CN106800040B - A vehicle electronically controlled compound steering system and its multi-objective optimization method - Google Patents

Abstract

The invention discloses an automobile electric control composite steering system and a multi-objective optimization method thereof. The mechanical transmission module comprises a steering wheel, a steering column, a circulating ball steering gear, a steering tie rod and the like; the electric control hydraulic power-assisted module comprises a hydraulic tank, a hydraulic pump driving motor, a rotary valve and the like; the electric power assisting module comprises an arc-shaped linear motor and the like. And determining the participation mode of the electro-hydraulic power assistance in the composite steering system according to the preference of a driver, road conditions, vehicle speed, the steering wheel rotation angle of the driver, the rotating speed and the like. And the important parameters of the composite steering system are optimized by a novel multi-objective optimization method by taking the automobile steering road feel, the steering sensitivity and the steering energy consumption as optimization targets and the steering power-assisted range as constraint conditions, so that the comprehensive performance of the composite steering system is improved.

Description

A vehicle electronically controlled compound steering system and its multi-objective optimization method

technical field

The invention relates to the field of automobile steering systems, in particular to an automobile electronically controlled compound steering system and a multi-objective optimization method thereof.

Background technique

Most of the existing steering systems use hydraulic power steering systems, electronically controlled hydraulic power steering systems and electric power steering systems. The traditional hydraulic power steering system, whose steering assistance is provided by the engine, still drives the hydraulic pump to work under non-steering conditions, and the steering condition accounts for about 10% of the vehicle's driving conditions, so it causes a certain waste of energy, and its The power assist characteristic is uncontrollable. When the car is at a low speed, the steering is heavy, and when the car is at a high speed, the steering sensitivity is too high; the electronically controlled hydraulic power steering system controls the power flow according to the speed of the vehicle, and controls the flow according to the amount of power required to achieve the power assist characteristic. Adjustment, but the valve-controlled electronically controlled hydraulic power steering system is used, its power is still driven by the engine, and the steering energy consumption is still high. The purely motor-driven electronically controlled hydraulic power steering system, due to the limitation of voltage, its steering assistance is limited. The electric power steering system, which is widely used in new energy vehicles, is provided by the electric motor with the lowest energy consumption, but limited by the voltage limit of the power supply, the steering assistance provided by the existing motor size is relatively small. The electronically controlled composite steering system adopts different power assist strategies under different steering conditions, which combines the excellent road feel of the electronically controlled hydraulic power steering system and the energy saving of the electric power steering system, and at the same time makes up for the smaller power assist range of the two. Defects, it is an ideal choice for passenger cars and trucks in the future.

However, in the current research on the electronically controlled composite steering system, the research on its structure is still in its infancy, and there are still many imperfections that need to be improved; in addition, the electronically controlled composite steering system involves steering road feel, steering sensitivity, steering energy In many aspects, such as energy consumption, it has a great impact on the driver's operating experience and energy saving. There are few public reports on how to improve the maneuverability and economy of the car.

In terms of optimization algorithm, the traditional multi-objective optimization algorithm has a good ability to search for optimization, and a better Pareto solution set can be obtained by using the sorting method that retains the elite strategy. Moreover, in the optimization process, as the optimal solution is approached, the optimization efficiency decreases, and there is even a problem that the optimal solution cannot be found in the end.

SUMMARY OF THE INVENTION

The technical problem to be solved by the present invention is to provide an automobile electronically controlled compound steering system and a multi-objective optimization method thereof aiming at the defects involved in the background technology.

The present invention adopts the following technical solutions for solving the above-mentioned technical problems:

An automobile electronically controlled compound steering system, comprising a control module, a mechanical transmission module, an electric power assist module and an electronically controlled hydraulic power assist module;

The mechanical transmission module shown includes steering wheel, steering column, recirculating ball steering gear, tie rod, steering wheel angle sensor, torque sensor and vehicle speed sensor;

One end of the steering column is fixedly connected to the steering wheel through a steering wheel angle sensor, and the other end is connected to an input end of the recirculating ball steering gear;

The recirculating ball steering gear adopts a recirculating ball steering gear with hydraulic function, the output end of which is connected with the input end of the steering tie rod;

The two output ends of the tie rod are respectively connected with the two front wheels of the vehicle;

The torque sensor is on the steering column, and is used to acquire the torque on the steering column and transmit it to the control module;

The steering wheel angle sensor is used to obtain the steering wheel angle and transmit it to the control module;

The vehicle speed sensor is arranged on the car and is used to obtain the speed of the car and transmit it to the control module;

The electric power assist module includes an arc-shaped linear motor and a deceleration mechanism, and the output end of the arc-shaped linear motor and the other input end of the recirculating ball steering gear are connected through the deceleration mechanism;

The electronically controlled hydraulic booster module includes a hydraulic tank, a hydraulic pump, a rotary valve and a hydraulic pump driving motor;

The output end of the hydraulic pump driving motor is fixedly connected with the input end of the hydraulic pump;

The oil inlet port of the hydraulic pump is connected with the oil inlet pipeline of the hydraulic tank, and the oil outlet port is connected with the oil inlet pipeline of the rotary valve;

The oil outlet of the rotary valve is connected with the oil return pipeline of the hydraulic tank, the high pressure oil outlet is connected with the oil inlet pipeline of the circulating ball steering gear, and the low pressure oil outlet is connected with the outlet of the circulating ball steering gear. The oil port pipeline is connected;

The control module is electrically connected with the vehicle speed sensor, the torque sensor, the steering wheel angular displacement sensor, the arc linear motor and the hydraulic pump drive motor respectively, and is used for controlling the arc linear motor according to the received vehicle speed signal, torque sensor signal and steering wheel angle signal. , The hydraulic pump drives the motor to work.

As a further optimized solution of an automobile electronically controlled compound steering system of the present invention, the recirculating ball steering gear includes a steering rocker arm, a toothed sector, a steering screw and a steering nut;

One end of the steering screw is connected with the lower end of the steering column, and a circulating steel ball chain is provided at the meshing position between the thread on the steering screw and the thread on the steering nut;

The gear outside the steering nut meshes with the tooth sector;

The shaft center of the tooth sector is connected with one end of the steering rocker arm, and the other end of the steering rocker arm is connected with the input end of the steering tie rod.

The invention also discloses a multi-objective optimization method based on the vehicle electronically controlled compound steering system, comprising the following steps:

Step 1), establish an electronically controlled composite steering system model, a vehicle dynamics model and an energy consumption model, wherein the electronically controlled composite steering system model includes a steering wheel model, an input and output shaft model, a hydraulic pump model, a circulating ball model, Motor model, tire model;

Step 2), take the steering road feel, steering sensitivity and steering energy consumption of the vehicle electronically controlled composite steering system as the performance evaluation indicators of the electronically controlled composite steering system, and establish three performance evaluation indicators of steering road feel, steering sensitivity, and steering energy consumption quantification formula;

Step 3), take the steering road feel, steering sensitivity, and steering energy consumption as the optimization goals, take the steering assist size range and steering sensitivity as the constraints, and take the average frequency domain energy of the effective frequency range of the road information as the steering road feel, steering sensitivity The optimization evaluation function of ;

Step 4), set the center distance _{ra of the steering screw, the pitch circle radius r p of} the gear sector, the stiffness K _s of the steering column, the equivalent moment of inertia J _m2 of the arc linear motor, the equivalent moment of inertia J _m1 of the hydraulic pump drive motor, and the steering nut The effective area A _P , the moment of inertia J _cs of the tooth sector, and the thickness B of the hydraulic pump stator are used as the design variables of the composite electronically controlled steering system;

Step 5), with the aid of isight optimization software, adopt the NSGA-II algorithm of fusion cell membrane optimization algorithm to optimize the design variables of the composite steering system, obtain the optimal pareto solution set according to the optimization result, and select the optimal compromise solution;

The specific steps of the NSGA-II algorithm of the fusion cell membrane optimization algorithm are as follows:

Step 5.1), coding:

According to the range of design variables and constraints, the feasible solution data of the solution space is obtained, and it is expressed as floating-point structure data in the search space. Different combinations of these string structure data constitute different feasible solutions;

Step 5.2), generate the initial population:

The initial population is randomly generated. For time t=0, the first generation of individuals is P ₀ and the population number is N. The specific randomly generated feasible solution X _i is:

X _i =rand(0,1)(X _max -X _min )+X _min

X _max is the upper boundary of the feasible solution range, and X _min is the lower boundary of the feasible solution range;

Step 5.3), fitness calculation:

Substitute the obtained feasible solution into the objective function, the obtained objective function value corresponds to the fitness, and the individual corresponding to the better objective function value is regarded as an excellent individual;

Step 5.4), select, cross, sort

Select M excellent individuals from the previous generation population through the championship method, and calculate the initial M individuals according to the crossover operator to generate a new population:

P ₁ ^new =w ₁ P ₁ +(1-w ₁ )P ₂

P ₂ ^new =w ₂ P ₂ +(1-w ₂ )P ₁

In the formula, P ₁ and P ₂ are two parent individuals randomly selected from the population; P ₁ ^new and P ₂ ^new are two new individuals generated by the crossover operator, and w ₁ and w ₂ are [0,1] Two random numbers randomly generated on the above;

In the new population generated by the hybridization operation, the mutation operation is performed with the mutation operator given by the following formula:

In the formula, V is the selected mutation parameter, V ^new is the parameter after mutation, sign is randomly selected as 0 or 1, b _up and b _lb are the upper and lower bounds of the parameter value, respectively, and r is a random value on [0,1]. The random number generated, _t =gc/gm is the symbol of population evolution, where _gc is the current evolutionary algebra of the population, and gm is the largest evolutionary algebra of the population;

After a new generation of population Q _t is obtained, a combined population R _t =P _t ∪Q _t is generated by merging P _t and Q _t ;

Finally, the non-dominated sorting method is used to sort the individuals in R _t , and M individuals are selected to form a new generation population P'_t+1;

Step 5.5), search for optimization:

The individuals in P _t ′ ₊₁ are used as the initial population of the cell membrane optimization algorithm for optimization, and the population is divided into fat-soluble substances, high-concentration non-fat-soluble substances and low-concentration substances according to the non-dominated sorting, fitness level, and crowding degree distance. non-fat-soluble substances;

The parameters of the electronically controlled compound steering system are optimized by the cell membrane optimization algorithm, and after the multi-objective optimization solution set is obtained, the individuals in the obtained solution set and P' _t+1 are merged into a new population. Sort by the non-dominated sorting method based on the crowding degree to obtain a new population P _t+1 ;

Step 5.6), loop step 5.3) to step 5.5), until the number of iterations is equal to the preset maximum number of iterations, otherwise, continue to iterate, t=t+1;

Step 5.7), perform decoding to obtain the optimal Pareto optimal solution set, and select the optimal compromise solution according to the Pareto solution set.

As a further optimization scheme of the multi-objective optimization method based on the vehicle electronically controlled compound steering system of the present invention, the quantification formula of steering road feel described in step 2) is:

In the formula, _ra is the center distance of the steering screw in the recirculating ball steering gear, _rp is the pitch circle radius of the tooth sector in the recirculating ball steering gear, K _s is the stiffness of the steering column; _Th (s) is the input torque of the steering wheel, T _r (s) is the resistance torque of the steering column output shaft, and s is the laplace operator;

θ _r is the rotation angle of the steering screw, J _e is the equivalent moment of inertia of the deceleration mechanism and the steering screw, J _m2 is the equivalent moment of inertia of the arc linear motor, n ₂ is the ratio of the wheel rotation angle to the steering screw rotation angle of the recirculating ball steering gear, n _e2 is the ratio of the angle of the steering screw to the angle of the arc linear motor, J _m1 is the equivalent moment of inertia of the hydraulic pump drive motor, _{n e1} is the ratio of the screw angle to the angle of the hydraulic pump drive motor, ra is the center distance of the screw force, A _P is the effective area of the steering nut, q is the displacement of the hydraulic pump, B _m2 is the equivalent viscous damping coefficient of the arc linear motor, B _m1 is the equivalent viscous damping coefficient of the hydraulic pump driving motor, ρ is the hydraulic oil density, N is the number of valve ports of the rotary valve, P is the screw pitch of the steering screw, C _q is the flow coefficient, _{A 1} is the oil flow area of the valve port clearance of the rotary valve, Ka is the torque coefficient of the arc linear motor, and K is the assist coefficient of the arc linear motor. , n _m2 is the transmission ratio of the arc linear motor, n _m1 is the transmission ratio of the hydraulic pump drive motor, m _lm is the equivalent mass of the steering nut, J _cs is the moment of inertia of the gear sector, B is the thickness of the hydraulic pump stator, R ₂ is the hydraulic pump The radius of the long axis of the stator, R ₁ is the radius of the short axis of the stator of the hydraulic pump, Z is the number of blades of the hydraulic pump, t is the thickness of the blades of the hydraulic pump; B _lm and B _cs are the viscosity coefficients of the steering nut and the tooth sector, respectively, and θ _cs is the tooth sector Rotation angle, T _cs is the tooth sector torque, and T _p is the equivalent torque of the steering resistance torque on the rocker arm shaft.

As a further optimization scheme of the multi-objective optimization method based on the vehicle electronically controlled compound steering system of the present invention, the steering sensitivity quantification formula described in step 2) is:

where:

Q ₆ =B ₄ X ₂

Q ₅ =B ₄ Y ₂ +B ₃ X ₂

Q ₄ =B ₄ Z ₂ +B ₃ Y ₂ +B ₂ X ₂

in,

A ₂ = -I _xz L _β Y _δ +I _xz L _δ Y _β -I _x N _β Y _δ +I _x N _δ Y _β +muL _p N _δ +m _s hL _β N _δ -m _s hL _δ N _β

A ₁ =L _p N _β Y _δ -L _p N _δ Y _β -muL _δ N _φ +muL _φ N _δ +m _s huN _δ Y _φ -m _s huN _φ Y _δ

A ₀ =-L _β N _φ Y _δ +L _β N _δ Y _φ -L _δ N _β Y _φ +L _δ N _φ Y _β +L _φ N _β Y _δ -L _φ N _δ Y _β

B ₁ =I _z L _β Y _φ -I _z L _φ Y _β +I _xz N _β Y _φ -I _xz N _φ Y _β -L _p N _β Y _r +L _p N _r Y _β

+muL _p N _β -muL _φ N _r +muL _r N _φ +m _s huN _φ Y _r -m _s huN _r Y _φ

B ₀ =L _β N _φ Y _r -L _β N _r Y _φ -L _φ N _β Y _r +L _φ N _r Y _β +L _r N _β Y _φ -L _r N _φ Y _β

-muL _β N _φ +muL _φ N _β +m _s huN _β Y _φ -m _s huN _φ Y _β

F ₁ = -I _z L _δ Y _φ +I _z L _φ Y _δ -I _xz N _δ Y _φ +I _xz N _φ Y _δ +L _p N _δ Y _r -L _p N _r Y _δ -muL _p N _δ

F ₀ =-L _δ N _φ Y _r +L _δ N _r Y _φ +L _φ N _δ Y _r -L _φ N _r Y _δ -L _r N _δ Y _φ +L _r N _φ Y _δ

+muL _δ N _φ -muL _φ N _δ +m _s huN _φ Y _δ -m _s huN _δ Y _φ

N _β =-a(k ₁ +k ₂ )+b(k ₃ +k ₄ )

N _φ =-aE ₁ (k ₁ +k ₂ )+bE ₂ (k ₃ +k ₄ )

N _δ =a(k ₁ +k ₂ );

Y _β = -(k ₁ +k ₂ +k ₃ +k ₄ )

Y _φ = -(k ₁ +k ₂ )E ₁ -(k ₃ +k ₄ )E ₂

Y _δ =k ₁ +k ₂ ;

L _β =-(k ₁ +k ₂ +k ₃ +k ₄ )h

L _θ = -[(C ₂₁ -C ₂₂ )a+(C ₂₃ -C ₂₄ )b]d

L _δ =(k ₁ +k ₂ )h

L _p =-(D ₂₁ +D ₂₂ +D ₂₃ +D ₂₄ )d ²

L _e =-[(D ₂₁ -D ₂₂ )a+(D ₂₃ -D ₂₄ )b]d

θ _h (s) is the steering wheel angle after Laplace transformation, ω _r (s) is the yaw rate after Laplace transformation, n is the transmission ratio from the output shaft to the front wheel, and a is the center of mass of the car Distance to the front axle, u is the vehicle speed, d is the 1/2 wheel base of the vehicle, E ₁ is the roll steering coefficient, k ₁ and k ₂ are the cornering stiffnesses of the left front wheel and the right front wheel of the vehicle, respectively; h is the vehicle m is the mass of the vehicle; m _s is the sprung mass of the vehicle; I _x is the moment of inertia of the suspension mass of the vehicle to the x-axis; I _y is the moment of inertia of the suspension mass of the vehicle to the y-axis ; I _z is the moment of inertia of the car's suspension mass to the z-axis; I _xz is the inertia product of the car's suspension mass to the x and z-axes; E ₁ is the front roll steering coefficient of the car; E ₂ is the rear roll of the car Steering coefficient; C _a1 is the angular stiffness of the car's front suspension stabilizer bar; C _a2 is the car's rear suspension stabilizer bar angular stiffness; C21, C22 are the car's left front suspension stiffness and right front suspension stiffness respectively; C23, C24 is the stiffness of the left rear suspension and the right rear suspension of the car respectively; _D21 and _D22 are the damping coefficient of the left front suspension and the damping coefficient of the right front suspension respectively; _D23 and _D24 are the left rear suspension of the car respectively frame damping coefficient and right rear suspension damping coefficient.

As a further optimization scheme of the multi-objective optimization method based on the vehicle electronically controlled compound steering system of the present invention, the quantification formula of the steering energy consumption described in step 2) is:

In the formula, E _loss is the total power consumption of the system, P _ECU-loss is the power consumption of the ECU, P _m1-loss is the power loss of the hydraulic pump drive motor, P _m2-loss is the power loss of the arc linear motor, P _v-loss is the rotary valve Power loss, P _p-loss is the power loss of the hydraulic pump, U _A is the working effective voltage of the hydraulic pump drive motor, I _A is the current of the hydraulic pump drive motor, U _S is the power supply voltage of the hydraulic pump drive motor, R _elec is the hydraulic pump drive motor The resistance on the non-armature current, Q _s is the hydraulic pump flow, and P _e is the power of the arc linear motor.

As a further optimization scheme of the multi-objective optimization method based on the vehicle electronically controlled compound steering system of the present invention, the effective frequency range of the road information in step 3) is 0 to 40 Hz;

The evaluation function of road sense is:

The evaluation index of sensitivity is:

The multi-objective optimization objective of the composite electronically controlled steering system is:

Compared with the prior art, the present invention adopts the above technical scheme, and has the following technical effects:

1) The integrated electronically controlled hydraulic power steering system of the present invention has the advantages of good road feel, adjustable power steering characteristics, and low energy consumption of electric power steering. At the same time, the combination of the two power assist forms also overcomes the two power assist systems. The disadvantage of the small power assist range is that its flexible power assist form can not only provide a suitable power assist size through electro-hydraulic composite power assist at low speed and high torque, but also improve the economy of the steering system with pure electric power assist at high speed and low torque. The proportion of electro-hydraulic assistance in the composite steering system is reasonably matched under different driving needs, providing drivers with a more comfortable operating experience and improving steering economy.

2) The present invention comprehensively considers the energy consumption in the steering process of the vehicle, and takes into account the steering feel of the driver, proposes the main performance evaluation index of the electronically controlled compound steering system, and establishes its quantitative formula; Energy consumption is the optimization objective, and multi-objective optimization design is carried out for multiple parameters of the compound steering system, so that the steering system can ensure that the driver can obtain a good steering feeling with less energy consumption.

3) In the multi-objective optimization method of the electronically controlled compound steering system proposed by the present invention, the cell membrane optimization method is implanted into the multi-objective optimization algorithm NSGA-II. The method uses a multi-objective genetic mechanism to select, cross, and mutate individuals in the population, conduct a global breadth search, and use the cell membrane optimization algorithm to locally optimize the new generation of individuals formed by optimization according to the cell membrane transport theory. The coordinated development of global optimization and local heuristic learning can greatly improve the search breadth of the global optimal solution and the depth of the local optimal solution search, improve the convergence of the algorithm, and further improve the robust stability of the algorithm. , so as to improve the multi-objective optimization efficiency and optimization effect of the electronically controlled compound steering system.

Description of drawings

Figure 1 is a structural diagram of an electronically controlled compound steering system;

Fig. 2 is the flow chart of the optimization method of the electronically controlled compound steering system;

Figure 3 is the flow chart of the NSGA-II algorithm of the fusion cell membrane optimization algorithm.

In the figure, 1-steering wheel, 2-steering wheel angle sensor, 3-steering column, 4-torque sensor, 5-rotary valve, 6-hydraulic pump, 7-hydraulic pump drive motor, 8-oil return line, 9-oil inlet pipe Road, 10- hydraulic tank, 11- steering tie rod, 12- recirculating ball steering gear, 12.1- steering rocker arm, 12.2- rack and pinion sector, 12.3- steering screw, 12.4- steering nut, 13- reduction mechanism, 14- Arc Linear Motor, 15-wheels.

Detailed ways

Below in conjunction with accompanying drawing, the technical scheme of the present invention is described in further detail:

As shown in FIG. 1 , the present invention discloses a vehicle electronically controlled compound steering system, which includes a control module (ECU), a mechanical transmission module, an electric booster module and an electronically controlled hydraulic booster module.

The mechanical transmission module shown includes steering wheel, steering column, recirculating ball steering gear, tie rod, steering wheel angle sensor, torque sensor and vehicle speed sensor;

One end of the steering column is fixedly connected to the steering wheel through a steering wheel angle sensor, and the other end is connected to an input end of the recirculating ball steering gear;

The recirculating ball steering gear adopts a recirculating ball steering gear with hydraulic function, the output end of which is connected with the input end of the steering tie rod;

The two output ends of the tie rod are respectively connected with the two front wheels of the vehicle;

The torque sensor is on the steering column, and is used to acquire the torque on the steering column and transmit it to the control module;

The steering wheel angle sensor is used to obtain the steering wheel angle and transmit it to the control module;

The vehicle speed sensor is arranged on the car and is used to obtain the speed of the car and transmit it to the control module;

The electric power assist module includes an arc-shaped linear motor and a deceleration mechanism, and the output end of the arc-shaped linear motor and the other output end of the recirculating ball steering gear are connected through the deceleration mechanism;

The electronically controlled hydraulic booster module includes a hydraulic tank, a hydraulic pump, a rotary valve and a hydraulic pump driving motor;

The output end of the hydraulic pump driving motor is fixedly connected with the input end of the hydraulic pump;

The oil inlet port of the hydraulic pump is connected with the oil inlet pipeline of the hydraulic tank, and the oil outlet port is connected with the oil inlet pipeline of the rotary valve;

The oil outlet of the rotary valve is connected with the oil return pipeline of the hydraulic tank, the high pressure oil outlet is connected with the oil inlet pipeline of the circulating ball steering gear, and the low pressure oil outlet is connected with the outlet of the circulating ball steering gear. The oil port pipeline is connected;

The control module (ECU) is electrically connected with the vehicle speed sensor, the torque sensor, the steering wheel angular displacement sensor, the arc linear motor, and the hydraulic pump drive motor, respectively, and is used to control the arc according to the received vehicle speed signal, torque sensor signal and steering wheel angle signal. The linear motor and hydraulic pump drive the motor to work.

The recirculating ball steering gear includes a steering rocker arm, a rack, a gear sector, a steering screw and a steering nut. The lower end of the steering column is directly connected to the input shaft of the recirculating ball steering gear. The input shaft is connected to the rack through the recirculating ball. It meshes directly with the gear sector and transmits the displacement to the steering rocker arm, which drives the steering tie rod. At the same time, the hydraulic oil is connected to the oil inlet and outlet of the recirculating ball steering gear through the oil pipe, and the two oil ports are respectively connected with the recirculating ball. The left and right oil cylinder chambers of the steering gear are connected, and hydraulic power is provided for steering through the pressure difference of the hydraulic cylinder chambers.

Compared with the traditional electronically controlled hydraulic power steering system and the electric power steering system, the electronically controlled composite steering system of this embodiment takes into account the advantages of both excellent road feel and better economy, and at the same time overcomes the difference in the power assist range of the two. Small disadvantage. The electro-hydraulic composite steering system provides drivers with a better driving experience while ensuring steering economy through different electro-hydraulic participation ratios.

The invention also discloses an optimization method based on the electronically controlled compound steering system. The modeling software used is MATLAB-simulink, and the optimization software is isight, as shown in Figure 2, and the specific steps are as follows:

Step 1), according to "Design and Research of Electro-hydraulic Power Steering System" (Zhang Junjun, Jiangsu University), "Control Strategy of Electro-hydraulic Power Steering System and Its Energy Consumption Analysis Method" (Su Jiankuan, etc., Mechanical Design and Manufacturing), "Automobile The method disclosed in the document "Research on Force and Displacement Coupling Control of Active Front Wheel Steering System" (Li Yijun, Nanjing University of Aeronautics and Astronautics) establishes the electronically controlled composite steering system model, the vehicle dynamics model and the energy consumption model. Among them, the electronically controlled composite steering system The models include steering wheel model, input and output shaft model, hydraulic pump model, circulating ball model, motor model, and tire model. By establishing an electronically controlled composite steering system model, it lays the foundation for the subsequent simulation and optimization of the electronically controlled composite steering system;

Step 2), take the steering road feel, steering sensitivity and steering energy consumption of the vehicle electronically controlled composite steering system as the performance evaluation index of the electronically controlled composite steering system, and establish a quantitative formula for three performance evaluation indicators:

Among them, the quantification formula of steering road feel is:

r _a is the center distance of the steering screw in the recirculating ball steering gear, _rp is the pitch circle radius of the tooth sector in the recirculating ball steering gear, K _s is the stiffness of the steering column; _Th (s) is the input torque of the steering wheel, T _r (s ) is the resistance torque of the steering column output shaft, and s is the laplace operator;

θ _r is the rotation angle of the steering screw, J _e is the equivalent moment of inertia of the deceleration mechanism and the steering screw, J _m2 is the equivalent moment of inertia of the arc linear motor, n ₂ is the ratio of the wheel rotation angle to the steering screw rotation angle of the recirculating ball steering gear, n _e2 is the ratio of the angle of the steering screw to the angle of the arc linear motor, J _m1 is the equivalent moment of inertia of the hydraulic pump drive motor, _{n e1} is the ratio of the screw angle to the angle of the hydraulic pump drive motor, ra is the center distance of the screw force, A _P is the effective area of the steering nut, q is the displacement of the hydraulic pump, B _m2 is the equivalent viscous damping coefficient of the arc linear motor, B _m1 is the equivalent viscous damping coefficient of the hydraulic pump driving motor, ρ is the hydraulic oil density, N is the number of rotary valve ports, P steering screw pitch, C _q flow coefficient, A ₁ valve clearance oil flow area, K _a is the torque coefficient of the arc linear motor, K is the assist coefficient of the arc linear motor, n _m2 is the arc Linear motor transmission ratio, n _m1 is the hydraulic pump drive motor transmission ratio, m _lm is the equivalent mass of the steering nut, J _cs is the moment of inertia of the gear sector, B is the thickness of the hydraulic pump stator, R ₂ is the radius of the long axis of the stator, and R ₁ is The radius of the short axis of the stator, Z is the number of vane pump blades, t is the thickness of the blades; B _lm and B _cs are the viscosity coefficients of the steering nut and the tooth sector, respectively, θ _cs is the tooth sector rotation angle, T _cs is the tooth sector torque, and T _p is the equivalent torque of the steering resistance torque on the rocker arm shaft;

The quantification formula of steering sensitivity is:

Q ₆ =B ₄ X ₂

Q ₅ =B ₄ Y ₂ +B ₃ X ₂

Q ₄ =B ₄ Z ₂ +B ₃ Y ₂ +B ₂ X ₂

A ₂ = -I _xz L _β Y _δ +I _xz L _δ Y _β -I _x N _β Y _δ +I _x N _δ Y _β +muL _p N _δ +m _s hL _β N _δ -m _s hL _δ N _β

A ₁ =L _p N _β Y _δ -L _p N _δ Y _β -muL _δ N _φ +muL _φ N _δ +m _s huN _δ Y _φ -m _s huN _φ Y _δ

A ₀ =-L _β N _φ Y _δ +L _β N _δ Y _φ -L _δ N _β Y _φ +L _δ N _φ Y _β +L _φ N _β Y _δ -L _φ N _δ Y _β

B ₁ =I _z L _β Y _φ -I _z L _φ Y _β +I _xz N _β Y _φ -I _xz N _φ Y _β -L _p N _β Y _r +L _p N _r Y _β

+muL _p N _β -muL _φ N _r +muL _r N _φ +m _s huN _φ Y _r -m _s huN _r Y _φ

B ₀ =L _β N _φ Y _r -L _β N _r Y _φ -L _φ N _β Y _r +L _φ N _r Y _β +L _r N _β Y _φ -L _r N _φ Y _β

-muL _β N _φ +muL _φ N _β +m _s huN _β Y _φ -m _s huN _φ Y _β

F ₁ = -I _z L _δ Y _φ +I _z L _φ Y _δ -I _xz N _δ Y _φ +I _xz N _φ Y _δ +L _p N _δ Y _r -L _p N _r Y _δ -muL _p N _δ

F ₀ =-L _δ N _φ Y _r +L _δ N _r Y _φ +L _φ N _δ Y _r -L _φ N _r Y _δ -L _r N _δ Y _φ +L _r N _φ Y _δ

+muL _δ N _φ -muL _φ N _δ +m _s huN _φ Y _δ -m _s huN _δ Y _φ

N _β =-a(k ₁ +k ₂ )+b(k ₃ +k ₄ )

N _φ =-aE ₁ (k ₁ +k ₂ )+bE ₂ (k ₃ +k ₄ )

N _δ =a(k ₁ +k ₂ );

Y _β = -(k ₁ +k ₂ +k ₃ +k ₄ )

Y _φ = -(k ₁ +k ₂ )E ₁ -(k ₃ +k ₄ )E ₂

Y _δ =k ₁ +k ₂ ;

L _β =-(k ₁ +k ₂ +k ₃ +k ₄ )h

L _θ = -[(C ₂₁ -C ₂₂ )a+(C ₂₃ -C ₂₄ )b]d

L _δ =(k ₁ +k ₂ )h

L _p =-(D ₂₁ +D ₂₂ +D ₂₃ +D ₂₄ )d ²

L _e =-[(D ₂₁ -D ₂₂ )a+(D ₂₃ -D ₂₄ )b]d

θ _h (s) is the steering wheel angle after Laplace transformation, ω _r (s) is the yaw rate after Laplace transformation, n is the transmission ratio from the output shaft to the front wheel, and a is the center of mass of the car Distance to the front axle, u is the vehicle speed, d is the 1/2 wheel base of the vehicle, E ₁ is the roll steering coefficient, k ₁ and k ₂ are the cornering stiffnesses of the left front wheel and the right front wheel of the vehicle, respectively; h is the vehicle m is the mass of the vehicle; m _s is the sprung mass of the vehicle; I _x is the moment of inertia of the suspension mass of the vehicle to the x-axis; I _y is the moment of inertia of the suspension mass of the vehicle to the y-axis ; I _z is the moment of inertia of the car's suspension mass to the z-axis; I _xz is the inertia product of the car's suspension mass to the x and z-axes; E ₁ is the front roll steering coefficient of the car; E ₂ is the rear roll of the car Steering coefficient; C _a1 is the angular rigidity of the car's front suspension stabilizer bar; C _a2 is the car's rear suspension stabilizer bar angular rigidity; C21, C22 are the rigidity of the left front suspension and the right front suspension of the car respectively; C23, C24 is the stiffness of the left rear suspension and the right rear suspension of the car respectively; _D21 and _D22 are the damping coefficient of the left front suspension and the damping coefficient of the right front suspension respectively; _D23 and _D24 are the left rear suspension of the car respectively frame damping coefficient and right rear suspension damping coefficient.

The quantification formula of steering energy consumption is:

In the formula, E _loss is the total power consumption of the system, P _ECU-loss is the power consumption of the ECU, P _m1-loss is the power loss of the hydraulic pump drive motor, P _m2-loss is the power loss of the arc linear motor, P _v-loss is the rotary valve Power loss, P _p-loss is the power loss of the hydraulic pump, U _A is the effective voltage of the motor, I _A is the motor current, U _S is the power supply voltage, R _elec is the resistance on the non-armature current, Q _s is the hydraulic pump flow , P _e is the arc motor power;

Step 3), take the steering road feel, steering sensitivity, and steering energy consumption as the optimization goals, take the steering assist size range and steering sensitivity as the constraints, and take the average frequency domain energy of the effective frequency range of road information (0, ω ₀ ) as the Optimized evaluation function for road feel and sensitivity;

The sensitivity of the steering system needs to be kept within a certain range, which will help improve the driver's handling experience, while too high sensitivity will increase the driver's nervousness when the car is driving at high speed. Therefore, the steering sensitivity needs to be within an appropriate range as much as possible. is small, so steering sensitivity is both an optimization objective and a constraint.

In the optimization scheme, ω ₀ =40Hz.

The evaluation function of road sense is transformed into:

The evaluation index of sensitivity is transformed into:

Therefore, the multi-objective optimization objective of the composite electronically controlled steering system is:

Step 4), set the center distance of r _a steering screw, r _p tooth sector pitch circle radius, K _s steering column stiffness, J _m2 equivalent moment of inertia of arc linear motor, J _m1 equivalent moment of inertia of hydraulic pump drive motor, r _a The center distance of the screw force, the effective area of the A _P steering nut, the moment of inertia of the J _cs gear sector, and the thickness of the B hydraulic pump stator are used as design variables for the composite electronically controlled steering system;

Step 5), with the aid of isight optimization software, use the NSGA-II algorithm fused with the cell membrane optimization algorithm to optimize the design variables of the composite steering system, obtain the optimal pareto solution set according to the optimization results, and select the optimal compromise solution.

Figure 3 is the flow chart of the NSGA-II algorithm of the fusion cell membrane optimization algorithm. The specific steps are as follows:

Step 5.1), coding:

According to the range of design variables and constraints, the feasible solution data of the solution space is obtained, and it is expressed as floating-point structure data in the search space. Different combinations of these string structure data constitute different feasible solutions;

Step 5.2), generate the initial population:

The initial population is randomly generated. For time t=0, the first generation of individuals is P ₀ and the population number is N. The specific randomly generated feasible solution X _i is:

X _i =rand(0,1)(X _max -X _min )+X _min

X _max is the upper boundary of the feasible solution range, and X _min is the lower boundary of the feasible solution range;

Step 5.3), fitness calculation:

Substitute the obtained feasible solution into the objective function, the obtained objective function value corresponds to the fitness, and the individual corresponding to the better objective function value is regarded as an excellent individual;

Step 5.4), select, cross, sort

Select M excellent individuals from the previous generation population through the championship method, and calculate the initial M individuals according to the crossover operator to generate a new population:

P ₁ ^new =w ₁ P ₁ +(1-w ₁ )P ₂

P ₂ ^new =w ₂ P ₂ +(1-w ₂ )P ₁

In the formula: P ₁ , P ₂ are two parent individuals randomly selected from the population; P ₁ ^new , P ₂ ^new are new individuals generated by the crossover operator, w ₁ , w ₂ are random on [0,1] Generated random numbers;

In the new population generated by the hybridization operation, the mutation operation is performed with the mutation operator given by the following formula:

In the formula: V is the selected mutation parameter, V ^new is the parameter after mutation, sign is randomly selected as 0 or 1, b _up and b _lb are the upper and lower bounds of the parameter value, respectively, and r is random on [0,1]. The random number generated, _t =gc/gm is the symbol of population evolution, where _gc is the current evolutionary algebra of the population, and gm is the largest evolutionary algebra of the population;

In this way, a new generation of population Q _t is obtained, and a combined population R _t =P _t ∪Q _t is generated by combining P _t and Q _t ;

The non-dominated sorting method is used to sort the individuals in R _t , and M individuals are selected to form a new generation population P' _t+1 .

Step 5.5), the cell membrane optimization algorithm is optimized:

The individuals in P' _t+1 are used as the initial population of the cell membrane optimization algorithm for optimization, and the population is divided into fat-soluble substances, high-concentration non-fat-soluble substances and low-concentration substances according to non-dominated sorting, fitness level, and crowding degree distance. non-fat soluble substances. The parameters of the electronically controlled compound steering system are optimized by the cell membrane optimization algorithm, and the multi-objective optimization solution set is obtained. The obtained solution set individuals and P' _t+1 are merged into a new population, and the non-dominated sorting method based on crowding degree with elite strategy in NSGA-II algorithm is used to sort, and a new population P _t+1 is obtained.

Step 5.6), repeat step 5.3) to step 5.5) until the number of iterations is equal to the preset maximum number of iterations, otherwise, continue to iterate, t=t+1.

Step 5.7), perform decoding to obtain the optimal Pareto optimal solution set, and select the optimal compromise solution according to the Pareto solution set.

It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It should also be understood that terms such as those defined in general dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and, unless defined as herein, are not to be taken in an idealized or overly formal sense. explain.

The specific embodiments described above further describe the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above descriptions are only specific embodiments of the present invention, and are not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims (1)

1. A multi-objective optimization method for a vehicle electronically controlled composite steering system, the vehicle electronically controlled composite steering system comprising a control module, a mechanical transmission module, an electric booster module and an electronically controlled hydraulic booster module; The mechanical transmission module shown includes steering wheel, steering column, recirculating ball steering gear, tie rod, steering wheel angle sensor, torque sensor and vehicle speed sensor; One end of the steering column is fixedly connected to the steering wheel through a steering wheel angle sensor, and the other end is connected to an input end of the recirculating ball steering gear; The recirculating ball steering gear adopts a recirculating ball steering gear with hydraulic function, the output end of which is connected with the input end of the steering tie rod; The recirculating ball steering gear includes a steering rocker arm, a gear sector, a steering screw and a steering nut; One end of the steering screw is connected with the lower end of the steering column, and a circulating steel ball chain is provided at the meshing position between the thread on the steering screw and the thread on the steering nut; The gear outside the steering nut meshes with the tooth sector; The shaft center of the tooth sector is connected with one end of the steering rocker arm, and the other end of the steering rocker arm is connected with the input end of the steering tie rod; The two output ends of the tie rod are respectively connected with the two front wheels of the vehicle; The torque sensor is on the steering column, and is used to acquire the torque on the steering column and transmit it to the control module; The steering wheel angle sensor is used to obtain the steering wheel angle and transmit it to the control module; The vehicle speed sensor is arranged on the car and is used to obtain the speed of the car and transmit it to the control module; The electric power assist module includes an arc-shaped linear motor and a deceleration mechanism, and the output end of the arc-shaped linear motor and the other input end of the recirculating ball steering gear are connected through the deceleration mechanism; The electronically controlled hydraulic booster module includes a hydraulic tank, a hydraulic pump, a rotary valve and a hydraulic pump driving motor; The output end of the hydraulic pump driving motor is fixedly connected with the input end of the hydraulic pump; The oil inlet port of the hydraulic pump is connected with the oil inlet pipeline of the hydraulic tank, and the oil outlet port is connected with the oil inlet pipeline of the rotary valve; The oil outlet of the rotary valve is connected with the oil return pipeline of the hydraulic tank, the high pressure oil outlet is connected with the oil inlet pipeline of the circulating ball steering gear, and the low pressure oil outlet is connected with the outlet of the circulating ball steering gear. The oil port pipeline is connected; The control module is electrically connected with the vehicle speed sensor, the torque sensor, the steering wheel angular displacement sensor, the arc linear motor and the hydraulic pump drive motor respectively, and is used for controlling the arc linear motor according to the received vehicle speed signal, torque sensor signal and steering wheel angle signal. , The hydraulic pump drives the motor to work; It is characterized in that, the multi-objective optimization method of the vehicle electronically controlled compound steering system comprises the following steps: Step 1), establish an electronically controlled composite steering system model, a vehicle dynamics model and an energy consumption model, wherein the electronically controlled composite steering system model includes a steering wheel model, an input and output shaft model, a hydraulic pump model, a circulating ball model, Motor model, tire model; Step 2), take the steering road feel, steering sensitivity and steering energy consumption of the vehicle electronically controlled composite steering system as the performance evaluation indicators of the electronically controlled composite steering system, and establish three performance evaluation indicators of steering road feel, steering sensitivity, and steering energy consumption quantification formula; Step 3), take the steering road feel, steering sensitivity, and steering energy consumption as the optimization goals, take the steering assist size range and steering sensitivity as the constraints, and take the average frequency domain energy of the effective frequency range of the road information as the steering road feel, steering sensitivity The optimization evaluation function of ; Step 4), set the center distance _{ra of the steering screw, the pitch circle radius r p of} the gear sector, the stiffness K _s of the steering column, the equivalent moment of inertia J _m2 of the arc linear motor, the equivalent moment of inertia J _m1 of the hydraulic pump drive motor, and the steering nut The effective area A _P , the moment of inertia J _cs of the tooth sector, and the thickness B of the hydraulic pump stator are used as the design variables of the composite electronically controlled steering system; Step 5), with the aid of isight optimization software, adopt the NSGA-II algorithm of fusion cell membrane optimization algorithm to optimize the design variables of the composite steering system, obtain the optimal pareto solution set according to the optimization result, and select the optimal compromise solution; The specific steps of the NSGA-II algorithm of the fusion cell membrane optimization algorithm are as follows: Step 5.1), coding: According to the range of design variables and constraints, the feasible solution data of the solution space is obtained, and it is expressed as floating-point structure data in the search space. Different combinations of these string structure data constitute different feasible solutions; Step 5.2), generate the initial population: The initial population is randomly generated. For time t=0, the first generation of individuals is P ₀ and the population number is N. The specific randomly generated feasible solution X _i is: X _i =rand(0,1)(X _max -X _min )+X _min X _max is the upper boundary of the feasible solution range, and X _min is the lower boundary of the feasible solution range; Step 5.3), fitness calculation: Substitute the obtained feasible solution into the objective function, the obtained objective function value corresponds to the fitness, and the individual corresponding to the better objective function value is regarded as an excellent individual; Step 5.4), select, intersect, sort Select M excellent individuals from the previous generation population through the championship method, and calculate the initial M individuals according to the crossover operator to generate a new population: P ₁ ^new =w ₁ P ₁ +(1-w ₁ )P ₂ P ₂ ^new =w ₂ P ₂ +(1-w ₂ )P ₁ In the formula, P ₁ and P ₂ are two parent individuals randomly selected from the population; P ₁ ^new and P ₂ ^new are two new individuals generated by the crossover operator, and w ₁ and w ₂ are [0,1] Two random numbers randomly generated on the above; In the new population generated by the hybridization operation, the mutation operation is performed with the mutation operator given by the following formula:

In the formula, V is the selected mutation parameter, V ^new is the parameter after mutation, sign is randomly selected as 0 or 1, b _up and b _lb are the upper and lower bounds of the parameter value, respectively, and r is a random value on [0,1]. The random number generated, t=g _c /g _m is the sign of the evolution of the population, where g _c is the current evolutionary algebra of the population, and g _m is the largest evolutionary algebra of the population; After the new generation population Q _t is obtained, the combined population R _t =P _t ∪Q _t is generated by merging P _t and Q _t ; Finally, use the non-dominated sorting method to sort the individuals in R _t , and select M individuals to form a new generation of population P _t ′ ₊₁ ; Step 5.5), search for optimization: The individuals in P _t ′ ₊₁ are used as the initial population of the cell membrane optimization algorithm for optimization, and the population is divided into fat-soluble substances, high-concentration non-fat-soluble substances and low-concentration substances according to the non-dominated sorting, fitness level, and crowding degree distance. non-fat-soluble substances; The parameters of the electronically controlled compound steering system are optimized by the cell membrane optimization algorithm, and after the multi-objective optimization solution set is obtained, the individuals in the obtained solution set and P' _t+1 are merged into a new population. Sort by the non-dominated sorting method based on the crowding degree to obtain a new population P _t+1 ; Step 5.6), loop step 5.3) to step 5.5), until the number of iterations is equal to the preset maximum number of iterations, otherwise, continue to iterate, t=t+1; Step 5.7), perform decoding to obtain the optimal Pareto optimal solution set, and select the optimal compromise solution according to the Pareto solution set.

Images