Torque control method, device and equipment for vehicle modal switching, and medium

Abstract

The application discloses a torque control method, device, equipment and medium for vehicle mode switching, and relates to the field of torque control. The method comprises the following steps: obtaining the accelerator pedal opening degree of a vehicle, and determining the user expected torque according to the accelerator pedal opening degree; in the case that the vehicle is in an intelligent driving mode, determining the target wheel end torque of the vehicle according to the user expected torque and the intelligent driving torque, and determining the target torque difference according to the size relationship between the target wheel end torque and the preset first torque threshold; determining whether the vehicle meets the switching condition of the man-machine co-driving state according to the accelerator pedal opening degree, the size relationship between the torque difference between the user expected torque and the intelligent driving torque and the target torque difference; and if yes, controlling the vehicle to switch to the man-machine co-driving state based on a torque control strategy. The application can reduce the driving torque fluctuation caused by the jump between the intelligent driving torque and the user expected torque, and realize accurate identification and smooth transition of the man-machine co-driving state.

Description

Technical Field

[0001] This application belongs to the field of torque control, specifically relating to a torque control method, device, equipment, and medium for vehicle mode switching. Background Technology

[0002] Vehicles equipped with intelligent driving systems typically have a human-driven mode and an intelligent driving mode. In intelligent driving mode, the vehicle automatically controls its movement based entirely on the intelligent driving torque calculated by the system, without driver intervention. However, real-world driving scenarios are complex and varied. When the driver actively presses the accelerator pedal in intelligent driving mode, it is necessary to recognize the driver's intention to intervene and appropriately allocate control to determine whether to switch the vehicle to a human-machine co-driving state (a state in which the driver and the intelligent driving system jointly control the power, which belongs to intelligent driving mode) within intelligent driving mode.

[0003] Related technologies typically control the vehicle's entry into and exit from human-machine co-driving mode based on the relationship between the driver's accelerator pedal opening and a fixed threshold opening. If the driver misoperates the accelerator pedal, causing the accelerator pedal opening to fluctuate around the fixed threshold opening, or if road bumps cause momentary fluctuations in torque command, frequent and unexpected switching of the human-machine co-driving state will occur. Such switching is accompanied by jumps between the intelligent driving torque and the driver's desired torque, resulting in fluctuations in the vehicle's driving torque and thus producing a noticeable driving jolt. Summary of the Invention

[0004] This application provides a method, apparatus, device, and medium for torque control during vehicle mode switching, which can improve torque abrupt changes and driving jerks. This application provides the following technical solution: In a first aspect, embodiments of this application provide a torque control method for vehicle mode switching, comprising: acquiring the accelerator pedal opening of the vehicle, and determining the user's desired torque based on the accelerator pedal opening; when the vehicle is in intelligent driving mode, determining the target wheel-end torque of the vehicle based on the user's desired torque and the intelligent driving torque, and determining a target torque difference based on the relationship between the target wheel-end torque and a preset first torque threshold; determining whether the vehicle meets the switching conditions for human-machine co-driving state based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and the intelligent driving torque and the target torque difference; if so, controlling the vehicle to switch to the human-machine co-driving state based on a torque control strategy.

[0005] By adopting the above technical solution, the accelerator pedal opening is obtained to determine the user's desired torque. In intelligent driving mode, the target wheel-end torque is determined based on the user's desired torque and the intelligent driving torque. The dynamic target torque difference is then determined based on the relationship between this target wheel-end torque and a preset first torque threshold. This replaces the single judgment method in related technologies that relies solely on a fixed opening threshold, thereby reducing frequent and unexpected switching caused by instantaneous torque fluctuations due to accidental pedal touch or road bumps. Simultaneously, based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and the intelligent driving torque and the target torque difference, it is determined whether the switching conditions for human-machine co-driving are met, thus distinguishing between the driver's genuine intervention intention and disturbance signals, effectively filtering out false triggers. If the switching conditions are met, a switching is performed based on a torque control strategy, which can smoothly adjust the torque output during the state transition process, reducing drive torque fluctuations caused by jumps between the intelligent driving torque and the user's desired torque, thereby improving the driving experience and achieving accurate identification and smooth transition of the human-machine co-driving state.

[0006] Optionally, determining the target wheel-end torque of the vehicle based on the user-expected torque and the intelligent driving torque includes: if the vehicle's driving state is the human-machine co-driving state, then the user-expected torque is determined as the target wheel-end torque of the vehicle; if the vehicle's driving state is not the human-machine co-driving state, then the intelligent driving torque is determined as the target wheel-end torque; determining the target torque difference based on the relationship between the target wheel-end torque and a preset first torque threshold includes: if the target wheel-end torque is less than or equal to the preset first torque threshold, then the preset torque difference is used as the target torque difference; if the target wheel-end torque is greater than the preset first torque threshold, then the product of the target wheel-end torque and a preset coefficient is used as the target torque difference.

[0007] By adopting the above technical solutions, a branch judgment mechanism based on driving status enables a smooth switch of control between the driver and the intelligent driving system, effectively reducing torque command conflicts caused by unclear control ownership. The dynamic target torque difference determination method allows for the use of a fixed preset torque difference as the target torque difference under low torque conditions, reducing the possibility of minor torque fluctuations caused by road bumps being misjudged as effective intervention, and minimizing false triggering due to oversensitivity, thus ensuring control accuracy. Simultaneously, under high torque conditions, the target torque difference can change linearly with the target wheel-end torque, improving the insufficient sensitivity caused by fixed values ​​and ensuring accurate assessment of the significance of torque changes under different load conditions.

[0008] Optionally, based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and the intelligent driving torque and the target torque difference, it is determined whether the vehicle meets the switching conditions for human-machine co-driving state, including: if the accelerator pedal opening is greater than or equal to a preset first opening, and the torque difference between the user's desired torque and the intelligent driving torque is greater than or equal to the target torque difference, then it is determined that the vehicle meets the initial switching conditions for entering the human-machine co-driving state, and the duration of meeting the initial switching conditions is recorded; if the duration is greater than or equal to a preset first duration, then it is determined that the vehicle meets the switching conditions for entering the human-machine co-driving state.

[0009] By adopting the above technical solution, introducing dual judgment conditions of accelerator pedal opening and torque difference, as well as a time filtering mechanism, the frequent state jumps caused by fluctuations near a single threshold are effectively reduced, and the stability of vehicle driving state switching is improved.

[0010] Optionally, based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and the intelligent driving torque and the target torque difference, it is determined whether the vehicle meets the switching conditions for the human-machine co-driving state, including: when the vehicle's driving state is the human-machine co-driving state, if the accelerator pedal opening is less than or equal to a preset second opening, and the torque difference between the user's desired torque and the intelligent driving torque is less than or equal to the target torque difference, then it is determined that the vehicle meets the switching conditions for exiting the human-machine co-driving state.

[0011] By adopting the above technical solution, based on the dual-parameter joint constraint of the accelerator pedal opening and torque difference and the hysteresis arbitration method, the fluctuation of the accelerator pedal opening around a single threshold caused by slight vibration of the driver's foot or road bumps is effectively reduced. This prevents the vehicle from frequently entering and exiting the human-machine co-driving state, significantly improves the stability of the mode switching process, and reduces the driving torque fluctuation and driving jerking caused by frequent changes in the vehicle's driving state.

[0012] Optionally, based on a torque control strategy, controlling the vehicle to switch between human-machine co-driving states includes: determining a filter cutoff frequency based on the relationship between the vehicle speed and a preset vehicle speed; determining a filter coefficient based on the filter cutoff frequency and the duration of a unit control cycle; calculating the current filter output torque based on the filter coefficient, the target wheel-end torque, and the historical filter output torque; and controlling the vehicle to switch between human-machine co-driving states based on the current filter output torque.

[0013] By adopting the above technical solution, the filter cutoff frequency is determined based on the relationship between the vehicle speed and the preset vehicle speed, and the filter coefficient is accurately calculated in combination with the unit control cycle duration. This enables the filtering strategy to adaptively adjust with the vehicle's operating state, thereby improving the adaptability of the torque filtering control strategy to the vehicle's operating state.

[0014] Optionally, controlling the vehicle to switch to the human-machine co-driving state based on the current filtered output torque includes: dividing the difference between the current filtered output torque and the target wheel-end torque by the target wheel-end torque to obtain a quotient; if the absolute value of the quotient is greater than a constraint parameter, then compensating the current filtered output torque, and controlling the vehicle to switch to the human-machine co-driving state based on the compensated current filtered output torque; wherein the constraint parameter is a parameter determined according to the relationship between the target wheel-end torque and a preset second torque threshold.

[0015] By adopting the above technical solution, the difference between the current filtered output torque and the target wheel end torque is normalized into a quotient value and compared with the constraint parameters set in segments, which can meet the accuracy requirements for identifying different torque levels.

[0016] Optionally, the torque control method further includes: during the process of the vehicle switching from the intelligent driving mode to the human driving mode, determining the current filtered output torque based on the torque control strategy; calculating the current torque change rate based on the current filtered output torque and the historical filtered output torque; if the current torque change rate is less than or equal to a preset second change rate, then outputting torque based on the current filtered output torque; if the current torque change rate is greater than the preset second change rate, then compensating the current filtered output torque, and outputting torque based on the compensated current filtered output torque.

[0017] By adopting the above technical solution, a secondary verification and compensation mechanism based on a preset second rate of change is introduced during the vehicle's transition from intelligent driving mode to human driving mode. This mechanism calculates the current torque change rate based on the difference between the current filtered output torque and the historical filtered output torque, and compares the current torque change rate with the preset second rate of change, achieving refined control of the torque gradient. When the current torque change rate is within a safe range, it is output to ensure response speed. If the current torque change rate is too large, compensation logic is triggered to forcibly smooth the torque curve.

[0018] Optionally, before determining the current filtered output torque based on the torque control strategy, the torque control method further includes: acquiring torque control configuration parameters; if the torque control configuration parameters are in a first state, then performing the step of determining the current filtered output torque based on the torque control strategy; if the torque control configuration parameters are in a second state, then controlling the vehicle to output torque based on a preset second rate of change.

[0019] By adopting the above technical solution and introducing torque control configuration parameters, dynamic selectivity of the torque control strategy is achieved. By comparing these parameters with preset states, in the first state, the current filtered output torque can be determined based on the torque control strategy, and a torque gradient change limiting strategy can be implemented to reduce the probability of torque jumps. In the second state, the torque output is constrained by a fixed preset rate of change, ensuring that the vehicle can maintain basic torque output stability and safety under various extreme or abnormal operating conditions.

[0020] Optionally, based on a torque control strategy, controlling the vehicle to switch to the human-machine co-driving state includes: if the target wheel-end torque is in a preset zero-crossing torque range, then within a preset second time period, a preset compensation torque is superimposed on the target wheel-end torque based on a preset first rate of change to obtain a compensated target wheel-end torque, and based on the compensated target wheel-end torque, controlling the vehicle to switch to the human-machine co-driving state.

[0021] By adopting the above technical solution, during the switching of the vehicle into human-machine co-driving mode based on torque control strategy, a torque zero-crossing control strategy is executed in conjunction with the torque control strategy. This allows for timely compensation when the target wheel-end torque is within the preset zero-crossing torque range, improving vehicle vibration, stalling, and jerking issues during the torque zero-crossing phase. This active compensation mechanism effectively counteracts the negative impacts of motor inertia and transmission backlash, eliminating vibration and lag during the torque zero-crossing phase. Furthermore, since the compensated target wheel-end torque is the final torque command after zero-crossing smoothing, its value has deviated from the preset zero-crossing torque range, exhibiting higher stability and linearity. Therefore, controlling the vehicle to switch into human-machine co-driving mode based on the compensated target wheel-end torque ensures smooth and continuous output when crossing the preset zero-crossing torque range.

[0022] Secondly, embodiments of this application provide a torque control device for vehicle mode switching, comprising: an acquisition module, configured to acquire the accelerator pedal opening of the vehicle and determine the user's desired torque based on the accelerator pedal opening; a first determination module, configured to, when the vehicle is in intelligent driving mode, determine the target wheel-end torque of the vehicle based on the user's desired torque and the intelligent driving torque, and determine a target torque difference based on the relationship between the target wheel-end torque and a preset first torque threshold; a second determination module, configured to determine whether the vehicle meets the switching conditions for human-machine co-driving state based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and the intelligent driving torque and the target torque difference; and a control module, configured to, if the conditions are met, control the vehicle to switch to the human-machine co-driving state based on a torque control strategy.

[0023] By adopting the above technical solution, the various steps of the torque control method are modularized, which facilitates the implementation and maintenance of software and hardware. Each module has a clear function and works together to complete the entire process from obtaining the accelerator pedal opening to switching the driving state.

[0024] Thirdly, embodiments of this application provide an electronic device including a processor; a memory and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the torque control method as described in the first aspect.

[0025] By adopting the above technical solution, a hardware entity that carries the above torque control method is provided, enabling the method to be deployed and applied in actual electronic systems.

[0026] Fourthly, embodiments of this application provide a storage medium storing a program or instructions that, when executed by a processor, implement the torque control method as described in the first aspect.

[0027] By adopting the above technical solution, a medium for storing the above program or instructions is provided, which facilitates the dissemination, replication, loading, and execution of the torque control method on various electronic devices.

[0028] Understandably, the torque control device provided in the second aspect, the electronic device provided in the third aspect, and the storage medium provided in the fourth aspect are all used to execute some or all of the methods provided in this application. Therefore, the beneficial effects they can achieve also include the beneficial effects of the corresponding methods, which will not be elaborated here.

[0029] In summary, one or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: By acquiring the accelerator pedal opening, the user's desired torque is determined. In intelligent driving mode, the target wheel-end torque is determined based on the user's desired torque and the intelligent driving torque. The dynamic target torque difference is then determined based on the relationship between this target wheel-end torque and a preset first torque threshold. This replaces the single judgment method in related technologies that relies solely on a fixed opening threshold, thereby reducing frequent and unexpected switching caused by instantaneous torque fluctuations due to accidental pedal touches or road bumps. Simultaneously, based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and the intelligent driving torque and the target torque difference, the system determines whether the switching conditions for human-machine co-driving are met. This distinguishes between the driver's genuine intervention intentions and disturbance signals, effectively filtering out false triggers. If the switching conditions are met, a torque control strategy is used to switch, smoothly adjusting the torque output during the state transition. This reduces drive torque fluctuations caused by jumps between the intelligent driving torque and the user's desired torque, improving the driving experience and achieving accurate identification and smooth transition of the human-machine co-driving state.

[0030] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more easily understood, specific embodiments of this application are given below. Attached Figure Description

[0031] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0032] Figure 1 This is a schematic flowchart illustrating a torque control method for vehicle mode switching, as shown in an exemplary embodiment of this application.

[0033] Figure 2 Based on Figure 1 The exemplary embodiment shown illustrates a flowchart of another torque control method for vehicle mode switching.

[0034] Figure 3 This is a schematic diagram illustrating an application scenario of the torque control method for vehicle mode switching in this application.

[0035] Figure 4 This is a schematic diagram of the structure of a torque control device for vehicle mode switching, as illustrated in an exemplary embodiment of this application.

[0036] Figure 5This is a schematic diagram of the structure of a computer system for an electronic device illustrated in an exemplary embodiment of this application. Detailed Implementation

[0037] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0038] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0039] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0040] In this application, "multiple" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0041] Related technologies typically control the vehicle's entry into and exit from human-machine co-driving mode based on the relationship between the driver's accelerator pedal opening and a fixed threshold opening. If the driver misoperates the accelerator pedal, causing the accelerator pedal opening to fluctuate around the fixed threshold opening, or if road bumps cause momentary fluctuations in torque command, frequent and unexpected switching of the human-machine co-driving state will occur. Such switching is accompanied by jumps between the intelligent driving torque and the driver's desired torque, resulting in fluctuations in the vehicle's driving torque and thus producing a noticeable driving jolt.

[0042] One aspect of this application provides a torque control method for vehicle mode switching, which can accurately identify the driver's intervention intention in intelligent driving mode and achieve smooth mode switching, improving vehicle torque jumps and driving jerks, thereby significantly enhancing driving comfort. Please refer to Figure 1 , Figure 1This is a schematic flowchart illustrating a torque control method according to an exemplary embodiment of this application. The torque control method includes at least steps S110 to S140, as described below: S110 acquires the accelerator pedal opening of the vehicle and determines the user's desired torque based on the accelerator pedal opening.

[0043] Accelerator pedal opening is a parameter that characterizes the degree to which the accelerator pedal is open or closed. It refers to the percentage value of the electrical signal obtained by converting the physical travel of the accelerator pedal when it is pressed, and it comes from the accelerator pedal position sensor.

[0044] User-desired torque is the longitudinal driving torque that a driver expects the vehicle to output when pressing the accelerator pedal; it characterizes the driver's desired real-time power demand. The accelerator pedal opening can be substituted into a pre-calibrated accelerator pedal opening-torque mapping curve to determine the corresponding preset torque, which is then identified as the user-desired torque. In some implementations, to more accurately determine the user-desired torque, vehicle operating parameters such as gear position and speed are also incorporated for collaborative judgment.

[0045] For example, the executing entity acquires the accelerator pedal opening at fixed periodic intervals or in real time, and combines this with vehicle operating parameters such as gear position signal and vehicle speed signal to query the torque request curve, thereby obtaining the corresponding wheel-end torque required by the driver, i.e., the user's expected torque. For instance, if the accelerator pedal opening is 30% and the vehicle is in D gear (drive), the accelerator pedal opening and gear position signal are substituted into a pre-calibrated mapping relationship to determine that the user's expected torque is 150 Nm. By analyzing the accelerator pedal opening, the driver's intention to intervene in power can be accurately quantified.

[0046] When the vehicle is in intelligent driving mode, S120 determines the target wheel-end torque of the vehicle based on the user's desired torque and the intelligent driving torque, and determines the target torque difference based on the relationship between the target wheel-end torque and the preset first torque threshold.

[0047] Intelligent driving mode is a working mode in which the vehicle automatically controls its driving. In this mode, the vehicle's longitudinal drive torque is controlled based on the intelligent driving torque calculated by the intelligent driving system. The driver does not need to operate the accelerator or brake pedal, and the vehicle can autonomously follow the vehicle in front, maintain its speed, or execute other longitudinal movement commands. The intelligent driving torque can be the torque value calculated by the intelligent driving system based on the perceived environment, planned path, and vehicle dynamics model.

[0048] The target wheel-end torque is the torque value to be applied to the vehicle's drive wheels, which is obtained through arbitration within the control cycle and is determined based on the priority of the user's desired torque and the intelligent driving torque or the vehicle's driving status.

[0049] For example, the priority of the user-expected torque and the intelligent driving torque is arbitrated, and the torque with higher priority is used as the target wheel-end torque. For instance, the user-expected torque is set to have a higher priority than the intelligent driving torque to respond first to the driver's real-time acceleration intention. If the intelligent driving torque is 50 Nm, and the user-expected torque generated by the driver pressing the accelerator pedal is 80 Nm, then the arbitration result is that the user-expected torque has a higher priority, and the target wheel-end torque is determined to be 80 Nm.

[0050] In another example, the human-machine co-driving state is used as the basis for arbitration to achieve reasonable switching of the target wheel-end torque under different driving states. The human-machine co-driving state refers to the state in which the driver and the intelligent driving system jointly participate in the vehicle's power control, which belongs to the vehicle driving state under intelligent driving mode, such as the Override state. In intelligent driving mode, based on the arbitration result of whether the vehicle is in a human-machine co-driving state, the target wheel-end torque is determined to be either the user-expected torque or the intelligent driving torque. If the vehicle's driving state is a human-machine co-driving state, the user-expected torque is determined as the vehicle's target wheel-end torque; if the vehicle's driving state is not a human-machine co-driving state, the intelligent driving torque is determined as the target wheel-end torque.

[0051] In this system, if the vehicle is in a human-machine co-driving state, it indicates that the driver has actively intervened and made a clear demand on the vehicle's power output. The user's desired torque is set as the target wheel torque to prioritize the driver's control intentions and ensure the intuitiveness of the human-machine co-driving experience. For example, in human-machine co-driving mode, if the driver presses the accelerator pedal, resulting in a user's desired torque of 300 Nm and the intelligent driving torque of 150 Nm, the target wheel torque is set to 300 Nm. Conversely, if the vehicle is not in a human-machine co-driving state, i.e., in pure intelligent driving mode without effective driver intervention, the intelligent driving torque is set as the target wheel torque to maintain intelligent driving. For example, during pure intelligent driving cruise, regardless of slight fluctuations in the accelerator pedal, as long as the human-machine co-driving condition is not triggered, the target wheel torque always follows the changes in the intelligent driving torque. This branching judgment method based on driving state enables a smooth switch of control between the driver and the intelligent driving system, effectively reducing torque command conflicts caused by unclear control ownership.

[0052] The target torque difference is not a conventional static threshold, but a dynamic threshold used to determine the switching of human-machine co-driving states. It is determined segmentally based on the relationship between the target wheel-end torque and a preset first torque threshold. For example, if the target wheel-end torque is less than or equal to the preset first torque threshold, the preset torque difference is used as the target torque difference; if the target wheel-end torque is greater than the preset first torque threshold, the product of the target wheel-end torque and a preset coefficient is used as the target torque difference. Here, the preset first torque threshold is the critical torque value that distinguishes between high-torque and low-torque operating conditions, and the preset coefficient is a constant value. Both the preset first torque threshold and the preset coefficient are preset parameters configured according to the actual scenario, serving as the basic judgment parameters for the corresponding judgment conditions. This application does not limit their specific values. In other embodiments, when the target wheel-end torque equals the preset first torque threshold, the specific value of the target torque difference can be determined according to actual application requirements. The target torque difference can be the preset torque difference or the product of the target wheel-end torque and the preset coefficient; this application does not impose specific limitations.

[0053] For example, if the preset first torque threshold is 1000 Nm, and the target wheel-end torque is 800 Nm (less than the preset first torque threshold), then the preset torque difference of 50 Nm is used as the target torque difference. If the target wheel-end torque is 2000 Nm (greater than the preset first torque threshold), then the product of this torque difference and a preset coefficient of 0.05 is used as the target torque difference, i.e., 2000 Nm × 0.05 = 100 Nm. This segmented approach to obtaining a dynamic target torque difference allows for the use of a fixed preset torque difference under low torque conditions (i.e., when the target wheel-end torque is less than or equal to the preset first torque threshold). This reduces the possibility of small torque fluctuations caused by road bumps being misinterpreted as effective intervention, and reduces false triggering due to oversensitivity, thus ensuring control accuracy. Simultaneously, under high torque conditions (i.e., when the target wheel-end torque is greater than the preset first torque threshold), the target torque difference changes linearly with the target wheel-end torque, improving the insufficient sensitivity caused by a fixed value and ensuring accurate assessment of the significance of torque changes under different load conditions.

[0054] S130 determines whether the vehicle meets the switching conditions for human-machine co-driving state based on the accelerator pedal opening and the relationship between the torque difference between the user's expected torque and the intelligent driving torque and the target torque difference.

[0055] Human-machine co-driving state refers to the state in which the driver and the intelligent driving system jointly participate in the vehicle's power control, which belongs to the vehicle driving state under the intelligent driving mode. The switching condition for human-machine co-driving state refers to the logical criterion that triggers the vehicle to enter or exit the human-machine co-driving state, which is determined based on the joint constraint of the accelerator pedal opening and the torque difference. This embodiment uses a similar two-parameter hysteresis arbitration model to distinguish between the driver's true intervention intention and disturbance signals caused by road bumps or accidental touches. The following is an exemplary description of S130: For example, if the accelerator pedal opening is greater than or equal to a preset first opening, and the torque difference between the user's desired torque and the intelligent driving torque is greater than or equal to the target torque difference, then the vehicle is determined to meet the initial switching conditions for entering the human-machine co-driving state, and the duration of meeting the initial switching conditions is recorded; if the duration is greater than or equal to the preset first duration, then the vehicle is determined to meet the switching conditions for entering the human-machine co-driving state. Here, the preset first opening is a threshold value for the accelerator pedal position indicating a clear intention for driver intervention, and its value can be set based on vehicle calibration data. The preset first duration is the minimum duration threshold required to confirm the validity of the driver's intervention intention, used to verify the stability of the driver's operation. The duration is the length of time the initial switching conditions are continuously maintained.

[0056] When the accelerator pedal opening is greater than or equal to a preset first opening, and the difference between the driver's required torque and the intelligent driving torque is greater than or equal to the target torque difference, the vehicle is determined to meet the initial conditions for entering the human-machine co-driving state. This dual-parameter joint constraint can reduce misjudgments caused by relying solely on pedal opening, such as when road bumps cause instantaneous fluctuations in torque commands, and / or when the driver slightly touches the pedal accidentally.

[0057] The moment the executing entity determines that the initial switching conditions are met, it begins recording the duration for which these conditions are met. If, during the timing process, the accelerator pedal opening falls below a preset first opening, or the torque difference decreases below the target torque difference, the initial switching conditions are no longer met, the timer is reset, and it waits to restart. By introducing time-dimensional constraints, momentary false trigger signals caused by signal noise, driver foot tremors, or brief misoperations can be effectively filtered out.

[0058] If any judgment condition changes before the preset first duration is reached, causing the initial condition to be unmet, then the intervention is deemed invalid, and the vehicle maintains its original intelligent driving mode.

[0059] If the cumulative recorded duration reaches or exceeds the preset first duration, the vehicle is confirmed to meet the switching conditions for entering the human-machine co-driving state, and the vehicle in intelligent driving mode is controlled to enter the human-machine co-driving state; if the vehicle's original driving state is already the human-machine co-driving state in intelligent driving mode, the control operation here can be understood as maintaining the vehicle's human-machine co-driving state.

[0060] This example effectively reduces frequent state transitions caused by fluctuations around a single threshold by introducing dual judgment conditions of accelerator pedal opening and torque difference, as well as a time filtering mechanism, thereby improving the stability of vehicle driving state switching.

[0061] In another example, when the vehicle is in a human-machine co-driving state, if the accelerator pedal opening is less than or equal to a preset second opening, and the torque difference between the user's desired torque and the intelligent driving torque is less than or equal to the target torque difference, then the vehicle is determined to meet the switching conditions for exiting the human-machine co-driving state. The preset second opening is a critical accelerator pedal value used to determine the driver's intention to control the vehicle and exit the human-machine co-driving state. Its value is set lower than the preset first opening required to enter the human-machine co-driving state, thus forming a hysteresis interval in the opening dimension.

[0062] If the accelerator pedal opening drops to a preset second opening or below, and the torque difference between the user's desired torque and the intelligent driving torque converges to a target torque difference or below, it indicates that the driver has actively reduced the power request and relinquished control. This confirms that the vehicle meets the switching conditions for exiting the human-machine co-driving state, and the vehicle is controlled to exit the human-machine co-driving state. Through the dual-parameter joint constraint of accelerator pedal opening and torque difference and the hysteresis arbitration method, the fluctuation of accelerator pedal opening around a single threshold caused by slight vibrations of the driver's foot or road bumps is effectively reduced. This prevents the vehicle from frequently entering and exiting the human-machine co-driving state, significantly improving the stability of the mode switching process and reducing the driving torque fluctuations and driving jerks caused by frequent changes in vehicle driving state.

[0063] In some implementations, the human-machine co-driving state exit condition in this example is combined with the aforementioned human-machine co-driving state entry condition to form an asymmetric hysteresis logic. This means that entering the human-machine co-driving state requires a relatively large accelerator pedal opening and a large positive torque difference, while exiting the state requires a relatively small accelerator pedal opening and a small torque difference. This differentiated threshold configuration can accurately identify the driver's true intention, filter out misjudgment interference, and significantly improve the stability of the mode switching process. Furthermore, some implementations also incorporate the dynamic target torque difference from the aforementioned example. Because the target torque difference is adjusted in segments according to the target wheel-end torque, the adaptability of the judgment conditions for entering and exiting the human-machine co-driving state can be improved. This allows for the use of a fixed threshold to ensure control accuracy under low torque conditions, and a dynamic threshold to avoid false exits under high torque conditions, thus ensuring control sensitivity.

[0064] If S140 is satisfied, then based on the torque control strategy, the vehicle will be controlled to switch to human-machine co-driving mode.

[0065] The torque control strategy is a torque filtering control strategy used to smooth the vehicle's output torque during vehicle mode switching and / or driving state switching.

[0066] If the torque output after the switch to the new driving mode is directly applied, it will cause a sudden torque change, resulting in a noticeable jerkiness in the vehicle. This embodiment uses a torque control strategy to control the smooth change of the vehicle's output torque, thereby improving the jerkiness during the transition between driving modes.

[0067] For example, the filter cutoff frequency is determined based on the relationship between the vehicle speed and the preset vehicle speed; the filter coefficient is determined based on the filter cutoff frequency and the unit control cycle duration; the current filter output torque is calculated based on the filter coefficient, the target wheel-end torque, and the historical filter output torque; and the vehicle is controlled to switch to human-machine co-driving mode based on the current filter output torque. Here, the filter cutoff frequency is a frequency parameter used in the first-order inertial filtering algorithm to define the bandwidth through which the signal passes; its value determines the response speed and smoothness of the filter. The filter coefficient is a weighting parameter in the discrete domain filtering algorithm, typically ranging from 0 to 1. The closer the value is to 1, the weaker the filtering effect and the faster the response; the closer the value is to 0, the stronger the filtering effect and the smoother the torque delivery.

[0068] The filter cutoff frequency is determined by real-time vehicle speed monitoring and comparison with a pre-calibrated preset speed. For example, a mapping relationship between vehicle speed and filter cutoff frequency is pre-stored, automatically matching the corresponding cutoff frequency value for different speed ranges. In low-speed driving scenarios (e.g., less than 15 km / h), a relatively low filter cutoff frequency (e.g., 8Hz to 12Hz) is chosen to prioritize ride smoothness and suppress jerking caused by uneven road surfaces or torque fluctuations. In medium-to-high-speed driving scenarios (e.g., greater than or equal to 15 km / h), a relatively high filter cutoff frequency (e.g., 15Hz to 20Hz) is chosen to meet the driver's need for immediate power response. In relatively low-speed ranges, a relatively low cutoff frequency enhances the filtering effect, effectively suppressing jerking caused by torque fluctuations. In relatively high-speed ranges, a relatively high cutoff frequency weakens the filtering intensity, ensuring agile power response.

[0069] The formula for calculating the filter coefficients is: ;in, These are the filter coefficients; This is the filter cutoff frequency; is the unit control cycle duration, for example, the control cycle duration of VDC (Vehicle Dynamics Control) (10ms); e is a natural constant, with a value of approximately 2.71828.

[0070] The current filtered output torque is calculated using the following formula: ;in, This represents the current filtered output torque. This refers to the filtered output torque of the previous control cycle adjacent to the current control cycle, i.e., the historical filtered output torque. These are the filter coefficients; The target wheel-end torque is used. Therefore, the filter coefficient is essentially calculated dynamically based on vehicle speed. Here, the target wheel-end torque is weighted and fused with the historical filtered output torque to calculate the current filtered output torque. Essentially, this transforms the abruptly changing torque command into a continuously and gradually changing physical quantity. This not only improves the instantaneous torque jumps caused by driving state switching but also ensures the continuity of the filter channel throughout the entire driving state switching process, reducing secondary shocks caused by parameter mutations or filter interruptions, thus achieving smooth and comfortable torque output.

[0071] For example, during the transition from human-machine co-driving mode, if the target wheel-end torque suddenly changes from the intelligent driving torque of 200 Nm to the user-desired torque of 400 Nm, due to the filtering coefficient, the output torque in the current cycle will not immediately jump to 400 Nm. Instead, it will gradually increase to 300 Nm and then gradually approach 400 Nm in subsequent cycles, thus forming a smooth torque rise curve. The execution unit sends the current filtered output torque to the front and rear drive motor MCUs (Microcontroller Units) to execute the torque output, thereby achieving a smooth transition during the human-machine co-driving mode transition.

[0072] This example determines the filter cutoff frequency based on the relationship between the vehicle speed and the preset vehicle speed, and accurately calculates the filter coefficient by combining the unit control cycle duration. This allows the torque filter control strategy to adaptively adjust according to the vehicle's operating state, thereby improving the adaptability of the torque filter control strategy to the vehicle's operating state.

[0073] In some feasible implementations, the method of controlling the vehicle to switch to human-machine co-driving mode based on the current filtered output torque is described below: The difference between the current filtered output torque and the target wheel-end torque is divided by the target wheel-end torque to obtain a quotient. If the absolute value of the quotient is greater than the constraint parameter, the current filtered output torque is compensated, and the vehicle is controlled to switch to human-machine co-driving mode based on the compensated current filtered output torque. The constraint parameter is determined based on the relationship between the target wheel-end torque and a preset second torque threshold. The quotient is used to quantify the relative deviation between the current filtered output torque and the target wheel-end torque. If the absolute value of the quotient is greater than the constraint parameter, it is determined that the current filtered output torque has an excessive deviation, and compensation logic needs to be triggered; otherwise, if it is less than or equal to the constraint parameter, the current filtered output torque remains unchanged.

[0074] The constraint parameters are not fixed values, but are dynamically set in stages based on the relationship between the target wheel-end torque and the preset second torque threshold to adapt to the control characteristics of different torque ranges. If the target wheel-end torque is greater than the preset second torque threshold (e.g., 1100 Nm), i.e., a relatively high torque condition, the constraint parameters are calculated based on the target wheel-end torque and a preset proportional coefficient (e.g., the constraint parameter is 5% of the target wheel-end torque) to strictly limit the relative error under high torque conditions and ensure control accuracy under high loads. If the target wheel-end torque is less than or equal to the preset second torque threshold, i.e., a relatively low torque condition (e.g., a target wheel-end torque less than or equal to 1100 Nm), the constraint parameters can be set to the preset torque threshold (e.g., ±65 Nm + 10 Nm) to reduce false compensation caused by excessive error sensitivity under low torque conditions.

[0075] For example, the expression for the quotient is: ;in, This represents the current filtered output torque. Let the target wheel-end torque be 1000 Nm. If the target wheel-end torque is 1000 Nm and the current filtered output torque is 940 Nm, the difference is -60 Nm, and the calculated quotient is -0.06, with an absolute value of 0.06. The current constraint parameter is 0.05. Because the absolute value of the quotient is greater than the constraint parameter, the current filtered output torque is compensated to ensure that the compensated current filtered output torque meets the deviation requirement, i.e., the relative deviation between the compensated current filtered output torque and the target wheel-end torque is less than or equal to 0.05. Based on the compensated current filtered output torque, the vehicle is controlled to switch to human-machine co-driving mode. The compensation can be derived by back-calculating the target filtered output torque that meets the deviation requirement based on the current constraint parameter, and this target filtered output torque can be directly used as the compensated current filtered output torque. For example, if the target wheel-end torque is 1000 Nm and the current constraint parameter is 0.05, substituting them into the above quotient expression yields a compensated current filtered output torque of 1050 Nm.

[0076] By normalizing the difference between the current filtered output torque and the target wheel end torque into a quotient value and comparing it with the constraint parameters set in segments, the accuracy requirements for identifying different torque levels can be met.

[0077] In some implementation methods, during the execution of S140, a torque zero-crossing control strategy is executed in conjunction with the torque output to compensate for the target wheel-end torque when it is within a preset zero-crossing torque range. This improves the vehicle vibration, stalling, and jerking issues during the torque zero-crossing phase, as described below: If the target wheel-end torque is within the preset zero-crossing torque range, then within the preset second time period, the preset compensation torque is superimposed on the target wheel-end torque based on the preset first rate of change to obtain the compensated target wheel-end torque, and based on the compensated target wheel-end torque, the vehicle is controlled to switch to human-machine co-driving mode.

[0078] The zero-torque range refers to the sensitive nonlinear region during the switching process between drive torque and regenerative torque. Due to physical characteristics such as motor rotor inertia, reducer gear clearance, and abrupt changes in the direction of friction torque, directly switching torque commands can easily cause output torque jitter, stagnation, or obvious jerking.

[0079] The preset compensation torque is a pre-calibrated compensation torque value, the magnitude of which is determined based on the mechanical clearance characteristics of the powertrain. It is used to provide sufficient driving torque to quickly move out of the preset zero-crossing torque range.

[0080] The preset first rate of change refers to the speed limit of the compensation torque superposition process to avoid abrupt changes in torque command. This rate of change can be set according to the vehicle's ride comfort requirements.

[0081] The preset second duration refers to the maximum allowable time window for completing the compensation torque superposition action.

[0082] For example, if the filtered target wheel-end torque is detected to fall into a preset zero-crossing torque range, the current target wheel-end torque is no longer directly output. Instead, zero-crossing smoothing logic is activated based on the torque zero-crossing control strategy to determine the compensated target wheel-end torque. The preset compensation torque is then linearly or non-linearly superimposed onto the original target wheel-end torque according to a preset first rate of change slope. This superposition method allows the final output torque command to quickly and smoothly leave the preset zero-crossing torque range and enter a stable drive or regenerative braking range.

[0083] For example, if the preset zero-crossing torque range is [-5Nm, 5Nm], and the current target wheel-end torque is 2Nm, within a preset second time period of 100ms, a preset compensation torque of 60Nm is gradually added at a preset first rate of change not exceeding 100Nm / s. This counteracts the zero-crossing impact caused by motor inertia and transmission backlash, allowing the output torque to quickly increase to over 62Nm, thus completely avoiding the oscillation range. This active compensation mechanism effectively counteracts the negative impacts of motor inertia and transmission backlash, eliminating jitter and lag during the torque zero-crossing phase. Simultaneously, since the compensated target wheel-end torque is the final torque command after zero-crossing smoothing, its value has deviated from the preset zero-crossing torque range, exhibiting higher stability and linearity. Therefore, based on the compensated target wheel-end torque, the vehicle is controlled to switch between human-machine co-driving states, ensuring smooth and continuous output when crossing the preset zero-crossing torque range. For example, the executing entity converts the compensated target wheel-end torque into a current command or duty cycle signal and sends it to the motor controller of the drive motor to control the vehicle's output torque, thereby smoothly completing the switch to human-machine co-driving mode.

[0084] This embodiment determines the user's desired torque by acquiring the accelerator pedal opening. In intelligent driving mode, it determines the target wheel-end torque based on the user's desired torque and the intelligent driving torque. Furthermore, it determines the dynamic target torque difference based on the relationship between this target wheel-end torque and a preset first torque threshold. This replaces the single judgment method in related technologies that relies solely on a fixed opening threshold, thereby reducing frequent and unexpected switching caused by instantaneous torque fluctuations due to accidental pedal touch or road bumps. Simultaneously, based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and the intelligent driving torque and the target torque difference, it determines whether the switching conditions for human-machine co-driving are met, thus distinguishing between the driver's genuine intervention intentions and disturbance signals, effectively filtering out false triggers. If the switching conditions are met, a switching is performed based on a torque control strategy, smoothly adjusting the torque output during the state transition process. This reduces drive torque fluctuations caused by jumps between the intelligent driving torque and the user's desired torque, thereby improving the driving experience and achieving accurate identification and smooth transition of the human-machine co-driving state.

[0085] In another exemplary embodiment, it is illustrated that the vehicle can also perform torque control based on the above-described torque control strategy during mode switching. Please refer to [link to relevant documentation]. Figure 2 , Figure 2 Based on Figure 1 The exemplary embodiment shown illustrates a flowchart of another torque control method for vehicle mode switching. This torque control method, in... Figure 1 Based on S110 to S140 shown, at least S210 to S240 are also included, as detailed below: During the process of switching the vehicle from intelligent driving mode to human driving mode, S210 determines the current filtered output torque based on the torque control strategy.

[0086] Human-driven mode is a driving mode in which the driver has full control over the driving.

[0087] The current filtered output torque is calculated based on the discrete domain filtering formula of the torque filtering control strategy (i.e., torque control strategy). This formula uses the historical filtered output torque of the previous control cycle and the target wheel end torque of the current control cycle for weighted iteration.

[0088] For example, the current filtered output torque is calculated according to the following formula: ;in, This represents the current filtered output torque. This refers to the filtered output torque of the previous control cycle adjacent to the current control cycle, i.e., the historical filtered output torque. These are the filter coefficients; The target wheel-end torque is given. The formula for calculating the filter coefficient is: ;in, The value is the filter coefficient, which usually ranges from 0 to 1. The closer the value is to 1, the weaker the filtering effect and the faster the response. The closer the value is to 0, the stronger the filtering effect and the smoother the torque. This is the filter cutoff frequency; The unit control cycle duration is denoted as e, such as the VDC control cycle duration (10ms); e is a natural constant, with a value of approximately 2.71828. The filter cutoff frequency is determined by real-time acquisition of vehicle speed and comparison with a pre-calibrated preset speed. For example, a mapping relationship between vehicle speed and filter cutoff frequency is pre-stored, and the corresponding cutoff frequency value is automatically matched when the vehicle speed is in different ranges. Thus, the filter coefficient is essentially dynamically calculated based on vehicle speed. Here, the target wheel-end torque is weighted and fused with the historical filtered output torque to calculate the current filtered output torque. Essentially, this transforms the step-changing torque command into a continuously and gradually changing physical quantity. This not only improves the instantaneous torque jump caused by vehicle mode switching but also ensures the continuity of the filter channel throughout the entire mode switching process, reducing secondary shocks caused by parameter mutations or filter interruptions, and achieving smooth and comfortable torque output.

[0089] For example, when the vehicle is traveling at 60 km / h and is in intelligent driving mode, if the driver takes over the vehicle, selects the appropriate filter cutoff frequency for the medium-to-high speed range, calculates the corresponding filter coefficient in combination with the control cycle, and then calculates the filter output torque at the current moment.

[0090] S220 calculates the current torque change rate based on the current filtered output torque and the historical filtered output torque.

[0091] The historical filtered output torque is the filtered output torque of the previous control cycle adjacent to the current control cycle.

[0092] The current torque change rate refers to the magnitude of change in the filtered output torque within a unit control cycle. This rate is obtained by dividing the difference between the current filtered output torque and the historical filtered output torque of the previous control cycle by the control cycle duration. It can be understood as an absolute value, i.e., Current torque change rate = |(Current filtered output torque - Historical filtered output torque) / Unit control cycle duration|. For example, if the current filtered output torque is 200 Nm, the filtered output torque of the previous cycle is 195 Nm, and the unit control cycle is 0.01 s, then the calculated current torque change rate is 500 Nm / s.

[0093] S230 If the current torque change rate is less than or equal to the preset second change rate, then the torque output is based on the current filtered output torque.

[0094] The preset second rate of change is a pre-calibrated torque gradient safety threshold. The setting of this safety threshold takes into account the motor response characteristics, transmission system clearance, and ride comfort requirements. It is usually set to a large value to allow for normal dynamic response, but with a margin to prevent shocks.

[0095] The current torque change rate directly reflects the gradient of the torque command over time and is a key indicator for determining whether an additional compensation mechanism is needed. If the current torque change rate does not exceed the preset second change rate, it indicates that the current filtering process is sufficient to suppress torque fluctuations, and the current filtered output torque is directly sent to the drive motor MCU as the final command.

[0096] S240 If the current torque change rate is greater than the preset second change rate, then the current filtered output torque is compensated, and the torque is output based on the compensated current filtered output torque.

[0097] If the current torque change rate does not exceed the preset second change rate, it indicates that the torque change is relatively drastic, and the current filtered output torque is corrected to forcibly reduce its change gradient.

[0098] For example, if the preset second rate of change is 10000 Nm / s, and the current torque rate of change is 15000 Nm / s, the current torque rate of change is obviously greater than the preset second rate of change. The torque curve will be reconstructed according to the maximum allowable slope of 10000 Nm / s, generating a new, more smoothly changing compensated torque value. This compensation method effectively prevents rapid torque jumps, eliminating the feeling of power interruption or reverse shock caused by the rapid disengagement of intelligent driving torque before the driver's torque has fully developed, ensuring a seamless experience throughout the mode switching process.

[0099] In some implementations, torque control configuration parameters are introduced before determining the current filtered output torque based on the torque control strategy, to achieve dynamic selectivity of the torque control strategy. This is described below: The process involves acquiring torque control configuration parameters. If the torque control configuration parameters are in a first state, the step of determining the current filtered output torque based on the torque control strategy is executed. If the torque control configuration parameters are in a second state, the vehicle is controlled to output torque based on a preset second rate of change. The torque control configuration parameters are flags indicating the current operating mode of the vehicle's torque control strategy. Their function is to enable or disable torque smoothing logic to adapt to the torque control requirements of different vehicle configurations and driving scenarios. The first state indicates that the torque filtering control strategy (i.e., the torque control strategy) is enabled. The second state indicates that the torque filtering control strategy is disabled, and only the torque gradient change limiting strategy is enabled.

[0100] For example, obtain ADS_RapidRespEna (ADS fast response torque activation flag, i.e., torque control configuration parameter); if ADS_RapidRespEna=Disable (disabled state, i.e., first state), then the torque filtering control strategy and torque gradient change limiting strategy are enabled throughout the entire process to ensure a smooth ride. If ADS_RapidRespEna=Enable (enabled state, i.e., second state), then the conventional first-order inertial filtering is disabled (i.e., the torque filtering control strategy is disabled), and only the torque gradient change limiting strategy is enabled. Here, it works in deep coordination with the ADS signal to prioritize safety and response requirements in emergency situations.

[0101] By introducing torque control configuration parameters, dynamic selectivity of the torque control strategy is achieved. By comparing these parameters with preset states, in the first state, the current filtered output torque can be determined based on the torque control strategy, and a torque gradient change limiting strategy can be implemented to reduce the probability of torque jumps. In the second state, the torque output is constrained by a fixed preset rate of change, ensuring that the vehicle can maintain basic torque output stability and safety under various extreme or abnormal operating conditions.

[0102] This embodiment introduces a secondary verification and compensation mechanism based on a preset second rate of change during the vehicle's transition from intelligent driving mode to human driving mode. The current torque change rate is calculated based on the difference between the current filtered output torque and the historical filtered output torque, and then compared with the preset second rate of change, achieving refined control of the torque gradient. When the current torque change rate is within a safe range, it is output to ensure response speed. If the current torque change rate is too large, compensation logic is triggered to forcibly smooth the torque curve.

[0103] In another exemplary embodiment of this application, the application scenarios of the above-mentioned torque control methods are illustrated by way of example. Please refer to the following for details. Figure 3 , Figure 3 This is a schematic diagram illustrating an application scenario of the torque control method for vehicle mode switching according to this application. It includes a vehicle 100 and a server 200, which can be connected wirelessly or via wired communication; this application does not limit the connection method between them.

[0104] Server 200 can act as the execution subject of any of the above torque control methods to execute any of the above torque control methods, as illustrated below: Server 200 obtains the accelerator pedal opening of vehicle 100 and determines the user's desired torque based on the accelerator pedal opening. When vehicle 100 is in intelligent driving mode, server 200 determines the target wheel-end torque of vehicle 100 based on the user's desired torque and intelligent driving torque, and determines the target torque difference based on the relationship between the target wheel-end torque and a preset first torque threshold. Server 200 determines whether vehicle 100 meets the switching conditions for human-machine co-driving state based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and intelligent driving torque and the target torque difference. If it meets the conditions, server 200 controls vehicle 100 to switch to human-machine co-driving state based on torque control strategy.

[0105] Server 200 can be a server that includes an intelligent driving system, such as... Figure 3 The server 200, as shown, can be a standalone physical server, a server cluster or a distributed system composed of multiple physical servers, and multiple servers can form a blockchain, with the server being a node on the blockchain. The server 200 can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. This application does not limit the location, structure, type, etc. of the server 200.

[0106] Another aspect of this application provides a torque control device for vehicle mode switching, such as... Figure 4 As shown, Figure 4 This is a schematic diagram illustrating the structure of a torque control device for vehicle mode switching, as shown in an exemplary embodiment of this application. The torque control device 400 includes: The acquisition module 410 is used to acquire the accelerator pedal opening of the vehicle and determine the user's desired torque based on the accelerator pedal opening.

[0107] The first determining module 430 is used to determine the target wheel-end torque of the vehicle based on the user's expected torque and the intelligent driving torque when the vehicle is in intelligent driving mode, and to determine the target torque difference based on the relationship between the target wheel-end torque and the preset first torque threshold.

[0108] The second determining module 450 is used to determine whether the vehicle meets the switching conditions for human-machine co-driving state based on the accelerator pedal opening and the relationship between the torque difference between the user's expected torque and the intelligent driving torque and the target torque difference.

[0109] The control module 470 is used to control the vehicle to switch to human-machine co-driving mode based on the torque control strategy if the conditions are met.

[0110] In one possible implementation, the first determining module 430 includes: The first target wheel-end torque determination unit is used to determine the user-expected torque as the target wheel-end torque of the vehicle if the vehicle's driving state is a human-machine co-driving state.

[0111] The second target wheel-end torque determination unit is used to determine the intelligent driving torque as the target wheel-end torque if the vehicle's driving state is not a human-machine co-driving state.

[0112] The first target torque difference determination unit is used to determine the target torque difference if the target wheel end torque is less than or equal to a preset first torque threshold.

[0113] The second target torque difference determination unit is used to determine the target torque difference by multiplying the target wheel end torque by a preset coefficient if the target wheel end torque is greater than the preset first torque threshold.

[0114] In one possible implementation, the second determining module 450 includes: The recording unit is used to determine that the vehicle meets the initial switching conditions for entering the human-machine co-driving state if the accelerator pedal opening is greater than or equal to a preset first opening and the torque difference between the user's expected torque and the intelligent driving torque is greater than or equal to the target torque difference, and to record the duration of meeting the initial switching conditions.

[0115] The entry condition unit is used to determine that the vehicle meets the switching conditions for entering the human-machine co-driving state if the duration is greater than or equal to a preset first duration.

[0116] In one possible implementation, the second determining module 450 includes: The exit condition unit is used to determine that the vehicle meets the switching conditions for exiting the human-machine co-driving state when the vehicle's driving state is human-machine co-driving state, if the accelerator pedal opening is less than or equal to a preset second opening, and the torque difference between the user's expected torque and the intelligent driving torque is less than or equal to the target torque difference.

[0117] In one possible implementation, the control module 470 includes: The filter cutoff frequency determination unit is used to determine the filter cutoff frequency based on the relationship between the vehicle speed and the preset vehicle speed.

[0118] The filter coefficient determination unit is used to determine the filter coefficients based on the filter cutoff frequency and the unit control cycle duration.

[0119] The control unit is used to calculate the current filtered output torque based on the filtering coefficient, the target wheel-end torque, and the historical filtered output torque, and to control the vehicle to switch to human-machine co-driving mode based on the current filtered output torque.

[0120] In one possible implementation, the control unit includes: The calculation module is used to divide the difference between the current filtered output torque and the target wheel-end torque by the target wheel-end torque to obtain the quotient.

[0121] The control module is used to compensate the current filtered output torque if the absolute value of the quotient is greater than the constraint parameter, and to control the vehicle to switch to human-machine co-driving mode based on the compensated current filtered output torque; wherein, the constraint parameter is a parameter determined according to the relationship between the target wheel end torque and the preset second torque threshold.

[0122] In one possible implementation, the torque control device 400 further includes: The mode switching module is used to determine the current filtered output torque based on the torque control strategy during the process of switching the vehicle from intelligent driving mode to human driving mode.

[0123] The current torque change rate calculation module is used to calculate the current torque change rate based on the current filtered output torque and the historical filtered output torque.

[0124] The first torque output module is used to output torque based on the current filtered output torque if the current torque change rate is less than or equal to the preset second change rate.

[0125] The second torque output module is used to compensate the current filtered output torque if the current torque change rate is greater than the preset second change rate, and to output torque based on the compensated current filtered output torque.

[0126] In one possible implementation, the torque control device 400 further includes: The parameter acquisition module is used to acquire torque control configuration parameters.

[0127] The first execution module is used to execute the step of determining the current filtered output torque based on the torque control strategy if the torque control configuration parameters are in the first state.

[0128] The second execution module is used to control the vehicle to output torque based on a preset second rate of change if the torque control configuration parameter is in the second state.

[0129] In one possible implementation, the control module 470 includes: The compensation control unit is used to, if the target wheel-end torque is in a preset zero-crossing torque range, within a preset second time period, superimpose the preset compensation torque and the target wheel-end torque based on a preset first rate of change to obtain the compensated target wheel-end torque, and control the vehicle to switch to human-machine co-driving mode based on the compensated target wheel-end torque.

[0130] This application's torque control device determines the user's desired torque by acquiring the accelerator pedal opening. In intelligent driving mode, it determines the target wheel-end torque based on the user's desired torque and the intelligent driving torque, and determines the dynamic target torque difference based on the relationship between the target wheel-end torque and a preset first torque threshold. This replaces the single judgment method in related technologies that relies solely on a fixed opening threshold, thereby reducing frequent and unexpected switching caused by instantaneous torque fluctuations due to accidental pedal touch or road bumps. Simultaneously, based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and the intelligent driving torque and the target torque difference, it determines whether the switching conditions for human-machine co-driving are met, thus distinguishing between the driver's genuine intervention intention and disturbance signals, effectively filtering out false triggers. If the switching conditions are met, the switching is performed based on the torque control strategy, smoothly adjusting the torque output during the state transition process, reducing drive torque fluctuations caused by jumps between the intelligent driving torque and the user's desired torque, thereby improving the driving experience and achieving accurate identification and smooth transition of the human-machine co-driving state.

[0131] It should be noted that the above embodiments of the device are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The torque control device and implementation process provided in the above embodiments have been described in detail in the method embodiments, and will not be repeated here.

[0132] Another aspect of this application provides an electronic device, including: a processor; a memory and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement any of the torque control methods described above.

[0133] Please see Figure 5 , Figure 5This is a schematic diagram of the structure of a computer system for an electronic device according to an exemplary embodiment of this application, illustrating a schematic diagram of the structure of a computer system suitable for implementing the embodiments of this application.

[0134] It should be noted that, Figure 5 The computer system 500 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0135] like Figure 5 As shown, the computer system 500 includes a Central Processing Unit (CPU) 501, which can perform various appropriate actions and processes, such as executing the methods described in the above embodiments, based on programs stored in Read-Only Memory (ROM) 502 or programs loaded from storage portion 508 into Random Access Memory (RAM) 503. The RAM 503 also stores various programs and data required for system operation. The CPU 501, ROM 502, and RAM 503 are interconnected via a bus 504. An Input / Output (I / O) interface 505 is also connected to the bus 504.

[0136] The following components are connected to I / O interface 505: an input section 506 including a keyboard, mouse, etc.; an output section 507 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to I / O interface 505 as needed. Removable media 511, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 510 as needed so that computer programs read from them can be installed into storage section 508 as needed.

[0137] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 509, and / or installed from removable medium 511. When the computer program is executed by central processing unit (CPU) 501, it performs various functions defined in the system of this application.

[0138] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0139] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation that may be implemented in systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0140] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0141] Another aspect of this application provides a storage medium storing a program or instructions that, when executed by a processor, implement any of the torque control methods described above. This storage medium may be included in the electronic device described in the above embodiments, or it may exist independently and not incorporated into the electronic device.

[0142] Another aspect of this application provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the torque control method provided in the various embodiments described above.

[0143] According to one aspect of the embodiments of this application, a computer system is also provided, including a central processing unit (CPU), which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) or a program loaded from storage into random access memory (RAM), such as executing the torque control method in the above embodiments. Various programs and data required for system operation are also stored in the RAM. The CPU, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0144] The following components are connected to the I / O interface: input sections including keyboards, mice, etc.; output sections including cathode ray tubes (CRTs), liquid crystal displays (LCDs), and speakers; storage sections including hard drives; and communication sections including network interface cards such as LAN (Local Area Network) cards and modems. The communication sections perform communication processing via networks such as the Internet. Drives are also connected to the I / O interface as needed. Removable media, such as disks, optical discs, magneto-optical discs, semiconductor memories, etc., are installed on the drive as needed so that computer programs read from them can be installed into the storage section as required.

[0145] The above description is merely a preferred exemplary embodiment of this application and is not intended to limit the implementation of this application. Those skilled in the art can easily make corresponding modifications or alterations based on the main concept and spirit of this application. Therefore, the scope of protection of this application should be determined by the scope of protection claimed in the claims.

Claims

1. A torque control method for vehicle mode switching, characterized in that, include: The accelerator pedal opening of the vehicle is obtained, and the user's desired torque is determined based on the accelerator pedal opening. When the vehicle is in intelligent driving mode, if the vehicle is in human-machine co-driving mode, the user-expected torque is determined as the target wheel-end torque of the vehicle; if the vehicle is not in human-machine co-driving mode, the intelligent driving torque is determined as the target wheel-end torque. If the target wheel end torque is less than or equal to a preset first torque threshold, then the preset torque difference is used as the target torque difference. If the target wheel end torque is greater than the preset first torque threshold, then the product of the target wheel end torque and the preset coefficient is taken as the target torque difference. Based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and the intelligent driving torque and the target torque difference, determine whether the vehicle meets the switching conditions for the human-machine co-driving state; If the conditions are met, the vehicle is controlled to switch to the human-machine co-driving state based on the torque control strategy.

2. The torque control method according to claim 1, characterized in that, Based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and the intelligent driving torque and the target torque difference, determine whether the vehicle meets the switching conditions for the human-machine co-driving state, including: If the accelerator pedal opening is greater than or equal to a preset first opening, and the torque difference between the user's desired torque and the intelligent driving torque is greater than or equal to the target torque difference, then the vehicle is determined to meet the initial switching conditions for entering the human-machine co-driving state, and the duration of meeting the initial switching conditions is recorded. If the duration is greater than or equal to a preset first duration, then the vehicle is determined to meet the switching conditions for entering the human-machine co-driving state.

3. The torque control method according to claim 1, characterized in that, Based on the accelerator pedal opening and the relationship between the torque difference between the user's desired torque and the intelligent driving torque and the target torque difference, determine whether the vehicle meets the switching conditions for the human-machine co-driving state, including: When the vehicle is in the human-machine co-driving state, if the accelerator pedal opening is less than or equal to a preset second opening, and the torque difference between the user's desired torque and the intelligent driving torque is less than or equal to the target torque difference, then the vehicle is determined to meet the switching conditions for exiting the human-machine co-driving state.

4. The torque control method according to claim 1, characterized in that, Based on a torque control strategy, the vehicle is controlled to switch between human-machine co-driving states, including: The filter cutoff frequency is determined based on the relationship between the vehicle speed and the preset vehicle speed. The filter coefficients are determined based on the filter cutoff frequency and the unit control cycle duration. Based on the filtering coefficient, the target wheel-end torque, and the historical filtered output torque, the current filtered output torque is calculated, and based on the current filtered output torque, the vehicle is controlled to switch to the human-machine co-driving state.

5. The torque control method according to claim 4, characterized in that, Based on the current filtered output torque, control the vehicle to switch to the human-machine co-driving state, including: Divide the difference between the current filtered output torque and the target wheel end torque by the target wheel end torque to obtain the quotient. If the absolute value of the quotient is greater than the constraint parameter, the current filtered output torque is compensated, and based on the compensated current filtered output torque, the vehicle is controlled to switch to the human-machine co-driving state; wherein, the constraint parameter is a parameter determined according to the relationship between the target wheel end torque and the preset second torque threshold.

6. The torque control method according to any one of claims 1 to 5, characterized in that, Based on a torque control strategy, the vehicle is controlled to switch between human-machine co-driving states, including: If the target wheel-end torque is within a preset zero-crossing torque range, then within a preset second time period, the preset compensation torque is superimposed on the target wheel-end torque based on a preset first rate of change to obtain the compensated target wheel-end torque, and based on the compensated target wheel-end torque, the vehicle is controlled to switch to the human-machine co-driving state.

7. A torque control device for vehicle mode switching, characterized in that, include: The acquisition module is used to acquire the accelerator pedal opening of the vehicle and determine the user's desired torque based on the accelerator pedal opening. The first determining module is used to determine the user-expected torque as the target wheel-end torque of the vehicle if the vehicle's driving state is a human-machine co-driving state when the vehicle is in intelligent driving mode; and to determine the intelligent driving torque as the target wheel-end torque if the vehicle's driving state is not the human-machine co-driving state. If the target wheel end torque is less than or equal to a preset first torque threshold, then the preset torque difference is used as the target torque difference. If the target wheel end torque is greater than the preset first torque threshold, then the product of the target wheel end torque and the preset coefficient is taken as the target torque difference. The second determining module is used to determine whether the vehicle meets the switching conditions of the human-machine co-driving state based on the accelerator pedal opening and the relationship between the torque difference between the user's expected torque and the intelligent driving torque and the target torque difference. The control module is used to control the vehicle to switch to the human-machine co-driving state based on the torque control strategy if the conditions are met.

8. An electronic device, characterized in that, include: processor; A memory and a program or instructions stored in the memory and executable on the processor, wherein the program or instructions, when executed by the processor, implement the torque control method as described in any one of claims 1 to 6.

9. A storage medium, characterized in that, The storage medium stores a program or instructions that, when executed by a processor, implement the torque control method as described in any one of claims 1 to 6.

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