CN102914433B - Method for electrically simulating mechanical inertia - Google Patents

Abstract

The invention discloses a method for electrically simulating mechanical inertia, comprising the steps of: using Kalman filter to estimate angular acceleration according to the measured angular velocity; performing delay compensation on the estimated angular acceleration to obtain quasi-real-time angular acceleration; the quasi-real-time The angular acceleration of the angular acceleration forms the given value of the electric inertia torque according to the numerical value of the analog inertia, and transmits the given value of the electric inertia torque to the frequency converter, and the frequency converter controls the electromagnetic torque of the loading motor to realize the electrical simulation of the mechanical inertia. Through the above method, the method for electrically simulating mechanical inertia provided by the present invention meets the requirements of transmission test for inertia simulation, simplifies the mechanical structure of transmission test bench, improves the precision of inertia simulation, can realize stepless adjustment of inertia, and eliminates mechanical flywheel The level difference that exists when simulating the inertia ensures the reliability of the test and improves the degree of automation of the transmission test bench, which is widely valued and concerned by the automobile bench test equipment manufacturers.

Description

A Method of Electrically Simulating Mechanical Inertia

technical field

The invention relates to the field of transmission bench test equipment, in particular to a method for electrically simulating mechanical inertia.

Background technique

The transmission is one of the most important components in the vehicle transmission system. Its performance is directly related to the power performance, fuel economy and comfort of the vehicle, and has an important impact on the improvement of the vehicle performance. Its performance, efficiency, reliability and Parameters such as durability cannot only rely on calculations, but must be confirmed by tests. At the same time, the rationality of transmission gears, bearing materials, structural design, manufacturing processes, loads, speeds, and lubrication conditions must also be verified through tests, so as to provide a solid foundation for the product. Design and quality evaluation provide a solid scientific basis. The bench test in the preliminary research and development of the transmission can effectively improve the quality, reduce the development cost, and shorten the development cycle. It is widely used in tests and researches on automatic transmission shift schedule and shift quality.

In order to ensure the consistency between the test conditions and the actual working conditions, the traditional test bench not only uses the motor loading to simulate the driving resistance of the car, but also widely uses the mechanical flywheel to simulate the inertia of the actual car. The disadvantage of mechanical flywheel simulation inertia is that there are shortcomings such as simulation level difference and inertia adjustment difficulty, and the large-mass flywheel has high requirements for manufacturing processes such as machining accuracy and dynamic balance. In addition, the kinetic energy stored in the high-inertia flywheel rotating at high speed There is a certain danger to the equipment and test personnel. In order to simulate the inertia simulation requirements of different models, it is necessary to design the flywheel part into a flywheel set composed of multiple flywheels of different sizes according to the differential or proportional series, which increases the The complexity of the test bench, and the degree of automation is low. Electric simulation is to use the torque or speed control characteristics of the loading motor in the test bench to simulate the energy storage characteristics of the mechanical flywheel by adjusting the system and the computer to control its mechanical energy and electric energy conversion characteristics, and act on the main shaft in the form of inertial torque, so that the test The dynamic characteristic of the bench is consistent with the system using the mechanical flywheel. The research on the electric inertia abroad has been relatively in-depth, and it has been widely used in chassis dynamometers, transmission test benches, brake test benches and other instruments. However, this prior art has high Added value, not yet public. With the technical progress of the automobile industry, the development of transmission technology puts forward higher performance requirements and technical level for the test bench, and the inertial electrical simulation has become an essential function of the new generation of transmission test bench. In recent years, with the development of motor control technology, power electronics technology and computer control technology, the comprehensive performance of the electric drive system is close to perfection, which provides a reliable foundation for the engineering realization of electric inertia.

Contents of the invention

The technical problem mainly solved by the present invention is to provide a method for electrically simulating mechanical inertia that improves the precision of inertia simulation.

In order to solve the problems of the technologies described above, a technical solution adopted in the present invention is to provide a method comprising the steps of:

(1) Fix the transmission to be tested on the transmission test bench, start the control computer and the frequency converter, and input the parameters of the vehicle that matches the transmission to be tested into the control computer;

(2) The control computer detects the speed of the output shaft of the transmission, and calculates the torque to be loaded and the inertia to be simulated by the loading motor in the transmission test bench according to the parameters of the vehicle;

(3) Use the Kalman filter to estimate the angular acceleration based on the measured angular velocity;

(4) Delay compensation is performed on the estimated angular acceleration to obtain quasi-real-time angular acceleration;

(5) The quasi-real-time angular acceleration forms a given value of electric inertia torque according to the value of analog inertia calculated in step (2), and transmits the given value of electric inertia torque to the frequency converter, which controls the loading motor The electromagnetic torque realizes the electrical simulation of the mechanical inertia.

In a preferred embodiment of the present invention, in steps (3) and (4), the state before the loading motor rotates is used as the initial value to determine the system state vector, and the value of each element on the diagonal in the estimated error variance matrix is The value is 10 times the square of the filter estimation accuracy value of the corresponding variable, and the system state vector and the estimation error variance matrix are determined before Kalman filter recursion.

In a preferred embodiment of the present invention, step (3) determines the measurement noise covariance matrix according to the statistical characteristics of the measurement noise in the angular velocity, and determines the system noise covariance matrix by trial and error.

In a preferred embodiment of the present invention, in step (4), the measurement noise covariance matrix is determined according to the noise statistical characteristics in the estimated angular acceleration, and the system noise covariance matrix is determined by trial and error.

The beneficial effects of the present invention are: the method for electrically simulating mechanical inertia of the present invention meets the requirements of transmission test for inertia simulation, simplifies the mechanical structure of transmission test bench, improves the precision of inertia simulation, can realize stepless adjustment of inertia, and eliminates mechanical flywheel The level difference that exists when simulating the inertia ensures the reliability of the test and improves the degree of automation of the transmission test bench, which is widely valued and concerned by the automobile bench test equipment manufacturers.

Description of drawings

Fig. 1 is the flowchart of a preferred embodiment of the method for electrical simulation of mechanical inertia of the present invention;

Fig. 2 is the schematic diagram of delay compensation method in the method for electric simulation mechanical inertia of the present invention, among the figure represents the unknown actual angular acceleration, represents the estimated angular acceleration,

Detailed ways

The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, so as to define the protection scope of the present invention more clearly.

Please refer to Fig. 1, the present invention provides a kind of method of electrical simulation mechanical inertia, comprises steps as:

(1) Fix the transmission to be tested on the transmission test bench, start the control computer and the frequency converter, and input the parameters of the vehicle that matches the transmission to be tested into the control computer;

(2) The control computer detects the speed of the output shaft of the transmission, and calculates the torque to be loaded and the inertia to be simulated by the loading motor in the transmission test bench according to the parameters of the vehicle. The calculation steps are as follows:

1) Calculate the wheel speed n _tire : n _tire =n _transmission / _ic , where n _tire is the wheel speed (RPM), n _transmission is the transmission output shaft speed (RPM), and i _c is the main transmission from the transmission output shaft to the wheel transmission ratio;

2) Calculate the angular velocity ω _tire of the wheel: ω _tire = n _tire /9.55;

3) Calculate the driving speed v _i =ω _tire R _tire , where R _tire is the wheel radius (m);

4) Calculation of rolling resistance: F _roll (v _i )=fW, where f is the rolling resistance coefficient, which is related to the driving speed v _i , but below the speed of 140km/h, the value of f remains unchanged, and W is the vertical load ( N);

5) Calculate air resistance: F _w (u _r )= C _D Aρu , where, C _D is the air resistance coefficient; ρ is the air density, usually ρ=1.2258 N·s ² ·m ^-4 , A is the windward area, that is, the projected area in the driving direction of the vehicle (m ² ), u _r is the relative Velocity, i.e. the driving speed v _i (m/s) of the car when there is no wind;

6) Calculate the torque required to load the motor on the test bench: T _Le = [F _roll (v _i )+ F _w (u _r )]·R _tire =a·ω ² +b·ω+c, where, a, b, c are constants related to rolling coefficient, air resistance coefficient and vehicle parameters, and ω is the transmission output shaft speed (rad/s).

7) Calculate the inertia that needs to be simulated by the test bench as follows: , where, M _v is the mass of the vehicle (kg), _IT is the moment of inertia of the wheel (kg m ² );

(3) According to the measured angular velocity, use the Kalman filter to estimate the angular acceleration. The calculation steps are as follows:

The kinematic relationship between angular velocity ω and angular acceleration ζ is: , when processed by computer, it is discretized into the form of difference equation: ω(k+1)=ω(k)+Tζ(k), where k represents the time of discretization, and T is the sampling period.

The angular acceleration is also regarded as a state variable. In the sampling time, it is approximately considered that the angular acceleration changes slowly, ζ(k+1)=ζ(k), and the state variable is x(k)=〔ω(k) ζ( k)〕 ^T , the observed variable is z(k)=ω(k), considering the influence of the actual system input noise and measurement noise, the state equation and observation equation of the system in the discrete domain are , where the state transition matrix, measurement matrix, system input noise vector and measurement noise vector are respectively , , , , where w _ζ is the mean value is 0 and the variance is Gaussian white noise, v _ω is the mean value is 0, the variance is Gaussian white noise. w and v are uncorrelated zero-mean system white noise and observation white noise vectors, and the system noise covariance matrix corresponding to w for , the measurement noise covariance matrix corresponding to v is , pair The described system state equation and measurement equation use the Kalman filter theory to establish the following standard recursive process.

Time Update: State One-Step Prediction Equation: , one-step forecast error variance matrix: ;Measurement update: filter gain matrix: , state estimation: , the estimated error variance matrix: , after the above filtering and recursive calculation, it can be determined that at each discrete time status , that is, the angular acceleration is estimated from the measured angular velocity .

In the calculation step of the estimated angular acceleration, before performing the Kalman filter recursion, it is necessary to determine the system state vector and the initial value of the estimated error variance matrix ,in The determination method of is to take the state before the motor rotates as the initial value, and take the initial angular velocity , angular acceleration , the initial estimation error variance matrix It is a pair of diagonal arrays, and the value of each element on the diagonal can be taken as 10 times the square of the filter estimation accuracy value of the corresponding variable.

Also determine the system noise covariance matrix and the measurement noise covariance matrix. The measurement noise covariance matrix is determined according to the statistical characteristics of the angular velocity measurement noise; the system noise covariance matrix is determined by trial and error, the motor is controlled to run at a uniform acceleration, and the angular acceleration is estimated according to the collected angular velocity, and compared with the theoretical angular acceleration in real time. Optimizing the system noise covariance matrix is based on the filtered angular acceleration signal, where the theoretical angular acceleration can be obtained from the difference of a given angular velocity without noise.

When the Kalman filter estimates the angular acceleration in real time according to the angular velocity, in order to suppress high-frequency noise, it will cause a phase delay, and the estimated angular acceleration lags behind the real angular acceleration.

(4) Delay compensation is performed on the estimated angular acceleration to obtain quasi-real-time angular acceleration. The calculation steps are as follows:

Please refer to Figure 2, the angular acceleration estimation result in step (3) is approximately the output of the real angular acceleration passing through the first-order inertial link, by constructing a system with control input and inertial link, the output of the system tracks the input signal, The constructed control input can be approximately considered as leading the phase of the input signal, so as to realize the delay compensation of the angular acceleration estimation result, and the correction link is based on and error Generate control input to enable track ,but can be approximated as delay compensated output.

The equation of state for the actual angular acceleration is expressed as: , It is an unknown function, which represents the speed of the actual angular acceleration change. Assuming that the estimated angular acceleration is the output of the actual angular acceleration through the first-order inertia link, the state equation of the process is expressed as: , where, Indicates the delay time constant.

Let the state variable be , the observed variable is , then the continuous state equation and observation equation are: , where, is the state array, Enter the noise vector for the system, is the observation vector, is the observation array, is the observation noise vector, and , , , ,in, is the observation noise of the angular acceleration signal estimated in step (3), and is a mean of 0 and a variance of Gaussian white noise.

The angular acceleration is estimated by Perform delay compensation to obtain quasi-real-time angular acceleration , in fact, the state observation of the construction system is carried out according to the estimated angular acceleration, which can be realized by using the Kalman filter.

In the actual Kalman filter recursion process, it is necessary to use a discrete Kalman filter model. For this reason, the sampling period Discretization to the discrete system state equation and observation equation as , where the state transition matrix is , and the measurement matrix are , and are uncorrelated zero-mean system white noise and measurement white noise, in the sampling interval and is a constant value, and its statistical properties are: , , , , where is a non-negative definite matrix, is a positive definite matrix. for Kroneker function whose properties are , using the Kalman filter theory to establish a recursive equation for delay compensation: the state prediction is: ,

Estimate the prior estimate of the error variance matrix: , to calculate the Kalman gain matrix: , to update the state estimate based on the measurements, and calculate the optimal estimate of the state variables: , to update the covariance matrix: , after the above Kalman filter recursive calculation, it can be determined that at each discrete time status , that is, the quasi-real-time angular acceleration is calculated based on the estimated angular acceleration.

In the calculation step of the delay compensation method, before performing the Kalman filter recursion, it is necessary to determine the system state vector and the initial value of the estimated error variance matrix ,in The determination method of is to take the state before the motor rotates as the initial value, and take the initial angular velocity , angular acceleration , the initial estimation error variance matrix It is a pair of diagonal arrays, and the value of each element on the diagonal can be taken as 10 times the square of the filter estimation accuracy value of the corresponding variable.

Also determine the system noise covariance matrix and the measurement noise covariance matrix. The measurement noise covariance matrix is determined according to the noise statistical characteristics in the estimated angular acceleration; the system noise covariance matrix is determined by trial and error, and the motor is controlled to perform uniform acceleration and deceleration periodically, and the estimated angular acceleration described in step (3) Acceleration is used for delay compensation, and the quasi-real-time angular acceleration is compared with the theoretical angular acceleration in real time to optimize the system noise covariance matrix until it approaches the theoretical angular acceleration.

(5) The quasi-real-time angular acceleration forms a given value of electric inertia torque according to the value of analog inertia calculated in step (2), and the given value of electric inertia torque is in In order to load the moment of inertia (kg·m ² ) of the motor, the given value of the electric inertia torque is transmitted to the frequency converter, and the frequency converter controls the electromagnetic torque of the load motor to realize the electrical simulation of the mechanical inertia.

The actual effect of the method of electrically simulating mechanical inertia is verified by carrying out tests on a small-scale transmission test bench. The difference between the small-scale transmission test bench and the actual transmission test bench is that the power level is small, there is no transmission, and the function coefficient of loading torque and speed is different.

The test steps of the small-scale transmission test bench are: debugging the frequency converter, mainly including setting the rated data of the motor and the encoder, the control mode is set to the closed-loop vector control and torque control mode with the encoder, and the Profibus communication message is set , motor data identification; use the torque sensor to calibrate the electromagnetic torque of the motor; identify the mechanical moment of inertia of the bench, the moment of inertia of the test bench is 0.0124 kg·m ² ; set the relationship between the loading torque and the speed of the loading motor on the control computer, set up ,in , , the direction of torque loading is opposite to the direction of rotational speed; set the electric inertia to 0kg· ^m2 for acceleration and deceleration tests, set the electric inertia to 0.2 kg· ^m2 for acceleration and deceleration tests; manually control the torque of the drive motor during the test Size, in order to avoid the impact on the machine caused by sudden torque changes, the given value of the drive motor torque to the inverter is processed by a low-pass filter with a cut-off frequency of 100rad/s; during the acceleration test, in order to avoid the system when the speed is low In the non-linear region of friction torque, the driving motor is preloaded with 3N m before the test, and when it reaches a steady state, the driving torque is controlled to step from 3N m to 10N m; during the deceleration test, the driving motor torque suddenly drops from 10N m to 3N·m; during the test, the rotational speed, angular acceleration, driving torque and loading torque of the loading motor were collected respectively; the total inertia of the system was identified, and the control effect of the electric inertia during acceleration and deceleration was analyzed. After testing, the moment of inertia in the acceleration test results without electric inertia is 0.0126kg·m ² , the moment of inertia in the deceleration test results without electric inertia is 0.0129kg·m ² , and in the acceleration test results with electric inertia The moment of inertia is 0.2171kg·m ² , and the moment of inertia is 0.2122kg·m ² in the deceleration test results when there is electric inertia. According to the test results, it can be seen that the acceleration and deceleration process with the action of the electric inertia is obviously longer than that without the action of the electric inertia, and the moment of inertia obtained from the identification is basically close to the target value. The test results show that the method of the present invention can effectively realize the electrical simulation of the mechanical inertia.

The method for electrically simulating mechanical inertia disclosed by the present invention can effectively replace the simulated inertia of the mechanical flywheel, meet the requirements of the transmission test for inertia simulation, simplify the mechanical structure of the transmission test bench, improve the accuracy of inertia simulation, and realize stepless adjustment of inertia, eliminating The level difference that exists when the mechanical flywheel simulates the inertia ensures the reliability of the test. It can realize the stepless adjustment of simulated inertia by adjusting the control parameters within the design range, and improve the automation degree of the transmission test bench, which has received extensive attention and attention from the manufacturers of automobile bench test equipment.

The above is only an embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the description of the present invention and the contents of the accompanying drawings, or directly or indirectly used in other related technologies fields, all of which are equally included in the scope of patent protection of the present invention.

Claims (3)

1. a method for electric analogy mechanical inertia, is characterized in that, comprises step to be:

(1) variator to be measured is fixedly mounted on gearbox testrigs, starts computer for controlling and frequency converter, the parameter of the car that input and described variator to be measured match in described computer for controlling;

(2) described controlling calculation machine testing transmission output speed to be measured, according to the loading motor moment of torsion that will load and the inertia that will simulate that the parameter of car calculates in described gearbox testrigs;

(3) Kalman Filter Estimation angular acceleration is used according to the angular velocity measured;

(4) delay compensation is carried out to described estimation angular acceleration, obtain angular acceleration quasi real time;

(5) numerical value of the inertia of the simulation that angular acceleration quasi real time described in calculates according to step (2) forms electrical inertia moment of torsion set-point, described electrical inertia moment of torsion set-point is sent to frequency converter, and described in Frequency Converter Control, the electromagnetic torque of loading motor realizes mechanical inertia electric analogy;

State before rotating with described loading motor in step (3) and step (4) is for initial value certainty annuity state vector, in estimation error variance battle array, on diagonal line, the value of each element is 10 times of the filtering estimated accuracy value square of relevant variable, and described in described system state vector sum, estimation error variance battle array is determined before carrying out Kalman filtering recursion.

2. the method for electric analogy mechanical inertia according to claim 1, is characterized in that, step (3), according to the measurement noises statistical property determination measurement noises covariance matrix in angular velocity, gathers certainty annuity noise covariance battle array by examination.

3. the method for electric analogy mechanical inertia according to claim 1, is characterized in that, according to the noise statistics determination measurement noises covariance matrix estimated in angular acceleration in step (4), by trying to gather certainty annuity noise covariance battle array.