Suspension pitching cooperative control system and method combining dynamic vertical force distribution and multi-mode braking

Abstract

The invention discloses a suspension pitching cooperative control system and method combining dynamic vertical force distribution and multi-mode braking, and particularly relates to the field of vehicle suspensions. Meanwhile, the braking torque distribution unit and the suspension system are controlled in real time by defining a state machine; vehicle low-speed target braking torque and tire vertical force are calculated through the expected deceleration and correspondingly input into a braking torque distribution unit and a four-degree-of-freedom suspension model; converting the four-degree-of-freedom suspension model into a state-space equation and discretizing the state-space equation to obtain a prediction model, and further deriving a state prediction equation of the future N steps; designing a cost function comprising a state quantity weight matrix Q, an input quantity weight matrix R and a state final value weight matrix F, substituting a prediction state into the cost function to obtain an optimal input sequence, dynamically adjusting suspension rigidity, damping and a braking force distribution strategy, and correcting a control instruction in real time by using closed-loop feedback of a vehicle body attitude sensor, so as to improve the stability of a vehicle body. And the suspension pitching control is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicle suspension, in particular to a suspension pitch cooperative control system and method combining dynamic vertical force distribution and multi-modal braking. BACKGROUND

[0002] In the current field of intelligent vehicle suspension control, passive suspension relies on passive response of mechanical structure and cannot dynamically adjust stiffness or damping according to real-time load changes, and the body pitch phenomenon is obvious during braking; semi-active suspension can only adjust damping and cannot actively apply force, and the pitch suppression capability is limited, the response is slow in extreme conditions, and it is difficult to optimize tire grip and vehicle stability; existing active suspension mostly uses a single control strategy (such as PID control), which is difficult to cooperate with the braking system to suppress pitch, and does not consider the nonlinear distribution of dynamic vertical force. At the same time, in braking, acceleration and complex road conditions, there are problems such as inaccurate dynamic vertical force distribution, vehicle pitch limited to a single system, and control strategy cannot be adaptively optimized in different driving modes. Specifically, the traditional braking system often uses a single braking force distribution logic and does not design differently for different braking scenarios (such as emergency braking, slow braking, and slope braking), resulting in unreasonable braking force distribution in complex conditions. For example, in slope braking, the traditional system is difficult to adjust the front and rear axle braking force weight in real time according to the slope, and is prone to problems such as vehicle rear sliding or long braking distance; in emergency braking conditions, the response speed and distribution accuracy of the braking force are insufficient, which cannot fully utilize the tire grip, and thus affects the braking stability and risk avoidance ability of the vehicle. In addition, the existing braking control strategy lacks a cooperative mechanism with the suspension system, which is difficult to simultaneously optimize the vehicle body posture and braking force distribution during braking, resulting in limited pitch suppression effect and poor passenger comfort. SUMMARY

[0003] Therefore, the present application provides a suspension pitch cooperative control system and method combining dynamic vertical force distribution and multi-modal braking to solve the problems raised in the background art.

[0004] In order to achieve the above-mentioned purpose, the present application provides the following technical scheme: a suspension pitch cooperative control method combining dynamic vertical force distribution and multi-modal braking, by setting multiple sensors on the vehicle to obtain vehicle parameters that need to be preprocessed, characterized in that it comprises the following steps:

[0005] Step 1: obtaining the target deceleration of the driver; at the same time, defining a state machine in the electronic control unit (ECU) to control the braking torque distribution unit and the suspension system in real time;

[0006] Step 2: obtaining the expected deceleration through five polynomial smooth transition decelerations;

[0007] Step 3: Calculate the vehicle low-speed target braking torque and tire vertical force respectively by the expected deceleration obtained in step 2, and correspondingly input the braking torque distribution unit and the four-degree-of-freedom suspension model;

[0008] Convert the four-degree-of-freedom suspension model into a state space equation and discretize it to obtain a prediction model, and then derive a state prediction equation for the next N steps; design a cost function including a state quantity weight matrix Q, an input quantity weight matrix R, and a state final value weight matrix F, with zero pitch angle as the core target, by substituting the predicted state into the cost function and simplifying, the optimal input sequence is obtained, so as to dynamically adjust the suspension stiffness, damping and braking force distribution strategy, and use the closed-loop feedback of the vehicle body posture sensor to real-time correct the control command (completed by vehicle parameter preprocessing), realize dynamic vertical force distribution and multi-modal braking collaborative control suspension pitch.

[0009] Further, the vehicle parameters that need to be preprocessed include: driver's braking operation, vehicle driving state information, spring and spring related parameters.

[0010] Further, the state machine for real-time control of the braking torque distribution unit and the suspension system has the following running logic:

[0011] When the braking anti-pitch state machine is running, first perform vehicle state safety check, by comparing the vehicle related parameters with the preset threshold, judge whether each parameter is in the safe range, only when all parameters are in the safe range, it is determined that the braking system is normal, otherwise it is determined that there is a risk; after completing the safety check, combine the engine force, slope and the preset constant and interpolation data to calculate the minimum acceleration target value, and also consider the fixed lower limit and correction coefficient during calculation, and output the final result.

[0012] Further, the state machine includes five modes: disabled, passive, active, slope closed and emergency control, and the conversion between modes is realized through different trigger signals;

[0013] When the target mode is turned on and the driver enables the system, the system is converted from the disabled mode to the passive mode;

[0014] When the target mode is closed or the driver does not enable the system, it is converted from the passive mode to the disabled mode;

[0015] When the specific speed condition is met, there is no emergency situation, the system boundary is normal, and the minimum acceleration target value meets the requirements, the system is converted from the passive mode to the active mode;

[0016] In the active mode, if unstable control occurs, the target mode changes, the driver does not enable the system, or the relationship between the system target braking force and the driver target braking force does not meet the conditions, it will be converted to the passive mode;

[0017] When the state machine detects a certain emergency, it enters an emergency control mode; the emergency control mode duration meets certain conditions, or the brake force, target mode, and driver-activated mode conditions change, and it switches to a passive mode;

[0018] When the state machine detects that the vehicle is stationary and the active mode duration exceeds the limit condition, the active mode switches to a ramp-off mode.

[0019] When the vehicle is stationary, the emergency control state switches to a ramp-off state.

[0020] Further, when the vehicle speed is below a set threshold and the brake pressure meets the requirements, the activation time of the related brake safety system is detected. If the driver's target pressure is too high or the activation time exceeds the specified time, the vehicle is marked as being in an unstable control state.

[0021] When the system switches from passive mode to active mode, the virtual travel distance and the actual braking distance are calculated based on the current actual acceleration of the vehicle and the desired acceleration at the previous time, respectively. By comparing the difference between the two with a set threshold, the low-speed braking distance anomaly level is output.

[0022] When the system switches from non-active mode to active mode, the reference pressure value is saved, and based on the increment of the current pressure and the reference pressure and different threshold values set, different levels of driver over-ride operation during low-speed driving are marked. When the driver turns on the comfort mode of the vehicle, the vehicle is not in an emergency state, and the road surface is smooth, the low-speed driving under-braking flag is output by accumulating the time and calculating the wheel speed operation.

[0023] Further, the state machine uses an enumeration method to define multiple brake-related detection results as independent enumeration values and assign corresponding priorities and processing rules. At the same time, the system running state is also set as different enumeration constants. By judging whether the enumeration value of the current detection result is triggered one by one, combining the driver's operation instruction, time limit condition, and emergency information, and following the preset priority rules, it is directly mapped to the corresponding system state enumeration value, realizing the full-process management and logical arbitration of the brake system, and ensuring the safe and orderly operation and stable switching of the system under complex conditions.

[0024] Further, the expected deceleration is calculated as follows:

[0025] 1) Assume the target deceleration is a quintic polynomial:

[0026] ;

[0027] where A, B, C, D, E, and F are polynomial coefficients, and t is time.

[0028] The first derivative is:

[0029] ;

[0030] Second derivative:

[0031] ;

[0032] 2) List boundary conditions:

[0033] 1) At t = 0:

[0034] Position constraint:

[0035] ;

[0036] First derivative constraint (rate of change):

[0037] ;

[0038] Second derivative constraint:

[0039] ;

[0040] 2) At t = T: Smooth transition time:

[0041] Position constraint:

[0042] ;

[0043] First derivative constraint:

[0044] ;

[0045] Second derivative constraint:

[0046] ;

[0047] 3) Bring known D, E, F into the equation, and the boundary conditions become:

[0048] Position constraint:

[0049] ;

[0050] First derivative constraint:

[0051] ;

[0052] Second derivative constraint:

[0053] ;

[0054] 4) Summarize in matrix form: ​

[0055]

[0056] Solve A, B, C to get the final fitted quintic polynomial curve:

[0057]

[0058] 5) slope compensation to get the final expected acceleration:

[0059]

[0060] is the compensated expected acceleration; is the road pitch angle.

[0061] Further, the braking torque is calculated by the expected deceleration:

[0062] First, according to the preset minimum protection pressure, the minimum allowed longitudinal force is calculated by the pressure to force conversion coefficient, and the absolute value of the driver's target force is taken as the maximum allowed longitudinal force, then the activation condition is judged, when the system state is neither passive nor disabled and the minimum force does not exceed the maximum force, the system is activated, after activation, the expected deceleration is converted into expected longitudinal braking force by Newton's second law, and the braking force threshold is set to ensure that the force is within a safe range; for the target force output in the activated state, a first-order low-pass filter formula is used for smoothing processing to avoid sudden changes in force, if it is in a non-activated state or first activated, it is directly assigned;

[0063] Convert the target braking force into braking torque, and give different weights to the front and rear wheels:

[0064] The braking torque formula is:

[0065] ;

[0066] ;

[0067] , is the target front and rear wheel braking torque; , is the front and rear wheel braking torque distribution weight; is the target braking torque converted into target braking torque coefficient, is the target braking force.

[0068] Further, the expected acceleration and the lateral acceleration solving the tire vertical force, the vertical force formula is:

[0069] ;

[0070] ; ;

[0071] ;

[0072] , , , denotes the vertical force of each tire; m denotes the mass of the vehicle; g denotes the gravitational acceleration; a, b denote the distance from the mass center of the vehicle to the front axle and the rear axle, respectively; denotes the wheelbase, L = a + b; denotes the height of the mass center of the vehicle; denotes the desired acceleration of the vehicle; denotes the lateral acceleration of the vehicle; denotes the front wheel track; denotes the rear wheel track.

[0073] 1 Further, the four-degree-of-freedom suspension model is a state space equation:

[0074] ;

[0075] ;

[0076] wherein: denotes the state variable; denotes the system observation; denotes the control variable of the system; denotes the disturbance of the road surface;

[0077] wherein:

[0078] ;

[0079] ; ;

[0080] ;

[0081] wherein, denotes the vertical velocity of the mass center position of the vehicle; denotes the pitch angular velocity of the vehicle; represents vertical velocity on front and rear axle spring respectively; 、 represents vertical displacement on front and rear axle spring respectively; 、 represents vertical displacement on front and rear axle spring respectively; 、 represents vertical displacement on road surface respectively; 、 represents suspension damping value of front and rear axle respectively; 、 represents suspension stiffness value of front and rear axle respectively; 、 represents tire stiffness value of front and rear axle respectively; represents sprung mass; 、 represents unsprung mass of front and rear axle respectively; a, b represents distance from front and rear axle to center of mass respectively; represents moment of inertia about Y axis; 、 represents active vertical force (control variable) of front and rear axle respectively; represents road disturbance of front and rear axle respectively;

[0082] MPC derivation process:

[0083] State space equation of continuous system:

[0084] ;

[0085] ;

[0086] ;

[0087] ;

[0088] wherein: 、 represents dimension of A and B respectively; n=8; p=2 in the application.

[0089] Discretize the model as prediction model: (forward Euler method)

[0090] ;

[0091] wherein: Ts is discrete time; represents state variable of k step of prediction, represents control variable of k step of prediction.

[0092] ;

[0093] ;

[0094] Let ;

[0095] Predict the state of N steps:

[0096] ;

[0097] ;

[0098] ;

[0099]

[0100] ;

[0101] where: , denote the state and control quantities of the k+1 step predicted at the k step.

[0102] Let:

[0103] ;

[0104] ;

[0105] Get:

[0106] ;

[0107] where:

[0108] ;

[0109] ;

[0110] where: denote the dimension of ; denote the dimension of ; denote the dimension of M; denote the dimension of C.

[0111] The cost function is calculated as follows:

[0112] ;

[0113] Weight coefficient:

[0114] ;

[0115] ;

[0116] ;

[0117] Q is the weight of the state quantity, R is the weight of the input quantity, and F is the weight of the final value of the state quantity; the greater the weight coefficient, the more it tends to be smaller in optimization;

[0118] Substitute Xk into the cost function to simplify the above formula to obtain:

[0119]

[0120] Wherein:

[0121]

[0122]

[0123]

[0124]

[0125]

[0126] The input value Uk is obtained by solving the cost function J, As a fixed value, it does not affect the solution result, so it is obtained:

[0127]

[0128] Finally, the value of the control quantity at each moment is solved by function to achieve the purpose of optimal control.

[0129] The application also discloses a suspension pitch cooperative control system combining dynamic vertical force distribution and multi-modal braking, which is based on the above method.

[0130] (1) Precise dynamic vertical force distribution and real-time response: according to vehicle parameters, sensor data, brake pressure sensor data and the like, the vertical force distribution of front and rear axles is solved in real time through a vehicle kinematics model, and a self-adaptive suspension actuator is driven to dynamically adjust the stiffness and damping parameters. Compared with the fixed response mode of the traditional passive suspension depending on the mechanical structure, the response delay of the suspension system to the axle load transfer during braking is shortened, and the dynamic vertical force distribution lag problem is effectively solved.

[0131] ​​​​​​​(2) Suspension-Brake System Collaborative Pitch Suppression: The pitch coordination control unit embeds a model predictive control (MPC) algorithm, with the minimization of the vehicle pitch angle as the optimization objective. It prioritizes the suppression of pitch angular velocity through a dynamic weight matrix and combines closed-loop feedback from the vehicle attitude sensor to correct control commands in real time. Compared with the traditional single PID control strategy, this collaborative control mechanism reduces the peak value of the braking pitch angle and the fluctuation amplitude of the pitch angular velocity. At the same time, it adopts a fifth-order polynomial braking force control algorithm to generate a continuously differentiable expected acceleration curve based on the driver's target deceleration and the vehicle state, thereby reducing the rate of change of braking force. The two work together to achieve braking pitch suppression and smooth transition of braking force, significantly improving passenger ride comfort. Attached Figure Description

[0132] Figure 1 This is a general framework diagram of the braking anti-pitch control provided by the present invention;

[0133] Figure 2 The state machine logic diagram provided for this invention;

[0134] Figure 3 A framework diagram for calculating the desired acceleration provided by this invention;

[0135] Figure 4 This is a diagram illustrating the tire vertical force calculation framework provided by the present invention.

[0136] Figure 5 The framework diagram for calculating suspension stiffness and damping provided by this invention;

[0137] Figure 6 The suspension damping map provided for this invention. Detailed Implementation

[0138] The following specific embodiments illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0139] like Figures 1-6 As shown, this invention provides a suspension pitch coordination control method combining dynamic vertical force distribution and multimodal braking. It obtains vehicle parameters requiring preprocessing by installing multiple sensors on the vehicle. These parameters include: driver braking operations, vehicle driving status information, and sprung and unsprung related parameters. The method includes the following steps:

[0140] Step 1: Obtain the target deceleration of the driver; at the same time, control the brake torque distribution unit and the suspension system in real time by defining a state machine in the electronic control unit (ECU);

[0141] The state machine designed in the application includes five modes: disabled, passive, active, ramp-off, and emergency control. The conversion between modes is realized through different trigger signals.

[0142] When the target mode is on and the driver enables the system, the system is converted from the disabled mode to the passive mode;

[0143] When the target mode is off or the driver does not enable the system, the system is converted from the passive mode back to the disabled mode;

[0144] When the specific speed condition is met, there is no emergency situation, the system boundary is normal, and the minimum acceleration target value meets the requirements, the system is converted from the passive mode to the active mode;

[0145] In the active mode, if unstable control occurs, the target mode changes, the driver does not enable the system, or the relationship between the system target braking force and the driver target braking force does not meet the conditions, it will be converted to the passive mode;

[0146] When the state machine detects a specific emergency situation, it enters the emergency control mode. If the duration of the emergency control mode meets certain conditions, or if the braking force, target mode, or driver enable mode changes, it will be converted to the passive mode;

[0147] When the state machine detects that the vehicle is stationary and the active mode duration exceeds the limit condition, the active mode is converted to the ramp-off mode;

[0148] When the vehicle is stationary, the emergency control state is converted to the ramp-off state.

[0149] Specifically, the state machine for real-time control of the brake torque distribution unit and the suspension system has the following operation logic:

[0150] When the brake anti-dive state machine is running, first perform a vehicle state safety check by comparing the vehicle-related parameters with the preset threshold to determine whether each parameter is within the safe range. Only when all parameters are within the safe range, the braking system is considered normal, otherwise it is considered to be at risk. After completing the safety check, the minimum acceleration target value is calculated in combination with the engine force, slope, and preset constants and interpolation data. The fixed lower limit and correction coefficient are also considered in the calculation process, and the final result is output;

[0151] When the vehicle speed is below the set threshold and the brake pressure meets the requirements, the activation time of the related braking safety system is detected. If the driver target pressure is too high or the activation time exceeds the specified time, the vehicle is marked as being in an unstable control state;

[0152] When the system switches from passive mode to active mode, the virtual running distance and the actual braking distance are calculated by the current actual acceleration and the expected acceleration at the last time, and the low-speed braking distance anomaly level is output by comparing the difference between the two with the set threshold value;

[0153] When the system switches from non-active mode to active mode, the reference pressure value is saved, and different levels of driver over-ride operation during low-speed driving are marked according to the increment of the current pressure and the reference pressure and different threshold values set; when the driver turns on the comfort mode of the vehicle, the vehicle does not appear in an emergency state, and the road surface is smooth, the low-speed driving under-braking flag is output by accumulating the time and calculating the wheel speed operation.

[0154] Full working condition system safety redundancy guarantee: as shown in Figure 2 The safety detection mechanism is integrated in the state machine logic, and when the low-speed braking distance anomaly or the driver over-ride operation (such as the pressure increment greater than the threshold value) is detected, the emergency control state can take over the system within one response period.

[0155] The state machine uses enumeration, defines multiple brake-related detection results as independent enumeration values, and assigns corresponding priority and processing rules; at the same time, the system running state is also set as different enumeration constants, by judging whether the enumeration value of the current detection result is triggered one by one, combining the driver operation instruction, the time limit condition and the emergency information, according to the preset priority rule, it is directly mapped to the corresponding system state enumeration value, realizing the full flow management and logic arbitration of the brake system, ensuring that the system can still run safely and orderly and switch stably under complex conditions.

[0156] Step 2: The expected deceleration is obtained by five polynomial smoothing transition deceleration;

[0157] The expected deceleration is calculated as follows:

[0158] 1) Assume the target deceleration is a quintic polynomial:

[0159] ;

[0160] Where A, B, C, D, E, and F are polynomial coefficients, and t is time;

[0161] The first derivative is:

[0162] ;

[0163] The second derivative is:

[0164] ;

[0165] 2) List the boundary conditions:

[0166] ① At t = 0:

[0167] Position constraint:

[0168] ;

[0169] First derivative constraint (rate of change):

[0170] ;

[0171] Second derivative constraint:

[0172] ;

[0173] ② At t = t , is the smooth transition time:

[0174] Position constraint:

[0175] ;

[0176] First derivative constraint:

[0177] ;

[0178] Second derivative constraint:

[0179] ;

[0180] 3) Substitute the known D, E, F into the boundary conditions:

[0181] Position constraint:

[0182] ;

[0183] First derivative constraint:

[0184] ;

[0185] Second derivative constraint:

[0186] ;

[0187] 4) Summarize in matrix form:

[0188]

[0189] Solve for A, B, C to get the final fitted quintic polynomial curve:

[0190]

[0191] 5) slope compensation to get final desired acceleration:

[0192]

[0193] is compensated desired acceleration; is road pitch angle, slope estimation is obtained by vehicle sensors.

[0194] Step 3: Calculate vehicle low-speed target braking torque and tire vertical force respectively by desired deceleration obtained in step 2, and input brake torque distribution unit and four-degree-of-freedom suspension model correspondingly;

[0195] Calculate braking torque by desired deceleration:

[0196] First, according to the preset minimum protection pressure, the minimum allowed longitudinal force is calculated by the pressure to force conversion coefficient, and the absolute value of the driver target force is taken as the maximum allowed longitudinal force. Then, the activation condition is judged. When the system state is neither passive nor disabled, and the minimum force does not exceed the maximum force, the system is activated. After activation, the expected deceleration is converted into expected longitudinal braking force by Newton's second law, and the braking force threshold is set to ensure that the force is within a safe range. For the target force output in the activated state, a first-order low-pass filter formula is used for smoothing to avoid sudden changes in force. If it is in a non-activated state or activated for the first time, it is directly assigned;

[0197] Convert the target braking force into braking torque, and give different weights to the front and rear wheels:

[0198] The braking torque formula is:

[0199] ;

[0200] ;

[0201] , Target front and rear wheel braking torque; , Front and rear wheel braking torque distribution weight; Target braking torque is converted into target braking torque coefficient, Target braking force.

[0202] Further, the expected acceleration and the lateral acceleration Solve the tire vertical force, and the vertical force formula is:

[0203] ;

[0204] ; ;

[0205] ;

[0206] , , , denotes the vertical force of each tire; m denotes the vehicle mass; g denotes the gravitational acceleration; a, b denote the distance from the vehicle mass center to the front and rear axles, respectively; denotes the wheelbase, L = a + b; denotes the vehicle mass center height; denotes the vehicle desired acceleration; denotes the vehicle lateral acceleration; denotes the front wheel track; denotes the rear wheel track.

[0207] Further, the four-degree-of-freedom suspension model is a state space equation:

[0208] ;

[0209] ;

[0210] wherein: denotes the state variable; denotes the system observation; denotes the system control; denotes the road disturbance;

[0211] wherein:

[0212] ;

[0213] ; ;

[0214] ;

[0215] wherein, denotes the vertical velocity of the vehicle mass center position; denotes the vehicle pitch angular velocity; denotes the front and rear axle sprung vertical velocity; , respectively represent the vertical displacement of the front and rear axles of the vehicle on the spring; 、 respectively represent the vertical displacement of the front and rear axles of the vehicle under the spring; 、 respectively represent the vertical displacement of the road surface; 、 respectively represent the front and rear axle suspension damping values; 、 respectively represent the front and rear axle suspension stiffness values; 、 respectively represent the front and rear tire stiffness values; represent the sprung mass; 、 respectively represent the front and rear axle unsprung mass; a, b respectively represent the distance from the front and rear axles to the center of mass; represent the moment of inertia about the Y axis; 、 respectively represent the front and rear axle active vertical force (control variable); respectively represent the front and rear axle road surface disturbance;

[0216] MPC derivation process:

[0217] State space equation of continuous system:

[0218] ;

[0219] ;

[0220] ;

[0221] ;

[0222] wherein: 、 respectively represent the dimensions of A and B; the present application takes n=8; p=2.

[0223] Discretize the model as a prediction model: (forward Euler method)

[0224] ;

[0225] wherein: Ts is the discrete time; represents the state quantity of the kth step of prediction, represents the control quantity of the kth step of prediction.

[0226] ;

[0227] ;

[0228] Let ;

[0229] Predict the N-step state:

[0230] ;

[0231] ;

[0232] ;

[0233]

[0234] ;

[0235] where: , denote the state and control quantities at the k+1 step predicted at the k step.

[0236] Let:

[0237] ;

[0238] ;

[0239] Obtain:

[0240] ;

[0241] where:

[0242] ;

[0243] ;

[0244] where: denotes the dimension of ; denotes the dimension of ; denotes the dimension of M; denotes the dimension of C.

[0245] The cost function is calculated as follows:

[0246] ;

[0247] Weight coefficients:

[0248] ;

[0249] ;

[0250] ;

[0251] Q is the weight of state quantity, R is the weight of input quantity, F is the weight of final value of state quantity; the greater the weight coefficient is, the more the optimization tends to this item smaller;

[0252] Substitute Xk into the cost function to simplify the above formula to obtain:

[0253] ;

[0254] Wherein:

[0255] ;

[0256] ;

[0257] ;

[0258] ;

[0259] ;

[0260] The input value Uk is obtained by solving the cost function J, which is a fixed value and does not affect the solution result, so it is obtained:

[0261] .

[0262] Finally, the value of the control quantity at each time is solved by function to achieve the purpose of optimal control.

[0263] The suspension damping value is obtained from the damping map Figure 6 in the Figure Two , where cdc_force represents the damping force, current represents the damping current value, and DampSpd represents the damping moving speed;

[0264] The suspension stiffness value is obtained from the following formula:

[0265]

[0266]

[0267] Wherein: , respectively represent the front and rear axle air spring stiffness; , respectively represent the front and rear axle suspension force calculated by MPC; , respectively represent the front and rear axle spring vertical displacement; , respectively represent the front and rear axle spring vertical displacement;

[0268] The four-degree-of-freedom suspension model is converted into a state space equation and discretized to obtain a prediction model, and then a state prediction equation of future N steps is derived; a cost function including a state quantity weight matrix Q, an input quantity weight matrix R and a state final value weight matrix F is designed, a zero pitch angle is taken as a core target, the predicted state is substituted into the cost function and simplified, an optimal input sequence is solved, suspension stiffness, damping and brake force distribution strategies are dynamically adjusted, a closed-loop feedback of a vehicle body posture sensor is used to correct a control instruction (completed through vehicle parameter preprocessing) in real time, dynamic vertical force distribution and multi-modal brake collaborative control suspension pitch are realized.

[0269] The application further discloses a suspension pitch collaborative control system combining dynamic vertical force distribution and multi-modal braking.

[0270] The application realizes deep coupling of the suspension and the brake system by combination of the quintic polynomial and the MPC, breaks through the limitation of traditional single system control, and is a key to improving pitch suppression effect; the vertical force on the vehicle is accurately calculated by a four-degree-of-freedom suspension model, expected acceleration transmission and model predictive control MPC, and dynamic and accurate control of the suspension force is realized.

[0271] Although the application has been fully described in the foregoing by general description and specific embodiments, some modifications or improvements can be made on the basis of the application, which is obvious to those skilled in the art. Therefore, these modifications or improvements made on the basis of not deviating from the spirit of the application all belong to the scope of protection required by the application.

Claims

1. A method of suspension pitch coordination control combining dynamic vertical force distribution and multi-modal braking, by setting a plurality of sensors on the vehicle to obtain vehicle parameters that need to be pre-processed, characterized in that: The method comprises the following steps: Step 1: obtaining a target deceleration of a driver; simultaneously, controlling a brake torque distribution unit and a suspension system in real time by defining a state machine in an electronic control unit (ECU); Step 2: obtaining a desired deceleration through a five-order polynomial smooth transition deceleration; Step 3: calculating a target brake torque of a vehicle at low speed and a vertical force of a tire according to the desired deceleration obtained in step 2, and inputting the brake torque distribution unit and a four-degree-of-freedom suspension model; converting the four-degree-of-freedom suspension model into a state space equation and discretizing the state space equation to obtain a prediction model, and then deriving a state prediction equation for future N steps; designing a cost function comprising a state quantity weight matrix Q, an input quantity weight matrix R and a state final value weight matrix F, taking a zero pitch angle as a core target, substituting the predicted state into the cost function and simplifying, and solving to obtain an optimal input sequence, so as to dynamically adjust a suspension stiffness, a damping and a brake force distribution strategy, and using a closed-loop feedback of a vehicle body posture sensor to correct a control instruction in real time, and realizing dynamic vertical force distribution and multi-modal brake collaborative control suspension pitch.

2. The suspension pitch coordination control method combining dynamic vertical force distribution and multi-modal braking according to claim 1, characterized in that: The state machine for real-time control of the brake torque distribution unit and the suspension system has the following operation logic: When the brake anti-pitch state machine is running, first, vehicle state safety inspection is performed, whether each parameter is in a safe range is determined by comparing the vehicle related parameters with the preset threshold, only when all parameters are in the safe range, it is determined that the brake system is normal, otherwise it is determined that there is a risk; After completing the safety inspection, the minimum acceleration target value is calculated in combination with the engine force, the slope and the preset constant and interpolation data, and a fixed lower limit and a correction coefficient are also considered in the calculation process, and the final result is output.

3. The method of claim 1, wherein the method is characterized by: The state machine comprises five modes of disable, passive, active, slope close and emergency control, and the conversion between modes is realized through different trigger signals; When the target mode is opened and the driver enables the system, the system is converted from the disable mode to the passive mode; When the target mode is closed or the driver does not enable the system, the system is converted from the passive mode to the disable mode; When the specific speed condition is met, there is no emergency situation, the system boundary is normal and the minimum acceleration target value meets the requirements, the system is converted from the passive mode to the active mode; In the active mode, if an unstable control situation occurs, the target mode changes, the driver does not enable the system or the relationship between the system target brake force and the driver target brake force does not meet the conditions, the system is converted to the passive mode; When the state machine detects a specific emergency situation, the emergency control mode is entered; When the duration of the emergency control mode meets certain conditions, or the brake force, the target mode, the driver's enable mode, the system is converted to the passive mode; When the state machine detects that the vehicle is stationary and the duration of the active mode exceeds the limit condition, the active mode is converted to the slope close mode; When the vehicle is stationary, the emergency control state is converted to the slope close state.

4. The suspension pitch control method of claim 3, wherein: When the vehicle speed is lower than the set threshold and the brake pressure meets the requirements, the activation time of the related brake safety system is detected, if the driver target pressure is too high or the activation time exceeds the specified time, the vehicle is marked as being in an unstable control state; When the system switches from passive mode to active mode, the virtual running distance and the actual braking distance are calculated by the current actual acceleration and the expected acceleration at the last time, and the low-speed braking distance anomaly level is output by comparing the difference between the two with the set threshold value; When the system switches from non-active mode to active mode, the reference pressure value is saved, and different levels of driver over-ride operation during low-speed driving are marked according to the increment of the current pressure and the reference pressure and different threshold values set; When the driver turns on the comfort mode of the vehicle, the vehicle does not appear in an emergency state, and the road surface is smooth, the low-speed driving brake shortage flag is output by accumulating the time and calculating the wheel speed operation.

5. The method of claim 4, wherein the method is characterized by: The state machine uses an enumeration method to define multiple brake-related detection results as independent enumeration values and assign corresponding priorities and processing rules. At the same time, the system running state is also set as different enumeration constants. By judging whether the enumeration value of the current detection result is triggered one by one, combining the driver's operation instruction, time limit condition and emergency information, and according to the preset priority rule, it is directly mapped to the corresponding system state enumeration value to realize the full-process management and logic arbitration of the brake system.

6. The method of claim 1, wherein: The expected deceleration is calculated as follows: 1) Assume target deceleration is a quintic polynomial: ； Where A, B, C, D, E, and F are polynomial coefficients, and t is time. Corresponding to the first derivative: ； Corresponding to the second derivative: ； 2) List the boundary conditions: ① At t = 0: Position constraint: ； First derivative constraint: ； Second derivative constraint: ； (ii) at t = t for smooth transition time:​ Position constraint: ； First derivative constraint: ； Second derivative constraint: ； 3) Bring the known D, E, and F into the boundary conditions: Position constraint: ； First derivative constraint: ； Second derivative constraint: ； 4) Summarize in matrix form: Solve A, B, and C to get the final fitted quintic polynomial curve: 5) Slope compensation to get the final expected acceleration: is the compensated desired acceleration; is the road pitch angle.

7. The method of claim 6, wherein the method is characterized by: Calculate the braking torque by the expected deceleration: First, calculate the minimum allowed longitudinal force according to the preset minimum protection pressure through the pressure to force conversion coefficient, and take the absolute value of the driver's target force as the maximum allowed longitudinal force. Then, judge the activation condition. When the system state is neither passive nor disabled and the minimum force does not exceed the maximum force, the system is activated. After activation, the expected deceleration is converted to the expected longitudinal braking force through Newton's second law, and the braking force threshold is set to ensure that the force is within a safe range. For the target force output in the activated state, a first-order low-pass filter formula is used for smoothing to avoid sudden changes in force. If it is in a non-activated state or first activated, it is directly assigned a value. Convert the target braking force to braking torque, and give different weights to the front and rear wheels: The braking torque formula is: ； ； , target front and rear wheel braking torques; , front and rear wheel braking torque distribution weight; target braking torque to target braking torque coefficient, target braking force.

8. The method of claim 1, wherein: Desired acceleration With lateral acceleration Solving for the tire vertical force, the vertical force equation is: ； ； ； ； 、 、 、 represents the vertical force of each tire; m represents the mass of the vehicle; g represents the acceleration of gravity; a, b represent the distance from the mass center of the vehicle to the front axle and the rear axle, respectively; represents the wheelbase, L = a + b; represents the height of the mass center of the vehicle; represents the desired acceleration of the vehicle; represents the lateral acceleration of the vehicle; represents the front wheel track; represents the rear wheel track.

9. The method of claim 1, wherein: The four-degree-of-freedom suspension model is a state space equation: ； ； wherein: denotes a state variable; denotes a system observation; denotes a control variable of the system; denotes a road disturbance; Where: ； ； ； ； wherein, represents the vertical velocity of the vehicle mass center position; represents the pitch angular velocity of the vehicle; represents the vertical velocity on the front and rear axle springs; , respectively represent the vertical displacement on the front and rear axle springs of the vehicle; , respectively represent the vertical displacement under the front and rear axle springs of the vehicle; , respectively represent the road surface vertical displacement; , respectively represent the front and rear axle suspension damping values; , respectively represent the front and rear axle suspension stiffness values; , respectively represent the front and rear tire stiffness values; represents the sprung mass; , respectively represent the front and rear axle unsprung mass; a, b respectively represent the distance from the front and rear axle to the mass center; represents the moment of inertia about the Y axis; , respectively represent the front and rear axle active vertical force (control variable); respectively represent the front and rear axle road surface disturbance; MPC derivation process: State space equation of continuous system: ； ； ； ； wherein: , respectively denote the dimensions of A, B. Discretize the model as a prediction model: ； wherein: Ts is a discrete time; denotes the predicted state quantity at the kth step, denotes the predicted control quantity at the kth step. ； ； Set ; Predict N-step state: ； ； ； ； wherein: , denotes the prediction of the state and control quantities of step k+1 at step k. Let: ； ； Get: ； Where: ； ； wherein: represents the dimension of represents the dimension of represents the dimension of M; represents the dimension of C.​​ The cost function is calculated as follows: ； Weight coefficients: ； ； ； Q is the weight of the state quantity, R is the weight of the input quantity, and F is the weight of the final value of the state quantity. The larger the weight coefficient, the more it tends to this item in optimization. Substitute Xk into the cost function to simplify the above formula to get: ； Where: ； ； ； ； ； The input value Ukis obtained by solving the cost function J, As a fixed value does not affect the solution, so get: 。 Finally, by The value of each time control variable of the function solution is to achieve the purpose of optimal control.

10. A suspension pitch coordination control system that combines dynamic vertical force distribution with multi-modal braking, characterized by: The system is based on the method of any of claims 1-9. The system is based on the method of any of claims 1-9.

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