A control method for a hybrid vehicle during cornering

Abstract

The present invention provides a cornering control method for a hybrid vehicle. The upper controller adopts adaptive cruise based on model predictive control to obtain the desired acceleration and the forces of the four tires, so as to achieve longitudinal vehicle following control of the hybrid vehicle; the lower controller adopts model predictive control with active suspension to output the active suspension force, so as to achieve lateral stability control of the hybrid vehicle; through the upper and lower controllers, the present invention ensures the ride comfort and handling stability of the hybrid vehicle during cornering; the energy recovery suspension module of the present invention uses electromagnetic force to determine the battery power. When the battery power is less than 0, the drive motor acts as a generator, and part of the suspension mechanical energy is converted into electrical energy and stored in the battery to achieve energy regeneration, thereby ensuring the fuel economy of the hybrid vehicle during cornering.

Description

Technical Field

[0001] The present invention belongs to the technical field of dynamic control of hybrid vehicles, and particularly relates to a control method for a hybrid vehicle driving on a curve. Background Art

[0002] With the current situation of global environmental deterioration and energy shortage, hybrid vehicles are the most ideal transitional vehicle models today, and their related technologies are also the most popular research focuses in the current vehicle field.

[0003] When a hybrid vehicle is driving, due to the driver's intention, especially when accelerating or decelerating to change lanes to follow a target vehicle during curve driving, in this process, it is necessary to ensure both lateral stability during lane change and longitudinal following performance. However, for a traditional adaptive cruise following system, when the leading vehicle in front suddenly disappears, it will cause the vehicle to suddenly accelerate, resulting in an accident. Summary of the Invention

[0004] Aiming at the deficiencies in the prior art, the present invention provides a control method for a hybrid vehicle driving on a curve, which ensures the smoothness, handling stability and fuel economy of the hybrid vehicle driving on a curve.

[0005] The present invention achieves the above technical objectives through the following technical means.

[0006] A control method for a hybrid vehicle driving on a curve is specifically as follows:

[0007] The vehicle's overall vehicle dynamics model inputs the vehicle's acceleration a e , the relative displacement δd between vehicles, the relative speed δv between vehicles, the sideslip angle β of the center of mass and the yaw angle of the vehicle into the upper controller. The upper controller adopts model predictive control-based adaptive cruise to obtain the desired acceleration a des and the four tire forces F xij , and realizes the longitudinal following control of the hybrid vehicle; where i, j = 1, 2;

[0008] The suspension dynamics model inputs the vertical vibration displacement Z of the vehicle body, the vertical vibration rate the vertical vibration acceleration the roll angle φ of the vehicle body, the roll angle rate the roll angular acceleration of the vehicle body the pitch angle θ of the vehicle body, the pitch angle rate the pitch angular acceleration of the vehicle body into the lower controller. The lower controller adopts model predictive control of active suspension and outputs the active suspension force F i , and realizes the lateral stability control of the hybrid vehicle; where i = 1, 2, 3, 4.

[0009] For a further technical solution, the longitudinal following control of the hybrid vehicle is specifically as follows according to whether the hybrid vehicle is in a cornering condition:

[0010] When the hybrid vehicle is in a non-cornering condition, the adaptive cruise objective function is minimized:

[0011]

[0012] When the hybrid vehicle is in a cornering condition, both the adaptive cruise and the lateral stability objective functions are minimized:

[0013]

[0014] Where: J ACC and J VLS are the minimum objective functions of the vehicle in longitudinal following control and lateral stability control respectively, ω Δd and ω Δv , are the weight coefficients of distance, speed, and actual acceleration respectively, Δd and Δv are the relative distance and relative speed between the host vehicle and the leading vehicle, Δd ref and Δv ref are the relative reference distance and relative reference speed between the host vehicle and the leading vehicle respectively, ω β , ω Fxij are the weight coefficients of the sideslip angle of the center of mass, the yaw angle of the vehicle body, and the forces of the four tires respectively, β ref is the reference sideslip angle of the center of mass of the vehicle, is the reference yaw angle of the vehicle, F xij is the forces of the four tires, i, j = 1, 2.

[0015] For a further technical solution, the model predictive control of the active suspension, that is, an optimal objective function of the vehicle suspension model is established, and the specific expression is:

[0016]

[0017] Where: ω Z and ω θ and ω φ , ω Zui are the weight coefficients of vertical vibration acceleration, pitch acceleration, roll acceleration, vertical vibration rate, pitch angle rate, roll angle rate, vertical vibration displacement, pitch angle, roll angle, unsprung vertical vibration rate, and unsprung vertical vibration displacement respectively, Z ref , θ ref , φ ref, Z ui_ref are respectively the reference vertical acceleration of the centroid, the reference vertical velocity of the centroid, the reference vertical displacement of the centroid, the reference pitch angular acceleration, the reference pitch angular velocity, the reference pitch angle, the reference roll angular acceleration, the reference roll angular velocity, the reference roll angle, the reference vibration velocities and reference vibration displacements of the four unsprung masses, where i = 1, 2, 3, 4.

[0018] Further technical solution, the vehicle's overall vehicle dynamics model includes an HEV powertrain model and an 8-degree-of-freedom dynamics model. The HEV powertrain model includes a driver module, a hybrid vehicle module, a torque coupling module, and an energy management module. In the hybrid vehicle module, the HCU determines the vehicle demand torque T req according to the pedal opening and the real-time speeds of the engine and the drive motor, and then according to the demand torque T req , the SOC value, and the actual vehicle speed v act controls the vehicle operation mode M, and the vehicle operation mode M includes a pure electric mode, an engine drive mode, a combined drive mode, a driving power generation mode, and a regenerative braking mode.

[0019] Even further technical solution, the operating conditions of the pure electric mode are simultaneously satisfied: the demand torque T req is less than the engine shutdown torque T e_off , the current battery SOC value is greater than the minimum battery SOC value, and the actual vehicle speed v act is less than the minimum vehicle speed limit v low for pure electric vehicle driving; in the pure electric mode, the engine is in the shutdown state, and the target torque T e is 0; the drive motor is in the electric drive state, and the target torque T m is the demand torque T req .

[0020] Even further technical solution, the operating conditions of the engine drive mode are simultaneously satisfied: the demand torque T req is between the minimum torque T e_low and the maximum torque T e_high in the high-efficiency area of the engine, the current battery SOC value is between the minimum battery SOC value and the maximum battery SOC value, and the actual vehicle speed v act is greater than the minimum vehicle speed limit v low for pure electric vehicle driving; in the engine drive mode, the engine is in the startup state, and the target torque T e is the demand torque T req ; the drive motor is in the shutdown state, and the target torque T m is 0.

[0021] A further technical solution is that the operating conditions of the combined drive mode simultaneously satisfy: the required torque T req is greater than the maximum engine torque T e_max , the current battery SOC value is greater than the minimum battery SOC value, and the actual vehicle speed v act is greater than the minimum speed limit v low for pure electric vehicle driving; in the combined drive mode, the engine is in the on state, and the target torque T e is the maximum engine torque T e_max ; the drive motor is in the electric drive state, and the target torque T m is the difference between the required torque T req and the engine target torque T e .

[0022] A further technical solution is that the operating conditions of the driving power generation mode simultaneously satisfy: the required torque T req is between the engine shutdown torque T e_off and the maximum torque T e_high , the current battery SOC value is less than the minimum battery SOC value, and the actual vehicle speed v act is greater than the minimum speed limit v low for pure electric vehicle driving; in the driving power generation mode, the engine is in the on state, and the target torque T e is the sum of the required torque T req and the driving charging torque T charge ; the drive motor is in the electric drive state, and the target torque T m is the driving charging torque -T charge .

[0023] A further technical solution is that the operating conditions of the regenerative braking mode simultaneously satisfy: the required torque T req is less than 0, and the current battery SOC value is between the minimum and maximum battery SOC values; in the regenerative braking mode, the engine is in the state of not outputting torque, and the target torque T e is 0; the drive motor is in the power generation state, and the target torque T m is the required torque T req .

[0024] A further technical solution is that the 8-degree-of-freedom dynamics model includes the coupling of the vehicle body dynamics model and the suspension dynamics model. The suspension dynamics model includes a suspension controller and an energy harvesting suspension module. The suspension controller establishes equations for vehicle body acceleration, suspension dynamic deflection, and vehicle body dynamic load based on the road surface unevenness during vehicle driving, and outputs the electromagnetic force of the vehicle. The energy harvesting suspension module uses the electromagnetic force to determine the battery power. When the battery power is less than 0, the drive motor acts as a generator, and part of the suspension mechanical energy is converted into electrical energy and stored in the battery to achieve energy regeneration.

[0025] The beneficial effects of the present invention are as follows:

[0026] (1) In the present invention, the vehicle's overall vehicle dynamics model inputs the vehicle's own acceleration, relative displacement between vehicles, relative speed between vehicles δv, sideslip angle of the center of mass, and vehicle yaw angle into the upper-layer controller. The upper-layer controller adopts model predictive control-based adaptive cruise to obtain the desired acceleration and the four tire forces, realizing the longitudinal following control of the hybrid vehicle. The suspension dynamics model inputs the vertical vibration displacement of the vehicle body, vertical vibration speed, vertical vibration acceleration, roll angle of the vehicle body, roll angle speed of the vehicle body, roll angle acceleration of the vehicle body, pitch angle of the vehicle body, pitch angle speed of the vehicle body, and pitch angle acceleration of the vehicle body into the lower-layer controller. The lower-layer controller adopts model predictive control of active suspension to output the active suspension force, realizing the lateral stability control of the hybrid vehicle. Through the upper and lower layer controllers, the present invention ensures the smoothness and handling stability of the hybrid vehicle during cornering.

[0027] (2) The 8-degree-of-freedom dynamics model in the present invention includes the coupling of the vehicle body dynamics model and the suspension dynamics model. The suspension dynamics model includes a suspension controller and an energy-harvesting suspension module. The suspension controller establishes equations for vehicle body acceleration, suspension dynamic deflection, and vehicle body dynamic load based on the road surface unevenness during vehicle driving, and outputs the electromagnetic force of the vehicle. The energy-harvesting suspension module uses the electromagnetic force to determine the battery power. When the battery power is less than 0, the drive motor acts as a generator, and part of the suspension mechanical energy is converted into electrical energy and stored in the battery, realizing energy regeneration and ensuring the fuel economy of the hybrid vehicle during cornering. Description of the Drawings

[0028] Figure 1 is a schematic structural diagram of the vehicle's overall vehicle dynamics model of the present invention;

[0029] Figure 2 is a schematic diagram of the hierarchical control of the hybrid vehicle cornering control of the present invention. Detailed Embodiments

[0030] The present invention will be further described below in conjunction with the drawings and specific embodiments, but the protection scope of the present invention is not limited thereto.

[0031] A method for controlling a hybrid vehicle during cornering, through the coordinated control of model predictive control-based adaptive cruise and energy-harvesting suspension, taking into account the motor energy recovery control, realizing the driving safety and comfort of the hybrid vehicle, and ensuring the fuel economy. Refer to Figure 2 , the control method includes the following steps:

[0032] Step 1: Establish an overall vehicle dynamics model of the hybrid vehicle

[0033] The overall vehicle dynamics model of a hybrid vehicle includes a HEV (Hybrid Electric Vehicle) powertrain model and an 8-degree-of-freedom dynamics model. The 8-degree-of-freedom dynamics model includes the coupling of a body dynamics model and a suspension dynamics model. The HEV powertrain model includes a driver module, a hybrid vehicle module, a torque coupling module, and an energy management module, as Figure 1 shown;

[0034] The driver module uses PID (Proportional Integral Derivative) control. By adjusting the integral, differential, and proportional coefficients in the PID controller, the opening degrees of the accelerator pedal and the brake pedal are output. The specific expression of the driver module is:

[0035]

[0036] where: U driver (t) is the pedal adjustment opening degree, that is, the opening degree of the accelerator pedal or the brake pedal; K p , K i , K d are the proportional, integral, and differential adjustment coefficients of the PID controller respectively, v ref is the reference vehicle speed, v act is the actual vehicle speed, E(t) is the deviation between the reference vehicle speed and the actual vehicle speed. E(t)>0, E(t)=0, and E(t)<0 indicate that the vehicle is accelerating, stationary or cruising, and decelerating respectively.

[0037] In the hybrid vehicle module, the HCU (Hybrid Control Unit) determines the vehicle demand torque T req according to the pedal opening degree and the real-time speeds of the engine and the drive motor, and then controls the vehicle operation mode M according to the demand torque T req , the SOC value, and the actual vehicle speed v act . The specific formulas are as follows:

[0038] T req =f1(U driver (t),n e ,n m )

[0039] M=f2(T req ,SOC,v act )

[0040] where: n m is the drive motor speed, n e is the engine speed.

[0041] The vehicle operation mode M and the control strategy are specifically as follows:

[0042] ① Pure electric mode

[0043] The operating conditions are simultaneously satisfied: the required torque T req is less than the engine shutdown torque T e_off , the current battery SOC value is greater than the minimum battery SOC value, and the actual vehicle speed v act is less than the minimum vehicle speed limit v low during pure electric vehicle driving; in pure electric mode, the engine is in the off state, and the corresponding target torque T e is 0; the drive motor is in the electric drive state, and the corresponding target torque T m is the required torque T req .

[0044] ② Engine drive mode

[0045] The operating conditions are simultaneously satisfied: the required torque T req is between the minimum torque T e_low and the maximum torque T e_high in the high-efficiency area of the engine, the current battery SOC value is between the minimum and maximum battery SOC values, and the actual vehicle speed v act is greater than the minimum vehicle speed limit v low during pure electric vehicle driving; in engine drive mode, the engine is in the on state, and the corresponding target torque T e is the required torque T req ; the drive motor is in the off state, and the corresponding target torque T m is 0.

[0046] ③ Combined drive mode

[0047] The operating conditions are simultaneously satisfied: the required torque T req is greater than the maximum engine torque T e_max , the current battery SOC value is greater than the minimum battery SOC value, and the actual vehicle speed v act is greater than the minimum vehicle speed limit v low during pure electric vehicle driving; in combined drive mode, the engine is in the on state, and the corresponding target torque T e is the maximum engine torque T e_max ; the drive motor is in the electric drive state, and the corresponding target torque T m is the difference between the required torque T req and the engine target torque T e .

[0048] ④ Vehicle power generation mode

[0049] The operating conditions are simultaneously satisfied: the required torque T req is between the engine shutdown torque T e_off and the maximum torque Te_high between, the current battery SOC value is less than the minimum battery SOC value, and the actual vehicle speed v act is greater than the minimum speed limit v during the driving of the pure electric vehicle low ; In the driving power generation mode, the engine is in the on state, and the corresponding target torque T e is the required torque T req and the driving charging torque T charge The sum of; The drive motor is in the electric drive state, and the corresponding target torque T m is the driving charging torque -T charge .

[0050] ⑤ Regenerative braking mode

[0051] The operating conditions are simultaneously satisfied: the required torque T req is less than 0, and the current battery SOC value is between the minimum and maximum battery SOC values; In the regenerative braking mode, the engine is in the state of not outputting torque, and the corresponding target torque T e is 0; The drive motor is in the power generation state, and the corresponding target torque T m is the required torque T req .

[0052] Determine the connection and disconnection of the clutch according to the engine speed and the drive motor speed. Based on the engine target torque and the motor target torque in different operating modes, the torque coupling module outputs the actually required engine torque and motor torque;

[0053] The clutch is divided into two states:

[0054] (1) The engine speed and the drive motor speed are inconsistent, the engine and the drive motor are not combined through the clutch, and the output actual torques are the engine target torque and the motor target torque respectively;

[0055] (2) The engine speed and the drive motor speed are consistent, the engine and the drive motor are engaged through the clutch, and the output actual torques are the motor target torque and the engine output torque respectively; Specifically, PID control is adopted to determine the engine output torque by controlling the engine speed and the motor speed difference.

[0056] PID control can be expressed as:

[0057]

[0058] where: T e (t) is the engine output torque when the clutch is engaged, k p , k i , k dare the proportional, integral, and derivative adjustment coefficients of PID control, e(t) is the deviation between the driving motor speed and the engine speed, n m is the driving motor speed, n e is the engine speed.

[0059] The torque coupling module outputs the actual required engine torque and motor torque acting on the transmission to obtain the transmission ratio under different operating modes. The vehicle body dynamics model calculates the sum of the actual torques of the engine and the driving motor, subtracts the corresponding driving vehicle resistance torque, combines the transmission ratio and the tire radius, and then obtains the actual vehicle acceleration according to Newton's theorem, and the actual vehicle speed is obtained through integration.

[0060] The energy management module is used to estimate the state of charge (SOC) of the battery and calculate the fuel consumption, and then feedback the SOC to the driving motor and the suspension controller to form a closed loop to ensure the economy of the vehicle during cornering.

[0061] In the regenerative braking mode, the calculation formula for SOC is:

[0062]

[0063] where: V bat is the battery voltage, R bat is the battery resistance, P bat is the battery power, Q bat is the battery charge.

[0064] The engine steady-state fuel consumption model is established by using the method of torque look-up, fuel consumption and interpolation, and the fuel consumption is calculated:

[0065]

[0066] where: m fuel is the fuel consumption at time t, is the fuel consumption rate at time t, n e is the engine speed, T e is the engine output torque, and t0 and t1 are the start and end times of the engine operation respectively.

[0067] The suspension dynamics model includes a suspension controller and an energy harvesting suspension module. The energy harvesting suspension is adopted, combined with the operating conditions of the driving motor in the regenerative braking mode, and the energy recovery of the hybrid vehicle is carried out simultaneously.

[0068] The suspension controller establishes equations for vehicle body acceleration, suspension dynamic deflection, and vehicle body dynamic load according to the road surface unevenness of the vehicle's travel, and outputs the electromagnetic force of the vehicle (i.e., the active force generated by the actuator).

[0069] The relationship between road surface unevenness and the actual vehicle speed is as follows:

[0070]

[0071] Among them: is the road surface unevenness rate, Z(t) is the road surface unevenness, and v act is the actual vehicle speed, and G q (n0) is the road surface unevenness coefficient, and ω0(t) is white noise.

[0072] The established equations for vehicle body acceleration, suspension dynamic deflection, and vehicle body dynamic load are as follows:

[0073]

[0074]

[0075] Among them: m s is the mass above the vehicle's springs, z is the vertical displacement of the vehicle body, is the vertical acceleration of the vehicle body, and k si (i = 1, 2, 3, 4) are the stiffness coefficients of the left front, right front, left rear, and right rear suspensions of the vehicle respectively, and k ui (i = 1, 2, 3, 4) are the stiffness coefficients of the left front, right front, left rear, and right rear tires of the vehicle respectively, and z si (i = 1, 2, 3, 4) are the vertical displacements of the left front, right front, left rear, and right rear suspensions of the vehicle respectively, and z ui (i = 1, 2, 3, 4) are the displacements below the springs of the left front, right front, left rear, and right rear of the vehicle respectively, and z ri (i = 1, 2, 3, 4) are the vertical road surface excitations (caused by road surface unevenness) of the left front, right front, left rear, and right rear tires of the vehicle respectively, and m ui (i = 1, 2, 3, 4) respectively represent the masses below the springs of the left front, right front, left rear, and right rear of the vehicle, l f and l r are the distances from the vehicle's center of mass to the front axle and the rear axle respectively, B r and B f are the body widths of the vehicle at the front axle and the rear axle respectively, and F i (i = 1, 2, 3, 4) are the active forces generated by the left front, right front, left rear, and right rear actuators of the vehicle respectively, I y is the moment of inertia about the y-axis, and I x is the moment of inertia about the x-axis, θ are the pitch angular acceleration and pitch angle respectively, φ are the roll angular acceleration and roll angle respectively.

[0076] The energy-feeding suspension module uses the electromagnetic damping force of the vehicle to determine the battery power and current to obtain the SOC value. The formula for the battery power is:

[0077]

[0078] Where: k e is the motor coefficient, k i is the thrust constant, F ref is the ideal electromagnetic damping force (i.e. F1+F2+F3+F4), are the vertical vibration rates of the left front, right front, left rear and right rear suspension of the vehicle, are the unsprung vibration rates of the left front, right front, left rear and right rear of the vehicle respectively, and R is the resistance value of the energy feedback suspension.

[0079] Specifically, the energy-feeding suspension adopts a linear motor. When the power P>0, it means that the drive motor acts as a damper, that is, the drive motor converts electrical energy into mechanical energy and potential energy to reduce vibration; when the power P=0, it means that the drive motor is not working or all mechanical energy is converted into heat energy, and no electrical energy is consumed; when the power P<0, it means that the drive motor acts as a generator, and part of the suspension mechanical energy is converted into electrical energy, stored in the battery, realizing energy regeneration, and inputting the energy management module.

[0080] Step 2: The upper-level controller is used to implement the hybrid vehicle's longitudinal following control, and the lower-level controller is used to implement the lateral stability control. The vehicle's cornering control is achieved through the model predictive control-based curve adaptive cruise control and the suspension active model predictive control.

[0081] The upper controller will expect the acceleration a des 、Four tire forces F xij (i, j = 1, 2) Input vehicle dynamics model, where the expected acceleration a des Input HEV powertrain model, four tire forces F xij (i, j = 1, 2) is input into the vehicle body dynamics model; the vehicle dynamics model converts the vehicle acceleration a e , relative displacement δd, relative velocity δv, sideslip angle β and vehicle yaw angle Input the upper controller to form a feedback closed loop; among them, the sideslip angle β and the vehicle yaw angle Output from the vehicle body dynamics model, the vehicle acceleration a e , the workshop relative displacement δd, and the workshop relative speed δv are output by the HEV powertrain.

[0082] The lower controller converts the four suspension active forces F i(i = 1, 2, 3, 4) Input the suspension dynamics model; meanwhile, the suspension dynamics model inputs the vertical vibration displacement Z of the vehicle body, the vertical vibration velocity Vertical vibration acceleration Vehicle body roll angle φ, vehicle body roll rate Vehicle body roll acceleration Vehicle body pitch angle θ, vehicle body pitch rate Vehicle body pitch acceleration Input the lower-level controller to form a feedback closed loop.

[0083] The upper-level controller is used to implement longitudinal following control for hybrid vehicles, adopting adaptive cruise based on model predictive control; select the state variable x1, the control variable u1, and the disturbance variable ω1, and satisfy the following state equation:

[0084]

[0085] Linearize and discretize the above state equation, and the specific formulas are as follows:

[0086]

[0087] Where: a p Is the acceleration of the target vehicle, A1, B1, and C1 are the coefficient matrices of the state variable, control variable, and disturbance variable under linearization respectively, A 1k , B 1k , C 1k Are the coefficient matrices of the state variable, control variable, and disturbance variable under discretization respectively.

[0088] The vehicle body dynamics model mainly involves the vehicle body dynamics equation, which is specifically as follows:

[0089]

[0090] Where: v y Are the longitudinal acceleration and lateral velocity of the vehicle respectively, Is the yaw rate of the vehicle's center of mass, Is the yaw rate of the vehicle, F xij (i, j = 1, 2), F yij (i, j = 1, 2) Are the longitudinal and lateral driving forces of the vehicle's four tires respectively, I z Is the moment of inertia about the z-axis, a and b are the distances from the vehicle's center of mass to the front axle and rear axle respectively, T is the distance between the vehicle's left and right wheels, δ is the steering angle of the vehicle's front wheels, and m is the vehicle mass.

[0091] Based on the above vehicle body dynamics equation, establish the optimal objective function for vehicle longitudinal following control, which is specifically as follows:

[0092]

[0093] where: ω Δd and ω Δv , ω β , ω Fxij (i, j = 1, 2) are the weight coefficients of distance, speed, actual acceleration, sideslip angle of the center of mass, yaw angle of the vehicle body, and four tire forces respectively, Δd and Δv are the relative distance and relative speed between the host vehicle and the leading vehicle, β ref is the reference sideslip angle of the center of mass of the vehicle, is the reference yaw angle of the vehicle, Δd ref , Δv ref are the relative reference distance and relative reference speed between the host vehicle and the leading vehicle respectively.

[0094] When the hybrid vehicle is in a non-curved road condition, it is necessary to minimize the adaptive cruise objective function, that is, the relative displacement Δd, relative speed Δv, and desired acceleration a des are at minimum values; the specific formula is:

[0095]

[0096] When the hybrid vehicle is in a curved road condition, it is necessary to simultaneously minimize the objective functions of adaptive cruise and lateral stability, that is, the relative displacement Δd, relative speed Δv, desired acceleration a des , sideslip angle of the center of mass β, yaw angular velocity and four tire forces F xij (i, j = 1, 2) are at minimum values, specifically as follows:

[0097]

[0098] where: J ACC and J VLS are the minimum objective functions of the vehicle longitudinal following control and lateral stability control respectively.

[0099] The reference sideslip angle of the center of mass β ref and the reference yaw angle are obtained in the following manner: The wheel sensor obtains the front wheel steering angle signal, and then obtains the change curve of the front wheel steering angle of the vehicle. Considering the influence of the road adhesion coefficient and the actual running transient characteristics of the vehicle, a two-degree-of-freedom reference model of the hybrid vehicle is established. The specific formula is as follows:

[0100]

[0101]

[0102] Δdref , Δv ref The specific values are set as follows:

[0103]

[0104] Among them: β1, are respectively the ideal sideslip angle of the vehicle's center of mass and the reference value of the yaw angle, δ is the front wheel steering angle of the vehicle, l is the wheelbase of the vehicle, m is the body mass, K is the stability factor, τ β s is the inertia constant of the first-order filter, g is the acceleration due to gravity, μ is the road surface adhesion coefficient, Δd is the relative displacement, and Δv is the relative velocity.

[0105] The lower-layer controller is used to achieve lateral stability control. Model predictive control is adopted, and the state variables x2, control variables u2, and disturbance variables ω2 are selected and satisfy the following state equations:

[0106]

[0107] For the above state equations, linearization and discretization are performed, and the specific formulas are as follows:

[0108]

[0109] Among them: A2, B2, and C2 are respectively the coefficient matrices of the state variables, control variables, and disturbance variables under linearization, A 2k , B 2k , C 2k are respectively the coefficient matrices of the state variables, control variables, and disturbance variables under discretization, Z, are respectively the displacement, velocity, and acceleration of the vehicle body vibration, θ, are respectively the pitch angle, pitch angle rate, and pitch angle acceleration of the vehicle, φ, are respectively the roll angle, roll angle rate, and roll angle acceleration of the vehicle body, Z ui (i = 1, 2, 3, 4) are respectively the vibration displacements of the unsprung masses of the left front, right front, left rear, and right rear of the vehicle, are respectively the vibration velocities of the unsprung masses of the left front, right front, left rear, and right rear of the vehicle, F i (i = 1, 2, 3, 4) are respectively the active forces of the left front, right front, left rear, and right rear suspensions of the vehicle, Z ri (i = 1, 2, 3, 4) are respectively the vibration displacements of the left front, right front, left rear, and right rear tires of the vehicle.

[0110] The model predictive control of the active suspension, that is, the optimal objective function of the vehicle suspension model is established, and the specific expression is:

[0111]

[0112] Wherein: ω Z 、ω θ 、 are the weight coefficients of vertical vibration acceleration, pitch acceleration, roll acceleration, vertical vibration rate, pitch angle rate, roll angle rate, vertical vibration displacement, pitch angle, roll angle, vertical vibration rate of the unsprung mass, and vertical vibration displacement of the unsprung mass respectively, Z ref 、 θ ref 、 φ ref 、 Z ui_ref (i = 1, 2, 3, 4) are the reference vertical acceleration of the reference centroid, reference vertical rate of the reference centroid, reference vertical displacement of the reference centroid, reference pitch angular acceleration, reference pitch angle rate, reference pitch angle, reference roll angular acceleration, reference roll angle rate, reference roll angle, and reference vibration rates and reference vibration displacements of the unsprung masses of the left front, right front, left rear, and right rear of the vehicle respectively. The above reference values are all set to 0, thereby suppressing the vertical vibration, roll, and pitch problems during the vehicle's cornering, and ensuring the ride comfort and handling stability.

[0113] The described embodiment is a preferred implementation manner of the present invention, but the present invention is not limited to the above implementation manner. Without departing from the essential content of the present invention, any obvious improvements, substitutions, or modifications that those skilled in the art can make all fall within the protection scope of the present invention.

Claims

1. A control method for a hybrid vehicle during cornering, characterized in that: The vehicle's overall vehicle dynamics model takes the vehicle's own acceleration a e , the relative displacement δd between vehicles, the relative velocity δv between vehicles, the sideslip angle β of the center of mass, and the vehicle's yaw angle as inputs to the upper-layer controller. The upper-layer controller uses model predictive control-based adaptive cruise control to obtain the desired acceleration a des and the four tire forces F xij to achieve longitudinal following control of hybrid vehicles; where i, j = 1, 2; The suspension dynamics model takes the vertical vibration displacement Z of the vehicle body, the vertical vibration velocity and the vertical vibration acceleration of the vehicle body, the roll angle φ of the vehicle body, the roll angle velocity and the roll angle acceleration of the vehicle body, the pitch angle θ of the vehicle body, the pitch angle velocity and the pitch angle acceleration of the vehicle body as inputs to the lower-level controller. The lower-level controller uses model predictive control for active suspension and outputs the active suspension force F i , to achieve lateral stability control of the hybrid vehicle; where i = 1, 2, 3, 4; The longitudinal following control of the hybrid vehicle is specifically as follows according to whether the hybrid vehicle is in a cornering condition: When the hybrid vehicle is in a non-cornering condition, the adaptive cruise objective function is minimized: When the hybrid vehicle is in a cornering condition, both the adaptive cruise and the lateral stability objective functions are minimized: Where: J ACC and J VLS are the minimum objective functions for longitudinal vehicle following control and lateral stability control respectively, ω Δd and ω Δv , are the weight coefficients of distance, speed, and actual acceleration respectively, Δd and Δv are the relative distance and relative speed between the host vehicle and the leading vehicle, Δd ref and Δv ref are the relative reference distance and relative reference speed between the host vehicle and the leading vehicle respectively, ω β , and ω Fxij are the weight coefficients of sideslip angle of the center of mass, body yaw angle, and four tire forces respectively, β ref is the reference sideslip angle of the center of mass of the vehicle, is the reference yaw angle of the vehicle, F xij is the four tire forces, i, j = 1, 2.

2. The control method for a hybrid vehicle during cornering according to claim 1, wherein The model predictive control of the active suspension, that is, an optimal objective function of the vehicle suspension model is established, and the specific expression is: Wherein: ω Z 、 ω θ 、 ω φ 、 are the weight coefficients of vertical vibration acceleration, pitch acceleration, roll acceleration, vertical vibration velocity, pitch angle velocity, roll angle velocity, vertical vibration displacement, pitch angle, roll angle, unsprung vertical vibration velocity and unsprung vertical vibration displacement respectively, Z ref 、 θ ref 、 φ ref 、 Z ui_ref 、 Z ui 、 are the reference vertical acceleration of the center of mass, reference vertical velocity of the center of mass, reference vertical displacement of the center of mass, reference pitch angular acceleration, reference pitch angular velocity, reference pitch angle, reference roll angular acceleration, reference roll angular velocity, reference roll angle, reference vibration velocities and reference vibration displacements of the four unsprung masses, vibration displacements and vibration velocities of the four unsprung masses respectively, where i = 1, 2, 3, 4; J min is the optimal objective function of the vehicle suspension model.

3. The cornering control method for a hybrid vehicle according to claim 1, characterized in that, The vehicle's overall vehicle dynamics model includes an HEV powertrain model and an eight-degree-of-freedom dynamics model. The HEV powertrain model includes a driver module, a hybrid vehicle module, a torque coupling module, and an energy management module. In the hybrid vehicle module, the HCU determines the vehicle demand torque T based on the pedal opening and the real-time speeds of the engine and the drive motor. req Furthermore, based on the demand torque T req , the SOC value, and the actual vehicle speed v act to control the vehicle operation mode M, which includes pure electric mode, engine drive mode, combined drive mode, vehicle power generation mode, and regenerative braking mode.

4. The control method for a hybrid vehicle during cornering according to claim 3, characterized in that, The operating conditions of the pure electric mode are simultaneously satisfied: the required torque T req is less than the engine shutdown torque T e_off , the current battery SOC value is greater than the minimum battery SOC value, and the actual vehicle speed v act is less than the minimum vehicle speed limit v low for pure electric vehicle driving; in the pure electric mode, the engine is in the shutdown state, and the target torque T e is 0; the drive motor is in the electric drive state, and the target torque T m is the required torque T req .

5. The control method for a hybrid vehicle during cornering according to claim 3, characterized in that, The operating conditions of the engine drive mode are simultaneously satisfied: the required torque T req is between the minimum torque T e_low and the maximum torque T e_high in the high-efficiency area of the engine, the current battery SOC value is between the minimum and maximum values of the battery SOC, and the actual vehicle speed v act is greater than the minimum speed limit v low for pure electric vehicle driving; in the engine drive mode, the engine is in the on state, and the target torque T e is the required torque T req ; the drive motor is in the off state, and the target torque T m is 0.

6. The control method for a hybrid vehicle during cornering according to claim 3, characterized in that, The operating conditions of the combined drive mode are simultaneously satisfied: the required torque T req is greater than the maximum torque T e_max of the engine, the current battery SOC value is greater than the minimum battery SOC value, and the actual vehicle speed v act is greater than the minimum vehicle speed limit v low for pure electric vehicle driving; in the combined drive mode, the engine is in the on state, and the target torque T e is the maximum torque T e_max of the engine; the drive motor is in the electric drive state, and the target torque T m is the difference between the required torque T req and the engine target torque T e .

7. The hybrid vehicle cornering control method according to claim 3, wherein The operating conditions of the driving power generation mode are simultaneously satisfied: the required torque T req is between the engine-off torque T e_off and the maximum torque T e_high , the current battery SOC value is less than the minimum battery SOC value, and the actual vehicle speed v act is greater than the minimum speed limit v low for the pure electric vehicle to travel; in the driving power generation mode, the engine is in the on state, and the target torque T e is the sum of the required torque T req and the driving charging torque T charge ; the drive motor is in the electric drive state, and the target torque T m is the driving charging torque -T charge .

8. The control method for a hybrid vehicle during cornering according to claim 3, characterized in that, The operating conditions of the regenerative braking mode are simultaneously satisfied: the required torque T req is less than 0, and the current battery SOC value is between the minimum and maximum values of the battery SOC; in the regenerative braking mode, the engine is in a state of not outputting torque, and the target torque T e is 0; the drive motor is in a power generation state, and the target torque T m is the required torque T req .

9. The control method for a hybrid vehicle during cornering according to claim 3, characterized in that, The 8-degree-of-freedom dynamics model includes the coupling of the vehicle body dynamics model and the suspension dynamics model. The suspension dynamics model includes a suspension controller and an energy-harvesting suspension module. The suspension controller establishes equations for vehicle body acceleration, suspension dynamic deflection, and vehicle body dynamic load according to the road surface unevenness during vehicle driving, outputs the electromagnetic force of the vehicle, and the energy-harvesting suspension module uses the electromagnetic force to determine the battery power. When the battery power is less than 0, the drive motor acts as a generator, and part of the suspension mechanical energy is converted into electrical energy and stored in the battery to achieve energy regeneration.

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