Safety cooperative control method and device of electric vehicle and electronic equipment

Abstract

The invention provides a safety cooperative control method and device for an electric vehicle and electronic equipment, and the method comprises the steps: building a vehicle dynamics model based on a two-degree-of-freedom bicycle model and a model building parameter of the electric vehicle; based on the vehicle dynamics model and the vehicle driving parameters, a reference trajectory generator is constructed, and based on the reference trajectory generator, a target reference trajectory under the limit steering working condition is generated; tracking the target reference trajectory based on a pre-designed upper yaw moment controller, and outputting a target yaw moment; distributing the target yawing moment to each wheel of the electric vehicle by adopting a self-adaptive control mechanism so as to obtain a target torque corresponding to each wheel; and sending the target torque of each wheel to an actuator of the electric vehicle to control the electric vehicle. According to the mode, when the vehicle is in a limit steering working condition, the anti-sideslip capacity and the driving stability of the vehicle can be remarkably improved, and the safety of passengers is guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of vehicle control technology, and in particular to a safety cooperative control method, device and electronic equipment for an electric vehicle. Background Art

[0002] With the widespread use of electric buses, their safety issues have attracted widespread attention. Electric buses are prone to dangerous situations such as skidding and rollover under extreme steering conditions, threatening the safety of passengers. Traditional vehicle stability control systems and direct yaw moment control systems are mostly based on differential braking, which achieve vehicle stability by controlling the braking torque of each wheel. They have problems such as slow response speed and high energy consumption. Existing vehicle stability control technologies, such as sliding mode control and linear quadratic regulation, are not yet mature enough for application in electric buses, especially when dealing with multi-degree-of-freedom systems and multivariable collaborative control. In summary, when the vehicle is in extreme steering conditions, the relevant technologies lack effective solutions in terms of the vehicle's anti-skid ability and driving stability, making it difficult to ensure passenger safety. Summary of the invention

[0003] The purpose of the present invention is to provide a safe cooperative control method, device and electronic equipment for an electric vehicle, which can improve the vehicle's anti-skid ability and driving stability when the vehicle is in an extreme steering condition and ensure the safety of passengers.

[0004] The present invention provides a safe collaborative control method for an electric vehicle, the method comprising: constructing a vehicle dynamics model of the electric vehicle based on a two-degree-of-freedom bicycle model and model construction parameters of the electric vehicle; wherein the model construction parameters include: mass distribution characteristics, tire characteristics and power system parameters of the electric vehicle; constructing a reference trajectory generator based on the vehicle dynamics model and vehicle driving parameters, so as to generate a target reference trajectory under extreme steering conditions based on the reference trajectory generator; tracking the target reference trajectory based on a pre-designed upper-layer yaw moment controller, and outputting a target yaw moment; using an adaptive control mechanism, distributing the target yaw moment to each wheel of the electric vehicle, so as to obtain a target torque corresponding to each wheel; and sending the target torque of each wheel to an actuator of the electric vehicle, so as to control the electric vehicle.

[0005] Furthermore, based on the two-degree-of-freedom bicycle model and the model construction parameters of the electric vehicle, the steps of constructing the vehicle dynamics model of the electric vehicle include: constructing the lateral dynamics model of the electric vehicle based on the two-degree-of-freedom bicycle model and the model construction parameters of the electric vehicle; determining the lateral force balance model and the torque balance model based on the lateral dynamics model; determining the lateral force model based on the preset lateral cornering stiffness, longitudinal cornering stiffness, and the sideslip angle of the tire; substituting the lateral force model into the lateral force balance model and the torque balance model to obtain the vehicle dynamics model of the electric vehicle.

[0006] Furthermore, the vehicle dynamics model is expressed as follows:

[0007]

[0008] Where β represents the sideslip angle of the center of mass; r represents the actual yaw rate; C f Indicates the lateral cornering stiffness of the front axle of the vehicle; C r represents the lateral cornering stiffness of the rear axle of the vehicle; m represents the vehicle mass; v represents the longitudinal speed of the vehicle; l r Indicates the distance from the vehicle's center of gravity to the rear axle; l f Indicates the distance from the vehicle's center of gravity to the front axle; I z represents the vehicle's moment of inertia; δ represents the steering angle; M z represents the target yaw moment;

[0009] in, and C f0 All are preset constants.

[0010] Furthermore, based on the reference trajectory generator, the step of generating a target reference trajectory under extreme steering conditions includes: generating a desired reference trajectory based on the vehicle dynamics model and the reference trajectory generator; and correcting the desired reference trajectory to obtain a target reference trajectory.

[0011] Furthermore, the expected reference trajectory is expressed as follows:

[0012]

[0013] Among them, r des represents the desired yaw rate; v represents the longitudinal velocity of the vehicle; L represents the wheelbase of the vehicle; K us represents the understeering coefficient of the vehicle; δ represents the steering angle; μ represents the friction coefficient; and g represents the acceleration due to gravity.

[0014] Furthermore, the target reference trajectory is expressed as follows:

[0015]

[0016] Among them, r ref represents the target yaw rate; r represents the actual yaw rate; r des represents the desired yaw angular velocity; ∧ represents the “and” relationship; sign is the sign function.

[0017] Furthermore, the target yaw moment is expressed as follows:

[0018]

[0019] Among them, M z represents the target yaw moment; K p represents the proportional gain of the upper yaw moment controller; K i represents the integral gain of the upper yaw torque controller; K d represents the differential gain of the upper yaw moment controller; r ref represents the target yaw rate; r represents the actual yaw rate.

[0020] Furthermore, an adaptive control mechanism is used to distribute the target yaw moment to each wheel of the electric vehicle to obtain a target torque corresponding to each wheel, the steps including: determining a relationship model between wheel torque and yaw moment based on a vehicle dynamics model; constructing an objective function based on the relationship model, solving the objective function, and obtaining a target torque corresponding to each wheel.

[0021] The present invention provides a safety cooperative control device for an electric vehicle, which includes: a first construction module, used to construct a vehicle dynamics model of the electric vehicle based on a two-degree-of-freedom bicycle model and model construction parameters of the electric vehicle; wherein the model construction parameters include: mass distribution characteristics, tire characteristics and power system parameters of the electric vehicle; a second construction module, used to construct a reference trajectory generator based on the vehicle dynamics model and vehicle driving parameters, so as to generate a target reference trajectory under extreme steering conditions based on the reference trajectory generator; an output module, used to track the target reference trajectory based on a pre-designed upper-level yaw moment controller, and output a target yaw moment; a distribution module, used to adopt an adaptive control mechanism to distribute the target yaw moment to each wheel of the electric vehicle, so as to obtain a target torque corresponding to each wheel; and a sending module, used to send the target torque of each wheel to the actuator of the electric vehicle, so as to control the electric vehicle.

[0022] An electronic device provided by the present invention includes a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement any of the above-mentioned safety collaborative control methods for electric vehicles.

[0023] The safety cooperative control method, device and electronic device of the electric vehicle provided by the present invention construct a vehicle dynamics model of the electric vehicle based on a two-degree-of-freedom bicycle model and model construction parameters of the electric vehicle; wherein the model construction parameters include: mass distribution characteristics, tire characteristics and power system parameters of the electric vehicle; based on the vehicle dynamics model and vehicle driving parameters, a reference trajectory generator is constructed to generate a target reference trajectory under extreme steering conditions based on the reference trajectory generator; based on a pre-designed upper-layer yaw moment controller, the target reference trajectory is tracked and the target yaw moment is output; an adaptive control mechanism is used to distribute the target yaw moment to each wheel of the electric vehicle to obtain the target torque corresponding to each wheel; the target torque of each wheel is sent to the actuator of the electric vehicle to control the electric vehicle. This method can significantly improve the vehicle's anti-skid ability and driving stability when the vehicle is in extreme steering conditions, thereby ensuring the safety of passengers. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 A flowchart of a safety cooperative control method for an electric vehicle provided by an embodiment of the present invention;

[0026] Figure 2 A schematic diagram of a control structure provided by an embodiment of the present invention;

[0027] Figure 3 A schematic diagram of the structure of a safety cooperative control device for an electric vehicle provided by an embodiment of the present invention;

[0028] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0029] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] At present, the traditional vehicle stability control system and direct yaw moment control system play an important role in improving vehicle stability, but there are problems of slow response speed and high energy consumption; existing vehicle stability control technologies, such as sliding mode control, linear quadratic regulation, etc., perform well in dealing with complex nonlinear dynamic systems, but their application in electric buses is not yet mature enough; therefore, when the vehicle is in extreme steering conditions, the relevant technology lacks effective solutions in terms of the vehicle's anti-skid ability and driving stability, making it difficult to ensure passenger safety. Based on this, an embodiment of the present invention provides a safety collaborative control method, device and electronic equipment for an electric vehicle, which can be applied to the active safety control of electric vehicles.

[0031] To facilitate understanding of this embodiment, firstly, a safety cooperative control method for an electric vehicle disclosed in an embodiment of the present invention is introduced. Figure 1 As shown, the method comprises the following steps:

[0032] Step S102, constructing a vehicle dynamics model of the electric vehicle based on the two-degree-of-freedom bicycle model and the model construction parameters of the electric vehicle; wherein the model construction parameters include: mass distribution characteristics, tire characteristics and power system parameters of the electric vehicle;

[0033] The above two-degree-of-freedom bicycle model refers to a model that simplifies a complex vehicle into only two degrees of freedom: lateral motion in the y direction and yaw motion around the z axis. This model ignores longitudinal motion and the pitch, roll and other motions of the vehicle when analyzing vehicle motion, and mainly focuses on the lateral motion and yaw motion of the vehicle; the above mass distribution characteristics can be understood as the mass distribution of different parts of the electric vehicle (such as the body, bogie, etc.); the above tire characteristics can include: tire lateral characteristics, rolling resistance, grip and stiffness, etc.; the above power system parameters can include: maximum power, maximum torque, maximum torque speed and other parameters; in actual implementation, a vehicle dynamics model based on the two-degree-of-freedom bicycle model can be established. Since the characteristics of different electric vehicles are usually different, the vehicle dynamics model takes into account the model construction parameters such as the mass distribution characteristics, tire characteristics and power system parameters of the electric vehicle to ensure the accuracy of the constructed vehicle dynamics model.

[0034] Step S104, constructing a reference trajectory generator based on the vehicle dynamics model and the vehicle driving parameters, so as to generate a target reference trajectory under an extreme steering condition based on the reference trajectory generator;

[0035] The above-mentioned vehicle driving parameters may include: the current speed, steering angle and road friction coefficient of the electric vehicle, etc.; the above-mentioned reference trajectory generator is a technology for generating the motion trajectory of a vehicle under a specific environment; the above-mentioned extreme steering condition refers to a driving condition in which the vehicle movement approaches or reaches the dynamic limit due to emergencies, harsh environments and extreme road conditions during the driving process; in actual implementation, a reference trajectory generator can be designed based on the above-mentioned vehicle dynamics model and combined with the vehicle driving parameters. The reference trajectory generator is used to generate a target reference trajectory of the electric vehicle when it is about to become unstable under extreme steering conditions. The target reference trajectory is an ideal trajectory that can ensure the safety and stability of the electric vehicle.

[0036] Step S106, tracking the target reference trajectory based on the pre-designed upper layer yaw moment controller, and outputting the target yaw moment;

[0037] The upper yaw moment controller is a control strategy based on a linear quadratic regulator algorithm, which is mainly used for active safety performance control of vehicles. In actual implementation, the pre-designed upper yaw moment controller can track the target reference trajectory to output the ideal target yaw moment.

[0038] Step S108, using an adaptive control mechanism to distribute the target yaw moment to each wheel of the electric vehicle to obtain a target torque corresponding to each wheel;

[0039] In this embodiment, by introducing an adaptive control mechanism, the control parameters can be dynamically adjusted according to the real-time road friction coefficient and vehicle status to cope with different driving conditions and environmental changes; based on the adaptive control mechanism, the above-mentioned target yaw torque can be distributed to the drive motors of each wheel, and the target torque corresponding to each wheel can be determined. Each target wheel is controlled according to its corresponding target torque, which can ensure the stable driving of the electric vehicle.

[0040] Step S110 , sending the target torque of each wheel to an actuator of the electric vehicle to control the electric vehicle.

[0041] The above-mentioned actuator can be understood as a device that controls mechanical movement through electrical signals. The actuator can drive each wheel to perform corresponding actions according to the target torque corresponding to each wheel received, thereby achieving safe control of the electric vehicle under extreme steering conditions.

[0042] The above-mentioned safety cooperative control method of electric vehicles constructs a vehicle dynamics model of the electric vehicle based on a two-degree-of-freedom bicycle model and the model construction parameters of the electric vehicle; wherein the model construction parameters include: the mass distribution characteristics, tire characteristics and power system parameters of the electric vehicle; based on the vehicle dynamics model and the vehicle driving parameters, a reference trajectory generator is constructed to generate a target reference trajectory under extreme steering conditions based on the reference trajectory generator; based on the pre-designed upper-level yaw moment controller, the target reference trajectory is tracked and the target yaw moment is output; an adaptive control mechanism is used to distribute the target yaw moment to each wheel of the electric vehicle to obtain the target torque corresponding to each wheel; the target torque of each wheel is sent to the actuator of the electric vehicle to control the electric vehicle. This method can significantly improve the vehicle's anti-skid ability and driving stability when the vehicle is in extreme steering conditions, thereby ensuring the safety of passengers.

[0043] The embodiment of the present invention further provides another safety cooperative control method for an electric vehicle, which is implemented on the basis of the method in the above embodiment, and comprises the following steps:

[0044] Step 1: constructing a lateral dynamics model of the electric vehicle based on a two-degree-of-freedom bicycle model and model construction parameters of the electric vehicle; wherein the model construction parameters include: mass distribution characteristics, tire characteristics and power system parameters of the electric vehicle;

[0045] Step 2, determining a lateral force balance model and a torque balance model based on the lateral dynamics model;

[0046] The lateral dynamics are modeled using a two-degree-of-freedom bicycle model, where the left and right tires of each axle are considered as a whole. The system state is the vehicle's center of mass sideslip angle β and yaw rate r. Writing the lateral force balance model at the center of gravity of the vehicle as shown in formula (1) and the torque balance model as shown in formula (2) yields:

[0047]

[0048] Where m represents the vehicle mass; v represents the longitudinal velocity of the vehicle; Indicates the lateral force on the front axle; represents the lateral force on the rear axle; r represents the actual yaw angular velocity.

[0049]

[0050] Among them, I z Represents the vehicle's moment of inertia; l f Indicates the distance from the vehicle's center of gravity to the front axle; l r Indicates the distance from the vehicle's center of gravity to the rear axle; Indicates the lateral force on the front axle; Indicates the lateral force on the rear axle; M z Represents the target yaw moment and is the control variable.

[0051] Step 3, determining a lateral force model based on a preset lateral cornering stiffness, longitudinal cornering stiffness, and a tire slip angle;

[0052] Step 4, substituting the lateral force model into the lateral force balance model and the torque balance model to obtain a vehicle dynamics model of the electric vehicle;

[0053] Tire force depends on many variables. For ease of calculation, this embodiment considers a simplified model F x，y (α, λ) (the specific model is shown in formula (3) and formula (4) below), where α is the tire side slip angle, λ is the longitudinal tire slip, defined as Where R is the wheel radius and ω is the wheel angular velocity. For simplicity, F z is regarded as a constant. Here, the lateral cornering stiffness and longitudinal cornering stiffness are respectively expressed by linear approximation, where the lateral cornering stiffness includes the lateral cornering stiffness C of the front axle. f and the lateral cornering stiffness of the rear axle C r ; Longitudinal cornering stiffness includes the longitudinal cornering stiffness K of the front axle f and the longitudinal cornering stiffness of the rear axle K r :

[0054]

[0055] in, represents the positive force of the front axle; f Indicates longitudinal tire slip on the front axle; Represents the positive force of the rear axle; λ r Indicates longitudinal tire slip on the rear axle.

[0056]

[0057] in, Indicates the lateral force on the front axle; Represents the lateral force on the rear axle; α f Represents the tire slip angle of the front axle; α r Indicates the tire slip angle on the rear axle.

[0058] The tire slip angle α of the front axle is obtained from the two-degree-of-freedom bicycle model f and the tire slip angle α of the rear axle r , the specific method can refer to the relevant technology, which will not be repeated here:

[0059]

[0060] Where β represents the sideslip angle of the center of mass; l f represents the distance from the center of gravity of the vehicle to the front axle; r represents the actual yaw rate; v represents the longitudinal velocity of the vehicle; δ represents the steering angle.

[0061]

[0062] Where β represents the sideslip angle of the center of mass; l r represents the distance from the center of gravity of the vehicle to the rear axle; r represents the actual yaw rate; v represents the longitudinal velocity of the vehicle.

[0063] Substituting formula (5) and formula (6) into formula (4), and then substituting formula (4) into formula (1) and (2), the vehicle dynamics model can be obtained as follows:

[0064]

[0065] Where β represents the sideslip angle of the center of mass; r represents the actual yaw rate; C f Indicates the lateral cornering stiffness of the front axle of the vehicle; C r represents the lateral cornering stiffness of the rear axle of the vehicle; m represents the vehicle mass; v represents the longitudinal speed of the vehicle; l r Indicates the distance from the vehicle's center of gravity to the rear axle; l f Indicates the distance from the vehicle's center of gravity to the front axle; I z represents the vehicle's moment of inertia; δ represents the steering angle; M z represents the target yaw moment;

[0066] Controlling vehicle stability requires the ability to generate yaw moment. For electric buses, differential force cannot be generated, and yaw moment can only be applied by utilizing the coupling of longitudinal and lateral tire forces. Therefore, it is necessary to redefine the lateral cornering stiffness to describe this characteristic, which is defined as follows:

[0067]

[0068] in, and C f0 All are preset constants.

[0069] Step 5: construct a reference trajectory generator based on the vehicle dynamics model and vehicle driving parameters;

[0070] Step 6, generating a desired reference trajectory based on the vehicle dynamics model and the reference trajectory generator;

[0071] The generation of the reference trajectory has two goals; the first is to activate the ESC (Electronic Stability Controller) when the vehicle is close to instability. The second is to generate a suitable reference for the control system. Regarding the first goal, when the desired yaw rate r des The error between the measured yaw rate and r When the value is greater than the preset threshold value thh, the control is triggered. r When the value is less than the preset threshold value thl and lasts for more than 0.5 seconds, the control is stopped, wherein the threshold value thh is usually greater than the threshold value thl. The expected reference trajectory is expressed as follows:

[0072]

[0073] Among them, r des represents the desired yaw rate; v represents the longitudinal velocity of the vehicle; L represents the wheelbase of the vehicle; K us represents the understeering coefficient of the vehicle; δ represents the steering angle; μ represents the friction coefficient; and g represents the acceleration due to gravity.

[0074] In practical applications, the reference trajectory generator is used to generate the expected yaw rate of the vehicle when it is about to become unstable.

[0075] Step 7, correcting the expected reference trajectory to obtain the target reference trajectory;

[0076] However, it is difficult to accurately obtain the friction coefficient, so μ is usually considered to be fixed and equal to 1. In order to ensure robustness, the expected reference trajectory of formula (9) is corrected to obtain the corrected target reference trajectory as follows:

[0077]

[0078] Among them, r ref represents the target yaw rate; r represents the actual yaw rate; r des represents the expected yaw angular velocity; ∧ represents the "and" relationship; sign is the sign function, which is used to indicate the positive or negative nature of a number.

[0079] Step 8: Track the target reference trajectory based on the pre-designed upper-level yaw moment controller and output the target yaw moment:

[0080] In order to ensure the control effect of lateral stability under different working conditions, the upper yaw moment controller is designed using a table lookup PID (proportional-integral-derivative) algorithm. Figure 2A schematic diagram of a control structure is shown in FIG. 1 , where G1 and G2 form a system model. G1 is the transfer function of the yaw rate, and G2 is the transfer function of the center of mass sideslip angle. In order to obtain a specific transfer function, the longitudinal velocity v x Assuming that it always remains constant, for a vehicle speed of 40km / h and 90km / h, taking an electric vehicle as an example, the corresponding transfer function is specifically shown in formula (11).

[0081]

[0082] The table lookup PID controller designed in this embodiment is intended to make the electric vehicle follow the desired yaw rate r des And minimize the center of mass sideslip angle β (the desired center of mass sideslip angle is 0). As shown in formula (12), including the proportional gain K p , integral gain K i and differential gain K d ; These gains are added to form the transfer function block G of the upper yaw moment controller c .

[0083]

[0084] The proportional gain K in formula (12) p , integral gain K i and differential gain K d As the vehicle speed changes dynamically, the gain at different vehicle speeds can be obtained by looking up the difference in the table. By scheduling the PID parameters, the adaptability of the yaw moment controller under different working conditions is guaranteed. The gain parameters corresponding to the slow speed of 40km / h and the high speed of 90km / h are shown in the following table:

[0085] parameter Slow speed 40km / h High speed 90km / h <![CDATA[K p ]]> 2.12 1.21 <![CDATA[K i ]]> 56.23 7.65 <![CDATA[K d ]]> 0 0.56

[0086] The final target yaw moment is as follows:

[0087]

[0088] Among them, M z represents the target yaw moment; K p represents the proportional gain of the upper yaw moment controller; K i represents the integral gain of the upper yaw torque controller; K d represents the differential gain of the upper yaw moment controller; r ref represents the target yaw rate; r represents the actual yaw rate.

[0089] Step nine, determining a relationship model between wheel torque and yaw moment based on a vehicle dynamics model;

[0090] Step 10, constructing an objective function based on the relational model, solving the objective function, and obtaining a target torque adaptive control mechanism corresponding to each wheel;

[0091] A torque distribution model based on vehicle dynamics can be established, with the goal of distributing the target yaw torque to the drive motors of each wheel. An adaptive control mechanism is introduced to dynamically adjust the control parameters according to the real-time road friction coefficient and vehicle status to cope with different driving conditions and environmental changes. Finally, a comprehensive objective function of optimal power and energy is constructed, and a torque optimal distribution strategy based on a quadratic programming algorithm is designed.

[0092] Specifically, in order to obtain the wheel torque T of the front axle f , wheel torque T of the rear axle r and M z First, calculate the torque balance at the center of gravity of the vehicle and obtain the following relationship:

[0093]

[0094] in, represents the total yaw moment and is used as an intermediate variable; δ represents the steering angle; Indicates the positive force of the right wheel on the front axle; Indicates the positive force of the left wheel on the front axle; d f Indicates the wheelbase of the front wheel; l f Indicates the distance from the vehicle's center of gravity to the front axle; Indicates the lateral force of the right wheel on the front axle; Indicates the lateral force of the left wheel on the front axle; Represents the positive force of the right wheel on the rear axle: Represents the positive force of the left wheel on the rear axle; d r Indicates the wheelbase of the rear wheels; Indicates the lateral force of the left wheel on the rear axle; Indicates the lateral force of the right wheel on the rear axle; l r Indicates the distance from the vehicle's center of gravity to the rear axle.

[0095] According to the electric bus power system architecture, assuming Where T is the wheel torque and R is the wheel radius. The forces on the left and right sides will be equal. In addition, it is usually assumed that the steering angle δ and the sideslip angle β are small. Based on this small angle assumption and formula (13), we can get:

[0096]

[0097] according to and Combined with formula (4), formula (14) can be written as:

[0098]

[0099] Finally, substituting (2), (7), and (8) into (15), according to the assumed linear relationship between force and torque, we obtain:

[0100]

[0101] According to formula (16), the control variable M is obtained z equal:

[0102] M z =A(α f , α r )·T v ,

[0103]

[0104] In order to calculate the optimal torque distribution, an optimization problem is constructed here, as shown in formula (18):

[0105]

[0106] subject to A(α f , α r )·T v =M z

[0107] T i ≤h bi

[0108] T i ≥l bi (18) Where h bi =[0 0 0 0] T , I bi =[-∞ -∞ -∞ -∞] T , cost function As the objective function, it is used to minimize the torque of each axle. After completing the optimization problem of formula (18), the ideal target torque of each wheel can be obtained.

[0109] Step eleven: sending the target torque of each wheel to the actuator of the electric vehicle to control the electric vehicle.

[0110] The solved target torque for each wheel can be sent to the actuator via the CAN bus to complete the entire active safety control process.

[0111] The above-mentioned safe collaborative control method for electric vehicles comprehensively utilizes the advantages of the independent front and rear drive motors of electric buses, and calculates the required yaw rate and center of mass sideslip angle by real-time monitoring of the vehicle's turning angle and road friction coefficient parameters. This method designs a yaw torque control method based on a table lookup PID. According to the calculation results, an optimal torque distribution method based on an adaptive distribution rate is designed to achieve stable control of the vehicle. Under extreme steering conditions, this control method can significantly improve the stability and anti-skid ability of electric buses, reduce the risk of accidents, and ensure passenger safety.

[0112] Electric buses have the advantages of fast response and precise control due to their unique power system configuration, especially the independently driven front and rear axle motors. This method uses the independent control of the front and rear motors to achieve vehicle stability and improve the safety of the vehicle under extreme working conditions, which has important practical significance.

[0113] The above-mentioned safety cooperative control method for electric vehicles is an active safety cooperative control method that can effectively improve the stability of electric vehicles under extreme steering conditions, and has important application prospects. By comprehensively utilizing the front and rear independent drive motors of electric vehicles, torque distribution and optimization control are performed to improve the vehicle's anti-skid ability and driving stability, thereby ensuring passenger safety.

[0114] The embodiment of the present invention provides a safety cooperative control device for an electric vehicle, such as Figure 3 As shown, the device includes: a first construction module 30, which is used to construct a vehicle dynamics model of the electric vehicle based on a two-degree-of-freedom bicycle model and a model construction parameter of the electric vehicle; wherein the model construction parameters include: mass distribution characteristics, tire characteristics and power system parameters of the electric vehicle; a second construction module 31, which is used to construct a reference trajectory generator based on the vehicle dynamics model and the vehicle driving parameters, so as to generate a target reference trajectory under extreme steering conditions based on the reference trajectory generator; an output module 32, which is used to track the target reference trajectory based on a pre-designed upper-level yaw moment controller and output the target yaw moment; a distribution module 33, which is used to adopt an adaptive control mechanism to distribute the target yaw moment to each wheel of the electric vehicle to obtain a target torque corresponding to each wheel; a sending module 34, which is used to send the target torque of each wheel to the actuator of the electric vehicle to control the electric vehicle.

[0115] The above-mentioned safety cooperative control device for the electric vehicle can significantly improve the vehicle's anti-skid ability and driving stability when the vehicle is in an extreme turning condition, thereby ensuring the safety of passengers.

[0116] Furthermore, the first construction module is also used to: construct a lateral dynamics model of the electric vehicle based on the two-degree-of-freedom bicycle model and the model construction parameters of the electric vehicle; determine the lateral force balance model and the torque balance model based on the lateral dynamics model; determine the lateral force model based on the preset lateral cornering stiffness, longitudinal cornering stiffness, and tire slip angle; substitute the lateral force model into the lateral force balance model and the torque balance model to obtain the vehicle dynamics model of the electric vehicle.

[0117] Furthermore, the vehicle dynamics model is expressed as follows:

[0118]

[0119] Where β represents the sideslip angle of the center of mass; r represents the actual yaw rate; C f Indicates the lateral cornering stiffness of the front axle of the vehicle; C r represents the lateral cornering stiffness of the rear axle of the vehicle; m represents the vehicle mass; v represents the longitudinal speed of the vehicle; l r Indicates the distance from the vehicle's center of gravity to the rear axle; l f Indicates the distance from the vehicle's center of gravity to the front axle; I z represents the vehicle's moment of inertia; δ represents the steering angle; M z represents the target yaw moment;

[0120] in, and C f0 All are preset constants.

[0121] Furthermore, the second construction module is also used to: generate a desired reference trajectory based on the vehicle dynamics model and the reference trajectory generator; and correct the desired reference trajectory to obtain a target reference trajectory.

[0122] Furthermore, the expected reference trajectory is expressed as follows:

[0123]

[0124] Among them, r des represents the desired yaw rate; v represents the longitudinal velocity of the vehicle; L represents the wheelbase of the vehicle; K us represents the understeering coefficient of the vehicle; δ represents the steering angle; μ represents the friction coefficient; and g represents the acceleration due to gravity.

[0125] Furthermore, the target reference trajectory is expressed as follows:

[0126]

[0127] Among them, r ref represents the target yaw rate; r represents the actual yaw rate; r desrepresents the desired yaw angular velocity; ∧ represents the “and” relationship; sign is the sign function.

[0128] Furthermore, the target yaw moment is expressed as follows:

[0129]

[0130] Among them, M z represents the target yaw moment; K p represents the proportional gain of the upper yaw moment controller; K i represents the integral gain of the upper yaw torque controller; K d represents the differential gain of the upper yaw moment controller; r ref represents the target yaw rate; r represents the actual yaw rate.

[0131] Furthermore, the allocation module is also used to: determine a relationship model between wheel torque and yaw moment based on a vehicle dynamics model; construct an objective function based on the relationship model, solve the objective function, and obtain a target torque corresponding to each wheel.

[0132] The safety cooperative control device for an electric vehicle provided in an embodiment of the present invention has the same implementation principle and technical effects as those in the aforementioned embodiment of the safety cooperative control method for an electric vehicle. For the sake of brief description, for matters not mentioned in the embodiment of the safety cooperative control device for an electric vehicle, reference may be made to the corresponding contents in the aforementioned embodiment of the safety cooperative control method for an electric vehicle.

[0133] The embodiment of the present invention further provides an electronic device, see Figure 4 As shown, the electronic device includes a processor 130 and a memory 131, wherein the memory 131 stores machine executable instructions that can be executed by the processor 130, and the processor 130 executes the machine executable instructions to implement the above-mentioned safety collaborative control method for the electric vehicle.

[0134] Further, Figure 4 The electronic device shown further includes a bus 132 and a communication interface 133 , and the processor 130 , the communication interface 133 and the memory 131 are connected via the bus 132 .

[0135] The memory 131 may include a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 133 (which may be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. may be used. The bus 132 may be an ISA bus, a PCI bus, or an EISA bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0136] The processor 130 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 130. The above processor 130 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present invention can be directly embodied as a hardware decoding processor for execution, or a combination of hardware and software modules in the decoding processor for execution. The software module may be located in a storage medium mature in the art, such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory 131, and the processor 130 reads the information in the memory 131 and completes the steps of the method of the above embodiment in combination with its hardware.

[0137] An embodiment of the present invention also provides a machine-readable storage medium, which stores machine-executable instructions. When the machine-executable instructions are called and executed by a processor, the machine-executable instructions prompt the processor to implement the above-mentioned safe collaborative control method of the electric vehicle. The specific implementation can be found in the method embodiment, which will not be repeated here.

[0138] The computer program product of the electric vehicle safety collaborative control method, device and electronic device provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the previous method embodiments. The specific implementation can be found in the method embodiments, which will not be repeated here.

[0139] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the 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 several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0140] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention 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 or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A safety cooperative control method for an electric vehicle, characterized in that: The method comprises: Based on the two-degree-of-freedom bicycle model and the model building parameters of the electric vehicle, a vehicle dynamics model of the electric vehicle is constructed; wherein the model building parameters include: mass distribution characteristics, tire characteristics and power system parameters of the electric vehicle; Based on the vehicle dynamics model and the vehicle driving parameters, a reference trajectory generator is constructed to generate a target reference trajectory under an extreme steering condition based on the reference trajectory generator; Tracking the target reference trajectory based on a pre-designed upper layer yaw moment controller and outputting a target yaw moment; Adopting an adaptive control mechanism to distribute the target yaw moment to each wheel of the electric vehicle to obtain a target torque corresponding to each wheel; The target torque of each wheel is sent to an actuator of the electric vehicle to control the electric vehicle.

2. The method according to claim 1, characterized in that Based on the two-degree-of-freedom bicycle model and the model building parameters of the electric vehicle, the steps of building the vehicle dynamics model of the electric vehicle include: Constructing a lateral dynamics model of the electric vehicle based on a two-degree-of-freedom bicycle model and model construction parameters of the electric vehicle; Determining a lateral force balance model and a torque balance model based on the lateral dynamics model; Determine a lateral force model based on preset lateral cornering stiffness, longitudinal cornering stiffness, and tire slip angle; The lateral force model is substituted into the lateral force balance model and the torque balance model to obtain a vehicle dynamics model of the electric vehicle.

3. The method according to claim 1, characterized in that: The vehicle dynamics model is expressed as follows: Where β represents the sideslip angle of the center of mass; r represents the actual yaw rate; C f Indicates the lateral cornering stiffness of the front axle of the vehicle; C r represents the lateral cornering stiffness of the rear axle of the vehicle; m represents the vehicle mass; v represents the longitudinal speed of the vehicle; l r Indicates the distance from the vehicle's center of gravity to the rear axle; l f Indicates the distance from the vehicle's center of gravity to the front axle; I z represents the vehicle's moment of inertia; δ represents the steering angle; M z represents the target yaw moment; in, and C f0 All are preset constants.

4. The method according to claim 1, characterized in that: Based on the reference trajectory generator, the step of generating a target reference trajectory under extreme steering conditions includes: generating a desired reference trajectory based on the vehicle dynamics model and the reference trajectory generator; The expected reference trajectory is corrected to obtain a target reference trajectory.

5. The method according to claim 4, characterized in that The desired reference trajectory is expressed as follows: Among them, r des represents the desired yaw rate; v represents the longitudinal velocity of the vehicle; L represents the wheelbase of the vehicle; K us represents the understeering coefficient of the vehicle; δ represents the steering angle; μ represents the friction coefficient; and g represents the acceleration due to gravity.

6. The method according to claim 5, characterized in that The target reference trajectory is expressed as follows: Among them, r ref represents the target yaw rate; r represents the actual yaw rate; r des represents the desired yaw angular velocity; ∧ represents the "and" relationship; Sign is the sign function.

7. The method according to claim 1, characterized in that The target yaw moment is expressed as follows: Among them, M z represents the target yaw moment; K p represents the proportional gain of the upper yaw moment controller; K i represents the integral gain of the upper yaw torque controller; K d represents the differential gain of the upper yaw moment controller; r ref represents the target yaw rate; r represents the actual yaw rate.

8. The method according to claim 1, characterized in that The steps of using an adaptive control mechanism to distribute the target yaw moment to each wheel of the electric vehicle to obtain a target torque corresponding to each wheel include: Based on the vehicle dynamics model, determining a relationship model between wheel torque and yaw moment; An objective function is constructed based on the relationship model, and the objective function is solved to obtain a target torque corresponding to each wheel.

9. A safety cooperative control device for an electric vehicle, characterized in that: The device comprises: A first construction module is used to construct a vehicle dynamics model of the electric vehicle based on a two-degree-of-freedom bicycle model and model construction parameters of the electric vehicle; wherein the model construction parameters include: mass distribution characteristics, tire characteristics and power system parameters of the electric vehicle; A second construction module is used to construct a reference trajectory generator based on the vehicle dynamics model and the vehicle driving parameters, so as to generate a target reference trajectory under an extreme steering condition based on the reference trajectory generator; An output module, used for tracking the target reference trajectory based on a pre-designed upper layer yaw moment controller, and outputting a target yaw moment; a distribution module, configured to distribute the target yaw moment to each wheel of the electric vehicle by adopting an adaptive control mechanism, so as to obtain a target torque corresponding to each wheel; A sending module is used to send the target torque of each wheel to the actuator of the electric vehicle to control the electric vehicle.

10. An electronic device, characterized in that: It includes a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement the safety collaborative control method of the electric vehicle described in any one of claims 1-8.

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