CN205524447U - Automatically controlled power -assisted steering system - Google Patents

Abstract

The utility model relates to an automatically controlled power -assisted steering system, this automatically controlled power -assisted steering system is including turning to mechanical part, hydraulic pressure helping hand part, signal transducer subtotal ecu ECU, the driver makes the steering order through turning to mechanical part, a plurality of signal transducer are with speed of a motor vehicle signal, steering wheel angle signal, automatically controlled unit ECU is given in transmission such as motor rotation number signal, give hydraulic pressure helping hand part by the ECU give -out order, the power -assisted steering that drive hydraulic oil was realized ideal, simultaneously, carry out the multi -objective optimization to automatically controlled power -assisted steering system to steering response, sensitivity, energy consumption are the target, through in coordination with optimization method, carry out the optimal design to automatically controlled power -assisted steering system's mechanical parameter, hydraulic system part parameter, make the comprehensive properties of a steering system steering response, sensitivity, energy consumption more excellent.

Description

A kind of Electro-Hydraulic Power Steering System

Technical field

This utility model relates to automobile electrical control hydraulic steering system field, particularly a kind of Electro-Hydraulic Power Steering System.

Background technology

Electro-Hydraulic Power Steering System be a kind of when motor turning according to steering wheel angle, GES, control steering pump Drive motor speed, to steering pump oil so that hydraulic steering cylinder both sides produce the Novel steam that certain pressure reduction power-assisted wheel turns to Car power steering system, is now widely used in automobile power steering.Compare traditional hydraulic power-assist steering system, automatically controlled liquid Economy etc. in control feel when pressure servo steering system has a more preferable galloping and dynamic response and driving process Advantage, owing to this system replaces electromotor directly to drive hydraulic pump, speed and steering wheel rotating speed will to affect motor speed with motor Size, when, steering wheel angle speed low in speed is big, ECU response makes oil pump drive motor speed to increase, and increases hydraulic oil flow Amount, increases power steering；Otherwise, motor speed reduces, and the power-assisted that system provides reduces.

But in the research of existing Electro-Hydraulic Power Steering System, on the one hand, the machinery of Electro-Hydraulic Power Steering System, Hydraulic Elements parameter arranges the road feel on motor turning, the impact of sensitivity rarely has people to study, and in practical operation, road feel, Sensitivity etc. are directly experienced by driver, affect the biggest on the control feel of driver；On the other hand, existing electric-controlled hydraulic helps Power steering, it turns to energy consumption the biggest, still has a biggest energy-saving potential, and for machine liquid three subjects of electricity to more than Road feel, sensitivity, the report of energy consumption complex optimum there is not yet disclosure.

Utility model content

For the problems referred to above, this utility model provides a kind of Electro-Hydraulic Power Steering System, and based on this system, proposes comprehensive Consider mechanical steering system parameter, the parameter of electric machine, rotary valve parameter, the machine liquid electricity multidisciplinary collaboration optimization method of hydraulic pump parameter, This utility model is achieved in that

There is provided a kind of Electro-Hydraulic Power Steering System, including steering mechanical part, hydraulic booster part, signal transducer part With electronic control unit ECU；

Described steering mechanical part includes that the steering wheel, steering spindle, rotary valve, rack and pinion steering gear and the two ends that are sequentially connected with connect Having the track rod of wheel, track rod is provided with hydraulic cylinder, and steering spindle is provided with torque sensor；

Hydraulic booster part includes the oil can being linked in sequence, suction, return line, double-acting vane pump, connects rotary valve and hydraulic cylinder Hydraulic cylinder in-line and hydraulic cylinder return line, the vane pump being joined directly together with double-acting vane pump drives motor, the most brushless Direct current generator, rotary valve is not only mechanically connected with steering spindle, rack and pinion steering gear, also passes through hydraulic tube with vane pump, hydraulic cylinder Road is connected；

Described Sensor section includes the torque sensor in steering spindle, vehicle speed sensor, and motor speed sensor, with hydraulic cylinder The pressure transducer being connected, steering wheel angle sensor, longitudinal acceleration sensor, yaw-rate sensor；

Described electronic control unit ECU is connected with each sensor element, receives the signal of telecommunication that each sensor element sends, and to leaf Sheet pump drives motor to send control signal.

In conjunction with this system, it is provided that the Multipurpose Optimal Method of a kind of Electro-Hydraulic Power Steering System, the method comprises the steps:

1) setting up Electro-Hydraulic Power Steering System model, Full Vehicle Dynamics model, wherein electric-controlled hydraulic power-assisted steering model includes Steering wheel model, input and output shaft model, rotary valve model, rack-and-pinion model, steering pump model, vane pump drive motor Model, tire model；

2) optimizing index model is set up, including steering energy consumption model, sensitivity model, road feel model, by these three model As the evaluation index of steering design, set up steering optimization object function；Simultaneously with the energy value model of steering sensitivity Enclose as constraints, set up Electro-Hydraulic Power Steering System Model for Multi-Objective Optimization；

3) by stator thickness B, motor and the rotary inertia J of oil pump_m, torque sensor stiffness K_sLittle tooth radius r_p, hydraulic pressure Cylinder piston area A_pRotary valve valve port gap width w, as the design variable of Electro-Hydraulic Power Steering System；

4) use cooperative optimization method that Electro-Hydraulic Power Steering System is carried out STRUCTURE DECOMPOSITION, system is divided, is divided into Turn to energy consumption system, sensitivity system, road feel system；Total system uses archipelago genetic algorithm, and subsystem uses NLPQL algorithm, To Electro-Hydraulic Power Steering System in step 4) in design variable be optimized, obtain optimal solution.

The corresponding model of described brshless DC motor is: the control signal that motor transmits according to ECU, regulates PWM duty cycle, makes Obtaining motor and press certain rotation speed operation, using motor speed as feedback, regulate motor dutycycle, this is external feedback, meanwhile, motor By load effect, it is supported under rotation speed change and respective change also will occur, now, by internal feedback, electric current is adjusted, Constitute internal feedback.By interior external feedback, realize motor control, rotational speed regulation faster.

Converting through laplace, brshless DC motor speed responsive is:

$w\left(s\right)=\frac{K_T{U}_d\left(s\right)}{L_a{\mathrm{Js}}^2+(r_{a}J+L_a{B}_v+L_a{K}_L)s+r_a{K}_L+K_T{k}_e+r_a{B}_v}$

Wherein, L_aFor motor inductances, J is electric machine rotation inertia, r_aFor electric motor resistance, B_vFor motor viscous damping coefficient, K_LFor electricity Machine moment of resistance coefficient, K_TFor motor torque coefficient, K_ePower coefficient, U is disliked for motor_dFor motor busbar voltage, w is Electric machine rotation angular velocity.

Step 2) in, steering energy consumption quantitative formula is:

E=P_M-loss+P_v-loss+P_pump-loss

Wherein P_M-lossIt is lost for motor power, P_v-lossFor rotary valve energy loss, P_pump-lossFor hydraulic pump energy loss, E is gross energy Loss；

P_M-loss=U_di-K_Tiw

$U_d=\frac{\frac{B_{v}n\mathrm{\π}}{30}+T_{L_O}}{K_T}ra+\frac{k_{e}n\mathrm{\π}}{30}$

$i=\frac{J}{K_T}\frac{dw}{dt}+\frac{B_v}{K_T}w+\frac{T_L}{K_T}$

Wherein, i is current of electric, and n is motor speed, T_LFor electric motor load torque；

$P_{v-loss}=\frac{\mathrm{\ρ}}{{\left(C_q{A}_1\right)}^2}{(\frac{Q_s}{4}+A_p\frac{{\mathrm{dx}}_r}{dt})}^3+\frac{\mathrm{\ρ}}{8{\left(C_q{A}_2\right)}^2}{(\frac{Q_s}{4}-A_p\frac{{\mathrm{dx}}_r}{dt})}^3$

$A_1=NL\[w+R\frac{k_c({\mathrm{\θ}}_S-{\mathrm{\θ}}_P)}{k_c+k_n}\]$

$A_2=NL\[w-R\frac{k_c({\mathrm{\θ}}_S-{\mathrm{\θ}}_P)}{k_c+k_n}\]$

Wherein, A is the oily discharge area of valve clearance, and N is rotary valve valve port number, and L is rotary valve mouth narrow orifice length, and w is between rotary valve valve port Gap length degree, C_qFor the discharge coefficient of valve clearance, Q_sFor rotary valve oil inlet quantity, x_rFor rack-and-pinion displacement；

P_pump-loss=P_sqn-P_sQ_s

$P_S=\frac{\mathrm{\ρ}}{8C_q^2}\[{\left(\frac{Q_S-A_P{\stackrel{\·}{\mathrm{\θ}}}_P{r}_P}{A_2}\right)}^2+{\left(\frac{Q_S+A_P{\stackrel{\·}{\mathrm{\θ}}}_P{r}_P}{A_1}\right)}^2\]$

Wherein, θ_pFor turning to output shaft rotation angle；

Sensitivity quantitative formula is:

$\left\{\begin{array}{c}\frac{\mathrm{\δ}\left(s\right)}{{\mathrm{\θ}}_s\left(s\right)}=\frac{A}{{\mathrm{Xs}}^2+Ys+Z+\frac{qd(k_1+k_2)}{n_2}\[\frac{a}{u}\frac{w_r\left(s\right)}{\mathrm{\δ}\left(s\right)}+\frac{\mathrm{\β}\left(s\right)}{\mathrm{\δ}\left(s\right)}+E_1\frac{\mathrm{\φ}\left(s\right)}{\mathrm{\δ}\left(s\right)}\]}\\ A=A_p{r}_p{\mathrm{KK}}_a{K}_s+K_{TT}q\\ X=m_r{r_p}^2{\mathrm{qn}}_2+n_1{J}_m{A}_p{r}_p{n}_2\\ Y=(B_r{{\mathrm{qr}}_p}^2+n_1{B}_m{A}_p{r}_p+\frac{\left({\mathrm{\ρq}}^2{\mathrm{nn}}_v{A_p}^2{r_p}^2\right)}{2{C_q}^2{A_1}^2})n_2\\ Z=(A_p{r}_p{\mathrm{KK}}_a{K}_s+K_{TT}q)n_2-\frac{qd(k_1+k_2)}{n_2}\end{array}\right.$

In formula, δ (s) is the front wheel angle after Laplace transform, θ_sS () is the steering wheel angle after Laplace transform, β (s) For the yaw acceleration after Laplace transform, φ (s) is the side slip angle after Laplace transform, w_rS () is for general through drawing Yaw velocity after the conversion of Lars, n is the rotating speed of double-acting vane pump, n₁For turning to output shaft to the gear ratio of front-wheel, a to be Automobile barycenter is to front axle distance, and u is automobile speed, and d is vehicle 1/2 wheelspan, E₁For roll steer coefficient, k₁、k₂For front Wheel cornering stiffness, m_rFor rack mass, J_mFor the rotary inertia of motor Yu oil pump, B_rFor tooth bar damped coefficient, B_mFor electricity Machine and the viscous damping coefficient of oil pump, n_vFor the volumetric efficiency of oil pump, C_qFor the discharge coefficient of valve clearance, K is motor power-assisted Coefficient, K_aFor steering assist motor moment coefficient, K_sFor torque sensor rigidity, K_TTIntegral stiffness for steering spindle Yu torsion bar； Road feel quantitative formula is:

$\left\{\begin{array}{c}\frac{T_h\left(s\right)}{T_r\left(s\right)}=\frac{{\mathrm{qK}}_{TT}}{(m_r{r}_p^{2}q+n_1{J}_m{A}_p{r}_p)s^2+(B_r{\mathrm{qr}}_p^2+n_1{B}_m{A}_p{r}_p+\frac{{\mathrm{\ρq}}^2{\mathrm{n\η}}_v{A}_p^2{r}_p^2}{2C_q^2{A}^2})s+A_p{r}_p{\mathrm{KK}}_a{K}_s+{\mathrm{qK}}_{TT}}\\ q=2B\[\frac{1}{2}(R_2^2-R_1^2)\mathrm{\π}-(R_2-R_1)Zt\]\end{array}\right.$

In formula, T_hFor steering wheel input torque, T_rFor the power torque of steering screw, q is pump delivery, and B is stator thickness, R₂ For stator major axis radius, R₁For stator minor axis radius, Z is vane pump blade number, and t is vane thickness.

Described step 2) in, object function f (x) that Electro-Hydraulic Power Steering System optimizes is:

$\left\{\begin{array}{c}f\left(x\right)=\frac{k_1}{f\left(x_1\right)}+\frac{k_2}{f\left(x_2\right)}+f\left(x_3\right)\\ f\left(x_1\right)=\frac{1}{2{\mathrm{\π\ω}}_0}{\∫}_0^{{\mathrm{\ω}}_0}{{\left|\frac{T_h\left(s\right)}{T_r\left(s\right)}\right|}_{s=j\mathrm{\ω}}}^{2}d\mathrm{\ω}\\ f\left(x_2\right)=\frac{1}{2{\mathrm{\π\ω}}_0}{\∫}_0^{{\mathrm{\ω}}_0}{{\left|\frac{\mathrm{\δ}\left(s\right)}{{\mathrm{\θ}}_s\left(s\right)}\right|}_{s=j\mathrm{\ω}}}^{2}d\mathrm{\ω}\\ f\left(x_3\right)=E\end{array}\right.$

In formula: road feel function f (x₁) it is information of road surface effective frequency range (0, ω₀) frequency domain energy meansigma methods, in prioritization scheme ω₀=40Hz；Sensitivity function f (x₂) it is information of road surface effective frequency range (0, ω₀) frequency domain energy meansigma methods；f(x₃) For steering energy consumption；

During optimizing, function meets 2.8 × 10^-6≤f(x₂)≤8.6×10^-6Constraints.

In described step 4) in, its structure or implementing procedure be: sets up multiple target and works in coordination with Optimized model, with steering response, and sensitivity, Comprehensive mathematical model f (x) of energy consumption is as system-level optimization aim, more respectively with steering response, sensitivity, energy consumption as subsystem, Build multidisciplinary collaboration Optimized model；

System-level Optimized model:

$\left\{\begin{array}{c}Minimize\\ p=f\left(Z\right)=F(B,J_m,K_s,A_p,w,r_p)\\ \begin{array}{cc}s.t.& R_1<\mathrm{\&epsiv;},R_2<\mathrm{\&epsiv;},R_3<\mathrm{\&epsiv;}\\ & 0.003<B<0.01\\ & 0.001<J_m<0.01\\ & 10<K_s<150\\ & 5\&times;{10}^{-5}<A_p<2\&times;{10}^{-4}\\ & 2\&times;{10}^{-4}<w<{10}^{-3}\\ & 0.01<r_p<0.1\\ & 2.8\&times;{10}^{-6}<f_{ling\min }<8.6\&times;{10}^{-6}\end{array}\end{array}\right.$

In formula, Z is the design variable vector in system-level optimizer；F (Z) is the object function of system-level optimizer；R_iFor system-level The equation consistency constraint condition of optimizer and subsystem irrespective of size optimizer, meanwhile, is also the object function of subsystems, lax Factor ε takes 0.001 at this；

Using steering sensitivity as the first subsystem, then subsystem is unified Optimized model and is:

$\left\{\begin{array}{c}Minimize:\\ R_1={(1-B/B^{\&prime;})}^2+{(1-J_m/{J_m}^{\&prime;})}^2+{(1-K_s/{K_s}^{\&prime;})}^2\\ +{(1-A_p/{A_p}^{\&prime;})}^2+{(1-w/w^{\&prime;})}^2+{(1-r_p/{r_p}^{\&prime;})}^2\\ \begin{array}{cc}s.t.& \\ & 0.003<B^{\&prime;}<0.01\\ & 0.001<{J_m}^{\&prime;}<0.01\\ & 10<{K_s}^{\&prime;}<150\\ & 5\&times;{10}^{-5}<{A_p}^{\&prime;}<2\&times;{10}^{-4}\\ & 2\&times;{10}^{-4}<w^{\&prime;}<{10}^{-3}\\ & 0.01<{r_p}^{\&prime;}<0.1\\ & 2.8\&times;{10}^{-6}<{f_{ling\min }}^{\&prime;}<8.6\&times;{10}^{-6}\end{array}\end{array}\right.$

Using steering response as the second subsystem, then subsystem two Optimized model is:

$\left\{\begin{array}{c}Minimize:\\ R_2={(1-B/B^{\&prime;\&prime;})}^2+{(1-J_m/{J_m}^{\&prime;\&prime;})}^2+{(1-K_s/{K_s}^{\&prime;\&prime;})}^2\\ +{(1-A_p/{A_p}^{\&prime;\&prime;})}^2+{(1-w/w^{\&prime;\&prime;})}^2+{(1-r_p/{r_p}^{\&prime;\&prime;})}^2\\ \begin{array}{cc}s.t.& 0.003<B^{\&prime;\&prime;}<0.01\\ & 0.001<{J_m}^{\&prime;\&prime;}<0.01\\ & 10<{K_s}^{\&prime;\&prime;}<150\\ & 5\&times;{10}^{-5}<{A_p}^{\&prime;\&prime;}<2\&times;{10}^{-4}\\ & 2\&times;{10}^{-4}<w^{\&prime;\&prime;}<{10}^{-3}\\ & 0.01<{r_p}^{\&prime;\&prime;}<0.1\end{array}\end{array}\right.$

To turn to energy consumption as the 3rd subsystem, then subsystem three Optimized model is:

$\left\{\begin{array}{c}Minimize:\\ R_3={(1-B/B^{\&prime;\&prime;\&prime;})}^2+{(1-J_m/{J_m}^{\&prime;\&prime;\&prime;})}^2+{(1-K_s/{K_s}^{\&prime;\&prime;\&prime;})}^2\\ +{(1-A_p/{A_p}^{\&prime;\&prime;\&prime;})}^2+{(1-w/w^{\&prime;\&prime;\&prime;})}^2+{(1-r_p/{r_p}^{\&prime;\&prime;\&prime;})}^2\\ \begin{array}{cc}s.t.& 0.003<B^{\&prime;\&prime;\&prime;}<0.01\\ & 0.001<{J_m}^{\&prime;\&prime;\&prime;}<0.01\\ & 10<{K_s}^{\&prime;\&prime;\&prime;}<150\\ & 5\&times;{10}^{-5}<{A_p}^{\&prime;\&prime;\&prime;}<2\&times;{10}^{-4}\\ & 2\&times;{10}^{-4}<w^{\&prime;\&prime;\&prime;}<{10}^{-3}\\ & 0.01<{r_p}^{\&prime;\&prime;\&prime;}<0.1\end{array}\end{array}\right.$

According to choosing archipelago genetic algorithm as optimized algorithm in total system, subsystem is all chosen NLPQL algorithm as excellent Change algorithm, be optimized according to acquiescence step-length, obtain final optimum results.

This utility model uses above technical scheme compared with prior art, has following technical effect that

(1) road feel, sensitivity during this utility model considers motor turning, turn to energy consumption, carried out multidisciplinary excellent Change, from the point of view of optimum results, effectively raise steering response so that steering sensitivity meets requirement, still in suitable scope Within, reduce the energy consumption of steering simultaneously.

(2) the multidisciplinary collaboration optimization method for electric-controlled hydraulic steering that the utility model proposes, with other for total system The optimization method of system is compared, and significantly reduces total optimization operation time.

(3) the multidisciplinary collaboration optimization method for electric-controlled hydraulic steering that the utility model proposes uses archipelago genetic algorithm With the mode that NLPQL algorithm is combined, having taken into account optimization arithmetic speed and accuracy, optimal solution is the most of overall importance.

Accompanying drawing explanation

Below with reference to accompanying drawing, the utility model is described in further detail:

Fig. 1 is Electro-Hydraulic Power Steering System structure chart；

In figure, 1, steering wheel；2, torque sensor；3, steering spindle；4, rack and pinion steering gear；5, wheel；6、 Hydraulic cylinder return line；7, hydraulic cylinder；8, hydraulic cylinder piston；9, hydraulic cylinder in-line；10, rotary valve return line；11、 Hydraulic oil container；12, double-acting vane pump；13, oil pump drives motor；14, rotary valve in-line；15, pump oil motor speed Control signal；16, electronic control unit ECU；17, motor speed signal；18, GES；19, longitudinal acceleration Signal；20, steering wheel angle signal；21, yaw rate signal；22, hydraulic cylinder pressure difference signal；23, torque sensing Device signal；24, rotary valve；25, track rod.

Detailed description of the invention

This utility model provides a kind of Electro-Hydraulic Power Steering System, for making the purpose of this utility model, technical scheme and effect Clearer, clearly, and referring to the drawings and give an actual example this utility model is further described.Should be appreciated that this place Describe is embodied as only in order to explain this utility model, is not used to limit this utility model.

Embodiment 1 Electro-Hydraulic Power Steering System

As it is shown in figure 1, a kind of Electro-Hydraulic Power Steering System, pass including steering mechanical part, hydraulic booster part, signal Sensor part and electronic control unit ECU 16；

Wherein, steering mechanical unit includes being sequentially connected with steering wheel 1, steering spindle 3, rotary valve 24, rack and pinion steering gear 4 And two ends are connected with the track rod 25 of wheel 5, drag link being additionally provided with hydraulic cylinder 7, hydraulic fluid pressure cylinder piston 8 is positioned at liquid In cylinder pressure in 7；

Hydraulic booster part includes the hydraulic oil container 11 being linked in sequence, double-acting vane pump 12, is joined directly together with double-acting vane pump Oil pump drive motor 13, rotary valve 24 and double-acting vane pump 12 to pass through rotary valve in-line 14 to be connected, rotary valve 24 and hydraulic pressure It is provided with between fuel tank 11 between hydraulic oil-returning pipeline 10, and rotary valve 24 and hydraulic cylinder 7 and is provided with hydraulic cylinder in-line 9 and liquid Cylinder pressure return line 6；

Sensor section includes the torque sensor 2 in steering spindle, vehicle speed sensor, and motor speed sensor, with hydraulic cylinder phase Pressure transducer even, steering wheel angle sensor, longitudinal acceleration sensor, yaw-rate sensor, they transmit Corresponding signal is to ECU16.

When driver has steering operation, torque sensor 2 transmits torque sensor signal 23 and arrives ECU16, and meanwhile, ECU16 connects Receive from the corresponding GES 18 of signal transducer, steering wheel angle signal 20, yaw rate signal 21, analyze these Signal, searches Map figure prefabricated for ECU16, ECU16 drives motor 13 to transmit pump oil motor speed control signal to oil pump 15, control motor speed, oil pump drives motor 13 directly to drive double-acting vane pump 12 pump from fuel tank 11 oily to rotary valve 24 In, fluid shunts at rotary valve 24, and a part of hydraulic oil passes through hydraulic cylinder in-line 9 influent cylinder pressure 7 side, at hydraulic pressure Cylinder 7 both sides produce pressure reduction, promote hydraulic cylinder piston 8 to move, and the hydraulic oil of hydraulic cylinder 7 opposite side is flowed back to by return line 6 again Rotary valve 26, finally flows back to hydraulic oil container 11, the pressure reduction of hydraulic cylinder 7 both sides be electric-controlled hydraulic power-assisted steering offer power-assisted, meanwhile, On the one hand ECU16 receives the motor speed signal 17 driving motor 13 from oil pump, and motor speed carries out PID control, right The speed controling signal 15 passing to motor is modified, and the opposing party ECU16 receives from the pressure transducer being connected with hydraulic cylinder The hydraulic cylinder pressure difference signal 22 of transmission, compares with preferable boost pressure, by robust control method, regulates electric moter voltage Output so that pressure maintains near ideal value (± 1%), helps driver to complete to turn to.

Embodiment 2 multidisciplinary collaboration optimization method

In the present embodiment, the modeling software used is MATLAB-simulink, and optimization software is isight；

The present embodiment uses system described in embodiment 1 to carry out multidisciplinary optimization calculating, specifically comprises the following steps that

Step 1: according to " analysis of rotary valve hydraulic power-assist steering system modeling and simulation " (Shi Peiji, Beijing Institute of Technology), " nothing Brushless motor control system " (Xia Changliang, Science Press), " design studies of Electro-Hydraulic Power Steering System " (Mr. Zhang Monarch, Jiangsu University), " electric hydraulic power-assisted steering system control strategy and energy consumption analysis method thereof " (Su Jiankuan etc., Machine Design With manufacture) method disclosed in document, set up electric hydraulic power-assisted steering system model, Full Vehicle Dynamics model, and energy consumption mould Type, wherein electric hydraulic power-assisted steering system model includes motor model, steering wheel model, rack-and-pinion model, steering pump mould Type, rotary valve model, input and output shaft model, hydraulic position servo control model, tire model, by setting up steering Model, energy consumption model, the steering for subsequent step emulates and optimizes and lays the foundation；

Step 2: set up optimizing index model, including steering energy consumption model, sensitivity model, road feel model, by this three The evaluation index that individual mathematical model designs as steering；

Wherein, steering energy consumption quantitative formula is:

E=P_M-loss+P_v-loss+P_pump-loss

Wherein P_M-lossIt is lost for motor power, P_v-lossFor rotary valve energy loss, P_pump-lossFor hydraulic pump energy loss, E is total Energy loss

P_M-loss=U_di-K_Tiw

$U_d=\frac{\frac{B_{v}n\mathrm{\&pi;}}{30}+T_{L_O}}{K_T}ra+\frac{k_{e}n\mathrm{\&pi;}}{30}$

$i=\frac{J}{K_T}\frac{dw}{dt}+\frac{B_v}{K_T}w+\frac{T_L}{K_T}$

Wherein, i is current of electric, and n is motor speed, T_LFor electric motor load torque；

$P_{v-loss}=\frac{\mathrm{\&rho;}}{{\left(C_q{A}_1\right)}^2}{(\frac{Q_s}{4}+A_p\frac{{\mathrm{dx}}_r}{dt})}^3+\frac{\mathrm{\&rho;}}{8{\left(C_q{A}_2\right)}^2}{(\frac{Q_s}{4}-A_p\frac{{\mathrm{dx}}_r}{dt})}^3$

$A_1=NL\&lsqb;w+R\frac{k_c({\mathrm{\&theta;}}_S-{\mathrm{\&theta;}}_P)}{k_c+k_n}\&rsqb;$

$A_2=NL\&lsqb;w-R\frac{k_c({\mathrm{\&theta;}}_S-{\mathrm{\&theta;}}_P)}{k_c+k_n}\&rsqb;$

Wherein, AP is hydraulic cylinder piston area, and A is the oily discharge area of valve clearance, and N is rotary valve valve port number, and L is that rotary valve mouth is narrow Mouth length, w is rotary valve valve port gap width, and Cq is the discharge coefficient of valve clearance, Q_SFor rotary valve oil inlet quantity, x_rFor rack-and-pinion Displacement；

P_pump-loss=P_sqn-P_sQ_s

$P_S=\frac{\mathrm{\&rho;}}{8C_q^2}\&lsqb;{\left(\frac{Q_S-A_P{\stackrel{\&CenterDot;}{\mathrm{\&theta;}}}_P{r}_P}{A_2}\right)}^2+{\left(\frac{Q_S+A_P{\stackrel{\&CenterDot;}{\mathrm{\&theta;}}}_P{r}_P}{A_1}\right)}^2\&rsqb;$

Wherein, θ_pFor turning to output shaft rotation angle.

Sensitivity quantitative formula is:

$\left\{\begin{array}{c}\frac{\mathrm{\&delta;}\left(s\right)}{{\mathrm{\&theta;}}_s\left(s\right)}=\frac{A}{{\mathrm{Xs}}^2+Ys+Z+\frac{qd(k_1+k_2)}{n_2}\&lsqb;\frac{a}{u}\frac{w_r\left(s\right)}{\mathrm{\&delta;}\left(s\right)}+\frac{\mathrm{\&beta;}\left(s\right)}{\mathrm{\&delta;}\left(s\right)}+E_1\frac{\mathrm{\&phi;}\left(s\right)}{\mathrm{\&delta;}\left(s\right)}\&rsqb;}\\ A=A_p{r}_p{\mathrm{KK}}_a{K}_s+K_{TT}q\\ X=m_r{r_p}^2{\mathrm{qn}}_2+n_1{J}_m{A}_p{r}_p{n}_2\\ Y=(B_r{{\mathrm{qr}}_p}^2+n_1{B}_m{A}_p{r}_p+\frac{\left({\mathrm{\&rho;q}}^2{\mathrm{nn}}_v{A_p}^2{r_p}^2\right)}{2{C_q}^2{A_1}^2})n_2\\ Z=(A_p{r}_p{\mathrm{KK}}_a{K}_s+K_{TT}q)n_2-\frac{qd(k_1+k_2)}{n_2}\end{array}\right.$

In formula, δ (s) is the front wheel angle after Laplace transform, θ_sS () is the steering wheel angle after Laplace transform, β (s) is the yaw acceleration after Laplace transform, and φ (s) is the side slip angle after Laplace transform, w_r(s) be Yaw velocity after Laplace transform, n is the rotating speed of double-acting vane pump, n be turn to output shaft to the gear ratio of front-wheel, A be automobile barycenter to front axle distance, u is automobile speed, and d is vehicle 1/2 wheelspan, and E1 is roll steer coefficient, k1, K2 is front-wheel cornering stiffness, and mr is rack mass, and rp is little tooth radius, and n1 is that steering steering wheel angle is to front round The gear ratio at angle, Jm is the rotary inertia of motor and oil pump, and Br is tooth bar damped coefficient, and Bm is the viscosity resistance of motor and oil pump Buddhist nun's coefficient, nv is the volumetric efficiency of oil pump, and Cq is the discharge coefficient of valve clearance, and K is motor power-assisted coefficient, and Ka helps for turning to Force motor moment coefficient, Ks is torque sensor rigidity, and kTT is the integral stiffness of steering spindle and torsion bar；

Road feel quantitative formula is:

$\left\{\begin{array}{c}\frac{T_h\left(s\right)}{T_r\left(s\right)}=\frac{{\mathrm{qK}}_{TT}}{(m_r{r}_p^{2}q+n_1{J}_m{A}_p{r}_p)s^2+(B_r{\mathrm{qr}}_p^2+n_1{B}_m{A}_p{r}_p+\frac{{\mathrm{\&rho;q}}^2{\mathrm{n\&eta;}}_v{A}_p^2{r}_p^2}{2C_q^2{A}^2})s+A_p{r}_p{\mathrm{KK}}_a{K}_s+{\mathrm{qK}}_{TT}}\\ q=2B\&lsqb;\frac{1}{2}(R_2^2-R_1^2)\mathrm{\&pi;}-(R_2-R_1)Zt\&rsqb;\end{array}\right.$

In formula, T_hFor steering wheel input torque, T_rFor the power torque of steering screw, q is pump delivery, and B is stator thickness, R₂For stator major axis radius, R₁For stator minor axis radius, Z is vane pump blade number, and t is vane thickness；

3) with steering response, sensitivity, energy consumption sets up steering optimization object function, simultaneously with the energy value of steering sensitivity Scope, as constraints, sets up Electro-Hydraulic Power Steering System Model for Multi-Objective Optimization, and Electro-Hydraulic Power Steering System is excellent Object function f (x) changed is:

$\left\{\begin{array}{c}f\left(x\right)=\frac{k_1}{f\left(x_1\right)}+\frac{k_2}{f\left(x_2\right)}+f\left(x_3\right)\\ f\left(x_1\right)=\frac{1}{2{\mathrm{\&pi;\&omega;}}_0}{\&Integral;}_0^{{\mathrm{\&omega;}}_0}{{\left|\frac{T_h\left(s\right)}{T_r\left(s\right)}\right|}_{s=j\mathrm{\&omega;}}}^{2}d\mathrm{\&omega;}\\ f\left(x_2\right)=\frac{1}{2{\mathrm{\&pi;\&omega;}}_0}{\&Integral;}_0^{{\mathrm{\&omega;}}_0}{{\left|\frac{\mathrm{\&delta;}\left(s\right)}{{\mathrm{\&theta;}}_s\left(s\right)}\right|}_{s=j\mathrm{\&omega;}}}^{2}d\mathrm{\&omega;}\\ f\left(x_3\right)=E\end{array}\right.$

In formula: road feel function f (x₁) it is information of road surface effective frequency range (0, ω₀) frequency domain energy meansigma methods, optimization side ω in case₀=40Hz；Sensitivity function f (x₂) it is information of road surface effective frequency range (0, ω₀) frequency domain energy meansigma methods； f(x₃) it is steering energy consumption；

During optimizing, function meets 2.8 × 10^-6≤f(x₂)≤8.6×10^-6Constraints；

4) by stator thickness B, motor and the rotary inertia J of oil pump_m, torque sensor stiffness K_s, little tooth radius r_p, Hydraulic cylinder piston area A_P, rotary valve valve port gap width w, as the design variable of Electro-Hydraulic Power Steering System；

5) use cooperative optimization method that Electro-Hydraulic Power Steering System is carried out STRUCTURE DECOMPOSITION, system is divided, is divided into Turn to energy consumption system, sensitivity system, road feel system.Total system uses archipelago genetic algorithm, and subsystem uses NLPQL algorithm, To that hydraulic power-assist steering system 4 automatically controlled) in design variable be optimized, obtain optimal solution.Optimization object function value is less than Before optimization, then it is assumed that optimize effectively.

Described cooperative optimization method, it is characterised in that its structure or implementing procedure be:

51) set up multiple target and work in coordination with Optimized model, with steering response, sensitivity, comprehensive mathematical model f (x) conduct of energy consumption System-level optimization aim, more respectively with steering response, sensitivity, energy consumption as subsystem, build multidisciplinary collaboration Optimized model.

System-level Optimized model:

$\left\{\begin{array}{c}Minimize\\ p=f\left(Z\right)=F(B,J_m,K_s,A_p,w,r_p)\\ \begin{array}{cc}s.t.& R_1<\mathrm{\&epsiv;},R_2<\mathrm{\&epsiv;},R_3<\mathrm{\&epsiv;}\\ & 0.003<B<0.01\\ & 0.001<J_m<0.01\\ & 10<K_s<150\\ & 5\&times;{10}^{-5}<A_p<2\&times;{10}^{-4}\\ & 2\&times;{10}^{-4}<w<{10}^{-3}\\ & 0.01<r_p<0.1\\ & 2.8\&times;{10}^{-6}<f_{ling\min }<8.6\&times;{10}^{-6}\end{array}\end{array}\right.$

In formula, Z is the design variable vector in system-level optimizer；F (Z) is the object function of system-level optimizer；R_iFor being The equation consistency constraint condition of irrespective of size optimizer and subsystem irrespective of size optimizer, meanwhile, is also the object function of subsystems, pine Relaxation factor ε takes 0.001 at this.

Using steering sensitivity as the first subsystem, then subsystem is unified Optimized model and is:

$\left\{\begin{array}{c}Minimize:\\ R_1={(1-B/B^{\&prime;})}^2+{(1-J_m/{J_m}^{\&prime;})}^2+{(1-K_s/{K_s}^{\&prime;})}^2\\ +{(1-A_p/{A_p}^{\&prime;})}^2+{(1-w/w^{\&prime;})}^2+{(1-r_p/{r_p}^{\&prime;})}^2\\ \begin{array}{cc}s.t.& \\ & 0.003<B^{\&prime;}<0.01\\ & 0.001<{J_m}^{\&prime;}<0.01\\ & 10<{K_s}^{\&prime;}<150\\ & 5\&times;{10}^{-5}<{A_p}^{\&prime;}<2\&times;{10}^{-4}\\ & 2\&times;{10}^{-4}<w^{\&prime;}<{10}^{-3}\\ & 0.01<{r_p}^{\&prime;}<0.1\\ & 2.8\&times;{10}^{-6}<{f_{ling\min }}^{\&prime;}<8.6\&times;{10}^{-6}\end{array}\end{array}\right.$

Using steering response as the second subsystem, then subsystem two Optimized model is:

$\left\{\begin{array}{c}Minimize:\\ R_2={(1-B/B^{\&prime;\&prime;})}^2+{(1-J_m/{J_m}^{\&prime;\&prime;})}^2+{(1-K_s/{K_s}^{\&prime;\&prime;})}^2\\ +{(1-A_p/{A_p}^{\&prime;\&prime;})}^2+{(1-w/w^{\&prime;\&prime;})}^2+{(1-r_p/{r_p}^{\&prime;\&prime;})}^2\\ \begin{array}{cc}s.t.& 0.003<B^{\&prime;\&prime;}<0.01\\ & 0.001<{J_m}^{\&prime;\&prime;}<0.01\\ & 10<{K_s}^{\&prime;\&prime;}<150\\ & 5\&times;{10}^{-5}<{A_p}^{\&prime;\&prime;}<2\&times;{10}^{-4}\\ & 2\&times;{10}^{-4}<w^{\&prime;\&prime;}<{10}^{-3}\\ & 0.01<{r_p}^{\&prime;\&prime;}<0.1\end{array}\end{array}\right.$

To turn to energy consumption as the 3rd subsystem, then subsystem three Optimized model is:

$\left\{\begin{array}{c}Minimize:\\ R_3={(1-B/B^{\&prime;\&prime;\&prime;})}^2+{(1-J_m/{J_m}^{\&prime;\&prime;\&prime;})}^2+{(1-K_s/{K_s}^{\&prime;\&prime;\&prime;})}^2\\ +{(1-A_p/{A_p}^{\&prime;\&prime;\&prime;})}^2+{(1-w/w^{\&prime;\&prime;\&prime;})}^2+{(1-r_p/{r_p}^{\&prime;\&prime;\&prime;})}^2\\ \begin{array}{cc}s.t.& 0.003<B^{\&prime;\&prime;\&prime;}<0.01\\ & 0.001<{J_m}^{\&prime;\&prime;\&prime;}<0.01\\ & 10<{K_s}^{\&prime;\&prime;\&prime;}<150\\ & 5\&times;{10}^{-5}<{A_p}^{\&prime;\&prime;\&prime;}<2\&times;{10}^{-4}\\ & 2\&times;{10}^{-4}<w^{\&prime;\&prime;\&prime;}<{10}^{-3}\\ & 0.01<{r_p}^{\&prime;\&prime;\&prime;}<0.1\end{array}\end{array}\right.$

By the model analysis of above each system, the multidisciplinary collaboration Optimized model of Electro-Hydraulic Power Steering System can be expressed as: According to model above, isight software is set up the Electro-Hydraulic Power Steering System multidisciplinary collaboration Optimized model of correspondence, According to choosing archipelago genetic algorithm as optimized algorithm in total system, subsystem all chooses NLPQL algorithm as optimized algorithm, It is optimized according to acquiescence step-length, obtains final optimum results.

Optimizing operating mode is that automobile travels with 80km/h, and steering wheel rotational angle is 25 °

Each design variable and performance indications contrast table before and after the collaborative optimization of table 1

Through comparing, steering response increases, and steering sensitivity, within zone of reasonableness, turns to energy expenditure to reduce, and effect of optimization shows Write.

The above, only this utility model preferably detailed description of the invention, but protection domain of the present utility model is not limited to This, any those familiar with the art in the technical scope that this utility model discloses, the change that can readily occur in or Replace, all should contain within protection domain of the present utility model.Therefore, protection domain of the present utility model should be wanted with right The protection domain asked is as the criterion.

Claims (3)

1. an Electro-Hydraulic Power Steering System, it is characterised in that include steering mechanical part, hydraulic booster part, signal transducer part and electronic control unit ECU；

Described steering mechanical part includes that the steering wheel being sequentially connected with, steering spindle, rotary valve, rack and pinion steering gear and two ends are connected with the track rod of wheel, and track rod is provided with hydraulic cylinder, and steering spindle is provided with torque sensor；

Described hydraulic booster part includes the oil can being linked in sequence, suction, return line, double-acting vane pump, connect rotary valve and the hydraulic cylinder in-line of hydraulic cylinder and hydraulic cylinder return line, the vane pump being joined directly together with double-acting vane pump drives motor, rotary valve is not only mechanically connected with steering spindle, rack and pinion steering gear, is also connected by fluid pressure line with vane pump, hydraulic cylinder；

Described Sensor section includes the torque sensor in steering spindle, vehicle speed sensor, motor speed sensor, the pressure transducer being connected with hydraulic cylinder, steering wheel angle sensor, longitudinal acceleration sensor, yaw-rate sensor；

Described electronic control unit ECU is connected with each sensor element.

A kind of Electro-Hydraulic Power Steering System the most according to claim 1, it is characterised in that described vane pump drives motor to be brshless DC motor.

A kind of Electro-Hydraulic Power Steering System the most according to claim 1, it is characterised in that described electronic control unit ECU is for receiving the signal of telecommunication that each sensor element sends, and drives motor to send control signal to vane pump.