Ultra-high-speed motor non-inductive enhanced optimal sliding mode control system for air compressor

Abstract

The invention relates to a non-inductive enhanced optimal sliding mode control system of an ultra-high-speed motor for an air compressor. The non-inductive enhanced optimal sliding mode control system comprises an air compressor coupling control model, an enhanced optimal sliding mode rotating speed controller and an improved harmonic suppression sliding mode rotating speed observer, the air compressor coupling control model is used for fitting a curve based on air compressor test data and outputting enhanced optimal performance evaluation index parameters; the enhanced optimal sliding mode rotating speed controller establishes an enhanced optimal sliding mode surface and outputs target quadrature-axis current; the improved harmonic suppression sliding-mode rotating speed observer outputs the angular velocity and angle observation value of the air compressor based on a boundary layer self-adaptive sliding-mode control function and a voltage injection harmonic elimination algorithm, reduces current harmonics and realizes position sensorless control. The method effectively solves the problems that a traditional optimal sliding mode control system is poor in rotating speed control effect and not suitable for actual air compressor operation working conditions, has high working condition adaptability, and achieves rapid and accurate adjustment of the rotating speed of the air compressor under the condition of no position sensor.

Description

Technical Field

[0001] The invention relates to the technical field of air compressor control, and in particular to an ultra-high-speed motor non-sensing enhanced optimal sliding mode control system for an air compressor. Background Art

[0002] Turbine air compressors are widely used in large-flow, high-pressure industrial fields due to their high efficiency, stability, low noise and simple maintenance, especially in the field of hydrogen fuel cell technology. Turbine air compressors accelerate the air through high-speed rotating impellers, convert the kinetic energy of the air into pressure energy, increase the pressure of the air, and achieve the purpose of compressing the air.

[0003] As a key component of the fuel cell system, the turbine air compressor has torque coupling at the compression and expansion ends, pressure coupling, and flow coupling. It is difficult to accurately establish a mathematical model under multi-variable coupling. In addition, the ultra-high-speed motor speed fluctuates and responds late. If the speed cannot be adjusted quickly and accurately, it will directly lead to unstable output flow and pressure of the turbine air compressor, which will in turn affect the power output of the fuel cell. Therefore, it is of great significance to construct a model that can describe the output characteristics of the turbine air compressor and design a control system that is resistant to torque interference and responds quickly for the efficient operation of the turbine air compressor and fuel cell system. Summary of the invention

[0004] The purpose of the present invention is to provide a non-sensing enhanced optimal sliding mode control system for an ultra-high-speed motor for an air compressor. The control system effectively solves the problem that the speed control effect in the traditional optimal sliding mode control system is poor and is not suitable for the actual operating conditions of the air compressor. The control system has high adaptability to working conditions and realizes fast and accurate adjustment of the speed of the air compressor without a position sensor.

[0005] In order to achieve the above-mentioned purpose, the technical scheme adopted by the present invention is: an ultra-high-speed motor sensorless enhanced optimal sliding mode control system for an air compressor, comprising an air compressor coupling control model, an enhanced optimal sliding mode speed controller and an improved harmonic suppression sliding mode speed observer; the air compressor coupling control model outputs enhanced optimal performance evaluation index parameters based on a curve fitted by air compressor test data; the enhanced optimal sliding mode speed controller combines the enhanced optimal performance evaluation index with the extended state space equation to establish an enhanced optimal sliding mode surface and output the target quadrature axis current; the improved harmonic suppression sliding mode speed observer outputs air compressor angular velocity and angle observation values ​​based on a boundary layer adaptive sliding mode control function and a voltage injection harmonic elimination algorithm, reduces current harmonics, and realizes position sensorless control of the air compressor.

[0006] Furthermore, the air compressor coupling control model introduces the target speed signal and the actual speed observation signal into the air compressor compression end fitting physical curve, the expansion end fitting physical curve, and the air compressor efficiency optimal working curve, and monitors the compression end inlet air flow signal, the expansion end inlet air flow signal, the atmospheric temperature signal, and the expansion end inlet gas temperature signal in real time by setting a gas flow sensor at the air compressor compression end outlet, a gas flow sensor at the expansion end inlet, a temperature sensor at the air compressor air inlet position, and a temperature sensor at the expansion end inlet, and finally outputs the enhanced optimal performance evaluation index parameters.

[0007] Furthermore, the implementation method of the air compressor coupling control model includes:

[0008] 1) The Jensen&Kristensen modeling method is adopted to fit the flow rate, pressure ratio, speed, and power consumption curves of the compression end and the expansion end based on the optimal efficiency based on the actual test data of the turbine air compressor. By receiving the target speed signal or the vehicle speed signal and combining the sampling signal of the gas flow sensor at the inlet of the compression end, the sampling signal of the gas flow sensor at the inlet of the expansion end, the sampling signal of the gas temperature sensor near the inlet of the compression end, and the sampling signal of the gas temperature sensor at the inlet of the expansion end, the control-oriented air compressor parameters are output;

[0009] 2) Calculate the motor drive torque index parameter λ of the air compressor enhanced optimal performance evaluation index according to the following equation: Te :

[0010]

[0011] Where P n is the number of pole pairs of the air compressor motor, Air compressor motor flux, J cp is the air compressor rotation inertia;

[0012] 3) Calculate the compression torque index parameter λ of the air compressor enhanced optimal performance evaluation index according to the following equation: cp :

[0013]

[0014] Where W cp is the gas mass flow rate at the compression end outlet, T atm is the atmospheric temperature, c c is the constant pressure specific heat capacity of the gas at the compression end, P rr is the target compression ratio at the compression end, ρ c is the specific heat ratio of the gas at the compression end, η cp is the compression end efficiency;

[0015] 4) Calculate the expansion torque index parameter λ of the air compressor enhanced optimal performance evaluation index according to the following equation: ep :

[0016]

[0017] Where W ep is the gas mass flow rate at the expansion end inlet, T tep is the gas temperature at the expansion end inlet, c e is the constant pressure specific heat capacity of the gas at the expansion end, η ep is the expansion end efficiency, P er is the target expansion ratio at the expansion end, ρ e is the specific heat ratio of the gas at the expansion end.

[0018] Furthermore, the enhanced optimal sliding mode speed controller receives the speed observation signal of the improved harmonic suppression sliding mode speed observer, extracts the system matrix and the control matrix according to the air compressor speed torque state space equation, and establishes the extended state space equation; based on the speed sample data of the traditional sliding mode control and the subjective and objective entropy weight analysis data, combined with the compression end compression torque index parameter and the expansion end expansion torque index parameter, an enhanced optimal performance evaluation index is established; combined with the extended state space equation and the strong performance evaluation index, enhanced control information is coupled, and finally an enhanced optimal sliding mode surface is established, which receives the target speed information and outputs the target quadrature axis current value; the target current is applied to the PI controller of the current loop, combined with the harmonic voltage injection signal of the improved harmonic suppression sliding mode speed observer, and then combined with the space vector pulse width modulation, a switching pulse signal is output to the inverter to generate AC current and drive the motor to rotate.

[0019] Furthermore, the implementation method of the enhanced optimal sliding mode speed controller includes:

[0020] 1) Input the control quantity as the state quantity and establish the extended state equation according to the following equation:

[0021]

[0022] Where, X ω is the extended state vector, A ω To expand the system matrix, B ω is the expanded input matrix, U ω is the extended control input vector, U is the control input vector, μ1 is a parameter greater than 0, and μ2 is a parameter greater than 0;

[0023] 2) Construct the extended state space matrix according to the following equation:

[0024]

[0025] Where X is the state vector, A is the system matrix, B is the input matrix, and I is the identity matrix;

[0026] 3) Establish the enhanced optimal performance evaluation index G according to the following equation:

[0027]

[0028] Where γ1 is the weighted coefficient obtained by analyzing the data based on the subjective and objective entropy weights, γ2 is the weighted coefficient obtained by analyzing the data based on the subjective and objective entropy weights, and ω ref is the target mechanical angular velocity, x 10 is the linearized working point matrix element at the current moment;

[0029] 4) Based on the enhanced optimal performance evaluation index and the extended state space equation, the enhanced control information is obtained, and the solution of the Riccati equation of the control information is obtained according to the following equation:

[0030]

[0031] Where M is the solution of the Riccati equation;

[0032] 5) Establish the enhanced optimal sliding surface S(X) according to the following equation ω ):

[0033]

[0034] Furthermore, the improved harmonic suppression sliding mode speed observer receives the Alpha and Beta axis voltage signals in the stationary coordinate system, observes the motor back electromotive force in the stationary coordinate system based on the improved sliding mode control function, outputs the air compressor angle and angular velocity observation values, and adds the angle observation values ​​to the harmonic extraction equation to extract the harmonic components of the motor current at the current moment, and uses the PI control algorithm to output the harmonic compensation voltage, thereby reducing the harmonics of the current while realizing the sensorless control of the air compressor and improving the accuracy of the sensorless control.

[0035] Furthermore, the implementation method of the improved harmonic suppression sliding mode speed observer includes:

[0036] 1) Establish the speed observation sliding mode function Z according to the following equation: α , Z β :

[0037]

[0038] In the formula, s α is the sliding surface of the Alpha axis observation error, s β is the Beta axis observation error sliding surface, M α is the adaptive saturation function of the boundary layer on the Alpha axis, M βis the Beta axis boundary layer adaptive saturation function, R α is the adaptive reaching law of the boundary layer on the Alpha axis, R β It is the adaptive reaching law of the Beta axis boundary layer;

[0039] 2) Define the boundary layer adaptive saturation function M according to the following equation:

[0040]

[0041] Where s is the observation error sliding surface, β is a parameter greater than 0, and r is the sliding mode observation error;

[0042] 3) Define the boundary layer adaptive reaching law R according to the following equation:

[0043]

[0044] In the formula, ε is a parameter greater than 0, η is a parameter greater than 0, and λ is a parameter greater than 0;

[0045] 4) Substitute the observed value of the motor back electromotive force into the inverse tangent function to obtain the observed value of the motor angle position; based on the observed value of the motor angle position, extract the harmonic component of the motor current, introduce it into the harmonic elimination PI algorithm, output the harmonic current compensation voltage value, superimpose it with the target voltage output by the current loop PI control algorithm, and output it to SVPWM together to generate a switching pulse signal.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] The ultra-high-speed motor non-sensing enhanced optimal sliding mode control system for an air compressor provided by the present invention adopts an air compressor coupling control model, establishes a control-oriented electromechanical coupling model of a turbine air compressor that couples the static characteristics of the compression end and the expansion end and the dynamic characteristics of the motor, provides a physical explanation of the system behavior, and has a certain degree of versatility; takes into account the influence of load torque, gives full play to the advantage that the flow rate of the air compressor can be measured more conveniently by a sensor, takes the flow rate as a constant and updates it in real time, and converts the efficiency according to the inlet and outlet temperatures, so as to achieve good dynamic and steady-state performance of the air compressor under any complex working conditions.

[0048] The ultra-high-speed motor sensorless enhanced optimal sliding mode control system for an air compressor provided by the present invention adopts an enhanced optimal sliding mode speed controller, combines the state vector and the control vector of the original state equation, constructs a new state vector, establishes an extended state equation, takes a new system state into consideration, and ensures that the control system has a better control effect; an enhanced performance evaluation index is established, starting from the actual working conditions, based on the subjective and objective entropy weight analysis method, covering the impact of the controller's performance on the output of the turbine air compressor, and also includes the performance requirements of the turbine air compressor speed control, so as to evaluate the performance of the controller, and achieve good dynamic and steady-state performance under any complex working conditions.

[0049] The ultra-high-speed motor non-sensing enhanced optimal sliding mode control system for an air compressor provided by the present invention adopts an improved harmonic suppression sliding mode speed observer, based on a boundary layer adaptive saturation function to ensure that the boundary layer thickness will not increase infinitely, so that the system can smoothly converge to a switching plane; based on the boundary layer adaptive convergence law, when the error approaches the sliding mode surface, the approach speed is automatically adjusted, and when the error is far away from the sliding mode surface, the approach rate also increases accordingly, but not too large, and when the observed error approaches 0, the boundary layer and the approach rate both adaptively approach 0, thereby accelerating the stability of the system; a PI harmonic voltage injection method based on current harmonic extraction is adopted to reduce the harmonic component of the motor current and improve the observation accuracy of the speed; the system jitter caused by the speed observation is reduced, the cost of the position sensor is saved, and the overall volume of the air compressor is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of a non-sensing enhanced optimal sliding mode control system for an ultra-high-speed motor for an air compressor according to an embodiment of the present invention.

[0051] Figure 2 Schematic diagram of the air compressor coupling control model in an embodiment of the present invention.

[0052] Figure 3 Schematic diagram of an enhanced optimal sliding mode speed controller in an embodiment of the present invention.

[0053] Figure 4 Schematic diagram of an improved harmonic suppression sliding mode speed observer in an embodiment of the present invention.

[0054] Figure 5 It is a comparison diagram of the control effects of the traditional optimal sliding mode and the present invention in the case of a step target speed signal in an embodiment of the present invention.

[0055] Figure 6 It is a comparison diagram of the control effects of the traditional optimal sliding mode and the present invention for a step target speed signal in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0057] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0058] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0059] like Figure 1 As shown, this embodiment provides an enhanced optimal sliding mode control system for an ultra-high-speed motor for an air compressor, including an air compressor coupling control model, an enhanced optimal sliding mode speed controller and an improved harmonic suppression sliding mode speed observer; the air compressor coupling control model outputs enhanced optimal performance evaluation index parameters based on a curve fitted by air compressor test data; the enhanced optimal sliding mode speed controller combines the enhanced optimal performance evaluation index with the extended state space equation to establish an enhanced optimal sliding mode surface, and outputs the target quadrature axis current; the improved harmonic suppression sliding mode speed observer outputs air compressor angular velocity and angle observation values ​​based on a boundary layer adaptive sliding mode control function and a voltage injection harmonic elimination algorithm, reduces current harmonics, and realizes position sensorless control of the air compressor.

[0060] like Figure 2 As shown, the air compressor coupling control model introduces the target speed signal and the actual speed observation signal into the air compressor compression end fitting physical curve, the expansion end fitting physical curve, and the air compressor efficiency optimal working curve, and sets a gas flow sensor at the air compressor compression end outlet, a gas flow sensor at the expansion end inlet, a temperature sensor at the air compressor air inlet, and a temperature sensor at the expansion end inlet to monitor the compression end inlet air flow signal, the expansion end inlet air flow signal, the atmospheric temperature signal, and the expansion end inlet gas temperature signal in real time, and finally outputs the enhanced optimal performance evaluation index parameters.

[0061] Specifically, the implementation method of the air compressor coupling control model includes:

[0062] 1) The Jensen&Kristensen modeling method is adopted to fit the flow, pressure ratio, speed and power consumption curves of the compression end and the expansion end based on the actual test data of the turbine air compressor. The control-oriented air compressor parameters are output by receiving the target speed signal or the vehicle speed signal and combining the sampling signal of the gas flow sensor at the inlet of the compression end, the sampling signal of the gas flow sensor at the inlet of the expansion end, the sampling signal of the gas temperature sensor near the inlet of the compression end, and the sampling signal of the gas temperature sensor at the inlet of the expansion end.

[0063] The model is derived from basic physical and thermodynamic principles. It is a semi-mechanistic and semi-empirical model that can be used to describe the relationship between air compressor flow, pressure ratio and speed. Using this method, a physical explanation of the system behavior can be provided with a certain degree of versatility.

[0064] 2) Calculate the motor drive torque index parameter λ of the air compressor enhanced optimal performance evaluation index according to the following equation: Te :

[0065]

[0066] Where P n is the number of pole pairs of the air compressor motor, Air compressor motor flux, J cp is the air compressor rotation inertia.

[0067] 3) Calculate the compression torque index parameter λ of the air compressor enhanced optimal performance evaluation index according to the following equation: cp :

[0068]

[0069] Where W cp is the gas mass flow rate at the compression end outlet, T atm is the atmospheric temperature, c c is the constant pressure specific heat capacity of the gas at the compression end, P rr is the target compression ratio at the compression end, ρ c is the specific heat ratio of the gas at the compression end, η cp is the compression end efficiency.

[0070] 4) Calculate the expansion torque index parameter λ of the air compressor enhanced optimal performance evaluation index according to the following equation: ep :

[0071]

[0072] Where W ep is the gas mass flow rate at the expansion end inlet, T tep is the gas temperature at the expansion end inlet, ce is the constant pressure specific heat capacity of the gas at the expansion end, η ep is the expansion end efficiency, P er is the target expansion ratio at the expansion end, ρ e is the specific heat ratio of the gas at the expansion end.

[0073] The design of general sliding mode controller usually ignores the influence of load torque. However, in the dynamic operation of turbine air compressor, since the compression torque and expansion torque will change with the speed, the assumption that they are constant over time is not applicable. Since the flow and pressure of the air compressor can be measured more conveniently through sensors, the flow and pressure ratio are taken as constants and updated in real time, and the efficiency is converted according to the inlet and outlet temperatures. Therefore, the index parameters shown above are proposed to lay the foundation for achieving good dynamic and steady-state performance of the air compressor under any complex working conditions.

[0074] like Figure 3 As shown, the enhanced optimal sliding mode speed controller receives the speed observation signal of the improved harmonic suppression sliding mode speed observer, extracts the system matrix and the control matrix according to the air compressor speed torque state space equation, and establishes the extended state space equation; according to the speed sample data of the traditional sliding mode control and the subjective and objective entropy weight analysis data, combined with the compression end compression torque index parameter and the expansion end expansion torque index parameter, an enhanced optimal performance evaluation index is established; combined with the extended state space equation and the strong performance evaluation index, the enhanced control information is coupled, and finally the enhanced optimal sliding mode surface is established, the target speed information is received, and the target quadrature axis current value is output; the target current is applied to the PI controller of the current loop, combined with the harmonic voltage injection signal of the improved harmonic suppression sliding mode speed observer, and then combined with the space vector pulse width modulation, the switch pulse signal is output to the inverter to generate AC current and drive the motor to rotate.

[0075] Specifically, the implementation method of the enhanced optimal sliding mode speed controller includes:

[0076] 1) Input the control quantity as the state quantity and establish the extended state equation according to the following equation:

[0077]

[0078] Where, X ω is the extended state vector, A ω To expand the system matrix, B ω is the expanded input matrix, U ω is the expanded control input vector, U is the control input vector, μ1 is a parameter greater than 0, and μ2 is a parameter greater than 0.

[0079] 2) Construct the extended state space matrix according to the following equation:

[0080]

[0081] Where X is the state vector, A is the system matrix, B is the input matrix, and I is the identity matrix.

[0082] By merging the state vector and control vector of the original state equation, a new state vector is constructed, an extended state equation is established, and a new system state is taken into consideration to ensure that the control system has a better control effect.

[0083] 3) Establish the enhanced optimal performance evaluation index G according to the following equation:

[0084]

[0085] Where γ1 is the weighted coefficient obtained by analyzing the data based on the subjective and objective entropy weights, γ2 is the weighted coefficient obtained by analyzing the data based on the subjective and objective entropy weights, and ω ref is the target mechanical angular velocity, x 10 It is the linearization working point matrix element at the current moment.

[0086] This enhanced optimal performance evaluation index starts from the actual operating conditions and is based on the subjective and objective entropy weight analysis method. It covers the impact of the controller's performance on the turbine air compressor output, and also includes the performance requirements of the turbine air compressor speed control. It is used to evaluate the performance of the controller and is a key step in achieving good dynamic and steady-state performance under complex operating conditions.

[0087] 4) Based on the enhanced optimal performance evaluation index and the extended state space equation, the enhanced control information is obtained, and the solution of the Riccati equation of the control information is obtained according to the following equation:

[0088]

[0089] Where M is the solution of the Riccati equation.

[0090] 5) Establish the enhanced optimal sliding surface S(X) according to the following equation ω ):

[0091]

[0092] like Figure 4As shown, the improved harmonic suppression sliding mode speed observer receives the Alpha and Beta axis voltage signals in the stationary coordinate system, observes the motor back electromotive force in the stationary coordinate system based on the improved sliding mode control function, outputs the air compressor angle and angular velocity observation values, and adds the angle observation values ​​to the harmonic extraction equation to extract the harmonic component of the motor current at the current moment, and uses the PI control algorithm to output the harmonic compensation voltage, thereby reducing the current harmonics while realizing the sensorless control of the air compressor and improving the accuracy of the sensorless control.

[0093] Specifically, the implementation method of the improved harmonic suppression sliding mode speed observer includes:

[0094] 1) Establish the speed observation sliding mode function Z according to the following equation: α , Z β :

[0095]

[0096] In the formula, s α is the sliding surface of the Alpha axis observation error, s β is the Beta axis observation error sliding surface, M α is the adaptive saturation function of the boundary layer on the Alpha axis, M β is the Beta axis boundary layer adaptive saturation function, R α is the adaptive reaching law of the boundary layer on the Alpha axis, R β is the adaptive reaching law of the Beta axis boundary layer.

[0097] 2) Define the boundary layer adaptive saturation function M according to the following equation:

[0098]

[0099] Where s is the observation error sliding surface, β is a parameter greater than 0, and r is the sliding mode observation error.

[0100] The boundary layer adaptive saturation function uses the inverse tangent function to ensure that the boundary layer thickness will not increase infinitely. When the sliding mode observation error approaches 0, the boundary layer also approaches 0, allowing the system to converge smoothly to the switching plane.

[0101] 3) Define the boundary layer adaptive reaching law R according to the following equation:

[0102]

[0103] Where ε is a parameter greater than 0, η is a parameter greater than 0, and λ is a parameter greater than 0.

[0104] The boundary layer adaptive approaching law automatically adjusts the approaching speed when the error approaches the sliding surface; when the error moves away from the sliding surface, the approaching rate also increases, but not too large; when the observed error approaches 0, the boundary layer and the approaching rate both adaptively approach 0, accelerating the stability of the system and reducing the system chattering caused by speed observation.

[0105] 4) Substitute the observed value of the motor back electromotive force into the inverse tangent function to obtain the observed value of the motor angle position; based on the observed value of the motor angle position, extract the harmonic component of the motor current, introduce it into the harmonic elimination PI algorithm, output the harmonic current compensation voltage value, superimpose it with the target voltage output by the current loop PI control algorithm, and output it to SVPWM together to generate a switching pulse signal.

[0106] The implementation process of each part of the sensorless enhanced optimal sliding mode control system for the ultra-high-speed motor for the air compressor of this embodiment is further described in detail below.

[0107] like Figure 2 As shown, the working principle and design method of the air compressor coupling control model are as follows:

[0108] 1) Based on the actual experimental data of the turbine air compressor, the compression end Mach number M is converted according to the following equation: a :

[0109]

[0110] Where U c is the linear velocity of the impeller tip at the pressure end, d c is the impeller diameter, N is the impeller speed, ρ c is the specific heat ratio of the gas at the compression end, R a Air gas constant, T atm is the atmospheric temperature.

[0111] 2) Based on the actual experimental data of the turbine air compressor, the compression end flow rate is converted according to the following equation:

[0112]

[0113] Where W cp is the air mass flow rate at the pressure end outlet, and ρ is the air density.

[0114] 3) Calculate the dimensionless parameter Ψ at the compression end according to the following equation:

[0115]

[0116] Where P r is the pressure ratio, c c is the specific heat of air at constant pressure.

[0117] 4) Fit the actual experimental data of the compression end according to the following equation:

[0118]

[0119] In the formula, a4, a3, a2, a1, a0, b2, b1, b0, c5, c4, c3, c2, c1, and c0 are fitting coefficients to be determined.

[0120] 5) According to the fitting curve results of the compression end, with the optimal efficiency as the primary condition, the highest efficiency working line is extracted from the fitting curve, which is used as the output reference for the target flow rate and target pressure ratio of the compression end, so as to realize the transition from the target speed signal to the target flow rate, target pressure ratio and compression efficiency signal.

[0121] 6) Based on the actual experimental data of the turbine air compressor, the expansion end Mach number Ma is converted according to the following equation: e :

[0122]

[0123] Where U e is the linear velocity of the turbine blade tip at the vortex end, d e is the turbine diameter, ρ e is the specific heat ratio of the gas at the expansion end.

[0124] 7) Based on the actual experimental data of the turbine air compressor, the expansion end flow rate is converted according to the following equation:

[0125]

[0126] Where W ep is the air intake mass flow rate at the expansion end.

[0127] 8) According to the following equation, the dimensionless parameter Ψ of the expansion end is calculated e Conversion:

[0128]

[0129] Where P ep is the expansion ratio, c e is the constant pressure specific heat capacity of the expansion end, T ep is the gas temperature at the expansion end inlet.

[0130] 9) According to the following equation, fit the actual machine experimental data of the expansion end

[0131]

[0132] In the formula, k i =k i1 +k i2 Mae +k i3 Ma e 2 , i=1~5 are all fitting coefficients to be determined.

[0133] 10) According to the fitting curve result of the expansion end, taking the optimal efficiency as the primary condition, the highest efficiency working line is extracted from the fitting curve, which is used as the target flow rate and target expansion ratio output of the expansion end as the benchmark to realize the transition from the target speed signal to the target flow rate, target expansion ratio and expansion efficiency signal.

[0134] 11) According to the following equation, define the air compressor enhanced optimal performance evaluation index motor drive torque index parameter λ Te :

[0135]

[0136] Where P n is the number of pole pairs of the air compressor motor, Air compressor motor flux, J cp is the air compressor rotation inertia.

[0137] 12) According to the following equation, define the compression torque index parameter λ of the air compressor enhanced optimal performance evaluation index: cp :

[0138]

[0139] Where P rr is the target compression ratio at the compression end, η cp is the compression end efficiency.

[0140] 13) According to the following equation, define the expansion end expansion torque index parameter λ of the air compressor enhanced optimal performance evaluation value index ep :

[0141]

[0142] Where η ep is the expansion end efficiency, T tep is the gas temperature at the expansion end inlet, P er is the target expansion ratio of the expansion end.

[0143] like Figure 3 As shown in the figure, the working principle and design method of the enhanced optimal sliding mode speed controller are as follows:

[0144] 1) According to the relationship between the electromagnetic drive torque of the motor, the compression load torque at the pressure end, and the expansion torque at the turbine end, the torque balance equation of the turbine air compressor is constructed:

[0145]

[0146] In the formula, ω m is the angular velocity of the air compressor, T e is the electromagnetic torque of the motor.

[0147] 2) Define the state quantities x1 and x2 of the turbine air compressor according to the following equation:

[0148]

[0149] In the formula, ω ref is the target angular velocity of the air compressor and u is the control input of the system.

[0150] 3) Using Taylor expansion at the equilibrium point of the system, the original nonlinear system is replaced by Taylor series, and the high-order terms are ignored to obtain an approximate linearized system:

[0151]

[0152] make f=[f 1 ,f 2 ] T , then the linear state equation can be expressed as:

[0153]

[0154] Where X0 and U0 are the linearized working points at the current moment.

[0155] 4) Define the extended state space equation as follows:

[0156]

[0157] Where, X ω is the extended state vector, A ω is the extended system matrix, B ω is the extended input matrix, U ω is the extended control input vector, U is the control input vector, μ1 is a parameter greater than 0, and μ2 is a parameter greater than 0.

[0158] 5) Construct the extended state space matrix according to the following equation:

[0159]

[0160] Where X is the state vector, A is the system matrix, B is the input matrix, and I is the identity matrix.

[0161]

[0162] 6) According to the following equation, construct the subjective weighted judgment matrix H of turbine air compressor performance evaluation index:

[0163]

[0164] 7) After performing consistency analysis on H to ensure that the matrix logic is correct, normalization is performed and the weight of each indicator is:

[0165] q j =[0.73 0.19 0.08]

[0166] In the formula, j is the index number.

[0167] 8) Based on the traditional sliding mode control sample data, the entropy weight method is combined to assign weights to obtain the sample data indicator matrix, and the matrix is ​​standardized to obtain the weight matrix; then the entropy value of each indicator is calculated, and the weight of each indicator is derived according to the following equation:

[0168] w j =[0.29 0.47 0.24]

[0169] 9) Calculate the combined weight γ according to the following equation: j :

[0170]

[0171] 10) Order The combined weight It can be obtained that the subjective weighted proportional coefficients of x1 and x2 are γ x1 =3.2 and γ x2 =2.1.

[0172] 11) Calculate the weighting coefficients γ1 and γ2 of x1 and x2 according to the following equation:

[0173]

[0174] Where β1 and β2 are parameters greater than 0.

[0175] 12) According to the following equation, establish the general performance evaluation index:

[0176]

[0177] 13) Based on the common performance evaluation index, the extended system state space equation is introduced, and the enhanced optimal performance evaluation index is established according to the following equation:

[0178]

[0179] 14) Based on the enhanced optimal performance evaluation index and the extended state space equation, the enhanced control information is obtained, and the solution M of the Riccati equation of the control information is obtained according to the following equation:

[0180]

[0181] 16) According to the following equation, the enhanced optimal sliding surface S(X ω ):

[0182]

[0183] 17) Select the constant velocity approach rate according to the following equation:

[0184]

[0185] In the formula, ε is a parameter greater than 0.

[0186] 18) According to the following equation, the sliding mode control rate is designed as:

[0187]

[0188] like Figure 4 As shown in the figure, the working principle and design method of the improved harmonic suppression sliding mode speed observer are as follows:

[0189] 1) According to the following equation, the two-phase current state variable equation of the sliding mode observer based on back EMF is constructed:

[0190]

[0191] In the formula, i α 、i β is the current value of the current sensor in the two-phase stationary coordinate system, R s is the motor line resistance, L s is the motor line inductance, u α 、u β is the voltage value of the voltage sensor in the two-phase stationary coordinate system, e α 、e β is the extended back EMF in the two-phase stationary coordinate system.

[0192] 2) Construct a sliding mode observer according to the following equation:

[0193]

[0194] In the formula, “^” represents observation, Z α , Z β is the speed observation sliding mode function.

[0195] 3) Define the sliding mode observation error r according to the following equation: α 、rβ :

[0196]

[0197] 4) Define the sliding surface s of the sliding mode observation error according to the following equation: α 、s β :

[0198]

[0199] In the formula, c smo A parameter greater than 0.

[0200] 5) Define the speed observation sliding mode function Z according to the following equation: α , Z β :

[0201]

[0202] Where M α is the adaptive saturation function of the boundary layer on the Alpha axis, M β is the Beta axis boundary layer adaptive saturation function, R α is the adaptive reaching law of the boundary layer on the Alpha axis, R β is the adaptive reaching law of the Beta axis boundary layer.

[0203] 6) Define the boundary layer adaptive saturation function M according to the following equation:

[0204]

[0205] Where s is the observation error sliding surface, β is a parameter greater than 0, and r is the sliding mode observation error.

[0206] 7) Define the boundary layer adaptive reaching law R according to the following equation:

[0207]

[0208] Wherein, ε is a parameter greater than 0, η is a parameter greater than 0, and λ is a parameter greater than 0.

[0209] 8) According to the following equation, the speed observation sliding mode function Z is equivalent to the extended back electromotive force e:

[0210]

[0211] 9) Output the extended back EMF observation value according to the following equation:

[0212]

[0213] 10) Input the observed values ​​of the air compressor motor angle and the air compressor motor angular velocity according to the following equations:

[0214]

[0215] 11) According to the following equation, extract the fundamental current i in the natural coordinate system af 、i bf 、i cf :

[0216]

[0217] In the formula, θ e is the motor electrical angle, i dr is the direct axis target current value, i qr is the quadrature-axis target current value.

[0218] 12) Calculate the harmonic current i in the natural coordinate system according to the following equation: ax 、i bx 、i cx :

[0219]

[0220] 13) Calculate the orthogonal axis harmonic current in the 5th and 7th rotation coordinate systems according to the following equations:

[0221]

[0222] In the formula, i d5 is the harmonic current in the fifth-order rotating coordinate, i q5 is the quadrature axis current in the 5-fold rotation coordinate system, i d7 is the direct axis current in the 7th optional coordinate system, i q7 is the quadrature axis current in the 7-fold rotation coordinate system.

[0223] 14) After passing through the low-pass filter, the corresponding filtered 5th and 7th harmonic currents i are obtained. d55 、i q55 、i d77 、i q77 .

[0224] 15) Define the 5th and 7th harmonic current target values ​​i according to the following equations: d5r 、i q5r 、i d7r 、i q7r :

[0225]

[0226] 16) Define the 5th and 7th harmonic current errors e according to the following equations: d5、e q5 、e d7 、e q7 :

[0227]

[0228] 17) Define the harmonic elimination compensation voltage U in the fifth-order rotating coordinate system according to the following equation: d5 , U q5 :

[0229]

[0230] In the formula, e d5PI To d5 The output signal after connecting to the PI controller, e q5PI To q5 The output signal after connecting to the PI controller, L d is the direct-axis inductance, L q is the quadrature-axis inductance.

[0231] 18) Define the harmonic elimination compensation voltage U in the 7th-order rotating coordinate system according to the following equation: d7 , U q7 :

[0232]

[0233] 19) Define the harmonic elimination compensation voltage U in the rotating coordinate system according to the following equation: dc , U qc , and superimposed and input into the SVPWM algorithm to achieve the reduction of motor voltage and current harmonics.

[0234]

[0235] in:

[0236]

[0237] Preferably, the ultra-high-speed motor non-inductive enhanced optimal sliding mode control system for the air compressor of this embodiment adopts wide bandgap semiconductor devices represented by silicon carbide (SiC) devices, which have the advantages of low switching loss, fast switching speed, and high device voltage resistance; silicon carbide driven optocouplers are adopted, which have the advantages of high withstand voltage, high power density, and low conduction loss; automotive-grade digital signal processor (DSP) chips are adopted, which have the advantages of strong vibration and impact resistance, high computing power, and compact design.

[0238] Preferably, the ultra-high-speed motor non-inductive enhanced optimal sliding mode control system for the air compressor of this embodiment adopts a power supply circuit design with capacitor filtering at the main power input position, and designs an anti-reverse connection scheme, which has the advantages of smooth voltage waveform, stronger power input protection, and improved system safety; a design scheme of connecting the CAN output end to the host computer is adopted to realize real-time control of the motor and real-time observation of the motor parameters and the motor operating status; a non-isolated PT100 acquisition circuit is adopted, and the power supply signal is protected by a diode anti-reverse connection and filtered by a bypass capacitor, and then input to the inverting input end through a resistor divider, and finally input to the DSP for signal processing after resistor-capacitor filtering.

[0239] Preferably, the ultra-high-speed motor non-inductive enhanced optimal sliding mode control system for the air compressor of this embodiment adopts an ultrasonic gas flow sensor, which calculates the flow rate by measuring the propagation time difference of the gas through the pipeline, and has the advantages of high measurement accuracy and a wide measuring range; a semiconductor temperature sensor is used to measure the temperature through the property that the resistance of the metal changes with the temperature, and has the advantages of high temperature measurement accuracy, fast response speed and small size.

[0240] Preferably, the ultra-high-speed motor non-sensing enhanced optimal sliding mode control system for the air compressor of this embodiment adopts Honeywell 133Series voltage and current sensors, which are suitable for real-time monitoring of high-voltage and high-power motor systems and meet the actual working conditions of the air compressor.

[0241] Preferably, for the air compressor ultra-high-speed motor with enhanced sensorless type of this embodiment, the motor control integrator is required to adopt a DSP multi-core processor with 1MB program memory, 128KB data memory, 6KB stack memory, 150MHz main frequency, 16-bit bit width, and support for single-precision floating-point operations; a high-precision ADC with 16-bit resolution, 200kHz sampling rate, and 50kHz signal bandwidth; a MOSFET power device with a switching frequency of 50kHz, a power voltage of 500V, and SiC material; a filter and a protection circuit are used to reduce the influence of noise and vibration; the EtherCAT communication protocol is used, and the transmission rate is required to be up to 50Mbps; current and voltage sensors with a frequency of more than 50kHz are used to provide a solid hardware foundation for the present invention and ensure that the system can operate efficiently, stably and safely.

[0242] In this embodiment, a turbine air compressor operating condition simulation with a step signal of a simulation time of 3s and a target speed of 70000rpm is carried out. The absolute value of the speed error is less than 200rpm and no longer exceeds 200rpm over time, which is defined as the system entering a stable state. The maximum speed overshoot, stabilization time data and their analysis after the system stabilizes are shown in Figure 2. Figure 5, as shown in Table 1. Compared with the traditional optimal sliding mode control algorithm, the ultra-high-speed motor non-sensing enhanced optimal sliding mode control system for air compressor provided by the present invention has a year-on-year reduction of 46.16% in stabilization time and a reduction of 95.18% in maximum overshoot; when responding to a step speed signal, the present invention not only reduces the stabilization time but also reduces the maximum overshoot, reflecting good adaptability to working conditions.

[0243] Table 1 Data table of turbine air compressor simulation results based on step target speed signal

[0244]

[0245] In this embodiment, the simulation time is 3s; the target speed starts from 0.6s, increases by 10,000rpm every 0.3s from 30,000rpm, and then decreases by 10,000rpm every 0.3s to 70,000rpm. Figure 6 Compared with the traditional optimal sliding mode control, the ultra-high-speed motor sensorless enhanced optimal sliding mode control system for air compressors provided by the present invention is superior to the traditional optimal sliding mode control in terms of both stabilization time and overshoot in the face of the step target speed signal of the typical working condition of the air compressor, reflecting excellent speed control performance.

[0246] Compared with the traditional optimal sliding mode speed control system, the ultra-high-speed motor non-sensing enhanced optimal sliding mode control system for air compressor provided by the present invention adopts the coupling control of air compressor coupling control model, enhanced optimal sliding mode speed controller and improved harmonic suppression sliding mode speed observer. By taking advantage of the measurable air flow and temperature at the compression end and expansion end of the turbine air compressor, a gas flow sensor at the outlet of the compression end of the air compressor, a flow signal of the gas flow sensor at the inlet of the expansion end, a temperature sensor at the air inlet of the air compressor and a temperature sensor at the inlet of the expansion end are arranged to monitor the air flow signal at the compression end inlet in real time. The signal, expansion end inlet air flow signal, atmospheric temperature signal, expansion end inlet gas temperature signal are used to establish an enhanced optimal performance evaluation index; the control quantity is input into the state space equation as a state quantity to establish an extended state space equation; the enhanced optimal performance evaluation index is combined with the extended state space equation to construct an enhanced optimal sliding surface; the harmonic voltage compensation signal input value SVPWM of the improved harmonic suppression sliding mode speed observer can reduce the current harmonic component and improve the speed observation accuracy; at the same time, the speed observation signal is input into the enhanced optimal sliding surface, and finally the speed of the air compressor can be quickly and accurately adjusted without a position sensor.

[0247] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0248] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0249] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0250] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0251] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any technician familiar with the profession may use the above disclosed technical content to change or modify it into an equivalent embodiment with equivalent changes. However, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention still belongs to the protection scope of the technical solution of the present invention.

Claims

1. An ultra-high-speed motor non-sensing enhanced optimal sliding mode control system for an air compressor, characterized in that: It includes an air compressor coupling control model, an enhanced optimal sliding mode speed controller and an improved harmonic suppression sliding mode speed observer; the air compressor coupling control model outputs enhanced optimal performance evaluation index parameters based on a curve fitted by air compressor test data; the enhanced optimal sliding mode speed controller combines the enhanced optimal performance evaluation index with the extended state space equation to establish an enhanced optimal sliding mode surface and output the target quadrature axis current; the improved harmonic suppression sliding mode speed observer outputs air compressor angular velocity and angle observation values ​​based on a boundary layer adaptive sliding mode control function and a voltage injection harmonic elimination algorithm, reduces current harmonics, and realizes position sensorless control of the air compressor.

2. The non-sensing enhanced optimal sliding mode control system for ultra-high-speed motors for air compressors according to claim 1 is characterized in that: The air compressor coupling control model introduces the target speed signal and the actual speed observation signal into the air compressor compression end fitting physical curve, the expansion end fitting physical curve, and the air compressor efficiency optimal working curve, and sets a gas flow sensor at the air compressor compression end outlet, a gas flow sensor at the expansion end inlet, a temperature sensor at the air compressor air inlet, and a temperature sensor at the expansion end inlet to monitor the compression end inlet air flow signal, the expansion end inlet air flow signal, the atmospheric temperature signal, and the expansion end inlet gas temperature signal in real time, and finally outputs the enhanced optimal performance evaluation index parameters.

3. The non-sensing enhanced optimal sliding mode control system for ultra-high-speed motors for air compressors according to claim 2 is characterized in that: The implementation method of the air compressor coupling control model includes: 1) The Jensen&Kristensen modeling method is adopted to fit the flow rate, pressure ratio, speed, and power consumption curves of the compression end and the expansion end based on the optimal efficiency based on the actual test data of the turbine air compressor. By receiving the target speed signal or the vehicle speed signal and combining the sampling signal of the gas flow sensor at the inlet of the compression end, the sampling signal of the gas flow sensor at the inlet of the expansion end, the sampling signal of the gas temperature sensor near the inlet of the compression end, and the sampling signal of the gas temperature sensor at the inlet of the expansion end, the control-oriented air compressor parameters are output; 2) Calculate the motor drive torque index parameter λ of the air compressor enhanced optimal performance evaluation index according to the following equation: Te : Where P n is the number of pole pairs of the air compressor motor, Air compressor motor flux, J cp is the air compressor rotation inertia; 3) Calculate the compression torque index parameter λ of the air compressor enhanced optimal performance evaluation index according to the following equation: cp : Where W cp is the gas mass flow rate at the compression end outlet, T atm is the atmospheric temperature, c c is the constant pressure specific heat capacity of the gas at the compression end, P rr is the target compression ratio at the compression end, ρ c is the specific heat ratio of the gas at the compression end, η cp is the compression end efficiency; 4) Calculate the expansion torque index parameter λ of the air compressor enhanced optimal performance evaluation index according to the following equation: ep : Where W ep is the gas mass flow rate at the expansion end inlet, T tep is the gas temperature at the expansion end inlet, c e is the constant pressure specific heat capacity of the gas at the expansion end, η ep is the expansion end efficiency, P er is the target expansion ratio at the expansion end, ρ e is the specific heat ratio of the gas at the expansion end.

4. The non-sensing enhanced optimal sliding mode control system for ultra-high-speed motors for air compressors according to claim 1 is characterized in that: The enhanced optimal sliding mode speed controller receives the speed observation signal of the improved harmonic suppression sliding mode speed observer, extracts the system matrix and the control matrix according to the air compressor speed torque state space equation, and establishes the extended state space equation; based on the speed sample data of the traditional sliding mode control and the subjective and objective entropy weight analysis data, combined with the compression end compression torque index parameter and the expansion end expansion torque index parameter, an enhanced optimal performance evaluation index is established; combined with the extended state space equation and the strong performance evaluation index, the enhanced control information is coupled, and finally an enhanced optimal sliding mode surface is established, the target speed information is received, and the target quadrature axis current value is output; The target current is applied to the PI controller of the current loop, combined with the harmonic voltage injection signal of the improved harmonic suppression sliding mode speed observer, and then combined with space vector pulse width modulation, and a switching pulse signal is output to the inverter to generate AC current to drive the motor to rotate.

5. The non-sensing enhanced optimal sliding mode control system for ultra-high-speed motors for air compressors according to claim 4 is characterized in that: The implementation method of the enhanced optimal sliding mode speed controller includes: 1) Input the control quantity as the state quantity and establish the extended state equation according to the following equation: Where, X ω is the extended state vector, A ω To expand the system matrix, B ω is the expanded input matrix, U ω is the extended control input vector, U is the control input vector, μ1 is a parameter greater than 0, and μ2 is a parameter greater than 0; 2) Construct the extended state space matrix according to the following equation: Where X is the state vector, A is the system matrix, B is the input matrix, and I is the identity matrix; 3) Establish the enhanced optimal performance evaluation index G according to the following equation: Where γ1 is the weighted coefficient obtained by analyzing the data based on the subjective and objective entropy weights, γ2 is the weighted coefficient obtained by analyzing the data based on the subjective and objective entropy weights, and ω ref is the target mechanical angular velocity, x 10 is the linearized working point matrix element at the current moment; 4) Based on the enhanced optimal performance evaluation index and the extended state space equation, the enhanced control information is obtained, and the solution of the Riccati equation of the control information is obtained according to the following equation: Where M is the solution of the Riccati equation; 5) Establish the enhanced optimal sliding surface S(X) according to the following equation ω ):

6. The non-sensing enhanced optimal sliding mode control system for ultra-high-speed motors for air compressors according to claim 1 is characterized in that: The improved harmonic suppression sliding mode speed observer receives the Alpha and Beta axis voltage signals in a stationary coordinate system, observes the motor back electromotive force in the stationary coordinate system based on the improved sliding mode control function, outputs the air compressor angle and angular velocity observation values, and adds the angle observation values ​​into the harmonic extraction equation to extract the harmonic components of the motor current at the current moment, uses the PI control algorithm to output the harmonic compensation voltage, reduces the harmonics of the current while realizing the sensorless control of the air compressor, and improves the accuracy of the sensorless control.

7. The non-sensing enhanced optimal sliding mode control system for ultra-high-speed motors for air compressors according to claim 6 is characterized in that: The implementation method of the improved harmonic suppression sliding mode speed observer includes: 1) Establish the speed observation sliding mode function Z according to the following equation: α , Z β : In the formula, s α is the sliding surface of the observed error of the Alpha axis, s β is the Beta axis observation error sliding surface, M α is the adaptive saturation function of the boundary layer on the Alpha axis, M β is the Beta axis boundary layer adaptive saturation function, R α is the adaptive reaching law of the boundary layer on the Alpha axis, R β It is the adaptive reaching law of the Beta axis boundary layer; 2) Define the boundary layer adaptive saturation function M according to the following equation: Where s is the observation error sliding surface, β is a parameter greater than 0, and r is the sliding mode observation error; 3) Define the boundary layer adaptive reaching law R according to the following equation: In the formula, ε is a parameter greater than 0, η is a parameter greater than 0, and λ is a parameter greater than 0; 4) Substitute the observed value of the motor back electromotive force into the inverse tangent function to obtain the observed value of the motor angle position; based on the observed value of the motor angle position, extract the harmonic component of the motor current, introduce it into the harmonic elimination PI algorithm, output the harmonic current compensation voltage value, superimpose it with the target voltage output by the current loop PI control algorithm, and output it to SVPWM together to generate a switching pulse signal.

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