Adaptive Converter Topology Reconfiguration and Intelligent Control System for Load Fluctuations

Abstract

This invention discloses an adaptive converter topology reconfiguration and intelligent control system for load fluctuations, relating to the field of vehicle power control technology. The system uses a load disturbance scenario determination module to collect and comprehensively analyze vehicle operating data and environmental parameters in real time. This system can accurately identify load disturbance scenarios under various complex operating conditions, such as repeated braking on gentle slopes, differential offset during low-speed cornering, motor obstruction, and tire slippage in extreme environments. This precise identification capability effectively improves the system's response speed and accuracy to load changes, avoiding misjudgments and response delays caused by perception lag or insufficient discrimination in traditional systems in complex dynamic environments. By constructing targeted load disturbance indices Ld, differential offset indices Sd, motor obstruction indices Bd, and tire slippage rates Ed, the system achieves quantitative evaluation of multi-source disturbance factors, providing a scientific basis for subsequent intelligent control and topology reconfiguration.

Description

Technical Field

[0001] This invention relates to the field of vehicle power control technology, specifically to an adaptive converter topology reconfiguration and intelligent control system for load fluctuations. Background Technology

[0002] With the widespread adoption of two-wheeled electric vehicles as a green mode of transportation, the performance of their power control systems directly impacts the vehicle's safety, comfort, and energy efficiency. In existing technologies, the inverter, as a core component of the electric vehicle drive system, plays a crucial role in energy conversion and drive control. However, traditional inverter control strategies often rely on fixed topologies and static parameter settings, making it difficult to adapt to complex and changing road conditions and environmental environments.

[0003] Especially during actual driving, electric vehicles often face various load disturbances such as changes in slope, frequent braking, turning, and wading through water. Existing control systems typically lack the ability to perceive and accurately identify these multi-source disturbances in real time, leading to frequent motor overload, energy waste, and safety hazards. Particularly in risk-prone scenarios such as motor obstruction, tire slippage, or thermal runaway, traditional systems struggle to trigger protection mechanisms or optimize output paths in a timely manner, potentially causing system lag, increased energy consumption, or even hardware damage. Furthermore, when encountering sudden load changes, traditional converters typically employ only simple power limiting or equalization compensation methods, lacking adaptive topology reconfiguration capabilities. They cannot dynamically adjust output paths or control parameters based on disturbance type, and lack hierarchical control and dynamic topology reconfiguration capabilities based on disturbance intensity and evolution trends. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an adaptive converter topology reconfiguration and intelligent control system for load fluctuations, thereby solving the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an adaptive load fluctuation converter topology reconfiguration and intelligent control system, comprising:

[0006] The load scenario perception module is used to collect vehicle operation data and external environmental parameters during the operation of the electric vehicle. The vehicle operation data includes speed, acceleration, current, voltage and wheel speed, and the environmental parameters include temperature, humidity and road condition information.

[0007] The load disturbance scenario determination module identifies the following load disturbance scenarios based on the collected vehicle operation data and external environmental parameters: When the vehicle is identified as being in an urban gentle slope area with frequent braking, a load disturbance index Ld is constructed; when the vehicle is identified as being in a low-speed U-turn or turning process with a significant difference in front and rear wheel speeds, a differential offset index Sd is constructed to describe the degree of inconsistency between front and rear wheel drive; when the vehicle is detected as being in a water-wading condition with a sudden drop in motor speed and a sudden increase in current, a motor resistance index Bd is constructed to characterize the degree of motor lock-up or resistance; when the vehicle is detected as being in an environment with extremely cold or wet road conditions, a tire slip ratio Ed is constructed to characterize the degree of environmental disturbance.

[0008] The load disturbance index Ld, differential deviation index Sd, motor resistance index Bd, and tire slip ratio Ed are evaluated to obtain corresponding warning instructions;

[0009] The regulation effectiveness evaluation module is used to receive corresponding early warning commands, generate corresponding topology reconfiguration commands, and synchronously collect converter output power, voltage response, motor control accuracy, and power device thermal characteristic data after execution. This is used to construct and evaluate the regulation deviation index Pd, thermal response offset index Hd, and power stability index Wd. If any one of them fails to meet the requirements, a topology adaptability score coefficient Rt is constructed to correct the corresponding topology reconfiguration command.

[0010] Preferably, the load disturbance scenario determination module includes a gentle slope area identification unit, a frequent braking identification unit, and a first analysis unit;

[0011] The gentle slope area identification unit is used to obtain the vehicle pitch angle Wp using the vehicle's built-in inertial measurement IMU. When the vehicle pitch angle Wp > 3°, it is determined that the vehicle has entered the "gentle slope" state.

[0012] The frequent braking identification unit is used to collect the vehicle's braking signals and count the braking frequency f per unit time. If the braking frequency f is ≥ 3 times within a time window of T=10 seconds, or the braking duration is > 40% of the total time, it is determined to be a "multiple braking" state.

[0013] If the vehicle pitch angle Wp exceeds 3° and the braking frequency f≥3, or the braking duration exceeds 40% of the total time, it is determined to be a "gentle slope + multiple braking" disturbance condition.

[0014] Preferably, after determining the "gentle slope + multiple braking" disturbance condition, the first analysis unit extracts the acceleration / deceleration intensity, braking frequency, slope angle, and time window length to construct the load disturbance index Ld.

[0015]

[0016] in, This represents the intensity of acceleration or deceleration of the vehicle in the i-th second. This represents the braking frequency of the vehicle per unit time at second i. This represents the slope of the road where the vehicle is located at second i; n is the number of sampling points within the evaluation time.

[0017] If the load disturbance index Ld > 1.2, it indicates that the vehicle is at risk of increased load on the drive system due to the superposition of gradient, acceleration and frequent braking under the current operating conditions, triggering the first warning command.

[0018] Preferably, the load disturbance scenario determination module further includes a low-speed U-turn identification unit, a wheel speed difference analysis unit, and a second analysis unit;

[0019] The low-speed U-turn recognition unit is used to collect the vehicle's yaw angle and linear velocity v, collect the vehicle's GPS trajectory point time series and the yaw angle output by the IMU, and calculate the steering angle change rate ω based on the time series.

[0020]

[0021] in, This represents the yaw angle in the i-th second. This represents the heading angle at the (i-1)th second. Indicates the sampling period;

[0022] When the rate of change of steering angle ω > 30° / s and the vehicle linear speed v < 10km / h, it is determined to be a "low-speed turn or U-turn" state.

[0023] The wheel speed difference analysis unit is used to collect the vehicle's GPS trajectory points and steering angle information, while simultaneously collecting real-time rotational speed data of the front and rear wheels to obtain the front wheel speed. and rear wheel speed Calculate the instantaneous speed difference Δv between the front and rear wheels. If the instantaneous speed difference Δv between the front and rear wheels is greater than 8 km / h and the duration exceeds 1 second, it is determined to be a state of "inconsistent front and rear wheel drive".

[0024] If both the "low-speed turning or U-turn" and "front and rear wheel drive inconsistency" conditions are met simultaneously, it is identified as a differential drive offset condition.

[0025] After identifying the differential drive offset condition, the instantaneous speed difference Δv between the front and rear wheels, the rate of change of steering angle ω, and the vehicle linear speed v are extracted through the second analysis unit to construct the differential offset index Sd. The differential offset index Sd is then normalized to the range of [0,1] to obtain the normalized differential offset index Sd'.

[0026] If the normalized differential offset index Sd' > 0.8, it indicates that there is a potential risk of steering load deviation in the current drive system, and a second warning command is output.

[0027] Preferably, the load disturbance scenario determination module also includes a water immersion condition identification unit, a motor anomaly detection unit, and a third analysis unit;

[0028] The wading condition identification unit is used to determine whether a vehicle is in a wading, flooded, or muddy road environment by using wheel humidity sensors, tire slip ratio, or road adhesion coefficient. If any one of these conditions is met, the vehicle is identified as being in a "wading condition," including:

[0029] The ambient humidity (RH) under the wheels is ≥90%.

[0030] The water level sensor detects a water level ≥ 1 / 2 of the wheel hub height;

[0031] The motor anomaly detection unit is used to simultaneously monitor the instantaneous motor speed Z and output current I when the vehicle is determined to be in a "water-crossing" state, and to construct the speed change rate at the i-th second. and current surge rate :

[0032]

[0033]

[0034] in, and This represents the instantaneous rotational speed of the motor in the i-th second and the previous second; and This represents the motor output current in the i-th second and the previous second;

[0035] The motor is considered to be in an "abnormal" state if any of the following conditions are met:

[0036] A1. If the motor speed drops by ≥30% within 1 second, the expression is: ;

[0037] A2. If the current suddenly increases by ≥40% within the same cycle, the expression is: ;

[0038] A3 <100 rpm, while the output current I is greater than or equal to 80% of the rated current;

[0039] A4. The wheel speed is not equal to 0, but the motor output power is 0, resulting in "drag and slip" behavior;

[0040] If both the "water-related operating condition" and "motor abnormality" conditions are met simultaneously, it is identified as a "motor obstruction disturbance condition." The third analysis unit then extracts the rate of change of rotational speed and the rate of increase of current per unit time; constructs the motor obstruction index Bd; and normalizes the motor obstruction index Bd to the range [0,1] to obtain the normalized motor obstruction index. ;

[0041] If three consecutive seconds A value greater than 0.25 indicates that the motor is under continuous obstruction and disturbance, which continues to worsen and poses a risk of the motor being in an overload or seizing critical state, triggering the third warning command.

[0042] Preferably, the load disturbance scenario determination module further includes an environmental condition monitoring unit, a road condition attachment identification unit, and a fourth analysis unit;

[0043] The environmental condition monitoring unit is used to collect data from the vehicle's temperature and humidity sensors. When the ambient temperature is below -5°C or the relative humidity is above 95%, it is determined to be an "extremely cold or humid environment".

[0044] The road condition adhesion recognition unit is used to collect the tire longitudinal acceleration change rate and yaw rate γ;

[0045] If the longitudinal acceleration change rate of the tire is less than 0.5 m / s² and the yaw rate γ is ≥ 35° / s, it is judged as a "low adhesion coefficient road surface".

[0046] If either "extremely cold or humid environment" or "low-adhesion road surface" is met, it is identified as an environmental disturbance condition.

[0047] In this case, the tire radius R, wheel angular velocity Ww, and vehicle linear velocity v are extracted using the fourth analysis unit to construct the tire slip ratio Ed.

[0048] If the tire slip ratio Ed > 0.3, it is considered that the current environment poses a risk of interference to the stability of drive control, and a fourth warning command is output.

[0049] Preferably, the regulation effectiveness evaluation module includes a topology reconstruction unit and a dynamic response error analysis unit;

[0050] The topology reconfiguration unit, upon receiving the first, second, third, and fourth warning commands, executes the following corresponding topology reconfiguration commands to control the converter:

[0051] Adjust the inverter input power, limit the maximum output torque, dynamically adjust the front and rear wheel drive force distribution, perform differential compensation, limit the maximum steering angular velocity, limit the maximum allowable motor current, and adjust the input frequency and sensitivity of the traction control system (TCS) and the anti-lock braking system (ABS).

[0052] Preferably, the dynamic response error analysis unit is used to collect the converter output power, voltage response, motor control accuracy, and power device thermal characteristic data after the converter executes the corresponding topology reconfiguration command, and calculate the regulation deviation index Pd, thermal response offset index Hd, and power stability index Wd. If the regulation deviation index Pd, thermal response offset index Hd, and power stability index Wd exceed the corresponding response deviation threshold, the first correction signal is output.

[0053] Preferably, the regulation effectiveness assessment module includes a first correlation unit and a second correlation unit;

[0054] The first associated unit is used to receive the load disturbance index Ld, differential offset index Sd, motor resistance index Bd, and tire slip ratio Ed, and obtain the weighted sum of disturbance indexes Dsum by weighted summation. If no determination is made, the corresponding value is equal to 0.

[0055] The second related unit is used to combine the control deviation index Pd, the thermal response offset index Hd, and the power stability index Wd, obtain the weighted sum of feedback-type indices Fsum through weighted summation, and combine it with the weighted sum of disturbance-type indices Dsum to calculate the topology adaptability score coefficient Rt of the converter under the current operating state:

[0056]

[0057] and These are the control weight coefficients for the disturbance index weighted sum Dsum and the feedback index weighted sum Fsum, respectively.

[0058] Preferably, the regulation effectiveness evaluation module further includes a correction unit, which is used for comparison with a preset adaptability threshold X.

[0059] If Rt < X, then the second determination correction signal is output. Based on the difference between the adaptability threshold X and the topology adaptability score coefficient Rt, the correction unit successively lowers the power limit, current limit, torque distribution or intervention sensitivity parameters by 3% to 5% until Rt ≥ X.

[0060] This invention provides an adaptive converter topology reconfiguration and intelligent control system for load fluctuations. It offers the following advantages:

[0061] This invention achieves accurate identification and grading of complex load disturbances during electric vehicle operation through multi-dimensional sensor data fusion, significantly improving the system's adaptability to various operating conditions such as slope changes, frequent braking, turning, and wading. It employs a comprehensive evaluation using multiple indicators, including load disturbance index Ld, differential offset index Sd, motor resistance index Bd, and tire slip rate Ed, to promptly trigger multi-level warnings and effectively avoid safety hazards such as motor overload, lock-up, and tire slippage. Through a dynamic output of targeted topology reconfiguration commands via a control effectiveness evaluation module, combined with real-time collected power, temperature, and motor control accuracy data, it constructs a control deviation index Pd, a thermal response offset index Hd, and a power stability index Wd, achieving closed-loop adaptive control. The system features a topology adaptability score feedback mechanism, which intelligently corrects control parameters based on operating status, improving the converter's robustness and energy efficiency, and extending equipment lifespan. Overall, this invention effectively solves the problem of traditional converters lacking dynamic topology adjustment and real-time feedback, significantly improving the safety, stability, and energy utilization of electric vehicle power systems, and meeting the practical application needs under complex and variable road conditions. Attached Figure Description

[0062] Figure 1 This is a schematic diagram of the converter topology reconfiguration and intelligent control system for adaptive load fluctuations according to the present invention. Detailed Implementation

[0063] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0064] Example 1

[0065] Please see Figure 1 This invention provides an adaptive converter topology reconfiguration and intelligent control system for load fluctuations.

[0066] The load scenario perception module is used to collect vehicle operation data and external environmental parameters during the operation of the electric vehicle. The vehicle operation data includes speed, acceleration, current, voltage and wheel speed, and the environmental parameters include temperature, humidity and road condition information. The data is obtained by sampling and measurement from the speed, acceleration, current, voltage and angle sensors built into the electric two-wheeler and the external temperature and humidity sensors.

[0067] The load disturbance scenario determination module identifies the following load disturbance scenarios based on the collected vehicle operation data and external environmental parameters: When the vehicle is identified as being in an urban gentle slope area with frequent braking, a load disturbance index Ld is constructed; when the vehicle is identified as being in a low-speed U-turn or turning process with a significant difference in front and rear wheel speeds, a differential offset index Sd is constructed to describe the degree of inconsistency between front and rear wheel drive; when the vehicle is detected as being in a water-wading condition with a sudden drop in motor speed and a sudden increase in current, a motor resistance index Bd is constructed to characterize the degree of motor lock-up or resistance; when the vehicle is detected as being in an environment with extremely cold or wet road conditions, a tire slip ratio Ed is constructed to characterize the degree of environmental disturbance.

[0068] The load disturbance index Ld, differential deviation index Sd, motor resistance index Bd, and tire slip ratio Ed are evaluated to obtain corresponding warning instructions;

[0069] The regulation effectiveness evaluation module is used to receive corresponding early warning commands, generate corresponding topology reconfiguration commands, and synchronously collect converter output power, voltage response, motor control accuracy, and power device thermal characteristic data after execution. This is used to construct and evaluate the regulation deviation index Pd, thermal response offset index Hd, and power stability index Wd. If any one of them fails to meet the requirements, a topology adaptability score coefficient Rt is constructed to correct the corresponding topology reconfiguration command.

[0070] In this embodiment, the present invention achieves accurate identification and classification of complex load disturbances during electric vehicle operation through multi-dimensional sensor data fusion, significantly improving the system's adaptability to various operating conditions such as slope changes, frequent braking, turning, and wading. By comprehensively evaluating multiple indicators such as load disturbance index Ld, differential offset index Sd, motor resistance index Bd, and tire slip rate Ed, multi-level early warnings can be triggered in a timely manner, effectively avoiding safety hazards such as motor overload, lock-up, and tire slippage. Through a dynamic output of targeted topology reconfiguration commands by the control effectiveness evaluation module, combined with real-time collected power, temperature, and motor control accuracy data, control deviation index Pd, thermal response offset index Hd, and power stability index Wd are constructed, achieving closed-loop adaptive control. The system possesses a topology adaptability score feedback mechanism, which can intelligently correct control parameters according to the operating status, improving the robustness and energy efficiency of the converter and extending equipment life. Overall, the present invention effectively solves the problem of traditional converters lacking dynamic topology adjustment and real-time feedback, significantly improving the safety, stability, and energy utilization of the electric vehicle power system, and meeting the practical application needs under complex and variable road conditions.

[0071] Example 2

[0072] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1Specifically, the load disturbance scenario determination module includes a gentle slope area identification unit, a frequent braking identification unit, and a first analysis unit;

[0073] The gentle slope area identification unit is used to obtain the vehicle pitch angle Wp using the vehicle's built-in inertial measurement IMU. When the vehicle pitch angle Wp > 3°, it is determined that the vehicle has entered the "gentle slope" state.

[0074] The frequent braking identification unit is used to collect the vehicle's braking signals and count the braking frequency f per unit time. If the braking frequency f is ≥ 3 times within a time window of T=10 seconds, or the braking duration is > 40% of the total time, it is determined to be a "multiple braking" state.

[0075] If the vehicle pitch angle Wp exceeds 3° and the braking frequency f≥3, or the braking duration exceeds 40% of the total time, it is determined to be a "gentle slope + multiple braking" disturbance condition.

[0076] The first analysis unit, after determining the "gentle slope + multiple braking" disturbance condition, extracts acceleration / deceleration intensity, braking frequency, slope angle, and time window length to construct the load disturbance index Ld.

[0077]

[0078] in, This represents the intensity of acceleration or deceleration of the vehicle in the i-th second. This represents the braking frequency of the vehicle per unit time at second i. This represents the slope of the road where the vehicle is located at second i; n is the number of sampling points within the evaluation time.

[0079] If the load disturbance index Ld > 1.2, it indicates that the vehicle is at risk of increased load on the drive system due to the superposition of gradient, acceleration and frequent braking under the current operating conditions, triggering the first warning command.

[0080] The threshold of 1.2 was determined by analyzing the relationship between drive system load and failure rate under different road conditions through extensive real-world road testing and collected vehicle operating data. Experimental results show that when Ld exceeds 1.2, the load on the vehicle drive system increases significantly, and the risk of failure or anomalies rises dramatically. Based on industry standards and the rated performance of electric vehicle motors and converters, a safety threshold of 1.2 was set to ensure that the sensitivity covers most high-load conditions while avoiding frequent false alarms that trigger protection, thus ensuring stable system operation.

[0081] The following is an example table of data collected from electric vehicles after determining the "gentle slope + multiple braking" disturbance condition, identifying the load disturbance index Ld for 10 seconds:

[0082]

[0083] Calculated according to Table 1 :

[0084] First second: 0.8 × 0.2 × 4.5 = 0.72;

[0085] Second second: 1.0 × 0.3 × 5.0 = 1.5;

[0086] ...10th second: 0.8 × 0.3 × 5.2 = 1.248;

[0087] Then calculate all and take the average:

[0088] (0.72+1.5+1.98+1.872+0.672+1.65+0.918+1.944+1.59+1.248) / 10=1.3104;

[0089] In this real-time scenario, the present invention integrates a gentle slope area identification unit and a frequent braking identification unit, combining vehicle inertial measurement data and braking signals to achieve accurate judgment of complex operating conditions involving "gentle slope + multiple braking". It employs multi-dimensional indicators such as vehicle pitch angle, braking frequency, and braking duration for comprehensive judgment, avoiding misjudgments caused by single parameters and improving the accuracy and robustness of disturbance scene recognition. Based on real-time collected acceleration / deceleration intensity, braking frequency, and slope angle, a load disturbance index Ld is constructed to quantify the degree of load disturbance, enabling dynamic assessment of the load risk of the vehicle drive system.

[0090] By performing multiplication and averaging of continuously sampled data using multiple indicators, the system can reflect the comprehensive impact of load fluctuations and promptly detect increased stress in the drive system caused by the combined effects of gradient and frequent braking. If the Ld value exceeds 1.2, the system can quickly trigger the first warning command, reminding the control module to activate corresponding protective measures. This method effectively avoids the limitations of traditional single-factor judgment, improves the safety and reliability of electric vehicle power systems under complex road conditions, significantly reduces the failure risk of motors and converters, extends equipment life, and enhances the user's driving experience.

[0091] Example 3

[0092] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the load disturbance scenario determination module also includes a low-speed U-turn identification unit, a wheel speed difference analysis unit, and a second analysis unit;

[0093] The low-speed U-turn recognition unit is used to collect the vehicle's yaw angle and linear velocity v, collect the vehicle's GPS trajectory point time series and the yaw angle output by the IMU, and calculate the steering angle change rate ω based on the time series.

[0094]

[0095] in, This represents the yaw angle in the i-th second. This represents the heading angle at the (i-1)th second. Indicates the sampling period;

[0096] When the rate of change of steering angle ω > 30° / s and the vehicle linear speed v < 10km / h, it is determined to be a "low-speed turn or U-turn" state.

[0097] The wheel speed difference analysis unit is used to collect the vehicle's GPS trajectory points and steering angle information, while simultaneously collecting real-time rotational speed data of the front and rear wheels to obtain the front wheel speed. and rear wheel speed Calculate the instantaneous speed difference Δv between the front and rear wheels. If the instantaneous speed difference Δv between the front and rear wheels is greater than 8 km / h and the duration exceeds 1 second, it is determined to be a state of "inconsistent front and rear wheel drive".

[0098]

[0099] If both the "low-speed turning or U-turn" and "front and rear wheel drive inconsistency" conditions are met simultaneously, it is identified as a differential drive offset condition.

[0100] After identifying the differential drive offset condition, the second analysis unit extracts the instantaneous speed difference Δv between the front and rear wheels, the rate of change of the steering angle ω, and the vehicle linear velocity v to construct the differential offset index Sd.

[0101]

[0102] in, This represents the normalized proportion of the instantaneous speed difference between the front and rear wheels to the overall vehicle linear velocity. Let ϵ represent the rate of change of the steering angle in the i-th second, where ϵ is a small constant to prevent the denominator from being 0, and n is the number of sampling points within the evaluation period; the product represents the intensity of the differential speed disturbance at a certain moment, and the summation and averaging yield the overall disturbance intensity; and the differential speed deviation index Sd is normalized to the range of [0,1] to obtain the normalized differential speed deviation index Sd': in, This indicates the maximum reference disturbance value for differential offset, for example, 50;

[0103] If the normalized differential offset index Sd' > 0.8, it indicates a potential risk of steering load deviation in the current drive system, and a second warning command is output. The 0.8 setting is based on sampling and analysis of a large amount of vehicle data in low-speed turning and U-turn scenarios. It was found that when Sd' reaches 0.8 or higher, the torque difference between the front and rear wheels is sufficient to affect the vehicle's yaw stability, the ESP control frequency increases significantly, and there is a stability control pressure boundary.

[0104] The following is an example table 2 of the data collected from electric vehicles after determining the differential drive offset disturbance condition, identifying the differential offset index Sd for 10 seconds:

[0105] Table 2 is as follows:

[0106]

[0107]

[0108] in, This represents the normalized proportion of the instantaneous speed difference between the front and rear wheels to the overall vehicle linear velocity. The product represents the intensity of the differential disturbance at a certain moment, and the summation and averaging yields the overall disturbance intensity.

[0109] In the formula, ϵ is a small constant to prevent the denominator from being 0, and n is the number of sampling points within the evaluation period;

[0110] Calculated according to Table 2 ,set up =0.1

[0111] First second: =70.6;

[0112] 2nd second: =68.3;

[0113] ...10th second: =36.6;

[0114] Then calculate all and take the average:

[0115] (70.6+68.3+44.6+40.2+36.5+43.3+32.3+25.6+34.1+36.6) / 10=43.10;

[0116] In this embodiment, by introducing a low-speed U-turn recognition unit and a wheel speed difference analysis unit, the system can accurately identify situations where the front and rear wheel drives are inconsistent during low-speed steering, avoiding the control lag problem caused by the inability of traditional systems to accurately perceive the speed difference between wheels during steering. The introduction of the differential offset index Sd helps to quantify the dynamic evolution trend of the torque distribution deviation between wheels, and by comparing the normalized result Sd' with a threshold, targeted control strategies (such as adjusting the torque between wheels, improving ESP response sensitivity, etc.) can be triggered, effectively reducing the risks of decreased vehicle stability, slippage, or increased energy consumption caused by steering interference. This mechanism improves the handling safety and energy efficiency stability of two-wheeled electric vehicles in complex urban U-turns, narrow road turns, and slippery curves.

[0117] Example 4

[0118] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the load disturbance scenario determination module also includes a water immersion condition identification unit, a motor anomaly detection unit, and a third analysis unit;

[0119] The wading condition identification unit is used to determine whether a vehicle is in a wading, flooded, or muddy road environment by using wheel humidity sensors, tire slip ratio, or road adhesion coefficient. If any one of these conditions is met, the vehicle is identified as being in a "wading condition," including:

[0120] The ambient humidity (RH) under the wheels is ≥90%.

[0121] The water level sensor detects a water level ≥ 1 / 2 of the wheel hub height;

[0122] The motor anomaly detection unit is used to simultaneously monitor the instantaneous motor speed Z and output current I when the vehicle is determined to be in a "water-crossing" state, and to construct the speed change rate at the i-th second. and current surge rate :

[0123]

[0124]

[0125] in, and This represents the instantaneous rotational speed of the motor in the i-th second and the previous second; and This represents the motor output current in the i-th second and the previous second;

[0126] The motor is considered to be in an "abnormal" state if any of the following conditions are met:

[0127] A1. If the motor speed drops by ≥30% within 1 second, the expression is: If the motor speed drops by more than 30% within one second, it indicates a sudden increase in load, possibly caused by tire resistance in water, foreign objects in the water, or mechanical jamming. The motor almost stops, but the system still attempts to maintain rotation. If the speed is 300 rpm at a certain moment and drops to 180 rpm the next second, the speed has dropped by 40%, and the condition is met. In complex scenarios such as wading, being stuck by foreign objects, climbing a slope and braking, the motor may be "hard stopped," but the system has not yet detected a complete stop. The motor's attempt to maintain rotation is an "unplanned deceleration" signal, a precursor to obstruction or seizure.

[0128] A2. If the current suddenly increases by ≥40% within the same cycle, the expression is: When the motor encounters resistance or jamming, it increases the output current to maintain rotation, causing a sudden surge in load current. This surge indicates that the system interprets the "speed drop" as being caused by increased load and attempts to drive with greater force; this is an "overdrive" signal, indicating that the system is fighting against resistance or a fault. When the load suddenly increases (such as due to mud, water pressure, or malfunction of the braking system), the controller does not immediately limit the output but attempts to maintain the speed with greater torque; this "counteracting behavior" usually occurs at the lock-up critical point or under system misjudgment, reflecting a potential anomaly.

[0129] A3 <100 rpm, while the output current I is greater than or equal to 80% of the rated current; this is the condition of "the motor is almost not turning, but is still outputting a large current"; it means that "although the speed is very low", the system is still outputting a high current to try to drive ⇒ standard seizure precursor or already in seizure state.

[0130] A4. If the wheel speed is not equal to 0, but the motor output power is 0, resulting in "drag and slip" behavior, this indicates that the motor has failed but the wheel is still being driven by an external force. For example, when going downhill or wading through water, the wheel is rolled by the water flow or inertia, but the motor does not provide power output. It may also be a "reverse drag" state of the motor, that is, the wheel is turning but the motor is not doing work under no load. If the wheel speed is not equal to 0 and the motor output power is 0 for a long time, and A1 or A2 was previously met, it can be determined that "the system has entered a protective disengagement state", which indirectly reflects "the consequences of obstruction".

[0131] If both the "water-related operating condition" and "motor abnormality" conditions are met simultaneously, it is identified as a "motor obstruction disturbance condition." The third analysis unit then extracts the rate of change of rotational speed and the rate of current surge per unit time; and constructs the motor obstruction index Bd.

[0132]

[0133] Where u and The rate of change of rotational speed in the i-th second are respectively and current surge rate The weights are determined; and the motor resistance index Bd is normalized to the range of [0,1] to obtain the normalized motor resistance index. : in, This indicates the maximum reference disturbance value for the motor under resistance, set to 0.35; , ;

[0134] If three consecutive seconds A value greater than 0.25 indicates that the motor is under continuous obstruction and disturbance, which continues to worsen and poses a risk of the motor being in an overload or seizing critical state, triggering the third warning command.

[0135] The basis for the claim that the ambient humidity (RH) under the wheels is ≥90% is as follows: RH (Relative Humidity) exceeding 90% usually indicates a relatively humid environment with significant surface dampness, condensation, or water accumulation, often accompanied by a decrease in the coefficient of friction between the tires and the ground. In vehicle anti-skid control systems (such as ABS / TCS), RH >90% is often considered a critical value used to judge rainy weather, water accumulation, or slippery road conditions. When the water depth reaches more than half the wheel hub, the vehicle's chassis electronic control system and exposed motor components may be submerged.

[0136] A sudden drop in motor speed of ≥30% is a typical critical point for overload precursors. Analysis of multiple sets of wading and climbing sudden stop conditions revealed that a sudden drop in speed of more than 30% will significantly increase the probability of a sudden current surge. Generally, drive control systems can accept a sudden current surge of 10%-20%. If the surge is ≥40%, it usually exceeds the safety redundancy and poses a risk of short-term overheating.

[0137] Sources with speed <100rpm and current ≥80% of rated current were tested under three working conditions: congestion, uphill, and wading. The motor will overheat or automatically disengage after the <100rpm + high current state usually lasts for 1-2 seconds.

[0138] If three consecutive seconds With a value greater than 0.25, the normalization upper limit of Bd is set to 0.35. Therefore, 0.25 accounts for approximately 71% of the disturbance intensity, which has a high warning significance. Setting a 3-second delay avoids single-point false triggering and ensures that the judgment is made under continuous disturbance conditions. The 3-second delay can give the controller room to adjust its response, such as limiting current, disconnecting the output or disconnecting the drive.

[0139] After determining the "motor under obstructed disturbance condition", samples were collected from the electric vehicle to identify the rate of change of rotational speed over 5 seconds. and current surge rate Example data table 3:

[0140] Table 3 is as follows:

[0141]

[0142] In this embodiment, by introducing a "water wading condition identification unit" and a "motor anomaly detection unit" on the basis of traditional load disturbance monitoring, it can effectively identify the high-risk "motor obstruction" conditions faced by electric vehicles when driving on water, mud, or low-adhesion surfaces. By introducing real-time linkage analysis of motor speed change rate and current surge rate, it can accurately capture overload signs of the motor under abnormal loads, such as "pre-lock-up signs" or "drag and slip" states.

[0143] Furthermore, by integrating composite indicators such as ambient humidity, water level, and discrepancies between wheel speed and power, the system constructs a more realistic and interpretable operating condition identification logic, significantly improving the system stability and control safety of electric two-wheelers in complex urban environments, flooded areas, downhill slopes, and muddy roads. The introduction of this mechanism effectively reduces the risks of motor overheating, control misjudgments, and system damage caused by obstructions.

[0144] Example 5

[0145] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the load disturbance scenario determination module also includes an environmental status monitoring unit, a road condition attachment identification unit, and a fourth analysis unit;

[0146] The environmental condition monitoring unit is used to collect data from the vehicle's temperature and humidity sensors. When the ambient temperature is below -5°C or the relative humidity is above 95%, it is determined to be an "extremely cold or humid environment".

[0147] The road condition adhesion recognition unit is used to collect the tire longitudinal acceleration change rate and yaw rate γ;

[0148] If the longitudinal acceleration change rate of the tire is less than 0.5 m / s² and the yaw rate γ is ≥ 35° / s, it is judged as a "low adhesion coefficient road surface".

[0149] If either "extremely cold or humid environment" or "low-adhesion road surface" is met, it is identified as an environmental disturbance condition.

[0150] In this case, the tire radius R, wheel angular velocity Ww, and vehicle linear velocity v are extracted using the fourth analysis unit to construct the tire slip ratio Ed.

[0151]

[0152] Tire slip ratio Ed reflects the degree of slippage between the tire and the road surface;

[0153] If the tire slip ratio Ed > 0.3, it is considered that the current environment poses a risk of interference to the stability of drive control, and a fourth warning command is output.

[0154] In this embodiment, by introducing an environmental condition monitoring unit and a road condition adhesion recognition unit, the system achieves active identification and classification modeling of high-risk driving environments such as extremely cold, humid, and low-adhesion road surfaces. The system can not only monitor environmental parameters such as temperature and humidity in real time, but also accurately determine the road condition adhesion status by combining vehicle kinematic characteristics (such as tire acceleration change rate and yaw rate), thereby effectively identifying complex conditions that can easily cause tire slippage or loss of steering control, such as ice and snow, water accumulation, slippery surfaces, or mud and sand coverings.

[0155] Based on this, by constructing a tire slip ratio (Ed) index, the system can quantify the degree of slippage between the tire and the road surface, achieving closed-loop control from perception to risk quantification. When Ed exceeds the threshold, the system can issue a warning signal immediately and coordinate control strategies, significantly improving the vehicle's driving safety, stability, and handling precision under special road conditions.

[0156] Example 6

[0157] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the regulation effectiveness evaluation module includes a topology reconstruction unit and a dynamic response error analysis unit;

[0158] The topology reconfiguration unit, upon receiving the first, second, third, and fourth warning commands, executes the following corresponding topology reconfiguration commands to control the converter:

[0159] The system adjusts the inverter input power, limits the maximum output torque, dynamically adjusts the front and rear wheel drive force distribution, performs differential compensation, limits the maximum steering angular velocity, limits the maximum allowable motor current, and adjusts the traction control system. Specifically, the topology reconfiguration commands not only cover inverter power regulation, front and rear wheel drive dynamic compensation, and the triggering of the motor's protective disengagement mechanism, but also include the linkage parameter adjustment of the entire vehicle safety control system such as TCS and ABS, thereby achieving coordinated control of the "electronic control system-drive unit-vehicle stability system". Combined with the feedback evaluation mechanism of the dynamic response error analysis unit, the system continuously optimizes the control strategy, improving the vehicle's operational stability, safety, and thermal management capabilities under disturbed conditions, significantly enhancing the electric vehicle's adaptability in complex urban traffic and extreme environments, and improving the ABS input frequency and sensitivity.

[0160] When the load disturbance index Ld exceeds 1.2, the system determines that there is a risk of overload. The control strategy is to limit the converter output power to 80% to 90% of the rated power, while enhancing the energy feedback braking capability, increasing the feedback energy by 10% to 15%, and starting the cooling system to prevent the equipment from overheating. Based on this, the first topology reconfiguration command is generated.

[0161] When the normalized differential offset index Sd' exceeds 0.8, it is determined that there is a risk of steering load deviation. The control strategy is to dynamically adjust the front and rear wheel drive forces, adjust the torque difference between wheels by ±10% to 15%, and increase the sensitivity of the Electronic Stability Program (ESP) intervention by about 10%. By adjusting the relevant control parameters, the vehicle handling is optimized, thereby generating the second topology reconfiguration command.

[0162] When the motor is resisted, the index If the value exceeds 0.25 for three consecutive seconds, it indicates that the motor is in a state of continuous obstruction and overload risk. The control strategy is to limit the maximum allowable current of the motor to 70% to 85% of the rated current, reduce the drive force output to 50% to 70%, and activate the protective de-drive mechanism to prevent the motor from seizing. At the same time, a fault warning is issued, and the third topology reconfiguration command is triggered based on this.

[0163] When the tire slip ratio Ed exceeds 0.3, it is determined that there is a significant risk of tire slippage in the environment. The control strategy is to reduce the converter output torque to 60% to 75% of the rated torque, increase the intervention frequency and sensitivity of the traction control system (TCS) and anti-lock braking system (ABS) by 15% to 25%, and adjust the parameters of the vehicle stability control system (VSC) to ensure vehicle driving safety, thereby generating the fourth topology reconfiguration command.

[0164] In this embodiment, the present invention, by setting a topology reconfiguration unit in the control effectiveness evaluation module, can generate differentiated and targeted topology reconfiguration instruction sets for various typical disturbance risks (such as load overload, differential speed deviation, motor obstruction, and tire slippage), thereby achieving real-time control optimization of the converter. Compared with traditional control systems that only use static strategies to deal with complex operating conditions, this unit can automatically adjust power output, torque distribution, current limiting, and drive response according to the actual scenario, realizing adaptive evolution and local reconfiguration of the control strategy.

[0165] Specifically, the topology reconfiguration command not only covers the triggering of inverter power regulation, front and rear wheel drive dynamic compensation, and motor protective disengagement mechanisms, but also includes the linkage parameter adjustment of vehicle safety control systems such as TCS and ABS, thereby achieving coordinated control of the "electronic control system-drive unit-vehicle stability system". Combined with the feedback evaluation mechanism of the dynamic response error analysis unit, the system can continuously optimize the control strategy, improve the vehicle's operational stability, safety, and thermal management capabilities under disturbed conditions, and significantly enhance the adaptability of electric vehicles in complex urban traffic and extreme environments.

[0166] Example 7

[0167] This embodiment is an explanation based on Embodiment 6. Please refer to it. Figure 1Specifically, the dynamic response error analysis unit is used to collect data on the converter's output power, voltage response, motor control accuracy, and power device thermal characteristics after the converter executes the corresponding topology reconfiguration command. It calculates the regulation deviation index Pd, thermal response offset index Hd, and power stability index Wd. If the regulation deviation index Pd, thermal response offset index Hd, and power stability index Wd exceed the corresponding response deviation threshold, the first correction signal is output.

[0168] The formulas for calculating the regulation deviation index Pd, the thermal response offset index Hd, and the power stability index Wd are as follows:

[0169]

[0170]

[0171]

[0172] in, This represents the actual output power collected at time j. This represents the expected output power at time j. This represents the total number of output power samples taken during the evaluation period. The higher the Pd value, the worse the control command execution effect and the more obvious the power deviation. When Pd > 0.1, it indicates that the control effect is unqualified.

[0173] in, This represents the actual temperature of the power device collected at time j. This represents the expected temperature at time j. This indicates the total number of temperature samples taken during the evaluation period; the higher the hd value, the worse the temperature rise response deviation caused by the control command. When Pd > 0.08, it indicates that the control effect is unqualified.

[0174] in, This represents the actual output power collected at time j. This represents the average output power during the evaluation period.

[0175] Wd reflects the power output stability of the converter under disturbance conditions. The smaller the Wd, the more stable the output. If Wd > 0.12, it indicates that there may be electromagnetic interference or control delay in the system.

[0176] 0.1, 0.08, and 0.12 are the corresponding response deviation thresholds;

[0177] In this embodiment, the present invention, by setting up a dynamic response error analysis unit, can collect key operating response parameters in real time after the converter executes the topology reconfiguration command. These parameters include output power, voltage fluctuation, motor control accuracy, and thermal behavior of power devices. Based on these parameters, a regulation deviation index Pd, a thermal response offset index Hd, and a power stability index Wd are constructed to achieve quantitative evaluation and error determination of the control strategy execution effect. Compared with traditional control schemes that judge the effectiveness of the system solely based on the final output or subjective experience, this analysis unit realizes digital and indexed feedback of the entire dynamic response process, possessing higher accuracy and adaptability.

[0178] By setting corresponding response deviation thresholds, the system can quickly identify whether the current topology reconfiguration strategy is at risk of execution failure or insufficient adaptation. When any of the indicators Pd, Hd, or Wd exceeds the preset range, the first correction signal is output, providing a decision-making basis for subsequent strategy correction or Rt score adjustment, thereby constructing a closed-loop control process of "identification-execution-evaluation-correction". This mechanism significantly improves the converter's control stability, autonomous adaptability, and thermal safety assurance level under complex disturbance conditions.

[0179] Example 8

[0180] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the regulation effectiveness assessment module includes a first related unit and a second related unit;

[0181] The first associated unit is used to receive the load disturbance index Ld, differential offset index Sd', and motor resistance index. The tire slip ratio Ed is used to obtain the weighted sum of disturbance-type indices Dsum through weighted summation. If no determination is made, the corresponding value is equal to 0.

[0182]

[0183] In the formula, , , and These are the load disturbance index Ld, the normalized differential speed deviation index Sd', and the normalized motor resistance index. The weights of the tire slip ratio Ed are given; and the sum of the weights equals 1.

[0184] The second related unit is used to combine the regulation deviation index Pd, the thermal response offset index Hd, and the power stability index Wd, and obtain the weighted sum of feedback-type indices Fsum through weighted summation:

[0185]

[0186] In the formula, , and These are the weight values ​​for the regulation deviation index Pd, the thermal response offset index Hd, and the power stability index Wd, respectively; and the sum of the weights is equal to 1.

[0187] By combining the disturbance-type exponential weighted sum Dsum and the feedback-type exponential weighted sum Fsum, the topology adaptability score coefficient Rt of the converter under the current operating state is calculated:

[0188]

[0189] and These are the control weight coefficients for the disturbance index weighted sum Dsum and the feedback index weighted sum Fsum, respectively.

[0190] In this embodiment, the first correlation unit weights and summarizes the load disturbance index Ld, differential offset index Sd, motor resistance index Bd, and tire slip ratio Ed to form a disturbance-type index weighted sum Dsum; and the second correlation unit weights and summarizes the control deviation index Pd, thermal response offset index Hd, and power stability index Wd to form a feedback-type index weighted sum Fsum. This bidirectional coupling constructs the topology adaptability score Rt, effectively reflecting the degree of matching between the intensity of external disturbances and the system's response capability. Each type of index can be configured with weight coefficients; for example, the weights for Ld, Sd, Bd, and Ed are respectively... , , and and This allows the system to adjust its focus based on actual application scenarios (such as urban roads, mountainous areas, rain, snow, and slippery conditions), enhancing the model's scalability and adaptability.

[0191] The weights were determined based on industry expert experience and engineering practice. Through on-site debugging and verification, the weight parameters were adjusted to adapt to specific application environments. Vehicle operation data under various typical road conditions and load disturbances were collected. Correlation analysis was used to evaluate the impact of each indicator on system performance, and the preliminary weights for each indicator were determined. , , and ; , and , and ;

[0192] The regulation effectiveness evaluation module also includes a correction unit, which is used for comparison with a preset adaptive threshold X.

[0193] If Rt < X, then the second determination correction signal is output. Based on the difference between the adaptability threshold X and the topology adaptability score coefficient Rt, the correction unit successively lowers the power limit, current limit, torque distribution or intervention sensitivity parameters by 3% to 5% until Rt ≥ X.

[0194] In this embodiment, a correction unit is introduced into the control effectiveness evaluation module to achieve dynamic adaptive adjustment of the converter topology reconfiguration command. A preset adaptability threshold X is used as the benchmark for judging system performance, ensuring continuous monitoring of the topology adaptability score coefficient Rt during operation. When Rt is lower than the threshold X, the system automatically triggers a correction mechanism, gradually making minor adjustments of 3% to 5% to key parameters such as power limiting, current limiting, torque distribution, and intervention sensitivity, thereby effectively eliminating potential deviations and deficiencies in the control strategy. This dynamic correction process enables the system to continuously optimize the control strategy based on real-time feedback, improving the converter's load response capability and thermal management level, preventing equipment overload and performance degradation, and enhancing the overall stability and safety of operation. Simultaneously, the step-by-step parameter reduction avoids system oscillations caused by excessive control amplitude, achieving smooth and efficient operation and maintenance. This technology significantly improves the adaptability and reliability of the electric vehicle drive system, ensuring safe driving and energy utilization efficiency of the vehicle under complex operating conditions.

[0195] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value, it is acceptable.

[0196] The above formulas are all derived from software simulation using a large amount of data, and are selected to be close to the actual values. The coefficients in the formulas are set by those skilled in the art according to the actual situation. The above are only preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or changes made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An adaptive load fluctuation converter topology reconfiguration and intelligent control system, applicable to two-wheeled electric vehicles, characterized in that: include: The load scenario perception module is used to collect vehicle operation data and external environmental parameters during the operation of the electric vehicle. The vehicle operation data includes speed, acceleration, current, voltage and wheel speed, and the environmental parameters include temperature, humidity and road condition information. The load disturbance scenario determination module identifies the following load disturbance scenarios based on the collected vehicle operation data and external environmental parameters: When the vehicle is identified as being in an urban gentle slope area with frequent braking, a load disturbance index Ld is constructed; when the vehicle is identified as being in a low-speed U-turn or turning process with a significant difference in front and rear wheel speeds, a differential offset index Sd is constructed to describe the degree of inconsistency between front and rear wheel drive; when the vehicle is detected as being in a water-wading condition with a sudden drop in motor speed and a sudden increase in current, a motor resistance index Bd is constructed to characterize the degree of motor lock-up or resistance; when the vehicle is detected as being in an environment with extremely cold or wet road conditions, a tire slip ratio Ed is constructed to characterize the degree of environmental disturbance. The load disturbance index Ld, differential deviation index Sd, motor resistance index Bd, and tire slip ratio Ed are evaluated to obtain corresponding warning instructions; The load disturbance scenario determination module includes a gentle slope area identification unit, a frequent braking identification unit, and a first analysis unit; The gentle slope area identification unit is used to obtain the vehicle pitch angle Wp using the vehicle's built-in inertial measurement IMU. When the vehicle pitch angle Wp > 3°, it is determined that the vehicle has entered the "gentle slope" state. The frequent braking identification unit is used to collect the vehicle's braking signal and count the braking frequency f per unit time. If the braking frequency f ≥ 3 times within a time window of T = 10 seconds, or the braking duration > 40% of the total time, it is determined to be a "multiple braking" state. If the vehicle pitch angle Wp exceeds 3° and the braking frequency f≥3, or the braking duration exceeds 40% of the total time, it is determined to be a "gentle slope + multiple braking" disturbance condition. After determining the "gentle slope + multiple braking" disturbance condition, the first analysis unit extracts the acceleration / deceleration intensity, braking frequency, slope angle, and time window length to construct the load disturbance index Ld. in, This represents the intensity of acceleration or deceleration of the vehicle in the i-th second. This represents the braking frequency of the vehicle per unit time at second i. This represents the slope of the road where the vehicle is located at second i; n is the number of sampling points within the evaluation time. If the load disturbance index Ld > 1.2, it indicates that the vehicle is at risk of increased load on the drive system due to the superposition of gradient, acceleration and frequent braking under the current working conditions, triggering the first warning command; The regulation effectiveness evaluation module is used to receive corresponding early warning commands, generate corresponding topology reconfiguration commands, and synchronously collect converter output power, voltage response, motor control accuracy, and power device thermal characteristic data after execution. This is used to construct and evaluate the regulation deviation index Pd, thermal response offset index Hd, and power stability index Wd. If any one of them fails to meet the requirements, a topology adaptability score coefficient Rt is constructed to correct the corresponding topology reconfiguration command.

2. The adaptive load fluctuation converter topology reconfiguration and intelligent control system according to claim 1, characterized in that, The load disturbance scenario determination module also includes a low-speed U-turn identification unit, a wheel speed difference analysis unit, and a second analysis unit. The low-speed U-turn recognition unit is used to collect the vehicle's yaw angle and linear velocity v, collect the vehicle's GPS trajectory point time series and the yaw angle output by the IMU, and calculate the steering angle change rate ω based on the time series: in, This represents the yaw angle in the i-th second. This represents the heading angle at the (i-1)th second. Indicates the sampling period; When the rate of change of steering angle ω > 30° / s and the vehicle linear speed v < 10km / h, it is determined to be a "low-speed turn or U-turn" state. The wheel speed difference analysis unit is used to collect the vehicle's GPS trajectory points and steering angle information, while simultaneously collecting real-time rotational speed data of the front and rear wheels to obtain the front wheel speed. and rear wheel speed Calculate the instantaneous speed difference Δv between the front and rear wheels. If the instantaneous speed difference Δv between the front and rear wheels is greater than 8 km / h and the duration exceeds 1 second, it is determined to be a state of "inconsistent front and rear wheel drive". If both the "low-speed turning or U-turn" and "front and rear wheel drive inconsistency" conditions are met simultaneously, it is identified as a differential drive offset condition. After identifying the differential drive offset condition, the instantaneous speed difference Δv between the front and rear wheels, the rate of change of steering angle ω, and the vehicle linear speed v are extracted through the second analysis unit to construct the differential offset index Sd. The differential offset index Sd is then normalized to the range of [0,1] to obtain the normalized differential offset index Sd'. If the normalized differential offset index Sd' > 0.8, it indicates that there is a potential risk of steering load deviation in the current drive system, and a second warning command is output.

3. The adaptive load fluctuation converter topology reconfiguration and intelligent control system according to claim 1, characterized in that, The load disturbance scenario determination module also includes a water immersion condition identification unit, a motor anomaly detection unit, and a third analysis unit; The wading condition identification unit is used to determine whether a vehicle is in a wading, flooded, or muddy road environment by using wheel humidity sensors, tire slip ratio, or road adhesion coefficient. If any one of these conditions is met, the vehicle is identified as being in a "wading condition," including: The ambient humidity (RH) under the wheels is ≥90%. The water level sensor detects a water level ≥ 1 / 2 of the wheel hub height; The motor anomaly detection unit is used to simultaneously monitor the instantaneous motor speed Z and output current I when the vehicle is determined to be in a "water-crossing" state, and to construct the speed change rate at the i-th second. and current surge rate : in, and This represents the instantaneous rotational speed of the motor in the i-th second and the previous second; and This represents the motor output current in the i-th second and the previous second; The motor is considered to be in an "abnormal" state if any of the following conditions are met: A1. If the motor speed drops by ≥30% within 1 second, the expression is: ; A2. If the current suddenly increases by ≥40% within the same cycle, the expression is: ; A3 <100 rpm, while the output current I is greater than or equal to 80% of the rated current; A4. When the wheel speed is not equal to 0, but the motor output power is 0, "drag and slip" behavior occurs. If both the "water-related operating condition" and "motor abnormality" conditions are met simultaneously, then it is identified as a "motor obstruction disturbance condition." The third analysis unit then extracts the rate of change of rotational speed and the rate of increase of current per unit time; constructs a motor obstruction index Bd; and normalizes the motor obstruction index Bd to the range [0,1] to obtain the normalized motor obstruction index. ; If three consecutive seconds A value greater than 0.25 indicates that the motor is under continuous obstruction and disturbance, which continues to worsen and poses a risk of the motor being in an overload or seizing critical state, triggering the third warning command.

4. The adaptive load fluctuation converter topology reconfiguration and intelligent control system according to claim 1, characterized in that, The load disturbance scenario determination module also includes an environmental status monitoring unit, a road condition attachment identification unit, and a fourth analysis unit; The environmental condition monitoring unit is used to collect data from the vehicle's temperature sensor and humidity sensor. When the ambient temperature is below -5°C or the relative humidity is above 95%, it is determined to be an "extremely cold or humid environment". The road condition adhesion recognition unit is used to collect the tire longitudinal acceleration change rate and yaw rate γ; When the longitudinal acceleration change rate of the tire is less than 0.5 m / s² and the yaw rate γ is ≥ 35° / s, it is judged as "low adhesion coefficient road surface"; If either "extremely cold or humid environment" or "low-adhesion road surface" is met, it is identified as an environmental disturbance condition. In this case, the tire radius R, wheel angular velocity Ww, and vehicle linear velocity v are extracted using the fourth analysis unit to construct the tire slip ratio Ed. If the tire slip ratio Ed > 0.3, it is considered that the current environment poses a risk of interference to the stability of drive control, and a fourth warning command is output.

5. The adaptive load fluctuation converter topology reconfiguration and intelligent control system according to claim 4, characterized in that, The regulation effectiveness evaluation module includes a topology reconstruction unit and a dynamic response error analysis unit; The topology reconfiguration unit, upon receiving the first, second, third, and fourth warning commands, is configured to execute the following corresponding topology reconfiguration commands by controlling the converter: Adjust the inverter input power, limit the maximum output torque, dynamically adjust the front and rear wheel drive force distribution, perform differential compensation, limit the maximum steering angular velocity, limit the maximum allowable motor current, and adjust the input frequency and sensitivity of the traction control system (TCS) and the anti-lock braking system (ABS).

6. The adaptive load fluctuation converter topology reconfiguration and intelligent control system according to claim 5, characterized in that, The dynamic response error analysis unit is used to collect the converter output power, voltage response, motor control accuracy, and power device thermal characteristic data after the converter executes the corresponding topology reconfiguration command, and calculate the regulation deviation index Pd, thermal response offset index Hd, and power stability index Wd. If the regulation deviation index Pd, thermal response offset index Hd, and power stability index Wd exceed the corresponding response deviation threshold, the first correction signal is output.

7. The adaptive load fluctuation converter topology reconfiguration and intelligent control system according to claim 6, characterized in that, The regulation effectiveness assessment module includes a first correlation unit and a second correlation unit; The first associated unit is used to receive the load disturbance index Ld, differential offset index Sd, motor resistance index Bd and tire slip ratio Ed, and obtain the weighted sum of disturbance indexes Dsum by weighted summation. If no determination is made, the corresponding value is equal to 0. The second associated unit is used to combine the control deviation index Pd, the thermal response offset index Hd, and the power stability index Wd, obtain the weighted sum of feedback-type indices Fsum through weighted summation, and combine it with the weighted sum of disturbance-type indices Dsum to calculate the topology adaptability score coefficient Rt of the converter under the current operating state. and These are the control weight coefficients for the disturbance index weighted sum Dsum and the feedback index weighted sum Fsum, respectively.

8. The adaptive load fluctuation converter topology reconfiguration and intelligent control system according to claim 7, characterized in that, The regulation effectiveness evaluation module also includes a correction unit, which is used for comparison with a preset adaptive threshold X. If Rt < X, then the second determination correction signal is output. Based on the difference between the adaptability threshold X and the topology adaptability score coefficient Rt, the correction unit successively lowers the power limit, current limit, torque distribution or intervention sensitivity parameters by 3% to 5% until Rt ≥ X.

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