阅读说明：本技术 一种用于提高越野汽车驾驶舒适性的控制方法 (Control method for improving driving comfort of off-road vehicle ) 是由 曾繁鸣 付畅 黄祖胜 张志勇 胡孝恒 于 2020-12-30 设计创作，主要内容包括：本发明涉及汽车控制方法技术领域,具体地指一种用于提高越野汽车驾驶舒适性的控制方法。采集车身的垂向加速度信号,基于垂向加速度信号获得车身的垂向加速度均方根值和均方根值变化率、最大功率谱对应振动频率和振动频率变化率,以垂向加速度均方根值和均方根值变化率为基础进行二维阻尼模糊控制得到最佳阻尼；以最大功率谱对应振动频率和振动频率变化率为基础进行二维刚度模糊控制得到最佳刚度；对最佳阻尼和最佳刚度进行修正获得目标阻尼和目标刚度；车身的悬架控制器调节悬架的阻尼至目标阻尼、调节刚度至目标刚度。本发明获取目标阻尼和目标刚度,主动调节达到提高驾驶舒适性的目的,能够让车身振动频率远离人体共振频率范围。(The invention relates to the technical field of automobile control methods, in particular to a control method for improving driving comfort of an off-road automobile. Acquiring a vertical acceleration signal of the vehicle body, obtaining a vertical acceleration root mean square value and a root mean square value change rate of the vehicle body and a vibration frequency change rate corresponding to a maximum power spectrum based on the vertical acceleration signal, and performing two-dimensional damping fuzzy control on the basis of the vertical acceleration root mean square value and the root mean square value change rate to obtain optimal damping; carrying out two-dimensional rigidity fuzzy control on the basis of the vibration frequency corresponding to the maximum power spectrum and the vibration frequency change rate to obtain the optimal rigidity; correcting the optimal damping and the optimal rigidity to obtain target damping and target rigidity; a suspension controller of the vehicle body adjusts damping of the suspension to a target damping, and adjusts stiffness to a target stiffness. The invention obtains the target damping and the target rigidity, actively adjusts to achieve the purpose of improving the driving comfort, and can lead the vibration frequency of the vehicle body to be far away from the human body resonance frequency range.)

1. A control method for improving the driving comfort of an off-road vehicle is characterized in that: acquiring a vertical acceleration signal of the vehicle body through an acceleration sensor arranged on the vehicle body, acquiring a vertical acceleration root mean square value and a root mean square value change rate of the vehicle body based on the vertical acceleration signal, and performing two-dimensional damping fuzzy control on the vertical acceleration root mean square value and the root mean square value change rate to obtain optimal damping; carrying out two-dimensional rigidity fuzzy control on the basis of the vibration frequency corresponding to the maximum power spectrum and the vibration frequency change rate to obtain the optimal rigidity; correcting the optimal damping and the optimal rigidity to obtain target damping and target rigidity; a suspension controller of the vehicle body adjusts damping of the suspension to a target damping, and adjusts stiffness to a target stiffness.

2. A control method for improving ride comfort of an off-road vehicle as claimed in claim 1, wherein: the method for correcting the optimal rigidity comprises the following steps: acquiring a longitudinal acceleration signal and a vehicle speed signal of a vehicle body, and inquiring a rigidity two-dimensional table obtained through calibration based on the longitudinal acceleration and the vehicle speed of the vehicle body to obtain a minimum rigidity limit value; the greater of the optimal stiffness and the minimum stiffness limit is taken as the target stiffness.

3. A control method for improving ride comfort of an off-road vehicle as claimed in claim 1, wherein: the method for correcting the optimal damping comprises the following steps: acquiring a longitudinal acceleration signal and a vehicle speed signal of a vehicle body, and inquiring a damping two-dimensional table obtained through calibration based on the longitudinal acceleration and the vehicle speed of the vehicle body to obtain a minimum damping limit value; the larger of the optimal damping and the minimum damping limit is taken as the target damping.

4. A control method for improving ride comfort of an off-road vehicle as claimed in claim 1, wherein: the method for carrying out two-dimensional rigidity fuzzy control on the basis of the vibration frequency corresponding to the maximum power spectrum and the vibration frequency change rate to obtain the optimal rigidity comprises the following steps: recording the product of the vibration frequency corresponding to the maximum power spectrum and the quantization factor of the vibration frequency corresponding to the maximum power spectrum as a frequency fuzzy domain value of a two-dimensional stiffness fuzzy control rule, recording the product of the vibration frequency change rate and the quantization factor of the vibration frequency change rate as a frequency change rate fuzzy domain value of the two-dimensional stiffness fuzzy control rule, inputting an input membership function corresponding to the vibration frequency and the vibration frequency change rate corresponding to the maximum power spectrum in the two-dimensional stiffness fuzzy control rule, converting the frequency fuzzy domain value and the frequency change rate fuzzy domain value into a fuzzy subset, obtaining the fuzzy subset of the optimal stiffness according to the two-dimensional stiffness fuzzy control rule, converting the fuzzy subset of the optimal stiffness into the fuzzy domain value of the optimal stiffness through an output membership function corresponding to the optimal stiffness, and multiplying the fuzzy domain value of the optimal stiffness by a scale factor of the optimal stiffness, the optimum stiffness is obtained.

5. A control method for improving ride comfort of an off-road vehicle as claimed in claim 4, wherein: the quantization factor of the maximum power spectrum corresponding to the vibration frequency in the two-dimensional rigidity fuzzy control is as follows:

wherein: k is a radical of_f-the maximum power spectrum corresponds to a quantization factor of the vibration frequency;

f₁obtaining a smaller value of the variation range of the maximum power corresponding to the vibration frequency f through real vehicle calibration;

f₂obtaining a larger value of the variation range of the maximum power corresponding to the vibration frequency f through real vehicle calibration;

x₃the maximum power spectrum in the two-dimensional stiffness fuzzy control rule corresponds to the fuzzy domain range of the vibration frequency;

the quantization factor for the rate of change of the vibration frequency is:

wherein: k is a radical of_Δf-a quantization factor of the rate of change of the vibration frequency;

Δf₀obtaining the unilateral change range of the frequency change rate delta f corresponding to the maximum vibration power through real vehicle calibration;

x₄-a fuzzy domain range of vibration frequency rate of change in the two-dimensional stiffness fuzzy control rule;

the output variables, i.e. the quantization factors for the optimal stiffness, are:

wherein: k is a radical of_K-a quantization factor of the optimal stiffness;

K₁-minimum value of active suspension stiffness adjustment;

K₂-maximum value of active suspension stiffness adjustment;

y₂optimum stiffness in two-dimensional stiffness fuzzy control ruleThe domain of ambiguity range of (c).

6. A control method for improving ride comfort of an off-road vehicle as claimed in claim 1, wherein: the method for carrying out two-dimensional damping fuzzy control on the basis of the vertical acceleration root mean square value and the root mean square value change rate to obtain the optimal damping comprises the following steps: recording the product of the vertical acceleration root-mean-square value and the quantization factor of the vertical acceleration root-mean-square value as a root-mean-square value fuzzy theory domain value of a two-dimensional damping fuzzy control rule, recording the product of the root-mean-square value rate of change and the quantization factor of the root-mean-square value rate of change as a root-mean-square value rate of change fuzzy theory domain value of the two-dimensional damping fuzzy control rule, inputting input membership functions corresponding to the vertical acceleration root-mean-square value and the root-mean-square value rate of change in the two-dimensional damping fuzzy control rule, converting the root-mean-square value fuzzy theory domain value and the root-mean-square value rate of change into fuzzy subsets, obtaining a fuzzy subset of the optimal damping according to the two-dimensional damping fuzzy control rule, converting the fuzzy subset of the optimal damping into a fuzzy theory domain value of the optimal damping through an output membership function, the best damping can be obtained.

7. A control method for improving ride comfort of an off-road vehicle as claimed in claim 6, wherein: the quantization factor of the root mean square value of the vertical acceleration in the two-dimensional damping fuzzy control is as follows:

wherein: k is a radical of_A-a quantization factor of the vertical acceleration root mean square value;

A₁obtaining a smaller value of the variation range of the vertical acceleration root mean square value through real vehicle calibration;

A₂obtaining a larger value of the variation range of the vertical acceleration root mean square value through real vehicle calibration;

x₁the fuzzy domain range of the root mean square value of the vertical acceleration in the two-dimensional damping fuzzy control rule;

the quantization factor of the rate of change of the root mean square value is:

wherein: k is a radical of_ΔA-a quantization factor of the rate of change of the root mean square value;

ΔA₀obtaining a unilateral variation range of the variation rate delta A of the vertical acceleration root mean square value through real vehicle calibration;

x₂-a ambiguity domain range of the root mean square value rate of change in the two-dimensional damping fuzzy control rule;

the output variable, the quantization factor for the optimal damping, is:

wherein: k is a radical of_C-a quantization factor for optimal damping;

C₁-minimum value of active suspension damping adjustment;

C₂-minimum value of active suspension damping adjustment;

y₁-the universe of ambiguities for optimal damping in the two-dimensional damping fuzzy control rule.

8. A control method for improving ride comfort of an off-road vehicle as claimed in claim 1, wherein: the method for obtaining the root mean square value of the vertical acceleration of the vehicle body based on the vertical acceleration comprises the following steps: calculating the root mean square value of the vertical acceleration according to the following formula:

wherein：A_ZtThe vertical acceleration of the vehicle body acquired at the moment t;

ns is the vertical acceleration signal acquisition period;

t-time period.

9. A control method for improving ride comfort of an off-road vehicle as claimed in claim 1, wherein: the method for obtaining the vibration frequency corresponding to the maximum power spectrum based on the vertical acceleration comprises the following steps: calculating the vibration frequency corresponding to the maximum power spectrum according to the following formula:

f(t)＝f_(P＝Pmax)

wherein: f (T) -the maximum power spectrum within the period T (T-T, T) corresponds to the vibration frequency;

p_max-maximum power spectrum within period T (T-T, T);

the power spectral density function p (f) is represented as follows:

wherein: p (f) -power spectral density function;

x (f) -carrying out frequency normalization value taking on the vertical acceleration time domain signal;

f_s-a sampling frequency;

the calculation method for carrying out frequency normalization value X (f) on the time domain signal of the vertical acceleration in the period T (T-T, T) is as follows:

wherein: n is the number of sampling points in the period T (T-T, T);

A_Zn-a vertical acceleration time domain signal;

f_s-a sampling frequency;

n is a natural number with the value of 1, 2 and 3 … N;

j is an imaginary unit, j 2 ^ -1.

10. A control method for improving ride comfort of an off-road vehicle as claimed in claim 9, wherein: the method for obtaining the vibration frequency change rate of the vehicle body based on the vertical acceleration comprises the following steps: the vibration frequency change rate was calculated according to the following formula:

wherein: Δ f (t) -the vibration frequency change rate corresponding to the maximum power spectrum at the time t;

f (T) -the maximum power spectrum within the period T (T-T, T) corresponds to the vibration frequency;

f (T- Δ T) -the maximum power spectrum within the period T (T- Δ T-T, T- Δ T) corresponds to the vibration frequency;

Δ t — calculate step size.

Technical Field

The invention relates to the technical field of automobile control methods, in particular to a control method for improving driving comfort of an off-road automobile.

Background

During the process of testing and trial driving of the off-road vehicle, the main factor limiting the average speed of the off-road vehicle is that a driver cannot bear fatigue caused by violent jolt when the vehicle runs on the off-road. Generally, as the vehicle speed increases, the vibration in the vehicle interior caused by the road surface increases, and the vehicle stability deteriorates, increasing the degree of fatigue of the occupant. And, during the vibration of the vehicle, if the vibration frequency is concentrated in the human resonance frequency range, the occupant feels very uncomfortable.

The patent proposes a method for improving driving comfort by actively adjusting damping, and the patent is a Chinese invention patent with the patent number of CN103204043A named as a frequency domain control method of a semi-active suspension system of an automobile, and the patent proposes that the frequency domain transmission characteristics of vertical acceleration of an automobile body, dynamic load of wheels and dynamic deflection of the suspension are taken as the basis, the vibration frequency band range of the semi-active suspension system can be adaptively judged, so that response damping is exerted, better control performance can be achieved in the whole frequency domain, and the suspension performance of the automobile is obviously improved. The method mainly achieves the purpose of improving the performance of the vehicle suspension by actively controlling the damping, but actually influences the vehicle suspension and the driving comfort not only by one damping factor, the damping influence is mainly the vibration amplitude of the vehicle suspension, if the vibration frequency of the vehicle body is in the range of the human body resonance frequency, drivers and passengers can generate serious discomfort, and the adjustment of the vehicle body rigidity which influences the vibration frequency is temporarily provided with no public data at present.

Disclosure of Invention

The present invention is to solve the above-mentioned drawbacks of the prior art, and to provide a control method for improving driving comfort of an off-road vehicle.

The technical scheme of the invention is as follows: a control method for improving the driving comfort of an off-road vehicle is characterized in that: acquiring a vertical acceleration signal of the vehicle body through an acceleration sensor arranged on the vehicle body, acquiring a vertical acceleration root mean square value and a root mean square value change rate of the vehicle body based on the vertical acceleration signal, and performing two-dimensional damping fuzzy control on the vertical acceleration root mean square value and the root mean square value change rate to obtain optimal damping; carrying out two-dimensional rigidity fuzzy control on the basis of the vibration frequency corresponding to the maximum power spectrum and the vibration frequency change rate to obtain the optimal rigidity; correcting the optimal damping and the optimal rigidity to obtain target damping and target rigidity; a suspension controller of the vehicle body adjusts damping of the suspension to a target damping, and adjusts stiffness to a target stiffness.

The further method for correcting the optimal rigidity comprises the following steps: acquiring a longitudinal acceleration signal and a vehicle speed signal of a vehicle body, and inquiring a rigidity two-dimensional table obtained through calibration based on the longitudinal acceleration and the vehicle speed of the vehicle body to obtain a minimum rigidity limit value; the greater of the optimal stiffness and the minimum stiffness limit is taken as the target stiffness.

The method for correcting the optimal damping further comprises the following steps: acquiring a longitudinal acceleration signal and a vehicle speed signal of a vehicle body, and inquiring a damping two-dimensional table obtained through calibration based on the longitudinal acceleration and the vehicle speed of the vehicle body to obtain a minimum damping limit value; the larger of the optimal damping and the minimum damping limit is taken as the target damping.

The method for carrying out two-dimensional rigidity fuzzy control on the basis of the vibration frequency corresponding to the maximum power spectrum and the vibration frequency change rate to obtain the optimal rigidity further comprises the following steps: recording the product of the vibration frequency corresponding to the maximum power spectrum and the quantization factor of the vibration frequency corresponding to the maximum power spectrum as a frequency fuzzy domain value of a two-dimensional stiffness fuzzy control rule, recording the product of the vibration frequency change rate and the quantization factor of the vibration frequency change rate as a frequency change rate fuzzy domain value of the two-dimensional stiffness fuzzy control rule, inputting an input membership function corresponding to the vibration frequency and the vibration frequency change rate corresponding to the maximum power spectrum in the two-dimensional stiffness fuzzy control rule, converting the frequency fuzzy domain value and the frequency change rate fuzzy domain value into a fuzzy subset, obtaining the fuzzy subset of the optimal stiffness according to the two-dimensional stiffness fuzzy control rule, converting the fuzzy subset of the optimal stiffness into the fuzzy domain value of the optimal stiffness through an output membership function corresponding to the optimal stiffness, and multiplying the fuzzy domain value of the optimal stiffness by a scale factor of the optimal stiffness, the optimum stiffness is obtained.

Further, the quantization factor of the maximum power spectrum corresponding to the vibration frequency in the two-dimensional stiffness fuzzy control is as follows:

wherein: k is a radical of_f-the maximum power spectrum corresponds to a quantization factor of the vibration frequency;

f₁obtaining a smaller value of the variation range of the maximum power corresponding to the vibration frequency f through real vehicle calibration;

f₂obtaining a larger value of the variation range of the maximum power corresponding to the vibration frequency f through real vehicle calibration;

x₃the maximum power spectrum in the two-dimensional stiffness fuzzy control rule corresponds to the fuzzy domain range of the vibration frequency;

the quantization factor for the rate of change of the vibration frequency is:

wherein: k is a radical of_Δf-a quantization factor of the rate of change of the vibration frequency;

Δf₀obtaining the unilateral change range of the frequency change rate delta f corresponding to the maximum vibration power through real vehicle calibration;

x₄-a fuzzy domain range of vibration frequency rate of change in the two-dimensional stiffness fuzzy control rule;

the output variables, i.e. the quantization factors for the optimal stiffness, are:

wherein: k is a radical of_K-a quantization factor of the optimal stiffness;

K₁-minimum value of active suspension stiffness adjustment;

K₂-maximum value of active suspension stiffness adjustment;

y₂-the universe of ambiguities for optimal stiffness in the two-dimensional stiffness fuzzy control rule.

The method for carrying out two-dimensional damping fuzzy control on the basis of the vertical acceleration root mean square value and the root mean square value change rate to obtain the optimal damping further comprises the following steps: recording the product of the vertical acceleration root-mean-square value and the quantization factor of the vertical acceleration root-mean-square value as a root-mean-square value fuzzy theory domain value of a two-dimensional damping fuzzy control rule, recording the product of the root-mean-square value rate of change and the quantization factor of the root-mean-square value rate of change as a root-mean-square value rate of change fuzzy theory domain value of the two-dimensional damping fuzzy control rule, inputting input membership functions corresponding to the vertical acceleration root-mean-square value and the root-mean-square value rate of change in the two-dimensional damping fuzzy control rule, converting the root-mean-square value fuzzy theory domain value and the root-mean-square value rate of change into fuzzy subsets, obtaining a fuzzy subset of the optimal damping according to the two-dimensional damping fuzzy control rule, converting the fuzzy subset of the optimal damping into a fuzzy theory domain value of the optimal damping through an output membership function, the best damping can be obtained.

Further, the quantization factor of the root mean square value of the vertical acceleration in the two-dimensional damping fuzzy control is as follows:

wherein: k is a radical of_A-a quantization factor of the vertical acceleration root mean square value;

A₁by calibration of a real vehicleObtaining a smaller value of the variation range of the vertical acceleration root-mean-square value;

A₂obtaining a larger value of the variation range of the vertical acceleration root mean square value through real vehicle calibration;

x₁the fuzzy domain range of the root mean square value of the vertical acceleration in the two-dimensional damping fuzzy control rule;

the quantization factor of the rate of change of the root mean square value is:

wherein: k is a radical of_ΔA-a quantization factor of the rate of change of the root mean square value;

ΔA₀obtaining a unilateral variation range of the variation rate delta A of the vertical acceleration root mean square value through real vehicle calibration;

x₂-a ambiguity domain range of the root mean square value rate of change in the two-dimensional damping fuzzy control rule;

the output variable, the quantization factor for the optimal damping, is:

wherein: k is a radical of_C-a quantization factor for optimal damping;

C₁-minimum value of active suspension damping adjustment;

C₂-minimum value of active suspension damping adjustment;

y₁-the universe of ambiguities for optimal damping in the two-dimensional damping fuzzy control rule.

The method for obtaining the root mean square value of the vertical acceleration of the vehicle body based on the vertical acceleration further comprises the following steps: calculating the root mean square value of the vertical acceleration according to the following formula:

wherein: a. the_ZtThe vertical acceleration of the vehicle body acquired at the moment t;

ns is the vertical acceleration signal acquisition period;

t-time period.

The method for obtaining the vibration frequency corresponding to the maximum power spectrum based on the vertical acceleration further comprises the following steps: calculating the vibration frequency corresponding to the maximum power spectrum according to the following formula:

f(t)＝f_(P＝Pmax)

wherein: f (T) -the maximum power spectrum within the period T (T-T, T) corresponds to the vibration frequency;

p_max-maximum power spectrum within period T (T-T, T);

the power spectral density function p (f) is represented as follows:

wherein: p (f) -power spectral density function;

x (f) -carrying out frequency normalization value taking on the vertical acceleration time domain signal;

f_s-a sampling frequency;

the calculation method for carrying out frequency normalization value X (f) on the time domain signal of the vertical acceleration in the period T (T-T, T) is as follows:

wherein: n is the number of sampling points in the period T (T-T, T);

A_Zn-a vertical acceleration time domain signal;

f_s-a sampling frequency;

n is a natural number with the value of 1, 2 and 3 … N;

j is an imaginary unit, j 2 ^ -1.

Further, the method for obtaining the vibration frequency change rate of the vehicle body based on the vertical acceleration comprises the following steps: the vibration frequency change rate was calculated according to the following formula:

wherein: Δ f (t) -the vibration frequency change rate corresponding to the maximum power spectrum at the time t;

f (T) -the maximum power spectrum within the period T (T-T, T) corresponds to the vibration frequency;

f (T- Δ T) -the maximum power spectrum within the period T (T- Δ T-T, T- Δ T) corresponds to the vibration frequency;

Δ t — calculate step size.

Aiming at the defect that the vibration frequency of a vehicle body can not be far away from the resonance frequency of a human body in the prior control technology, a damping and fuzzy control rule is established, and the damping is adjusted through a two-dimensional fuzzy controller to reduce the vibration amplitude; and a rigidity fuzzy control rule is established, and the rigidity of the active suspension is adjusted through a two-dimensional fuzzy controller, so that the vibration frequency is far away from the human body resonance frequency range, and the driving comfort of the vehicle is improved.

Meanwhile, the invention also considers that under the condition of high vehicle speed, the stability of the vehicle is deteriorated due to too low damping and rigidity, and the driver feels uncomfortable due to large pitch angle and roll angle of the vehicle during braking and steering, so that the target rigidity and the target damping are limited according to the vehicle speed and the longitudinal acceleration, the stability of the vehicle is maintained, and the aim of improving the driving comfort is achieved.

The control method fully considers various factors influencing the driving comfort of the vehicle, obtains proper target damping and target rigidity through the fuzzy control rule, actively adjusts to achieve the purpose of improving the driving comfort, can enable the vibration frequency of the vehicle body to be far away from the resonance frequency range of the human body, and has great popularization value.

Drawings

FIG. 1: the control logic flow of the invention is shown schematically;

FIG. 2: the invention discloses a vehicle body suspension rigidity adjusting schematic diagram;

FIG. 3: the fuzzy controller of the present invention is a schematic diagram.

Detailed Description

Reference will now be made in detail to the embodiments of the present invention, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.

In the description of the present invention, it is to be understood that the terms "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.

Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.

The invention is described in further detail below with reference to the figures and the specific embodiments.

As shown in fig. 1-3, in this embodiment, an acceleration sensor is installed below a seat, time domain signals of a vertical acceleration and a longitudinal acceleration of a vehicle body are collected by the acceleration sensor, the time domain signals of the vertical acceleration are transmitted to a vehicle control unit, the vehicle control unit calculates a root mean square value a of the vertical acceleration within a time period T, and a calculation formula is as follows:

wherein: a. the_ZtThe vertical acceleration of the vehicle body acquired at the moment t;

ns is the vertical acceleration signal acquisition period;

t-time period.

The root mean square value A of the vertical acceleration is obtained by squaring, summing and then squaring the vertical acceleration acquired in the time period T (T-T, T).

At the time of T, performing spectrum analysis on a vertical acceleration time domain signal in a period T (T-T, T), wherein the number N of sampling points in the period T is T/ns, and the vertical acceleration time domain signal is marked as A_ZnN is 1, 2, 3 ….. N, the frequency of the signal is normalized, and the specific calculation formula is as follows:

wherein: n is the number of sampling points in the period T;

A_Zn-a vertical acceleration time domain signal;

n is a natural number with the value of 1, 2 and 3 … N;

j is an imaginary unit, j ^2 ═ 1;

f_s-sampling frequency.

The power spectral density function is expressed as follows:

wherein: p (f) -power spectral density function;

x (f) -carrying out frequency normalization value taking on the vertical acceleration time domain signal;

f_s-sampling frequency.

Then the calculation formula of the maximum power corresponding to the frequency of the power spectrum density function in the period T (T-T, T) is as follows:

f(t)＝f_(P＝Pmax)

wherein: f (T) -the maximum power spectrum within the period T (T-T, T) corresponds to the vibration frequency;

p is the power spectrum;

P_max-maximum power spectrum within period T (T-T, T).

Calculating the variation rate of the vibration frequency corresponding to the vertical acceleration root mean square value and the maximum power spectrum in the period T (T-T, T), wherein the calculation formula is as follows:

wherein: Δ f (t) -the vibration frequency change rate corresponding to the maximum power spectrum at the time t;

Δ A (t) -the variation rate of the root mean square value of the vertical acceleration at the time t;

f (T) -the maximum power spectrum within the period T (T-T, T) corresponds to the vibration frequency;

a (T) -the root mean square value of the vertical acceleration in the period T (T-T, T);

f (T- Δ T) -the maximum power spectrum within the period T (T- Δ T-T, T- Δ T) corresponds to the vibration frequency;

a (T- Δ T) -the root mean square value of the vertical acceleration within the period T (T- Δ T-T, T- Δ T);

Δ t — calculate step size.

As shown in fig. 3, a two-dimensional damping fuzzy controller and a two-dimensional stiffness fuzzy controller are established according to the fuzzy control rule in fig. 3, the vertical acceleration root mean square value a and the root mean square value change rate Δ a are used as the input of the two-dimensional damping fuzzy controller, and the optimal damping C is obtained according to the damping fuzzy control rule. And (3) taking the vibration frequency f corresponding to the maximum power spectrum and the vibration frequency change rate delta f as the input of the two-dimensional rigidity fuzzy controller, and obtaining the optimal rigidity K according to the two-dimensional rigidity fuzzy control rule.

In two dimensionsIn the damping fuzzy controller, the root mean square value A of the vertical acceleration in the input variable is constantly larger than 0, and the actual variation range [ A ] of A can be obtained through the calibration measurement of a real vehicle₁，A₂](A₁Obtaining a smaller value of the variation range of the vertical acceleration root mean square value through real vehicle calibration; a. the₂Obtaining a larger value of a variation range of a vertical acceleration root mean square value through real vehicle calibration, and converting the variation range into [ - (A) through an offset zero point₂-A₁)/2，(A₂-A₁)/2]. The actual variation range of the variation rate Delta A of the root mean square value of the vertical acceleration can be obtained by the calibration measurement of an actual vehicle and is marked as [ -Delta A ]₀，ΔA₀](ΔA₀The unilateral variation range of the vertical acceleration root mean square value variation rate delta A is obtained through real vehicle calibration). The optimal damping of the output variable is constantly greater than 0 and the variation range [ C ] thereof₁，C₂](C₁Is the minimum value of active suspension damping adjustment; c₂Is the maximum value of active suspension damping adjustment) is converted into [ - (C) by offsetting the zero point₂-C₁)/2，(C₂-C₁)/2]。

In a two-dimensional rigidity fuzzy controller, the vibration frequency f corresponding to the maximum power spectrum in input variables is constantly larger than 0, and the actual variation range [ f ] of f can be obtained through real vehicle calibration measurement₁，f₂](f₁Obtaining a smaller value of the variation range of the maximum power corresponding to the vibration frequency f through real vehicle calibration; f. of₂Obtaining a larger value of the variation range of the maximum power corresponding to the vibration frequency f through real vehicle calibration, and converting the maximum power corresponding to the vibration frequency f into [ - (f) through an offset zero point₂-f₁)/2，(f₂-f₁)/2]. The vibration frequency change rate deltaf can be obtained by real-vehicle calibration measurement and is recorded as [ -deltaf₀，Δf₀](Δf₀The single-side change range of the frequency change rate delta f corresponding to the maximum vibration power is obtained through real vehicle calibration). The optimal rigidity of the output variable is constantly more than 0, and the variation range is recorded as K₁，K₂](K₁Is the minimum value of active suspension stiffness adjustment; k₂Is the maximum value of active suspension stiffness adjustment) is converted into [ - (K) by offsetting the zero point₂-K₁)/2，(K₂-K₁)/2]。

Converting the actual range of the input variable into corresponding values of the ambiguity domain, and respectively representing the root mean square value of the vertical acceleration and the change rate thereof, and the corresponding values of the ambiguity domain of the maximum power corresponding to the vibration frequency and the change rate thereof as X₁、X₂、X₃、X₄、X₁＝{-x₁，-x₁+1，…0，1，x₁-1，x₁}，X₂＝{-x₂，-x₂+2，…0，1，x₂-1，x₂}，X₃＝{-x₃，-x₃+3，…0，1，x₃-1，x₃}，X₄＝{-x₄，-x₄+4，…0，1，x₄-1，x₄Converting the actual range of the output variable into a corresponding value of a fuzzy domain, and respectively representing the corresponding values of the fuzzy domain of the optimal damping and the optimal rigidity as Y₁、Y₂，Y₁＝{-y₁，-y₁+1，…0，1，y₁-1，y₁}，Y₂＝{-y₂，-y₂+1，…0，1，y₂-1，y₂}。

The quantization factor of the input variable vertical acceleration root mean square value a is:

wherein: k is a radical of_A-a quantization factor of the vertical acceleration root mean square value;

A₁obtaining a smaller value of the variation range of the vertical acceleration root mean square value through real vehicle calibration;

A₂obtaining a larger value of the variation range of the vertical acceleration root mean square value through real vehicle calibration;

x₁ambiguity domain range of the root mean square value of the vertical acceleration in the two-dimensional damping fuzzy control rule, x in the method₁＝6；

The quantization factor of the variation rate of the root mean square value of the vertical acceleration is as follows:

wherein: k is a radical of_ΔA-a quantization factor of the rate of change of the root mean square value;

ΔA₀obtaining a unilateral variation range of the variation rate delta A of the vertical acceleration root mean square value through real vehicle calibration;

x₂-the domain of ambiguity of the rate of change of the root mean square value in the two-dimensional damping fuzzy control rule, in which method x₂＝6。

The output variable, the quantization factor for the optimal damping, is:

wherein: k is a radical of_C-a quantization factor for optimal damping;

C₁-minimum value of active suspension damping adjustment;

C₂-maximum value of active suspension damping adjustment;

y₁ambiguity domain range for optimal damping in two-dimensional damping fuzzy control rule, y in the method₁＝6。

The quantization factor of the maximum power spectrum corresponding to the vibration frequency in the two-dimensional rigidity fuzzy control is as follows:

wherein: k is a radical of_f-the maximum power spectrum corresponds to a quantization factor of the vibration frequency;

f₁obtaining a smaller value of the variation range of the maximum power corresponding to the vibration frequency f through real vehicle calibration;

f₂obtaining a larger value of the variation range of the maximum power corresponding to the vibration frequency f through real vehicle calibration;

x₃-maximum power spectrum pair in two-dimensional stiffness fuzzy control ruleIn response to the domain of ambiguity of the vibration frequency, x in the method₃＝6。

The quantization factor for the rate of change of the vibration frequency is:

wherein: k is a radical of_Δf-a quantization factor of the rate of change of the vibration frequency;

Δf₀obtaining the unilateral change range of the frequency change rate delta f corresponding to the maximum vibration power through real vehicle calibration;

x₄-the domain of ambiguity of the vibration frequency rate of change in the two-dimensional stiffness fuzzy control rule, x in the method₄＝6。

The output variables, i.e. the quantization factors for the optimal stiffness, are:

wherein: k is a radical of_K-a quantization factor of the optimal stiffness;

K₁-minimum value of active suspension stiffness adjustment;

K₂-maximum value of active suspension stiffness adjustment;

y₂ambiguity domain range for optimal stiffness in two-dimensional stiffness ambiguity control rule, y in the method₂＝6。

And carrying out scale transformation on the input and output variables through the quantization factor and the scale factor, and transforming the actual value into a corresponding value on the fuzzy domain.

Dividing the real range of the input and output variables into 7 fuzzy subsets (the product of the actual variation range of the input variable and the quantization factor is recorded as the value of the fuzzy domain, converting the two inputs into the fuzzy subsets after obtaining the value of the fuzzy domain through the input membership function, then obtaining the output fuzzy subsets according to the fuzzy rule, converting the output fuzzy subsets into the fuzzy domain value through the output membership function, and multiplying the fuzzy domain value with the scale factor to obtain the actual value of the output, namely the optimal damping and the optimal rigidity of the embodiment), wherein the 7 fuzzy subsets are respectively expressed as: positive large (PB), Positive Medium (PM) Positive Small (PS), zero (Z), Negative Small (NS), Negative Medium (NM), negative large (NB).

After the fuzzy subset and the fuzzy domain are determined, the fuzzy domain can be converted into the fuzzy subset through the membership function, in the embodiment, the fuzzy controller type selects the Mamdani type, the membership function guassm is adopted to divide the fuzzy subset of the input quantity, the membership function trimf is adopted to divide the fuzzy subset of the output quantity, the input is represented as e and ec, and the output is represented as u.

After the fuzzy subset is obtained, the fuzzy subset of the optimal damping C can be obtained according to the fuzzy subset of the vertical acceleration root mean square value A and the change rate delta A of the vertical acceleration root mean square value A through a two-dimensional damping fuzzy control rule.

The two-dimensional damping fuzzy control rule is shown in table one, and the root mean square value of the vertical acceleration is reduced by increasing the damping of the active suspension.

TABLE 1 two-dimensional damping fuzzy control rule

And obtaining the fuzzy subset of the optimal rigidity K according to the fuzzy subset of the frequency f corresponding to the maximum vibration power and the change rate delta f thereof through a two-dimensional rigidity fuzzy control rule.

The two-dimensional damping fuzzy control rule is shown in the table I, the two-dimensional stiffness fuzzy control rule is established by reducing the root mean square value of the vertical acceleration by increasing the damping of the active suspension, and the maximum vibration power corresponding frequency is far away from the human body resonance frequency interval [ f ] by adjusting the stiffness of the active suspension_min，f_max]As shown in FIG. 2, wherein [ f ]₁，f₂]Is the true range of vibration frequencies.

Table 2 is a two-dimensional stiffness fuzzy control rule, as shown in table 2.

TABLE 2 two-dimensional stiffness fuzzy control rule

After passing through a two-dimensional damping fuzzy controller and a two-dimensional rigidity fuzzy controller, passing through a scale factor k_CObtaining an optimum damping C by a scaling factor k_KThe optimum stiffness K is obtained.

Meanwhile, the vehicle control unit receives a vehicle speed signal sent by the ABS and a longitudinal acceleration signal sent by the acceleration sensor, and obtains a minimum rigidity limit value K according to real vehicle meter calibration data preset by the controller_minAnd minimum damping limit C_min. When the vehicle speed is high (the vehicle speed is acquired through an ABS system, and a specific limit value is acquired through calibration), a high rigidity limit value damping limit value is set to ensure that the vehicle has good stability when running at a high speed. The vehicle control unit calculates the optimal rigidity K and the minimum rigidity limit value K_minComparing, optimal damping C and minimum damping Limit C_minComparing, taking the larger value to obtain the target rigidity K₁And target damping C₁And transmits the rigidity K to an active suspension controller, and the active suspension controller receives the actual rigidity K sent by the active suspension₂And actual damping C₂And the damping and the rigidity of the active suspension are adjusted by utilizing PID closed-loop control, so that the aim of improving the driving comfort is fulfilled.

The technical scheme of the invention is divided into three stages, and the specific strategy is as shown in figure 1, wherein one stage is a signal acquisition stage which mainly acquires vertical acceleration and longitudinal acceleration signals through an acceleration sensor and receives a vehicle speed signal sent by an ABS (anti-lock braking system); the vehicle control unit receives a vertical acceleration time domain signal, performs spectrum analysis, obtains a vertical acceleration root mean square value and a change rate thereof, obtains a vibration frequency corresponding to maximum power spectral density and a change rate thereof through calculation, obtains optimal damping and optimal rigidity through two-dimensional fuzzy control, compares the optimal damping and the optimal rigidity with a minimum rigidity limit value and a minimum damping limit value obtained through vehicle speed and longitudinal acceleration, and obtains a target rigidity and a target damping by taking a larger value; and the three stages are a stage of adjusting the rigidity and the damping of the active suspension, the suspension controller receives the target damping and the target rigidity sent by the whole vehicle controller and the actual rigidity and the actual damping fed back by the active suspension, and the damping and the rigidity of the active suspension are adjusted through PID feedback control.

The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are given by way of illustration of the principles of the present invention, and that various changes and modifications may be made without departing from the spirit and scope of the invention as defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.