CN106800040B - Automobile electric control composite steering system and multi-objective optimization method thereof - Google Patents
Automobile electric control composite steering system and multi-objective optimization method thereof Download PDFInfo
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- CN106800040B CN106800040B CN201710101760.5A CN201710101760A CN106800040B CN 106800040 B CN106800040 B CN 106800040B CN 201710101760 A CN201710101760 A CN 201710101760A CN 106800040 B CN106800040 B CN 106800040B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
- B62D—MOTOR VEHICLES; TRAILERS
- B62D5/00—Power-assisted or power-driven steering
- B62D5/04—Power-assisted or power-driven steering electrical, e.g. using an electric servo-motor connected to, or forming part of, the steering gear
- B62D5/0421—Electric motor acting on or near steering gear
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
- B62D—MOTOR VEHICLES; TRAILERS
- B62D5/00—Power-assisted or power-driven steering
- B62D5/04—Power-assisted or power-driven steering electrical, e.g. using an electric servo-motor connected to, or forming part of, the steering gear
- B62D5/0457—Power-assisted or power-driven steering electrical, e.g. using an electric servo-motor connected to, or forming part of, the steering gear characterised by control features of the drive means as such
- B62D5/046—Controlling the motor
- B62D5/0463—Controlling the motor calculating assisting torque from the motor based on driver input
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
- B62D—MOTOR VEHICLES; TRAILERS
- B62D5/00—Power-assisted or power-driven steering
- B62D5/06—Power-assisted or power-driven steering fluid, i.e. using a pressurised fluid for most or all the force required for steering a vehicle
- B62D5/062—Details, component parts
- B62D5/064—Pump driven independently from vehicle engine, e.g. electric driven pump
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
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
Technical Field
The invention relates to the field of automobile steering systems, in particular to an automobile electronic control composite steering system and a multi-objective optimization method thereof.
Background
Most of the existing steering systems adopt a hydraulic power-assisted steering system, an electric control hydraulic power-assisted steering system and an electric power-assisted steering system. In the traditional hydraulic power-assisted steering system, the steering power is provided by an engine, a hydraulic pump is still driven to work under the non-steering condition, and the steering working condition accounts for about 10% of the running working condition of the automobile, so that certain waste is caused to energy sources, the power-assisted characteristic is uncontrollable, the steering is heavy when the automobile is at low speed, and the steering sensitivity is overhigh when the automobile is at high speed; the electric control hydraulic power-assisted steering system controls the power-assisted flow according to the vehicle speed and the like, and controls the flow according to the magnitude of the required power to realize the adjustment of the power-assisted characteristic, but the valve-controlled electric control hydraulic power-assisted steering system is adopted, the power is still driven by an engine, the steering energy consumption is still higher, and the electric control hydraulic power-assisted steering system driven by a pure electric motor is adopted, so the steering power is limited due to the limitation of voltage; the electric power-assisted steering system is widely applied to new energy automobiles, the steering power of the electric power-assisted steering system is provided by the electric motor, the energy consumption is the lowest, but the electric power-assisted steering system is limited by the voltage limit of a power supply, and the steering power provided under the size of the existing electric motor is relatively small. The electric control composite steering system adopts different power-assisted strategies under different steering working conditions, has excellent road feel of the electric control hydraulic power-assisted steering system, saves energy of the electric power-assisted steering system, overcomes the defect of small power-assisted range of the electric power-assisted steering system and the electric power-assisted steering system, and is an ideal power-assisted selection for future passenger cars and trucks.
However, in the existing research of the electric control composite steering system, the research on the structure of the electric control composite steering system is still in a starting stage, and a plurality of imperfect places are provided, so that improvement is needed; in addition, the electronic control composite steering system relates to a plurality of aspects such as steering road feel, steering sensitivity, steering energy consumption and the like, has great influence on the operation feeling and energy saving performance of a driver, and has few public reports on researches on how to improve the maneuverability and the economy of an automobile.
In the aspect of optimization algorithm, the traditional multi-objective optimization algorithm has good optimization searching capability, a better Pareto solution set can be obtained by utilizing a sorting method for retaining an elite strategy, but the algorithm has the problems of easiness in precocity and easiness in falling into a local optimal solution, and in the optimization process, along with approaching to the optimal solution, the optimization efficiency is reduced, and even the problem that the optimal solution cannot be found finally exists.
Disclosure of Invention
The invention aims to solve the technical problem of providing an automobile electric control composite steering system and a multi-objective optimization method thereof aiming at the defects involved in the background technology.
The invention adopts the following technical scheme for solving the technical problems:
an automobile electronic control composite steering system comprises a control module, a mechanical transmission module, an electric power-assisted module and an electronic control hydraulic power-assisted module;
the mechanical transmission module comprises a steering wheel, a steering column, a circulating ball steering gear, a steering tie rod, a steering wheel corner sensor, a torque sensor and a vehicle speed sensor;
one end of the steering column is fixedly connected with the steering wheel through a steering wheel corner sensor, and the other end of the steering column is connected with one input end of the recirculating ball steering gear;
the recirculating ball steering gear adopts a recirculating ball steering gear with a hydraulic function, and the output end of the recirculating ball steering gear is connected with the input end of the tie rod;
two output ends of the steering tie rod are respectively connected with two front wheels of the automobile;
the torque sensor is arranged on the steering column and used for acquiring the torque on the steering column and transmitting the torque to the control module;
the steering wheel angle sensor is used for acquiring the angle of the steering wheel and transmitting the angle to the control module;
the vehicle speed sensor is arranged on the vehicle and used for acquiring the vehicle speed of the vehicle and transmitting the vehicle speed to the control module;
the electric power-assisted module comprises an arc-shaped linear motor and a speed reducing mechanism, and the output end of the arc-shaped linear motor is connected with the other input end of the recirculating ball steering gear through the speed reducing mechanism;
the electric control hydraulic power-assisted module comprises 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;
an oil inlet port of the hydraulic pump is connected with an oil inlet pipeline of the hydraulic tank, and an oil outlet port of the hydraulic pump is connected with an oil inlet pipeline of the rotary valve;
an oil outlet of the rotary valve is connected with an oil return pipeline of the hydraulic tank, a high-pressure oil outlet is connected with an oil inlet pipeline of the recirculating ball steering gear, and a low-pressure oil outlet is connected with an oil outlet pipeline of the recirculating ball steering gear;
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 driving motor respectively and is used for controlling the arc linear motor and the hydraulic pump driving motor to work according to the received vehicle speed signal, the received torque sensor signal and the received steering wheel corner signal.
As a further optimization scheme of the automobile electronic control composite steering system, the recirculating ball steering gear comprises a steering rocker arm, a sector, a steering screw rod and a steering nut;
one end of the steering screw rod is connected with the lower end of the steering column, and a circulating steel ball chain is arranged at the meshing position of the thread on the steering screw rod and the thread on the steering nut;
the gear on the outer side of the steering nut is meshed with the sector;
the axle center of the sector gear 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 automobile electric control composite steering system, which comprises the following steps:
step 1), establishing an electric control composite steering system model, a whole vehicle dynamics model and an energy consumption model, wherein the electric control composite steering system model comprises a steering wheel model, an input and output shaft model, a hydraulic pump model, a circulating ball model, a motor model and a tire model;
step 2), taking the steering road feel, the steering sensitivity and the steering energy consumption of the automobile electric control composite steering system as performance evaluation indexes of the electric control composite steering system, and establishing a quantitative formula of the three performance evaluation indexes of the steering road feel, the steering sensitivity and the steering energy consumption;
step 3), taking the steering road feel, the steering sensitivity and the steering energy consumption as optimization targets, taking the steering power-assisted range and the steering sensitivity as constraint conditions, and taking the frequency domain energy average value of the effective frequency range of the road surface information as an optimization evaluation function of the steering road feel and the steering sensitivity;
step 4), adjusting the center distance r of the steering screw a Pitch radius r of sector p Steering column stiffness K s Arc linear motor equivalent moment of inertia J m2 Equivalent rotary inertia J of hydraulic pump driving motor m1 Effective area A of steering nut P And the rotational inertia J of the sector cs The thickness B of the stator of the hydraulic pump is used as a design variable of the composite electric control steering system;
step 5), optimizing design variables of the composite steering system by adopting an NSGA-II algorithm fused with a cell membrane optimization algorithm by means of the sight optimization software, obtaining an optimal pareto solution set according to an optimization result, and selecting an optimal compromise solution;
the NSGA-II algorithm of the fusion cell membrane optimization algorithm comprises the following specific steps:
step 5.1), encoding:
obtaining feasible solution data of a solution space according to the value range of the design variable and the restriction condition limit, and expressing the feasible solution data as floating point type structure data of a search space, wherein different feasible solutions are formed by different combinations of the series of structure data;
step 5.2), generating an initial population:
the initial population was randomly generated, and for time t =0, the first generation individuals were P 0 The number of the population is N, and the feasible solution X is generated randomly i Comprises the following steps:
X i ＝rand(0,1)(X max -X min )+X min
X max at the upper boundary of the feasible solution range, X min Is the lower boundary of the feasible solution range;
step 5.3), fitness calculation:
substituting the obtained feasible solution into an objective function, wherein the obtained objective function value corresponds to fitness, and an individual corresponding to the better objective function value is taken as a good individual;
step 5.4), selecting, crossing and sorting
Selecting M excellent individuals from the previous generation population by a tournament method, and calculating the initial M individuals according to a hybridization 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 Two father individuals randomly selected from the population; p 1 new 、P 2 new For two new individuals generated by the crossover operator, w 1 、w 2 Is [0,1 ]]Two random numbers generated randomly;
in the new population generated by the hybridization operation, mutation operation is carried out according to a mutation operator given by the following formula:
wherein V is a selected variation parameter, V new For the parameters after mutation, sign takes 0 or 1,b randomly up 、b lb Respectively an upper bound and a lower bound of parameter values, r is [0,1 ]]The random number generated at random is shown as above, and t = gc/gm is a sign of population evolution, wherein g c Is the algebra of the current evolution of the population, g m Is the evolutionary algebra with the largest population;
obtaining a new generation of population Q t Then, by merging P t And Q t Generating a combinatorial population R t ＝P t ∪Q t ；
Finally, applying a non-dominated sorting method to R t The middle individuals are sequenced, M individuals are selected to form a new generation population P' t+1 ；
Step 5.5), optimizing:
will P t ′ +1 The individual in the method is used as an initial population of a cell membrane optimization algorithm to carry out optimization, and the population is divided into fat-soluble substances, high-concentration non-fat-soluble substances and low-concentration non-fat-soluble substances according to non-dominated sorting, high-low fitness level and crowding distance;
optimizing parameters of the electric control composite steering system through a cell membrane optimization algorithm to obtain a multi-objective optimization solution set, and then concentrating the obtained solution set into individuals and P' t+1 Combining into a new population, and sequencing by using a congestion degree-based non-dominated sequencing method with elite strategy in NSGA-II algorithm to obtain a new population P t+1 ；
Step 5.6), the step 5.3) to the step 5.5) are circulated until the iteration number is equal to the preset maximum iteration number, otherwise, the iteration is continued, and t = t +1;
and 5.7) decoding to obtain an optimal Pareto optimal solution set, and selecting an optimal compromise solution according to the Pareto optimal solution set.
As a further optimization scheme of the multi-objective optimization method based on the automobile electronic control composite steering system, the quantization formula of the steering road feel in the step 2) is as follows:
in the formula, r a Is the center distance r of a steering screw rod in the recirculating ball steering gear p Is the pitch radius of a sector in a recirculating ball steering gear, K s Steering column stiffness; t is h (s) is steering wheel input torque, T r (s) is the drag torque of the steering column output shaft, s is the laplace operator;
θ r is the turning angle of the steering screw, J e Is the equivalent moment of inertia of the reduction gear and the steering screw, J m2 Is equivalent rotational inertia of an arc linear motor, n 2 Is the ratio of the wheel angle to the angle of the steering screw 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 Equivalent moment of inertia of the hydraulic pump drive motor, n e1 Is the ratio of the screw angle to the hydraulic pump drive motor rotation angle, r a Is the center distance of the screw force, A P Q 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 a hydraulic pump driving motor, rho is the hydraulic oil density, N is the number of valve ports of a rotary valve, P is the pitch of a steering screw, C q Is the flow coefficient, A 1 Is the oil flow area of the gap of the valve port of the rotary valve, K a Is the torque coefficient of the arc linear motor, K is the power assisting coefficient of the arc linear motor, n m2 Is the transmission ratio of the arc linear motor, n m1 For the drive ratio of the hydraulic pump drive motor, m lm For steering nut equivalent mass, J cs Is the rotational inertia of the sector, B is the thickness of the stator of the hydraulic pump, R 2 For the length of the stator of the hydraulic pumpRadius of axis, R 1 The radius of a short shaft of a stator of the hydraulic pump is Z, the number of hydraulic pump blades is Z, and t is the thickness of the hydraulic pump blades; b is lm 、B cs Viscosity coefficients of steering nut and sector, theta cs Is a gear sector corner, T cs As sector torque, T p Is the equivalent torque of the steering resistance torque on the rocker shaft.
As a further optimization scheme of the multi-objective optimization method based on the automobile electronic control composite steering system, the steering sensitivity quantization formula in the step 2) is as follows:
in the formula:
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
wherein the content of the first and second substances,
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 Laplace transformed steering wheel angle, ω r (s) is the yaw velocity after Laplace transform, n is the transmission ratio from the output shaft to the front wheel, a is the distance from the center of mass of the automobile to the front shaft, u is the speed of the automobile, d is the 1/2 wheel base of the automobile, E 1 As coefficient of roll deflection, k 1 、k 2 The cornering stiffness of the left front wheel and the right front wheel of the automobile respectively; h is the side-tipping moment arm of the automobile; m is the total mass of the automobile; m is s Is the sprung mass of the automobile; I.C. A x For suspended mass pairs of vehiclesMoment of inertia of the x-axis; i is y The moment of inertia of the suspended mass of the vehicle to the y-axis; i is z The moment of inertia of the suspended mass of the vehicle to the z-axis; i is xz The product of inertia of the suspended mass of the vehicle on the x and z axes; e 1 The front roll steering coefficient of the automobile; e 2 The rear roll steering coefficient of the automobile; c a1 Angular stiffness of a stabilizer bar of a front suspension of the vehicle; c a2 Angular stiffness of a rear suspension stabilizer bar of an automobile; c21 and C22 are respectively the rigidity of the left front suspension and the rigidity of the right front suspension of the automobile; c23 and C24 respectively represent the rigidity of the left rear suspension and the rigidity of the right rear suspension of the automobile; d 21 、D 22 Respectively a left front suspension damping coefficient and a right front suspension damping coefficient of the automobile; d 23 、D 24 The damping coefficient of the left rear suspension and the damping coefficient of the right rear suspension of the automobile are respectively.
As a further optimization scheme of the multi-objective optimization method based on the automobile electronic control composite steering system, the quantization formula of the steering energy consumption in the step 2) is as follows:
in the formula, E loss For total power consumption of the system, P ECU-loss Consuming power for the ECU, P m1-loss Power loss of hydraulic pump drive motor, P m2-loss For power loss, P, of arc-shaped linear motors v-loss Power loss of rotary valve, P p-loss For power loss of hydraulic pumps, U A Effective voltage for operation of hydraulic pump drive motor, I A For driving motor current to hydraulic pumps, U S Supply voltage for the hydraulic pump drive motor, R elec Resistance, Q, on non-armature current for hydraulic pump drive motor s For the hydraulic pump flow, P e Is the power of the arc linear motor.
As a further optimization scheme of the multi-objective optimization method based on the automobile electronic control composite steering system, the effective frequency range of the road information in the step 3) is 0-40 Hz;
evaluation function of road feelComprises the following steps:
the evaluation indexes of the sensitivity are as follows:
the multi-objective optimization target of the composite electric control steering system is as follows:
compared with the prior art, the technical scheme adopted by the invention has the following technical effects:
1) The comprehensive electric control hydraulic power-assisted steering system has the advantages of good road feel, adjustable design of power-assisted steering characteristics and lower energy consumption of electric power-assisted steering, and simultaneously, the combination of the two power-assisted forms also overcomes the defect of smaller power-assisted range of the two power-assisted systems.
2) The invention comprehensively considers the energy consumption in the automobile steering process and gives consideration to the steering feeling of a driver, provides the main performance evaluation index of the electric control composite steering system and establishes the quantization formula of the main performance evaluation index; the steering system is optimized by taking steering road feel, steering sensitivity and steering energy consumption of the steering system as optimization targets and performing multi-objective optimization design on a plurality of parameters of the composite steering system, so that the steering system ensures that a driver obtains good steering feel with low energy consumption.
3) The invention provides a multi-objective optimization method of an electronic control composite steering system, which implants a cell membrane optimization method into a multi-objective optimization algorithm NSGA-II. The method adopts a multi-target genetic mechanism to carry out selection, crossing and mutation operations on individuals in a population, carries out global breadth search, adopts a cell membrane optimization algorithm to carry out local optimization on a new generation of individuals formed by optimization according to a cell membrane transportation theory, realizes the collaborative development of global optimization and local heuristic learning of the population, can improve the breadth of global optimal solution search and the depth of local optimal solution search of the algorithm to a greater extent, improves the convergence of the algorithm, further improves the robustness and stability of the algorithm, and thus improves the multi-target optimization efficiency and optimization effect of the electric control composite steering system.
Drawings
FIG. 1 is a block diagram of an electronically controlled compound steering system;
FIG. 2 is a flow chart of a method for optimizing an electronically controlled compound steering system;
FIG. 3 is a 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-steering valve, 6-hydraulic pump, 7-hydraulic pump driving motor, 8-oil return pipeline, 9-oil inlet pipeline, 10-hydraulic tank, 11-steering tie rod, 12-circulating ball steering gear, 12.1-steering rocker arm, 12.2-rack sector, 12.3-steering screw, 12.4-steering nut, 13-speed reducing mechanism, 14-arc linear motor, 15-wheel.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the attached drawings:
as shown in FIG. 1, the invention discloses an electric control composite steering system for an automobile, which comprises a control module (ECU), a mechanical transmission module, an electric power-assisted module and an electric control hydraulic power-assisted module.
The mechanical transmission module comprises a steering wheel, a steering column, a circulating ball steering gear, a steering tie rod, a steering wheel corner sensor, a torque sensor and a vehicle speed sensor;
one end of the steering column is fixedly connected with the steering wheel through a steering wheel corner sensor, and the other end of the steering column is connected with one input end of the recirculating ball steering gear;
the recirculating ball steering gear adopts a recirculating ball steering gear with a hydraulic function, and the output end of the recirculating ball steering gear is connected with the input end of the tie rod;
two output ends of the steering tie rod are respectively connected with two front wheels of the automobile;
the torque sensor is arranged on the steering column and used for acquiring torque on the steering column and transmitting the torque to the control module;
the steering wheel angle sensor is used for acquiring the angle of the steering wheel and transmitting the angle to the control module;
the vehicle speed sensor is arranged on the vehicle and used for acquiring the vehicle speed of the vehicle and transmitting the vehicle speed to the control module;
the electric power-assisted module comprises an arc-shaped linear motor and a speed reducing mechanism, and the output end of the arc-shaped linear motor is connected with the other output end of the recirculating ball steering gear through the speed reducing mechanism;
the electric control hydraulic power-assisted module comprises 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;
an oil inlet port of the hydraulic pump is connected with an oil inlet pipeline of the hydraulic tank, and an oil outlet port of the hydraulic pump is connected with an oil inlet pipeline of the rotary valve;
an oil outlet of the rotary valve is connected with an oil return pipeline of the hydraulic tank, a high-pressure oil outlet is connected with an oil inlet pipeline of the recirculating ball steering gear, and a low-pressure oil outlet is connected with an oil outlet pipeline of the recirculating ball steering gear;
the control module (ECU) is respectively and electrically connected with the vehicle speed sensor, the torque sensor, the steering wheel angular displacement sensor, the arc linear motor and the hydraulic pump driving motor and is used for controlling the arc linear motor and the hydraulic pump driving motor to work according to the received vehicle speed signal, the received torque sensor signal and the received steering wheel corner signal.
The recirculating ball steering gear comprises a steering rocker arm, a rack, a sector, a steering screw rod and a steering nut, the lower end of a steering column is directly connected with an input shaft of the recirculating ball steering gear, the input shaft is connected with the rack through a recirculating ball, the rack is directly meshed with the sector and transfers displacement to the steering rocker arm, the steering rocker arm drives a steering tie rod, meanwhile, hydraulic oil is connected with an oil inlet and an oil outlet of the recirculating ball steering gear through an oil pipe, two oil ports are respectively communicated with a left oil cylinder cavity and a right oil cylinder cavity of the recirculating ball steering gear, and hydraulic power is provided for steering through pressure difference of the hydraulic cylinder cavities.
Compared with the traditional electric control hydraulic power-assisted steering system and the electric power-assisted steering system, the electric control composite steering system has the advantages of good road feel and better economy, and overcomes the defect of small power-assisted range. The electro-hydraulic composite steering system provides better driving feeling for a driver while ensuring steering economy through different electro-hydraulic participation proportions.
The invention also discloses an optimization method based on the electric control composite steering system, the used modeling software is MATLAB-simulink, the optimization software is aim, and as shown in figure 2, the specific steps are as follows:
step 1), establishing an electric control composite steering system model, a whole vehicle dynamics model and an energy consumption model according to methods disclosed in the documents of design research of an electric control hydraulic power-assisted steering system (Zhang Jun, jiangsu university), "control strategy of the electric hydraulic power-assisted steering system and energy consumption analysis method thereof (Sujian Width, mechanical design and manufacture)," research on coupling force and displacement of an automobile active front wheel steering system (Liyu Jun, nanjing aerospace university), wherein the electric control composite steering system model comprises a steering wheel model, an input and output shaft model, a hydraulic pump model, a circulating ball model, a motor model and a tire model, and laying a foundation for subsequent simulation and optimization of the electric control composite steering system by establishing the electric control composite steering system model;
step 2), taking the steering road feel, steering sensitivity and steering energy consumption of the automobile electric control composite steering system as performance evaluation indexes of the electric control composite steering system, and establishing quantitative formulas of the three performance evaluation indexes:
wherein, the quantization formula of the steering road feel is as follows:
r a is the center distance r of a steering screw rod in the circulating ball steering gear p Is the pitch radius of a sector in a recirculating ball steering gear, K s Steering column stiffness; t is h (s) is steering wheel input torque, T r (s) is the drag torque of the steering column output shaft, s is the laplace operator;
θ r is the angle of rotation of the steering screw, J e Is the equivalent moment of inertia of the reduction gear and the steering screw, J m2 Is equivalent rotational inertia of an arc linear motor, n 2 Is the ratio of the wheel angle to the steering screw 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 For equivalent moment of inertia of the hydraulic pump drive motor, n e1 Is the ratio of the screw angle to the rotational angle of the hydraulic pump drive motor, r a Is the center distance of the screw force, A P Q 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 The equivalent viscous damping coefficient of a hydraulic pump driving motor is shown as rho is hydraulic oil density, N is the number of valve ports of a rotary valve, P is the pitch of a steering screw rod, and C is q Flow coefficient, A 1 Oil flow area of valve clearance, K a Is the torque coefficient of the arc linear motor, K is the power assisting coefficient of the arc linear motor, n m2 Is the transmission ratio of the arc linear motor, n m1 For the drive ratio of the hydraulic pump drive motor, m lm For steering nut equivalent mass, J cs Is the rotational inertia of the sector, B is the thickness of the stator of the hydraulic pump, R 2 Radius of stator major axis, R 1 The radius of a minor axis of the stator, Z is the number of blades of the vane pump, and t is the thickness of the blades; b lm 、B cs Viscosity coefficients of steering nut and sector, theta cs Is a gear sector corner, T cs As sector torque, T p To moment of resistance to steeringAn equivalent moment on the rocker shaft;
the steering sensitivity quantization formula 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 laplace transformed steering wheel angle, ω r (s) is the yaw velocity after Laplace transform, n is the transmission ratio from the output shaft to the front wheel, a is the distance from the center of mass of the automobile to the front shaft, u is the speed of the automobile, d is the 1/2 wheel base of the automobile, E 1 As coefficient of roll deflection, k 1 、k 2 The lateral deflection rigidity of the left front wheel and the right front wheel of the automobile are respectively; h is the lateral force arm of the automobile; m is the total mass of the automobile; m is s Is the sprung mass of the automobile; I.C. A x The moment of inertia of the suspended mass of the vehicle to the x-axis; i is y The moment of inertia of the suspended mass of the vehicle to the y-axis; I.C. A z The moment of inertia of the suspended mass of the vehicle to the z-axis; I.C. A xz Is the product of the inertia of the suspended mass of the vehicle to the x and z axes; e 1 The front roll steering coefficient of the automobile; e 2 The rear roll steering coefficient of the automobile; c a1 Angular stiffness of a transverse stabilizer bar of a front suspension of an automobile; c a2 The angular stiffness of a transverse stabilizer bar of a rear suspension of the automobile; c21 and C22 are respectively the rigidity of the left front suspension and the rigidity of the right front suspension of the automobile;c23 and C24 respectively represent the rigidity of a left rear suspension and the rigidity of a right rear suspension of the automobile; d 21 、D 22 Respectively a left front suspension damping coefficient and a right front suspension damping coefficient of the automobile; d 23 、D 24 The damping coefficient of the left rear suspension and the damping coefficient of the right rear suspension of the automobile are respectively.
The steering energy consumption quantization formula is as follows:
in the formula, E loss For the total power consumption of the system, P ECU-loss Consuming power for the ECU, P m1-loss Loss power of hydraulic pump driving motor, P m2-loss For power loss, P, of arc-shaped linear motors v-loss Power loss of rotary valve, P p-loss For power loss of hydraulic pumps, U A For the operating effective voltage of the motor, I A Is the motor current, U S Is the supply voltage, R elec Being a resistance on non-armature current, Q s For the hydraulic pump flow, P e Is the power of the arc-shaped motor;
and 3) taking the steering road feel, the steering sensitivity and the steering energy consumption as optimization targets, taking the steering power range and the steering sensitivity as constraint conditions, and taking the effective frequency range (0, omega) of the road surface information 0 ) The frequency domain energy average value of (2) is used as an optimized evaluation function of road feel and sensitivity;
the sensitivity of the steering system needs to be kept within a certain range, which contributes to improvement of the steering feeling of the driver, while an excessively high sensitivity increases the tension of the driver when the automobile is running at high speed, and therefore, the steering sensitivity needs to be as small as possible within an appropriate range, so that the steering sensitivity is used as both an optimization target and a constraint condition.
Omega in optimization scheme 0 ＝40Hz。
The evaluation function of road feel is converted into:
evaluation of sensitivityThe value index translates into:
therefore, the multi-objective optimization target of the composite electric control steering system is as follows:
step 4), mixing r a Center distance r of steering screw p Pitch radius of sector, K s Steering column stiffness, J m2 Arc linear motor equivalent moment of inertia, J m1 Equivalent rotary inertia r of hydraulic pump driving motor a Center distance of screw force, A P Effective area, J, of steering nut cs The gear sector rotational inertia and the thickness of a stator of a hydraulic pump B are used as design variables of the composite electric control steering system;
and 5) optimizing the design variables of the composite steering system by adopting an NSGA-II algorithm fused with a cell membrane optimization algorithm by means of the sight optimization software, obtaining an optimal pareto solution set according to an optimization result, and selecting an optimal compromise solution.
FIG. 3 is a flow chart of the NSGA-II algorithm of the fusion cell membrane optimization algorithm, which comprises the following specific steps:
step 5.1), encoding:
obtaining feasible solution data of a solution space according to the value range of the design variable and the restriction condition limit, and representing the feasible solution data as floating point type structure data of a search space, wherein different feasible solutions are formed by different combinations of the string structure data;
step 5.2), generating an initial population:
the initial population is randomly generated, and for the time t =0, the first generation individual is P 0 The number of the population is N, and the feasible solution X is generated randomly i Comprises the following steps:
X i ＝rand(0,1)(X max -X min )+X min
X max to the upper bound of the feasible solution range, X min To the lower boundary of the feasible solution range；
Step 5.3), fitness calculation:
substituting the obtained feasible solution into an objective function, wherein the obtained objective function value corresponds to fitness, and an individual corresponding to the better objective function value is taken as a good individual;
step 5.4), selecting, crossing and sorting
Selecting M excellent individuals from the previous generation population by a tournament method, and calculating the initially generated M individuals according to a hybridization 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 Two father individuals randomly selected from the population; p 1 new 、P 2 new For new individuals generated by the crossover operator, w 1 、w 2 Is [0,1 ]]A random number generated randomly;
in the new population generated by the hybridization operation, mutation operation is carried out according to a mutation operator given by the following formula:
in the formula: v is a selected variation parameter, V new Sign takes 0 or 1 at random for the parameters after mutation up 、b lb Respectively an upper bound and a lower bound of parameter values, r is [0,1 ]]The random number generated at random, t = gc/gm, is the sign of population evolution, where g c Is the algebra of the current evolution of the population, g m Is the evolutionary algebra with the largest population;
thereby obtaining a new generation population Q t By merging P t And Q t Generating a combinatorial population R t ＝P t ∪Q t ；
Applying non-dominated sorting method to R t Sorting the individuals, and selecting M individuals to form a new oneSubstitute population P' t+1 。
Step 5.5), optimizing a cell membrane optimization algorithm:
prepared from P' t+1 The individual in (1) is used as an initial population of a cell membrane optimization algorithm to carry out optimization, and the population is divided into fat-soluble substances, high-concentration non-fat-soluble substances and low-concentration non-fat-soluble substances according to non-dominated sorting, high-low fitness level and crowding distance. And optimizing the parameters of the electric control composite steering system through a cell membrane optimization algorithm to obtain a multi-objective optimization solution set. Mixing the obtained solution with P' t+1 Combining into new population, sorting by using non-dominated sorting method based on congestion degree with elite strategy in NSGA-II algorithm to obtain new population P t+1 。
Step 5.6), looping steps 5.3) to 5.5) until the number of iterations is equal to a preset maximum number of iterations, otherwise, continuing the iteration, and t = t +1.
And 5.7) decoding to obtain an optimal Pareto optimization solution set, and selecting an 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 will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only examples of the present invention, and should not be construed as limiting the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (1)
1. A multi-objective optimization method for an automobile electric control composite steering system comprises a control module, a mechanical transmission module, an electric power-assisted module and an electric control hydraulic power-assisted module;
the mechanical transmission module comprises a steering wheel, a steering column, a circulating ball steering gear, a steering tie rod, a steering wheel corner sensor, a torque sensor and a vehicle speed sensor;
one end of the steering column is fixedly connected with the steering wheel through a steering wheel corner sensor, and the other end of the steering column is connected with one input end of the recirculating ball steering gear;
the recirculating ball steering gear adopts a recirculating ball steering gear with a hydraulic function, and the output end of the recirculating ball steering gear is connected with the input end of the steering tie rod;
the circulating ball steering gear comprises a steering rocker arm, a sector gear, a steering screw and a steering nut;
one end of the steering screw rod is connected with the lower end of the steering column, and a circulating steel ball chain is arranged at the meshing position of the thread on the steering screw rod and the thread on the steering nut;
the gear on the outer side of the steering nut is meshed with the gear sector;
the axle center of the sector gear is connected with one end of a steering rocker arm, and the other end of the steering rocker arm is connected with the input end of the steering tie rod;
two output ends of the tie rod are respectively connected with two front wheels of the automobile;
the torque sensor is arranged on the steering column and used for acquiring the torque on the steering column and transmitting the torque to the control module;
the steering wheel angle sensor is used for acquiring the angle of the steering wheel and transmitting the angle to the control module;
the vehicle speed sensor is arranged on the vehicle and used for acquiring the vehicle speed of the vehicle and transmitting the vehicle speed to the control module;
the electric power-assisted module comprises an arc-shaped linear motor and a speed reducing mechanism, and the output end of the arc-shaped linear motor is connected with the other input end of the recirculating ball steering gear through the speed reducing mechanism;
the electric control hydraulic power-assisted module comprises 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;
an oil inlet port of the hydraulic pump is connected with an oil inlet pipeline of the hydraulic tank, and an oil outlet port of the hydraulic pump is connected with an oil inlet pipeline of the rotary valve;
an oil outlet of the rotary valve is connected with an oil return pipeline of the hydraulic tank, a high-pressure oil outlet is connected with an oil inlet pipeline of the recirculating ball steering gear, and a low-pressure oil outlet is connected with an oil outlet pipeline of the recirculating ball steering gear;
the control module is respectively electrically connected with the vehicle speed sensor, the torque sensor, the steering wheel angular displacement sensor, the arc linear motor and the hydraulic pump driving motor and is used for controlling the arc linear motor and the hydraulic pump driving motor to work according to the received vehicle speed signal, torque sensor signal and steering wheel corner signal;
the method is characterized by comprising the following steps:
step 1), establishing an electric control composite steering system model, a whole vehicle dynamics model and an energy consumption model, wherein the electric control composite steering system model comprises a steering wheel model, an input and output shaft model, a hydraulic pump model, a circulating ball model, a motor model and a tire model;
step 2), taking the steering road feel, the steering sensitivity and the steering energy consumption of the automobile electric control composite steering system as performance evaluation indexes of the electric control composite steering system, and establishing a quantitative formula of the three performance evaluation indexes of the steering road feel, the steering sensitivity and the steering energy consumption;
step 3), taking the steering road feel, the steering sensitivity and the steering energy consumption as optimization targets, taking the steering power-assisted range and the steering sensitivity as constraint conditions, and taking the frequency domain energy average value of the effective frequency range of the road surface information as an optimization evaluation function of the steering road feel and the steering sensitivity;
step 4), adjusting the center distance r of the steering screw a Pitch radius r of sector p Steering column stiffness K s Arc shapeEquivalent moment of inertia J of linear motor m2 Hydraulic pump driving motor equivalent moment of inertia J m1 Effective area A of steering nut P And the rotational inertia J of the sector cs The thickness B of the stator of the hydraulic pump is used as a design variable of the composite electric control steering system;
step 5), optimizing design variables of the composite steering system by adopting an NSGA-II algorithm fused with a cell membrane optimization algorithm by means of the sight optimization software, obtaining an optimal pareto solution set according to an optimization result, and selecting an optimal compromise solution;
the NSGA-II algorithm of the fusion cell membrane optimization algorithm comprises the following specific steps:
step 5.1), encoding:
obtaining feasible solution data of a solution space according to the value range of the design variable and the restriction condition limit, and expressing the feasible solution data as floating point type structure data of a search space, wherein different feasible solutions are formed by different combinations of the series of structure data;
step 5.2), generating an initial population:
the initial population was randomly generated, and for time t =0, the first generation individuals were P 0 The number of the population is N, and the feasible solution X is generated randomly i Comprises the following steps:
X i ＝rand(0,1)(X max -X min )+X min
X max at the upper boundary of the feasible solution range, X min Is the lower boundary of the feasible solution range;
step 5.3), fitness calculation:
substituting the obtained feasible solution into an objective function, wherein the obtained objective function value corresponds to fitness, and an individual corresponding to the better objective function value is taken as a good individual;
step 5.4), selecting, crossing and sorting
Selecting M excellent individuals from the previous generation population by a tournament method, and calculating the initially generated M individuals according to a hybridization 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 Two father individuals randomly selected from the population; p is 1 new 、P 2 new For two new individuals generated by the crossover operator, w 1 、w 2 Is [0,1 ]]Two random numbers generated randomly;
in the new population generated by the hybridization operation, mutation operation is carried out according to a mutation operator given by the following formula:
wherein V is a selected variation parameter, V new For the parameters after mutation, sign takes 0 or 1,b randomly up 、b lb Respectively an upper bound and a lower bound of the parameter value, r is [0,1 ]]Random number generated at random, t = g c /g m Is a marker for population evolution, wherein g c Is the algebra of the current evolution of the population, g m Is the evolution algebra with the largest population;
obtaining a new generation of population Q t Then, by merging P t And Q t Generating a combinatorial population R t ＝P t ∪Q t ；
Finally, applying a non-dominated sorting method to R t Sorting the medium individuals, selecting M individuals to form a new generation of population P t ′ +1 ；
Step 5.5), optimizing:
will P t ′ +1 The individuals in the method are used as an initial population of a cell membrane optimization algorithm for optimizing, and the population is divided into fat-soluble substances, high-concentration non-fat-soluble substances and low-concentration non-fat-soluble substances according to non-dominated sorting, high and low fitness level and crowding distance;
optimizing parameters of the electric control composite steering system through a cell membrane optimization algorithm to obtain a multi-objective optimization solution set, and then concentrating the obtained solution set into individuals and P' t+1 Are combined into a new populationSorting by using a congestion degree-based non-dominated sorting method with elite strategy in NSGA-II algorithm to obtain a new population P t+1 ；
Step 5.6), the steps 5.3) to 5.5) are circulated until the iteration number is equal to the preset maximum iteration number, otherwise, the iteration is continued, and t = t +1;
and 5.7) decoding to obtain an optimal Pareto optimization solution set, and selecting an optimal compromise solution according to the Pareto solution set.
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