Anti-skid control method, device and system for distributed wheel edge drive loader

Abstract

The invention discloses an anti-skid control method, device and system for a distributed wheel edge drive loader. The anti-skid control method comprises the steps that the current whole vehicle speed is estimated based on the obtained longitudinal acceleration of the loader, the measured vehicle speed of the loader and the rotating speed of each wheel edge motor; calculating the whole vehicle speed corresponding to the rotating speed of each wheel-side motor based on the rotating speed of each wheel-side motor; calculating the actual slip rate of each wheel based on the estimated current vehicle speed and the vehicle speed corresponding to the rotating speed of each wheel motor; estimating the current optimal slip rate based on the response speed of each wheel-side motor; when it is judged that a certain wheel slips on the basis of the actual slip rate and the current optimal slip rate, the anti-slip demand torque is calculated on the basis of the actual slip rate, the current optimal slip rate and the demand torque of the slipped wheel and an anti-slip algorithm, and the anti-slip demand torque is sent to a wheel edge motor corresponding to the slipped wheel. The maximum driving capacity of the loader can be achieved under the condition that it is guaranteed that the loader does not slip, and the running reliability of the loader on the road surface with the low adhesion coefficient is improved.

Description

Technical Field

[0001] The present invention belongs to the field of engineering machinery power domain drive, and in particular relates to an anti-skid control method, device and system for a distributed wheel-side drive loader. Background Art

[0002] With the popularization of new energy technologies in loading vehicles, distributed wheel-side drives are being widely used in loading vehicles. Due to the complex and diverse road conditions of loading vehicles, when loaders are operating on muddy roads and other roads with low road adhesion coefficients and when the load of the loader is unevenly distributed, the wheel-side motor is prone to slippage.

[0003] In the Chinese invention patent application with application number 202010005558.4, a train anti-skid control method and an anti-skid control device are disclosed, which relate to the field of rail transit technology. Among them, the above-mentioned train anti-skid control method includes: monitoring the real-time rotation speed of each axle of the train during the braking process of the train; initializing the reference speed of the train; based on the real-time rotation speed of each axle of the train and the current reference speed, performing a sliding judgment of each axle by the creep rate method or the speed difference method, and obtaining the first judgment result of each axle; based on the real-time rotation speed of each axle, performing a sliding judgment of each axle by the deceleration method, and obtaining the second judgment result of each axle; combining the first judgment result and the second judgment result of each axle, respectively determine the final sliding judgment result of each axle; based on the final sliding judgment result of each axle, the braking system of the train is anti-skid controlled, which is conducive to improving the accuracy of train anti-skid control. However, this scheme relies too much on the axle speed, and judges whether the vehicle is slipping by the difference in the speed of each axle. It is impossible to judge and control the situation of the vehicle when all the axles are slipping.

[0004] In the Chinese invention patent application with application number 201910084487.9, a multi-layer drive anti-skid control method suitable for electric wheel drive vehicles is disclosed, including: step 1, determining a first active drive anti-skid control torque according to an optimization objective function, and distributing wheel torque according to the first active drive anti-skid control torque; step 2, comparing the actual slip rate of the drive wheel with the target slip rate; when the actual slip rate is not less than the target slip rate, determining the second active drive anti-skid control torque of the wheel and the passive drive anti-skid control torque of the wheel; and when the actual slip rate is less than the target slip rate, repeating step 1; step 3, obtaining a third active drive anti-skid control torque according to the second active drive anti-skid control torque and the passive drive anti-skid control torque, and distributing wheel torque according to the third active drive anti-skid control torque. This solution requires the installation of a high-definition camera, which is extremely costly, and the road adhesion algorithm is complex.

[0005] In the Chinese invention patent application with application number 201710135260.3, a distributed drive electric vehicle road adaptive anti-skid control system and method are disclosed. The system includes a motor controller, a motor torque distributor, a measured sensor unit, a nonlinear road estimation unit, an anti-skid control selective access unit and a drive anti-skid control unit. The nonlinear road estimation unit is used to obtain the peak road adhesion coefficient of each wheel. The drive anti-skid control unit performs anti-skid control and outputs the control torque according to the peak road adhesion coefficient of the wheel obtained by the nonlinear road estimation unit and the measured data of the measured sensor unit. The anti-skid control selective access unit performs logical judgment according to the output control torque of the drive anti-skid control unit, the distributed torque of the motor torque distributor and the measured data of the measured sensor unit, and then outputs the control torque or distributes the torque to the motor controller. The motor controller controls the movement of four drive motors. Compared with the prior art, the present invention has high control accuracy and good anti-skid effect. The scheme adopts sliding film variable structure control, and the control logic is complex and cannot be used for engineering applications. In addition, the invention is overly dependent on the speed of the wheel-side motor, and judges whether the vehicle is skidding by the difference in the speed of each wheel-side motor. It is impossible to judge and control the vehicle's situation when all wheel-side motors are slipping. Summary of the invention

[0006] In response to the above problems, the present invention proposes an anti-skid control method, device and system for a distributed wheel-side drive loader, which can maximize the driving capacity of the loader while ensuring that the loader does not slip, and increase the driving reliability of the loader on roads with low adhesion coefficients.

[0007] In order to achieve the above technical objectives and the above technical effects, the present invention is implemented through the following technical solutions:

[0008] In a first aspect, the present invention provides an anti-skid control method for a distributed wheel-side drive loader, comprising:

[0009] The current vehicle speed is estimated based on the acquired longitudinal acceleration of the loader, the measured vehicle speed of the loader and the speed of each wheel motor;

[0010] Based on the rotation speed of each wheel-side motor, the vehicle speed corresponding to the rotation speed of each wheel-side motor is calculated;

[0011] Based on the estimated current vehicle speed and the vehicle speed corresponding to the speed of each wheel side motor, the actual slip rate of each wheel is calculated;

[0012] Estimate the current optimal slip ratio based on the response speed of each wheel-side motor;

[0013] When a wheel is determined to be slipping based on the actual slip rate and the current optimal slip rate of each wheel, the anti-skid required torque is calculated based on the actual slip rate, the current optimal slip rate and the required torque of the slipping wheel, and the preset anti-skid algorithm, and the anti-skid required torque is sent to the wheel-side motor corresponding to the slipping wheel.

[0014] In combination with the first aspect, optionally, the method for estimating the current vehicle speed includes:

[0015] Based on the speed of each wheel motor, calculate the effective speed n_1 of the vehicle;

[0016] The vehicle effective speed n_1, the loader longitudinal acceleration, and the loader measured vehicle speed are input into the vehicle calculation estimation module based on the extended Kalman filter, so that the vehicle calculation estimation module based on the extended Kalman filter outputs the current vehicle speed vVeh K .

[0017] In combination with the first aspect, optionally, the vehicle speed estimation module based on the extended Kalman filter estimates the current vehicle speed vVeh based on a preset vehicle speed estimation method. K , the vehicle speed estimation method comprises:

[0018] Calculate the vehicle speed vVeh at the current moment k based on the vehicle speed at the previous moment K_pre , vehicle speed vVeh K_pre The calculation formula is: K_pre =vVeh K-1 +Δt*a k , where vVeh K-1 is the vehicle speed at the previous moment, a k is the longitudinal acceleration of the loader k at the current moment; Δt is the time interval;

[0019] According to the covariance matrix P at the previous moment K Calculate the covariance matrix P of the current k prediction process K_Pre , the formula is as follows:

[0020] P K_Pre =F*P K *F'+Q;

[0021] Where F is the Jacobian matrix of the state transfer matrix, F' is the transposed matrix of F, and Q is the process noise covariance;

[0022] The vehicle speed vVeh_GPS is measured by the vehicle effective speed n_1, the vehicle main reduction ratio FinalRatio, the wheel radius WheelR and the loader K , calculate the current vehicle speed measurement value Z k , the current vehicle speed measurement value Zk The formula is as follows:

[0023] Z K =ave(n_1*WheelR / FinalRatio, vVeh_GPS K );

[0024] Among them, ave means taking the average value;

[0025] Calculate the vehicle speed vVeh at the current time k K_pre and the current vehicle speed measurement value Z k The residual Y K , the residual Y K The calculation formula is:

[0026] Y K =Z K -vVeh K_pre ;

[0027] Calculate the measurement process covariance matrix K k :

[0028] S K =H*P K_Pre *H'+R;

[0029] K k =P K_Pre *H' / S K ;

[0030] Wherein, H is the Jacobian matrix of the measurement matrix, H = [1; 1]; H' is the transposed matrix of H, R is the measurement noise covariance, R = [0.1, 0.1];

[0031] According to the measurement process covariance matrix K k , the calculated vehicle speed vVeh at the current time k K_pre , residual Y K Calculate the current vehicle speed vVeh K， This value is used as the external output value of the Kalman filter:

[0032] v K =vVeh K_pre +K k *Y K

[0033] Update the next moment prediction process covariance matrix P K+1 , as the input of the Kalman filter at the next moment, the calculation formula of the prediction process covariance matrix is:

[0034] P K+1 =(IK k *H)*PK_Pre .

[0035] In combination with the first aspect, optionally, the method for calculating the effective speed n_1 of the whole vehicle includes:

[0036] When the driver steps on the brake: the vehicle effective speed n_1 = Max[ave(n_FL, n_FR), ave(n_BL, n_BR)];

[0037] When the driver does not step on the brake: the vehicle effective speed n_1 = Min[ave(n_FL, n_FR), ave(n_BL, n_BR)];

[0038] Among them, ave means taking the average value, Max means taking the maximum value, Min means taking the minimum value, n_FL means the wheel-side motor speed of the front left wheel, n_FR means the wheel-side motor speed of the front right wheel, n_BL means the wheel-side motor speed of the rear left wheel, and n_BR means the wheel-side motor speed of the rear right wheel.

[0039] In combination with the first aspect, optionally, the calculation formula for the vehicle speed corresponding to the rotation speed of each wheel-side motor is:

[0040] According to the wheel motor speed n_FL of the front left wheel, the corresponding vehicle speed vVeh_Mt_FL is calculated, and the calculation formula is: vVeh_Mt_FL=n_FL*WheelR / FinalRatio;

[0041] According to the wheel motor speed n_FR of the front right wheel, the corresponding vehicle speed vVeh_Mt_FR is calculated, and the calculation formula is: vVeh_Mt_FR=n_FR*WheelR / FinalRatio;

[0042] According to the wheel motor speed n_BL of the rear left wheel, the corresponding vehicle speed vVeh_Mt_BL is calculated using the following formula: vVeh_Mt_BL = n_BL*WheelR / FinalRatio;

[0043] According to the wheel motor speed n_BR of the rear right wheel, the corresponding vehicle speed vVeh_Mt_BR is calculated using the following formula: vVeh_Mt_BR = n_BR*WheelR / FinalRatio;

[0044] Among them, FinalRatio is the vehicle's final reduction ratio, and WheelR is the wheel radius.

[0045] In combination with the first aspect, optionally, a method for calculating an actual slip rate of each wheel includes:

[0046] b2_FL=(vVeh_Mt_FL-vVeh K ) / vVeh K ;

[0047] b2_FR=(vVeh_Mt_FR-vVeh K ) / vVeh K ;

[0048] b2_BL=(vVeh_Mt_BL-vVeh K ) / vVeh K ;

[0049] b2_BR=(vVeh_Mt_BR-vVeh K ) / vVeh K ;

[0050] Among them, b2_FL is the actual slip rate of the front left wheel, b2_FR is the actual slip rate of the front right wheel, b2_BL is the actual slip rate of the rear left wheel, b2_BR is the actual slip rate of the rear right wheel, and vVeh K is the estimated current vehicle speed.

[0051] In combination with the first aspect, optionally, the method for calculating the optimal slip ratio includes:

[0052] Through the membership function, the current wheel-side motor response speed p and the vehicle mass m are fuzzified from the domain representing the real physical meaning and converted into fuzzy language in the fuzzy subset of the fuzzy control algorithm. Through the preset fuzzy rule base, the fuzzy language in the fuzzy subset of the optimal slip rate c is decided, and finally resolved into the specific physical value of the optimal slip rate c in the real physical meaning through defuzzification processing of the membership function.

[0053] In combination with the first aspect, optionally, the method for calculating the anti-slip required torque includes:

[0054] When the actual slip rate of a wheel b2>(optimal slip rate c+threshold Thb), that is, b2>c+Thb, the vehicle is judged to be in a slipping state, and the torque of the wheel motor corresponding to the slipping wheel is adjusted through PID control; the PID control process includes:

[0055] Calculate the slip rate error Err, the slip rate error Err is calculated as follows: slip rate error Err = optimal slip rate c - actual slip rate b2;

[0056] The current vehicle torque coefficient r is calculated by PID control with the slip rate error Err as input, and the torque driver demand torque Trq_ReqRaw is corrected by using the coefficient r, and the final torque calculation formula is obtained as follows: anti-slip demand torque Trq_Req = vehicle torque coefficient r * driver demand torque Trq_ReqRaw, so that the actual slip rate of the slipping wheel approaches the optimal slip rate;

[0057] When the actual slip rate of a wheel b2<(optimal slip rate c+threshold Thb), that is, b2≤c+Thb, the current wheel is not slipping, and the wheel-side motor corresponding to the wheel is not allowed to perform anti-skid processing.

[0058] In a second aspect, the present invention provides an anti-skid control device for a distributed wheel-side drive loader, comprising:

[0059] The current vehicle speed estimation module is used to estimate the current vehicle speed based on the acquired loader longitudinal acceleration, the loader measured speed and the speed of each wheel side motor;

[0060] The vehicle speed calculation module is used to calculate the vehicle speed corresponding to the speed of each wheel-side motor based on the speed of each wheel-side motor;

[0061] The actual slip rate calculation module is used to calculate the actual slip rate of each wheel based on the estimated current vehicle speed and the vehicle speed corresponding to the speed of each wheel side motor;

[0062] A current optimal slip ratio estimation module is used to estimate the current optimal slip ratio based on the response speed of each wheel-side motor;

[0063] The anti-skid required torque calculation module is used to calculate the anti-skid required torque based on the actual slip rate, current optimal slip rate and required torque of the slipping wheel, and a preset anti-skid algorithm when it is determined that a wheel is slipping based on the actual slip rate of each wheel and the current optimal slip rate, and send the anti-skid required torque to the wheel-side motor corresponding to the slipping wheel.

[0064] In a third aspect, the present invention provides an anti-skid control system for a distributed wheel-side drive loader, comprising a storage medium and a processor;

[0065] The storage medium is used to store instructions;

[0066] The processor is configured to operate according to the instructions to execute the method according to any one of the first aspects.

[0067] Compared with the prior art, the present invention has the following beneficial effects:

[0068] The present invention proposes an anti-skid control method, device and system for a distributed wheel-side drive loader, which can exert the maximum driving capacity of the loader while ensuring that the loader does not slip, and increase the driving reliability of the loader on a road with a low adhesion coefficient.

[0069] The implementation process of the present invention is simple, does not require the aid of complex algorithms, is easy to apply in engineering, and has good portability. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative labor, among which:

[0071] Figure 1 It is a schematic diagram of the principle of an anti-skid control system for a distributed wheel-side drive loader according to an embodiment of the present invention;

[0072] Figure 2 A schematic flow chart of an anti-skid control method for a distributed wheel-side drive loader according to an embodiment of the present invention;

[0073] Figure 3 A schematic diagram of a flow chart of the effective speed of a vehicle according to an embodiment of the present invention;

[0074] Figure 4 A schematic diagram of a process of estimating the current vehicle speed by a vehicle speed estimation module based on an extended Kalman filter according to an embodiment of the present invention based on a preset vehicle speed estimation method;

[0075] Figure 5 A schematic diagram of a flow chart of an optimal slip ratio c according to an embodiment of the present invention;

[0076] Figure 6 The figure is a flow chart of a PID control process according to an embodiment of the present invention. DETAILED DESCRIPTION

[0077] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0079] Example 1

[0080] In an embodiment of the present invention, a method for anti-skid control of a distributed wheel-side drive loader is provided. Figure 2 As shown, the following steps are included:

[0081] (1) Estimate the current vehicle speed based on the acquired loader longitudinal acceleration, the loader measured vehicle speed, and the speed of each wheel motor;

[0082] (2) Based on the rotation speed of each wheel-side motor, calculate the vehicle speed corresponding to the rotation speed of each wheel-side motor;

[0083] (3) Based on the estimated current vehicle speed and the vehicle speed corresponding to the speed of each wheel motor, the actual slip rate of each wheel is calculated;

[0084] (4) Estimate the current optimal slip ratio based on the response speed of each wheel-side motor;

[0085] (5) When a wheel is determined to be slipping based on the actual slip rate and the current optimal slip rate of each wheel, the anti-skid required torque is calculated based on the actual slip rate, the current optimal slip rate and the required torque of the slipping wheel, and the preset anti-skid algorithm, and the anti-skid required torque is sent to the wheel-side motor corresponding to the slipping wheel.

[0086] In a specific implementation process, the anti-skid control method for a distributed wheel-side drive loader can be applied to an anti-skid control system for a distributed wheel-side drive loader as shown in Figure 1, and the anti-skid control system for a distributed wheel-side drive loader includes: a controller of a left front wheel motor ( Figure 1 FL_MCU in the right front wheel motor controller ( Figure 1 FR_MCU in the left rear wheel motor controller ( Figure 1 BL_MCU in the right rear wheel motor controller ( Figure 1 BR_MCU in the vehicle controller ( Figure 1VCU in), gyroscope, and GPS vehicle speed collector; the anti-skid control method for distributed wheel-side drive loader is placed in the controller in the form of a program, and the gyroscope is used to collect the vehicle longitudinal acceleration a k The GPS speed collector is used to collect the speed measured by the loader. The vehicle controller collects the speed of the four wheel motors and controls FL_MCU, FR_MCU, BR_MCU, and BL_MCU to drive the four wheel motors (FL, FR, BR, and BL) to output torque.

[0087] An anti-skid control method for a distributed wheel-side drive loader proposed in an embodiment of the present invention can maximize the driving capacity of the loader while ensuring that the loader does not slip, thereby increasing the driving reliability of the loader on a road with a low adhesion coefficient.

[0088] In a specific implementation of the embodiment of the present invention, Figure 2 As shown, the current vehicle speed estimation method includes:

[0089] Based on the speed of each wheel motor, calculate the effective speed n_1 of the vehicle;

[0090] The vehicle effective speed n_1, the loader longitudinal acceleration, and the loader measured vehicle speed are input into the vehicle calculation estimation module based on the extended Kalman filter, so that the vehicle calculation estimation module based on the extended Kalman filter outputs the current vehicle speed vVeh K .

[0091] In a specific implementation of the embodiment of the present invention, Figure 4 As shown, the vehicle speed estimation module based on the extended Kalman filter estimates the current effective value of the vehicle speed vVeh based on a preset vehicle speed estimation method. K , the vehicle speed estimation method comprises:

[0092] The initial value of the vehicle speed vVeh_init is the initial vehicle speed of the loader collected by GPS: vVeh_init = vVeh_GPS; the initial estimation error covariance P = 1; the process noise covariance Q = 0.1; the measurement noise covariance R = [0.1, 0.1]; the Jacobian matrix of the state transfer matrix is ​​F = 1, and the Jacobian matrix of the observation matrix is ​​H = [1; 1];

[0093] Calculate the vehicle speed vVeh at the current moment k based on the vehicle speed at the previous moment K_pre , vehicle speed vVeh K_pre The calculation formula is: K_pre =vVeh K-1 +Δt*a k , where vVeh K-1 is the vehicle speed at the previous moment, ak is the longitudinal acceleration of the loader k at the current moment; Δt is the time interval;

[0094] According to the covariance matrix P at the previous moment K Calculate the covariance matrix P of the current k prediction process K_Pre , the formula is as follows:

[0095] P K_Pre =F*P K *F'+Q;

[0096] Where F is the Jacobian matrix of the state transfer matrix, F = 1, Q is the process noise covariance, Q = 0.1;

[0097] The vehicle speed vVeh_GPS is measured by the vehicle effective speed n_1, the vehicle main reduction ratio FinalRatio, the wheel radius WheelR and the loader K , calculate the current vehicle speed measurement value Z k , the current vehicle speed measurement value Z k The formula is as follows:

[0098] Z K =ave(n_1*WheelR / FinalRatio, vVeh_GPS K );

[0099] Calculate the vehicle speed vVeh at the current time k K_pre and the current vehicle speed measurement value Z k The residual Y K , the residual Y K The calculation formula is:

[0100] Y K =Z K -vVeh K_pre ;

[0101] Calculate the measurement process covariance matrix K k :

[0102] S K =H*P K_Pre *H'+R;

[0103] K k =P K_Pre *H' / S K ;

[0104] Where H is the Jacobian matrix of the measurement matrix, H = [1; 1]; R is the measurement noise covariance, R = [0.1, 0.1];

[0105] According to the measurement process covariance matrix Kk , the calculated vehicle speed vVeh at the current time k K_pre , residual Y K Calculate the current effective value of vehicle speed vVeh K， This value is used as the external output value of the Kalman filter:

[0106] v K =vVeh K_pre +K k *Y K

[0107] Update the next moment prediction process covariance matrix P K+1 , as the input of the Kalman filter at the next moment, the calculation formula of the prediction process covariance matrix is:

[0108] P K+1 =(IK k *H)*P K_Pre .

[0109] In a specific implementation of the present invention, due to differences in the driver's total torque distribution, load center of mass position and driving road surface, n_FL, n_FR, n_BL and n_BR are not the same under different driving conditions. In view of the above situation, in order to ensure the effectiveness of subsequent calculations, it is necessary to calculate the effective speed n_1 of the vehicle through n_FL, n_FR, n_BL and n_BR. Figure 3 As shown, the calculation method of the vehicle effective speed n_1 includes:

[0110] When the driver steps on the brake: the vehicle effective speed n_1 = Max[ave(n_FL, n_FR), ave(n_BL, n_BR)];

[0111] When the driver does not step on the brake: the vehicle effective speed n_1 = Min[ave(n_FL, n_FR), ave(n_BL, n_BR)];

[0112] Among them, ave means taking the average value, Max means taking the maximum value, Min means taking the minimum value, n_FL means the wheel-side motor speed of the front left wheel, n_FR means the wheel-side motor speed of the front right wheel, n_BL means the wheel-side motor speed of the rear left wheel, and n_BR means the wheel-side motor speed of the rear right wheel.

[0113] In a specific implementation of the embodiment of the present invention, the calculation formula of the vehicle speed corresponding to the rotation speed of each wheel-side motor is:

[0114] According to the wheel motor speed n_FL of the front left wheel, the corresponding vehicle speed vVeh_Mt_FL is calculated, and the calculation formula is: vVeh_Mt_FL=n_FL*WheelR / FinalRatio;

[0115] According to the wheel motor speed n_FR of the front right wheel, the corresponding vehicle speed vVeh_Mt_FR is calculated, and the calculation formula is: vVeh_Mt_FR=n_FR*WheelR / FinalRatio;

[0116] According to the wheel motor speed n_BL of the rear left wheel, the corresponding vehicle speed vVeh_Mt_BL is calculated using the following formula: vVeh_Mt_BL = n_BL*WheelR / FinalRatio;

[0117] According to the wheel motor speed n_BR of the rear right wheel, the corresponding vehicle speed vVeh_Mt_BR is calculated using the following formula: vVeh_Mt_BR = n_BR*WheelR / FinalRatio;

[0118] Among them, FinalRatio is the vehicle's final reduction ratio, and WheelR is the wheel radius.

[0119] In a specific implementation of the embodiment of the present invention, the method for calculating the actual slip rate of each wheel includes:

[0120] b2_FL=(vVeh_Mt_FL-vVeh K ) / vVeh K ;

[0121] b2_FR=(vVeh_Mt_FR-vVeh K ) / vVeh K ;

[0122] b2_BL=(vVeh_Mt_BL-vVeh K ) / vVeh K ;

[0123] b2_BR=(vVeh_Mt_BR-vVeh K ) / vVeh K ;

[0124] Among them, b2_FL is the actual slip rate of the front left wheel, b2_FR is the actual slip rate of the front right wheel, b2_BL is the actual slip rate of the rear left wheel, b2_BR is the actual slip rate of the rear right wheel, and vVeh K is the estimated current vehicle speed.

[0125] In a specific implementation of the embodiment of the present invention, the anti-skid control method calculates the optimal slip ratio value c of the current loader based on the response speed p of the wheel-side motor and the current loader mass m through a fuzzy control algorithm, wherein the wheel-side motor response speed p = (current motor actual speed - previous moment motor actual speed) / (current moment motor actual torque - previous moment motor actual torque); the vehicle mass is obtained through the vehicle specification book The vehicle curb weight; specifically, if Figure 5 As shown, the calculation method of the optimal slip ratio c includes:

[0126] The currently acquired wheel-side motor response speed p and vehicle mass m are fuzzified from the domain representing the real physical meaning through the membership function, and converted into fuzzy language in the fuzzy subset in the fuzzy control algorithm. The fuzzy language in the fuzzy subset of the optimal slip rate c is determined through the preset fuzzy rule library, and finally parsed into the specific physical value in the domain representing the optimal slip rate c in the real physical meaning through the defuzzification processing of the membership function;

[0127] Specifically, the fuzzy control algorithm processes data as follows:

[0128] Determine the fuzzy subset of the variable language describing the input and output {NB NS ZO PS PB};

[0129] The domain of the wheel-side motor response speed p and the vehicle mass m is divided, specifically including: mapping the domain of the wheel-side motor response speed p {0 10 20 30 40} to the fuzzy subsets p_{NB NS ZO PS PB} through the membership function, parsing the wheel-side motor response speed p into the fuzzy subset p_Des through the membership function, and the value of p_Des is p_NB, p_NS, p_ZO, p_PS, p_PB; mapping the domain of the vehicle mass m {0 5 10 15 20} to the fuzzy subsets m_{NB NS ZO PS PB} through the membership function, parsing the vehicle mass m into the fuzzy subset m_Des through the membership function, and the value of m_Des is m_NB, m_NS, m_ZO, m_PS, m_PB; mapping the domain of the slip rate c {1 1.3 1.5 1.61.8} are mapped to fuzzy subsets c_{NB NS ZO PS PB} respectively, and the slip ratio c is resolved into fuzzy subset c_Des through membership function, and the values ​​of c_Des are c_NB, c_NS, m_ZO, c_PS, c_PB;

[0130] The currently acquired wheel-side motor response speed p and vehicle mass m are converted into corresponding fuzzy languages ​​p_Des and m_Des through the membership function, and the corresponding fuzzy language c_Des is calculated through the fuzzy controller, wherein the fuzzy controller stores a fuzzy rule base, and the form of the fuzzy rule base is as follows:

[0131] m_NB m_NS m_ZO m_PS m_PB p_NB c_PB cP cP c_ZO c_ZO p_NS c_PB c_PB cP cP c_ZO p_ZO c_PB c_PB cP cP c_ZO p_PS cP c_ZO c_ZO c_NS c_NS p_PB cP c_ZO c_NS c_NS c_NB

[0132] Through the membership function, the calculated fuzzy language c_Des is defuzzified into the true current optimal slip rate c.

[0133] In a specific implementation of the embodiment of the present invention, the method for calculating the anti-slip required torque includes:

[0134] When the actual slip rate of a wheel b2>(optimal slip rate c+threshold Thb), that is, b2>c+Thb, the vehicle is determined to be in a slipping state, and the torque of the wheel-side motor corresponding to the slipping wheel is adjusted through PID control; in the specific implementation process, the threshold Thb can be set according to actual needs, for example, it can be set to 0.3; Figure 6 As shown in the figure, the process of PID control includes:

[0135] Calculate the slip rate error Err, the slip rate error Err is calculated as follows: slip rate error Err = optimal slip rate c - actual slip rate b2;

[0136] The current vehicle torque coefficient r is calculated by PID control with the slip rate error Err as input, and the torque driver demand torque Trq_ReqRaw is corrected by using the coefficient r, and the final torque calculation formula is obtained as follows: anti-slip demand torque Trq_Req = vehicle torque coefficient r * driver demand torque Trq_ReqRaw, so that the actual slip rate of the slipping wheel approaches the optimal slip rate;

[0137] When the actual slip rate of a wheel b2<(optimal slip rate c+threshold Thb), that is, b2≤c+Thb, the current wheel is not slipping, and the wheel-side motor corresponding to the wheel is not allowed to perform anti-skid processing.

[0138] Example 2

[0139] An embodiment of the present invention provides an anti-skid control device for a distributed wheel-side drive loader, comprising:

[0140] The current vehicle speed estimation module is used to estimate the current vehicle speed based on the acquired loader longitudinal acceleration, the loader measured speed and the speed of each wheel side motor;

[0141] The vehicle speed calculation module is used to calculate the vehicle speed corresponding to the speed of each wheel-side motor based on the speed of each wheel-side motor;

[0142] The actual slip rate calculation module is used to calculate the actual slip rate of each wheel based on the estimated current vehicle speed and the vehicle speed corresponding to the speed of each wheel side motor;

[0143] A current optimal slip ratio estimation module is used to estimate the current optimal slip ratio based on the response speed of each wheel-side motor;

[0144] The anti-skid required torque calculation module is used to calculate the anti-skid required torque based on the actual slip rate, current optimal slip rate and required torque of the slipping wheel, and a preset anti-skid algorithm when it is determined that a wheel is slipping based on the actual slip rate of each wheel and the current optimal slip rate, and send the anti-skid required torque to the wheel-side motor corresponding to the slipping wheel.

[0145] The rest are the same as in Example 1.

[0146] Example 3

[0147] An embodiment of the present invention provides an anti-skid control system for a distributed wheel-side drive loader, including a storage medium and a processor;

[0148] The storage medium is used to store instructions;

[0149] The processor is configured to operate according to the instructions to execute the method according to any one of the embodiments 1.

[0150] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0151] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0152] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0153] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0154] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which all fall within the protection of the present invention.

[0155] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An anti-skid control method for a distributed wheel-side drive loader, characterized in that: include: The current vehicle speed is estimated based on the acquired longitudinal acceleration of the loader, the measured vehicle speed of the loader and the speed of each wheel motor; Based on the rotation speed of each wheel-side motor, the vehicle speed corresponding to the rotation speed of each wheel-side motor is calculated; Based on the estimated current vehicle speed and the vehicle speed corresponding to the speed of each wheel side motor, the actual slip rate of each wheel is calculated; Estimate the current optimal slip ratio based on the response speed of each wheel-side motor; When a wheel is determined to be slipping based on the actual slip rate and the current optimal slip rate of each wheel, the anti-skid required torque is calculated based on the actual slip rate, the current optimal slip rate and the required torque of the slipping wheel, and the preset anti-skid algorithm, and the anti-skid required torque is sent to the wheel-side motor corresponding to the slipping wheel.

2. The anti-skid control method for a distributed wheel-side drive loader according to claim 1, characterized in that: The current vehicle speed estimation method includes: Based on the speed of each wheel motor, calculate the effective speed n_1 of the vehicle; The vehicle effective speed n_1, the loader longitudinal acceleration, and the loader measured vehicle speed are input into the vehicle calculation estimation module based on the extended Kalman filter, so that the vehicle calculation estimation module based on the extended Kalman filter outputs the current vehicle speed vVeh K .

3. The anti-skid control method for a distributed wheel-side drive loader according to claim 2, characterized in that: The vehicle speed estimation module based on the extended Kalman filter estimates the current vehicle speed vVeh based on a preset vehicle speed estimation method. K , the vehicle speed estimation method comprises: Calculate the vehicle speed vVeh at the current moment k based on the vehicle speed at the previous moment K_pre , vehicle speed vVeh K_pre The calculation formula is: K_pre =vVeh K-1 +Δt*a k , where vVeh K-1 is the vehicle speed at the previous moment, a k is the longitudinal acceleration of the loader k at the current moment; Δt is the time interval; According to the covariance matrix P at the previous moment K Calculate the covariance matrix P of the current k prediction process K_Pre , the formula is as follows: P K_Pre =F*P K *F'+Q; Where F is the Jacobian matrix of the state transfer matrix, F' is the transposed matrix of F, and Q is the process noise covariance; The vehicle speed vVeh_GPS is measured by the vehicle effective speed n_1, the vehicle main reduction ratio FinalRatio, the wheel radius WheelR and the loader K , calculate the current vehicle speed measurement value Z k , the current vehicle speed measurement value Z k The formula is as follows: Z K have(n_1*WheelR / FinalRatio,vVeh_GPS K ); Among them, ave means taking the average value; Calculate the vehicle speed vVeh at the current time k K_pre and the current vehicle speed measurement value Z k The residual between Y K , the residual Y K The calculation formula is: AND K =Z K -vVeh K_pre ; Calculate the measurement process covariance matrix K k : S K =H*P K_Pre *H'+R; K k =P K_Pre *H' / S K ; Where H is the Jacobian matrix of the measurement matrix, H = [1; 1]; H' is the transposed matrix of H, R is the measurement noise covariance, R＝[0.1，0.1]； According to the measurement process covariance matrix K k , the calculated vehicle speed vVeh at the current time k K_pre , residual Y K Calculate the current vehicle speed vVeh K , which is used as the external output value of Kalman filter: vVeh K =vVeh K_pre +K k *AND K Update the next moment prediction process covariance matrix P K+1 , as the input of the Kalman filter at the next moment, the calculation formula of the prediction process covariance matrix is: P K+1 =(I-K k *H)*P K_Pre 。 4. The anti-skid control method for a distributed wheel-side drive loader according to claim 2, characterized in that: The calculation method of the vehicle effective speed n_1 includes: When the driver steps on the brake: the vehicle effective speed n_1 = Max[ave(n_FL, n_FR), ave(n_BL, n_BR)]; When the driver does not step on the brake: the vehicle effective speed n_1 = Min[ave(n_FL, n_FR), ave(n_BL, n_BR)]; Among them, ave means taking the average value, Max means taking the maximum value, Min means taking the minimum value, n_FL means the wheel-side motor speed of the front left wheel, n_FR means the wheel-side motor speed of the front right wheel, n_BL means the wheel-side motor speed of the rear left wheel, and n_BR means the wheel-side motor speed of the rear right wheel.

5. The anti-skid control method for a distributed wheel-side drive loader according to claim 1, characterized in that: The calculation formula of the vehicle speed corresponding to the speed of each wheel motor is: According to the wheel motor speed n_FL of the front left wheel, the corresponding vehicle speed vVeh_Mt_FL is calculated, and the calculation formula is: vVeh_Mt_FL=n_FL*WheelR / FinalRatio; According to the wheel motor speed n_FR of the front right wheel, the corresponding vehicle speed vVeh_Mt_FR is calculated, and the calculation formula is: vVeh_Mt_FR=n_FR*WheelR / FinalRatio; According to the wheel motor speed n_BL of the rear left wheel, the corresponding vehicle speed vVeh_Mt_BL is calculated using the following formula: vVeh_Mt_BL = n_BL*WheelR / FinalRatio; According to the wheel motor speed n_BR of the rear right wheel, the corresponding vehicle speed vVeh_Mt_BR is calculated using the following formula: vVeh_Mt_BR = n_BR*WheelR / FinalRatio; Among them, FinalRatio is the vehicle's final reduction ratio, and WheelR is the wheel radius.

6. The anti-skid control method for a distributed wheel-side drive loader according to claim 5, characterized in that: The calculation method of the actual slip rate of each wheel includes: <h2 style=";text-align:left;direction:ltr">b2_FL = (vVeh_Mt_FL - vVeh<h2 style=";text-align:left;direction:ltr"> K <h2 style=";text-align:left;direction:ltr"> ) / vVeh<h2 style=";text-align:left;direction:ltr"> K <h2 style=";text-align:left;direction:ltr"> ; b2_FR=(vVeh_Mt_FR-vVeh K ) / vVeh K ; <h2 style=";text-align:left;direction:ltr">b2_BL = (vVeh_Mt_BL - vVeh<h2 style=";text-align:left;direction:ltr"> K <h2 style=";text-align:left;direction:ltr"> ) / vVeh<h2 style=";text-align:left;direction:ltr"> K <h2 style=";text-align:left;direction:ltr"> ; b2_BR=(vVeh_Mt_BR-vVeh K ) / vVeh K ; Among them, b2_FL is the actual slip rate of the front left wheel, b2_FR is the actual slip rate of the front right wheel, b2_BL is the actual slip rate of the rear left wheel, b2_BR is the actual slip rate of the rear right wheel, and vVeh K is the estimated current vehicle speed.

7. The anti-skid control method for a distributed wheel-side drive loader according to claim 1, characterized in that: The calculation method of the optimal slip ratio includes: Through the membership function, the current wheel-side motor response speed p and the vehicle mass m are fuzzified from the domain representing the real physical meaning and converted into fuzzy language in the fuzzy subset of the fuzzy control algorithm. Through the preset fuzzy rule base, the fuzzy language in the fuzzy subset of the optimal slip rate c is decided, and finally resolved into the specific physical value of the optimal slip rate c in the real physical meaning through defuzzification processing of the membership function.

8. The anti-skid control method for a distributed wheel-side drive loader according to claim 1, characterized in that: The calculation method of the anti-slip required torque includes: When the actual slip rate of a wheel b2>(optimal slip rate c+threshold Thb), that is, b2>c+Thb, the vehicle is judged to be in a slipping state, and the torque of the wheel motor corresponding to the slipping wheel is adjusted through PID control; the PID control process includes: Calculate the slip rate error Err, the slip rate error Err is calculated as follows: slip rate error Err = optimal slip rate c - actual slip rate b2; The current vehicle torque coefficient r is calculated by PID control with the slip rate error Err as input, and the torque driver demand torque Trq_ReqRaw is corrected by using the coefficient r, and the final torque calculation formula is obtained as follows: anti-slip demand torque Trq_Req = vehicle torque coefficient r * driver demand torque Trq_ReqRaw, so that the actual slip rate of the slipping wheel approaches the optimal slip rate; When the actual slip rate of a wheel b2<(optimal slip rate c+threshold Thb), that is, b2≤c+Thb, the current wheel is not slipping, and the wheel-side motor corresponding to the wheel is not allowed to perform anti-skid processing.

9. An anti-skid control device for a distributed wheel-side drive loader, characterized in that: include: The current vehicle speed estimation module is used to estimate the current vehicle speed based on the acquired loader longitudinal acceleration, the loader measured speed and the speed of each wheel side motor; The vehicle speed calculation module is used to calculate the vehicle speed corresponding to the speed of each wheel-side motor based on the speed of each wheel-side motor; The actual slip rate calculation module is used to calculate the actual slip rate of each wheel based on the estimated current vehicle speed and the vehicle speed corresponding to the speed of each wheel side motor; A current optimal slip ratio estimation module is used to estimate the current optimal slip ratio based on the response speed of each wheel-side motor; The anti-skid required torque calculation module is used to calculate the anti-skid required torque based on the actual slip rate, current optimal slip rate and required torque of the slipping wheel, and a preset anti-skid algorithm when it is determined that a wheel is slipping based on the actual slip rate of each wheel and the current optimal slip rate, and send the anti-skid required torque to the wheel-side motor corresponding to the slipping wheel.

10. An anti-skid control system for a distributed wheel-side drive loader, characterized in that: including storage media and processors; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to perform the method according to any one of claims 1-8.

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