Driving anti-slip control method of electric vehicle, electric vehicle and storage medium

Abstract

The invention discloses a driving anti-skid control method of an electric vehicle, the electric vehicle and a storage medium, and belongs to the field of electric vehicle control. The method comprises the steps that when the electric vehicle is in a driving state, the actual rotating speed of a motor of the electric vehicle is obtained; under the condition that the actual rotating speed is larger than the target rotating speed, an initial anti-slip control stage is started, a first motor torque control signal is generated through the active disturbance rejection controller according to the target rotating speed and the actual rotating speed, and the first motor torque control signal is used for controlling the motor torque; and under the condition of entering the continuous anti-skid control stage, real-time wheel load torque is obtained, a second motor torque control signal is generated through the active disturbance rejection controller according to the target rotating speed, the actual rotating speed and the real-time wheel load, and the second motor torque control signal is used for controlling the motor torque. By dividing the anti-skid control stages and selecting different anti-skid control methods, the wheel slippage can be quickly and stably controlled, and the driving safety and comfort are improved.

Description

Technical Field

[0001] The present application belongs to the technical field of electric vehicle control, and in particular, relates to a driving anti-skid control method for an electric vehicle, an electric vehicle and a storage medium. Background Art

[0002] At present, the vehicle traction control system (TCS) has become a standard configuration for automobiles, playing an important role in improving the driving stability, safety and acceleration performance of automobiles. Its working principle is: according to the driving conditions of the vehicle, the slip rate of the vehicle's driving wheels is kept as close to the optimal slip rate as possible through appropriate control algorithms, so that the vehicle can maximize the use of the driving torque of the power source under poor road adhesion or complex driving conditions, ensuring that the vehicle starts and accelerates quickly and stably. For example: in the process of slip control, from low adhesion to lower adhesion road surface, the drive anti-skid control system needs to adapt to the road surface very quickly to obtain the best road adhesion and avoid excessive slip; or in the process of slip control, from low adhesion to slightly higher adhesion road surface, it needs to respond very quickly to obtain greater adhesion and improve the power performance of the whole vehicle under harsh conditions. For electric drive vehicles, compared with wheels driven by internal combustion engines, the power system has a smaller rotational inertia and a greater slip rate change rate.

[0003] In the prior art, the control algorithms currently used by TCS mainly include: (1) rule-based logic threshold control; (2) proportional-integral-differential (PID) control or nonlinear PID control; (3) sliding mode variable structure control, etc. However, due to the limitations of the algorithms themselves, these control algorithms limit the full play of the drive anti-skid control performance, resulting in the inability to quickly and stably control wheel slip. Therefore, the prior art has the problem of poor stability of the drive anti-skid control of electric vehicles. Summary of the invention

[0004] The embodiments of the present application provide a drive anti-skid control method, a drive anti-skid control device, an electric vehicle and a computer storage medium for an electric vehicle, which can quickly and stably control wheel slip and improve driving safety and comfort.

[0005] In a first aspect, an embodiment of the present application provides a driving anti-skid control method for an electric vehicle, the method comprising:

[0006] When the electric vehicle is in a driving state, obtaining an actual rotation speed of a motor of the electric vehicle;

[0007] When the actual speed is greater than the target speed, the initial anti-slip control stage is entered, and a first motor torque control signal is generated according to the target speed and the actual speed by an anti-disturbance controller, and the first motor torque control signal is used to control the motor torque;

[0008] When entering the continuous anti-slip control stage, the real-time wheel load torque is obtained, and the second motor torque control signal is generated by the active disturbance rejection controller according to the target speed, the actual speed and the real-time wheel load, and the second motor torque control signal is used to control the motor torque.

[0009] In a second aspect, an embodiment of the present application provides a driving anti-skid control device for an electric vehicle, the driving anti-skid control device comprising:

[0010] An acquisition module, used to acquire an actual rotation speed of a motor of the electric vehicle when the electric vehicle is in a driving state;

[0011] An initial anti-slip control module, used for entering the initial anti-slip control stage when the actual speed is greater than the target speed, generating a first motor torque control signal according to the target speed and the actual speed through an anti-disturbance controller, the first motor torque control signal being used for controlling the motor torque;

[0012] The continuous anti-skid control module is used to obtain the real-time wheel load torque when entering the continuous anti-skid control stage, and generate a second motor torque control signal according to the target speed, the actual speed and the real-time wheel load through an anti-disturbance controller, and the second motor torque control signal is used to control the motor torque.

[0013] In a third aspect, an embodiment of the present application provides an electric vehicle, wherein the device includes:

[0014] a processor and a memory storing computer program instructions;

[0015] When the processor executes the computer program instructions, the driving anti-skid control method for the electric vehicle as described in the first aspect is implemented.

[0016] In a fourth aspect, an embodiment of the present application provides a computer storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the driving anti-skid control method for an electric vehicle as described in the first aspect is implemented.

[0017] In a fifth aspect, an embodiment of the present application provides a computer program product. When instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the drive anti-skid control method for an electric vehicle as described in the first aspect.

[0018] In the embodiment of the present application, when the electric vehicle is in a driving state, the actual speed of the motor of the electric vehicle is first obtained, and then when the actual speed is greater than the target speed, the initial anti-skid control stage is entered, and the first motor torque control signal is generated according to the target speed and the actual speed by the self-disturbance rejection controller, and the first motor torque control signal is used to control the motor torque, and then when entering the continuous anti-skid control stage, the real-time wheel load torque is obtained, and the second motor torque control signal is generated according to the target speed, the actual speed and the real-time wheel load by the self-disturbance rejection controller, and the second motor torque control signal is used to control the motor torque. In this way, different anti-skid control methods are used in different anti-skid control stages, which can quickly and stably control wheel slip and improve driving safety and comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 It is a flow chart of a driving anti-skid control method for an electric vehicle provided in an embodiment of the present application;

[0021] Figure 2 is a schematic diagram of a driving anti-skid control process provided by an embodiment of the present application;

[0022] Figure 3 is a schematic diagram of a wheel motion dynamics model provided in an embodiment of the present application;

[0023] Figure 4 It is a schematic diagram of observation principle of wheel load torque provided in an embodiment of the present application;

[0024] Figure 5 is a structural diagram of a control system provided in an embodiment of the present application;

[0025] Figure 6 It is a division diagram of an anti-skid control stage provided in an embodiment of the present application;

[0026] Figure 7 It is a flowchart of a driving anti-skid control method for an electric vehicle provided in a specific embodiment of the present application;

[0027] Figure 8 is a structural diagram of a drive anti-skid control device provided in an embodiment of the present application;

[0028] Fig. 9 It is a schematic diagram of the hardware structure of a drive anti-skid control provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0030] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0031] The driving anti-skid control method for an electric vehicle provided in the embodiment of the present application is described in detail below through some embodiments and their application scenarios in combination with the accompanying drawings.

[0032] See also Figure 1 , Figure 1 1 is a flow chart of a driving anti-skid control method for an electric vehicle provided in an embodiment of the present application. Figure 1 As shown, the driving anti-skid control method of an electric vehicle may include the following steps:

[0033] Step 101: When the electric vehicle is in a driving state, obtain the actual rotation speed of the motor of the electric vehicle.

[0034] In the embodiments of the present application, an electric vehicle refers to a vehicle that is driven in whole or in part by electric energy, and the anti-skid control of the electric vehicle refers to the anti-skid control of the wheels of the vehicle. The reason for wheel slippage is the insufficient adhesion between the tire and the road surface. When the adhesion is large enough, the wheel can hold the ground tightly and remain stable; when the adhesion is insufficient, the wheel is easy to slide on the road surface, causing slippage. For electric vehicles, the motor torque is the direct source of the driving torque. The torque of the motor determines the size of the driving torque, which in turn affects the acceleration performance and power output of the car. When the driving force generated by the driving torque exceeds the adhesion of the road surface, slippage will occur. The motor torque is positively correlated with the motor speed. Therefore, it is possible to judge whether the vehicle needs anti-skid control based on the actual speed of the motor.

[0035] Step 102: When the actual speed is greater than the target speed, the initial anti-slip control stage is entered, and a first motor torque control signal is generated according to the target speed and the actual speed by an anti-disturbance controller, and the first motor torque control signal is used to control the motor torque.

[0036] In the embodiment of the present application, when the actual speed of the motor is greater than the target speed, it indicates that the driving wheel is slipping, and the period of time after the driving wheel enters the wheel slipping state from the non-slip state is the initial anti-slip control stage. Figure 2 , is a schematic diagram of a driving anti-skid control process provided by an embodiment of the present application, such as Figure 2 As shown in the figure, in the initial anti-skid control stage, the control goal is to suppress the wheel slipping tendency as quickly as possible, prevent the wheel from slipping too much, and even cause the vehicle to become unstable, that is, quickly reduce the driving torque to eliminate the wheel end slip that has already occurred, so that the actual speed of the motor drops below the target speed.

[0037] Active disturbance rejection control (ADRC) is evolved from PID control and adopts the core concept of PID error feedback control, but the control accuracy is much better than the classic PID controller. It is suitable for high-precision measurement and control systems. It has good stability and robustness, and can maintain a stable control effect when system parameters change or are disturbed. In the initial anti-slip control stage, the target speed and the actual speed are compared by the ADRC. The two values ​​are constantly compared inside the controller to determine the difference between them (i.e., the error). Based on the error signal, the ADRC calculates the necessary control input to eliminate the error. The control input is the motor torque control signal. The motor torque control signal is sent to the motor driver to adjust the output torque of the motor so that the actual speed of the motor falls below the target speed, thereby eliminating the wheel end slip that has already occurred.

[0038] Step 103: When entering the continuous anti-skid control stage, the real-time wheel load torque is obtained, and a second motor torque control signal is generated by the anti-disturbance control controller according to the target speed, the actual speed and the real-time wheel load, wherein the second motor torque control signal is used to control the motor torque.

[0039] In the embodiment of the present application, the stage after the initial anti-skid control stage is the continuous anti-skid control stage. The control goal of this stage is to make the driving force generated by the driving torque below the road adhesion and maintain a small low-frequency fluctuation. Figure 3 , is a schematic diagram of a wheel motion dynamics model provided in an embodiment of the present application, and its dynamics equation is formula (1):

[0040]

[0041] In the formula, J w is the moment of inertia of the power transmission system from the motor to the wheels; T m is the actual torque of the motor; F x is the adhesion between the road surface and the tire; R r is the tire rolling radius; T f is the rolling resistance torque; μ is the adhesion coefficient of the road-tire effect; λ is the wheel slip rate; F N is the vertical support force provided by the road surface to the tire, ω is the motor speed, V x is the actual vehicle speed.

[0042] From the analysis of the dynamic model of the system composed of the motor and the wheel, it can be seen that the sum of the rolling resistance torque and the road adhesion resistance torque can be regarded as the load of the wheel. If this load is regarded as the disturbance of the system, the system can be compensated into an integral series type.

[0043] In one example, based on the dynamics formula of the drive system, the load can be quickly and accurately estimated through the proportional-integral observer. The real-time load is added to the active disturbance rejection controller as compensation, which is the feedforward compensation control. Figure 4 , is a schematic diagram of the observation principle of wheel load torque provided in the embodiment of the present application. For an electric vehicle driven by a permanent magnet synchronous motor, the actual output of the motor, i.e., the actual torque T m The current value i can be obtained by measuring the three-phase current sensor a 、i b 、i c , rotor position θ and permanent magnet flux The calculation can be approximately considered to be directly measurable, and the motor speed is recorded as ω. The wheel load torque estimation expression is formula (2):

[0044]

[0045] In the formula, is a differential operator; is the motor wheel speed observed by the observer; is the wheel load torque observed by the observer; J w K is the moment of inertia of the power transmission system from the motor to the wheels; P , K I is the gain coefficient of the proportional integral observer, which is an adjustable parameter. P , K I The parameter setting can be obtained based on the empirical formula. The following empirical formula (3) is an example:

[0046]

[0047] In the formula, α s is the bandwidth of the observer closed loop; ε is the set damping coefficient.

[0048] Since the estimation of wheel load torque is used as disturbance compensation and is directly used as feedforward and superimposed into the control system, the error generated is not adjustable. Therefore, it can be limited to obtain the final output wheel load torque estimation expression as formula (4):

[0049]

[0050] In the formula, is the final output wheel load torque, μ max is the maximum adhesion coefficient, F N The vertical support provided by the road surface to the tire. is the wheel load torque observed by the observer.

[0051] It should be noted that the wheel load torque is not limited to being obtained through observation by a proportional differential observer, but may also be obtained by other methods that can more accurately obtain the wheel load torque, such as installing a torque sensor on the wheel axle or drive shaft and directly measuring the wheel load torque through the torque sensor.

[0052] In this way, based on the actual speed and target speed of the motor, the anti-disturbance control is carried out according to the wheel load torque observation as feedforward, and the main disturbance is adjusted in time, which can greatly reduce the burden of feedback control. The vehicle is driven by anti-skid control during the continuous anti-skid control stage to avoid the situation where the actual speed of the motor is stabilized at a speed point that is too high above the target speed, that is, to avoid the wheel movement balance at a point with too large slip rate. Based on the anti-disturbance controller, the method of controlling the motor torque according to the target speed, actual speed and real-time wheel load torque can obtain better control performance while also having higher control robustness and adaptability.

[0053] Through the above steps, when the electric vehicle is in a driving state, the actual speed of the motor of the electric vehicle is first obtained, and then when the actual speed is greater than the target speed, the initial anti-skid control stage is entered, and the first motor torque control signal is generated according to the target speed and the actual speed by the self-disturbance rejection controller, and the first motor torque control signal is used to control the motor torque, and then when entering the continuous anti-skid control stage, the real-time wheel load torque is obtained, and the second motor torque control signal is generated according to the target speed, the actual speed and the real-time wheel load by the self-disturbance rejection controller, and the second motor torque control signal is used to control the motor torque. In this way, different anti-skid control methods are used in different anti-skid control stages, which can quickly and stably control wheel slip and improve driving safety and comfort.

[0054] In some implementations, generating the second motor torque control signal according to the target speed, the actual speed, and the real-time wheel load by the ADRC may include:

[0055] Based on the real-time wheel load torque, the speed factor of the derivative tracker of the active disturbance rejection controller is adjusted;

[0056] Based on the adjusted ADRC, the feedback control amount is determined according to the target speed and the actual speed;

[0057] Determine a target feedforward control amount based on the real-time wheel load torque;

[0058] The target control amount is obtained by adding the feedback control amount and the feedforward control amount;

[0059] A second motor torque control signal is generated according to the target control amount.

[0060] Since the vehicle running conditions are complex and diverse, in order to further improve the applicability of the driving anti-skid control method and adapt to the dynamic characteristics and control requirements of the anti-skid control system under different road adhesion coefficients, the control parameters of the anti-disturbance control algorithm can be dynamically adjusted. Figure 5 , is a structural diagram of a control system provided in an embodiment of the present application. Figure 5 As shown in Figure 1, the ADRC includes three parts: differential tracker, extended state observer and nonlinear error feedback control law. Among them, the speed factor of the differential tracker is a parameter related to the response speed, that is, the speed factor affects the rate at which the actual speed changes to the target speed. Therefore, based on the real-time road adhesion of the vehicle, selecting different speed factors is an effective way to improve the applicability of the drive anti-skid control method.

[0061] Specifically, the real-time wheel load torque observed by the proportional differential observer reflects the road adhesion of the vehicle in real time. Therefore, the speed factor in the differential tracker in the ADRC algorithm can be adjusted in real time based on the observed wheel load torque, thereby further enhancing the road adaptability of the drive anti-skid control method. The basis for dynamic adjustment of the speed factor is: the larger the speed factor, the faster the tracking differentiator tracks the instruction, and it is suitable for roads with lower adhesion. In other words, the relationship of dynamic setting is: the larger the observed wheel load torque, the smaller the speed factor is set; the smaller the observed wheel load torque, the larger the speed factor is set. In the initial anti-skid control stage, the speed factor is set to a fixed large value, so that the actual speed of the motor can slip below the target speed. In the continuous anti-skid control stage, the vehicle is in a stable slip control state. The optimal speed factor in this state is the optimal speed factor under different steady-state load torques. Therefore, according to the real-time load torque, the speed factor corresponding to the real-time load torque can be obtained by looking up the table, and then the differential tracker of the ADRC is adjusted according to the corresponding speed factor, and the feedback control amount is determined based on the target speed and the actual speed.

[0062] It should be noted that, in some embodiments, the speed factor of the differential tracker may not be adjusted, that is, the value of the speed factor remains unchanged during the entire control process. In this case, the value of the speed factor may be set to be relatively small to ensure the smooth operation of the control system.

[0063] like Figure 5 As shown in the figure, the input of the differential tracker is the desired speed, i.e., the target speed ω0(k). After ω0(k) is input to the differential tracker, the target speed tracking value v1(k) and the rate of change of the target speed tracking value v2(k) are output. That is, v1(k) tracks ω0(k), and v2(k) tracks the first-order differential of ω0(k).

[0064] The discrete expression of the differential tracker is formula (5):

[0065]

[0066] In the formula, fst is the fastest tracking function, and its two input parameters are v1(k)-ω0(k) and v2(k), v1(k-1) is the target speed tracking value at the k-1th moment, v2(k-1) is the rate of change of the target speed tracking value at the k-1th moment, v1(k) is the target speed tracking value at the kth moment, and v2(k) is the rate of change of the target speed tracking value at the kth moment. Its calculation expression is formula (6):

[0067]

[0068] Where h0 and h are the integration steps, which can be selected as the scheduling period of function processing; r is the speed factor; sgn is the sign function, x1=v1(k)-ω0(k), x2=v2(k).

[0069] The input of the extended state observer is the actual speed ω of the motor and the control output u calculated by the ADRC, i.e., the feedback control quantity. Its calculation expression is formula (7):

[0070]

[0071] In the formula, β 01 , β 02 and β 03 is the gain coefficient of the extended state observer, which is an adjustable parameter; z1 is the observed motor speed; z2 is the observed motor acceleration; z3 is the disturbance estimated by the extended state observer; e is the deviation calculated in real time, ω is the actual motor speed, b0 is the controller gain coefficient, δ is the filter factor, δ>0, and the expression of the nonlinear function fal is formula (8):

[0072]

[0073] Where e is the deviation calculated in real time; α is an adjustable parameter, usually selected as a combination of 0.5 and 0.25; δ is the filter factor, δ>0, indicating the interval length of the linear segment of the function; sgn is the sign function; and b0 is the controller gain coefficient.

[0074] For the nonlinear error feedback control law, since the load torque in the system has obtained accurate observation values ​​through the proportional differential observer and corrected as the system disturbance value, and the self-disturbance rejection control algorithm has disturbance estimation capability and strong anti-disturbance performance, the part that relies on integral compensation to eliminate the influence of disturbances and unmodeled parts is small, so the integral term can be omitted. As shown in formula (9):

[0075]

[0076] In the formula, β 11 , β 12 is the gain coefficient of the nonlinear error feedback control law, which is an adjustable parameter; α1 and α2 are adjustable parameters, and α1<1<α2 is usually selected; u0 is the output of the nonlinear error feedback control law module, v1 is the target speed tracking value, v2 is the rate of change of the target speed tracking value, and e1 and e2 are real-time deviations.

[0077] Finally, the disturbance z3 estimated by the extended state observer is compensated to the output u0 of the nonlinear error feedback control law, and the output calculated by the active disturbance rejection controller, i.e., the feedback control quantity u, can be obtained, as shown in formula (10):

[0078]

[0079] Where: b0 is the gain coefficient of the controller, which is an adjustable parameter and is usually taken as the inverse of the moment of inertia.

[0080] After calculating the feedback control amount u and determining the target feedforward control amount FF based on the real-time wheel load torque, the feedback control amount and the feedforward control amount are added to obtain the target control amount. The target control amount is output to the motor driver to adjust the output torque of the motor. In other words, the composite control system acts on the input u of the controlled object. * As shown in formula (11):

[0081] u * =u+FF (11)

[0082] In this way, in the continuous anti-skid control stage, on the basis of the anti-disturbance control, the method of controlling the motor torque by combining the real-time wheel load torque can make the control performance better and the adaptability higher.

[0083] In some implementations, determining the target feedforward control amount based on the real-time wheel load torque may include:

[0084] Obtain the feedforward control value at the k-1th moment, where k is a positive integer greater than 1;

[0085] Determine the difference between the feedforward control amount at the k-1th moment and the real-time wheel load torque;

[0086] When the difference is within the first interval, the real-time load torque is determined as the target feedforward control amount;

[0087] When the difference is within or outside the first interval, the feedforward control amount at the kth moment is obtained by using the feedforward control amount at the k-1th moment and the preset step size; and the target feedforward control amount is determined based on the feedforward control amount at the kth moment or the real-time wheel load torque.

[0088] Specifically, in the continuous anti-skid control stage, the self-disturbance rejection control and feedforward compensation work together, that is, the feedforward compensation is connected on the basis of the self-disturbance rejection control. In order to avoid the situation where the output of the controller suddenly adds a step feedforward value when the control system adds feedforward, thereby giving a large impact to the controlled system and the extended state observer, a transition process of connection can be arranged, that is, the connection amount of the real-time wheel load torque is limited until it is completely connected normally. It should be noted that the connection amount of the real-time wheel load torque is the feedforward amount. At the initial moment of the real-time wheel load torque connection, that is, when k is 0, the connection amount is 0, that is, the feedforward amount at this time is 0, and then the connection amount is gradually increased with a preset step size until it is fully connected.

[0089] In the continuous anti-skid control stage, the system can obtain the observed load torque and the feedforward control quantity at time k-1 in real time, and determine the difference between the feedforward control quantity at time k-1 and the real-time wheel load torque. When the difference is in the first interval, it means that the difference between the access quantity at the previous moment and the real-time wheel load torque is already very small, that is, the transition process of the feedforward item access has been completed, and then the real-time load torque can be directly determined as the target feedforward control quantity access. In some embodiments, the difference in the first interval can be expressed as shown in the following formula (12):

[0090]

[0091] In the formula, dT is the sampling period, time is the sampling time, Inc×dT is the preset step size, which is a positive number, y(k-1) is the access volume at the k-1th time, is the wheel load torque at the kth moment.

[0092] It should be noted that the specific expression of the first interval is not limited to the above formula. In other embodiments, the end value of the first interval can be set based on actual needs.

[0093] When the difference is greater than or equal to the first threshold, it means that the difference between the access amount at the previous moment and the real-time wheel load torque is still large, and it is not possible to directly fully access. At this time, it is necessary to first use the feedforward control amount at the k-1 moment and the preset step size to calculate the feedforward control amount at the kth moment, that is, the feedforward control amount at the current moment. Then, based on the feedforward control amount at the kth moment or the real-time wheel load torque, determine the target feedforward control amount.

[0094] In some implementations, determining the target feedforward control amount based on the feedforward control amount or the real-time wheel load torque at the kth moment may include:

[0095] Compare the feedforward control quantity at the k-1th moment with the real-time wheel load torque;

[0096] In the case where the feedforward control amount at the k-1th moment is less than the real-time wheel load torque, the smaller value of the feedforward control amount at the kth moment and the real-time wheel load torque is determined as the target feedforward control amount, wherein the feedforward control amount at the kth moment is the sum of the feedforward control amount at the k-1th moment and the preset step length;

[0097] When the feedforward control amount at the k-1th moment is greater than or equal to the real-time wheel load torque, the larger value of the feedforward control amount at the kth moment and the real-time wheel load torque is determined as the target feedforward control amount, wherein the feedforward control amount at the kth moment is the difference between the feedforward control amount at the k-1th moment and the preset step size.

[0098] Specifically, after determining that the difference between the feedforward control quantity at the k-1th moment and the real-time wheel load torque is greater than or equal to the first threshold, the k-1th feedforward control quantity is compared with the real-time wheel load torque. If the feedforward control quantity at the k-1th moment is less than the real-time wheel load torque, the smaller value of the feedforward control quantity at the k-1th moment and the real-time wheel load torque is determined as the target feedforward control quantity; if the feedforward control quantity at the k-1th moment is greater than or equal to the real-time wheel load torque, the larger value of the feedforward control quantity at the k-1th moment and the real-time wheel load torque is determined as the target feedforward control quantity. In this way, the real-time wheel load torque can be smoothly connected to avoid a large impact on the controlled system. The calculation formula of the connected feedforward quantity, i.e., the target feedforward control quantity, is shown in formula (13):

[0099]

[0100] In the formula, y(k) is the access volume at the kth moment, is the wheel load torque at the kth moment, dT is the sampling period, Inc×dT is the preset step size, which is a positive number.

[0101] The preset step size may be calculated in real time according to the sampling period during the control process, or may be set in advance by relevant personnel according to actual conditions and input into the control system.

[0102] In some embodiments, after controlling the motor torque according to the target speed and the actual speed based on the active disturbance rejection controller, determining the real-time wheel load torque through a proportional-integral observer, and before controlling the motor torque according to the target speed, the actual speed and the real-time wheel load torque based on the active disturbance rejection controller, the drive anti-slip control method may further include:

[0103] When the actual speed is in the second interval and the acceleration of the motor is positive, determining that the electric vehicle enters a continuous anti-skid control stage;

[0104] The first end value of the second interval is the target speed, and the second end value of the second interval is the difference between the target speed and the preset deviation.

[0105] Specifically, the second interval is as shown in formula (14):

[0106]

[0107] Where ω0 is the target speed of the motor, ω is the actual speed of the motor, Δω is the set deviation, and V x is the actual vehicle speed, i g is the transmission ratio from motor to wheel, λ opt is the slip rate.

[0108] See also Figure 6, is a diagram of the division of anti-skid control stages provided by an embodiment of the present application. Figure 6 As shown in the figure, when the actual speed of the motor is in the second interval, it means that the system has adjusted the current actual speed to be below the target speed, and the difference with the target speed is small. At this time, the control target is no longer to quickly reduce the motor torque and speed, but to maintain the torque and speed in this interval and maintain a small low-frequency fluctuation, that is, the electric vehicle enters the continuous anti-slip control stage.

[0109] In some embodiments, after controlling the motor torque according to the target speed and the actual speed based on the active disturbance rejection controller, determining the real-time wheel load torque through a proportional integral observer, and controlling the motor torque according to the target speed, the actual speed and the real-time wheel load torque based on the active disturbance rejection controller, the drive anti-skid control method may further include:

[0110] Obtain the continuous anti-skid control flag position of the electric vehicle;

[0111] When the continuous anti-skid control flag is at a first value, it is determined that the electric vehicle enters the continuous anti-skid control stage, wherein the first value is a preset value indicating that the electric vehicle enters the continuous anti-skid control stage.

[0112] Specifically, in addition to judging whether the vehicle has entered the continuous anti-skid control stage based on the actual motor speed, it can also be judged based on the flag. That is, during the control process, the system can obtain the value of the continuous anti-skid control flag of the electric vehicle in real time, and judge whether the vehicle has entered the continuous anti-skid control stage by the value of the continuous anti-skid control flag. In practical applications, the continuous anti-skid control flag can be pre-set with a first value to indicate that the electric vehicle has entered the continuous anti-skid control stage, and a second value to indicate that the electric vehicle has not entered the continuous anti-skid control stage. In one example, the first value is 1 and the second value is 0. When the electric vehicle enters the continuous anti-skid control stage, the continuous anti-skid control flag is set to 1, and when the electric vehicle ends the anti-skid control, the anti-skid control flag is set to 0.

[0113] In some embodiments, the electric vehicle further includes an initial anti-skid control flag. Similarly, the initial anti-skid control flag may be pre-set with a first value for indicating that the electric vehicle has entered the initial anti-skid control stage, and a second value for indicating that the electric vehicle has not entered the initial anti-skid control stage. In one example, the first value is 1 and the second value is 0. When the electric vehicle enters the initial anti-skid control stage, the initial anti-skid control flag is set to 1. When the electric vehicle enters the continuous anti-skid control stage, the value of the initial anti-skid control flag remains unchanged, and the continuous anti-skid control flag is set to 1 until the electric vehicle ends the anti-skid control, and both the initial anti-skid control flag and the continuous anti-skid control flag are set to 0.

[0114] In some embodiments, when the electric vehicle is in a driving state, the driving anti-skid control method further includes:

[0115] Obtaining the actual speed of the electric vehicle;

[0116] The target speed of the motor is determined based on the transmission ratio between the wheels and the motor, the actual vehicle speed and the slip ratio.

[0117] Specifically, for different tire-road conditions, there is an optimal slip ratio that can achieve the maximum adhesion coefficient, thereby enabling the wheel to achieve maximum road adhesion. Therefore, after obtaining the actual speed of the electric vehicle, the target speed of the motor can be calculated according to formula (15):

[0118] ω0=V x ×i g ×(1+λ opt ) (15)

[0119] Where ω0 is the target speed of the motor, V x is the actual vehicle speed, i g is the transmission ratio from motor to wheel, λ opt is the best slip rate.

[0120] It should be noted that the various optional implementation modes introduced in the embodiments of the present application can be implemented in combination with each other or separately if they do not conflict with each other, and the embodiments of the present application are not limited to this.

[0121] For ease of understanding, a specific embodiment is used as an example for illustration:

[0122] like Figure 7 As shown, the driving anti-skid control method of an electric vehicle may include the following steps:

[0123] S1: Determine whether the anti-skid control is turned on, if so, go to step S2, if not, go to step S5;

[0124] S2: Determine whether it is the initial stage of anti-skid control, if yes, proceed to step S3, if no, proceed to step S4;

[0125] S3: ADRC control acts alone;

[0126] S4: ADRC and feedforward control work together;

[0127] S5: Anti-skid control does not work.

[0128] In this specific embodiment, the specific implementation can refer to the above description and will not be repeated here.

[0129] Based on the driving anti-skid control method provided in the above embodiment, the present application also provides a specific implementation of the driving anti-skid control device. Please refer to the following embodiment.

[0130] See also Figure 8 , is a structural diagram of a driving anti-skid control device provided in an embodiment of the present application, and the driving anti-skid control device may include:

[0131] An acquisition module 810 is used to acquire an actual rotation speed of a motor of the electric vehicle when the electric vehicle is in a driving state;

[0132] The initial anti-slip control module 820 is used to enter the initial anti-slip control stage when the actual speed is greater than the target speed, and generate a first motor torque control signal according to the target speed and the actual speed through an anti-disturbance controller, and the first motor torque control signal is used to control the motor torque;

[0133] The continuous anti-skid control module 830 is used to obtain the real-time wheel load torque when entering the continuous anti-skid control stage, and generate a second motor torque control signal according to the target speed, actual speed and real-time wheel load through an anti-disturbance control controller, and the second motor torque control signal is used to control the motor torque.

[0134] The driving anti-skid control device provided in the embodiment of the present application can achieve Figure 1 The various processes implemented by driving the anti-skid control device in the method embodiment will not be described again here to avoid repetition.

[0135] See also Fig. 9 , is a schematic diagram of the hardware structure of a drive anti-skid control provided in an embodiment of the present application.

[0136] The electric vehicle may include a processor 901 and a memory 902 storing computer program instructions.

[0137] Specifically, the processor 901 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0138] The memory 902 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 902 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 902 may include a removable or non-removable (or fixed) medium. In appropriate cases, the memory 902 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 902 is a non-volatile solid-state memory.

[0139] The memory may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Therefore, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of the present disclosure.

[0140] The processor 901 implements any one of the driving anti-skid control methods for an electric vehicle in the above embodiments by reading and executing computer program instructions stored in the memory 902 .

[0141] In one example, the electric vehicle may further include a communication interface 903 and a bus 910. Fig. 9 As shown, the processor 901, the memory 902, and the communication interface 903 are connected via a bus 910 and communicate with each other.

[0142] The communication interface 903 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0143] Bus 910 includes hardware, software or both, and couples the components of the electric vehicle to each other. For example, but not limitation, the bus may include an accelerated graphics port (AGP) or other graphics bus, an enhanced industrial standard architecture (EISA) bus, a front-end bus (FSB), a hypertransport (HT) interconnect, an industrial standard architecture (ISA) bus, an infinite bandwidth interconnect, a low pin count (LPC) bus, a memory bus, a microchannel architecture (MCA) bus, a peripheral component interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA) bus, a video electronics standard association local (VLB) bus or other suitable bus or a combination of two or more of these. Where appropriate, bus 910 may include one or more buses. Although the present application embodiment describes and shows a specific bus, the present application considers any suitable bus or interconnect.

[0144] In addition, in combination with the anti-skid control method for driving an electric vehicle in the above embodiments, the embodiment of the present application can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when the computer program instructions are executed by the processor, any of the anti-skid control methods for driving an electric vehicle in the above embodiments is implemented.

[0145] It should be clear that the present application is not limited to the specific configuration and processing described above and shown in the figures. For the sake of simplicity, a detailed description of the known method is omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps after understanding the spirit of the present application.

[0146] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0147] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps, that is, the steps can be performed in the order mentioned in the embodiment, or in a different order from the embodiment, or several steps can be performed simultaneously.

[0148] Aspects of the present disclosure are described above with reference to the flowchart and / or block diagram of the method, device (system) and computer program product according to the embodiment of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box 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, or other programmable data processing device to produce a machine so that these instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field programmable logic circuit. It can also be understood that each box in the block diagram and / or flowchart and the combination of boxes in the block diagram and / or flowchart can also be implemented by dedicated hardware that performs a specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0149] The above is only a specific implementation of the present application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the protection scope of the present application is not limited to this. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be included in the protection scope of this application.

Claims

1. A driving anti-skid control method for an electric vehicle, characterized in that: include: When the electric vehicle is in a driving state, obtaining an actual rotation speed of a motor of the electric vehicle; When the actual speed is greater than the target speed, an initial anti-slip control stage is entered, and a first motor torque control signal is generated according to the target speed and the actual speed by an active disturbance rejection controller, wherein the first motor torque control signal is used to control the motor torque; When entering the continuous anti-slip control stage, the real-time wheel load torque is obtained, and the second motor torque control signal is generated by the active disturbance rejection controller according to the target speed, the actual speed and the real-time wheel load, and the second motor torque control signal is used to control the motor torque.

2. The driving anti-skid control method according to claim 1, characterized in that: The generating a second motor torque control signal according to the target speed, the actual speed and the real-time wheel load by the active disturbance rejection controller includes: Based on the real-time wheel load torque, adjusting a speed factor of a differential tracker of the active disturbance rejection controller; Based on the adjusted active disturbance rejection controller, determining a feedback control amount according to the target speed and the actual speed; Determining a target feedforward control amount based on the real-time wheel load torque; Adding the feedback control amount and the feedforward control amount to obtain a target control amount; The second motor torque control signal is generated according to the target control amount.

3. The driving anti-skid control method according to claim 2, characterized in that: The determining of the target feedforward control amount based on the real-time wheel load torque comprises: Obtain the feedforward control value at the k-1th moment, where k is a positive integer greater than 1; Determine the difference between the feedforward control amount at the k-1th moment and the real-time wheel load torque; When the difference is within the first interval, determining the real-time load torque as the target feedforward control amount; When the difference is outside the first interval, the feedforward control amount at the kth moment is obtained by using the feedforward control amount at the k-1th moment and the preset step size; and the target feedforward control amount is determined based on the feedforward control amount at the kth moment or the real-time wheel load torque.

4. The driving anti-skid control method according to claim 3, characterized in that: The determining the target feedforward control amount based on the feedforward control amount at the kth moment or the real-time wheel load torque comprises: Comparing the feedforward control amount at the k-1th moment with the real-time wheel load torque; In the case where the feedforward control amount at the k-1th moment is less than the real-time wheel load torque, the smaller value of the feedforward control amount at the k-1th moment and the real-time wheel load torque is determined as the target feedforward control amount, wherein the feedforward control amount at the k-1th moment is the sum of the feedforward control amount at the k-1th moment and the preset step size; When the feedforward control amount at the k-1th moment is greater than or equal to the real-time wheel load torque, the larger value of the feedforward control amount at the kth moment and the real-time wheel load torque is determined as the target feedforward control amount, wherein the feedforward control amount at the kth moment is the difference between the feedforward control amount at the k-1th moment and the preset step size.

5. The driving anti-skid control method according to claim 1, characterized in that: After the active disturbance rejection controller generates the first motor torque control signal according to the target speed and the actual speed, and before the active disturbance rejection controller generates the second motor torque control signal according to the target speed, the actual speed and the real-time wheel load, the driving anti-skid control method further includes: When the actual speed is in the second interval and the acceleration of the motor is positive, determining that the electric vehicle enters a continuous anti-skid control stage; The first end value of the second interval is the target speed, and the second end value of the second interval is the difference between the target speed and the preset deviation.

6. The driving anti-skid control method according to claim 1, characterized in that: After the active disturbance rejection controller controls the motor torque according to the target speed and the actual speed, after the active disturbance rejection controller generates a first motor torque control signal according to the target speed and the actual speed, and before the active disturbance rejection controller generates a second motor torque control signal according to the target speed, the actual speed and the real-time wheel load, the drive anti-slip control method further includes: Obtaining a continuous anti-skid control flag position of the electric vehicle; When the continuous anti-skid control flag is a first value, it is determined that the electric vehicle enters a continuous anti-skid control stage, wherein the first value is a preset value indicating that the electric vehicle enters a continuous anti-skid control stage.

7. The driving anti-skid control method according to claim 1, characterized in that: When the electric vehicle is in a driving state, the driving anti-skid control method further includes: Obtaining an actual speed of the electric vehicle; The target rotation speed of the motor is determined according to the transmission ratio between the wheels and the motor, the actual vehicle speed and the slip ratio.

8. A driving anti-skid control device for an electric vehicle, characterized in that: The driving anti-skid control device comprises: An acquisition module, used for acquiring an actual rotation speed of a motor of the electric vehicle when the electric vehicle is in a driving state; an initial anti-slip control module, configured to enter an initial anti-slip control phase when the actual speed is greater than the target speed, and generate a first motor torque control signal according to the target speed and the actual speed through an active disturbance rejection controller, wherein the first motor torque control signal is used to control the motor torque; The continuous anti-skid control module is used to obtain the real-time wheel load torque when entering the continuous anti-skid control stage, and generate a second motor torque control signal according to the target speed, the actual speed and the real-time wheel load through the active disturbance rejection controller, wherein the second motor torque control signal is used to control the motor torque.

9. An electric vehicle, characterized in that: The electric vehicle includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the driving anti-skid control method for an electric vehicle as described in any one of claims 1-7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the driving anti-skid control method for an electric vehicle as described in any one of claims 1 to 7 is implemented.

11. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the driving anti-skid control method for an electric vehicle as described in any one of claims 1 to 7.

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