Dynamic compensation control method and system for vehicle jitter suppression

Abstract

The invention discloses a dynamic compensation control method and system for vehicle jitter suppression, and the method comprises the steps: collecting the state information of a vehicle through a vehicle end, and transmitting the state information to a cloud platform, the state information comprising the whole vehicle operation state data, the motor operation state data and the vibration data; the cloud platform inputs the state information into a preset anti-shake adjustment model to obtain an output torque dynamic compensation parameter set; the cloud platform issues the torque dynamic compensation parameter set to the vehicle end; and the motor controller at the vehicle end adjusts the torque output of the driving motor according to the torque dynamic compensation parameter set, so that the aging trend of the vehicle is dynamically predicted, accurate compensation parameters are generated, the jitter problems such as torque zero-crossing impact are effectively eliminated, the jitter control effect is kept stable in the whole life cycle, and the service life of the vehicle is prolonged. And the driving smoothness and comfort are improved in all directions.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, specifically to a dynamic compensation control method and system for suppressing vehicle vibration. Background Technology

[0002] With the rapid development of electric vehicle technology, the market's demands for vehicle driving comfort are increasing. The powertrain system of electric vehicles has unique structural characteristics, namely the direct and rapid torque response of the drive motor. This means that excitation from the road surface and torque fluctuations within the motor itself cannot be effectively blocked or absorbed, making them more easily transmitted to the entire vehicle and causing vibrations. Furthermore, the manufacturing process dictates that a certain amount of backlash inevitably exists between the gear pairs in the transmission system. Under rapid changes in driving conditions, the gear pairs may disengage and re-engage due to this backlash, resulting in knocking noises. This phenomenon severely affects the smoothness of the vehicle's ride.

[0003] In existing technologies, active damping algorithms are integrated into the vehicle-side motor controller. For example, by monitoring motor speed fluctuations in real time, a reverse compensation torque is calculated to counteract vibration. However, this type of control method has the following drawbacks: First, throughout the vehicle's lifespan, the transmission system's key parameters dynamically change due to continuous wear and aging. The control parameters of the vehicle-side control strategy are usually set before the vehicle leaves the factory and remain fixed throughout its lifespan. This results in a significant decline in control effectiveness as vehicle mileage increases and gear backlash widens, making it unable to effectively suppress gear knocking and vibration. Second, onboard computing resources are limited, and the onboard controller struggles to handle complex vibration root cause diagnosis and big data correlation analysis tasks. It cannot perform personalized and refined parameter adjustments based on the specific operating conditions, real-time aging status, and unique vibration characteristics of a particular vehicle. Third, general anti-vibration strategies rely on detecting and compensating for existing vibration signals, which is a "passive response" mechanism. For sudden, severe impacts such as torque crossing zero, this passive compensation method has an inherent control lag, failing to achieve proactive and smooth control and making it difficult to completely eliminate the impact.

[0004] Therefore, how to proactively and precisely suppress vehicle vibration is a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0005] This application provides a dynamic compensation control method and system for vehicle vibration suppression, which can solve the technical problem in the prior art that it is impossible to actively and accurately suppress vehicle vibration.

[0006] In a first aspect, embodiments of this application provide a dynamic compensation control for vehicle vibration suppression, the dynamic compensation control method for vehicle vibration suppression comprising: The vehicle-mounted system collects vehicle status information and sends it to the cloud platform. The status information includes vehicle operating status data, motor operating status data, and vibration data. The cloud platform inputs the status information into a preset anti-shake adjustment model to obtain a set of output torque dynamic compensation parameters. The cloud platform sends the set of dynamic torque compensation parameters to the vehicle. The motor controller at the vehicle end adjusts the torque output of the drive motor according to the set of torque dynamic compensation parameters.

[0007] In conjunction with the first aspect, in one implementation method: The vehicle operating status data includes: vehicle speed, vehicle requested torque, accelerator pedal opening, transmission gear signal, driving cycle, and driving mileage; The motor operating status data includes: the drive motor speed signal, the output torque command value, the actual output torque value, and the reducer temperature; The vibration data includes vibration data of the drive assembly, reducer housing, and vehicle floor.

[0008] In conjunction with the first aspect, in one implementation, the cloud platform inputs the state information into a preset anti-shake adjustment model to obtain a set of output torque dynamic compensation parameters, including: The anti-shake adjustment model includes a gear backlash aging prediction model and an anti-shake gain adjustment model. The state information is input into the gear backlash aging prediction model to obtain the tooth-fitting torque adjustment parameters, wherein the tooth-fitting torque adjustment parameters include the zero-crossing torque slope adjustment coefficient, the lead time constant, and the compensation amplitude gain coefficient. The state information is input into the anti-shake gain adjustment model to obtain anti-shake gain adjustment parameters, wherein the anti-shake gain adjustment parameters include active anti-shake adjustment coefficients, as well as the center frequency, attenuation depth, equivalent transmission stiffness correction factor, and damping coefficient correction factor of the filter. The tooth-fitting torque adjustment parameters and the anti-shake gain adjustment parameters are packaged together to generate the torque dynamic compensation parameter set.

[0009] In conjunction with the first aspect, in one implementation, the state information is input into the gear backlash aging prediction model to obtain the tooth-fitting torque adjustment parameters, including: The state information is input into the gear backlash aging prediction model to obtain the aging prediction result of the reducer gear pair in the drive motor, wherein the aging prediction result includes the gear backlash increment, the probability of gear pair impact, and the impact intensity. The gear backlash aging prediction model generates the tooth-fitting torque adjustment parameters based on the aging prediction results.

[0010] In conjunction with the first aspect, in one embodiment, the vehicle-side motor controller adjusts the torque output of the drive motor according to the set of torque dynamic compensation parameters, including: When the torque of the drive motor is in a state of zero torque and the driving mileage of the vehicle is less than a preset mileage threshold, the torque zero-crossing range of the drive motor is determined according to the requested torque of the vehicle. The torque zero-crossing interval is divided using the lead time constant, wherein the lead time constant includes the first moment characterizing the start of torque zero-crossing control intervention, the second moment characterizing the completion of the torque zero-crossing segment, the third moment characterizing the control torque entering the first tooth-fitting torque segment, and the fourth moment characterizing the control torque entering the second tooth-fitting torque segment. Between the first moment and the second moment, the torque slope of the output torque command value is multiplied by the first zero torque slope adjustment coefficient to obtain the first adjusted torque slope, and the torque output of the drive motor is controlled by the first adjusted torque slope. Between the second and third moments, the torque slope of the output torque command value is multiplied by the second zero torque slope adjustment coefficient to obtain the second adjusted torque slope, and the torque output of the drive motor is controlled by the second adjusted torque slope. Between the third and fourth moments, the torque slope of the output torque command value is multiplied by the third zero torque slope adjustment coefficient to obtain the third adjusted torque slope. The torque output of the drive motor is controlled by the third adjusted torque slope until the output torque of the drive motor is the same as the output torque command value. Wherein, the absolute value of the first adjustment torque slope is less than the absolute value of the torque slope of the output torque command value, and the absolute value of the second adjustment slope is greater than the absolute value of the first adjustment slope.

[0011] In conjunction with the first aspect, in one embodiment, the vehicle-side motor controller adjusts the torque output of the drive motor according to the set of torque dynamic compensation parameters, including: When the torque of the drive motor is in a state of zero torque crossing and the driving mileage of the vehicle is greater than or equal to a preset mileage threshold, between the first moment and the second moment, the first adjustment torque slope is multiplied by the compensation amplitude gain coefficient to obtain the fourth adjustment torque slope, and the torque output of the drive motor is controlled by the fourth adjustment torque slope. Between the second and third moments, the second adjustment torque slope is multiplied by the compensation amplitude gain coefficient to obtain the fifth adjustment torque slope, and the torque output of the drive motor is controlled by the fifth adjustment torque slope.

[0012] In conjunction with the first aspect, in one embodiment, the vehicle-side motor controller adjusts the torque output of the drive motor according to the set of torque dynamic compensation parameters, including: When the torque of the drive motor is not at zero, the vehicle end extracts the speed fluctuation component from the speed signal of the drive motor. Based on the requested torque of the vehicle and the speed signal of the drive motor, a preset gain coefficient matrix is ​​searched to obtain the corresponding torque gain coefficient. Multiply the torque gain coefficient by the active stabilization adjustment coefficient to obtain the final adjustment gain coefficient; The anti-shake compensation torque is obtained by inverting the speed fluctuation component and then combining it with the final adjustment gain coefficient. The vehicle's requested torque is added to the anti-shake compensation torque to obtain the vehicle's final requested torque, which is then applied to the drive motor.

[0013] In conjunction with the first aspect, in one embodiment, before the vehicle end extracts the speed fluctuation component from the speed signal of the drive motor, the method further includes: Adjust the filter according to the center frequency, attenuation depth, equivalent transmission stiffness correction factor, and damping coefficient correction factor; The speed signal of the drive motor is filtered using an adjusted filter.

[0014] In conjunction with the first aspect, in one embodiment, after the motor controller at the vehicle end adjusts the torque output of the drive motor according to the set of torque dynamic compensation parameters, it further includes: The vehicle-mounted device continues to collect vibration data of the vehicle and upload it to the cloud platform; The cloud platform evaluates the vibration suppression effect on the vehicle based on the continuously collected vibration data, and uses the evaluation results to iteratively optimize the anti-shake adjustment model.

[0015] Secondly, embodiments of this application provide a dynamic compensation control system for vehicle vibration suppression, the dynamic compensation control system for vehicle vibration suppression comprising: The vehicle-side component is used to collect vehicle status information and send it to the cloud platform. The status information includes vehicle operating status data, motor operating status data, and vibration data. The cloud platform is used to input the status information into a preset anti-shake adjustment model to obtain a set of output torque dynamic compensation parameters. The cloud platform is also used to send the set of torque dynamic compensation parameters to the vehicle. The vehicle end is also used to adjust the torque output of the drive motor according to the set of torque dynamic compensation parameters through the motor controller.

[0016] The beneficial effects of the technical solutions provided in this application include: The system collects vehicle status information at the vehicle end and sends it to a cloud platform. This status information includes overall vehicle operating status data, motor operating status data, and vibration data. The cloud platform inputs this status information into a preset anti-shake adjustment model to obtain a set of output torque dynamic compensation parameters. The cloud platform then sends this set of torque dynamic compensation parameters back to the vehicle end. The vehicle end's motor controller adjusts the torque output of the drive motor based on the set of torque dynamic compensation parameters. This solves the technical problems in related technologies where fixed control parameters cannot adapt to the aging of the vehicle throughout its entire life cycle, and where limited onboard computing resources lead to a single and lagging vehicle vibration control strategy. By constructing a closed-loop control system that coordinates vehicle and cloud, the system deeply integrates real-time data acquisition from the vehicle with big data analysis and intelligent decision-making in the cloud. Through a cloud-based anti-shake adjustment model, it dynamically predicts vehicle aging trends and generates precise compensation parameters, ensuring stable vibration control throughout the entire lifecycle. By employing a refined control strategy that distinguishes between operating conditions and root causes, it effectively eliminates vibration issues such as torque zero-crossing shocks. Furthermore, by placing complex calculations in the cloud, the architecture reduces reliance on vehicle-side hardware resources, laying the foundation for the continuous evolution of control algorithms. Ultimately, this comprehensively improves driving smoothness and comfort. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating an embodiment of the dynamic compensation control method for vehicle vibration suppression according to this application; Figure 2 This is a schematic diagram illustrating the specific process of the dynamic compensation control method for vehicle vibration suppression in this application; Figure 3 This is a schematic diagram of torque control under zero-crossing conditions; Figure 4 This is a schematic diagram of torque slope control under zero-crossing conditions. Figure 5 This is a block diagram illustrating the core algorithm principle of the adaptive anti-shake torque control logic. Figure 6 This is a schematic diagram of the gain coefficient matrix; Figure 7 This is a schematic diagram of the architecture of the dynamic compensation control system for vehicle vibration suppression in this application. Detailed Implementation

[0018] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0020] In a first aspect, embodiments of this application provide a dynamic compensation control method for suppressing vehicle vibration.

[0021] In one embodiment, reference is made to Figure 1 and Figure 2 , Figure 1 This is a flowchart illustrating the first embodiment of the dynamic compensation control method for vehicle vibration suppression according to this application. Figure 1 As shown, the dynamic compensation control method for vehicle vibration suppression includes: Step S101: The vehicle terminal collects the vehicle's status information and sends it to the cloud platform. The status information includes vehicle operating status data, motor operating status data, and vibration data.

[0022] In one embodiment, the vehicle's motor controller collects vehicle operating status data in real time through the vehicle's CAN bus network. The vehicle operating status data includes: vehicle speed, vehicle requested torque, accelerator pedal opening, transmission gear signal, driving cycle, and driving mileage.

[0023] The motor controller can also acquire motor operating status data, including: the drive motor speed signal, the output torque command value, the actual output torque value, and the reducer temperature. If no sensor is installed to collect the reducer temperature, the drive motor temperature can be used instead.

[0024] Simultaneously, multi-axis vibration data characterizing the degree of vehicle vibration are collected using vibration acceleration sensors installed at the vehicle drive assembly mounting points, reducer housing, and vehicle floor. This vibration data includes vibration data from the drive assembly, reducer housing, and vehicle floor. Preliminary preprocessing and feature extraction can be performed on the vibration data to obtain corresponding feature data, such as the effective value and order amplitude of the vibration data.

[0025] Next, the raw data of the collected vehicle status information and the feature data extracted after preliminary preprocessing can be uploaded to the cloud big data platform in a secure and encrypted manner through the cellular vehicle-to-everything (V2X) communication module via the vehicle-side communication gateway (T-Box).

[0026] It is worth noting that the cloud platform can receive encrypted status information packets, including vehicle status information, from a large number of online electric vehicles in real time or near real time via the communication module. The cloud performs integrity verification, timestamp synchronization and alignment, outlier removal, and standardized formatting on the received data, and stores it in a distributed big data storage system.

[0027] Step S102: The cloud platform inputs the status information into the preset anti-shake adjustment model to obtain the output torque dynamic compensation parameter set.

[0028] It is worth noting that the cloud platform can receive encrypted status information packets, including vehicle status information, from a large number of online electric vehicles in real-time or near real-time via the communication module. The cloud performs integrity verification, timestamp synchronization and alignment, outlier removal, and standardized formatting on the received data. It then associates the processed valid data with the historical database and activates the feature extraction engine. This engine calculates and extracts high-value feature vectors for accurate identification and prediction from preprocessed data such as vibration signals, including but not limited to time-domain and frequency-domain features, providing high-quality input information for subsequent accurate analysis and decision-making by the model.

[0029] As a preferred implementation, the cloud platform's built-in cloud analysis model uses multi-dimensional data such as vibration data uploaded from the vehicle, motor speed, and requested vehicle torque as input to quantitatively assess the current driving comfort of the vehicle and generate a precise vibration evaluation that includes the type and severity level of vibration. Its core decision-making logic is as follows: when the identified vibration type belongs to the target vibration type to be suppressed (such as nonlinear impact caused by gear backlash), and its severity level exceeds a preset threshold, the system automatically triggers an optimization process, inputting relevant status information into a preset anti-vibration adjustment model, dynamically calculating and outputting the optimal set of dynamic torque compensation parameters, thereby initiating targeted vibration suppression.

[0030] As an example, the cloud-based analytics model first performs online feature enhancement on the preprocessed vehicle vibration data. By parallel computing of time-domain features (such as motor speed fluctuations and actual output torque values), frequency-domain features (such as the energy of order components related to motor speed and the amplitude of meshing frequency sidebands), and time-frequency-domain features (such as the short-term energy of specific impact events), a high-dimensional feature vector set comprehensively characterizing the system's vibration state is constructed. This step provides a rich data foundation for subsequent accurate diagnosis. Relying on the built-in machine learning diagnostic engine and continuously training the engine by integrating historical fault case libraries and expert rule bases, the model can perform high-precision pattern recognition on the above feature vectors, accurately determine the vibration type (such as torque fluctuations, resonance, or gear knocking), and quantify the severity level of the vibration. After completing the basic diagnosis, the model further combines uploaded real-time vehicle operating conditions, cumulative mileage, and reducer oil temperature (or equivalent replacement parameters) and other contextual data for in-depth root cause analysis. This process can effectively distinguish whether the vibration is caused by instantaneous operating conditions (such as rapid acceleration) or by systematic degradation of the transmission system (such as gear wear and component aging), thus providing a key decision-making basis for generating targeted compensation strategies.

[0031] The anti-shake adjustment model includes a gear backlash aging prediction model and an anti-shake gain adjustment model. These two models, using machine learning algorithms and based on the vehicle's historical and real-time status information, as well as a torque dynamic compensation parameter database, are continuously trained and optimized to achieve high-precision diagnostic and predictive capabilities.

[0032] In the process of building gear backlash aging prediction models and anti-vibration gain adjustment models based on historical data, the cloud platform extensively collects and stores massive amounts of historical operating and vibration data from vehicles across the entire domain. Based on this big data, machine learning algorithms are used for training to construct an initial model. This model is not only used for all subsequent real-time analysis, prediction, and optimization decisions, but also possesses the ability to continuously learn online and iteratively optimize itself, adapting to new data and operating conditions over time to improve system performance and accuracy.

[0033] In one embodiment, the cloud platform inputs the state information into a preset anti-shake adjustment model to obtain an output set of dynamic torque compensation parameters, including: inputting the state information into the gear backlash aging prediction model to obtain gear-fitting torque adjustment parameters, wherein the gear-fitting torque adjustment parameters include a zero-crossing torque slope adjustment coefficient, a lead time constant, and a compensation amplitude gain coefficient; inputting the state information into the anti-shake gain adjustment model to obtain anti-shake gain adjustment parameters, wherein the anti-shake gain adjustment parameters include an active anti-shake adjustment coefficient, as well as the filter's center frequency, attenuation depth, equivalent transmission system stiffness correction factor, and damping coefficient correction factor; and packaging the gear-fitting torque adjustment parameters and the anti-shake gain adjustment parameters to generate the set of dynamic torque compensation parameters.

[0034] Specifically, inputting the state information into the gear backlash aging prediction model to obtain the tooth-fitting torque adjustment parameters includes: inputting the state information into the gear backlash aging prediction model to obtain the aging prediction result of the reducer gear pair in the drive motor, wherein the aging prediction result includes the gear backlash increment, the probability of gear pair impact, and the impact intensity; and generating the tooth-fitting torque adjustment parameters based on the aging prediction result through the gear backlash aging prediction model.

[0035] It is worth noting that the gear backlash aging prediction model uses key data such as the vehicle's cumulative driving mileage, historical torque load spectrum (with particular attention to the frequency and amplitude of high torque change rate conditions), and the reducer's operating temperature history as its main inputs. It combines the physical laws of material wear with a statistical regression algorithm based on a large sample of maintenance data from the same type of vehicle to achieve dynamic and accurate prediction of the current backlash value of the vehicle's reducer gear pair.

[0036] When the drive motor torque crosses zero, the model analyzes the drive motor's speed fluctuations and torque input, and statistically analyzes the number of gear knocking events and their average amplitude. Based on these analysis results, the model can dynamically adjust the tooth contact torque as needed to adapt to changes in gear backlash.

[0037] To simplify the practical implementation of the model, motor temperature can be used as a substitute when reducer temperature data is unavailable. The gear backlash aging prediction model is affected by driving mileage, reducer temperature, and aggressive operating conditions. Its main influencing factor is the natural aging factor that increases with driving mileage, while the increased vibration during zero crossings during aggressive driving is a secondary influencing factor that requires intervention.

[0038] The gear backlash aging prediction model dynamically estimates the current gear backlash increment of a vehicle reducer gear pair. Its implementation is based on two methods: First, it uses load spectrum statistical accumulation: analyzing the frequency and magnitude of high-torque impact conditions in the vehicle's historical data, such as the number of rapid acceleration starts and high-intensity regenerative braking events. Second, it uses multi-factor fusion degradation prediction: combining material wear physical models such as mileage, load spectrum, and oil temperature history with a statistical regression model based on a large sample of maintenance data from similar vehicles to comprehensively calculate the gear backlash increment ΔBacklash.

[0039] This study quantifies the impact of increased gear backlash on the nonlinear dynamic characteristics of gear pairs. Specifically, it calculates the probability and estimated impact intensity of gear disengagement and re-impact under transient torque conditions, particularly near the torque zero-crossing point. This impact intensity is mapped to specific high-frequency impact energy characteristics captured by vibration sensors. For high-impact-risk conditions, tooth-fitting torque adjustment parameters are calculated. These parameters provide precise torque compensation in the zero-crossing torque region to counteract transmission system impacts caused by backlash, achieving smooth meshing.

[0040] In one embodiment, the anti-shake gain adjustment model uses real-time vehicle status data and vibration characteristics as primary inputs. By analyzing this data, it calculates the corresponding anti-shake gain adjustment parameters. These parameters can adaptively adjust the intensity and frequency band of vibration suppression according to the actual operating conditions of the vehicle, thereby achieving precise control of vehicle vibration. This model ensures effective vibration suppression under different operating conditions and improves driving comfort by dynamically adjusting the gain.

[0041] Step S103: The cloud platform sends the set of torque dynamic compensation parameters to the vehicle.

[0042] Specifically, the cloud encapsulates the set of torque dynamic compensation parameters, version number, and applicable conditions generated by the anti-shake adjustment model into an encrypted configuration command package with a digital signature. This encapsulation method ensures the security and integrity of the data, preventing data from being tampered with or leaked during transmission.

[0043] Based on the severity of the diagnosed vibration and the current network conditions, the cloud employs a differentiated delivery strategy. For high-priority updates, such as those detected in cases of severe vibration or emergency situations, the cloud will deliver parameters in real time to ensure the vehicle can immediately apply the new compensation strategy to quickly improve the driving experience. For general updates, the cloud will select an appropriate time to deliver the updates based on network conditions and the vehicle's operating status to avoid unnecessary interference with the vehicle's normal operation.

[0044] The parameter distribution and execution steps specifically include: the cloud sends the encapsulated downlink command packet to the vehicle's communication module (such as a T-Box) via a wireless network. Upon receiving the command packet, the vehicle communication module performs security authentication to ensure the packet's reliable origin and lack of tampering. After successful authentication, the vehicle communication module transmits the command packet to the motor controller. Upon receiving the command packet, the motor controller parses the adjustment coefficient set, version number, and applicable conditions within the command packet using the CAN communication protocol.

[0045] Furthermore, the motor controller transmits the parsed set of adjustment coefficients to the active stabilization and torque zero-crossing control module. The control module adds the new adjustment coefficients to the existing control algorithm, updating the torque zero-crossing and active stabilization control strategies. The updated control strategy takes effect in the next driving cycle, and the motor controller performs torque zero-crossing and active stabilization control based on the new parameters, thereby optimizing the vehicle's vibration suppression effect.

[0046] Step S104: The motor controller at the vehicle end adjusts the torque output of the drive motor according to the set of torque dynamic compensation parameters.

[0047] In a preferred embodiment, the vehicle-side motor controller adjusts the torque output of the drive motor according to the set of torque dynamic compensation parameters, including: when the torque of the drive motor is in a torque zero-crossing state and the vehicle's driving mileage is less than a preset mileage threshold, determining the torque zero-crossing interval of the drive motor based on the vehicle's requested torque; dividing the torque zero-crossing interval using the lead time constant, wherein the lead time constant includes a first moment representing the start of torque zero-crossing control intervention, a second moment representing the completion of the torque zero-crossing segment, a third moment representing the control torque entering the first gear-fitting torque segment, and a fourth moment representing the control torque entering the second gear-fitting torque segment; between the first moment and the second moment, multiplying the torque slope of the output torque command value by a first zero torque slope adjustment coefficient to obtain a first adjustment torque. The torque output of the drive motor is controlled by the first adjusted torque slope. Between the second and third time points, the torque slope of the output torque command value is multiplied by a second zero torque slope adjustment coefficient to obtain a second adjusted torque slope, which is then used to control the torque output of the drive motor. Between the third and fourth time points, the torque slope of the output torque command value is multiplied by a third zero torque slope adjustment coefficient to obtain a third adjusted torque slope, which is then used to control the torque output of the drive motor until the output torque of the drive motor is the same as the output torque command value. Wherein, the absolute value of the first adjusted torque slope is less than the absolute value of the torque slope of the output torque command value, and the absolute value of the second adjusted slope is greater than the absolute value of the first adjusted slope.

[0048] Explained in this context, the zero-crossing condition refers to the process where the requested torque from the vehicle controller gradually increases from a negative value (i.e., braking torque in energy recovery mode) and crosses zero, transforming into a positive value (i.e., drive torque in acceleration mode). This process typically occurs when the vehicle switches from coasting or braking to acceleration. For example, during coasting or braking, the vehicle controller issues a negative torque command to achieve energy recovery. However, when the driver depresses the accelerator pedal, the vehicle's requested torque begins to rise from a negative value, eventually crossing zero and becoming positive. At this instant of torque switching from negative to positive, the drive motor gears need to switch from engagement in one direction to engagement in the opposite direction.

[0049] Because of the backlash between gears, at the instant the torque crosses zero, the gears may momentarily lose mesh, causing a collision between the gear teeth, resulting in mechanical knocking sounds and vibrations. This gear knocking phenomenon at zero torque is a common problem in new energy vehicles, which not only affects the driving comfort of the vehicle but may also cause additional wear on the transmission system components.

[0050] To address this issue, this application reduces the impact between gear teeth by precisely controlling the rate and magnitude of torque change and providing additional torque compensation in the torque zero-crossing region, thereby effectively suppressing vibrations caused by torque zero-crossing. The core of this solution lies in using an intelligent control strategy to ensure that the gears smoothly switch meshing directions at the instant torque crosses zero, avoiding mechanical knocking caused by backlash, thus improving driving smoothness and comfort.

[0051] As an example, the vehicle-side drive motor controller can identify the torque zero-crossing range based on the vehicle's torque request and divide this range into different time periods. For example... Figure 3 As shown, the lead time constant includes the first time t0, which characterizes the start of torque zero-crossing control, at which time the vehicle requests torque Tq1; the second time t1, which characterizes the completion of the torque zero-crossing segment, at which time the vehicle requests torque Tq2; the third time t2, which characterizes the control torque entering the first tooth-fitting torque segment, at which time the vehicle requests torque Tq3; and the fourth time t3, which characterizes the control torque entering the second tooth-fitting torque segment, at which time the vehicle requests torque Tq4.

[0052] like Figure 4 As shown, with the drive motor torque at zero crossing, after optimizing the tooth-fitting torque adjustment parameters, the output torque slope control graph of the drive motor displays the variation curve of the torque command slope k (unit: Nm / s). These variation curves are related to... Figure 3The torque segments are configured one-to-one to ensure that the torque command is output accurately as expected. In this control strategy, the output torque command no longer simply follows the requested torque, but is adjusted in conjunction with the zero-crossing torque slope adjustment coefficient and compensation amplitude gain coefficient sent from the cloud, thereby realizing a segmented slope precision control strategy.

[0053] Within the interval from t0 to t1, the torque command gradually increases with a preset, low initial adjustment torque slope k1 (|k1| < |krequest|). The key objective of this stage is to slow down the rate of torque change in advance, thereby absorbing energy in the transmission system, making full preparations for a smooth entry into the zero-crossing zone, and effectively avoiding the shock that may occur when the torque reverses.

[0054] Within the interval t1 to t2, to prevent the gear pair from losing meshing force and disengaging due to zero torque, this application specifically introduces an active tooth-fitting compensation mechanism. This compensation mechanism ensures that the provided torque is sufficient to overcome the system's operating resistance, thereby maintaining slight contact between the driven gear and the driving gear tooth surface at all times, completely eliminating backlash. During this period, the torque command increases slowly with an extremely gentle second adjustment torque slope k2 (|k2|>|k1|), smoothly transitioning to the positive drive torque Tq3.

[0055] Once the torque command smoothly transitions to a certain positive torque value Tq3, the system determines that the gear engagement has entered a stable state, at which point the risk of knocking has been eliminated. Subsequently, the slope limit of the torque command is gradually released, and its change slope can recover to a higher third adjustment torque slope k3 to quickly track the requested torque until the two coincide. This process ensures that the driver's power request receives a timely and accurate response, thereby improving driving comfort while also ensuring the vehicle's power performance.

[0056] It is worth noting that in this embodiment, during the torque zero-crossing control process, the motor controller outputs different torque commands according to different time periods to ensure smooth gear meshing and reduce vibration.

[0057] From time t0 to t1, the torque command output by the motor controller changes to a relatively gentle curve, completing the reversal of the gear teeth from one direction to another. This torque change trajectory closely matches the gear backlash, ensuring that at the moment of reversal, the torque is precisely applied to one side of the gear, avoiding mechanical knocking and vibration caused by backlash. From time t1 to t2, the torque command output by the motor controller completes the gear teeth contact with a relatively rapid slope, with the torque increasing from Tq2 to Tq3, ensuring that the gears can quickly and smoothly contact each other after reversal, further reducing the impact caused by backlash. From time t2 to t3, the torque command output by the motor controller starts from Tq3 and gradually catches up with the torque requested by the vehicle. During this stage, it is necessary to ensure that the torque output by the motor controller can smoothly transition to the torque requested by the vehicle Tq4. By gradually adjusting the torque command, it is ensured that the vehicle's power request can be responded to in a timely manner after the torque crosses zero, while avoiding vibration caused by sudden torque changes.

[0058] It is worth noting that through the aforementioned segmented control strategy, the motor controller can precisely manage the torque zero-crossing process, ensuring a smooth transition of gears during commutation and engagement, reducing mechanical knocking and vibration caused by backlash. This precise torque control not only improves driving comfort but also extends the service life of the transmission system.

[0059] In a preferred embodiment, when the torque of the drive motor is in a zero-torque state and the vehicle's driving mileage is greater than or equal to a preset mileage threshold, between the first moment and the second moment, the first adjusted torque slope is multiplied by a compensation amplitude gain coefficient to obtain a fourth adjusted torque slope, and the torque output of the drive motor is controlled by the fourth adjusted torque slope; between the second moment and the third moment, the second adjusted torque slope is multiplied by a compensation amplitude gain coefficient to obtain a fifth adjusted torque slope, and the torque output of the drive motor is controlled by the fifth adjusted torque slope.

[0060] As an example, during the zero-crossing condition of the drive motor, the torque output command is not only affected by the torque slope, but also needs to be adjusted in conjunction with the compensation amplitude gain coefficient Tqcoffe from the cloud. This adjustment strategy can dynamically optimize the torque output according to the actual operating conditions of the vehicle, reducing vibrations caused by changes in gear backlash.

[0061] As mileage increases, mechanical wear and aging cause changes in gear backlash. Continuing to use the initial torque slope k may result in the gear teeth not engaging properly, causing vibration. To address this, the cloud dynamically adjusts the compensation amplitude gain coefficient Tqcoffe based on the vehicle's actual operating conditions. From time t0 to t1, the fourth adjusted torque slope k4 = k1 × Tqcoffe is used to complete the gear tooth surface reversal. By introducing Tqcoffe, the adjusted slope k4 better adapts to changes in gear backlash, ensuring a smooth reversal process. From time t1 to t2: the new fifth adjusted torque slope k5 = k2 × Tqcoffe is used to complete the gear tooth surface engagement. The adjusted slope k5 ensures that the gears engage quickly and smoothly after reversal, reducing the impact from backlash.

[0062] During the time interval t2 to t3, the torque command output by the motor controller starts from Tq3 and gradually catches up with the torque requested by the vehicle. During this stage, the third torque adjustment slope k3 can continue to be used until the output torque of the drive motor is the same as the output torque command value. This process ensures a smooth transition in torque output, meeting the vehicle's power requirements while avoiding vibrations caused by sudden torque changes.

[0063] It's worth noting that to ensure the effectiveness and safety of the torque zero-crossing logic, a torque boundary needs to be set. This boundary is predefined based on the vehicle's specific operating conditions and design requirements, and is used to limit the applicable range of the torque zero-crossing logic. The adjusted torque slope and compensation amplitude gain coefficient will only be applied when the output torque is within this boundary. When the output zero-crossing torque does not exceed the set torque boundary, the torque zero-crossing logic is allowed. At this time, the system will replace the vehicle's torque request and send the adjusted torque command to the motor controller for control. In this way, it can be ensured that the torque change is smooth and meets design requirements during the torque zero-crossing process, avoiding mechanical shocks and vibrations caused by sudden torque changes.

[0064] Once the output torque exceeds the set torque boundary, the torque zero-crossing logic needs to be exited as quickly as possible. This means the system will stop applying the adjusted torque slope and compensation amplitude gain coefficient, reverting to normal torque control mode. After exiting the torque zero-crossing logic, the system needs to quickly adjust the output torque to match the vehicle's requested torque. This process needs to be fast and smooth to ensure the vehicle's power performance is not affected. This strategy not only ensures the smoothness and safety of the torque zero-crossing process but also improves the vehicle's driving comfort and the reliability of the transmission system.

[0065] In one embodiment, when the torque of the drive motor is not at zero crossing, the vehicle-side motor controller adjusts the torque output of the drive motor according to the set of torque dynamic compensation parameters. This includes: the vehicle-side controller extracting the speed fluctuation component from the speed signal of the drive motor; searching a preset gain coefficient matrix based on the vehicle's requested torque and the speed signal of the drive motor to obtain the corresponding torque gain coefficient; multiplying the torque gain coefficient by the active anti-shake adjustment coefficient to obtain the final adjustment gain coefficient; inverting the speed fluctuation component and then combining it with the final adjustment gain coefficient to obtain the anti-shake compensation torque; adding the vehicle's requested torque to the anti-shake compensation torque to obtain the vehicle's final requested torque, and applying it to the drive motor.

[0066] Preferably, before extracting the speed fluctuation component from the speed signal of the drive motor at the vehicle end, the method further includes: adjusting the filter according to the center frequency, attenuation depth, equivalent transmission stiffness correction factor, and damping coefficient correction factor; and using the adjusted filter to filter the speed signal of the drive motor.

[0067] Exemplary, such as Figure 5 As shown, when the torque of the drive motor is not at zero, the vehicle-side motor controller will adjust the torque output of the drive motor according to the anti-shake gain adjustment parameter set. The specific steps include: Step S201: High-precision speed signal acquisition: The vehicle-side motor controller acquires the original speed signal of the drive motor in real time at an extremely high sampling rate. This signal contains rich system dynamic information, but it is also mixed with high-frequency noise and electromagnetic harmonic interference. Typically, the motor speed signal is acquired through a resolver simulator, which can be either hardware-based or software-based. Due to the limitations of the motor control system, the original speed signal contains AC low-frequency components, AC high-frequency components, DC components, and acceleration components.

[0068] Step S302, Speed ​​Signal Filtering: After acquiring the original speed signal, it is necessary to extract the speed fluctuation component DeltaSpd, which represents the instantaneous torsional vibration state of the transmission system. The core of this process lies in the design of the filter. The original speed signal is input to one or a group of parallel filters, including but not limited to bandpass filters, low-pass filters, and high-pass filters. The filter is adjusted according to the center frequency, attenuation depth, equivalent transmission stiffness correction factor, and damping coefficient correction factor in the anti-shake gain adjustment parameters, so that it can accurately extract the speed fluctuation component that reflects the jitter characteristics.

[0069] Step S303, Speed ​​Fluctuation Component Extraction: The speed fluctuation component DeltaSpd, representing the instantaneous torsional vibration state of the transmission system, is extracted from the filtered motor speed using a filter. This component is the direct basis for assessing system jitter energy and implementing active intervention. The speed fluctuation component must accurately represent the speed fluctuation, its phase characteristics must be consistent with the original speed, and its amplitude characteristics must fluctuate around the zero speed axis without any acceleration trend.

[0070] Step S304, Adaptive Gain Coefficient Scheduling: The extracted speed fluctuation component is used as input and fed into a gain coefficient matrix for calculation. The gain coefficient matrix consists of two dimensions: the vehicle's requested torque and the motor's actual speed. The gain coefficients of this matrix are not fixed but need to be superimposed with active anti-shake adjustment coefficients from the cloud. The cloud coefficients serve as the desired performance indicators, ensuring that the system's dynamic response converges quickly to the performance target expected by the cloud while maintaining stability. The gain coefficient matrix essentially realizes a multi-input multi-output mapping relationship, which can call different gain combination strategies according to different vehicle operating conditions, such as low-speed creep, rapid acceleration, and regenerative braking, thereby achieving optimal control under all operating conditions.

[0071] Step S305, Anti-shake Torque Calculation and Output: After gain coefficient matrix operation, the torque gain coefficient is obtained. The torque gain coefficient is multiplied by the active anti-shake adjustment coefficient to obtain the final adjustment gain coefficient. The speed fluctuation component is inverted and then combined with the final adjustment gain coefficient to output the final anti-shake compensation torque. The anti-shake compensation torque is a composite control quantity that combines feedforward compensation and feedback control. It is superimposed with the vehicle's requested torque command and acts together on the motor to generate an active damping torque, which is used to counteract the torsional vibration of the transmission system in real time and in reverse, thereby smoothing speed fluctuations and suppressing vehicle body vibration at the source.

[0072] It is worth noting that the motor controller continuously receives and verifies the active anti-shake adjustment coefficients sent from the cloud. These coefficients are parsed into high-performance instructions for the vehicle-side local adaptive control law. These active anti-shake adjustment coefficient instructions are used in the online update step S304, and are superimposed with the adjustment gain coefficients obtained according to the gain scheduling matrix for torque compensation. This ensures that the vehicle-side control performance is always synchronized with the latest decisions in the cloud while maintaining system stability, achieving performance-level cloud collaboration.

[0073] The gain coefficient matrix is ​​a two-dimensional matrix. The torque gain coefficients, obtained by looking up the table from the gain coefficient matrix, represent the magnitude of the anti-vibration torque applied under different speed and torque conditions. In the gain coefficient matrix, as shown... Figure 6As shown, the vehicle's requested torque table represents the torque range during motor operation. Points are taken from specific intervals. When the vehicle's requested torque is low, the intervals are more closely spaced to achieve precise control within a small torque range; when the vehicle's requested torque is high, the intervals can be wider to cover a broader torque range. Similarly, the drive motor's speed signal table represents the motor's speed range during operation. Points are also taken from specific intervals. When the actual motor speed is low, the intervals are more closely spaced to achieve precise control within a small speed range; when the actual motor speed is high, the intervals can be wider to accommodate high-speed operation.

[0074] Under preset conditions, the anti-shake compensation torque is added to the vehicle's requested torque to obtain the final torque requirement sent to the motor controller. This process ensures that the motor controller receives accurate torque commands under various operating conditions, thereby achieving smooth torque output. Furthermore, the active anti-shake torque has a maximum torque limit to ensure that the output of the anti-shake torque does not exceed the motor's safe operating range within the operating range. This limit not only protects the motor from overload damage but also ensures the stability and reliability of the entire system.

[0075] In a preferred embodiment, after the motor controller at the vehicle end adjusts the torque output of the drive motor according to the set of torque dynamic compensation parameters, the method further includes: the vehicle end continues to collect vibration data of the vehicle and uploads it to the cloud platform; the cloud platform evaluates the vibration suppression effect on the vehicle based on the continuously collected vibration data, and uses the evaluation results to iteratively optimize the anti-shake adjustment model.

[0076] As an example, after the vehicle operates with new parameters, key vibration characteristics are continuously fed back to the cloud. The cloud analyzes key indicators such as the rate of decrease in vibration amplitude at specific orders and the reduction in impact energy by comparing data before and after compensation, thus evaluating the compensation effect. These evaluation results will be used to continuously iterate and optimize the vibration analysis model, backlash aging model, and coefficient generation strategy, forming a self-evolving closed-loop control.

[0077] The driving data feedback process specifically includes: after applying the new parameter set, the motor controller continuously monitors the vehicle's vibration level and shaking rate. These key performance indicators, including vibration amplitude, frequency, and impact energy, reflect the vehicle's actual operating status. This key performance indicator data is then uploaded to the cloud. The cloud uses this feedback data to evaluate and verify the effectiveness of the parameter adjustments. The evaluation results will be used as part of the optimization data pool for subsequent iterative optimization of the cloud-based analysis model. In this way, the cloud platform can continuously optimize models and strategies based on actual operating data, improving system performance and reliability.

[0078] This application provides a dynamic compensation control method for vehicle vibration suppression. Through a vibration suppression architecture based on a vehicle-cloud collaborative closed-loop system, it achieves precise control and continuous optimization of vehicle vibration. The vehicle-cloud collaborative closed-loop system architecture of this application includes a closed-loop control system architecture consisting of a vehicle-side signal acquisition unit, a cloud-based analysis and decision-making platform, and a vehicle-side execution unit, connected via vehicle-to-everything (V2X) communication. This architecture, through close collaboration between the vehicle and the cloud, enables real-time monitoring, analysis, and dynamic compensation control of vehicle vibration.

[0079] Based on historical and real-time vehicle data, the cloud-based system dynamically predicts the backlash increment of the gear pairs in a vehicle's reducer and quantifies the risk level of gear knocking by integrating physical wear models and statistical learning algorithms. This method can predict the health status of the gear system in advance, providing a scientific basis for vibration suppression. Furthermore, based on the backlash prediction results and real-time vibration diagnosis results, a set of coefficients is dynamically generated and distributed for adaptive adjustment by the vehicle-side controller. These adjustment coefficients can dynamically optimize the vibration suppression strategy according to the actual operating conditions of the vehicle.

[0080] The specific implementation method for applying coefficients received from the cloud to the local control algorithm by the vehicle-side controller includes using a gear-fitting torque compensation coefficient to generate a micro-torque holding platform or smooth transition command near the torque zero-crossing condition to actively maintain gear meshing and avoid impact. In this way, the vehicle-side controller can adjust its control strategy in real time based on the cloud's optimization suggestions, improving the vibration suppression effect. Furthermore, the compensated data is used in a closed-loop learning method for continuous iterative optimization of the cloud's predictive model, diagnostic model, and coefficient generation rules. By continuously collecting and analyzing the vehicle-side's operating data, the cloud can continuously optimize the model and strategy, improving system performance and adaptability, thereby achieving continuous performance evolution.

[0081] The beneficial effects of this method lie in its shift from "passive response" to "active prediction and adaptation," improving the accuracy and foresight of control. Through a cloud platform, based on historical big data, advanced machine learning and physical models can proactively predict the potential vibration risks of specific vehicles due to aging and wear, and issue optimal adjustment coefficients in advance or in real-time before the vibration becomes severe. This solution effectively solves the problem of persistent vibration caused by the time-varying aging of mechanical systems, achieving lifelong adaptability of control. Constructing and continuously updating a gear backlash aging model allows for accurate prediction of the current actual backlash state for each vehicle, generating compensation coefficients to dynamically adjust torque zero-crossing damping and optimize feedforward compensation. It fully leverages the advantages of vehicle-cloud collaboration, placing complex calculations in the cloud, decoupling control performance from onboard computing resources, reducing system costs, and ensuring efficient algorithm iteration. By smoothing torque output and reducing severe impact loads, it helps reduce fatigue damage to key components of the transmission system, potentially extending the service life of mechanical components such as the gearbox, indirectly reducing long-term maintenance costs for users and after-sales warranty costs for OEMs.

[0082] Secondly, embodiments of this application also provide a dynamic compensation control system for vehicle vibration suppression.

[0083] In one embodiment, reference is made to Figure 7 , Figure 7 This is a functional module diagram of an embodiment of the dynamic compensation control system for vehicle vibration suppression according to this application. Figure 7 As shown, the dynamic compensation control device for vehicle vibration suppression includes: The vehicle-side component is used to collect vehicle status information and send it to the cloud platform. The status information includes vehicle operating status data, motor operating status data, and vibration data. The cloud platform is used to input the status information into a preset anti-shake adjustment model to obtain a set of output torque dynamic compensation parameters. The cloud platform is also used to send the set of torque dynamic compensation parameters to the vehicle. The vehicle end is also used to adjust the torque output of the drive motor according to the set of torque dynamic compensation parameters through the motor controller.

[0084] Furthermore, in one embodiment, the vehicle operating status data includes: vehicle speed, vehicle requested torque, accelerator pedal opening, transmission gear signal, driving cycle, and driving mileage; The motor operating status data includes: the drive motor speed signal, the output torque command value, the actual output torque value, and the reducer temperature; The vibration data includes vibration data of the drive assembly, reducer housing, and vehicle floor.

[0085] Furthermore, in one embodiment, the cloud platform is also used for: The anti-shake adjustment model includes a gear backlash aging prediction model and an anti-shake gain adjustment model. The state information is input into the gear backlash aging prediction model to obtain the tooth-fitting torque adjustment parameters, wherein the tooth-fitting torque adjustment parameters include the zero-crossing torque slope adjustment coefficient, the lead time constant, and the compensation amplitude gain coefficient. The state information is input into the anti-shake gain adjustment model to obtain anti-shake gain adjustment parameters, wherein the anti-shake gain adjustment parameters include active anti-shake adjustment coefficients, as well as the center frequency, attenuation depth, equivalent transmission stiffness correction factor, and damping coefficient correction factor of the filter. The tooth-fitting torque adjustment parameters and the anti-shake gain adjustment parameters are packaged together to generate the torque dynamic compensation parameter set.

[0086] Furthermore, in one embodiment, the cloud platform is also used for: The state information is input into the gear backlash aging prediction model to obtain the aging prediction result of the reducer gear pair in the drive motor, wherein the aging prediction result includes the gear backlash increment, the probability of gear pair impact, and the impact intensity. The gear backlash aging prediction model generates the tooth-fitting torque adjustment parameters based on the aging prediction results.

[0087] Furthermore, in one embodiment, the vehicle end is also used for: When the torque of the drive motor is in a state of zero torque and the driving mileage of the vehicle is less than a preset mileage threshold, the torque zero-crossing range of the drive motor is determined according to the requested torque of the vehicle. The torque zero-crossing interval is divided using the lead time constant, wherein the lead time constant includes the first moment characterizing the start of torque zero-crossing control intervention, the second moment characterizing the completion of the torque zero-crossing segment, the third moment characterizing the control torque entering the first tooth-fitting torque segment, and the fourth moment characterizing the control torque entering the second tooth-fitting torque segment. Between the first moment and the second moment, the torque slope of the output torque command value is multiplied by the first zero torque slope adjustment coefficient to obtain the first adjusted torque slope, and the torque output of the drive motor is controlled by the first adjusted torque slope. Between the second and third moments, the torque slope of the output torque command value is multiplied by the second zero torque slope adjustment coefficient to obtain the second adjusted torque slope, and the torque output of the drive motor is controlled by the second adjusted torque slope. Between the third and fourth moments, the torque slope of the output torque command value is multiplied by the third zero torque slope adjustment coefficient to obtain the third adjusted torque slope. The torque output of the drive motor is controlled by the third adjusted torque slope until the output torque of the drive motor is the same as the output torque command value. Wherein, the absolute value of the first adjustment torque slope is less than the absolute value of the torque slope of the output torque command value, and the absolute value of the second adjustment slope is greater than the absolute value of the first adjustment slope.

[0088] Furthermore, in one embodiment, the vehicle end is also used for: When the torque of the drive motor is in a state of zero torque crossing and the driving mileage of the vehicle is greater than or equal to a preset mileage threshold, between the first moment and the second moment, the first adjustment torque slope is multiplied by the compensation amplitude gain coefficient to obtain the fourth adjustment torque slope, and the torque output of the drive motor is controlled by the fourth adjustment torque slope. Between the second and third moments, the second adjustment torque slope is multiplied by the compensation amplitude gain coefficient to obtain the fifth adjustment torque slope, and the torque output of the drive motor is controlled by the fifth adjustment torque slope.

[0089] Furthermore, in one embodiment, the vehicle end is also used for: When the torque of the drive motor is not at zero, the vehicle end extracts the speed fluctuation component from the speed signal of the drive motor. Based on the requested torque of the vehicle and the speed signal of the drive motor, a preset gain coefficient matrix is ​​searched to obtain the corresponding torque gain coefficient. Multiply the torque gain coefficient by the active stabilization adjustment coefficient to obtain the final adjustment gain coefficient; The anti-shake compensation torque is obtained by inverting the speed fluctuation component and then combining it with the final adjustment gain coefficient. The vehicle's requested torque is added to the anti-shake compensation torque to obtain the vehicle's final requested torque, which is then applied to the drive motor.

[0090] Furthermore, in one embodiment, the vehicle end is also used for: Adjust the filter according to the center frequency, attenuation depth, equivalent transmission stiffness correction factor, and damping coefficient correction factor; The speed signal of the drive motor is filtered using an adjusted filter.

[0091] Furthermore, in one embodiment, the vehicle end is also used for: The vehicle-mounted device continues to collect vibration data of the vehicle and upload it to the cloud platform; The cloud platform evaluates the vibration suppression effect on the vehicle based on the continuously collected vibration data, and uses the evaluation results to iteratively optimize the anti-shake adjustment model.

[0092] The functions of each module in the above-mentioned dynamic compensation control system for vehicle vibration suppression correspond to the steps in the above-mentioned dynamic compensation control method embodiment for vehicle vibration suppression, and their functions and implementation processes will not be described in detail here.

[0093] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0094] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0095] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0096] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0097] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0098] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0099] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A dynamic compensation control method for vehicle vibration suppression, characterized in that, The dynamic compensation control method for vehicle vibration suppression includes: The vehicle-mounted system collects vehicle status information and sends it to the cloud platform. The status information includes vehicle operating status data, motor operating status data, and vibration data. The cloud platform inputs the status information into a preset anti-shake adjustment model to obtain a set of output torque dynamic compensation parameters. The cloud platform sends the set of dynamic torque compensation parameters to the vehicle. The motor controller at the vehicle end adjusts the torque output of the drive motor according to the set of torque dynamic compensation parameters.

2. The dynamic compensation control method for vehicle vibration suppression as described in claim 1, characterized in that: The vehicle operating status data includes: vehicle speed, vehicle requested torque, accelerator pedal opening, transmission gear signal, driving cycle, and driving mileage; The motor operating status data includes: the drive motor speed signal, the output torque command value, the actual output torque value, and the reducer temperature; The vibration data includes vibration data of the drive assembly, reducer housing, and vehicle floor.

3. The dynamic compensation control method for vehicle vibration suppression as described in claim 2, characterized in that, The cloud platform inputs the status information into a preset anti-shake adjustment model to obtain a set of output torque dynamic compensation parameters, including: The anti-shake adjustment model includes a gear backlash aging prediction model and an anti-shake gain adjustment model. The state information is input into the gear backlash aging prediction model to obtain the tooth-fitting torque adjustment parameters, wherein the tooth-fitting torque adjustment parameters include the zero-crossing torque slope adjustment coefficient, the lead time constant, and the compensation amplitude gain coefficient. The state information is input into the anti-shake gain adjustment model to obtain anti-shake gain adjustment parameters, wherein the anti-shake gain adjustment parameters include active anti-shake adjustment coefficients, as well as the center frequency, attenuation depth, equivalent transmission stiffness correction factor, and damping coefficient correction factor of the filter. The tooth-fitting torque adjustment parameters and the anti-shake gain adjustment parameters are packaged together to generate the torque dynamic compensation parameter set.

4. The dynamic compensation control method for vehicle vibration suppression as described in claim 3, characterized in that, The state information is input into the gear backlash aging prediction model to obtain the tooth contact torque adjustment parameters, including: The state information is input into the gear backlash aging prediction model to obtain the aging prediction result of the reducer gear pair in the drive motor, wherein the aging prediction result includes the gear backlash increment, the probability of gear pair impact, and the impact intensity. The gear backlash aging prediction model generates the tooth-fitting torque adjustment parameters based on the aging prediction results.

5. The dynamic compensation control method for vehicle vibration suppression as described in claim 4, characterized in that, The vehicle-side motor controller adjusts the torque output of the drive motor according to the set of dynamic torque compensation parameters, including: When the torque of the drive motor is in a state of zero torque and the driving mileage of the vehicle is less than a preset mileage threshold, the torque zero-crossing range of the drive motor is determined according to the requested torque of the vehicle. The torque zero-crossing interval is divided using the lead time constant, wherein the lead time constant includes the first moment characterizing the start of torque zero-crossing control intervention, the second moment characterizing the completion of the torque zero-crossing segment, the third moment characterizing the control torque entering the first tooth-fitting torque segment, and the fourth moment characterizing the control torque entering the second tooth-fitting torque segment. Between the first moment and the second moment, the torque slope of the output torque command value is multiplied by the first zero torque slope adjustment coefficient to obtain the first adjusted torque slope, and the torque output of the drive motor is controlled by the first adjusted torque slope. Between the second and third moments, the torque slope of the output torque command value is multiplied by the second zero torque slope adjustment coefficient to obtain the second adjusted torque slope, and the torque output of the drive motor is controlled by the second adjusted torque slope. Between the third and fourth moments, the torque slope of the output torque command value is multiplied by the third zero torque slope adjustment coefficient to obtain the third adjusted torque slope. The torque output of the drive motor is controlled by the third adjusted torque slope until the output torque of the drive motor is the same as the output torque command value. Wherein, the absolute value of the first adjustment torque slope is less than the absolute value of the torque slope of the output torque command value, and the absolute value of the second adjustment slope is greater than the absolute value of the first adjustment slope.

6. The dynamic compensation control method for vehicle vibration suppression as described in claim 5, characterized in that, The vehicle-side motor controller adjusts the torque output of the drive motor according to the set of dynamic torque compensation parameters, including: When the torque of the drive motor is in a state of zero torque crossing and the driving mileage of the vehicle is greater than or equal to a preset mileage threshold, between the first moment and the second moment, the first adjustment torque slope is multiplied by the compensation amplitude gain coefficient to obtain the fourth adjustment torque slope, and the torque output of the drive motor is controlled by the fourth adjustment torque slope. Between the second and third moments, the second adjustment torque slope is multiplied by the compensation amplitude gain coefficient to obtain the fifth adjustment torque slope, and the torque output of the drive motor is controlled by the fifth adjustment torque slope.

7. The dynamic compensation control method for vehicle vibration suppression as described in claim 3, characterized in that, The vehicle-side motor controller adjusts the torque output of the drive motor according to the set of dynamic torque compensation parameters, including: When the torque of the drive motor is not at zero, the vehicle end extracts the speed fluctuation component from the speed signal of the drive motor. Based on the requested torque of the vehicle and the speed signal of the drive motor, a preset gain coefficient matrix is ​​searched to obtain the corresponding torque gain coefficient. Multiply the torque gain coefficient by the active stabilization adjustment coefficient to obtain the final adjustment gain coefficient; The anti-shake compensation torque is obtained by inverting the speed fluctuation component and then combining it with the final adjustment gain coefficient. The vehicle's requested torque is added to the anti-shake compensation torque to obtain the vehicle's final requested torque, which is then applied to the drive motor.

8. The dynamic compensation control method for vehicle vibration suppression as described in claim 7, characterized in that, Before the vehicle end extracts the speed fluctuation component from the speed signal of the drive motor, the method further includes: Adjust the filter according to the center frequency, attenuation depth, equivalent transmission stiffness correction factor, and damping coefficient correction factor; The speed signal of the drive motor is filtered using an adjusted filter.

9. The dynamic compensation control method for vehicle vibration suppression as described in claim 1, characterized in that, After the motor controller at the vehicle end adjusts the torque output of the drive motor according to the set of torque dynamic compensation parameters, it also includes: The vehicle-mounted device continues to collect vibration data of the vehicle and upload it to the cloud platform; The cloud platform evaluates the vibration suppression effect on the vehicle based on the continuously collected vibration data, and uses the evaluation results to iteratively optimize the anti-shake adjustment model.

10. A dynamic compensation control system for vehicle vibration suppression, characterized in that, The dynamic compensation control system for vehicle vibration suppression includes: The vehicle-side component is used to collect vehicle status information and send it to the cloud platform. The status information includes vehicle operating status data, motor operating status data, and vibration data. The cloud platform is used to input the status information into a preset anti-shake adjustment model to obtain a set of output torque dynamic compensation parameters. The cloud platform is also used to send the set of torque dynamic compensation parameters to the vehicle. The vehicle end is also used to adjust the torque output of the drive motor according to the set of torque dynamic compensation parameters through the motor controller.

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