Electric vehicle driving anti-skid control system and control method

Abstract

The present invention discloses an electric vehicle drive anti-skid control system and control method, comprising obtaining a pre-collected wheel speed signal and a vehicle speed signal, calculating and obtaining a slip rate and a slip rate change rate; judging whether the slip rate change rate is greater than a pre-set threshold value; when a condition is met, judging to enter a logic threshold value control and a fuzzy combined control mode; if the condition is not met within a set interval time, judging to enter a logic threshold value control mode; in the logic threshold value control mode, calculating and obtaining a torque adjustment coefficient; in the fuzzy combined control mode, calculating and obtaining an additional adjustment coefficient; and obtaining a final torque adjustment coefficient by calculating the torque adjustment coefficient and the additional adjustment coefficient for drive anti-skid adjustment. The present invention can achieve a stable control effect, i.e., it takes into account the stability of simple logic threshold value adjustment and also includes adjustment characteristics for complex working conditions.

Description

Technical Field

[0001] The invention relates to an electric vehicle driving anti-skid control system and a control method, belonging to the technical field of passenger vehicles and engineering machinery vehicles. Background Art

[0002] With the continuous depletion of resources like oil and natural gas, and the increasing severity of environmental pollution, people have gradually developed a variety of electric and hybrid vehicles to address resource depletion and environmental damage. Electric vehicles offer outstanding advantages, including zero emissions and zero pollution, and significantly improve power and economy over traditional fuel vehicles.

[0003] Traditional series hybrid vehicles (HEVs) use an engine-generator set to generate electricity, which is then rectified and filtered to generate DC power. This power is then driven by a variety of configurations, including centralized drive, bridge drive, and distributed drive. Although HEVs utilize electrical energy, this energy is generated by the engine burning diesel, which is not energy-efficient and environmentally friendly. Pure electric vehicles, which use batteries as their sole power source, offer inherent advantages in energy conservation and environmental protection. Under certain operating conditions, energy recovery can significantly reduce vehicle operating costs. Similar to fuel-powered vehicles, the anti-skid performance of electric vehicles is also related to vehicle dynamics and stability. When operating on low-grip surfaces, the high torque of the motor at low speed can easily cause wheel slip, causing the tire's lateral adhesion characteristics to enter the nonlinear region, leading to side slip and a sharp decrease in stability. Improving the vehicle's anti-skid performance through motor torque control is currently a hot topic of research.

[0004] The shaft-driven electric vehicle anti-skid control system proposed in the Chinese patent application with patent number 201010133357.9 intervenes by applying mechanical braking torque in the medium and low speed stages, which increases the energy consumption of the entire vehicle. The motor torque adjustment process is too simple and the accuracy is not high.

[0005] Chinese patent application No. 201410568284.4 proposes a differential fuzzy combined control method for anti-skid driving of electric vehicles. The method uses a differential controller to adjust the vibration effect of the fuzzy control output. However, when the wheel is in a nonlinear state, the differential calculation is not very accurate and sometimes there will be a huge overshoot, leading to system instability.

[0006] The Chinese patent application with patent number 201810943271.9 proposes a drive anti-skid control method and system for a pure electric vehicle. The method judges the vehicle slip state by comparing the speed change rate value range obtained through experience with the actual speed change rate. This does not necessarily match the characteristics of the vehicle itself, and does not provide a specific torque adjustment process. Summary of the Invention

[0007] The purpose of the present invention is to overcome the deficiencies in the prior art and provide an electric vehicle drive anti-skid control system and control method that can achieve a stable control effect, that is, taking into account the stability of simple logic threshold value adjustment and also including the adjustment characteristics for complex working conditions.

[0008] To achieve the above object, the present invention is implemented by adopting the following technical solutions:

[0009] In the first aspect, the present invention provides an electric vehicle drive anti-skid control system, comprising: a gearbox, a wheel speed sensor, a GPS navigation, a five-in-one driver, a vehicle controller, a motor controller, and a drive motor. The drive motor is directly connected to the gearbox, and the main drive shaft of the gearbox is connected to the middle and rear axles of the vehicle to transmit power. The wheel speed sensor is installed on one side of the tire on one side of the middle axle, the GPS navigation is installed at the front end of the vehicle cab, the vehicle controller is placed in the cab, and the motor controller is arranged in the five-in-one driver.

[0010] Furthermore, the wheel speed sensor is a Hall sensor installed at the wheel end, which is used to feed back the wheel speed signal.

[0011] Furthermore, the GPS navigation uses a global positioning system to collect vehicle speed signals obtained by satellite positioning.

[0012] In a second aspect, the present invention provides a control method for an electric vehicle drive anti-skid control system according to any one of the aforementioned items, characterized in that the control method is applied to a vehicle controller, and comprises:

[0013] Obtaining pre-collected wheel speed signals and vehicle speed signals, and calculating the slip rate and slip rate change rate;

[0014] When the vehicle speed is greater than a set threshold, a timer is started, and within a set interval, it is determined whether the slip rate change rate is greater than a pre-set threshold; if the condition is met, the logic threshold control and fuzzy combined control modes are entered; if the condition is not met within the set interval, the logic threshold control mode is entered, wherein each time the timer passes the set interval, it constitutes a cycle, and the control mode is changed in real time according to the slip rate change rate;

[0015] In the logic threshold control mode, set the upper and lower limits of the slip rate and calculate the torque adjustment coefficient;

[0016] In the fuzzy joint control mode, the slip rate and wheel acceleration are used as the input of the fuzzy controller, and the additional adjustment coefficient Φ2 is finally obtained by fuzzification language and formulation of fuzzy rules;

[0017] The final torque adjustment coefficient is calculated by the torque adjustment coefficient and the additional adjustment coefficient and is used for driving anti-slip adjustment.

[0018] Furthermore, the method of obtaining the pre-collected wheel speed signal and vehicle speed signal and calculating the slip rate and slip rate change rate includes: the vehicle controller collects the wheel speed signal of the wheel speed sensor and the vehicle speed signal of the GPS navigation, and calculates the slip rate by the slip rate calculation formula Get the slip rate , and the derivative is the slip rate change rate .

[0019] Furthermore, in the logic threshold control mode, the upper and lower limits of the slip rate are set and the torque adjustment coefficient is calculated, including:

[0020] Set the upper limit of slip rate and slip rate lower limit ;

[0021] When the actual slip rate Greater than the upper limit , indicating that the vehicle is in a serious slip state at this time, and the torque adjustment coefficient Φ1=0;

[0022] When the actual slip rate Less than the lower limit , indicating that the vehicle is in a non-slip state, and the torque adjustment coefficient Φ1=1;

[0023] When the actual slip rate is between the upper and lower limits, use the formula Φ1= The torque adjustment coefficient Φ1 at this time is calculated;

[0024] Assuming that the original driving torque of the motor is T, the adjusted torque output in the logic threshold control mode is Teq=T*Φ1.

[0025] Furthermore, the calculation of the final torque adjustment coefficient by the torque adjustment coefficient and the additional adjustment coefficient for driving anti-slip adjustment includes:

[0026] When the vehicle slip rate change rate is detected within the set timer time, Greater than a fixed threshold , judge that the vehicle is in the logic threshold value and fuzzy joint control mode, Φ3=Φ1-Φ2;

[0027] When the slip rate changes more, the wheel tends to slip rapidly. By adding fuzzy control on the basis of logic threshold control, the necessary motor force is applied to achieve rapid drive anti-slip; the formula for calculating the vehicle torque is Teq2=T*Φ3.

[0028] In a third aspect, the present invention provides an electric vehicle driving anti-skid control device, comprising:

[0029] a first calculation unit, configured to obtain a pre-collected wheel speed signal and a vehicle speed signal, and calculate a slip rate and a slip rate change rate;

[0030] a judgment unit, configured to start a timer when the vehicle speed is greater than a set threshold, and determine whether the slip rate change rate is greater than a preset threshold within a set interval; if the condition is met, determine to enter a logic threshold control mode and a fuzzy combined control mode; if the condition is not met within the set interval, determine to enter a logic threshold control mode, wherein each time the timer passes the set interval, it constitutes a cycle, and the control mode is changed in real time according to the slip rate change rate;

[0031] The second calculation unit is used to set the upper limit and lower limit of the slip rate in the logic threshold control mode and calculate the torque adjustment coefficient;

[0032] The third calculation unit is used to use the slip rate and wheel acceleration as the input of the fuzzy controller in the fuzzy joint control mode, and finally defuzzify the additional adjustment coefficient by fuzzifying the language and formulating the fuzzy rules;

[0033] The calculation and adjustment unit is used to calculate the final torque adjustment coefficient through the torque adjustment coefficient and the additional adjustment coefficient, which is used for driving anti-slip adjustment.

[0034] In a fourth aspect, the present invention provides an electric vehicle driving anti-skid control device, comprising a processor and a storage medium;

[0035] The storage medium is used to store instructions;

[0036] The processor is configured to operate according to the instructions to execute the steps of any of the aforementioned methods.

[0037] In a fifth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of any of the aforementioned methods when executed by a processor.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] The present invention provides an electric vehicle drive anti-skid control system and control method. First, a fixed logical threshold value is set to obtain a torque adjustment coefficient Φ1 to adjust the torque of the vehicle drive motor, and then an additional adjustment coefficient Φ2 is obtained through a fuzzy controller. Then, according to different working conditions, it is determined whether the drive anti-skid control mode is a logical threshold value and fuzzy combined control or a logical threshold alone control. The final adjustment coefficient is calculated to cope with the drive anti-skid adjustment under complex working conditions. Stability adjustment in a stable slip state is ensured while taking into account rapid response under complex working conditions. The control system accuracy and reliability are increased, and the control response time is reduced. Through the combined control of logical threshold values ​​and fuzzy values, the stability of nonlinear systems is improved, the control accuracy is higher, and the system response time is shortened. By setting a timer, system oscillation caused by singular points is avoided, thereby increasing the stability and reliability of the control system. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a diagram of a vehicle electric drive system provided by an embodiment of the present invention;

[0041] Figure 2 is a block diagram of a control system provided by an embodiment of the present invention;

[0042] Figure 3 This is a logic threshold control block diagram provided by an embodiment of the present invention;

[0043] Figure 4 This is a fuzzy control block diagram provided by an embodiment of the present invention.

[0044] In the figure: 1. Drive motor; 2. Gearbox; 3. Battery box; 4. Wheel speed sensor; 5. GPS navigation; 6. Five-in-one driver; 7. Vehicle controller. DETAILED DESCRIPTION

[0045] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention.

[0046] Example 1

[0047] like Figure 1 、 Figure 2As shown, this embodiment introduces an electric vehicle drive anti-skid control system, including a battery box 3, a gearbox 2, a wheel speed sensor 4, a GPS navigation 5, a five-in-one driver 6, a vehicle controller 7, a motor controller, and a drive motor 1. The drive motor 1 is directly connected to the gearbox 2, and the drive motor 1 is a permanent magnet synchronous dual motor. The main drive shaft of the gearbox 2 is connected to the middle and rear axles of the vehicle to transmit power. The gearbox 2 is an AMT 4-speed gearbox. The wheel speed sensor 4 is installed on the side of the tire on the side of the middle bridge. The GPS navigation 5 is installed at the front end of the vehicle cab. The vehicle controller 7 is placed in the cab. The motor controller and other accessory units of the vehicle are integrated in the five-in-one driver 6.

[0048] The battery box 3 is used to provide high-voltage power to the motor drive. The wheel speed sensor 4 is a Hall effect sensor installed at the wheel end, which provides feedback on the wheel speed signal. The GPS, a global positioning system, collects vehicle speed signals calculated through satellite positioning.

[0049] Example 2

[0050] This embodiment provides a control method for an electric vehicle driving anti-skid control system according to any one of Embodiment 1, which is applied to a vehicle controller. The control method includes:

[0051] Obtaining pre-collected wheel speed signals and vehicle speed signals, and calculating the slip rate and slip rate change rate;

[0052] When the vehicle speed is greater than a set threshold, a timer is started, and within a set interval, it is determined whether the slip rate change rate is greater than a pre-set threshold; if the condition is met, the logic threshold control and fuzzy combined control modes are entered; if the condition is not met within the set interval, the logic threshold control mode is entered, wherein each time the timer passes the set interval, it constitutes a cycle, and the control mode is changed in real time according to the slip rate change rate;

[0053] In the logic threshold control mode, set the upper and lower limits of the slip rate and calculate the torque adjustment coefficient;

[0054] In the fuzzy joint control mode, the slip rate and wheel acceleration are used as the input of the fuzzy controller, and the additional adjustment coefficient Φ2 is finally obtained by fuzzification language and formulation of fuzzy rules;

[0055] The final torque adjustment coefficient is calculated by the torque adjustment coefficient and the additional adjustment coefficient and is used for driving anti-slip adjustment.

[0056] Specifically, the method of obtaining the pre-collected wheel speed signal and vehicle speed signal and calculating the slip rate and slip rate change rate includes: the vehicle controller collects the wheel speed signal of the wheel speed sensor and the vehicle speed signal of the GPS navigation, and calculates the slip rate by the slip rate calculation formula Get the slip rate , and the derivative is the slip rate change rate .

[0057] Specifically, in the logic threshold control mode, the upper and lower limits of the slip rate are set, and the torque adjustment coefficient is calculated, including:

[0058] Set the upper limit of slip rate and slip rate lower limit ;

[0059] When the actual slip rate Greater than the upper limit , indicating that the vehicle is in a serious slip state at this time, and the torque adjustment coefficient Φ1=0;

[0060] When the actual slip rate Less than the lower limit , indicating that the vehicle is in a non-slip state, and the torque adjustment coefficient Φ1=1;

[0061] When the actual slip rate is between the upper and lower limits, use the formula Φ1= The torque adjustment coefficient Φ1 at this time is calculated;

[0062] Assuming that the original driving torque of the motor is T, the adjusted torque output in the logic threshold control mode is Teq=T*Φ1.

[0063] Specifically, the calculation of the final torque adjustment coefficient by the torque adjustment coefficient and the additional adjustment coefficient for driving anti-slip adjustment includes:

[0064] When the vehicle slip rate change rate is detected within the set timer time, Greater than a fixed threshold , judge that the vehicle is in the logic threshold value and fuzzy joint control mode, Φ3=Φ1-Φ2;

[0065] When the slip rate changes more, the wheel tends to slip rapidly. By adding fuzzy control on the basis of logic threshold control, the necessary motor force is applied to achieve rapid drive anti-slip; the formula for calculating the vehicle torque is Teq2=T*Φ3.

[0066] The following describes the contents designed in the above embodiment in conjunction with a preferred embodiment.

[0067] The vehicle controller collects the wheel speed signal 4 from the wheel speed sensor and the vehicle speed signal from the GPS navigation 5, and calculates the slip rate using the formula Get the slip rate , and the derivative is the slip rate change rate When the vehicle speed is greater than 5km / h, start the timer and judge the slip rate change rate within 30s Is it greater than a fixed threshold? If the conditions are met, the vehicle controller 7 determines whether to enter the logic threshold control mode or the fuzzy combined control mode. If the above conditions are not met within 2 seconds, the vehicle controller enters the logic threshold control mode. The timer loops every 2 seconds and changes the control mode in real time according to the slip rate change rate.

[0068] Among them, the logic threshold control mode, such as Figure 3 Set the upper limit of slip rate and slip rate lower limit When the actual slip rate Greater than the upper limit , indicating that the vehicle is in a serious slip state, the torque adjustment coefficient Φ1=0; when the actual slip rate Less than the lower limit , indicating that the vehicle is in a non-slip state, and the torque adjustment coefficient Φ1=1; when the actual slip rate is between the upper and lower limits, the formula Φ1= The torque adjustment coefficient Φ1 is calculated. Assuming that the original driving torque of the motor is T, the adjusted torque output in the logic threshold control mode is Teq=T*Φ1.

[0069] Furthermore, fuzzy control modes such as Figure 4 As shown. Design a fuzzy controller with the input variable being the slip rate and wheel acceleration , the output is the additional adjustment coefficient Φ2. Slip rate The fuzzy subset is [VS, S, M, B, VB], the domain is [0,1], and the wheel acceleration The fuzzy subset of is [VS, MS, S, M, B, MB, VB], and the domain is [0, 200]. The fuzzy subset of the additional adjustment coefficient Φ2 is [VS, MS, S, M, B, MB, VB], and the domain is [0 0.3]. The trigonometric function membership of Φ2 and the fuzzy rule table of the controller are established as follows:

[0070] Table 1 Membership degree of Φ2

[0071]

[0072] Table 2 Fuzzy rule table

[0073]

[0074] When the vehicle slip rate change rate is detected within the set timer time, Greater than a fixed threshold , determining whether the vehicle is in a combined logic threshold and fuzzy control mode, Φ3 = Φ1 - Φ2. A greater change in slip rate indicates a tendency for rapid wheel slip. By adding fuzzy control to logic threshold control, the necessary motor force is applied to achieve rapid anti-slip driving. The formula for calculating vehicle torque is Teq2 = T * Φ3.

[0075] Beneficial effects brought by the technical solution of the present invention

[0076] A drive anti-slip control method for electric vehicles combines logic thresholds and fuzzy control. First, a fixed logic threshold is set to determine the torque adjustment coefficient Φ1 to adjust the vehicle's drive motor torque. A fuzzy controller is then used to derive an additional adjustment coefficient Φ2. Depending on the operating conditions, the method determines whether to use a combination of logic thresholds and fuzzy control or logic threshold control alone. The final adjustment coefficient is calculated to address drive anti-slip control under complex operating conditions.

[0077] It ensures stability adjustment under smooth sliding state, while taking into account rapid response under complex working conditions.

[0078] Increase control system accuracy and reliability, and reduce control response time. Through the combination of logic threshold and fuzzy control, the stability of nonlinear systems is higher, the control accuracy is higher, and the system response time is shorter.

[0079] By setting the timer, the oscillation of the system due to singular points is avoided, and the stability and reliability of the control system are increased.

[0080] Example 3

[0081] This embodiment provides an electric vehicle driving anti-skid control device, comprising:

[0082] a first calculation unit, configured to obtain a pre-collected wheel speed signal and a vehicle speed signal, and calculate a slip rate and a slip rate change rate;

[0083] a judgment unit, configured to start a timer when the vehicle speed is greater than a set threshold, and determine whether the slip rate change rate is greater than a preset threshold within a set interval; if the condition is met, determine to enter a logic threshold control mode and a fuzzy combined control mode; if the condition is not met within the set interval, determine to enter a logic threshold control mode, wherein each time the timer passes the set interval, it constitutes a cycle, and the control mode is changed in real time according to the slip rate change rate;

[0084] The second calculation unit is used to set the upper limit and lower limit of the slip rate in the logic threshold control mode and calculate the torque adjustment coefficient;

[0085] The third calculation unit is used to use the slip rate and wheel acceleration as the input of the fuzzy controller in the fuzzy joint control mode, and finally defuzzify the additional adjustment coefficient by fuzzifying the language and formulating the fuzzy rules;

[0086] The calculation and adjustment unit is used to calculate the final torque adjustment coefficient through the torque adjustment coefficient and the additional adjustment coefficient, which is used for driving anti-slip adjustment.

[0087] Example 4

[0088] This embodiment provides an electric vehicle driving anti-skid control device, including a processor and a storage medium;

[0089] The storage medium is used to store instructions;

[0090] The processor is configured to operate according to the instructions to execute the steps of the method according to any one of Embodiment 2.

[0091] Example 5

[0092] This embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the steps of any one of the methods described in Embodiment 2 are implemented.

[0093] The present invention proposes using Hall wheel speed sensors and GPS to acquire vehicle signal information. Alternatively, CAN message collection or other remote positioning systems can be used, and this also falls within the scope of protection of this patent. The specific implementation of logic threshold and fuzzy combined control uses slip rate change and wheel acceleration to determine the control mode, which is one specific embodiment. Other signals such as vehicle speed, acceleration, slip rate, or a combination of different signals can also be used. As long as the logic threshold and fuzzy combined control mode are used, they fall within the scope of protection of this patent.

[0094] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An electric vehicle drive anti-skid control system, characterized in that: include: Gearbox, wheel speed sensor, GPS navigation, five-in-one driver, vehicle controller, motor controller, drive motor, the drive motor is directly connected to the gearbox, the gearbox main drive shaft is connected to the vehicle's middle and rear axles to transmit power, the gearbox is an AMT 4-speed gearbox, the wheel speed sensor is installed on one side of the tire on one side of the middle axle, the GPS navigation is installed at the front end of the vehicle cab, the vehicle controller is placed in the cab, and the motor controller is set in the five-in-one driver; The vehicle controller is used to execute the following control method: Obtain the pre-collected wheel speed signal and vehicle speed signal, calculate the slip rate and slip rate change rate; including: the vehicle controller collects the wheel speed signal of the wheel speed sensor and the vehicle speed signal of the GPS navigation, and calculates the slip rate through the slip rate calculation formula Get the slip rate , and the derivative is the slip rate change rate ; When the vehicle speed is greater than a set threshold, a timer is started, and within a set interval, it is determined whether the slip rate change rate is greater than a pre-set threshold; if the condition is met, the logic threshold control and fuzzy combined control modes are entered; if the condition is not met within the set interval, the logic threshold control mode is entered, wherein each time the timer passes the set interval, it constitutes a cycle, and the control mode is changed in real time according to the slip rate change rate; In the logic threshold control mode, set the upper and lower limits of the slip rate and calculate the torque adjustment coefficient; including: Set the upper limit of slip rate and slip rate lower limit ; When the actual slip rate Greater than the upper limit , indicating that the vehicle is in a serious slip state at this time, and the torque adjustment coefficient Φ1=0; When the actual slip rate Less than the lower limit , indicating that the vehicle is in a non-slip state, and the torque adjustment coefficient Φ1=1; When the actual slip rate is between the upper and lower limits, use the formula Φ1= The torque adjustment coefficient Φ1 at this time is calculated; Assuming that the original driving torque of the motor is T, the adjusted torque output in the logic threshold control mode is Teq=T*Φ1; In the fuzzy joint control mode, the slip rate and wheel acceleration are used as the input of the fuzzy controller, and the additional adjustment coefficient Φ2 is finally obtained by fuzzification language and formulation of fuzzy rules; The final torque adjustment coefficient is calculated by the torque adjustment coefficient and the additional adjustment coefficient, and is used for driving anti-slip adjustment, including: When the vehicle slip rate change rate is detected within the set timer time, Greater than a fixed threshold , judge that the vehicle is in the logic threshold value and fuzzy joint control mode, Φ3=Φ1-Φ2; When the slip rate changes more, the wheel tends to slip rapidly. By adding fuzzy control on the basis of logic threshold control, the necessary motor force is applied to achieve rapid drive anti-slip; the formula for calculating the vehicle torque is Teq2=T*Φ3.

2. The electric vehicle driving anti-skid control system according to claim 1, characterized in that: The wheel speed sensor is a Hall sensor installed at the wheel end, which is used to feed back the wheel speed signal.

3. The electric vehicle driving anti-skid control system according to claim 1, characterized in that: The GPS navigation uses a global positioning system to collect vehicle speed signals obtained by satellite positioning.

4. A control method for an electric vehicle drive anti-skid control system, characterized in that: Applied to a vehicle controller, the control method includes: Obtain the pre-collected wheel speed signal and vehicle speed signal, calculate the slip rate and slip rate change rate; including: the vehicle controller collects the wheel speed signal of the wheel speed sensor and the vehicle speed signal of the GPS navigation, and calculates the slip rate through the slip rate calculation formula Get the slip rate , and the derivative is the slip rate change rate ; When the vehicle speed is greater than a set threshold, a timer is started, and within a set interval, it is determined whether the slip rate change rate is greater than a pre-set threshold; if the condition is met, the logic threshold control and fuzzy combined control modes are entered; if the condition is not met within the set interval, the logic threshold control mode is entered, wherein each time the timer passes the set interval, it constitutes a cycle, and the control mode is changed in real time according to the slip rate change rate; In the logic threshold control mode, set the upper and lower limits of the slip rate and calculate the torque adjustment coefficient; including: Set the upper limit of slip rate and slip rate lower limit ; When the actual slip rate Greater than the upper limit , indicating that the vehicle is in a serious slip state at this time, and the torque adjustment coefficient Φ1=0; When the actual slip rate Less than the lower limit , indicating that the vehicle is in a non-slip state, and the torque adjustment coefficient Φ1=1; When the actual slip rate is between the upper and lower limits, use the formula Φ1= The torque adjustment coefficient Φ1 at this time is calculated; Assuming that the original driving torque of the motor is T, the adjusted torque output in the logic threshold control mode is Teq=T*Φ1; In the fuzzy joint control mode, the slip rate and wheel acceleration are used as the input of the fuzzy controller, and the additional adjustment coefficient Φ2 is finally obtained by fuzzification language and formulation of fuzzy rules; The final torque adjustment coefficient is calculated by the torque adjustment coefficient and the additional adjustment coefficient, and is used for driving anti-slip adjustment, including: When the vehicle slip rate change rate is detected within the set timer time, Greater than a fixed threshold , judge that the vehicle is in the logic threshold value and fuzzy joint control mode, Φ3=Φ1-Φ2; When the slip rate changes more, the wheel tends to slip rapidly. By adding fuzzy control on the basis of logic threshold control, the necessary motor force is applied to achieve rapid drive anti-slip; the formula for calculating the vehicle torque is Teq2=T*Φ3.

5. An electric vehicle driving anti-skid control device, using the method according to claim 4, characterized in that: include: a first calculation unit, configured to obtain a pre-collected wheel speed signal and a vehicle speed signal, and calculate a slip rate and a slip rate change rate; a judgment unit, configured to start a timer when the vehicle speed is greater than a set threshold, and determine whether the slip rate change rate is greater than a preset threshold within a set interval; if the condition is met, determine to enter a logic threshold control mode and a fuzzy combined control mode; if the condition is not met within the set interval, determine to enter a logic threshold control mode, wherein each time the timer passes the set interval, it constitutes a cycle, and the control mode is changed in real time according to the slip rate change rate; The second calculation unit is used to set the upper limit and lower limit of the slip rate in the logic threshold control mode and calculate the torque adjustment coefficient; The third calculation unit is used to use the slip rate and wheel acceleration as the input of the fuzzy controller in the fuzzy joint control mode, and finally defuzzify the additional adjustment coefficient by fuzzifying the language and formulating the fuzzy rules; The calculation and adjustment unit is used to calculate the final torque adjustment coefficient through the torque adjustment coefficient and the additional adjustment coefficient, which is used for driving anti-slip adjustment.

6. An electric vehicle driving anti-skid control device, characterized by: including processor and storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to claim 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to claim 4 are implemented.

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