Driving control parameter adjusting method and device based on vehicle mass, equipment and medium

Abstract

The invention provides a driving control parameter adjusting method and device based on vehicle mass, equipment and a medium. The driving control parameter adjusting method comprises the steps that the current mass and the gravity center position of a vehicle are obtained based on a multi-source sensor; on the basis of the current mass, the equivalent radius from the gravity center position to the X rotating shaft of the vehicle and the equivalent radius from the gravity center position to the Z rotating shaft of the vehicle, the yaw rotational inertia and the longitudinal rotational inertia of the vehicle are determined; and determining automatic driving control parameters of the vehicle under the current mass based on the yawing rotational inertia and the longitudinal swinging rotational inertia so as to dynamically adjust the automatic driving control parameters. By sensing the mass change of the vehicle in real time, the automatic driving control parameters of the vehicle are dynamically optimized, and the driving safety and comfort are ensured.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle control, and in particular to a method, device, equipment and medium for adjusting driving control parameters based on vehicle mass. Background Art

[0002] Traditional autonomous driving systems usually rely on fixed vehicle parameters. Generally, vehicle manufacturers use the median value of vehicle load to design control strategies for vehicle acceleration and deceleration. However, in actual scenarios, factors such as vehicle load, cargo distribution, and the number of passengers can cause significant changes in mass. For example, the braking distance of a fully loaded vehicle can be several times that of an empty vehicle. If the control parameters are not adjusted dynamically, it is easy to cause rear-end collisions or rollovers. When passengers are unevenly distributed, for example, the left side is full of passengers, it will cause the vehicle's center of mass to shift, affecting the stability of the vehicle in curves. Therefore, how to dynamically adjust driving control parameters according to the mass of the vehicle has become a technical problem that cannot be underestimated. Summary of the Invention

[0003] In view of this, the purpose of the present application is to provide a method, device, equipment and medium for adjusting driving control parameters based on vehicle mass, which can dynamically optimize the autonomous driving control parameters of the vehicle by real-time sensing the change of vehicle mass, ensuring driving safety and comfort.

[0004] An embodiment of the present application provides a method for adjusting driving control parameters based on vehicle mass, and the driving control parameter adjustment method includes:

[0005] Obtain the current mass and the position of the center of gravity of the vehicle based on multi-source sensors;

[0006] Based on the current mass, the equivalent radius of the center of gravity position to the X rotation axis of the vehicle, and the equivalent radius of the center of gravity position to the Z rotation axis of the vehicle, determine the yaw moment of inertia and the pitch moment of inertia of the vehicle;

[0007] Based on the yaw moment of inertia and the pitch moment of inertia, determine the autonomous driving control parameters of the vehicle under the current mass, so as to dynamically adjust the autonomous driving control parameters.

[0008] In a possible implementation manner, the determining the autonomous driving control parameters of the vehicle under the current mass based on the yaw moment of inertia and the pitch moment of inertia includes:

[0009] Determine the current mode of the vehicle based on the proportional relationship between the yaw moment of inertia and the pitch moment of inertia;

[0010] For the current mode being the high yaw mode, based on the current mass, the reference mass of the vehicle, and the maximum steering angle at the reference mass, predict the steering angle rate of the vehicle when turning at the current mass.

[0011] For the current mode being the high longitudinal mode, based on the current mass, the reference mass of the vehicle, the mass compensation coefficient, the initial speed of the vehicle, and the friction coefficient, predict the safe braking distance of the vehicle at the current mass.

[0012] In a possible implementation manner, the determining the current mode of the vehicle based on the proportional relationship between the yaw moment of inertia and the pitch moment of inertia includes:

[0013] If the yaw moment of inertia is equal to the pitch moment of inertia, the current mode of the vehicle is the load balance mode;

[0014] If the yaw moment of inertia gradually increases, the current mode of the vehicle is the high yaw mode;

[0015] If the pitch moment of inertia gradually increases, the current mode of the vehicle is the high longitudinal mode;

[0016] Based on the yaw moment of inertia and the pitch moment of inertia, determine the left - right wheel load difference of the vehicle. If the left - right wheel load difference is greater than a preset threshold, the current mode of the vehicle is the single - side load offset mode.

[0017] In a possible implementation manner, predict the steering angle rate of the vehicle when turning through the following formula:

[0018]

[0019] where m is the current mass, m0 is the reference mass, θ base is the maximum steering angle at the reference mass, and θ max is the steering angle rate when turning.

[0020] In a possible implementation manner, after predicting the safe braking distance of the vehicle for the current mode being the high longitudinal mode to dynamically adjust the safe braking distance, the driving control parameter adjustment method further includes:

[0021] Based on the actual braking distance and the safe braking distance of the vehicle, determine the braking mode of the vehicle.

[0022] In a possible implementation manner, the driving control parameter adjustment method further includes:

[0023] For the unilateral load offset mode, the torque distribution of the vehicle is adjusted based on the current mass, or the asymmetric steering sensitivity of the vehicle is adjusted.

[0024] In a possible implementation, the obtaining of the current mass and the center of gravity position of the vehicle based on multi-source sensors includes:

[0025] Collect vehicle information based on a tire pressure sensor, a suspension height sensor, and inertial measurement unit data;

[0026] Perform information fusion on multiple pieces of the vehicle information based on a confidence weighted fusion formula to determine the current mass and the center of gravity position of the vehicle.

[0027] The embodiment of the present application also provides a driving control parameter adjustment device based on vehicle mass, and the driving control parameter adjustment device includes:

[0028] A mass dynamic perception module, configured to obtain the current mass and the center of gravity position of the vehicle based on multi-source sensors;

[0029] An inertia parameter determination module, configured to determine the yaw moment of inertia and the pitch moment of inertia of the vehicle based on the current mass, the equivalent radius of the center of gravity position to the X rotation axis of the vehicle, and the equivalent radius of the center of gravity position to the Z rotation axis of the vehicle;

[0030] A dynamic adjustment module, configured to determine the autonomous driving control parameters of the vehicle under the current mass based on the yaw moment of inertia and the pitch moment of inertia, so as to dynamically adjust the autonomous driving control parameters.

[0031] The embodiment of the present application also provides an electronic device, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device runs, the processor communicates with the memory through the bus. When the machine-readable instructions are executed by the processor, the steps of the above-mentioned driving control parameter adjustment method based on vehicle mass are executed.

[0032] The embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, the steps of the above-mentioned driving control parameter adjustment method based on vehicle mass are executed.

[0033] The driving control parameter adjustment method, device, equipment and medium based on vehicle mass provided by the embodiments of the present application, the driving control parameter adjustment method includes: obtaining the current mass and the center of gravity position of the vehicle based on multi-source sensors; determining the yaw moment of inertia and the pitch moment of inertia of the vehicle based on the current mass, the equivalent radius from the center of gravity position to the X rotation axis of the vehicle, and the equivalent radius from the center of gravity position to the Z rotation axis of the vehicle; determining the automatic driving control parameters of the vehicle under the current mass based on the yaw moment of inertia and the pitch moment of inertia, so as to dynamically adjust the automatic driving control parameters. By real-time sensing the change of vehicle mass, the automatic driving control parameters of the vehicle are dynamically optimized to ensure driving safety and comfort.

[0034] In order to make the above objects, features and advantages of the present application more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, makes a detailed description as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0036] Figure 1 It is a flowchart of a driving control parameter adjustment method based on vehicle mass provided by the embodiments of the present application;

[0037] Figure 2 It is one of the structural schematic diagrams of a driving control parameter adjustment device based on vehicle mass provided by the embodiments of the present application;

[0038] Figure 3 It is another structural schematic diagram of a driving control parameter adjustment device based on vehicle mass provided by the embodiments of the present application;

[0039] Figure 4 It is a structural schematic diagram of an electronic device provided by the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0040] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. Apparently, the described embodiments are only a part rather than all of the embodiments of this application. Components of the embodiments of this application usually described and illustrated in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of this application claimed, but merely represents selected embodiments of this application. Based on the embodiments of this application, every other embodiment obtained by those skilled in the art without creative efforts falls within the scope of protection of this application.

[0041] First, the applicable application scenarios of this application will be introduced. This application can be applied to the field of vehicle control technology.

[0042] Through research, it is found that traditional autonomous driving systems usually rely on fixed vehicle parameters. Generally, vehicle manufacturers will take the median value of vehicle load to design the control strategies for vehicle acceleration and deceleration. However, in actual scenarios, factors such as vehicle load, cargo distribution, and the number of passengers will cause significant changes in mass. For example, the braking distance difference between a fully loaded vehicle and an empty vehicle can reach several times. If the control parameters are not adjusted dynamically, it is easy to cause rear-end collisions or rollovers. When the passengers are unevenly distributed, such as when the left side is full of passengers, it will cause the vehicle's center of mass to shift, affecting the stability of turning. Therefore, how to dynamically adjust the driving control parameters according to the vehicle's mass has become a technical problem that cannot be underestimated.

[0043] Based on this, the embodiments of this application provide a method for adjusting driving control parameters based on vehicle mass, which dynamically optimizes the autonomous driving control parameters of the vehicle by real-time sensing the change in vehicle mass to ensure driving safety and comfort.

[0044] Please refer to Figure 1 , Figure 1 which is a flowchart of a method for adjusting driving control parameters based on vehicle mass provided by the embodiments of this application. As shown in Figure 1 , the method for adjusting driving control parameters provided by the embodiments of this application includes:

[0045] S101: Obtain the current mass and center of gravity position of the vehicle based on multi-source sensors.

[0046] In this step, the current mass and center of gravity position of the vehicle are obtained through multi-source sensors.

[0047] Among them, the multi-source sensors include a tire pressure sensor, a suspension height sensor, and an inertial measurement unit (IMU).

[0048] In a possible implementation manner, acquiring the current mass and the center-of-gravity position of the vehicle based on multi-source sensors includes:

[0049] Collecting vehicle information based on a tire-pressure sensor, a suspension-height sensor, and inertial measurement unit data; performing information fusion on multiple pieces of the vehicle information based on a confidence-weighted fusion formula to determine the current mass and the center-of-gravity position of the vehicle.

[0050] Here, the corresponding vehicle information is collected by using a tire-pressure sensor, a suspension-height sensor, and inertial measurement unit data, and information fusion is performed on multiple pieces of vehicle information by using a confidence-weighted fusion formula to determine the current mass and the center-of-gravity position of the vehicle.

[0051] In a specific embodiment, all sensor data is aligned with a hardware timestamp (error <1 ms), and the coordinate system is converted to the vehicle's center-of-gravity coordinate system. Confidence-weighted fusion formula: D = w1·D1 + w2·D2 +... + w n ·D, n where the parameters D1...D n are vehicle information from different sensors (such as radar ranging values, distances of obstacles identified by a camera, etc.). The parameters W1...W n are the confidence weights of each sensor, reflecting the reliability of the sensor in the current environment (range 0 to 1). Weight assignment rules: Sensor accuracy: Higher-precision sensors have higher weights (for example, radar is usually more accurate in ranging than a camera). Environmental interference: Adverse weather weakens the weights of optical sensors (such as the weight of a camera decreases in rainy weather). Real-time status: When the self-check of the sensor is abnormal, the weight is set to zero (such as a tire-pressure sensor failure). Using the finally fused data as the decision basis for the control module is more reliable than single-sensor data, reduces the risk of false alarms / missing alarms, and dynamically adapts to environmental changes.

[0052] S102: Determine the yaw moment of inertia and the pitch moment of inertia of the vehicle based on the current mass, the equivalent radius from the center-of-gravity position to the X rotation axis of the vehicle, and the equivalent radius from the center-of-gravity position to the Z rotation axis of the vehicle.

[0053] In this step, the yaw moment of inertia and the pitch moment of inertia of the vehicle are determined according to the current mass, the equivalent radius from the center-of-gravity position to the X rotation axis of the vehicle, and the equivalent radius from the center-of-gravity position to the Z rotation axis of the vehicle.

[0054] Here, the calculation formulas for the yaw moment of inertia and the pitch moment of inertia of the vehicle are:

[0055]

[0056] where I z is the yaw moment of inertia, kz is the equivalent radius from the center of gravity position to the Z rotation axis of the vehicle, I x is the yaw moment of inertia, k x is the equivalent radius from the center of gravity position to the X rotation axis of the vehicle, and m is the current mass.

[0057] Here, through these two formulas, the motion postures of each wheel are obtained. At the same time, the IMU is used to monitor the actual yaw angular velocity, pitch angular velocity, and lateral acceleration, and compare them with the model prediction values to correct the estimation error of the moment of inertia. The yaw moment of inertia I z The relationship with the wheel rotation is as follows: The yaw moment of inertia is the inertial characteristic when the vehicle rotates around the vertical axis (Z axis), which mainly affects the yaw motion of the vehicle, such as the stability during steering and passing vehicles. Vehicle yaw motion: The larger the yaw moment of inertia, the greater the inertia when the vehicle rotates around the vertical axis, and the slower the change in yaw angular velocity. This means that under the same steering input, a vehicle with a large yaw moment of inertia requires a greater torque to change its yaw angular velocity. Lateral force of the wheel: In the yaw motion, the wheels of the vehicle will generate a lateral force Fy, whose magnitude is related to the yaw angular velocity (γ) and the sideslip angle (α) of the vehicle. The yaw moment of inertia indirectly affects the lateral force of the wheel by affecting the yaw angular velocity, and further affects the steering characteristics and stability of the vehicle. The longitudinal moment of inertia I x The relationship with the wheel rotation is as follows: The longitudinal moment of inertia is the inertial characteristic when the vehicle rotates around the longitudinal axis (X axis), which mainly affects the pitch motion of the vehicle. Vehicle pitch motion: The larger the longitudinal moment of inertia, the greater the inertia when the vehicle rotates around the longitudinal axis, and the slower the change in pitch angular velocity. During acceleration or braking, the vehicle will generate pitch motion, and the longitudinal moment of inertia affects the pitch angular velocity and pitch acceleration of the vehicle. Longitudinal force of the wheel: In the pitch motion, the wheels of the vehicle will generate a longitudinal force Fx, whose magnitude is related to the pitch angular velocity and longitudinal acceleration of the vehicle. The longitudinal moment of inertia indirectly affects the longitudinal force of the wheel by affecting the pitch angular velocity, and further affects the acceleration and braking performance of the vehicle.

[0058] S103: Based on the yaw moment of inertia and the pitch moment of inertia, determine the automatic driving control parameters of the vehicle under the current mass so as to dynamically adjust the automatic driving control parameters.

[0059] In this step, according to the yaw moment of inertia and the pitch moment of inertia, determine the automatic driving control parameters of the vehicle under the current mass so as to dynamically adjust the automatic driving control parameters.

[0060] In a possible implementation manner, the determining the automatic driving control parameters of the vehicle under the current mass based on the yaw moment of inertia and the pitch moment of inertia includes:

[0061] (1) Determine the current mode of the vehicle based on the proportional relationship between the yaw moment of inertia and the pitch moment of inertia.

[0062] Among them, the modes of the vehicle include a load balance mode, a high yaw mode, a high longitudinal mode, and a unilateral load offset mode.

[0063] In a possible implementation manner, the determining the current mode of the vehicle based on the proportional relationship between the yaw moment of inertia and the pitch moment of inertia includes:

[0064] I: If the yaw moment of inertia is equal to the pitch moment of inertia, the current mode of the vehicle is the load balance mode.

[0065] Here, if the ratio between the yaw moment of inertia and the pitch moment of inertia is close to 1:1, the current mode of the vehicle is the load balance mode, indicating that the load of the vehicle is evenly distributed.

[0066] II: If the yaw moment of inertia gradually increases, the current mode of the vehicle is the high yaw mode.

[0067] Here, if the yaw moment of inertia gradually increases, the current mode of the vehicle is the high yaw mode, indicating that the goods of the vehicle are concentrated at the tail.

[0068] III: If the pitch moment of inertia gradually increases, the current mode of the vehicle is the high longitudinal mode.

[0069] Here, if the pitch moment of inertia gradually increases, the current mode of the vehicle is the high longitudinal mode, indicating that the front of the vehicle is loaded.

[0070] IV: Based on the yaw moment of inertia and the pitch moment of inertia, determine the left and right wheel load difference of the vehicle. If the left and right wheel load difference is greater than a preset threshold, the current mode of the vehicle is the unilateral load offset mode.

[0071] Here, according to the yaw moment of inertia and the pitch moment of inertia, determine the left and right wheel load difference of the vehicle. If the left and right wheel load difference is greater than a preset threshold, the current mode of the vehicle is the unilateral load offset mode.

[0072] Among them, the preset threshold can be 25%.

[0073] (2): For the current mode being the high yaw mode, based on the current mass, the reference mass of the vehicle, and the maximum steering angle under the reference mass, predict the steering angle rate of the vehicle when turning at the current mass.

[0074] Here, for the current mode being the high yaw mode, based on the current mass, the reference mass of the vehicle, and the maximum steering angle at the reference mass, the steering angle rate of the vehicle during cornering at the current mass is predicted, and the steering wheel angle increment is restricted in advance.

[0075] Here, the steering angle rate of the vehicle during cornering is predicted by the following formula:

[0076]

[0077] where m is the current mass, m0 is the reference mass, θ base is the maximum steering angle at the reference mass, and θ max is the steering angle rate during cornering.

[0078] (3): For the current mode being the high longitudinal mode, based on the current mass, the reference mass of the vehicle, the mass compensation coefficient, the initial speed of the vehicle, and the friction coefficient, the safe braking distance of the vehicle at the current mass is predicted.

[0079] Here, for the current mode being the high longitudinal mode, based on the current mass, the reference mass of the vehicle, the no-load reference time of the vehicle, the mass compensation coefficient, the initial speed of the vehicle, and the friction coefficient, the safe braking distance of the vehicle at the current mass is predicted.

[0080] where the safe braking distance is determined by the following formula:

[0081]

[0082] where S require is the safe braking distance, V is the initial speed, μ is the friction coefficient between the tire and the road surface, K1 is the mass compensation coefficient, about 0.2 - 0.4 for a passenger car, for example, generally 0.3 can be taken for a sedan, and m0 is the reference mass.

[0083] Here, the theoretical braking distance S brake can also be used as a basis, and by introducing a tire pressure compensation coefficient, the braking performance degradation caused by insufficient tire pressure is corrected to obtain the safe braking distance under tire pressure.

[0084]

[0085] where S require is the safe braking distance, S brake is the theoretical braking distance, K is the safety factor, P0 is the standard tire pressure (cold tire) specified by the vehicle manufacturer, and P tire is the actual tire pressure detected in real time.

[0086] In a possible implementation, when the current mode is the high longitudinal mode and the safe braking distance of the vehicle is predicted so as to dynamically adjust the safe braking distance, the driving control parameter adjustment method further includes:

[0087] Based on the actual braking distance and the safe braking distance of the vehicle, determine the braking mode of the vehicle.

[0088] Here, if the actual braking distance of the vehicle is less than 1.2 times the safe braking distance, control the vehicle to enter the braking mode of "hazard warning flash + maximum braking force + ESC intervention"; if the actual braking distance of the vehicle is between 1.2 times and 2 times the safe braking distance, control the vehicle to enter the braking mode of "linearly increasing braking force + pretensioning seat belt"; if the actual braking distance of the vehicle is greater than 2 times the safe braking distance, control the vehicle to enter the braking mode of "gradual braking curve".

[0089] In a possible implementation, the driving control parameter adjustment method further includes:

[0090] For the unilateral load offset mode, based on the current mass, adjust the torque distribution of the vehicle, or adjust the asymmetric steering sensitivity of the vehicle.

[0091] Here, for the unilateral load offset mode, adjust the torque distribution based on the mass, such as reducing the rear axle torque when the rear-wheel drive vehicle is fully loaded, or adjust the asymmetric steering sensitivity of the vehicle. For example, in the vehicle steering system: when the left steering sensitivity is high, an exponential curve can be used to increase the sensitivity of small-angle steering. When the right steering sensitivity is low, a linear curve can be used to reduce the over-response of large-angle steering.

[0092] Here, when the pressure difference between the left and right wheels exceeds 15%, a warning is triggered; when the lateral acceleration > 0.4g (such as during high-speed cornering), a high-risk warning is issued. When the difference between the actual value and the theoretical value > 20%, a reverse steering angle compensation is performed, thereby realizing the function of the cockpit system to automatically issue an early warning and timely prompt the driver of driving safety.

[0093] In this application, the above parameters such as the moment of inertia, steering angular rate, and safe braking distance are determined through a multi-sensor fusion mass-inertia feedback mechanism, and finally conveyed to each relevant component of the vehicle through instructions to achieve the autonomous driving state.

[0094] A method for adjusting driving control parameters based on vehicle mass provided by an embodiment of the present application, the driving control parameter adjustment method includes: obtaining the current mass and the center of gravity position of the vehicle based on multi-source sensors; determining the yaw moment of inertia and the pitch moment of inertia of the vehicle based on the current mass, the equivalent radius from the center of gravity position to the X rotation axis of the vehicle, and the equivalent radius from the center of gravity position to the Z rotation axis of the vehicle; determining the automatic driving control parameters of the vehicle under the current mass based on the yaw moment of inertia and the pitch moment of inertia, so as to dynamically adjust the automatic driving control parameters. By real-time sensing the change of vehicle mass, dynamically optimizing the automatic driving control parameters of the vehicle, ensuring driving safety and comfort.

[0095] Please refer to Figure 2 、 Figure 3 , Figure 2 which is one of the structural schematic diagrams of a driving control parameter adjustment device based on vehicle mass provided by an embodiment of the present application; Figure 3 which is the second structural schematic diagram of a driving control parameter adjustment device based on vehicle mass provided by an embodiment of the present application. As shown in Figure 2 , the driving control parameter adjustment device 200 includes:

[0096] A mass dynamic perception module 210, configured to obtain the current mass and the center of gravity position of the vehicle based on multi-source sensors;

[0097] An inertia parameter determination module 220, configured to determine the yaw moment of inertia and the pitch moment of inertia of the vehicle based on the current mass, the equivalent radius from the center of gravity position to the X rotation axis of the vehicle, and the equivalent radius from the center of gravity position to the Z rotation axis of the vehicle;

[0098] A dynamic adjustment module 230, configured to determine the automatic driving control parameters of the vehicle under the current mass based on the yaw moment of inertia and the pitch moment of inertia, so as to dynamically adjust the automatic driving control parameters.

[0099] Further, when the dynamic adjustment module 230 is used to determine the automatic driving control parameters of the vehicle under the current mass based on the yaw moment of inertia and the pitch moment of inertia, the dynamic adjustment module 230 is specifically configured to:

[0100] Determine the current mode of the vehicle based on the proportional relationship between the yaw moment of inertia and the pitch moment of inertia;

[0101] For the current mode being the high yaw mode, predict the steering angle rate of the vehicle when turning based on the current mass, the reference mass of the vehicle, and the maximum steering angle under the reference mass;

[0102] For the current mode being the high longitudinal mode, based on the current mass, the reference mass of the vehicle, the mass compensation coefficient, the initial speed of the vehicle, and the friction coefficient, predict the safe braking distance of the vehicle under the current mass.

[0103] Further, when the dynamic adjustment module 230 is used to determine the current mode of the vehicle based on the proportional relationship between the yaw moment of inertia and the pitch moment of inertia, the dynamic adjustment module 230 is specifically configured to:

[0104] If the yaw moment of inertia is equal to the pitch moment of inertia, the current mode of the vehicle is the load balance mode;

[0105] If the yaw moment of inertia gradually increases, the current mode of the vehicle is the high yaw mode;

[0106] If the pitch moment of inertia gradually increases, the current mode of the vehicle is the high longitudinal mode;

[0107] Based on the yaw moment of inertia and the pitch moment of inertia, determine the left and right wheel load difference of the vehicle. If the left and right wheel load difference is greater than a preset threshold, the current mode of the vehicle is the unilateral load offset mode.

[0108] Further, the dynamic adjustment module 230 predicts the steering angular velocity of the vehicle when turning through the following formula:

[0109]

[0110] where m is the current mass, m0 is the reference mass, θ base is the maximum steering angle under the reference mass, and θ max is the steering angular velocity when turning.

[0111] Further, as Figure 3 shown, the driving control parameter adjustment device 200 further includes a hierarchical response module 240, and the hierarchical response module 240 is used for:

[0112] Based on the actual braking distance and the safe braking distance of the vehicle, determine the braking mode of the vehicle.

[0113] Further, the dynamic adjustment module 230 is further used for:

[0114] For the unilateral load offset mode, based on the current mass, adjust the torque distribution of the vehicle, or adjust the asymmetric steering sensitivity of the vehicle.

[0115] Further, when the mass dynamic perception module 210 is used to obtain the current mass and the center of gravity position of the vehicle based on multi-source sensors, the mass dynamic perception module 210 is specifically configured to:

[0116] Collect vehicle information based on the tire pressure sensor, the suspension height sensor, and the inertial measurement unit data;

[0117] Perform information fusion on multiple pieces of the vehicle information based on the confidence weighted fusion formula to determine the current mass and the center of gravity position of the vehicle.

[0118] A driving control parameter adjustment device based on vehicle mass provided by an embodiment of the present application, the driving control parameter adjustment device includes: a mass dynamic perception module, configured to obtain the current mass and the center of gravity position of the vehicle based on multi-source sensors; an inertial parameter determination module, configured to determine the yaw moment of inertia and the pitch moment of inertia of the vehicle based on the current mass, the equivalent radius from the center of gravity position to the X rotation axis of the vehicle, and the equivalent radius from the center of gravity position to the Z rotation axis of the vehicle; a dynamic adjustment module, configured to determine the automatic driving control parameters of the vehicle under the current mass based on the yaw moment of inertia and the pitch moment of inertia, so as to dynamically adjust the automatic driving control parameters. By real-time sensing the change of vehicle mass, dynamically optimizing the automatic driving control parameters of the vehicle, ensuring driving safety and comfort.

[0119] Please refer to Figure 4 , Figure 4 which is a schematic structural diagram of an electronic device provided by an embodiment of the present application. As Figure 4 shown in

[0120] the electronic device 400 includes a processor 410, a memory 420, and a bus 430. Figure 1 The memory 420 stores machine-readable instructions executable by the processor 410. When the electronic device 400 runs, the processor 410 communicates with the memory 420 through the bus 430. When the machine-readable instructions are executed by the processor 410, the steps of the method for adjusting driving control parameters based on vehicle mass in the method embodiment as shown above can be executed. The specific implementation manner can refer to the method embodiment and will not be elaborated here.

[0121] An embodiment of the present application further provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium. When the computer program is run by a processor, the steps of the method for adjusting driving control parameters based on vehicle mass in the method embodiment as shown above can be executed. The specific implementation manner can refer to the method embodiment and will not be elaborated here. Figure 1 shown above

[0122] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0123] In several embodiments provided in the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some communication interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0124] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0125] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0126] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0127] Finally, it should be noted that the above-described embodiments are only specific implementation manners of the present application, used to illustrate the technical solutions of the present application, rather than limiting it. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: Any person skilled in the art within the technical scope disclosed by the present application can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A driving control parameter adjustment method based on vehicle mass, characterized in that: The driving control parameter adjustment method comprises: Obtain the current mass and center of gravity position of the vehicle based on multi-source sensors; Determining a yaw moment of inertia and a pitch moment of inertia of the vehicle based on the current mass, an equivalent radius from the center of gravity to an X-axis of rotation of the vehicle, and an equivalent radius from the center of gravity to a Z-axis of rotation of the vehicle; Based on the yaw moment of inertia and the pitch moment of inertia, the automatic driving control parameters of the vehicle under the current mass are determined so that the automatic driving control parameters can be dynamically adjusted.

2. The driving control parameter adjustment method according to claim 1, characterized in that: The determining, based on the yaw moment of inertia and the pitch moment of inertia, the automatic driving control parameters of the vehicle under the current mass includes: determining a current mode of the vehicle based on a proportional relationship between the yaw moment of inertia and the pitch moment of inertia; When the current mode is a high yaw mode, based on the current mass, the reference mass of the vehicle, and the maximum steering angle under the reference mass, predicting a steering angle rate of the vehicle when turning under the current mass; When the current mode is a high longitudinal mode, a safe braking distance of the vehicle under the current mass is predicted based on the current mass, a reference mass of the vehicle, a mass compensation coefficient, an initial speed of the vehicle, and a friction coefficient.

3. The driving control parameter adjustment method according to claim 2, characterized in that: The determining the current mode of the vehicle based on the proportional relationship between the yaw moment of inertia and the pitch moment of inertia includes: If the yaw moment of inertia is equal to the pitch moment of inertia, the current mode of the vehicle is a load balancing mode; If the yaw moment of inertia gradually increases, the current mode of the vehicle is a high yaw mode; If the pitch moment of inertia gradually increases, the current mode of the vehicle is a high longitudinal mode; Based on the yaw moment of inertia and the pitch moment of inertia, a load difference between the left and right wheels of the vehicle is determined. If the load difference between the left and right wheels is greater than a preset threshold, the current mode of the vehicle is a single-side load offset mode.

4. The driving control parameter adjustment method according to claim 2, characterized in that: The steering angle rate of the vehicle when turning is predicted by the following formula: Among them, m is the current mass, m0 is the reference mass, θ base is the maximum steering angle under reference mass, θ max is the steering angle rate when turning.

5. The driving control parameter adjustment method according to claim 2, characterized in that: After predicting the safe braking distance of the vehicle for the current mode being the high longitudinal mode so as to dynamically adjust the safe braking distance, the driving control parameter adjustment method further includes: A braking mode of the vehicle is determined based on the actual braking distance of the vehicle and the safe braking distance.

6. The driving control parameter adjustment method according to claim 3, characterized in that: The driving control parameter adjustment method further includes: For the one-sided load offset mode, the torque distribution of the vehicle is adjusted based on the current mass, or the asymmetric steering sensitivity of the vehicle is adjusted.

7. The driving control parameter adjustment method according to claim 1, characterized in that: The method of obtaining the current mass and center of gravity position of the vehicle based on the multi-source sensor includes: Collect vehicle information based on tire pressure sensors, suspension height sensors, and inertial measurement unit data; Based on the confidence weighted fusion formula, the multiple vehicle information are fused to determine the current mass and center of gravity position of the vehicle.

8. A driving control parameter adjustment device based on vehicle mass, characterized in that: The driving control parameter adjustment device comprises: The dynamic mass perception module is used to obtain the current mass and center of gravity position of the vehicle based on multi-source sensors; an inertia parameter determination module, configured to determine the yaw moment of inertia and pitch moment of inertia of the vehicle based on the current mass, an equivalent radius from the center of gravity to the X-axis of rotation of the vehicle, and an equivalent radius from the center of gravity to the Z-axis of rotation of the vehicle; A dynamic adjustment module is used to determine the automatic driving control parameters of the vehicle under the current mass based on the yaw moment of inertia and the pitch moment of inertia, so as to dynamically adjust the automatic driving control parameters.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the driving control parameter adjustment method based on vehicle mass as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the driving control parameter adjustment method based on vehicle mass as claimed in any one of claims 1 to 7 are executed.

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