the mean value of the sensitivity analysis, and the standard deviation of the sensitivity analysis is greater than or equal to the reference threshold of the standard deviation of the sensitivity analysis, it indicates that the communication line performs inconsistently at different time periods and there is unstable strong interference. At this time, a level one warning signal is generated. Relevant personnel need to conduct in-depth interference source analysis, which may require redesigning the shielding or taking additional anti-interference measures. It is also necessary to further increase the frequency of battery health status assessment and closely monitor the system status.

[0089] If the mean value of the sensitivity analysis is less than the reference threshold of the mean value of the sensitivity analysis, and the standard deviation of the sensitivity analysis is greater than or equal to the reference threshold of the standard deviation of the sensitivity analysis, it indicates that the line performs normally for most of the time, but is occasionally subject to significant interference. At this time, a level 3 warning signal is generated. Relevant personnel need to investigate the sources of occasional interference and strengthen monitoring within a specific time period, dynamically adjust the evaluation frequency, increase the frequency when an abnormality is found, and otherwise maintain a low frequency.

[0090] If the mean value of the sensitivity analysis is less than the reference threshold for the mean value of the sensitivity analysis, and the standard deviation of the sensitivity analysis is less than the reference threshold for the standard deviation of the sensitivity analysis, it indicates that the communication line is stable and insensitive most of the time. In this case, no warning signal is generated, and it is advisable to reduce the frequency of battery health status assessment, reduce system load, maintain the existing energy management strategy, and no further adjustments are required.

[0091] It should be noted that Level 1 warning signals are more important than Level 2 warning signals, and Level 2 warning signals are more important than Level 3 warning signals. Relevant personnel can take corresponding adjustment measures according to the different warning signal levels.

[0092] Specifically, the dynamic adjustment of battery health status assessment time and energy management decisions includes:

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

[0094] Increase assessment frequency: When the line is found to be highly sensitive and fluctuating, increase the assessment frequency and shorten the time interval between each assessment.

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

[0096] Ensure that the assessment of battery health status matches the current condition of the communication lines.

[0097] 2) Adjust energy management strategy:

[0098] Optimized charge and discharge control: Under highly sensitive and volatile conditions, the charging or discharging rate is adjusted in real time to avoid excessive battery consumption and extend battery life.

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

[0100] Continuous monitoring and optimization: Continue to collect sensitivity analysis values ​​regularly and conduct rolling analysis based on new data. Dynamically adjust battery health status 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, by identifying all communication lines related to the CAN bus in the electric drive platform, the data rate and bandwidth requirements of each communication line are calculated according to the communication needs of the BMS intelligent battery management system, 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 judged 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 change of 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. Based on the integrity of the communication signals of the marked communication lines and their tolerance under various interference conditions, the sensitivity of the marked communication lines is evaluated. Based on the evaluation results, the sensitivity of the marked communication lines is divided into different sensitivity levels, classifying them into high-sensitivity marked lines and low-sensitivity marked lines. Electromagnetic shielding is added to the high-sensitivity communication lines, and the accuracy of the battery data transmitted by the BMS through the electromagnetically shielded communication lines is evaluated and feedback is provided. Based on the feedback results, the battery health status evaluation time and energy management decisions are dynamically adjusted. It effectively improves the accuracy and stability of data transmission in the BMS system, ensuring the precision and timeliness of battery health status assessment and energy management decisions, thereby improving the overall reliability and safety of the electric drive platform system and extending battery life.

[0102] The BMS intelligent battery management and control system for electric drive platforms, which applies the above method, is shown in the attached figure. Figure 2 As shown, it 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;

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

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

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

[0106] Sensitivity assessment module: Evaluates the sensitivity of the marked communication line based on the integrity of the communication signal and its tolerance to various interference conditions;

[0107] Sensitivity Classification Module: Based on the evaluation results, the sensitivity of the marked communication lines is classified into different sensitivity levels, and they are divided into high-sensitivity marked lines and low-sensitivity marked lines.

[0108] Control and Management Module: Adds electromagnetic shielding to highly sensitive communication lines, evaluates and provides feedback on the accuracy of battery data transmitted by the BMS through the electromagnetically shielded communication lines, and dynamically adjusts the battery health status assessment time and energy management decisions based on the feedback results.

[0109] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0110] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. 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. 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 a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

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

Claims

1. A BMS intelligent battery management control method for an electric drive platform, comprising the following steps: S1: Identify all communication lines related to the CAN bus 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 the 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 operating conditions, and evaluate the integrity of the line communication signals; S3: Monitor the electromagnetic interference data generated by the high-power components of the electric drive platform during operation, analyze the frequency of change of the communication error rate of the marked communication line under different interference intensities and frequencies, and evaluate the tolerance of the line under various interference conditions. S4: Assess the sensitivity of the marked communication lines based on the integrity of the communication signals and their tolerance to various interference conditions. S5. Based on the evaluation results of step S4, mark the highly sensitive communication lines; 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, 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 are defined for high data rate and high bandwidth requirement, 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, it 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, it 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.

3. The method according to claim 1, characterized in that, Step S2 specifically includes: S21, Calculate the waveform distortion index of the marked communication line communication signal under different operating conditions: The time-domain waveform data of the acquired signal under different operating conditions is recorded as x(t); Perform a discrete Fourier transform on the time-domain signal x(t): Where X(k) is the value of the frequency domain signal at the k-th frequency point, x(n) is the value of the time domain signal at the n-th sample point, N is the total number of signal sample points, and e -j2πkt / N It is the kernel function of the Fourier transform, where j is the imaginary unit; Extracting the amplitude from the frequency domain signal X(k) in complex form: Where, Re(X(k)) 2 It is the real part of X(k), IM(X(k)) 2 It is the imaginary part of X(k); Calculate the signal waveform distortion index: In the formula, |X(k) i |X(k1)| represents the amplitude of the i-th harmonic, |X(k1)| represents the amplitude of the fundamental frequency, and THD represents the signal waveform distortion index. S22, compare the obtained signal waveform distortion index with the preset corresponding threshold. If it is greater than or equal to the threshold, mark the communication line signal as having low integrity. Otherwise, the integrity of the communication signal on the marked 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 for each time period: Real-time acquisition of bit error rate under different operating conditions within time period t, and construction of bit error rate time series {BER(t)}; Connect all the 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: Subtracting the local average value m(t) from the original bit error rate signal yields 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) satisfies the intrinsic mode function of the IMF. 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 IMF; Thus, the bit error rate time series BER(t) is decomposed into several IMFs and a residual trend term, where IMFs represent different frequency components of the bit error rate; For each IMFi(t), compute its Hilbert transform IMF^i(t): In the formula, 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) for 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: In the formula, SD is the bit error rate fluctuation index; S32, compare the obtained bit error rate fluctuation index with the preset bit error rate tolerance. If it exceeds the tolerance, mark the communication line as having low tolerance under various interference conditions; otherwise, mark the communication line as having high tolerance under various interference conditions.

5. The method according to claim 4, characterized in that, In step S4, the sensitivity assessment method for communication lines specifically includes: The signal waveform distortion index and bit error rate fluctuation index are converted into the first feature vector. The first feature vector is used as the input of the machine learning model. The machine learning model uses the prediction of the sensitivity analysis value label of the communication line for each set of first feature vectors as the prediction objective. The training objective is to minimize the sum of the prediction errors of the sensitivity analysis value labels of all communication lines. The machine learning model is trained until the sum of prediction errors converges and the model training stops. The sensitivity analysis value of the communication line is determined based on the model output. The method for obtaining the sensitivity analysis value of the communication line is as follows: from the training data of the first feature vector of the trained machine learning model, obtain the corresponding function expression: 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 1-5, characterized in that, 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 values ​​of the communication line are gathered. A dataset is established, and the mean and standard deviation of the dataset are calculated. After analysis, the battery health status assessment time and energy management decisions are dynamically adjusted based on the analysis results, including: If the mean value of the sensitivity analysis within the dataset is greater than or equal to its corresponding threshold, and the standard deviation of the sensitivity analysis value 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 assessment. If the mean value of the sensitivity analysis 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 first-level warning signal is generated, 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 is less than its corresponding threshold and the standard deviation of the sensitivity analysis value is greater than or equal to its corresponding threshold, a level three warning signal is generated to investigate occasional interference sources, dynamically adjust the evaluation frequency, increase the evaluation frequency when an anomaly is found, and otherwise maintain a low frequency. If the mean value of the sensitivity analysis is less than its corresponding threshold and the standard deviation of the sensitivity analysis value is less than its corresponding threshold, no warning signal will be generated, the frequency of battery health status assessment will be reduced, the system load will be reduced, and the existing energy management strategy will be maintained.

7. An intelligent battery management and control system for an electric drive platform BMS applying the method of any one of claims 1-6, characterized in that, include: The module 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; among which: Communication Management Module: Identifies all communication lines related to the CAN bus in the electric drive platform, calculates the data rate and bandwidth requirements of each communication line according to 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 signals of the marked communication lines in real time, determine the waveform distortion of the signals under different operating conditions, and evaluate the integrity of the communication signals of the marked communication lines; Electromagnetic Interference Analysis Module: Used to monitor the electromagnetic interference data generated by the high-power components of the electric drive platform during operation, analyze the frequency of communication error rate changes of the marked communication line under different interference intensities and frequencies, and evaluate the tolerance of the marked communication line under various interference conditions. Sensitivity assessment module: Used to assess the sensitivity of marked communication lines based on the integrity of the communication signals and their tolerance to various interference conditions; and to mark highly sensitive communication lines based on the assessment results. Control and Management Module: After adding electromagnetic shielding to highly sensitive communication lines, it evaluates and provides feedback on the accuracy of BMS battery data transmitted through the electromagnetically shielded communication lines, and dynamically adjusts the battery health status assessment time and energy management decisions based on the feedback results.

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