Braking force adjusting method based on electromagnetic valve

Abstract

The invention discloses a braking force adjusting method based on an electromagnetic valve, which belongs to the field of automobile braking, and comprises the following steps of: S1, comprehensively considering electromagnetic characteristics, hydraulic characteristics and mechanical motion characteristics of the electromagnetic valve, and establishing a multi-physical field coupled dynamic model containing electromagnetic force, valve core motion and hydraulic force, the dynamic relation between the position of the valve element of the electromagnetic valve and the braking force is described; s2, optimal structure parameters of the electromagnetic valve are obtained through a finite element simulation method; s3, based on the optimal structure parameters of the electromagnetic valve and the dynamic model of multi-physics field coupling, a fractional order sliding mode variable structure control algorithm is adopted, and PWM signals are generated; and S4, controlling the current of the electromagnetic coil through the PWM signal. By the adoption of the braking force adjusting method based on the electromagnetic valve, high-precision, quick-response and high-robustness adjustment of the braking force is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile braking, and in particular to a braking force regulating method based on a solenoid valve. Background Art

[0002] Solenoid valves, as core actuators in automotive braking and industrial machinery transmission, directly impact system safety and energy efficiency through their braking force regulation accuracy and response speed. The advancement of intelligent driving technology is placing higher demands on the dynamic performance of solenoid valves under complex operating conditions, such as anti-interference capabilities, nonlinear compensation, and energy loss control.

[0003] Existing technologies primarily focus on solenoid valve structural design, drive control algorithms, and hydraulic system matching, but fail to fully consider the dynamic interaction between the electromagnetic, mechanical, and hydraulic fields, resulting in significant deviations between the model and actual operating conditions. Furthermore, traditional linear control algorithms (such as PID) struggle to cope with the strong nonlinear characteristics of solenoid valves (such as magnetic saturation and reluctance nonlinearity caused by air gap variations) and have weak anti-interference capabilities. Summary of the Invention

[0004] The purpose of the present invention is to provide a braking force adjustment method based on a solenoid valve to solve the above technical problems.

[0005] To achieve the above object, the present invention provides a braking force adjustment method based on a solenoid valve, comprising the following steps:

[0006] S1. Comprehensively consider the electromagnetic, hydraulic, and mechanical motion characteristics of the solenoid valve and establish a multi-physics coupled dynamic model that includes electromagnetic force, valve core motion, and hydraulic force to describe the dynamic relationship between the solenoid valve core position and the braking force.

[0007] S2. Obtain the optimal structural parameters of the solenoid valve through finite element simulation method;

[0008] S3, based on the optimal structural parameters of the solenoid valve and the dynamic model of multi-physics field coupling, a fractional-order sliding mode variable structure control algorithm is used to generate a PWM signal;

[0009] S4. Control the electromagnetic coil current through PWM signal to achieve braking force adjustment.

[0010] Preferably, step S1 specifically includes the following steps:

[0011] S11. Based on Maxwell stress theory, establish the electromagnetic force model:

[0012]

[0013] Where, F m represents electromagnetic force; ψ represents magnetic flux, and R m1 Represents the working air gap reluctance, R m2 represents the secondary air gap magnetic resistance, n represents the number of turns of the electromagnetic coil, e represents the secondary air gap length, R represents the valve core radius, l s represents the secondary air gap width; μ0 represents the vacuum magnetic permeability; S0 represents the magnetic pole area; i represents the electromagnetic coil current; z ev Indicates the true position of the solenoid valve core;

[0014] S12. Consider the electromagnetic force F m , spring force F k , hydraulic pressure F s As well as the viscous friction force, the valve core mechanical balance equation is established:

[0015]

[0016] in,

[0017] F k =F0+K k ·z ev (3);

[0018]

[0019] Where m represents the mass of the valve core; Cu represents the viscous damping coefficient of the solenoid valve core movement; and They represent the first-order derivative and second-order derivative of the true position of the solenoid valve core; F0 represents the spring preload; K k Indicates spring stiffness; P m Indicates the master cylinder pressure; P w Indicates wheel cylinder pressure; c d represents the flow coefficient; c1 represents the pressure distribution compensation coefficient; A t Indicates the throttle area; A ev Indicates the valve outlet area; α indicates the valve seat cone half angle; A tw represents the cone area; ζ represents the energy loss coefficient;

[0020] S13. Considering the coil inductance and the back electromotive force generated by the valve core movement, establish the coil circuit equation:

[0021]

[0022] Where u i represents the electromagnetic coil voltage; r represents the electromagnetic coil resistance; Represents the first derivative of the electromagnetic coil current.

[0023] Preferably, step S2 specifically includes the following steps:

[0024] S21. Use ANSYS Electronics to build a solenoid valve model, simulate the effects of different guide sleeve thicknesses and outer magnetic pole thicknesses on the static electromagnetic force, and simplify formula (1) under the initial constraints to obtain:

[0025]

[0026] Where, F δ represents the initial electromagnetic force, and F δ >15N;B δ Indicates the air gap magnetic induction intensity; d a1 Indicates the effective diameter of the armature; δ1 indicates the sum of the working air gap and the length of the limit piece;

[0027] S22, comprehensive response speed and electromagnetic force requirements, through orthogonal test to determine the optimal structural parameters of the solenoid valve: guide sleeve thickness d g =0.5mm, outer magnetic pole thickness d p =6mm, armature length l a =12.1mm, magnetic isolation angle θ m =45°.

[0028] Preferably, under the initial constraint conditions described in step S21, the initial valve core position z ev0 =0.1mm, initial current of electromagnetic coil i0=0.12A, number of turns of electromagnetic coil n=1000.

[0029] Preferably, step S3 specifically includes the following steps:

[0030] S31, Estimation of solenoid valve spool position based on square root volume Kalman filter The state equation is as follows:

[0031]

[0032] Where A and B are state variables, and ΔP represents the difference between the master cylinder pressure and the wheel cylinder pressure;

[0033] S32. Design fractional sliding surface s:

[0034]

[0035] Where z nom 、 and They represent the target position of the solenoid valve core, the first-order derivative of the target position, and the second-order derivative of the target position respectively; k x and k z Both represent weight coefficients; γ and μ both represent fractional orders, and 0<γ,μ<2; Represents the first derivative of the estimated position of the solenoid valve spool;

[0036] S34. Design the following control law:

[0037]

[0038] in,

[0039]

[0040] Where, ε represents the sliding mode robust gain coefficient; k s represents the damping coefficient of the sliding surface, and 0 <k s <10;

[0041] S34, convert the current target value into PWM duty cycle D through PID algorithm pwm :

[0042]

[0043] in,

[0044] Δi e =i nom -i(13);

[0045] Where K p-duty , K i-duty and K d-duty Respectively represent the proportional, integral, and differential gain coefficients of the PID controller; Δi e (t) and Δi e (t-1) represents the current deviation between time t and time t-1; i nom represents the target electromagnetic coil current; Δt represents the sampling interval.

[0046] Preferably, in step S33, γ is adjusted according to the interference frequency, and μ is adjusted according to the system overshoot, so as to improve robustness from the aspects of error convergence, interference suppression, and chattering relief.

[0047] Therefore, the present invention adopts the above-mentioned braking force adjustment method based on the solenoid valve, which has the following beneficial effects:

[0048] 1. Multi-physics field coupling modeling improves dynamic control accuracy: A coupling model is established by comprehensively considering electromagnetic, mechanical, and hydraulic characteristics to accurately describe the dynamic relationship between valve core position and braking force. This solves the problem of large deviation in traditional single-physics field modeling and provides a reliable theoretical basis for the control algorithm.

[0049] 2. Structural parameter optimization significantly improves electromagnetic force response: Through finite element simulation and orthogonal testing, parameters such as the guide sleeve thickness (0.5mm) and the outer magnetic pole thickness (6mm) were optimized. Combined with a 45° magnetic isolation angle design, the initial electromagnetic force is increased by 40%, the response time is shortened to 1.5ms, and eddy current losses are reduced, breaking through the bottleneck of slow response and high energy consumption of traditional solenoid valves.

[0050] 3. Fractional-order sliding mode control enhances system robustness: By introducing fractional orders γ and μ, the control system improves the ability to suppress solenoid valve nonlinearities (such as magnetic saturation and fluid-dynamic coupling) and multi-frequency interference (high-frequency current ripple and low-frequency pressure fluctuations) by adjusting the error convergence rate and phase characteristics. This reduces control error by 30% compared to traditional PID, and improves anti-interference capability by 40%.

[0051] 4. Square Root Cubic Kalman Filter (SRCKF) for Accurate Implicit State Estimation: The SRCKF algorithm is designed based on a coupled model to indirectly estimate the valve core position through measurable variables (current, pressure), avoiding the cost of direct measurement. The estimation error is controlled within 5μm, providing real-time, high-precision feedback for closed-loop control.

[0052] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a flow chart of a braking force adjustment method based on a solenoid valve according to the present invention. DETAILED DESCRIPTION

[0054] In order to make the purposes, technical solutions and advantages disclosed in the embodiments of the present invention clearer, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention and are not intended to limit the embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application. Examples of the embodiments are shown in the accompanying drawings, where the same or similar numbers throughout represent the same or similar elements or elements with the same or similar functions.

[0055] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or devices.

[0056] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0057] like Figure 1 As shown, a braking force adjustment method based on a solenoid valve includes the following steps:

[0058] S1. Comprehensively consider the electromagnetic, hydraulic, and mechanical motion characteristics of the solenoid valve and establish a multi-physics coupled dynamic model that includes electromagnetic force, valve core motion, and hydraulic force to describe the dynamic relationship between the solenoid valve core position and the braking force.

[0059] Step S1 specifically includes the following steps:

[0060] S11. Based on Maxwell stress theory, establish the electromagnetic force model:

[0061]

[0062] Where, F m represents electromagnetic force; ψ represents magnetic flux, and R m1 Represents the working air gap reluctance, R m2 represents the secondary air gap magnetic resistance, n represents the number of turns of the electromagnetic coil, e represents the secondary air gap length, R represents the valve core radius, l s represents the secondary air gap width; μ0 represents the vacuum magnetic permeability; S0 represents the magnetic pole area; i represents the electromagnetic coil current; z ev Indicates the true position of the solenoid valve core;

[0063] S12. Consider the electromagnetic force F m , spring force F k , hydraulic pressure F s As well as the viscous friction force, the valve core mechanical balance equation is established:

[0064]

[0065] in,

[0066] F k =F0+K k ·z ev (3);

[0067]

[0068] Where m represents the mass of the valve core; Cu represents the viscous damping coefficient of the solenoid valve core movement; and They represent the first-order derivative and second-order derivative of the true position of the solenoid valve core; F0 represents the spring preload; K k Indicates spring stiffness; P m Indicates the master cylinder pressure; P wIndicates wheel cylinder pressure; c d represents the flow coefficient; c1 represents the pressure distribution compensation coefficient; A t Indicates the throttle area; A ev Indicates the valve outlet area; α indicates the valve seat cone half angle; A tw represents the cone area; ζ represents the energy loss coefficient;

[0069] S13. Considering the coil inductance and the back electromotive force generated by the valve core movement, establish the coil circuit equation:

[0070]

[0071] Where u i represents the electromagnetic coil voltage; r represents the electromagnetic coil resistance; Represents the first derivative of the electromagnetic coil current.

[0072] S2. Obtain the optimal structural parameters of the solenoid valve through finite element simulation method;

[0073] Step S2 specifically includes the following steps:

[0074] S21. Use ANSYS Electronics to build a solenoid valve model, simulate the effects of different guide sleeve thicknesses and outer magnetic pole thicknesses on the static electromagnetic force, and simplify formula (1) under the initial constraints to obtain:

[0075]

[0076] Where, F δ represents the initial electromagnetic force, and F δ >15N;B δ Indicates the air gap magnetic induction intensity; d a1 Indicates the effective diameter of the armature; δ1 indicates the sum of the working air gap and the length of the limit piece;

[0077] S22, comprehensive response speed and electromagnetic force requirements, through orthogonal test to determine the optimal structural parameters of the solenoid valve: guide sleeve thickness d g =0.5mm, outer magnetic pole thickness d p =6mm, armature length l a =12.1mm, magnetic isolation angle θ m =45°.

[0078] Preferably, under the initial constraint conditions described in step S21, the initial valve core position z ev0 =0.1mm, initial current of electromagnetic coil i0=0.12A, number of turns of electromagnetic coil n=1000.

[0079] S3, based on the optimal structural parameters of the solenoid valve and the dynamic model of multi-physics field coupling, a fractional-order sliding mode variable structure control algorithm is used to generate a PWM signal;

[0080] Step S3 specifically includes the following steps:

[0081] S31, Estimation of solenoid valve spool position based on square root volume Kalman filter The state equation is as follows:

[0082]

[0083] Where A and B are state variables, and ΔP represents the difference between the master cylinder pressure and the wheel cylinder pressure;

[0084] S32. Design fractional sliding surface s:

[0085]

[0086] Where z nom 、 and They represent the target position of the solenoid valve core, the first-order derivative of the target position, and the second-order derivative of the target position respectively; k x and k z Both represent weight coefficients; γ and μ both represent fractional orders, and 0<γ,μ<2; Represents the first derivative of the estimated position of the solenoid valve spool;

[0087] S34. Design the following control law:

[0088]

[0089] in,

[0090]

[0091] Where, ε represents the sliding mode robust gain coefficient; k s represents the damping coefficient of the sliding surface, and 0 <k s <10;

[0092] In step S33, γ is adjusted according to the interference frequency, and μ is adjusted according to the system overshoot, achieving improved robustness in terms of error convergence, interference suppression, and chattering mitigation. Specifically, γ is set to 1.5 for high-frequency interference and γ to 0.8 for low-frequency interference; μ is set to 0.5 for large overshoot and 1.2 for small overshoot.

[0093] S34, convert the current target value into PWM duty cycle D through PID algorithm pwm :

[0094] in,

[0095] Δi e =i nom -i(13);

[0096] Where K p-duty , K i-duty and K d-duty Respectively represent the proportional, integral, and differential gain coefficients of the PID controller; Δi e (t) and Δi e (t-1) represents the current deviation between time t and time t-1; i nom represents the target electromagnetic coil current; Δt represents the sampling interval.

[0097] S4. Control the electromagnetic coil current through PWM signal to achieve braking force adjustment.

[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solutions of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A braking force adjustment method based on a solenoid valve, characterized in that: The following steps are involved: S1. Comprehensively consider the electromagnetic, hydraulic, and mechanical motion characteristics of the solenoid valve and establish a multi-physics coupled dynamic model that includes electromagnetic force, valve core motion, and hydraulic force to describe the dynamic relationship between the solenoid valve core position and the braking force. S2. Obtain the optimal structural parameters of the solenoid valve through finite element simulation method; S3, based on the optimal structural parameters of the solenoid valve and the dynamic model of multi-physics field coupling, a fractional-order sliding mode variable structure control algorithm is used to generate a PWM signal; S4. Control the electromagnetic coil current through PWM signal to achieve braking force adjustment.

2. The braking force adjustment method based on a solenoid valve according to claim 1, characterized in that: Step S1 specifically includes the following steps: S11. Based on Maxwell stress theory, establish the electromagnetic force model: Where, F m represents electromagnetic force; ψ represents magnetic flux, and R m1 Represents the working air gap reluctance, R m2 represents the secondary air gap magnetic resistance, n represents the number of turns of the electromagnetic coil, e represents the secondary air gap length, R represents the valve core radius, l s represents the secondary air gap width; μ0 represents the vacuum magnetic permeability; S0 represents the magnetic pole area; i represents the electromagnetic coil current; z ev Indicates the true position of the solenoid valve core; S12. Consider the electromagnetic force F m , spring force F k , hydraulic pressure F s As well as the viscous friction force, the valve core mechanical balance equation is established: in, F k =F0+K k ·z ev (3); Where m represents the mass of the valve core; Cu represents the viscous damping coefficient of the solenoid valve core movement; and They represent the first-order derivative and second-order derivative of the true position of the solenoid valve core; F0 represents the spring preload; K k Indicates spring stiffness; P m Indicates the master cylinder pressure; P w Indicates wheel cylinder pressure; c d represents the flow coefficient; c1 represents the pressure distribution compensation coefficient; A t Indicates the throttle area; A ev Indicates the valve outlet area; α indicates the valve seat cone half angle; A tw represents the cone area; ζ represents the energy loss coefficient; S13. Considering the coil inductance and the back electromotive force generated by the valve core movement, establish the coil circuit equation: Where u i represents the electromagnetic coil voltage; r represents the electromagnetic coil resistance; Represents the first derivative of the electromagnetic coil current.

3. The braking force adjustment method based on a solenoid valve according to claim 2, characterized in that: Step S2 specifically includes the following steps: S21. Use ANSYS Electronics to build a solenoid valve model, simulate the effects of different guide sleeve thicknesses and outer magnetic pole thicknesses on the static electromagnetic force, and simplify formula (1) under the initial constraints to obtain: Where, F δ represents the initial electromagnetic force, and F δ >15N;B δ Indicates the air gap magnetic induction intensity; d a1 Indicates the effective diameter of the armature; δ1 indicates the sum of the working air gap and the length of the limit piece; S22, comprehensive response speed and electromagnetic force requirements, through orthogonal test to determine the optimal structural parameters of the solenoid valve: guide sleeve thickness d g =0.5mm, outer magnetic pole thickness d p =6mm, armature length l a =12.1mm, magnetic isolation angle θ m =45°.

4. The braking force adjustment method based on a solenoid valve according to claim 3, characterized in that: Under the initial constraint conditions described in step S21, the initial valve core position z ev0 =0.1mm, initial current of electromagnetic coil i0=0.12A, number of turns of electromagnetic coil n=1000.

5. The braking force adjustment method based on a solenoid valve according to claim 3, characterized in that: Step S3 specifically includes the following steps: S31, Estimation of solenoid valve spool position based on square root volume Kalman filter The state equation is as follows: Where A and B are state variables, and ΔP represents the difference between the master cylinder pressure and the wheel cylinder pressure; S32. Design fractional sliding surface s: Where z nom 、 and They represent the target position of the solenoid valve core, the first-order derivative of the target position, and the second-order derivative of the target position respectively; k x and k z Both represent weight coefficients; γ and μ both represent fractional orders, and 0<γ,μ<2; Represents the first derivative of the estimated position of the solenoid valve spool; S34. Design the following control law: in, Where, ε represents the sliding mode robust gain coefficient; k s represents the damping coefficient of the sliding surface, and 0 <k s <10; S34, convert the current target value into PWM duty cycle D through PID algorithm pwm : in, Δi e =i nom -i (13); Where K p-duty , K i-duty and K d-duty Respectively represent the proportional, integral, and differential gain coefficients of the PID controller; Δi e (t) and Δi e (t-1) represents the current deviation between time t and time t-1; i nom represents the target electromagnetic coil current; Δt represents the sampling interval.

6. The braking force adjustment method based on a solenoid valve according to claim 5, characterized in that: In step S33 , γ is adjusted according to the interference frequency, and μ is adjusted according to the system overshoot, so as to improve robustness in terms of error convergence, interference suppression, and chattering relief.

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