Multi-actuator full-vector control method and related equipment

Abstract

The invention discloses a multi-actuator full-vector control method and related equipment, and the method comprises the steps: obtaining vehicle motion state information and road adhesion information, the vehicle motion state information is obtained based on a vehicle-mounted sensor and / or a vehicle state estimation module, and the road adhesion information is obtained based on a road identification module; acquiring steering wheel angle information based on the vehicle motion state information to determine an expected yaw velocity tracking sequence; upper-layer control information is determined based on the vehicle motion state information, the road surface attachment information and the expected yaw velocity tracking sequence, and the upper-layer control information comprises an additional yaw moment, an additional roll moment, an additional pitch moment and a rear wheel steering angle; and lower-layer control information is determined based on the vehicle motion state information, the road surface attachment information and the upper-layer control information, the lower-layer control information is used for deploying a vehicle actuator, and the lower-layer control information comprises additional driving torque and suspension active force.

Description

Technical Field

[0001] The present invention relates to the field of driving control technology, and in particular to a multi-actuator full vector control method and related equipment. Background Art

[0002] During driving, vehicles are affected by acceleration, deceleration, lane changing, etc., and are prone to become unstable in many aspects, such as high lateral speed, excessive pitch angle and roll angle, and uncontrolled yaw rate. In order to reduce the instability of vehicle driving, there are many designs to ensure that the vehicle runs in a reasonable motion state and control the stability of the vehicle.

[0003] However, most of these solutions are passive solutions with poor adaptability to real-time road conditions, and the coupling between the various actuators is also low. Summary of the invention

[0004] In view of the above problems, the present invention provides a multi-actuator full vector control method and related equipment, the main purpose of which is to improve the coupling between the actuators and improve the operating efficiency.

[0005] In order to solve at least one of the above technical problems, in a first aspect, the present invention provides a multi-actuator full vector control method, the method comprising: Acquire vehicle motion state information and road adhesion information, wherein the vehicle motion state information is acquired based on a vehicle-mounted sensor and / or a vehicle state estimation module, and the road adhesion information is acquired based on a road recognition module; Acquire steering wheel angle information based on vehicle motion state information to determine a desired yaw rate tracking sequence; Determining upper-level control information based on vehicle motion state information, road adhesion information, and a desired yaw rate tracking sequence, wherein the upper-level control information includes an additional yaw moment, an additional roll moment, an additional pitch moment, and a rear wheel steering angle; The lower-level control information is determined based on the vehicle motion state information, the road adhesion information, and the upper-level control information, wherein the lower-level control information is used to deploy the vehicle actuator, and the lower-level control information includes the additional driving torque and the main suspension force.

[0006] Optionally, obtaining steering wheel angle information based on vehicle motion state information to determine a desired yaw rate tracking sequence includes: determining a desired front wheel steering angle based on the variable transmission ratio and the steering wheel angle information; Determining a desired yaw rate based on a desired front wheel turning angle and a second-order reference model; defining an upper limit value of a desired yaw rate based on road adhesion information; A desired yaw rate tracking sequence is determined based on the desired yaw rate and an upper limit value of the desired yaw rate.

[0007] Optionally, the above method further includes: Determine the side slip angles of the front and rear wheels of the vehicle based on the vehicle motion state information; Determine the tire stress based on the vehicle's front and rear wheel slip angles, tire model, road adhesion information, vertical load, and tire cornering stiffness; Determine the nonlinear dynamic equation based on the tire force, the actuator state vector and the input vector combined with the vehicle six-degree-of-freedom model; Determining items to be optimized based on a desired yaw rate tracking sequence, a roll angle suppression, a pitch angle suppression, and a lateral velocity suppression; Determine the control quantity constraints of the actuation energy; Define the objective function based on the item to be optimized and the control quantity constraints; The incremental model is determined based on the Taylor expansion at the working point of the vehicle's six-degree-of-freedom dynamic model and by ignoring high-order terms: in, The nonlinear dynamic equations at the working point are The Jacobian matrix at .

[0008] Optionally, the upper-level control information is determined based on the vehicle motion state information, the road adhesion information, and the expected yaw rate tracking sequence, including: Euler discretization of the incremental model to obtain the prediction horizon The prediction equation inside: in, Represents the state prediction value in the entire prediction time domain, Represents the control quantity increment in the entire prediction time domain, , and is the corresponding matrix; Determine an observation matrix in the prediction time domain based on the observation vector, wherein the observation matrix is ​​used to calculate the observation variables, and the observation variables are used to calculate the objective function; Constructing an objective function based on tracking expected observations and suppressing control quantities; The six-degree-of-freedom dynamics model is converted into the standard form of QP problem based on the quadratic term matrix and the linear term matrix; Solve the QP problem to determine the additional yaw moment, additional roll moment, additional pitch moment and rear wheel steering angle.

[0009] Optionally, the above method further includes: Determine the force equation during tire rotation: Among them, the state variable of the tire rotation system is the tire speed The moment of inertia of the tire is , the effective rolling radius of the tire is The longitudinal force on the tire is The total torque acting on the tire is ; determining a tire slip ratio based on the longitudinal velocities of the four tires; Determine a desired wheel speed of the tire based on a vector sum of the vehicle center of mass velocity and an actual yaw rate generated at the tire, wherein the desired wheel speed is used to construct an objective function for driving torque distribution of the actuator; Determining a composite brush model based on the total tire force, the composite tire slip and the composite slip threshold, wherein the composite tire slip includes a longitudinal slip and a lateral slip; The tire force data is determined based on the tire rotation force equation, tire slip rate and composite brush model.

[0010] Optionally, determining the lower-layer control information based on the vehicle motion state information, the road adhesion information, and the upper-layer control information includes: The objective function for distributing the actuator's driving torque is determined based on tire force data, reducing additional torque energy consumption, additional yaw torque, and desired wheel speed: in, , and are the weights of the corresponding items, and are the lower and upper bounds of the control volume, respectively. and are the lower and upper bounds of the slip rate, , , ; The objective function of the actuator's driving torque distribution is solved to determine the additional driving torque.

[0011] Optionally, determining the lower-layer control information based on the vehicle motion state information, the road adhesion information, and the upper-layer control information includes: Determine the expression for the sprung mass of the suspension and the state and control vectors of the suspension actuator; Determine the additional rolling moment and the additional pitching moment; Determine the objective function of the suspension actuator based on the expression of the suspension sprung mass, the state vector and control vector of the suspension actuator, the additional roll moment and the additional pitch moment; The objective function of the suspension actuator is solved to determine the suspension active force.

[0012] In a second aspect, an embodiment of the present invention further provides a multi-actuator full vector control device, comprising: A first acquisition unit, used to acquire vehicle motion state information and road adhesion information, wherein the vehicle motion state information is acquired based on a vehicle-mounted sensor and / or a vehicle state estimation module, and the road adhesion information is acquired based on a road recognition module; a second acquisition unit, configured to acquire steering wheel angle information based on the vehicle motion state information to determine a desired yaw angular velocity tracking sequence; a first determining unit, configured to determine upper-level control information based on vehicle motion state information, road adhesion information, and a desired yaw rate tracking sequence, wherein the upper-level control information includes an additional yaw moment, an additional roll moment, an additional pitch moment, and a rear wheel steering angle; The second determination unit is used to determine lower-level control information based on vehicle motion state information, road adhesion information, and upper-level control information, wherein the lower-level control information is used to allocate vehicle actuators, and the lower-level control information includes additional driving torque and suspension active force.

[0013] In order to achieve the above-mentioned purpose, according to the third aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored program, wherein when the above-mentioned program is executed by a processor, the steps of the above-mentioned multi-actuator full vector control method are implemented.

[0014] In order to achieve the above-mentioned purpose, according to the fourth aspect of the present invention, there is provided an electronic device, comprising at least one processor and at least one memory connected to the processor; wherein the above-mentioned processor is used to call the program instructions in the above-mentioned memory to execute the steps of the above-mentioned multi-actuator full vector control method.

[0015] By means of the above technical scheme, the multi-actuator full vector control method and related equipment provided by the present invention solve the problem that the coupling between the actuators is low and there is a lack of a better method for implementing the deployment. The present invention obtains vehicle motion state information and road adhesion information, wherein the vehicle motion state information is obtained based on the vehicle-mounted sensor and / or the vehicle state estimation module, and the road adhesion information is obtained based on the road recognition module; based on the vehicle motion state information, the steering wheel angle information is obtained to determine the expected yaw rate tracking sequence; based on the vehicle motion state information, the road adhesion information and the expected yaw rate tracking sequence, the upper-level control information is determined, wherein the upper-level control information includes an additional yaw moment, an additional roll moment, an additional pitch moment and a rear wheel steering angle; based on the vehicle motion state information, the road adhesion information and the upper-level control information, the lower-level control information is determined, wherein the lower-level control information is used to deploy the vehicle actuator, and the lower-level control information includes an additional driving torque and a suspension active force. In the above scheme, through active solutions, the power situation is adjusted in real time according to the different power system conditions during vehicle driving, which can adapt to more common driving conditions, and taking into account the coupling between various systems, multiple actuators are coordinated to control and optimize the stability of the vehicle. This application optimizes the stability and smoothness of the vehicle in the three directions of lateral, longitudinal and vertical directions by adjusting the vehicle's rear wheel turning angle, the additional torque of the four tires, the main force of the suspension and other actuators, thereby improving the safety and comfort of the vehicle during driving.

[0016] Correspondingly, the multi-actuator full-vector control device, equipment and computer-readable storage medium provided by the embodiments of the present invention also have the above-mentioned technical effects.

[0017] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1 A schematic flow chart of a multi-actuator full vector control method provided by an embodiment of the present invention is shown; Figure 2 A schematic diagram of the principle of a multi-actuator full vector parameter control process provided by an embodiment of the present invention is shown; Figure 3 A schematic diagram of full vector parameters of a vehicle multi-actuator provided by an embodiment of the present invention is shown; Figure 4 Another schematic diagram of full vector parameters of multiple actuators of a vehicle provided by an embodiment of the present invention is shown; Figure 5 A schematic block diagram showing the composition of a multi-actuator full vector control device provided by an embodiment of the present invention is shown; Figure 6 A schematic block diagram of the composition of a multi-actuator full vector control electronic device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0019] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to enable the scope of the present invention to be fully communicated to those skilled in the art.

[0020] In order to solve the problem that the coupling between the actuators is low and there is a lack of a better method for implementing the deployment, an embodiment of the present invention provides a multi-actuator full vector control method, such as Figure 1-2 As shown, the method includes: S101, obtaining vehicle motion state information and road adhesion information, wherein the vehicle motion state information is obtained based on a vehicle-mounted sensor and / or a vehicle state estimation module, and the road adhesion information is obtained based on a road surface recognition module; Exemplarily, the vehicle motion state includes but is not limited to stationary state, starting state, driving state, deceleration state, braking state, reversing state, emergency braking state, bumping state, drifting state and rollover state. The road adhesion information is the ratio of adhesion to wheel normal (direction perpendicular to the road surface) pressure. It is determined by the road surface and tires. The larger this coefficient is, the greater the available adhesion is, and the less likely the car is to slip. The road adhesion information will be affected by rain and snow.

[0021] S102, acquiring steering wheel angle information based on the vehicle motion state information to determine a desired yaw rate tracking sequence; Exemplarily, the present application establishes an original control target, i.e., steering wheel angle information, based on vehicle driving requirements input by a user, such as improving vehicle maneuverability and vehicle stability, and generates a desired yaw rate tracking sequence for a torque vectoring actuator.

[0022] S103, determining upper-level control information based on the vehicle motion state information, the road adhesion information and the desired yaw rate tracking sequence, wherein the upper-level control information includes an additional yaw moment, an additional roll moment, an additional pitch moment and a rear wheel steering angle; Exemplarily, the present application optimizes the overall control torque and rear-wheel steering angle of the vehicle based on the vehicle's current vehicle motion state information, road adhesion information and the desired yaw rate tracking sequence, to obtain a control torque and rear-wheel steering angle that can meet the vehicle's maneuverability, stability and comfort goals, and sends the desired control torque and rear-wheel steering angle to the lower-level actuator as reference inputs of the lower-level actuator.

[0023] It can be understood that the expected yaw rate tracking sequence is determined based on the expected state information generated by the expected reference value module and the control demand analysis information generated by the control demand analysis module.

[0024] S104. Determine lower-level control information based on the vehicle motion state information, the road adhesion information, and the upper-level control information, wherein the lower-level control information is used to deploy vehicle actuators, and the lower-level control information includes additional driving torque and suspension active force.

[0025] Exemplarily, the present application takes into account the coupling relationship between various actuators of the vehicle and the system constraints, and comprehensively coordinates the control quantities of actuators such as drive, steering, and suspension to achieve coordinated longitudinal and lateral vertical control of the vehicle based on the current driving state of the vehicle and the desired control input generated by the upper-level actuator, including additional yaw moment, additional roll moment, additional pitch moment, and rear wheel steering angle.

[0026] Therefore, the longitudinal and lateral vertical coordinated stability control of the vehicle is achieved by adjusting the additional torque of the four wheels of the distributed drive vehicle and the active suspension control amount.

[0027] In summary, the present application is used for the longitudinal, lateral and vertical coordinated stability control of distributed drive vehicles. By receiving the vehicle motion state information collected from the vehicle-mounted sensors and output by the vehicle state estimation module and the road adhesion information from the road surface identification module, the coordinated motion control strategy inside the module is optimized and calculated, and finally the control quantities of multiple actuators such as drive, steering, and suspension are output to adjust the vehicle motion posture under different working conditions to ensure stable driving of the vehicle. The present application adjusts the power situation in real time according to the different power system conditions during vehicle driving. It can adapt to more common driving conditions, and considering the coupling between various systems, multiple actuators are coordinated to control and optimize the stability of the vehicle. The present application optimizes the stability and smoothness of the vehicle in the three directions of lateral, longitudinal and vertical by adjusting the rear wheel turning angle of the vehicle, the additional torque of the four tires, the main power of the suspension and other actuators, thereby improving the safety and comfort of vehicle driving.

[0028] In one embodiment, acquiring steering wheel angle information based on the vehicle motion state information to determine a desired yaw rate tracking sequence includes: determining a desired front wheel steering angle based on the variable transmission ratio and the steering wheel angle information; Determining a desired yaw rate based on the desired front wheel turning angle and a second-order reference model; defining an upper limit value of a desired yaw rate based on the road adhesion information; The desired yaw rate tracking sequence is determined based on the desired yaw rate and an upper limit value of the desired yaw rate.

[0029] Specifically, assume that the variable transmission ratio of the external input is , then according to the steering wheel angle information input by the driver The corresponding expected front wheel turning angle can be calculated as :

[0030] Since the driver is manipulating the steering wheel, the expected yaw rate of the vehicle during driving is Desired front wheel turning angle Calculated.

[0031] In the reference model, a second-order reference model is used to calculate the desired front wheel turning angle according to the current And the corresponding transfer function to calculate the desired yaw rate:

[0032] in, is the steady-state gain value of yaw angular velocity, is the yaw rate differential coefficient, is the oscillation frequency, is the damping coefficient.

[0033] When the road adhesion coefficient is low, the maximum tire force that the tire can generate is not enough to support the required large yaw rate. The upper limit of the desired yaw rate is defined as:

[0034] in, is the road adhesion coefficient, is the acceleration due to gravity, is the longitudinal velocity of the vehicle.

[0035] Reference value of yaw rate due:

[0036] Based on the above scheme, the present application establishes original control targets according to vehicle driving requirements, such as improving vehicle maneuverability and vehicle stability, establishes a mapping of desired control targets to desired yaw rate based on the vehicle's six-degree-of-freedom dynamics model, and generates a desired yaw rate tracking sequence for the torque vector actuator.

[0037] In one embodiment, the method further includes: Determining the sideslip angles of the front and rear wheels of the vehicle based on the vehicle motion state information; Determining tire stress conditions based on the side slip angles of the front and rear wheels of the vehicle, a tire model, road adhesion information, vertical loads, and tire cornering stiffness; Determine a nonlinear dynamic equation based on the tire force condition, the state vector and the input vector of the actuator in combination with the six-degree-of-freedom model of the vehicle; Determining an item to be optimized based on the desired yaw rate tracking sequence, roll angle suppression, pitch angle suppression, and lateral velocity suppression; Determine the control quantity constraints of the actuation energy; Defining an objective function based on the item to be optimized and the control amount constraint; The incremental model is determined based on the Taylor expansion at the working point of the vehicle's six-degree-of-freedom dynamic model and by ignoring high-order terms:

[0038] in, The nonlinear dynamic equations at the working point are The Jacobian matrix at .

[0039] It is understandable that the motion states of each degree of freedom of the vehicle are coupled to each other, so the present application establishes a high-order coupled vehicle dynamics equation based on the motion characteristics of the entire vehicle. The present invention uses a vehicle six-degree-of-freedom model to describe the lateral motion, yaw motion, pitch motion and roll motion of the vehicle. The vehicle state is predicted at the current working point. Within a very short period of time, the longitudinal speed of the vehicle can be considered to be approximately unchanged. At this time, the longitudinal speed of the vehicle is introduced into the vehicle's six-degree-of-freedom model as a variable parameter and is updated at each calculation to ensure a higher degree of accuracy. The formula for the vehicle's six-degree-of-freedom model is as follows, and the schematic diagram is shown in Figure 3 .

[0040]

[0041] in, is the distance from the sprung mass to the coordinate system, and is the angle of rotation of the vehicle around the x-axis and y-axis, It represents the lateral force of the left front wheel, right front wheel, left rear wheel and right rear wheel respectively. and Respectively represent the distances from the front and rear axles to the center of mass of the vehicle, is the mass of the vehicle, is the sprung mass of the vehicle, Is the vehicle around The moment of inertia of the shaft rotation, represents the longitudinal velocity, represents the lateral speed, represents the yaw angular velocity, Indicates the front wheel turning angle, Indicates the left and right wheelbase, are the additional torques on the x-axis, y-axis and z-axis respectively.

[0042] remember is the rear wheel turning angle, the sideslip angles of the front and rear axles can be calculated as follows: The lateral force of the tire is described by the Fiala tire model. When I was very young, , then the tire model can be approximated as: in is the tire cornering force, is the tire slip angle, is the road adhesion coefficient, is the vertical load, the tire cornering stiffness Front wheel cornering stiffness and rear wheel cornering stiffness .

[0043] This determines the stress conditions on the tire.

[0044] For actuator design, its state vector is defined as: Its control input vector is defined as: Combined with the six-degree-of-freedom dynamics model of the vehicle, the nonlinear dynamics equation of the vehicle can be obtained as follows: In predictive control, it is necessary to define an objective function to describe the optimization problem. Taking into account the vehicle's yaw rate tracking, roll angle suppression, pitch angle suppression, and lateral velocity suppression, the target item to be optimized can be defined as: in, , , and They are respectively the reference value of the yaw angular velocity, the reference value of the roll angle, the reference value of the pitch angle and the reference value of the lateral velocity.

[0045] In addition, the actuation energy of the control quantity must be constrained: The actuator has a limited range of motion, and the control quantity itself needs to be constrained: in, and are the lower and upper bounds of the control volume respectively.

[0046] Combining the above-mentioned items to be optimized and the corresponding control quantity constraints, the objective function of the upper actuator can be defined as: in, , , , , , , and are the weights of the corresponding items respectively.

[0047] This optimization problem is a nonlinear optimization problem, which can be solved using the interior point method or sequential quadratic programming method. Since this problem is a highly coupled and highly nonlinear optimization problem, if the traditional interior point method or sequential quadratic programming method is used to solve it, it will take up a lot of computing resources and it is difficult to solve it in real time. In order to solve this problem, the original optimization problem is transformed and solved. Assume that its current working point is , Taylor expansion of the above nonlinear model at its working point and ignoring the higher-order terms can obtain the following incremental model: in, The nonlinear system equations are respectively The Jacobian matrix at .

[0048] In one embodiment, the determining the upper-level control information based on the vehicle motion state information, the road adhesion information and the expected yaw rate tracking sequence includes: The incremental model is subjected to Euler discretization to obtain the prediction time domain The prediction equation inside: in, Represents the state prediction value in the entire prediction time domain, Represents the control quantity increment in the entire prediction time domain, , and is the corresponding matrix; Determining an observation matrix in a prediction time domain based on the observation vector, wherein the observation matrix is ​​used to calculate observation variables, and the observation variables are used to calculate an objective function; Constructing the objective function based on tracking expected observations and suppressing control amounts; The six-degree-of-freedom dynamics model is converted into a standard form of a QP problem based on a quadratic term matrix and a linear term matrix; The QP problem is solved to determine the additional yaw moment, the additional roll moment, the additional pitch moment and the rear wheel steering angle.

[0049] Specifically, the present application converts the above equation into a sampling time By performing Euler discretization, the prediction time domain can be obtained The prediction equation is: in, Represents the state prediction value in the entire prediction time domain, Represents the control quantity increment in the entire prediction time domain, , and is the corresponding matrix.

[0050] set up is the observation matrix, then the observation vector in the prediction time domain is: Assume that the expected observation value to be tracked is , the objective function The first term is the expected observation value of tracking, and the second term is the size of the inhibitory control amount: Among them and are the expected value tracking weight matrix and the control amount weight matrix respectively, and are the lower and upper bounds of the observation vector, respectively. and are the lower and upper bounds of the control volume respectively.

[0051] For the standard form of the QP problem: The quadratic matrix can be obtained and the linear term matrix The separable table can be expressed as: in, is the reference value matrix, .

[0052] For the system constraints, the upper and lower limits of the control quantity are defined as follows: and , then the upper and lower limits of the control quantity in the entire prediction time domain are: The MPC problem can then be solved using QP to determine the additional yaw moment, additional roll moment, additional pitch moment, and rear wheel steering angle.

[0053] In one embodiment, the method further comprises: Determine the force equation during tire rotation: Among them, the state variable of the tire rotation system is the tire speed The moment of inertia of the tire is , the effective rolling radius of the tire is The longitudinal force on the tire is The total torque acting on the tire is ; determining a tire slip ratio based on the longitudinal velocities of the four tires; A desired wheel speed of the tire based on the vehicle center of mass velocity and a vector sum of the actual yaw rate generated at the tire, wherein the desired wheel speed is used to construct an objective function for driving torque distribution of the actuator; Determining a composite brush model based on the total tire force, the composite tire slip and the composite slip threshold, wherein the composite tire slip includes a longitudinal slip and a lateral slip; The tire force data is determined based on the tire rotation process force equation, the tire slip rate and the composite brush model.

[0054] The lower-level actuator is mainly responsible for coordinating the control quantities of multiple actuators such as drive, steering, and suspension to achieve coordinated control of the longitudinal and lateral vertical directions of the vehicle. The force applied to the tire during rotation is: Among them, the state variable of the tire rotation system is the tire speed The moment of inertia of the tire is , the effective rolling radius of the tire is The longitudinal force on the tire is The total torque acting on the tire is .

[0055] The total torque on the tire is the torque desired by the driver. The additional torque calculated with the actuator The sum of Tire slip rate It can be calculated as follows: in, Represents the longitudinal speed of the four tires respectively.

[0056] Specifically, the speed at the center of the tire consists of two parts. The first part is the speed of the vehicle's center of mass, and the second part is the speed generated at the tire due to the yaw angular velocity. The speed at the center of the tire is the vector sum of these two parts, which can be calculated as follows.

[0057] Therefore, the expected wheel speed can be expressed as: This application introduces a composite brush tire model to calculate tire force to predict the future tire rotation state. The composite brush model can be expressed as: in, . , and They represent the total tire force, the tire composite slip, and the threshold of the composite slip. The tire composite slip can be calculated as follows: The longitudinal slip and lateral slip The calculation is as follows: The longitudinal force and lateral force of the tire are calculated as follows: The tire rotation equation is discretized and the sampling time is , we can get: The state vector of the system is defined as , define the control vector as ,in Indicates the additional torque of the motor, represents the slack variable.

[0058] According to vehicle dynamics, the additional yaw moment generated by the differential torque is It can be expressed as: in .

[0059] In one embodiment, the determining the lower-layer control information based on the vehicle motion state information, the road adhesion information, and the upper-layer control information includes: The objective function for distributing the actuator's driving torque is determined based on tire force data, reducing additional torque energy consumption, additional yaw torque, and desired wheel speed: in, , and are the weights of the corresponding items, and are the lower and upper bounds of the control volume, respectively. and are the lower and upper bounds of the slip rate, , , ; An objective function for distributing the drive torque of the actuator is solved to determine the additional drive torque.

[0060] In the lower layer driving torque distribution actuator, it is necessary to simultaneously consider tracking the desired additional yaw torque output by the upper layer additional yaw torque actuator. and expected wheel speed , and reduce the energy consumption required to generate additional torque. Considering the constraints at the same time, the objective function in the lower-level driving torque distribution actuator is defined as: in, , and are the weights of the corresponding items, and are the lower and upper bounds of the control volume, respectively. and are the lower and upper bounds of the slip rate, , , .

[0061] The MPC problem can then be solved using QP to determine the additional driving torque.

[0062] In one embodiment, the determining the lower-layer control information based on the vehicle motion state information, the road adhesion information, and the upper-layer control information includes: Determine the expression for the sprung mass of the suspension and the state and control vectors of the suspension actuator; Determine the additional rolling moment and the additional pitching moment; Determine the objective function of the suspension actuator based on the expression of the suspension sprung mass, the state vector and control vector of the suspension actuator, the additional roll moment and the additional pitch moment; The objective function of the suspension actuator is solved to determine the suspension active force.

[0063] Assume that the sprung masses corresponding to the four suspensions are respectively, and the elastic stiffness coefficient of the suspension is , the damping coefficient of the suspension is , let the compression stroke of each suspension spring be expressed as , define the positive direction as downward compression and the negative direction as upward stretching. Figure 4 As shown, the main force of the suspension is defined as , the positive direction of the suspension force is upward, and negative downward. At this time, the equations corresponding to each sprung mass can be expressed as: Define the state vector of the suspension actuator and control vector They are: The additional roll moment and additional pitch moment generated by the active suspension force can be expressed as: in, .

[0064] In the suspension force actuator of the active suspension, it is necessary to consider tracking the additional roll moment and additional pitch moment generated by the upper actuator at the same time, and also consider the energy consumption required to generate the additional moment. Therefore, the objective function in the lower active suspension actuator is defined as: in, , and are the weights of the corresponding items, and are the lower and upper bounds of the control volume, respectively. and are the lower and upper bounds of the slip rate, respectively.

[0065] The MPC problem can then be solved using QP to determine the active suspension forces.

[0066] Based on the above scheme, by actively adjusting the rear wheel turning angle, tire additional torque, suspension main force and other mechanisms, the stability of the vehicle in the lateral, longitudinal and vertical directions during operation is improved, and the lateral speed, pitch angle and roll angle of the vehicle are kept as 0 as possible, while the yaw rate is kept close to the reference yaw rate value. The above full vector control technology can effectively ensure the stability of the vehicle, avoid the dangers of rollover, loss of control, etc., thereby improving the safety during driving. For drivers and passengers, reducing body shaking can also improve the comfort and convenience of driving and riding. In addition, the algorithm also optimizes energy consumption, which can improve energy efficiency and reduce vehicle wear.

[0067] Furthermore, as a response to the above Figure 1 In order to realize the method shown in the figure, the embodiment of the present invention also provides a multi-actuator full vector control device for the above Figure 1 The device embodiment corresponds to the aforementioned method embodiment. For ease of reading, this device embodiment will not repeat the details of the aforementioned method embodiment one by one, but it should be clear that the device in this embodiment can correspond to all the contents of the aforementioned method embodiment. Figure 5 As shown, the device includes: a first acquisition unit 21, a determination unit 22, a second acquisition unit 23 and a generation unit 24, wherein A first acquisition unit 21, used to acquire vehicle motion state information and road adhesion information, wherein the vehicle motion state information is acquired based on a vehicle-mounted sensor and / or a vehicle state estimation module, and the road adhesion information is acquired based on a road recognition module; A second acquisition unit 22, configured to acquire steering wheel angle information based on the vehicle motion state information to determine a desired yaw angular velocity tracking sequence; a first determining unit 23, configured to determine upper-level control information based on the vehicle motion state information, the road adhesion information and the desired yaw rate tracking sequence, wherein the upper-level control information includes an additional yaw moment, an additional roll moment, an additional pitch moment and a rear wheel steering angle; The second determination unit 24 is used to determine lower-level control information based on the vehicle motion state information, the road adhesion information, and the upper-level control information, wherein the lower-level control information is used to allocate vehicle actuators, and the lower-level control information includes additional driving torque and suspension active force.

[0068] The processor includes a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and a multi-actuator full vector control method is implemented by adjusting kernel parameters, which can solve the problem of low coupling between the actuators and lack of a better implementation method.

[0069] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored program, and when the program is executed by a processor, the multi-actuator full vector control method is implemented.

[0070] An embodiment of the present invention provides a processor, which is used to run a program, wherein the multi-actuator full vector control method is executed when the program is running.

[0071] An embodiment of the present invention provides an electronic device, the electronic device comprising at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the multi-actuator full vector control method as described above An embodiment of the present invention provides an electronic device 30, such as Figure 6 As shown, the electronic device includes at least one processor 301, and at least one memory 302 and a bus 303 connected to the processor; wherein the processor 301 and the memory 302 communicate with each other through the bus 303; the processor 301 is used to call the program instructions in the memory to execute the above-mentioned multi-actuator full vector control method.

[0072] The intelligent electronic devices in this article can be PCs, PADs, mobile phones, etc.

[0073] The present application also provides a computer program product, which, when executed on a process management electronic device, is suitable for executing a program initialized with the steps of the above-mentioned multi-actuator full vector control method.

[0074] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0075] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0076] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0077] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0078] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0079] The present application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device is caused to execute the following Figure 1 This corresponds to the flow of control of the memory in the embodiment.

[0080] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0081] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0082] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0083] 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 units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0084] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0085] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0086] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some of the technical features therein by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A multi-actuator full vector control method, characterized in that: include: Acquire vehicle motion state information and road adhesion information, wherein the vehicle motion state information is acquired based on a vehicle-mounted sensor and / or a vehicle state estimation module, and the road adhesion information is acquired based on a road recognition module; Based on the vehicle motion state information, obtaining steering wheel angle information to determine a desired yaw rate tracking sequence; Determining upper-level control information based on the vehicle motion state information, the road adhesion information and the desired yaw rate tracking sequence, wherein the upper-level control information includes an additional yaw moment, an additional roll moment, an additional pitch moment and a rear wheel steering angle; Based on the vehicle motion state information, the road adhesion information and the upper-level control information, lower-level control information is determined, wherein the lower-level control information is used to allocate vehicle actuators, and the lower-level control information includes additional driving torque and suspension active force.

2. The method according to claim 1, characterized in that The acquiring steering wheel angle information based on the vehicle motion state information to determine an expected yaw rate tracking sequence includes: determining a desired front wheel turning angle based on the variable transmission ratio and the steering wheel angle information; Determining a desired yaw rate based on the desired front wheel turning angle and a second-order reference model; defining an upper limit value of a desired yaw rate based on the road adhesion information; The desired yaw rate tracking sequence is determined based on the desired yaw rate and an upper limit value of the desired yaw rate.

3. The method according to claim 2, characterized in that Also includes: Based on the vehicle motion state information, determining the sideslip angles of the front and rear wheels of the vehicle; Determining tire stress conditions based on the side slip angles of the front and rear wheels of the vehicle, the tire model, road adhesion information, vertical load, and tire cornering stiffness; Determining a nonlinear dynamic equation based on the tire force condition, the state vector and the input vector of the actuator in combination with the six-degree-of-freedom model of the vehicle; Determining an item to be optimized based on the desired yaw rate tracking sequence, roll angle suppression, pitch angle suppression, and lateral velocity suppression; Determine the control quantity constraints of the actuation energy; Defining an objective function based on the item to be optimized and the control amount constraint; Based on the Taylor expansion at the working point of the vehicle's six-degree-of-freedom dynamic model and ignoring high-order terms, the incremental model is determined: in, The nonlinear dynamic equations at the working point are The Jacobian matrix at .

4. The method according to claim 3, characterized in that The determining of upper-level control information based on the vehicle motion state information, the road adhesion information and the expected yaw rate tracking sequence includes: The incremental model is subjected to Euler discretization to obtain the prediction time domain The prediction equation inside: in, Represents the state prediction value in the entire prediction time domain, Represents the control quantity increment in the entire prediction time domain, , and is the corresponding matrix; Determining an observation matrix in a prediction time domain based on the observation vector, wherein the observation matrix is ​​used to calculate observation variables, and the observation variables are used to calculate an objective function; Constructing the objective function based on tracking expected observations and suppressing control amounts; The six-degree-of-freedom dynamics model is converted into a standard form of a QP problem based on a quadratic term matrix and a linear term matrix; The QP problem is solved to determine the additional yaw moment, the additional roll moment, the additional pitch moment and the rear wheel steering angle.

5. The method according to claim 1, characterized in that Also includes: Determine the force equation during tire rotation: Among them, the state variable of the tire rotation system is the tire speed The moment of inertia of the tire is , the effective rolling radius of the tire is The longitudinal force on the tire is The total torque acting on the tire is ; determining a tire slip ratio based on the longitudinal velocities of the four tires; Determining a desired wheel speed of the tire based on a vector sum of the vehicle center of mass velocity and an actual yaw rate generated at the tire, wherein the desired wheel speed is used to construct an objective function for driving torque distribution of the actuator; Determining a composite brush model based on the total tire force, the composite tire slip and the composite slip threshold, wherein the composite tire slip includes a longitudinal slip and a lateral slip; The tire force data is determined based on the tire rotation process force equation, the tire slip rate and the composite brush model.

6. The method according to claim 5, characterized in that The determining of the lower-layer control information based on the vehicle motion state information, the road adhesion information and the upper-layer control information includes: Based on tire force data, reducing additional torque energy consumption, additional yaw torque and expected wheel speed, determine the objective function of actuator drive torque distribution: in, , and are the weights of the corresponding items, and are the lower and upper bounds of the control volume, respectively. and are the lower and upper bounds of the slip rate, , , ; An objective function of the drive torque distribution of the actuator is solved to determine the additional drive torque.

7. The method according to claim 1, characterized in that The determining of the lower-layer control information based on the vehicle motion state information, the road adhesion information and the upper-layer control information includes: Determine the expression for the sprung mass of the suspension and the state and control vectors of the suspension actuator; Determine the additional rolling moment and the additional pitching moment; Determine the objective function of the suspension actuator based on the expression of the suspension sprung mass and the state vector and control vector of the suspension actuator, the additional roll moment and the additional pitch moment; The objective function of the suspension actuator is solved to determine the active suspension force.

8. A multi-actuator full vector control device, characterized in that: Also includes: A first acquisition unit, configured to acquire vehicle motion state information and road adhesion information, wherein the vehicle motion state information is acquired based on a vehicle-mounted sensor and / or a vehicle state estimation module, and the road adhesion information is acquired based on a road recognition module; a second acquisition unit, configured to acquire steering wheel angle information based on the vehicle motion state information to determine a desired yaw angular velocity tracking sequence; a first determining unit, configured to determine upper-level control information based on the vehicle motion state information, the road adhesion information, and the desired yaw rate tracking sequence, wherein the upper-level control information includes an additional yaw moment, an additional roll moment, an additional pitch moment, and a rear wheel steering angle; The second determination unit is used to determine lower-level control information based on the vehicle motion state information, the road adhesion information and the upper-level control information, wherein the lower-level control information is used to allocate vehicle actuators, and the lower-level control information includes additional driving torque and suspension active force.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed by a processor, the steps of the multi-actuator full vector control method according to any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that: The electronic device includes at least one processor and at least one memory connected to the processor; wherein the processor is used to call program instructions in the memory to execute the steps of the multi-actuator full vector control method as described in any one of claims 1 to claim 7.

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