阅读说明：本技术 一种运用遗传算法优化的双向dc-dc变换器的控制方法 (Control method of bidirectional DC-DC converter optimized by using genetic algorithm ) 是由 付主木 陶发展 王永强 朱龙龙 司鹏举 高爱云 高晓博 于 2020-03-26 设计创作，主要内容包括：本发明的目的是提供一种运用遗传算法优化的双向DC-DC变换器的控制方法,包括以下步骤：S1,建立buck变换器的自适应观测器,对总干扰建立观测器；S2,针对S1步骤所述的buck变换器建立基于自适应非奇异快速终端滑模控制的有限状态机控制器,并获得基于自适应非奇异快速终端滑模控制的有限状态机控制器收敛条件；S3,对S2步骤所述的自适应快速终端滑膜控制器通过遗传算法进行优化。本发明采用遗传算法对控制策略中的自适应快速终端滑膜控制器进行了参数优化,使得DC-DC变换器对功率控制的效果更好。(The invention aims to provide a control method of a bidirectional DC-DC converter optimized by using a genetic algorithm, which comprises the following steps: s1, establishing a self-adaptive observer of the buck converter, and establishing an observer for the total interference; s2, establishing a finite-state machine controller based on self-adaptive nonsingular fast terminal sliding mode control aiming at the buck converter in the step S1, and obtaining a convergence condition of the finite-state machine controller based on self-adaptive nonsingular fast terminal sliding mode control; and S3, optimizing the adaptive fast terminal synovial membrane controller in the step S2 through a genetic algorithm. The method adopts the genetic algorithm to carry out parameter optimization on the self-adaptive fast terminal sliding film controller in the control strategy, so that the effect of the DC-DC converter on power control is better.)

1. A method for controlling a bidirectional DC-DC converter optimized using a genetic algorithm, comprising the steps of:

s1, establishing a self-adaptive observer of the buck converter, solving the self-adaptive law of the power supply and the load resistance by utilizing the Lyapunov function, and establishing an observer for the total interference;

s2, establishing a finite-state machine controller based on self-adaptive nonsingular fast terminal sliding mode control aiming at the buck converter in the step S1, and obtaining a convergence condition of the finite-state machine controller based on self-adaptive nonsingular fast terminal sliding mode control;

s3, optimizing the adaptive fast terminal synovial controller in the step S2 by a genetic algorithm, wherein an objective function is designed as follows:

f(α，β，θ，D)＝min{∫₀ ^t|V_o-V_o ^{targ et}|dt)；

wherein α is the error amplification factor, β is the amplification factor of the estimator, θ is the sliding mode surface adjustment factor, D is the upper bound of the external disturbance, V_oIs the output voltage.

Then, automatically optimizing the target function within the constraint range of the parameters according to the designed target function;

the method comprises the following specific steps:

s301, initializing parameters, and randomly generating a first generation population Pop;

s302, calculating the fitness of each individual in the population Pop, and initializing an empty population newPop;

s303, selecting 2 individuals from the population Pop according to the fitness by a proportional selection algorithm, performing cross operation and mutation operation on the 2 individuals, and then adding 2 new individuals into the population newPop;

s304, replacing the population Pop in the step S302 with the population newPop in the step S303 until the fitness function of any individual generated by the evolution exceeds Tf, and terminating the evolution process.

2. The method for controlling a bidirectional DC-DC converter optimized using a genetic algorithm according to claim 1, wherein the S1 includes:

s1-1, establishing a differential equation under the controller starting structure according to the selected control variables, wherein the two selected control variables are respectively the inductive currentAnd an output voltageAccording to the structural characteristics of the controller, the input and output differential equations of the controller are converted into Obtaining two variable state observers, determining the self-adaptive rules of the input voltage and the load resistance by using a Lyapunov equation, and finally establishing an integral state observer;

s1-2, establishing a finite time controller based on self-adaptive nonsingular rapid terminal sliding control for the buck converter, carrying out error correction on estimated values and actual values of voltage and current of a circuit to obtain an error of the sliding mode controller, converting the error into a second-order form, and substituting the second-order form into a nonsingular rapid terminal sliding mode formula to obtain the controller.

3. The method for controlling a bidirectional DC-DC converter optimized using a genetic algorithm according to claim 2, wherein the S1-1 includes:

S1-A, obtaining an observer of current and voltage according to a mathematical model of a buck circuit:

to obtain the adaptive rule of input voltage and load conductance, the lyapunov function is derived to obtain the following equation:

order toThe adaptive rule is calculated as:wherein L is inductor, C is capacitor, R is resistor, and V_inIs the input voltage, G is the conductance.

4. The method for controlling a bidirectional DC-DC converter optimized by using genetic algorithm as claimed in claim 2, wherein the non-singular fast terminal sliding mode second order model in S1-2 is:

where C is the output capacitance, G is the load conductance, i_LIs the inductor current, L is the inductance, u is the controller, and d is the external disturbance.

5. The method for controlling a bidirectional DC-DC converter optimized using a genetic algorithm according to claim 1, wherein the S2 includes:

s2-1, setting an initial state, generating errors between actual values and estimated values of current and voltage when a circuit operates, obtaining the reciprocal of input voltage and load resistance conductance according to the errors, obtaining the input voltage and the load resistance conductance value through integration, substituting the input voltage and the load resistance conductance value into an output voltage reciprocal formula and an inductance reciprocal formula to obtain an input-output voltage reciprocal formula and an inductance reciprocal, and obtaining the estimated values of inductance current and output voltage through integration;

s2-2, obtained according to S1 with respect to i_L，V_o，The second-order nonsingular fast terminal sliding mode control surface is obtained through the differential equation, and in order to avoid flutter during switching, an sat function is adopted.

6. The method for controlling a bidirectional DC-DC converter optimized using a genetic algorithm according to claim 5, wherein the S2-1 comprises:

S2-A, the input and output observer differential equation of the buck converter is as follows:

wherein the current state is determined by an energy management strategy, when a positive energy command is received, the bidirectional DC-DC converter is in a boost state, the current is positive, when a negative energy command is received, the bidirectional DC-DC converter is in a buck state, the current is negative, and the energy management strategy is characterized in that the bidirectional DC-DC converter is in a boost state, the current is positive, and when a negative energy command is received, the bidirectional DC-DCThe power conservation formula can judge the inductance reference current under the reference voltage.

7. The method of claim 5, wherein the step s2-2 comprises the steps of:

designing a second-order nonsingular fast terminal sliding mode control method through a difference value of an actual value and an observer estimated value:

wherein z is₁Is the output voltage error value, z₂Is the derivative of the error, theta_zIs the sliding mode adjusting coefficient of the sliding mode,is the slip form adjustment index.

The switching conditions of the sat function are as follows:

；

wherein, V_inIs the input voltage and is a normal number.

Technical Field

The invention belongs to the field of hybrid power supply electric automobiles, and particularly relates to a control method of a bidirectional DC-DC converter optimized by using a genetic algorithm.

Background

The new energy automobile has the advantages of zero emission, no pollution, low noise and the like, and the new energy automobile meets the social requirements at present with higher and higher environmental requirements. Nowadays, in order to increase the range of new energy vehicles, fuel cells are generally selected as their main energy source.

However, when the vehicle is accelerated and started, the fluctuation of the load power is severe, the internal electrochemical structure of the fuel cell is easily impacted, the service life of the fuel cell is shortened, and the fuel cell cannot absorb the braking energy, so that the energy conservation of the new energy automobile is not facilitated. Therefore, the lithium battery and the super capacitor are selected as auxiliary energy sources, additional power is provided when the vehicle is started and accelerated to reduce the impact of load power fluctuation on the fuel battery, and the braking energy is absorbed to improve the fuel economy of the whole vehicle.

However, due to the introduction of lithium batteries and super capacitors, the energy management of the whole vehicle is relatively complex, and the vehicle DC-DC converter as a key component of the energy management has an important role in the dynamic performance and the cruising ability of the vehicle.

In the prior art, for example, chinese patent CN106130125 discloses a fuzzy sliding mode feedback charging controller for an electric vehicle and a feedback charging control method thereof, which adopt fuzzy sliding mode variable structure control, solve the problem of performance degradation of the controller caused by uncertain input voltage and output load change due to uncertainty of vehicle parameters and vehicle speed change and equivalent load resistance change during battery charging in the conventional control method under various driving conditions, have strong robustness, and can recover more braking energy.

It can be seen that the research direction of the existing control method for the DC-DC converter mainly focuses on improving the robustness of the system. The research on the power regulation capability of the energy source for the speed of responding to the power demand of the vehicle is also the research direction in the field of new energy vehicles.

Disclosure of Invention

The invention aims to provide a control method of a bidirectional DC-DC converter optimized by a genetic algorithm, so that the energy conversion quality is better, the efficiency is high, and the advantages of prolonging the service lives of a fuel cell and a lithium battery and enhancing the energy use efficiency are achieved.

In order to achieve the above object, a control method of a bidirectional DC-DC converter optimized using a genetic algorithm includes the steps of:

s1, establishing a self-adaptive observer of the buck converter, solving the self-adaptive law of the power supply and the load resistance by utilizing the Lyapunov function, and establishing an observer for the total interference;

s2, establishing a finite-state machine controller based on self-adaptive nonsingular fast terminal sliding mode control aiming at the buck converter in the step S1, and obtaining a convergence condition of the finite-state machine controller based on self-adaptive nonsingular fast terminal sliding mode control;

s3, optimizing the adaptive fast terminal synovial controller in the step S2 by a genetic algorithm, wherein an objective function is designed as follows:

wherein the meaning of the individual parameters

Then, automatically optimizing the target function within the constraint range of the parameters according to the designed target function;

the method comprises the following specific steps:

s301, initializing parameters, and randomly generating a first generation population Pop;

s302, calculating the fitness of each individual in the population Pop, and initializing an empty population newPop;

s303, selecting 2 individuals from the population Pop according to the fitness by a proportional selection algorithm, performing cross operation and mutation operation on the 2 individuals, and then adding 2 new individuals into the population newPop;

s304, replacing the population Pop in the step S302 with the population newPop in the step S303 until the fitness function of any individual generated by the evolution exceeds Tf, and terminating the evolution process.

The S1 includes:

s1-1, establishing a differential equation under the controller starting structure according to the selected control variables, wherein the two selected control variables are respectively the inductive currentAnd an output voltageAccording to the structural characteristics of the controller, the input and output differential equations of the controller are converted intoObtaining two variable state observers, determining the self-adaptive rules of the input voltage and the load resistance by using a Lyapunov equation, and finally establishing an integral state observer;

s1-2, establishing a finite time controller based on self-adaptive nonsingular rapid terminal sliding control for the buck converter, carrying out error correction on estimated values and actual values of voltage and current of a circuit to obtain an error of the sliding mode controller, converting the error into a second-order form, and substituting the second-order form into a nonsingular rapid terminal sliding mode formula to obtain the controller.

The S1-1 comprises:

S1-A, obtaining an observer of current and voltage according to a mathematical model of a buck circuit:

to obtain the adaptive rule of input voltage and load conductance, the lyapunov function is derived to obtain the following equation:

order toThe adaptive rule is calculated as:wherein L is inductor, C is capacitor, R is resistor, and V_inIs the input voltage, G is the conductance.

The nonsingular fast terminal sliding mode second-order model in the S1-2 is as follows:

where C is the output capacitance, G is the load conductance, i_LIs the inductor current, L is the inductance, u is the controller, and d is the external disturbance.

The S2 includes:

s2-1, setting an initial state, generating errors between actual values and estimated values of current and voltage when a circuit operates, obtaining the reciprocal of input voltage and load resistance conductance according to the errors, obtaining the input voltage and the load resistance conductance value through integration, substituting the input voltage and the load resistance conductance value into an output voltage reciprocal formula and an inductance reciprocal formula to obtain an input-output voltage reciprocal formula and an inductance reciprocal, and obtaining the estimated values of inductance current and output voltage through integration;

s2-2, obtained according to S1 with respect to i_L，V_o，To obtain a second order nonsingular blockAnd a fast terminal sliding mode control surface adopts an sat function in order to avoid chattering during switching.

The S2-1 comprises:

S2-A, the input and output observer differential equation of the buck converter is as follows:

wherein the current state is determined by an energy management strategy, when a positive energy command is received, the bidirectional DC-DC converter is in a boost state, the current is positive, when a negative energy command is received, the bidirectional DC-DC converter is in a buck state, the current is negative, and the energy management strategy is characterized in that the bidirectional DC-DC converter is in a boost state, the current is positive, and when a negative energy command is received, the bidirectional DC-DCThe power conservation formula can judge the inductance reference current under the reference voltage.

The s2-2 comprises the following specific steps:

designing a second-order nonsingular fast terminal sliding mode control method through a difference value of an actual value and an observer estimated value:

wherein, the meaning of the individual parameters;

the switching conditions of the sat function are as follows:

where C is the output capacitance, G is the load conductance, i_LIs the inductor current, L is the inductance, u is the controller, d is the external disturbance, V_inIs the input voltage, is a normal number, α is an error amplification factor, β is the amplification factor of the estimator, theta is the sliding mode surface adjustment factor, D is the upper bound of the external disturbance, V_oIs the output voltage.

Has the advantages that: the invention adopts self-adaptive control and fast terminal sliding mode control to carry out power control on the converter, so that the energy source has quicker response to the power required by the vehicle, more stable power regulation and more reasonable protection to the energy source, and adopts a genetic algorithm to carry out parameter optimization on the self-adaptive fast terminal sliding mode controller in the control strategy, so that the DC-DC converter has better effect on power control.

Drawings

FIG. 1 is a schematic diagram of a DC-DC converter according to the present invention.

FIG. 2 is a flow chart of genetic algorithm optimization.

Detailed Description

The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

Further details of the present invention are provided below in conjunction with the appended drawings.