Vehicle control method and device based on vehicle weight, storage medium and electronic device

Abstract

The invention provides a vehicle control method and device based on vehicle weight, a storage medium and an electronic device.The method comprises the steps that first sensor data collected by a seat weighing sensor of a vehicle and second sensor data collected by a deformation weighing sensor of the vehicle are obtained, the seat weighing sensor is used for collecting the load of a seat, and the deformation weighing sensor is used for collecting the deformation quantity of an axle; calculating the vehicle gravity center and the vehicle weight variation of the vehicle by adopting the first sensor data and the second sensor data; and real-time vehicle control parameters of the vehicle are adjusted according to the vehicle gravity center and the vehicle weight variation. According to the embodiment of the invention, the technical problem that the vehicle cannot be accurately controlled based on the gravity center and weight of the vehicle in the prior art is solved, and the accuracy and safety of vehicle control are improved.

Description

Technical Field

[0001] The present invention relates to the field of automobile technology, and in particular to a vehicle weight-based vehicle control method and device, a storage medium, and an electronic device. Background Art

[0002] In related technologies, vehicles with intelligent driving functions are gradually becoming popular in people's lives. However, how to obtain the vehicle's current center of gravity and changes in the vehicle's weight at all times, and thereby achieve more precise and safe control of the intelligent driving function, has always been a big problem.

[0003] With respect to the above-mentioned problems existing in the related technologies, no efficient and accurate solutions have been found yet. Summary of the invention

[0004] The present invention provides a vehicle weight-based vehicle control method and device, a storage medium, and an electronic device to solve technical problems in related technologies.

[0005] According to one embodiment of the present invention, a vehicle control method based on vehicle weight is provided, comprising: obtaining first sensor data collected by a seat weighing sensor of the vehicle, and obtaining second sensor data collected by a deformation weighing sensor of the vehicle, wherein the seat weighing sensor is used to collect the load-bearing capacity of the seat, and the deformation weighing sensor is used to collect the deformation of the axle; using the first sensor data and the second sensor data to calculate the vehicle center of gravity and vehicle weight change of the vehicle; and adjusting the real-time vehicle control parameters of the vehicle according to the vehicle center of gravity and the vehicle weight change.

[0006] Optionally, using the first sensor data and the second sensor data to calculate the vehicle center of gravity and vehicle weight change of the vehicle includes: determining the vehicle center of gravity of the vehicle according to the first sensor data; calculating the weighing coefficient of the deformation weighing sensor based on the vehicle center of gravity; and calculating the vehicle weight change of the vehicle based on the weighing coefficient and the second sensor data.

[0007] Optionally, determining the vehicle center of gravity of the vehicle based on the first sensor data includes: determining whether the vehicle meets the weighing conditions; if the vehicle meets the weighing conditions, determining the first sensor sub-data of each seat of the vehicle, the historical weight of the vehicle in the previous weighing cycle, and the whole vehicle layout information of the vehicle, wherein the first sensor sub-data includes weight data and sensor position, and the whole vehicle layout information is used to characterize the changing relationship between the vehicle center of gravity and the vehicle load-bearing distribution; determining the vehicle center of gravity of the vehicle based on the first sensor sub-data, the historical weight, and the whole vehicle layout information.

[0008] Optionally, calculating the weighing coefficient of the deformation weighing sensor based on the center of gravity of the vehicle includes: calculating the torque of each deformation weighing sensor according to the center of gravity of the vehicle, wherein the deformation weighing sensor includes multiple ones; for each deformation weighing sensor, converting the corresponding torque into a weighing coefficient, wherein the weighing coefficient is negatively or positively correlated with the torque.

[0009] Optionally, calculating the vehicle weight change based on the weighing coefficient and the second sensor data includes: obtaining the weighing zero position data of the deformation weighing sensor before the state is stable; calculating the vehicle weight change in the current weighing cycle based on the weighing zero position data, the weighing coefficient, and the second sensor data.

[0010] Optionally, calculating the vehicle weight change of the vehicle in the current weighing cycle according to the weighing zero position data, the weighing coefficient, and the second sensor data includes: using the following formula to calculate the vehicle weight change W of the vehicle in the current weighing cycle: W = KSlb*(WSlb-WSlb0)+KSrb*(WSrb-WSrb0)+KSla*(WSla-WSla0)+KSra*(WSra-WSra0); wherein, KSlb, KSrb, KSla, KSra are the weighing coefficients of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor respectively, WSlb, WSrb, WSla, WSra are the second sensor data of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor respectively, and WSlb0, WSrb0, WSla0, WSra0 are the weighing zero position data of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor respectively.

[0011] Optionally, adjusting the real-time vehicle control parameters of the vehicle according to the vehicle center of gravity and the vehicle weight change includes: identifying a driving scenario of the vehicle, wherein the driving scenario is used to describe the slope of a road on which the vehicle is located; and adjusting the real-time vehicle control parameters of the vehicle in the driving scenario using the vehicle center of gravity and the vehicle weight change.

[0012] Optionally, using the vehicle center of gravity and the vehicle weight change to adjust the real-time vehicle control parameters of the vehicle in the driving scenario includes: if the driving scenario is a horizontal driving scenario, selecting a first influence weight and a second influence weight that match the driving scenario; using the first influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserved distance change, and using the second influence weight and the vehicle weight change to calculate the vehicle's braking starting speed change; using the braking reserved distance change and the braking starting speed change to respectively adjust the vehicle's initial braking reserved distance and initial braking starting speed in the horizontal driving scenario.

[0013] Optionally, using the first influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's brake reserved distance change includes: calculating the distance between the vehicle center of gravity and the vehicle rear axle; using the following formula to calculate the vehicle's brake reserved distance change L1: L1 = K1*W+K2*L2, wherein the first influence weight includes K1 and K2, K1 and K2 are both greater than 1, W is the vehicle weight change, and L2 is the distance between the vehicle center of gravity and the vehicle rear axle.

[0014] Optionally, using the vehicle center of gravity and the vehicle weight change to adjust the real-time vehicle control parameters of the vehicle in the driving scenario includes: if the driving scenario is an uphill driving scenario, selecting a third influence weight and a fourth influence weight that match the driving scenario; using the third influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserve distance change, and using the fourth influence weight and the vehicle weight change to calculate the vehicle's output energy change; using the braking reserve distance change and the output energy change to respectively adjust the vehicle's initial braking reserve distance and initial output energy in the uphill driving scenario.

[0015] Optionally, using the vehicle center of gravity and the vehicle weight change to adjust the real-time vehicle control parameters of the vehicle in the driving scenario includes: if the driving scenario is a downhill driving scenario, selecting a fifth influence weight and a sixth influence weight that match the driving scenario; using the fifth influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserve distance change, and using the sixth influence weight and the vehicle weight change to calculate the vehicle's output energy change; using the braking reserve distance change and the output energy change to respectively adjust the vehicle's initial braking reserve distance and initial output energy in the downhill driving scenario.

[0016] According to another embodiment of the present invention, a vehicle control device based on vehicle weight is provided, including: an acquisition module, used to acquire first sensor data collected by a seat weighing sensor of the vehicle, and second sensor data collected by a deformation weighing sensor of the vehicle, wherein the seat weighing sensor is used to collect the load-bearing capacity of the seat, and the deformation weighing sensor is used to collect the deformation of the axle; a calculation module, used to calculate the vehicle center of gravity and vehicle weight change of the vehicle using the first sensor data and the second sensor data; an adjustment module, used to adjust the real-time vehicle control parameters of the vehicle according to the vehicle center of gravity and the vehicle weight change.

[0017] Optionally, the calculation module includes: a determination unit, used to determine the center of gravity of the vehicle based on the first sensor data; a first calculation unit, used to calculate the weighing coefficient of the deformation weighing sensor based on the center of gravity of the vehicle; and a second calculation unit, used to calculate the change in vehicle weight based on the weighing coefficient and the second sensor data.

[0018] Optionally, the determination unit includes: a judgment subunit, used to judge whether the vehicle meets the weighing conditions; a first determination subunit, used to determine the first sensor sub-data of each seat of the vehicle, the historical weight of the vehicle in the previous weighing cycle, and the whole vehicle layout information of the vehicle if the vehicle meets the weighing conditions, wherein the first sensor sub-data includes weight data and sensor position, and the whole vehicle layout information is used to characterize the changing relationship between the center of gravity of the vehicle and the vehicle load-bearing distribution; a second determination subunit, used to determine the vehicle center of gravity of the vehicle based on the first sensor sub-data, the historical weight, and the whole vehicle layout information.

[0019] Optionally, the first calculation unit includes: a calculation subunit, used to calculate the torque of each deformation weighing sensor according to the center of gravity of the vehicle, wherein the deformation weighing sensor includes multiple; a conversion subunit, used to convert the corresponding torque into a weighing coefficient for each deformation weighing sensor, wherein the weighing coefficient is negatively or positively correlated with the torque.

[0020] Optionally, the second calculation unit includes: an acquisition subunit, used to obtain the weighing zero position data of the deformation weighing sensor before the state is stabilized; and a calculation subunit, used to calculate the vehicle weight change of the vehicle in the current weighing cycle based on the weighing zero position data, the weighing coefficient, and the second sensor data.

[0021] Optionally, the calculation subunit is also used to calculate the vehicle weight change W of the vehicle in the current weighing cycle using the following formula: W = KSlb*(WSlb-WSlb0)+KSrb*(WSrb-WSrb0)+KSla*(WSla-WSla0)+KSra*(WSra-WSra0); wherein KSlb, KSrb, KSla, and KSra are respectively the weighing coefficients of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor; WSlb, WSrb, WSla, and WSra are respectively the second sensor data of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor; and WSlb0, WSrb0, WSla0, and WSra0 are respectively the weighing zero position data of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor.

[0022] Optionally, the adjustment module includes: an identification unit for identifying a driving scene of the vehicle, wherein the driving scene is used to describe the slope of the road on which the vehicle is located; and an adjustment unit for adjusting real-time vehicle control parameters of the vehicle in the driving scene using the vehicle center of gravity and the vehicle weight change.

[0023] Optionally, the adjustment unit includes: a first selection subunit, used to select a first influence weight and a second influence weight that match the driving scene if the driving scene is a horizontal driving scene; a first calculation subunit, used to use the first influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserved distance change, and use the second influence weight and the vehicle weight change to calculate the vehicle's braking starting speed change; a first adjustment subunit, used to use the braking reserved distance change and the braking starting speed change to respectively adjust the vehicle's initial braking reserved distance and initial braking starting speed in a horizontal driving scene.

[0024] Optionally, the first calculation subunit is also used to: calculate the distance between the center of gravity of the vehicle and the rear axle of the vehicle; calculate the change in braking reserve distance L1 of the vehicle using the following formula: L1=K1*W+K2*L2, wherein the first influence weight includes K1 and K2, K1 and K2 are both greater than 1, W is the change in vehicle weight, and L2 is the distance between the center of gravity of the vehicle and the rear axle of the vehicle.

[0025] Optionally, the adjustment unit includes: a second selection subunit, used to select a third influence weight and a fourth influence weight that match the driving scene if the driving scene is an uphill driving scene; a second calculation subunit, used to use the third influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserve distance change, and use the fourth influence weight and the vehicle weight change to calculate the vehicle's output energy change; a second adjustment subunit, used to use the braking reserve distance change and the output energy change to respectively adjust the vehicle's initial braking reserve distance and initial output energy in the uphill driving scene.

[0026] Optionally, the adjustment unit includes: a third selection subunit, used to select a fifth influence weight and a sixth influence weight that match the driving scene if the driving scene is a downhill driving scene; a third calculation subunit, used to use the fifth influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserve distance change, and use the sixth influence weight and the vehicle weight change to calculate the vehicle's output energy change; a third adjustment subunit, used to use the braking reserve distance change and the output energy change to respectively adjust the vehicle's initial braking reserve distance and initial output energy in the downhill driving scene.

[0027] According to another aspect of an embodiment of the present application, a storage medium is further provided, which includes a stored program, and the above steps are executed when the program is run.

[0028] According to another aspect of an embodiment of the present application, there is also provided an electronic device, including a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; wherein: the memory is used to store computer programs; and the processor is used to execute the steps in the above method by running the program stored in the memory.

[0029] The embodiment of the present application also provides a computer program product including instructions, which, when executed on a computer, enables the computer to execute the steps in the above method.

[0030] Beneficial effects of the present invention:

[0031] 1. A solution for accurate vehicle weighing and accurate vehicle control based on vehicle weight has been realized, which improves the accuracy of vehicle weighing;

[0032] 2. It solves the technical problem that related technologies cannot accurately control the vehicle based on the vehicle's center of gravity and weight, thereby improving the accuracy and safety of vehicle control. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0034] Figure 1 is a hardware structure block diagram of a vehicle-mounted domain controller according to an embodiment of the present invention;

[0035] Figure 2 is a flow chart of a vehicle control method based on vehicle weight according to an embodiment of the present invention;

[0036] Figure 3 is a deployment diagram of a weighing sensor in an embodiment of the present invention;

[0037] Figure 4 is a weighing flow chart of an embodiment of the present invention;

[0038] Figure 5 is a flow chart of controlling a vehicle based on the center of gravity and weight of the vehicle in an embodiment of the present invention;

[0039] Figure 6 The figure is a structural block diagram of a vehicle control device based on vehicle weight according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only embodiments of a part of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present application. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0041] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0042] Example 1

[0043] The method embodiment provided in the first embodiment of the present application can be executed in a vehicle, a vehicle-mounted domain controller, a processor or a similar processing device. Taking running on a vehicle-mounted domain controller as an example, Figure 1 FIG. 1 is a hardware structure diagram of a vehicle-mounted domain controller according to an embodiment of the present invention. Figure 1 As shown, the vehicle-mounted domain controller may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the vehicle-mounted domain controller may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the vehicle-mounted domain controller. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0044] The memory 104 can be used to store the vehicle-mounted domain controller program, for example, the software program and module of the application software, such as the vehicle-mounted domain controller program corresponding to the vehicle-weight-based vehicle control method of a vehicle-mounted domain controller in an embodiment of the present invention. The processor 102 executes various functional applications and data processing by running the vehicle-mounted domain controller program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the vehicle-mounted domain controller via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0045] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the vehicle-mounted domain controller. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0046] In this embodiment, a vehicle control method based on vehicle weight is provided. Figure 2is a flow chart of a vehicle control method based on vehicle weight according to an embodiment of the present invention, such as Figure 2 As shown, the process includes the following steps:

[0047] Step S202, obtaining first sensor data collected by a seat weighing sensor of the vehicle, and obtaining second sensor data collected by a deformation weighing sensor of the vehicle, wherein the seat weighing sensor is used to collect the load-bearing capacity of the seat, and the deformation weighing sensor is used to collect the deformation amount of the axle;

[0048] The deformation weighing sensors and seat weighing sensors of this embodiment both include multiple ones. The deformation weighing sensors are installed at both ends of the axle, and the positions are the positions where the deformation is the largest on the left and right symmetrical sides of the front and rear axles. The four deformation weighing sensors installed at the corresponding positions are: Slb (left front deformation sensor), Srb (right front deformation sensor), Sla (left rear deformation sensor), Sra (right rear deformation sensor). The seat weighing sensors are installed symmetrically under the seats. Taking the front and rear rows of seats as an example, four are installed respectively: SElb (driver's left front seat weighing sensor), SErb (passenger's right front seat weighing sensor), SEla (rear left rear seat weighing sensor), SEra (rear right rear seat weighing sensor). Figure 3 is a deployment diagram of the weighing sensor in an embodiment of the present invention.

[0049] The connection between the two types of weighing sensors and the vehicle's cockpit domain controller (YEDC), and the connection between the deformation weighing sensors on the front and rear axles, can be done through a CAN bus because of the large span, long connection distance, and the deformation weighing sensor itself needs to be powered. That is, each deformation weighing sensor is numbered and connected to the CAN bus through a CAN line, and the CAN bus is then connected to the cockpit domain controller. Similarly, the seat weighing sensor can also be connected to the cockpit domain controller using the CAN bus, or other methods such as UART (universal asynchronous receiver and transmitter), GPIO (general input / output), Ethernet, etc.

[0050] Step S204, calculating the center of gravity and vehicle weight change of the vehicle using the first sensor data and the second sensor data;

[0051] Step S206: adjusting the real-time vehicle control parameters of the vehicle according to the center of gravity of the vehicle and the change in vehicle weight.

[0052] Optionally, real-time vehicle control parameters include braking reserve distance, braking starting speed, output energy, etc.

[0053] Through the above steps, the first sensor data collected by the vehicle's seat weighing sensor and the second sensor data collected by the vehicle's deformation weighing sensor are obtained, wherein the seat weighing sensor is used to collect the load-bearing capacity of the seat, and the deformation weighing sensor is used to collect the deformation of the axle; the vehicle's center of gravity and vehicle weight change are calculated using the first sensor data and the second sensor data; the vehicle's real-time vehicle control parameters are adjusted according to the vehicle's center of gravity and the vehicle weight change, thereby realizing a solution for accurate vehicle weighing and accurate vehicle control based on vehicle weight, solving the technical problem that related technologies cannot accurately control vehicles based on vehicle center of gravity and weight, thereby improving the accuracy and safety of vehicle control.

[0054] In one implementation of the present embodiment, using the first sensor data and the second sensor data to calculate the vehicle center of gravity and vehicle weight change of the vehicle includes: determining the vehicle center of gravity of the vehicle according to the first sensor data; calculating the weighing coefficient of the deformation weighing sensor based on the vehicle center of gravity; and calculating the vehicle weight change of the vehicle based on the weighing coefficient and the second sensor data.

[0055] In one example, determining the vehicle center of gravity of the vehicle based on the first sensor data includes: determining whether the vehicle meets the weighing conditions; if the vehicle meets the weighing conditions, determining the first sensor sub-data of each seat of the vehicle, the historical weight of the vehicle in the previous weighing cycle, and the whole vehicle layout information of the vehicle, wherein the first sensor sub-data includes weight data and sensor position, and the whole vehicle layout information is used to characterize the changing relationship between the vehicle center of gravity and the vehicle load-bearing distribution; determining the vehicle center of gravity of the vehicle based on the first sensor sub-data, the historical weight, and the whole vehicle layout information.

[0056] Optionally, the vehicle engine speed or motor output power, as well as the door opening and closing signal are obtained. If the engine speed is 0 and the door is opened and closed continuously once, the weighing conditions are met and weighing can be performed.

[0057] Optionally, the vehicle center of gravity of this embodiment is the coordinate position of the vehicle's center of mass on the horizontal plane of the vehicle coordinate system. When determining the vehicle center of gravity, the historical center of gravity position of the vehicle in the previous weighing cycle can also be determined, and the current vehicle center of gravity of the vehicle is determined based on the historical center of gravity position and the first sensor sub-data. For example, if the first sensor sub-data of the left front seat increases, the vehicle center of gravity moves to the left front based on the historical center of gravity position, and if the first sensor sub-data of the right rear seat increases, the vehicle center of gravity moves to the right rear based on the historical center of gravity position, and the amount of movement is positively correlated with the amount of increase in the first sensor data.

[0058] Since various factors such as wear and temperature may affect the current weighing accuracy during the use of the vehicle, the center of gravity of the vehicle needs to be determined at each weighing moment. When the weighing conditions are met, the data of each seat weighing sensor is obtained to determine whether there is someone on each seat, and if there is someone, which seat position and the specific weight data of the human body. The precise weight data of the person and the existing weight of the vehicle itself (that is, the weight of the vehicle itself when it is empty, if it is loaded last time, the weight data of the load is used) are obtained by each seat weighing sensor, which is recorded as the weighing zero position: W0, and then combined with the corresponding overall layout, the center of gravity of the vehicle at this moment is calculated. If the weight data obtained by the seat weighing sensors at this time is incorrect, the correct weight data can also be manually entered for correction.

[0059] In one example, calculating the weighing coefficient of the deformation weighing sensor based on the center of gravity of the vehicle includes: calculating the torque of each deformation weighing sensor according to the center of gravity of the vehicle, wherein the deformation weighing sensor includes multiple ones; for each deformation weighing sensor, converting the corresponding torque into a weighing coefficient, wherein the weighing coefficient is negatively or positively correlated with the torque.

[0060] Calculate the distance from each deformation load cell (equivalent to the force point) to the center of the vehicle, and the torque is proportional to the distance.

[0061] In the example of determining the weighing coefficients of the four deformation weighing sensors on the front and rear axles, first, when the vehicle leaves the factory, the weighing coefficients of the four deformation weighing sensors Slb, Srb, Sla, and Sra have been calibrated at the factory, which are: KSlb0, KSrb0, KSla0, and KSra0. During each weighing, it is necessary to obtain the torque of the four deformation weighing sensors on the front and rear axles at the current moment according to the center of gravity at the weighing moment determined above: lSlb, lSrb, lSla, and lSra, and then convert them to obtain their corresponding weighing coefficients at the current moment: KSlb, KSrb, KSla, and KSra. That is, the deformation amount of each sensor at this moment is obtained by the real-time weight W1 and the precise weight W0 of the previous cycle. In an example, the weighing coefficient of the corresponding deformation weighing sensor is calculated using the following formula:

[0062]

[0063] The weighing coefficients of several other deformation weighing sensors can be obtained in the same way.

[0064] In one example, calculating the vehicle weight change based on the weighing coefficient and the second sensor data includes: obtaining the weighing zero position data of the deformation weighing sensor before the state is stable; calculating the vehicle weight change in the current weighing cycle based on the weighing zero position data, the weighing coefficient, and the second sensor data.

[0065] When the axle deformation weighing sensor confirms the zero position of the weighing, there is a time difference for the weight change of the vehicle during the cargo loading and unloading process to be "transmitted" to the axle deformation weighing sensor. After entering the weighing process, the weight information of each deformation weighing sensor of the axle is recorded, and a short cache of a few seconds is made to store the recorded weight data in an array (such as the acquisition frequency is once every 100ms, a total of dozens of times), and these weight data are sorted, and the first 10% and the last 10% of the data are removed in proportion, and then the average value of the remaining 80% of the data is calculated. When the weight information (average value) of each deformation weighing sensor of these axles changes > a certain threshold, the average value of the weight data of each deformation weighing sensor of the axle in the previous few seconds is taken as the zero position of the weighing. That is: WSlb0, WSrb0, WSla0, WSra0.

[0066] Optionally, calculating the vehicle weight change of the vehicle in the current weighing cycle according to the weighing zero position data, the weighing coefficient, and the second sensor data includes: using the following formula to calculate the vehicle weight change W of the vehicle in the current weighing cycle: W = KSlb*(WSlb-WSlb0)+KSrb*(WSrb-WSrb0)+KSla*(WSla-WSla0)+KSra*(WSra-WSra0); wherein, KSlb, KSrb, KSla, KSra are the weighing coefficients of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor respectively, WSlb, WSrb, WSla, WSra are the second sensor data of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor respectively, and WSlb0, WSrb0, WSla0, WSra0 are the weighing zero position data of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor respectively.

[0067] Figure 4It is a weighing flow chart of an embodiment of the present invention. At each weighing moment, it is necessary to first determine the center of gravity of the vehicle, determine the weighing coefficients of the four deformation weighing sensors of the front and rear axles, confirm the zero position of the axle deformation weighing sensor at the time of weighing, and finally weigh the result data. The weight data of each deformation weighing sensor of the axle a few seconds before the door is opened is selected. Because when the door is opened, the "stability" of the vehicle weighing environment will change, and the weighing result will be inaccurate. Finally, the screen of the cockpit domain controller displays the weighing results of the on-board cargo in real time. When the weighing is completed, the current positioning information and time information are obtained to form a complete weighing result record. W>0 (indicating loading); if: W<0 (indicating unloading), the loading and unloading of the cargo can be closed-loop managed through the record. At the same time, the TBOX of the cockpit domain controller is used to report and synchronize with the cloud, and if necessary, it can also be synchronized to the corresponding mobile terminal. Thus, a complete management of vehicle weighing is formed.

[0068] In this embodiment, adjusting the real-time vehicle control parameters of the vehicle according to the vehicle center of gravity and the vehicle weight change includes: identifying a driving scene of the vehicle, wherein the driving scene is used to describe the slope of the road on which the vehicle is located; and using the vehicle center of gravity and the vehicle weight change to adjust the real-time vehicle control parameters of the vehicle in the driving scene.

[0069] In this embodiment, after the vehicle turns on the automatic driving / assisted driving / intelligent driving function, the current center of gravity of the vehicle and the vehicle load weight or the weight of the whole vehicle are used as one of the vehicle control factors. Before the driver turns on the intelligent driving function to control the vehicle, the intelligent driving control function application: ADS_APP subscribes to the weighing APP through a service-oriented architecture (SOA) service-oriented manner. The center of gravity and vehicle weight data of the current vehicle on the weighing APP (published through the SOA service-oriented manner) are actually obtained through the internal vehicle network communication method.

[0070] In one implementation scenario, using the vehicle center of gravity and the vehicle weight change to adjust the real-time vehicle control parameters of the vehicle in the driving scene includes: if the driving scene is a horizontal driving scene, selecting a first influence weight and a second influence weight that match the driving scene; using the first influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserved distance change, and using the second influence weight and the vehicle weight change to calculate the vehicle's braking starting speed change; using the braking reserved distance change and the braking starting speed change to respectively adjust the vehicle's initial braking reserved distance and initial braking starting speed in the horizontal driving scene.

[0071] Optionally, using the first influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's brake reserved distance change includes: calculating the distance between the vehicle center of gravity and the vehicle rear axle; using the following formula to calculate the vehicle's brake reserved distance change L1: L1 = K1*W+K2*L2, wherein the first influence weight includes K1 and K2, K1 and K2 are both greater than 1, W is the vehicle weight change, and L2 is the distance between the vehicle center of gravity and the vehicle rear axle.

[0072] Figure 5 It is a flow chart of controlling the vehicle based on the center of gravity and weight of the vehicle in an embodiment of the present invention. For example, when the vehicle is traveling horizontally, the closer the center of gravity of the vehicle is to the front during horizontal driving, the heavier the weight of the vehicle, and the longer the distance required for braking. That is, the distance reserved for braking during horizontal driving is directly proportional to the center of gravity of the vehicle and the weight of the vehicle. When traveling horizontally or parking, the heavier the weight of the vehicle, the slower the speed that needs to be reduced to control the vehicle before braking. That is, the speed that needs to be reduced to control the vehicle before braking during horizontal driving is inversely proportional to the weight of the vehicle. That is, the first influence weights K1 and K2 are both greater than 1; the second influence weight K3 is less than 1.

[0073] L1 (change in brake reserve distance) = K1*W (vehicle weight) + K2*L2 (distance between center of gravity and rear axle);

[0074] V (change in braking speed) = K3*W (vehicle weight).

[0075] In another implementation scenario, using the vehicle center of gravity and the vehicle weight change to adjust the real-time vehicle control parameters of the vehicle in the driving scenario includes: if the driving scenario is an uphill driving scenario, selecting a third influence weight and a fourth influence weight that match the driving scenario; using the third influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserve distance change, and using the fourth influence weight and the vehicle weight change to calculate the vehicle's output energy change; using the braking reserve distance change and the output energy change to respectively adjust the vehicle's initial braking reserve distance and initial output energy in the uphill driving scenario.

[0076] For example, when going uphill, the further back the center of gravity of the vehicle is, the heavier the weight of the vehicle is, and the shorter the distance required for braking is (that is, the greater the current required for energy output), that is: the distance reserved for braking is inversely proportional to the center of gravity of the vehicle and the weight of the vehicle. When going uphill, the heavier the weight of the vehicle is, the greater the current required for the energy output of the vehicle is, that is: the energy output (output power) is directly proportional to the weight of the vehicle during the uphill process. That is: the third influence weights K1 and K2 are both less than 1; the fourth influence weight K4 is greater than 1.

[0077] L1 (change in brake reserve distance) = K1*W (vehicle weight) + K2*L2 (distance between center of gravity and rear axle);

[0078] Power (output energy change) = K4*W (vehicle weight);

[0079] In another implementation scenario, using the vehicle center of gravity and the vehicle weight change to adjust the real-time vehicle control parameters of the vehicle in the driving scenario includes: if the driving scenario is a downhill driving scenario, selecting a fifth influence weight and a sixth influence weight that match the driving scenario; using the fifth influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserve distance change, and using the sixth influence weight and the vehicle weight change to calculate the vehicle's output energy change; using the braking reserve distance change and the output energy change to respectively adjust the vehicle's initial braking reserve distance and initial output energy in the downhill driving scenario.

[0080] During the downhill process, it is also necessary to make corresponding adjustments according to the vehicle's center of gravity and vehicle load to achieve more accurate and safe vehicle control. That is: the fifth influence weights K1 and K2 are both less than 1; the sixth influence weight K4 is less than 1.

[0081] L1 (change in brake reserve distance) = K1*W (vehicle weight) + K2*L2 (distance between center of gravity and rear axle);

[0082] Power (output energy change) = K4*W (vehicle weight).

[0083] This embodiment proposes a vehicle-mounted weighing system, which can be applied to vehicles with intelligent driving functions. First, the deformation weighing sensor is installed. There are two axles in front and behind the passenger car. A deformation weighing sensor is installed on the left and right sides of each axle, and a corresponding seat weighing sensor is installed under the seat. The two types of weighing sensors are physically connected to the vehicle-mounted domain controller in the vehicle cabin, and then the corresponding weighing application APP is developed on the vehicle-mounted domain controller, which is displayed and operated on the corresponding display screen. When weighing, first identify the current state of the vehicle (driving or parking), then determine whether there is someone on the seat, and if there is someone, determine the position and weight of the person, thereby determining the center of gravity of the vehicle, and then load and unload goods in this scenario, automatically determine the weight change of the goods, and achieve accurate weighing every time. When the driver turns on the smart driving function, the function is based on the current horizontal, uphill or downhill scenario of the vehicle, the current center of gravity of the vehicle and the vehicle load weight, and the logic of the vehicle control algorithm: the braking reserved distance is proportional to the center of gravity of the vehicle and the weight of the vehicle; the weight of the vehicle is inversely proportional to the speed during vehicle control, etc., to achieve more accurate and safe vehicle control. Finally, the TBOX of the cockpit domain controller communicates with the cloud or the mobile terminal to synchronize the current weight changes and vehicle control conditions of the vehicle in real time to realize the self-learning optimization algorithm process.

[0084] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0085] Example 2

[0086] In this embodiment, a vehicle control device based on vehicle weight is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0087] Figure 6 is a structural block diagram of a vehicle control device based on vehicle weight according to an embodiment of the present invention, such as Figure 6 As shown, the device comprises:

[0088] An acquisition module 60, used to acquire first sensor data acquired by a seat weighing sensor of the vehicle, and to acquire second sensor data acquired by a deformation weighing sensor of the vehicle, wherein the seat weighing sensor is used to acquire the load-bearing capacity of the seat, and the deformation weighing sensor is used to acquire the deformation amount of the axle;

[0089] A calculation module 62, configured to calculate the vehicle center of gravity and vehicle weight change of the vehicle using the first sensor data and the second sensor data;

[0090] The adjustment module 64 is used to adjust the real-time vehicle control parameters of the vehicle according to the center of gravity of the vehicle and the change in vehicle weight.

[0091] Optionally, the calculation module includes: a determination unit, used to determine the center of gravity of the vehicle based on the first sensor data; a first calculation unit, used to calculate the weighing coefficient of the deformation weighing sensor based on the center of gravity of the vehicle; and a second calculation unit, used to calculate the change in vehicle weight based on the weighing coefficient and the second sensor data.

[0092] Optionally, the determination unit includes: a judgment subunit, used to judge whether the vehicle meets the weighing conditions; a first determination subunit, used to determine the first sensor sub-data of each seat of the vehicle, the historical weight of the vehicle in the previous weighing cycle, and the whole vehicle layout information of the vehicle if the vehicle meets the weighing conditions, wherein the first sensor sub-data includes weight data and sensor position, and the whole vehicle layout information is used to characterize the changing relationship between the center of gravity of the vehicle and the vehicle load-bearing distribution; a second determination subunit, used to determine the vehicle center of gravity of the vehicle based on the first sensor sub-data, the historical weight, and the whole vehicle layout information.

[0093] Optionally, the first calculation unit includes: a calculation subunit, used to calculate the torque of each deformation weighing sensor according to the center of gravity of the vehicle, wherein the deformation weighing sensor includes multiple; a conversion subunit, used to convert the corresponding torque into a weighing coefficient for each deformation weighing sensor, wherein the weighing coefficient is negatively or positively correlated with the torque.

[0094] Optionally, the second calculation unit includes: an acquisition subunit, used to obtain the weighing zero position data of the deformation weighing sensor before the state is stabilized; and a calculation subunit, used to calculate the vehicle weight change of the vehicle in the current weighing cycle based on the weighing zero position data, the weighing coefficient, and the second sensor data.

[0095] Optionally, the calculation subunit is also used to calculate the vehicle weight change W of the vehicle in the current weighing cycle using the following formula: W = KSlb*(WSlb-WSlb0)+KSrb*(WSrb-WSrb0)+KSla*(WSla-WSla0)+KSra*(WSra-WSra0); wherein KSlb, KSrb, KSla, and KSra are respectively the weighing coefficients of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor; WSlb, WSrb, WSla, and WSra are respectively the second sensor data of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor; and WSlb0, WSrb0, WSla0, and WSra0 are respectively the weighing zero position data of the left front deformation sensor, the right front deformation sensor, the left rear deformation sensor, and the right rear deformation sensor.

[0096] Optionally, the adjustment module includes: an identification unit for identifying a driving scene of the vehicle, wherein the driving scene is used to describe the slope of the road on which the vehicle is located; and an adjustment unit for adjusting real-time vehicle control parameters of the vehicle in the driving scene using the vehicle center of gravity and the vehicle weight change.

[0097] Optionally, the adjustment unit includes: a first selection subunit, used to select a first influence weight and a second influence weight that match the driving scene if the driving scene is a horizontal driving scene; a first calculation subunit, used to use the first influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserved distance change, and use the second influence weight and the vehicle weight change to calculate the vehicle's braking starting speed change; a first adjustment subunit, used to use the braking reserved distance change and the braking starting speed change to respectively adjust the vehicle's initial braking reserved distance and initial braking starting speed in a horizontal driving scene.

[0098] Optionally, the first calculation subunit is also used to: calculate the distance between the center of gravity of the vehicle and the rear axle of the vehicle; calculate the change in braking reserve distance L1 of the vehicle using the following formula: L1=K1*W+K2*L2, wherein the first influence weight includes K1 and K2, K1 and K2 are both greater than 1, W is the change in vehicle weight, and L2 is the distance between the center of gravity of the vehicle and the rear axle of the vehicle.

[0099] Optionally, the adjustment unit includes: a second selection subunit, used to select a third influence weight and a fourth influence weight that match the driving scene if the driving scene is an uphill driving scene; a second calculation subunit, used to use the third influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserve distance change, and use the fourth influence weight and the vehicle weight change to calculate the vehicle's output energy change; a second adjustment subunit, used to use the braking reserve distance change and the output energy change to respectively adjust the vehicle's initial braking reserve distance and initial output energy in the uphill driving scene.

[0100] Optionally, the adjustment unit includes: a third selection subunit, used to select a fifth influence weight and a sixth influence weight that match the driving scene if the driving scene is a downhill driving scene; a third calculation subunit, used to use the fifth influence weight, the vehicle center of gravity and the vehicle weight change to calculate the vehicle's braking reserve distance change, and use the sixth influence weight and the vehicle weight change to calculate the vehicle's output energy change; a third adjustment subunit, used to use the braking reserve distance change and the output energy change to respectively adjust the vehicle's initial braking reserve distance and initial output energy in the downhill driving scene.

[0101] It should be noted that the above modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0102] Example 3

[0103] An embodiment of the present invention further provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0104] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0105] S1, obtaining first sensor data collected by a seat weighing sensor of the vehicle, and obtaining second sensor data collected by a deformation weighing sensor of the vehicle, wherein the seat weighing sensor is used to collect the load-bearing capacity of the seat, and the deformation weighing sensor is used to collect the deformation of the axle;

[0106] S2, calculating the vehicle center of gravity and vehicle weight change of the vehicle using the first sensor data and the second sensor data;

[0107] S3, adjusting the real-time vehicle control parameters of the vehicle according to the center of gravity of the vehicle and the change in vehicle weight.

[0108] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0109] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0110] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0111] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0112] S1, obtaining first sensor data collected by a seat weighing sensor of the vehicle, and obtaining second sensor data collected by a deformation weighing sensor of the vehicle, wherein the seat weighing sensor is used to collect the load-bearing capacity of the seat, and the deformation weighing sensor is used to collect the deformation of the axle;

[0113] S2, calculating the vehicle center of gravity and vehicle weight change of the vehicle using the first sensor data and the second sensor data;

[0114] S3, adjusting the real-time vehicle control parameters of the vehicle according to the center of gravity of the vehicle and the change in vehicle weight.

[0115] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0116] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0117] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a general hardware platform, and of course, by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0118] It should be understood that the terms used herein are only for the purpose of describing specific example embodiments and are not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms "one", "an" and "said" as used herein may also be meant to include plural forms. The terms "include", "comprise", "contain", and "have" are inclusive, and therefore specify the existence of stated features, steps, operations, elements and / or parts, but do not exclude the existence or addition of one or more other features, steps, operations, elements, parts, and / or combinations thereof. The method steps, processes, and operations described herein are not interpreted as necessarily requiring them to be performed in the specific order described or illustrated, unless the execution order is clearly indicated. It should also be understood that additional or alternative steps may be used.

[0119] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A vehicle control method based on vehicle weight, characterized in that: include: Acquire first sensor data collected by a seat weighing sensor of the vehicle, and acquire second sensor data collected by a deformation weighing sensor of the vehicle, wherein the seat weighing sensor is used to collect the load-bearing capacity of the seat, and the deformation weighing sensor is used to collect the deformation amount of the axle; Calculating the vehicle center of gravity and vehicle weight change of the vehicle using the first sensor data and the second sensor data; The real-time vehicle control parameters of the vehicle are adjusted according to the center of gravity of the vehicle and the change in vehicle weight.

2. The method according to claim 1, characterized in that: Calculating the vehicle center of gravity and vehicle weight change of the vehicle using the first sensor data and the second sensor data includes: determining a vehicle center of gravity of the vehicle based on the first sensor data; Calculating a weighing coefficient of the deformation weighing sensor based on the center of gravity of the vehicle; A vehicle weight change of the vehicle is calculated based on the weighing coefficient and the second sensor data.

3. The method according to claim 2, characterized in that Determining the vehicle center of gravity of the vehicle according to the first sensor data includes: Determining whether the vehicle meets the weighing conditions; If the vehicle meets the weighing condition, determine the first sensor sub-data of each seat of the vehicle, the historical weight of the vehicle in the previous weighing cycle, and the whole vehicle layout information of the vehicle, wherein the first sensor sub-data includes weight data and sensor position, and the whole vehicle layout information is used to characterize the changing relationship between the center of gravity of the vehicle and the load-bearing distribution of the vehicle; The vehicle center of gravity of the vehicle is determined according to the first sensor sub-data, the historical weight, and the whole vehicle layout information.

4. The method according to claim 2, characterized in that: Calculating the weighing coefficient of the deformation weighing sensor based on the center of gravity of the vehicle includes: Calculating the moment of each deformation weighing sensor according to the center of gravity of the vehicle, wherein the deformation weighing sensor includes a plurality of sensors; For each deformation weighing sensor, the corresponding torque is converted into a weighing coefficient, wherein the weighing coefficient is negatively or positively correlated with the torque.

5. The method according to claim 2, characterized in that: Calculating the vehicle weight change based on the weighing coefficient and the second sensor data includes: Obtaining weighing zero position data of the deformation weighing sensor before the state is stable; The vehicle weight change of the vehicle in the current weighing cycle is calculated according to the weighing zero position data, the weighing coefficient, and the second sensor data.

6. The method according to claim 5, characterized in that Calculating the vehicle weight change of the vehicle in the current weighing cycle according to the weighing zero position data, the weighing coefficient, and the second sensor data includes: The following formula is used to calculate the vehicle weight change W of the vehicle in the current weighing cycle: W=KSlb*(WSlb-WSlb0)+KSrb*(WSrb-WSrb0)+KSla*(WSla-WSla0)+KSra*(WSra-WSra0); Among them, KSlb, KSrb, KSla, and KSra are the weighing coefficients of the left front deformation sensor, right front deformation sensor, left rear deformation sensor, and right rear deformation sensor respectively; WSlb, WSrb, WSla, and WSra are the second sensor data of the left front deformation sensor, right front deformation sensor, left rear deformation sensor, and right rear deformation sensor respectively; WSlb0, WSrb0, WSla0, and WSra0 are the weighing zero position data of the left front deformation sensor, right front deformation sensor, left rear deformation sensor, and right rear deformation sensor respectively.

7. The method according to claim 1, characterized in that Adjusting the real-time vehicle control parameters of the vehicle according to the center of gravity of the vehicle and the vehicle weight change includes: Identifying a driving scene of the vehicle, wherein the driving scene is used to describe the slope of a road on which the vehicle is located; The vehicle center of gravity and the vehicle weight change are used to adjust the real-time vehicle control parameters of the vehicle in the driving scene.

8. The method according to claim 7, characterized in that Using the vehicle center of gravity and the vehicle weight change to adjust the real-time vehicle control parameters of the vehicle in the driving scene includes: If the driving scene is a horizontal driving scene, selecting a first influence weight and a second influence weight that match the driving scene; Calculating a change in the vehicle's braking reserve distance using the first influence weight, the vehicle's center of gravity, and the vehicle weight change, and calculating a change in the vehicle's braking start speed using the second influence weight and the vehicle weight change; The braking reserve distance variation and the braking initial speed variation are used to adjust the initial braking reserve distance and the initial braking initial speed of the vehicle in a horizontal driving scenario, respectively.

9. The method according to claim 8, characterized in that Calculating the change in the braking reserve distance of the vehicle by using the first influence weight, the center of gravity of the vehicle, and the change in vehicle weight includes: Calculating the distance between the center of gravity of the vehicle and the rear axle of the vehicle; The following formula is used to calculate the braking distance change L1 of the vehicle: L1=K1*W+K2*L2, wherein the first influencing weight includes K1 and K2, K1 and K2 are both greater than 1, W is the vehicle weight change, and L2 is the distance between the center of gravity of the vehicle and the rear axle of the vehicle.

10. The method according to claim 7, characterized in that Using the vehicle center of gravity and the vehicle weight change to adjust the real-time vehicle control parameters of the vehicle in the driving scene includes: If the driving scene is an uphill driving scene, selecting a third influence weight and a fourth influence weight that match the driving scene; Calculating a change in a braking reserve distance of the vehicle using the third influence weight, the center of gravity of the vehicle, and the change in vehicle weight, and calculating a change in output energy of the vehicle using the fourth influence weight and the change in vehicle weight; The braking reserve distance variation and the output energy variation are used to adjust the initial braking reserve distance and the initial output energy of the vehicle in an uphill driving scenario respectively.

11. The method according to claim 7, characterized in that Using the vehicle center of gravity and the vehicle weight change to adjust the real-time vehicle control parameters of the vehicle in the driving scene includes: If the driving scene is a downhill driving scene, selecting a fifth influence weight and a sixth influence weight that match the driving scene; Calculating a change in a braking reserve distance of the vehicle using the fifth influence weight, the center of gravity of the vehicle, and the change in vehicle weight, and calculating a change in an output energy of the vehicle using the sixth influence weight and the change in vehicle weight; The braking reserve distance variation and the output energy variation are used to adjust the initial braking reserve distance and the initial output energy of the vehicle in a downhill driving scenario respectively.

12. A vehicle control device based on vehicle weight, characterized in that: include: An acquisition module, used to acquire first sensor data acquired by a seat weighing sensor of the vehicle, and to acquire second sensor data acquired by a deformation weighing sensor of the vehicle, wherein the seat weighing sensor is used to acquire the load-bearing capacity of the seat, and the deformation weighing sensor is used to acquire the deformation amount of the axle; A calculation module, configured to calculate the center of gravity and vehicle weight change of the vehicle using the first sensor data and the second sensor data; The adjustment module is used to adjust the real-time vehicle control parameters of the vehicle according to the center of gravity of the vehicle and the change in vehicle weight.

13. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 1 to 11 when executed.

14. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 11.

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