Vehicle torque determination method, vehicle, storage medium and program product

Abstract

One or more embodiments of the present specification provide a vehicle torque determination method, a vehicle, a storage medium and a program product, the method comprising: acquiring current vehicle driving information and load information of the vehicle, the vehicle driving information comprising a pedal opening and a vehicle speed; a basic torque corresponding to the vehicle driving information is determined according to a torque mapping table, a corresponding load correction factor is determined according to the load information, and the torque mapping table is used for representing the corresponding relation between different vehicle driving information and torques; and the product of the basic torque and the load correction factor serves as target torque to be used for controlling vehicle running.

Description

Technical Field

[0001] This specification relates to the field of image processing technology, and more particularly to a method for determining vehicle torque, a vehicle, a storage medium, and a program product. Background Technology

[0002] With the rapid popularization of electric vehicles, the characteristics of their drive motors—fast instantaneous response and high torque output—are widely recognized. While this characteristic brings strong power, it also makes vehicles more prone to significant longitudinal acceleration changes, or jerk, during common operating conditions such as starting, following other vehicles, and switching energy recovery modes. Current research and engineering practice further demonstrate that the human body is particularly sensitive to longitudinal vibrations in the frequency range of 0.1 to 0.5 Hz, and high jerk in this frequency band is the main physical cause of motion sickness. Therefore, how to effectively suppress jerk in specific frequency bands through precise torque control strategies while maintaining the power response advantages of electric vehicles has become a key technological challenge for the industry to improve driving quality and meet consumer comfort needs.

[0003] In related technologies, multiple preset driving modes (such as ECO, Normal, Sport, etc.) are typically provided to address the above issues, with each mode corresponding to a pedal mapping with a different torque response slope. However, such solutions are essentially based on statically calibrated fixed mapping relationships, and their design intention is primarily to cater to different driver style preferences rather than specifically optimizing for motion sickness suppression. In fact, because the mapping curve remains unchanged, it cannot adaptively adjust according to real-time vehicle operating conditions and dynamic loads. Therefore, when facing complex and ever-changing real-world driving scenarios, its effect on suppressing vibrations in key frequency bands that cause motion sickness is limited, and its overall ride comfort optimization capability is insufficient. Summary of the Invention

[0004] In view of the above, one or more embodiments of this specification provide the following technical solutions: According to a first aspect of one or more embodiments of this specification, a method for determining vehicle torque is provided, the method comprising: Obtain the vehicle's current driving information and load information, including pedal opening and vehicle speed; The torque mapping table is used to determine the base torque corresponding to the vehicle driving information, and the load correction factor is determined according to the load information. The torque mapping table is used to characterize the correspondence between different vehicle driving information and torque. The product of the base torque and the load correction factor is used as the target torque for controlling vehicle movement.

[0005] According to a second aspect of one or more embodiments of this specification, a vehicle is provided, comprising: a processor and a memory for storing processor-executable instructions; wherein the processor implements the steps of the method described in the first aspect by executing the executable instructions.

[0006] According to a third aspect of this specification, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0007] According to a fourth aspect of this specification, a computer program product includes a computer program / instructions that, when executed by a processor, implement the steps of the method described in the first aspect.

[0008] As can be seen from the above embodiments, the solution in this specification acquires vehicle load information in real time and dynamically determines a matching load correction factor accordingly. It then adaptively corrects the base torque obtained from the torque mapping table based on pedal opening and vehicle speed, thereby generating the final target torque. This allows the vehicle torque output to be precisely and dynamically adjusted according to the actual load conditions. In summary, the above solution, through adaptive control of the torque source, fundamentally suppresses the longitudinal jerkiness exacerbated by load changes within a specific sensitive frequency band, thus significantly improving the vehicle's ride smoothness under different load conditions and effectively alleviating motion sickness in passengers. Attached Figure Description

[0009] Figure 1 This is a schematic diagram of the architecture of a vehicle torque determination system shown in the embodiments disclosed in this specification; Figure 2 This is a flowchart illustrating a method for determining vehicle torque according to the embodiments disclosed in this specification; Figure 3 This is an auxiliary schematic diagram illustrating an embodiment of determining vehicle torque as disclosed in this specification; Figure 4 This is a schematic diagram of the transfer function of a band-stop filter shown in the embodiments disclosed in this specification; Figure 5 This is a flowchart illustrating another method for determining vehicle torque as shown in the embodiments disclosed in this specification; Figure 6 This is a schematic structural diagram of an electronic device shown in the embodiments of this specification; Figure 7 This is a block diagram illustrating a vehicle torque determination device according to an embodiment of this specification. Detailed Implementation

[0010] 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 denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this specification. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this specification.

[0011] It should be noted that in other embodiments, the steps of the corresponding methods are not necessarily performed in the order shown and described in this specification. In some other embodiments, the methods may include more or fewer steps than those described in this specification. Furthermore, a single step described in this specification may be broken down into multiple steps in other embodiments; and multiple steps described in this specification may be combined into a single step in other embodiments. It should be understood that although the terms first, second, third, etc., may be used in this specification to describe various information, this information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this specification, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0012] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this manual are all information and data authorized by the user or fully authorized by all parties. The collection, use and processing of related data shall comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals shall be provided for users to choose to authorize or refuse.

[0013] Figure 1 This is a schematic diagram of the architecture of a vehicle torque determination system provided in an exemplary embodiment. Figure 1 As shown, the system may include an information acquisition module 12 and a torque calculation module 14 in the vehicle 10.

[0014] The information acquisition module 12 is specifically responsible for acquiring the dynamic parameters of the vehicle 10 in real time during operation, including vehicle driving information provided by the pedal opening sensor and vehicle speed sensor, and load information provided by the load estimation system or related sensors to characterize the current load state of the vehicle. This module ensures the synchronization and real-time nature of the above driving information and load information, providing an accurate and consistent input data foundation for subsequent torque adaptive calculation.

[0015] The torque calculation module 14 receives vehicle driving information and load information from the information acquisition module 12. This module has a pre-stored reference torque mapping table and first queries this table based on the received pedal opening and vehicle speed to determine the corresponding base torque. Simultaneously, based on the received load information, the torque calculation module 14 dynamically determines a matching load correction factor using a built-in algorithm or mapping relationship. Finally, the torque calculation module 14 performs a multiplication operation between the base torque and the load correction factor, and the product is output as the target torque for directly driving the vehicle, thereby achieving precise and adaptive control of the vehicle's driving force.

[0016] The embodiments of the method for determining vehicle torque in this specification will be described in detail below with reference to the accompanying drawings.

[0017] Figure 2 This is a schematic flowchart illustrating an exemplary embodiment of a method for determining vehicle torque. Figure 2 As shown, the method may include the following steps: Step S202: Obtain the vehicle's current driving information and load information, wherein the driving information includes pedal opening and vehicle speed.

[0018] Before determining the vehicle torque, the solution described in this manual first acquires the vehicle's current driving and load information in real time via an information acquisition module. The driving information includes at least the pedal opening reflecting the driver's intention and the vehicle speed characterizing the vehicle's motion, while the load information indicates the vehicle's real-time load status. This step provides the necessary and comprehensive input parameters for subsequent accurate torque calculation.

[0019] In one embodiment, the accurate acquisition of the aforementioned load information is first achieved. Specifically, the load information may include two key parameters: the vehicle's curb weight and current gross weight. The curb weight, as an inherent parameter of the vehicle, can be pre-calibrated and stored in the vehicle's storage unit, such as the non-volatile memory of the Electronic Control Unit (ECU), and can be obtained by directly reading this storage unit. The dynamically changing current gross weight, however, needs to be estimated in real time using the vehicle's sensor system.

[0020] For example, the system can acquire the sensing signal from the vehicle's tire pressure sensor. Since tire pressure is directly related to the vehicle's total mass, the system can use this signal, combined with the corresponding vehicle model, to calculate or obtain the vehicle's current total mass in real time by querying and comparing relevant data. By acquiring the static curb weight and the dynamic current total mass in the above ways, they together constitute complete and accurate load information for subsequent calculations of load correction factors.

[0021] For example, for vehicles equipped with air suspension or ride height adjustment systems, signals from their suspension height sensors or suspension pressure sensors can be acquired. An increase in vehicle load directly leads to suspension compression or increased system pressure. By establishing a load-height or load-pressure calibration model, the vehicle's current total mass can also be calculated in real time.

[0022] In summary, in addition to the methods described above for determining the current total mass, other sensor systems or combinations thereof known in the art can also be used, and this specification does not limit this.

[0023] Step S204: Determine the base torque corresponding to the vehicle driving information according to the torque mapping table, and determine the corresponding load correction factor according to the load information. The torque mapping table is used to characterize the correspondence between different vehicle driving information and torque.

[0024] After obtaining the above information, on the one hand, the torque calculation module can query a pre-stored torque mapping table based on the obtained pedal opening and vehicle speed to determine a corresponding base torque. This torque mapping table defines the calibration values ​​of the base torque under different driving conditions. On the other hand, a corresponding load correction factor can be determined in parallel based on the obtained load information through specific rules or mapping relationships.

[0025] Specifically, the so-called torque mapping table, also known as the base pedal map, essentially uses pedal opening (θ) and vehicle speed (v) as inputs, and a base torque (θ) as the input. Let be the output two-dimensional function, that is, satisfying: = (Formula 1) This mapping table is used to represent the correspondence between driving information and torque for different vehicles. It can also be viewed as a carefully calibrated database that strikes a balance between power and ride comfort. Figure 3 As shown, it can reflect the slope of a three-dimensional surface composed of multiple basic torques output by different pedal openings and vehicle speeds.

[0026] In one embodiment, the calibration of the torque mapping table can follow the following partitioning strategy: 1. In the low-speed start-up zone, such as when the vehicle speed is below 10 km / h, the map uses a smaller torque output slope to provide a smooth pedal response, avoid excessive torque at the moment of start-up, and ensure a smooth start; Second, in the medium-speed common area, such as the vehicle speed between 10 and 80 km / h, the mapping table is calibrated with a medium slope to take into account both the smoothness when following other vehicles and the power response required when overtaking. Third, in high-speed areas, such as when the vehicle speed is above 80 km / h, the output slope of the mapping table can be gradually reduced, so that small pedal movements at high speeds will not cause excessive longitudinal acceleration changes, thereby ensuring vehicle stability and passenger comfort.

[0027] In this way, the torque mapping table provides a basic torque request that balances power and comfort for the vehicle under various operating conditions, laying a reliable foundation for subsequent load adaptive correction.

[0028] Furthermore, when determining the corresponding load correction factor based on the aforementioned load information, it can be calculated according to the relative relationship between the vehicle's curb weight and its current gross weight. Specifically, the value of the aforementioned load correction factor is positively correlated with the current gross weight; that is, the greater the vehicle load, the greater the value of the correction factor.

[0029] In one embodiment, this can be achieved by using the current total mass Compared with curb weight The calculated preset load threshold is compared to determine the value of the correction factor α in segments: When the vehicle is lightly loaded, such as when the current total mass is... Less than the curb weight 105% of At this time, the load correction factor α can be set to a value less than 1, such as 0.8. This is intended to appropriately reduce the output slope of the reference torque map, thereby reducing abrupt changes during start-up and acceleration, and improving ride smoothness under light load conditions.

[0030] When the vehicle is in a medium-load state, such as the current total mass Given the curb weight Between 105% and 110%, that is At this time, the load correction factor α can be set to 1. In this case, the original output characteristics of the reference torque mapping will be maintained, keeping the original balance between smoothness and power.

[0031] When the vehicle is under heavy load, such as its current total mass Greater than the curb weight 110% of When this is the case, the load correction factor α can be set to a value greater than 1, such as 1.2. This is equivalent to increasing the slope of the reference torque mapping, which can actively output greater torque to effectively compensate for the power lag caused by the increased load and ensure power response performance under heavy load.

[0032] Through the above segmented mapping strategy, this manual can adaptively adjust the torque output characteristics according to the actual load conditions of the vehicle, achieving an optimal balance between smoothness and power under different load conditions.

[0033] Step S206: The product of the above-mentioned basic torque and the above-mentioned load correction factor is used as the target torque for controlling vehicle movement.

[0034] The determined base torque is multiplied by the load correction factor, and the product is used as the target torque for driving the vehicle. Through this multiplication, the target torque can simultaneously respond to the driver's immediate operating intentions and the actual load state of the vehicle. Thus, the vehicle can generate corresponding torque control commands (hereinafter referred to as torque commands) based on the target torque to achieve precise and adaptive control of the vehicle's driving force.

[0035] Specifically, based on the implementation of the above steps, this specification describes the reference pedal mapping function. Output (i.e., base torque) ) and load correction factor Multiplying these together yields the final target torque used for vehicle propulsion. This process can be fully represented by the following relation: (Formula 2) This formula, based on the traditional torque mapping method using pedal opening and vehicle speed, introduces a factor related to real-time mass estimation. Related adaptive correction factor The final target torque It is not a static result of a single mapping, but rather a product of the dynamic coupling between the driver's intention and the vehicle's actual load state. Through this mechanism, this manual successfully integrates load perception and torque control, enabling the vehicle's power output to intelligently adapt to various complex operating conditions from no-load to heavy-load, thereby systematically improving the vehicle's driving smoothness and power response adaptability across the entire operating range.

[0036] After obtaining the target torque Subsequently, dynamic limiting processing based on the rate of change can be applied to further optimize smoothness, especially in scenarios where the corresponding torque command generated based on the target torque changes rapidly with the change of the target torque.

[0037] In one embodiment, the vehicle can adaptively constrain the rate of change of torque command based on the vehicle's actual load. Specifically, based on the aforementioned current total mass... Determine a maximum rate of change threshold for the target torque. And impose constraints on the rate of change of torque command (i.e., the amount of torque change per unit time |dT / dt|) to ensure that it satisfies: (Formula 3) Among them, the above-mentioned maximum rate of change threshold With the above current total mass They are positively correlated. This ensures that the vehicle accelerates responsively under light load conditions, as an excessively large torque change rate can easily lead to high jerkiness, so a smaller limit value is needed to suppress the impact; while under heavy load conditions, the vehicle has greater inertia and a relatively slower acceleration response, allowing for a larger torque change rate threshold, thus ensuring both smoothness and power responsiveness.

[0038] By introducing this load-adaptive torque change rate limiter, this manual enables dynamic and precise constraints on jerkiness, ensuring that the vehicle maintains a consistent level of ride comfort under different load conditions.

[0039] After obtaining the target torque, the torque command can be filtered to further optimize ride comfort from a frequency domain perspective and specifically attenuate vibrations in specific frequency bands that the human body is sensitive to.

[0040] In one embodiment, the vehicle can filter the target torque using a band-stop filter to attenuate fluctuations within a preset low-frequency band. Given that research and engineering practice indicate that occupants are most sensitive to longitudinal acceleration in the 0.1 Hz to 0.5 Hz frequency band, and fluctuations in this band are a major cause of motion sickness, the band-stop filter can be specifically configured to significantly suppress / attenuate signals in this preset frequency band.

[0041] The above filtering process can be described in the complex frequency domain using a transfer function. Specifically, it can be seen that... Represented as such Figure 4 The transfer function of the band-stop filter shown is... Given the aforementioned target torque in complex frequency domain form, the torque control command corresponding to the filtered target torque is... It can be expressed by the following formula: (Formula 4) This filtering operation can effectively remove fluctuations in the target torque command located in the sensitive frequency band, suppressing specific frequency vibrations that may cause discomfort to passengers from the source, thereby achieving a higher level of ride comfort.

[0042] After frequency domain filtering, the torque command can be smoothed by zero crossing, thereby solving the problem of the torque command crossing zero in the time domain, such as the instantaneous step and impact that may occur when switching between power drive and energy recovery.

[0043] In one embodiment, the vehicle can adjust the target torque based on a nonlinear smoothing coefficient to ensure a smooth transition when the target torque switches between positive and negative values, avoiding significant abrupt changes in torque sign that could induce abrupt acceleration. Specifically, a hyperbolic tangent function can be used to achieve this smooth transition. Let... This represents the target torque to be processed. As a parameter controlling the smoothness, the corrected final torque command It can be calculated using the following formula: (Formula 5) Among them, when hour, Output torque Approximately equal to input The impact on torque in the normal driving range is negligible; while when When approaching zero, , making This nonlinear relationship forces the torque to smoothly approach zero near the zero point, thus completely eliminating the hard step of torque command.

[0044] In summary, by introducing this zero-crossing smoothing process, this manual can effectively address the smoothness challenges in scenarios such as traction and braking switching, ensuring that the torque command remains smooth and consistent throughout the entire process, further improving the driving experience.

[0045] It should be noted that in the technical solution of this specification, "target torque" and "torque command" are essentially consistent in meaning. Both represent the core torque control quantity used to drive the vehicle after being calculated and processed by corresponding methods. The only difference lies in the emphasis of their descriptions: "target torque" usually emphasizes that it is the torque setpoint expected to be achieved through adaptive calculation based on driver input and load status; while "torque command" focuses more on describing the form in which this setpoint is issued as the final control signal to the actuators such as motor controllers. Therefore, the above-mentioned expressions "filtering / correcting the target torque" and "filtering / correcting the torque command" are technically equivalent. That is, in this specification, the latter can be interpreted as a specific implementation of the former, and both refer to applying subsequent processing steps aimed at improving smoothness to the same torque control quantity. This series of processing steps, from generation, to limiting, filtering, and then to zero-crossing smoothing, together constitute a complete, progressive torque optimization chain, ensuring that the final driving command applied to the vehicle has both load adaptability and high-order smoothness.

[0046] The above-mentioned solution mainly optimizes torque based on the vehicle's physical state. This invention can further introduce a feedback mechanism based on the real-time physiological state of the occupants to achieve higher-level intelligent and humanized control, ultimately forming a closed-loop anti-motion sickness system.

[0047] In one embodiment, the vehicle can acquire the physiological signals of at least one occupant through an onboard occupant monitoring system. These physiological signals may include, but are not limited to, respiratory rate, heart rate, or blood pressure. Subsequently, the processed physiological signal features are input into a preset physiological signal model, which calculates and outputs a motion sickness probability value that characterizes the occupant's current level of motion sickness.

[0048] To ensure the stability of obstacle control strategy switching and avoid frequent control mode jumps caused by instantaneous fluctuations in physiological signals, the corresponding vehicle system can be set with anti-motion sickness activation conditions that include duration determination. The activation conditions are defined as follows: the motion sickness probability value continuously exceeds a preset maximum motion sickness threshold, and the duration of this state exceeds a preset minimum activation time.

[0049] When the system determines that the above-mentioned anti-motion sickness driving activation conditions are met, it can automatically execute a series of anti-motion sickness driving operations.

[0050] Similarly, to ensure that the system can promptly exit and resume normal driving mode after the occupants' comfort improves, avoiding unnecessary power sacrifice, anti-motion sickness driving exit conditions can also be set accordingly. These exit conditions are defined as follows: the aforementioned motion sickness probability value remains below a preset minimum motion sickness threshold, and the duration of this state exceeds a preset minimum exit time.

[0051] When the system determines that the above-mentioned anti-motion sickness driving exit conditions are met, it will gradually or all at once remove the special control strategy adopted for anti-motion sickness, that is, the above-mentioned anti-motion sickness driving operation, so that the vehicle can return to the standard driving mode that balances power and smoothness.

[0052] By setting start and stop conditions with hysteresis and hold time characteristics, this invention achieves smooth and reliable switching between anti-motion sickness control modes, effectively preventing frequent oscillations between the two modes due to short-term fluctuations in physiological signals. This makes the closed-loop control logic based on the occupant's physiological state more robust and practical, ultimately making the vehicle an intelligent system capable of proactively sensing and intelligently responding to changes in occupant comfort. It provides personalized anti-motion sickness protection for susceptible occupants from the root, greatly enhancing the vehicle's driving and riding inclusiveness and comfort ceiling.

[0053] The core of the aforementioned anti-motion sickness driving operation lies in dynamically adjusting the stringency of the torque control strategy based on the real-time motion sickness probability value. Specifically, the system first adjusts the torque control strategy based on the aforementioned motion sickness probability value. Determine a corresponding anti-sickness strength coefficient. The coefficient is limited to a continuous range, for example, [0, 1], where This indicates that there is no anti-motion sickness control, and This represents the maximum level of motion sickness control. The value of . varies It continuously changes within a preset upper and lower threshold range, thereby achieving smooth, stepless adjustment and avoiding abrupt changes in the control strategy.

[0054] Determine the anti-sickness strength coefficient Then, the system can perform at least one of the following operations based on this coefficient: 1. Enhanced torque change rate limitation: Based on the above anti-sickness strength coefficient Reduce the maximum allowable rate of change threshold for the aforementioned target torque. Specifically, the effective torque change rate limit. It can be done through the formula: (Formula 6) The calculation yielded, where It is an adjustment coefficient, for example, with a value between 0.2 and 0.5. When When it increases, A reduction in torque means stricter constraints on instantaneous changes in torque, thus more effectively suppressing jerks.

[0055] 2. Softened torque output response: Based on the above anti-sickness strength coefficient Reduce the overall gain of the aforementioned target torque. Specifically, this can be achieved by adjusting the target torque after load adaptive correction. A further global scaling is applied to form the final torque command: (Formula 7) in It is an adjustment coefficient, for example, with a value ranging from 0.1 to 0.3. With... The increased torque output moderately reduces the overall torque output, resulting in a smoother pedal response and further ensuring smoothness.

[0056] In summary, by introducing an anti-motion sickness intensity coefficient linked to the probability of motion sickness and dynamically suppressing the torque change rate and overall gain, this manual enables precise and continuous adjustment of the anti-motion sickness control intensity. This not only avoids the abruptness of traditional on / off control but also provides just the right amount of personalized smoothness assurance for occupants experiencing different levels of discomfort, achieving a balance between comfort and usability.

[0057] The following is combined Figure 5This paper introduces another method for determining vehicle torque. The process clearly demonstrates how feedforward control, multi-domain filtering, and physiological feedback are integrated into a coherent processing chain. For example... Figure 5 As shown, the above method includes the following steps: In step S502, the torque calculation module performs adaptive load feedforward compensation.

[0058] In one embodiment, the process begins with the driver pressing the accelerator pedal. The torque calculation module simultaneously acquires the pedal opening, vehicle speed, and load information consisting of the curb weight and the current gross vehicle weight. The module first queries the torque mapping table (Pedal Map) based on the pedal opening and vehicle speed to obtain the base torque. Subsequently, the module determines the load correction factor based on the relationship between the current total mass and the curb weight. The two are then multiplied to generate the initial target torque. This step can be considered as feedforward control, which first eliminates the changes in dynamic response characteristics caused by mass differences, laying an adaptive foundation for ride comfort.

[0059] Step S504: The torque calculation module performs time-domain rate of change limiting.

[0060] In one embodiment, the initial target torque is obtained. Then, the torque calculation module further smooths it in the time domain. The module calculates the smoothness based on the current total mass. Determine the maximum rate of change threshold of the base. and the rate of change of torque command Constraints are imposed to ensure that the acceleration does not exceed the threshold. This layer of processing directly limits the rate of change of acceleration (jump), and is the first constraint to ensure smoothness.

[0061] Step S506: Frequency domain bandstop filtering is performed by the torque calculation module.

[0062] In one embodiment, the time-domain-limited torque command is further optimized in the frequency domain. The torque calculation module uses a band-stop filter designed for the 0.1-0.5 Hz sensitive frequency band. The torque command is filtered. This operation effectively filters out the oscillating components in this frequency band that are prone to causing motion sickness, serving as the second constraint for achieving higher-order comfort.

[0063] Step S508, the torque calculation module performs zero-crossing smoothing correction.

[0064] In one embodiment, to handle scenarios such as drive and regeneration switching, the torque calculation module performs zero-crossing checks on the filtered torque command. When the absolute value of the command is small, the module uses a hyperbolic tangent function. Nonlinear scaling forces the torque to transition smoothly near zero, completely eliminating torque abrupt changes. This is the third constraint ensuring continuous torque command across all operating conditions.

[0065] Step S510: The anti-dizziness control module performs physiological state monitoring and motion sickness probability assessment.

[0066] In one embodiment, in parallel with the torque preprocessing described above, the anti-motion sickness control module continuously collects the occupant's physiological signals, such as heart rate and respiratory rate, through an onboard occupant monitoring system (OMS). The module preprocesses and extracts features from these signals, inputs them into a preset physiological signal model, and calculates and outputs a motion sickness probability value in real time, characterizing the occupant's current level of motion sickness. .

[0067] Step S512: The anti-dizziness control module performs the anti-dizziness intensity coefficient decision.

[0068] In one embodiment, the anti-motion sickness control module will monitor the motion sickness probability in real time. It continuously compares the results with preset start and exit thresholds. When If the startup time continues to exceed the minimum startup duration for an extended period, the module determines that it is entering anti-motion sickness mode, and executes anti-motion sickness driving operations accordingly. Within the upper and lower threshold intervals, an anti-sickness strength coefficient that continuously varies in the range [0,1] is calculated using linear mapping or table lookup. .

[0069] Step S514: The anti-dizziness control module and the torque calculation module work together to dynamically adjust the anti-dizziness parameters.

[0070] In one embodiment, this step is a core feedback control step. The anti-dizziness control module calculates the anti-dizziness intensity coefficient. The data is sent to the torque calculation module. The torque calculation module then... Personalized adjustments to key control parameters: First, according to the formula Further tighten the torque change rate threshold; secondly, according to the formula By moderately reducing the overall torque gain, the pedal response becomes smoother.

[0071] Step S516: The anti-dizziness control module exits the anti-dizziness state.

[0072] In one embodiment, when the anti-motion sickness control module detects a motion sickness probability value... If the occupant's condition remains below the exit threshold and exceeds the minimum exit time, the occupant's condition is determined to have recovered. The module will automatically exit the anti-motion sickness control and notify the torque calculation module to gradually or all at once deactivate the special control strategy adopted for anti-motion sickness, switching back to the baseline pedal mapping, rate of change limit, and filter parameters to ensure that the vehicle's power performance is restored.

[0073] Figure 6 This is a schematic structural diagram of an electronic device according to an exemplary embodiment. Please refer to... Figure 6 At the hardware level, the electronic device includes a processor, internal bus, network interface, memory, and non-volatile storage, and may also include other necessary hardware. The processor reads the corresponding computer program from the non-volatile memory into memory and then executes it, forming a determination device based on vehicle torque at the logical level. Of course, this specification does not exclude other implementation methods besides software implementation, such as logic devices or a combination of hardware and software, etc. In other words, the execution entity of the following processing flow is not limited to individual logic units, but can also be hardware or logic devices.

[0074] Figure 7 This specification illustrates a block diagram of a vehicle torque determination device according to embodiments. Please refer to... Figure 7 This device can be applied to, for example Figure 6 The device shown, for implementing the technical solution described in this specification, includes: The information acquisition unit 702 is used to acquire the current vehicle driving information and load information of the vehicle, wherein the vehicle driving information includes pedal opening and vehicle speed. The factor determination unit 704 determines the base torque corresponding to the vehicle driving information according to the torque mapping table, and determines the corresponding load correction factor according to the load information. The torque mapping table is used to characterize the correspondence between different vehicle driving information and torque. The target torque determination unit 706 uses the product of the base torque and the load correction factor as the target torque for controlling vehicle movement.

[0075] Optionally, the load information includes the vehicle's curb weight and current gross weight; the information acquisition unit 702 is specifically used for: The curb weight is obtained from a preset vehicle storage unit; The current total mass is determined based on the sensing signals from the vehicle's tire pressure sensors.

[0076] Optionally, the factor determination unit 704 is specifically used for: The load correction factor is determined based on the relationship between the curb weight and the current total weight, and the load correction factor is positively correlated with the current total weight.

[0077] Optionally, the load information includes the current gross vehicle weight; the device further includes: The maximum rate of change threshold determination unit is used to determine the maximum rate of change threshold of the vehicle for the target torque based on the current total mass, wherein the current total mass is positively correlated with the maximum rate of change threshold.

[0078] Optionally, the device further includes: The target torque filtering unit is used to filter the target torque according to the band-stop filter in order to attenuate fluctuations in a preset low-frequency band.

[0079] Optionally, the device further includes: The target torque correction unit is used to correct the target torque based on a nonlinear smoothing coefficient so that the target torque can smoothly transition when switching between positive and negative values.

[0080] Optionally, the device further includes: An anti-motion sickness driving start unit is used to acquire the physiological signals of the occupants in the vehicle; The motion sickness probability value of the occupant is determined based on a preset physiological signal model; If the motion sickness probability value meets the conditions for activating anti-motion sickness driving, the anti-motion sickness driving operation is executed.

[0081] Optionally, the anti-motion sickness driving activation conditions include: the motion sickness probability value continuously exceeds the preset maximum motion sickness threshold and the duration of the duration exceeds the preset minimum activation time.

[0082] Optionally, the anti-motion sickness driving start unit is specifically used for: The corresponding anti-dizziness strength coefficient is determined based on the dizziness probability value; The maximum rate of change threshold for reducing the target torque is based on the anti-sickness strength coefficient, and / or the target torque is reduced.

[0083] The specific implementation process of the functions and roles of each unit in the above device can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.

[0084] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of the solution in this specification according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0085] Based on the same concept as the methods described above, this specification also provides a vehicle, including: a processor and a memory for storing processor-executable instructions; wherein the processor executes the executable instructions to implement the steps of the method as described in any of the above embodiments.

[0086] Based on the same concept as the methods described above, this specification also provides a computer-readable storage medium having computer instructions stored thereon that, when executed by a processor, implement the steps of the methods as described in any of the above embodiments.

[0087] Based on the same concept as the methods described above, this specification also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the methods as described in any of the above embodiments.

[0088] The embodiments of the subject matter and functional operation described in this specification can be implemented in the following ways: digital electronic circuits, tangibly embodied computer software or firmware, computer hardware including the structures disclosed in this specification and their structural equivalents, or combinations thereof. Embodiments of the subject matter described in this specification can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on a tangible, non-transitory program carrier for execution by a data processing apparatus or for controlling the operation of a data processing apparatus. Alternatively or additionally, the program instructions may be encoded on artificially generated propagation signals, such as machine-generated electrical, optical, or electromagnetic signals, which are generated to encode information and transmit it to a suitable receiving device for execution by the data processing apparatus. The computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or combinations thereof.

[0089] The processing and logic flow described in this specification can be executed by one or more programmable computers that execute one or more computer programs to perform corresponding functions by operating on input data and generating output. The processing and logic flow can also be executed by dedicated logic circuitry—such as FPGAs (Field-Programmable Gate Arrays) or ASICs (Application-Specific Integrated Circuits), and the device can also be implemented as dedicated logic circuitry.

[0090] Computers suitable for executing computer programs include, for example, general-purpose and / or special-purpose microprocessors, or any other type of central processing unit. Typically, the central processing unit receives instructions and data from read-only memory and / or random access memory. The basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include one or more mass storage devices for storing data, such as disks, magneto-optical disks, or optical disks, or the computer will be operatively coupled to such mass storage devices to receive data from or transfer data to them, or both. However, a computer is not required to have such devices. Furthermore, a computer can be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a GPS receiver, or a portable storage device such as a universal serial bus (USB) flash drive, to name a few.

[0091] Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, such as semiconductor memory devices (e.g., EPROM, EEPROM, and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto-optical disks, and CD-ROM and DVD-ROM disks. Processors and memory may be supplemented by or incorporated into dedicated logic circuitry.

[0092] While this specification contains numerous specific implementation details, these should not be construed as limiting the scope of any invention or the scope of the claims, but rather are primarily intended to describe features of specific embodiments of a particular invention. Certain features described in the various embodiments herein may also be implemented in combination in a single embodiment. Conversely, various features described in a single embodiment may also be implemented separately in various embodiments or in any suitable sub-combination. Furthermore, while features may function in certain combinations as described above and even initially claimed in this way, one or more features from a claimed combination may be removed from that combination in some cases, and a claimed combination may refer to a sub-combination or a variation thereof.

[0093] Similarly, although the operations are depicted in a specific order in the accompanying drawings, this should not be construed as requiring these operations to be performed in the specific order shown or sequentially, or requiring all illustrated operations to be performed to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. Furthermore, the separation of various system modules and components in the above embodiments should not be construed as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0094] Therefore, specific embodiments of the subject matter have been described. Furthermore, the processes depicted in the figures are not necessarily shown in a specific order or sequence to achieve the desired result. In some implementations, multitasking and parallel processing may be advantageous.

[0095] The above description is merely a preferred embodiment of this specification and is not intended to limit this specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of protection of this specification.

Claims

1. A method for determining vehicle torque, characterized in that, The method includes: Obtain the vehicle's current driving information and load information, including pedal opening and vehicle speed; The torque mapping table is used to determine the base torque corresponding to the vehicle driving information, and the load correction factor is determined according to the load information. The torque mapping table is used to characterize the correspondence between different vehicle driving information and torque. The product of the base torque and the load correction factor is used as the target torque for controlling vehicle movement.

2. The method according to claim 1, characterized in that, The load information includes the vehicle's curb weight and current gross weight; obtaining the load information includes: The curb weight is obtained from a preset vehicle storage unit; The current total mass is determined based on the sensing signals from the vehicle's tire pressure sensors.

3. The method according to claim 2, characterized in that, Determining the corresponding load correction factor based on the load information includes: The load correction factor is determined based on the relationship between the curb weight and the current total weight, and the load correction factor is positively correlated with the current total weight.

4. The method according to claim 1, characterized in that, The load information includes the current total mass of the vehicle; the method further includes: The maximum rate of change threshold of the vehicle for the target torque is determined based on the current total mass, and the current total mass is positively correlated with the maximum rate of change threshold.

5. The method according to claim 1, characterized in that, The method further includes: The target torque is filtered using a band-stop filter to attenuate fluctuations within a preset low-frequency band.

6. The method according to claim 1, characterized in that, The method further includes: The target torque is corrected based on a nonlinear smoothing coefficient to ensure a smooth transition when the target torque switches between positive and negative values.

7. The method according to claim 1, characterized in that, The method further includes: Acquire the physiological signals of the occupants in the vehicle; The motion sickness probability value of the occupant is determined based on a preset physiological signal model; If the motion sickness probability value meets the conditions for activating anti-motion sickness driving, the anti-motion sickness driving operation is executed.

8. The method according to claim 7, characterized in that, The anti-motion sickness driving activation conditions include: the motion sickness probability value continuously exceeds the preset maximum motion sickness threshold and the duration of the duration exceeds the preset minimum activation duration.

9. The method according to claim 7, characterized in that, The operation to prevent motion sickness while driving includes: The corresponding anti-dizziness strength coefficient is determined based on the dizziness probability value; The maximum rate of change threshold for reducing the target torque is based on the anti-sickness strength coefficient, and / or the target torque is reduced.

10. A vehicle, characterized in that, include: A processor; a memory for storing processor-executable instructions; wherein the processor implements the steps of the method as claimed in any one of claims 1-9 by executing the executable instructions.

11. A computer-readable storage medium, characterized in that, It stores computer instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1-9.

12. A computer program product, characterized in that, Includes a computer program / instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1-9.

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