A vehicle control method, device, medium and terminal based on road information

Abstract

The present invention discloses a vehicle control method, device, medium and terminal based on road information. The method includes: obtaining road information and vehicle information in front of the vehicle; determining an expected vehicle speed within a prediction time domain according to the vehicle information; and determining an optimal pedal torque at the current moment based on a model predictive control algorithm according to the road information, the vehicle information and the expected vehicle speed, and controlling the vehicle based on the optimal pedal torque. In this application, the vehicle speed is introduced into the model predictive control algorithm through the expected vehicle speed, so that the determined optimal pedal torque at the current moment can meet the requirement of stable vehicle speed, avoiding frequent gear shifting and speed regulation caused by too large a gap between the current vehicle speed and the vehicle speed corresponding to the optimal pedal torque, and enabling the vehicle to move forward smoothly.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle control, and particularly to a vehicle control method, device, medium and terminal based on road information. Background Art

[0002] MPC (Model Predictive Control) is an advanced process control method widely used in the field of vehicle control. Its core idea is that at the current sampling moment, the system dynamics within the prediction time domain are predicted, and then the optimal control sequence is obtained by solving the constructed optimal control problem within the prediction time domain. The first element of the optimal control sequence is applied to the controlled object, and the above steps are repeated at the next moment to achieve rolling control.

[0003] The current common vehicle control method is to calculate the optimal gear via MPC based on fuel consumption. However, when there is a certain gap between the current vehicle speed and the gear, this control method may require frequent gear shifting and speed adjustment, affecting the driving experience. Summary of the Invention

[0004] Embodiments of the present application provide a vehicle control method, device, medium and terminal based on road information. To provide a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary is not a comprehensive review, nor is it intended to identify key / important constituent elements or delineate the scope of protection of these embodiments. Its sole purpose is to present some concepts in a simple form as a prelude to the subsequent detailed description.

[0005] In a first aspect, embodiments of the present application provide a vehicle control method based on road information, the method comprising:

[0006] Obtain road information and vehicle information in front of the vehicle;

[0007] Determine the desired vehicle speed within the prediction time domain according to the vehicle information;

[0008] Based on the road information, the vehicle information and the desired vehicle speed, determine the optimal pedal torque at the current moment based on the model predictive control algorithm, and control the vehicle based on the optimal pedal torque.

[0009] Preferably, the desired vehicle speed within the prediction time domain is determined according to the following formula:

[0010] v(k + i) = i * (v(k) - v(k - h)) / h + v(k)

[0011] Among them, v(k) is the vehicle speed at time k, v(k+i) is the expected vehicle speed at time k+k, v(k-h) is the past vehicle speed at time k-h, i is a natural number, and h is a time period.

[0012] Preferably, the road information is obtained via the TBox module built in the vehicle.

[0013] Preferably, determining the optimal pedal torque at the current moment based on the model predictive control algorithm according to the road information, the vehicle information, and the expected vehicle speed includes:

[0014] Constructing an objective optimization function based on vehicle speed and fuel consumption;

[0015] Constructing a state space equation based on the expected vehicle speed and vehicle torque;

[0016] According to the objective optimization function and the state space equation, determining a vehicle torque correction sequence through the model predictive control algorithm;

[0017] Determining the optimal pedal torque at the current moment according to the vehicle torque correction sequence.

[0018] Preferably, the objective optimization function is:

[0019]

[0020] Among them, minz is the objective optimization function, z is its function substitute, is the sequence form of the torque correction amount, W r is the vehicle speed tracking coefficient, m f (v(k),T e (k)) is the minimum fuel consumption rate curve correction term based on vehicle speed and torque, Γ u is the torque fluctuation suppression coefficient, v(k) is the vehicle speed at time k, is its vector form, is the expected vehicle speed at time k, T e is the vehicle torque, T0 is the current moment, N is the number of periods of the prediction period, and u(k) is the torque correction amount at time k.

[0021] Preferably, the state space equation is:

[0022]

[0023]

[0024] Among them, v is the vehicle speed, T s is the time interval, η is the transmission efficiency, T e is the vehicle torque, is its first derivative, M is the vehicle weight, r is the tire radius, μ is the road surface friction coefficient, α is the road gradient, C d is the air resistance coefficient, A f is the frontal area, ρ is the air density, I f is the main reduction ratio, I g is the transmission ratio of the gearbox, and g is the gravitational coefficient.

[0025] Preferably, determining the optimal pedal torque at the current moment according to the vehicle torque correction sequence includes:

[0026] Obtaining the frictional torque of the vehicle;

[0027] Calculating the optimal pedal torque according to the first element of the vehicle torque correction sequence and the frictional torque.

[0028] In a second aspect, an embodiment of the present application provides a vehicle control device based on road information. The device includes:

[0029] An acquisition module, which is used to acquire road information and vehicle information in front of the vehicle;

[0030] A prediction module, which is used to determine the desired vehicle speed within a prediction time domain according to the vehicle information;

[0031] A control module, which is used to determine the optimal pedal torque at the current moment based on a model predictive control algorithm according to the road information, the vehicle information, and the desired vehicle speed, and control the vehicle based on the optimal pedal torque.

[0032] In a third aspect, an embodiment of the present application provides a computer storage medium. The computer storage medium stores multiple instructions, and the instructions are adapted to be loaded and executed by a processor to perform the above method steps.

[0033] In a fourth aspect, an embodiment of the present application provides a terminal, which may include: a processor and a memory; wherein, the memory stores a computer program, and the computer program is adapted to be loaded and executed by the processor to perform the above method steps.

[0034] The technical solution provided by the embodiment of the present application may include the following beneficial effects:

[0035] In the embodiment of the present application, in the present application, the vehicle speed is introduced into the model predictive control algorithm through the desired vehicle speed, so that the optimal pedal torque determined at the current moment can meet the requirement of stable vehicle speed, and avoid the frequent shift speed regulation situation caused by the large gap between the current vehicle speed and the vehicle speed corresponding to the optimal pedal torque, so that the vehicle can move forward smoothly.

[0036] In this application, while maintaining the vehicle speed to track the driver's expectation, a correction term for the minimum fuel consumption rate fitting curve is introduced to automatically select the engine internal torque with the lowest fuel consumption and the smallest amplitude fluctuation under the current working condition, effectively improving the driver's driving experience and the fuel economy of the whole vehicle. At the same time, road information is introduced to correct the current vehicle control torque, improve the control accuracy, reduce the ECU calculation load, and make a trade-off between the driver's driving comfort and fuel saving through the weight coefficient, effectively improving the performance of the whole vehicle.

[0037] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings herein are incorporated into and constitute a part of this specification, showing embodiments consistent with the present invention and, together with the specification, are used to explain the principles of the present invention.

[0039] Figure 1 is a schematic flowchart of a vehicle control method based on road information provided by an embodiment of this application;

[0040] Figure 2 is a flowchart of the predictive control process of a vehicle control method based on road information provided by an embodiment of this application;

[0041] Figure 3 is a flowchart of the optimal pedal torque calculation of a vehicle control method based on road information provided by an embodiment of this application;

[0042] Figure 4 is a schematic structural diagram of a vehicle control device based on road information provided by an embodiment of this application;

[0043] Figure 5 is a schematic structural diagram of a terminal provided by an embodiment of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] The following description and the accompanying drawings fully illustrate the specific embodiments of the present invention so that those skilled in the art can practice them.

[0045] It should be clear that the described embodiments are only a part of the embodiments of the present invention, rather than all of them. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0046] When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0047] In the description of the present invention, it should be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be construed as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. In addition, in the description of the present invention, unless otherwise specified, "a plurality" means two or more. "And / or" describes the association relationship of associated objects and indicates that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after.

[0048] The present application provides a vehicle control method, device, medium, and terminal based on road information to solve the problems existing in the above-mentioned related technical problems. In the technical solution provided by the present application, the vehicle speed is introduced into the model predictive control algorithm through the desired vehicle speed, so that the optimal pedal torque at the current moment determined can meet the requirement of vehicle speed stability, and the problem of frequent gear shifting and speed regulation caused by too large a gap between the current vehicle speed and the vehicle speed corresponding to the optimal pedal torque is avoided. The following will be described in detail with exemplary embodiments.

[0049] The following will be combined with the attached Figure 1 - attached Figure 3 to introduce in detail the vehicle control method based on road information provided by the embodiments of the present application. This method can be implemented depending on a computer program and can run on a vehicle control device based on the von Neumann architecture. This computer program can be integrated into an application or run as an independent tool class application.

[0050] Please refer to Figure 1 , which is a schematic flowchart of a vehicle control method based on road information provided by an embodiment of the present application. As Figure 1 shown, the method of the embodiment of the present application may include the following steps:

[0051] S100, obtain the road information and vehicle information in front of the vehicle;

[0052] Among them, the road information and vehicle information can be obtained by directly reading through pre-setting, or by reading from the cloud, or by other means.

[0053] In one embodiment, the road information is obtained via the in-vehicle TBox module.

[0054] Among them, the TBox (Telematics Box, remote communication terminal) module is a product integrating in-vehicle network and wireless communication functions, and can provide Telematics services.

[0055] In this embodiment, the TBox module is a module that the vehicle itself has. This module has a variety of information built in. By obtaining the road information in front of the vehicle through the TBox module, there is no need to additionally add other acquisition modules or acquisition methods, and only the road information data that needs to be read needs to be set, greatly simplifying the modification of the vehicle itself.

[0056] S200, determine the desired vehicle speed within the prediction horizon according to the vehicle information;

[0057] It should be noted that in this embodiment, the desired vehicle speed within the prediction horizon is a prediction of the vehicle speed. The determination of this desired vehicle speed is not to determine the desired vehicle speed as a constant, but to determine the prediction expression or prediction calculation method of the desired vehicle speed.

[0058] It needs to be determined that in this embodiment, the desired vehicle speed cannot be considered as the vehicle speed that the driver wants.

[0059] S300, based on the road information, the vehicle information, and the desired vehicle speed, determine the optimal pedal torque at the current moment based on the model predictive control algorithm, and control the vehicle based on the optimal pedal torque.

[0060] In this embodiment, the pedal torque has a one-to-one correspondence with the opening of the vehicle's accelerator pedal; for the control of the entire vehicle, after inputting the pedal torque, the specific control of the vehicle can be completed based on the existing control system. This specific control process is the control process that the vehicle itself already has and will not be elaborated in this application.

[0061] Through the pedal torque / optimal pedal torque, it can be directly connected to the vehicle's own control program, and the specific control is completed using the vehicle's own control system.

[0062] In this application, the vehicle speed is introduced into the model predictive control algorithm through the desired vehicle speed, so that the optimal pedal torque determined at the current moment can meet the requirement of stable vehicle speed, avoiding the frequent shift speed regulation situation caused by too large a gap between the current vehicle speed and the vehicle speed corresponding to the optimal pedal torque, and enabling the vehicle to move forward smoothly.

[0063] In one embodiment, the desired vehicle speed within the prediction horizon is determined according to the following formula:

[0064] v(k + i) = i * (v(k) - v(k - h)) / h + v(k)

[0065] Wherein, v(k) is the vehicle speed at time k, v(k + i) is the expected vehicle speed at time k + i, v(k - h) is the past vehicle speed at time k - h, i is a natural number, and h is a time period.

[0066] In this way, through this formula, the expected vehicle speed within the prediction horizon can be determined based on the current vehicle speed and the past vehicle speed, so that the vehicle speed can be introduced into the model predictive control algorithm.

[0067] In this embodiment, based on this expected vehicle speed formula, an expected vehicle speed sequence can be obtained.

[0068] In one implementation, as Figure 2 shown, determining the optimal pedal torque at the current moment based on the model predictive control algorithm according to the road information, the vehicle information, and the expected vehicle speed includes:

[0069] S310, constructing an objective optimization function based on vehicle speed and fuel consumption;

[0070] In this embodiment, since the objective optimization function is constructed based on vehicle speed and fuel consumption, during the model predictive control process, the vehicle speed changes more smoothly and the fuel consumption is less through the objective optimization function.

[0071] Preferably, the objective optimization function is constructed based on the deviation between the actual vehicle speed and the expected vehicle speed, so that the vehicle speed is stable during the model predictive control process and the problem of frequent gear shifting and speed adjustment is avoided.

[0072] Preferably, the objective optimization function is also constructed based on fuel consumption, so that the fuel consumption is less on the premise of a stable vehicle speed during the model predictive control process, meeting the driver's driving needs and the purpose of fuel saving.

[0073] In one implementation, the objective optimization function is:

[0074]

[0075] Wherein, minz is the objective optimization function, z is its function reference, is the sequence form of the torque correction amount, W r is the vehicle speed tracking coefficient, m f (v(k), T e (k)) is the correction term of the minimum fuel consumption rate curve based on vehicle speed and torque, Γ u is the torque fluctuation suppression coefficient, v(k) is the vehicle speed at time k, is its vector form, is the expected vehicle speed at time k, T eLet \(T\) be the vehicle torque, \(T_0\) be the current moment, \(N\) be the number of cycles in the prediction period, and \(u(k)\) be the torque correction at time \(k\).

[0076] Among them, In \(\min_z\), \(z\) represents the entire objective optimization function. Specifically, it means optimizing the value of the function \(z\) to the minimum. Here, \(z\) is a function alias, serving as the name of the function to be optimized; the subscript is the sequence form of the torque correction, which means is optimized within all value ranges of

[0077] Preferably, \(W\) r is the vehicle speed tracking coefficient, and \(\Gamma\) u is the torque fluctuation suppression coefficient. These two weight coefficient cases are selected to balance the driver's driving experience and the vehicle's economic performance.

[0078] Preferably, \(m\) is the correction term for the minimum fuel consumption rate curve based on vehicle speed and torque. This minimum fuel consumption rate curve is obtained by fitting the universal curve and the constant power curve.

[0079] In this application, the universal curve, that is, the universal characteristic curve / universal characteristic, takes the rotational speed as the abscissa and the torque or mean effective pressure as the ordinate, and draws many equal fuel consumption rate curves and constant power curves on the graph to form the engine universal characteristic.

[0080] Among them, the universal characteristic curve is essentially the synthesis of all load characteristic and speed characteristic curves, representing the variation relationship of the main parameters of the engine within the entire working range. Based on this, the most economical working area of the engine can be determined.

[0081] In this embodiment, the minimum fuel consumption rate curve is the tangent point of the universal curve and the constant power curve, representing the minimum fuel consumption at the current rotational speed under the current power. In the objective optimization function, the correction term for the minimum fuel consumption rate curve essentially serves as a correction coefficient to achieve the purpose of minimizing the limited fuel consumption.

[0082] In this application, the expression of the minimum fuel consumption fitting curve is:

[0083] \(T\) e \(= k \cdot n\)

[0084] Among them, \(T\) e is the torque inside the engine, \(k\) is the fitting coefficient, and \(n\) is the engine rotational speed.

[0085] In this application, \(u(k)\) is the torque correction at time \(k\). This torque correction is the square of the shortest distance between the current actual torque inside the engine and the actual rotational speed on the \(T\) e - \(n\) curve graph from the fitting curve (minimum fuel consumption fitting curve).

[0086] In this application, the in-engine torque is the vehicle torque.

[0087] In this embodiment, the target optimization function can ensure tracking of the driver's desired vehicle speed while keeping the vehicle torque fluctuation small, and at the same time reduce the vehicle's fuel consumption level.

[0088] In one implementation manner, the target optimization function is constructed after establishing a vehicle fuel consumption model and a vehicle dynamics model.

[0089] Among them, the vehicle fuel consumption model and the vehicle dynamics model are conventional models in the field of vehicle control, and their specific information is not elaborated in this application.

[0090] S320. Construct a state space equation based on the desired vehicle speed and the vehicle torque;

[0091] In this embodiment, since the state space equation is constructed based on the desired vehicle speed and the vehicle torque, during the model predictive control process, rolling control of the desired vehicle speed and the vehicle torque is achieved through the state space equation.

[0092] In one implementation manner, the state space equation is as follows:

[0093]

[0094]

[0095] Among them, v is the vehicle speed, T s is the time interval, η is the transmission efficiency, T e is the vehicle torque, is its first derivative, M is the vehicle weight, r is the tire radius, μ is the road surface friction coefficient, α is the road slope, C d is the air resistance coefficient, A f is the frontal area, ρ is the air density, I f is the final drive ratio, I g is the transmission ratio of the gearbox, and g is the gravitational coefficient.

[0096] S330. According to the target optimization function and the state space equation, determine the vehicle torque correction sequence through a model predictive control algorithm;

[0097] In this application, given the target optimization function and the state space equation, the corresponding vehicle torque correction sequence can be calculated through a model predictive control algorithm, and the specific calculation process is not elaborated in this application.

[0098] It should be noted that the above determination of the vehicle torque correction sequence is repeated at each moment / each cycle. By calculating and selecting the first element of the output vehicle torque correction sequence and then performing cyclic calculation, rolling optimization is carried out.

[0099] In this application, the vehicle torque is the internal torque of the engine.

[0100] S340. Determine the optimal pedal torque at the current moment according to the vehicle torque correction sequence.

[0101] Among them, there is a corresponding correlation between the vehicle torque and the optimal pedal torque. Based on this corresponding correlation, the optimal pedal torque corresponding to the vehicle torque can be calculated.

[0102] In this application, the vehicle torque correction sequence is a sequence composed of multiple vehicle torques, and the optimal pedal torque corresponding to the first vehicle torque is the optimal pedal torque at the current moment.

[0103] In one implementation, as Figure 3 shown, the determination of the optimal pedal torque at the current moment according to the vehicle torque correction sequence includes:

[0104] S341. Obtain the friction torque of the vehicle;

[0105] In this application, under the current accuracy, the friction torque of the vehicle is related to the vehicle model and the engine model. Therefore, when the vehicle model and the engine model are determined, the friction torque of the vehicle is also determined.

[0106] Based on this, the friction torque of the vehicle can be directly read when needed by pre-integrating it; or a correlation table between the friction torque of the vehicle and the vehicle model and the engine model can be pre-integrated, and the friction torque of the vehicle can be determined by looking up the table when needed.

[0107] S342. Calculate the optimal pedal torque according to the first element of the vehicle torque correction sequence and the friction torque.

[0108] In this embodiment, the optimal pedal torque at the current moment is calculated through the first vehicle torque of the vehicle torque correction sequence and the friction torque.

[0109] Among them, a calculation formula for calculating the optimal pedal torque from the vehicle torque and the friction torque can be preset in the vehicle system, and the optimal pedal torque at the current moment can be calculated through this formula.

[0110] Preferably, the optimal pedal torque is the sum of the vehicle torque and the friction torque.

[0111] In this application, torque loss is spontaneously compensated according to the road information ahead. Meanwhile, while keeping the vehicle speed within the range expected by the driver, fuel loss is reduced, achieving the purpose of improving the overall vehicle economy.

[0112] In this application, by selecting appropriate weight coefficients: vehicle speed tracking coefficient and torque fluctuation suppression coefficient, the driver's driving experience and the improvement of the overall vehicle economic performance are balanced.

[0113] In this application, while keeping the vehicle speed tracking the driver's expectation, a fitting curve correction term for the minimum fuel consumption rate is introduced to automatically select the engine internal torque with the lowest fuel consumption and the smallest amplitude fluctuation under the current working condition, effectively improving the driver's driving experience and the overall vehicle economy. At the same time, road information is introduced to correct the current vehicle control torque, improving the control accuracy, reducing the ECU calculation load, and making a trade-off between the driver's driving comfort and fuel saving through the weight coefficient, effectively improving the overall vehicle performance.

[0114] The following is an embodiment of the device of the present invention, which can be used to execute the method embodiment of the present invention. For details not disclosed in the device embodiment of the present invention, please refer to the method embodiment of the present invention.

[0115] Please refer to Figure 4 , which shows a schematic structural diagram of a vehicle control device based on road information provided by an exemplary embodiment of the present invention. The vehicle control device based on road information can be implemented as all or part of a terminal through software, hardware, or a combination of both. The device includes an acquisition module 10, a prediction module 20, and a control module 30.

[0116] The acquisition module 10 is used to acquire the road information and vehicle information in front of the vehicle;

[0117] The prediction module 20 is used to determine the expected vehicle speed within the prediction time domain according to the vehicle information;

[0118] The control module 30 is used to determine the optimal pedal torque at the current moment based on the model predictive control algorithm according to the road information, the vehicle information, and the expected vehicle speed, and control the vehicle based on the optimal pedal torque.

[0119] It should be noted that when the vehicle control device based on road information provided in the above embodiment executes the vehicle control method based on road information, only the above-mentioned division of each functional module is used for illustration. In actual application, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the vehicle control device based on road information provided in the above embodiment and the method embodiment of the vehicle control method based on road information belong to the same concept, and the implementation process is detailed in the method embodiment, which will not be repeated here.

[0120] The serial numbers of the embodiments of the present application above are only for description and do not represent the advantages or disadvantages of the embodiments.

[0121] In the embodiments of the present application, the vehicle speed is introduced into the model predictive control algorithm through the desired vehicle speed, so that the optimal pedal torque at the current moment determined can meet the requirement of stable vehicle speed, and the frequent shift speed regulation situation caused by too large a gap between the current vehicle speed and the vehicle speed corresponding to the optimal pedal torque is avoided, enabling the vehicle to move forward smoothly.

[0122] The present invention also provides a computer-readable medium, on which program instructions are stored, and when the program instructions are executed by a processor, the vehicle control method based on road information provided by each of the above method embodiments is implemented.

[0123] The present invention also provides a computer program product containing instructions, which when run on a computer, causes the computer to execute the vehicle control method based on road information of each of the above method embodiments.

[0124] Please refer to Figure 5 , which is a schematic structural diagram of a terminal provided by an embodiment of the present application. As Figure 5 shown, the terminal 1000 may include: at least one processor 1001, at least one network interface 1004, a user interface 1003, a memory 1005, and at least one communication bus 1002.

[0125] Among them, the communication bus 1002 is used to realize the connection and communication between these components.

[0126] Among them, the user interface 1003 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 1003 may further include a standard wired interface and a wireless interface.

[0127] Among them, the network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0128] Among them, the processor 1001 may include one or more processing cores. The processor 1001 connects various parts within the entire terminal 1000 through various interfaces and circuits. By running or executing instructions, programs, code sets, or instruction sets stored in the memory 1005, and by invoking data stored in the memory 1005, it executes various functions of the terminal 1000 and processes data. Optionally, the processor 1001 may be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 1001 may integrate a combination of one or several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem, etc. Among them, the CPU mainly processes the operating system, user interface, application programs, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communication. It can be understood that the above-mentioned modem may not be integrated into the processor 1001 and may be implemented separately by a single chip.

[0129] Among them, the memory 1005 may include random access memory (RAM) and may also include read-only memory. Optionally, the memory 1005 includes a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 1005 may include a program storage area and a data storage area. Among them, the program storage area can store instructions for implementing the operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area can store the data involved in the above-mentioned various method embodiments. Optionally, the memory 1005 may also be at least one storage device located far from the aforementioned processor 1001. As Figure 5 shown, the memory 1005, as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a vehicle control application program based on road information.

[0130] In Figure 5In the terminal 1000 shown, the user interface 1003 is mainly used to provide an interface for the user to input and obtain the data input by the user; and the processor 1001 can be used to call the vehicle control application program based on road information stored in the memory 1005 and specifically perform the following operations:

[0131] Obtain the road information and vehicle information in front of the vehicle;

[0132] Determine the desired vehicle speed within the prediction horizon according to the vehicle information;

[0133] Based on the road information, the vehicle information, and the desired vehicle speed, determine the optimal pedal torque at the current moment based on the model predictive control algorithm, and control the vehicle based on the optimal pedal torque.

[0134] In one embodiment, the desired vehicle speed within the prediction horizon is determined according to the following formula:

[0135] v(k+i) = i*(v(k)-v(k-h)) / h + v(k)

[0136] where v(k) is the vehicle speed at time k, v(k+i) is the desired vehicle speed at time k+i, v(k-h) is the past vehicle speed at time k-h, i is a natural number, and h is the time period.

[0137] In one embodiment, the road information is obtained via the in-vehicle TBox module.

[0138] In one embodiment, when the processor 1001 executes to determine the optimal pedal torque at the current moment based on the road information, the vehicle information, and the desired vehicle speed based on the model predictive control algorithm, it specifically performs the following operations:

[0139] Construct an objective optimization function based on vehicle speed and fuel consumption;

[0140] Construct a state space equation based on the desired vehicle speed and vehicle torque;

[0141] According to the objective optimization function and the state space equation, determine the vehicle torque correction sequence through the model predictive control algorithm;

[0142] Determine the optimal pedal torque at the current moment according to the vehicle torque correction sequence.

[0143] In one embodiment, the objective optimization function is:

[0144]

[0145] where minz is the objective optimization function and z is its function substitute, is the sequence form of the torque correction amount, W r is the vehicle speed tracking coefficient, m f (v(k), T e (k)) is the correction term of the minimum fuel consumption rate curve based on vehicle speed and torque, Γ u is the torque fluctuation suppression coefficient, v(k) is the vehicle speed at time k, is its vector form, is the desired vehicle speed at time k, T e is the vehicle torque, T0 is the current moment, N is the number of periods in the prediction period, and u(k) is the torque correction amount at time k.

[0146] In one embodiment, the state space equation is:

[0147]

[0148]

[0149] where v is the vehicle speed, T s is the time interval, η is the transmission efficiency, T e is the vehicle torque, is its first derivative, M is the vehicle weight, r is the tire radius, μ is the road surface friction coefficient, α is the road slope, C d is the air resistance coefficient, A f is the frontal area, ρ is the air density, I f is the main reduction ratio, I g is the transmission ratio of the gearbox, and g is the gravitational coefficient.

[0150] In one embodiment, when the processor 1001 executes to determine the optimal pedal torque at the current moment according to the vehicle torque correction sequence, the following operations are specifically performed:

[0151] Obtain the friction torque of the vehicle;

[0152] Calculate the optimal pedal torque according to the first element of the vehicle torque correction sequence and the friction torque.

[0153] In the embodiment of the present application, the vehicle speed is introduced into the model predictive control algorithm through the desired vehicle speed, so that the optimal pedal torque determined at the current moment can meet the requirement of stable vehicle speed, avoid the frequent gear shifting and speed regulation situation caused by the large gap between the current vehicle speed and the vehicle speed corresponding to the optimal pedal torque, and enable the vehicle to move forward smoothly.

[0154] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The program for vehicle control based on road information can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above various methods. The storage medium can be a magnetic disk, an optical disk, a read-only memory, or a random access memory, etc.

[0155] The above-disclosed are only the preferred embodiments of the present application. Of course, the scope of the rights of the present application cannot be limited thereby. Therefore, equivalent changes made according to the claims of the present application still fall within the scope covered by the present application.

Claims

1. A vehicle control method based on road information, characterized in that, The method includes: Obtaining road information and vehicle information in front of the vehicle; Determining the desired vehicle speed within the prediction horizon according to the vehicle information; Based on the road information, the vehicle information, and the desired vehicle speed, determining the optimal pedal torque at the current moment based on the model predictive control algorithm, and controlling the vehicle based on the optimal pedal torque; The determining the optimal pedal torque at the current moment based on the road information, the vehicle information, and the desired vehicle speed, based on the model predictive control algorithm, includes: Constructing an objective optimization function based on vehicle speed and fuel consumption; Constructing a state space equation based on the desired vehicle speed and vehicle torque; According to the objective optimization function and the state space equation, determining a vehicle torque correction sequence through the model predictive control algorithm; Determining the optimal pedal torque at the current moment according to the vehicle torque correction sequence; The objective optimization function is: Among them, minz is the target optimization function, and z is the function reference. is the sequence form of the torque correction amount, W r is the vehicle speed tracking coefficient, m f (v(k), T e (k)) is the correction term of the minimum fuel consumption rate curve based on vehicle speed and torque, Γ u is the torque fluctuation suppression coefficient, v(k) is the vehicle speed at time k, is its vector form, is the desired vehicle speed at time k, T e is the vehicle torque, T0 is the current time, N is the number of periods in the prediction period, and u(k) is the torque correction amount at time k.

2. The method according to claim 1, wherein The desired vehicle speed within the prediction horizon is determined according to the following formula: v(k+i) = i*(v(k) - v(k-h)) / h + v(k) where v(k) is the vehicle speed at time k of the vehicle, v(k+i) is the desired vehicle speed at time k+i of the vehicle, v(k-h) is the past vehicle speed at time k-h of the vehicle, i is a natural number, and h is a time period.

3. The method according to claim 1, wherein The road information is obtained via the in-vehicle TBox module.

4. The method according to claim 1, wherein The state space equation is: Among them, v is the vehicle speed, T s is the time interval, η is the transmission efficiency, T e is the vehicle torque, is its first derivative, M is the vehicle weight, r is the tire radius, μ is the road surface friction coefficient, α is the road slope, C d is the air resistance coefficient, A f is the frontal area, ρ is the air density, I f is the final drive ratio, I g is the transmission ratio of the gearbox, g is the gravity coefficient.

5. The method according to claim 1, characterized in that The determining the optimal pedal torque at the current moment according to the vehicle torque correction sequence includes: Obtaining the friction torque of the vehicle; Calculating the optimal pedal torque according to the first element of the vehicle torque correction sequence and the friction torque.

6. A vehicle control device based on road information, characterized in that, The device includes: An acquisition module, which is used to obtain road information and vehicle information in front of the vehicle; A prediction module, which is used to determine the desired vehicle speed within the prediction horizon according to the vehicle information; A control module, which is used to determine the optimal pedal torque at the current moment based on the road information, the vehicle information, and the desired vehicle speed, based on the model predictive control algorithm, and control the vehicle based on the optimal pedal torque; The control module is further used to execute the determining the optimal pedal torque at the current moment based on the road information, the vehicle information, and the desired vehicle speed, based on the model predictive control algorithm, in the following manner: Constructing an objective optimization function based on vehicle speed and fuel consumption; Constructing a state space equation based on the desired vehicle speed and vehicle torque; According to the objective optimization function and the state space equation, determining a vehicle torque correction sequence through the model predictive control algorithm; Determining the optimal pedal torque at the current moment according to the vehicle torque correction sequence; The objective optimization function is: Among them, minz is the target optimization function, and z is the function reference. is the sequence form of the torque correction amount, W r is the vehicle speed tracking coefficient, m f (v(k), T e (k)) is the correction term of the minimum fuel consumption rate curve based on vehicle speed and torque, Γ u is the torque fluctuation suppression coefficient, v(k) is the vehicle speed at time k, is its vector form, is the desired vehicle speed at time k, T e is the vehicle torque, T0 is the current time, N is the number of periods in the prediction period, and u(k) is the torque correction amount at time k.

7. A computer storage medium, characterized in that, The computer storage medium stores multiple instructions, and the instructions are suitable for being loaded and executed by a processor to perform the method steps of any one of claims 1-5.

8. A terminal, characterized in that, Including: A processor and a memory; wherein, the memory stores a computer program, and the computer program is suitable for being loaded and executed by the processor to perform the method steps of any one of claims 1-5.

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