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CN-122014438-A - Engine boost pressure control method based on nonlinear algebraic filtering and ascending and descending order observation

CN122014438ACN 122014438 ACN122014438 ACN 122014438ACN-122014438-A

Abstract

The invention belongs to the technical field of internal combustion engine electric control, and discloses an engine boost pressure control method based on nonlinear algebraic filtering and lifting order observation, which comprises the following steps that step 1, an electric supercharger boost pressure dynamic model is used for controlling a target rotating speed according to eTurbo at the current moment Output boost pressure Step 2, the nonlinear algebraic filter module is used for adjusting the target boost pressure according to the target boost pressure And boost pressure measurements Original tracking error of the boost pressure is calculated Then carrying out normalization, scaling and reconstruction to obtain a smoothed tracking error And Step 3, lifting the stage of the extended state observer For input, output of the rate of change of boost pressure and an estimate of the first and second derivatives thereof 、 And Step 4, calculating eTurbo target rotating speed at the next moment according to the active disturbance rejection control law . The invention realizes accurate estimation of rapid dynamic disturbance and intelligent suppression of measurement noise, and effectively improves dynamic response, disturbance resistance and steady state stability of eTurbo control.

Inventors

  • SONG KANG
  • Zhao Zuolong
  • CHENG ZHENYU
  • ZHANG ZILEI
  • Ding Zhanming
  • ZHANG YAN
  • XIE HUI

Assignees

  • 天津大学

Dates

Publication Date
20260512
Application Date
20260113

Claims (10)

  1. 1. The engine boost pressure control method based on nonlinear algebraic filtering and ascending and descending order observation is characterized by comprising the following steps of: step 1, a dynamic model of the boost pressure of the electric supercharger is based on eTurbo target rotating speed at the current moment Output boost pressure The model comprises the change rate of the boost pressure ; Step 2, the nonlinear algebraic filter module is used for adjusting the target boost pressure according to the target boost pressure And boost pressure measurements Original tracking error of the boost pressure is calculated Then normalizing to obtain normalized error Nonlinear scaling function For a pair of Scaling and reconstructing to obtain smoothed tracking error According to And Calculating smoothed boost pressure ; Step3, lifting the step-up and step-down expansion state observer For input, output of the rate of change of boost pressure and an estimate of the first and second derivatives thereof 、 And ; Step 4, based on 、 、 And calculating eTurbo target rotating speed at the next moment through an active disturbance rejection control law according to the estimated value of the system parameters And feeds back to the rotating speed control layer to form a closed loop to realize the supercharging pressure To target boost pressure Is a tracking of (a).
  2. 2. The method for controlling the boost pressure of the engine based on nonlinear algebraic filtering and ascending and descending order observation according to claim 1, wherein in the step 1, the dynamic model of the boost pressure of the electric supercharger is: ; Is the boost pressure at the time t, Is the first derivative of boost pressure at time t, Is the second derivative of boost pressure at time t, Is eTurbo target rotating speed at the time t, Respectively damping term dynamic coefficient and restoring force term dynamic coefficient, In order to control the gain of the gain control, As a constant disturbance, the signal is a constant disturbance, The rate of change of the boost pressure at time t.
  3. 3. The method for controlling the boost pressure of the engine based on the nonlinear algebraic filtering and the lifting order observation according to claim 1, wherein in the step 2, the original tracking error is The calculation formula of (2) is as follows: ; Wherein, the Is a discrete time series label of which the number is, Is that The original tracking error of the moment in time, Is that The target boost pressure at the moment in time, Is that A boost pressure measurement at time; Normalized error The calculation formula of (2) is as follows: ; Wherein the method comprises the steps of For a preset dead zone threshold value, , Is that Normalization error of time; Preferably, the method comprises the steps of, , The standard deviation of the noise is measured for the pressure sensor.
  4. 4. The method for controlling the boost pressure of the engine based on the nonlinear algebraic filtering and the lifting order observation according to claim 3, wherein in the step2, the nonlinear scaling function The expression of (2) is: ; smoothed tracking error The calculation formula of (2) is as follows: ; Is that Time-of-day smoothed tracking error , Is that Normalization error of time; Smoothed boost pressure 。
  5. 5. The method for controlling the boost pressure of the engine based on the nonlinear algebraic filtering and the lifting order observation according to claim 1, wherein in the step 3, a state update equation of the lifting order extended state observer is: ; ; ; 、 、 Respectively is The observer intermediate state variable of the moment in time, 、 、 Respectively is The observer intermediate state variable of the moment in time, 、 、 The coefficient matrices of the state update equations respectively, 、 、 Respectively the intermediate variables are respectively used for the preparation of the intermediate variables, The sampling period of the digital control system, For observer bandwidth, it is preferable, , Bandwidth is expected for a closed loop system; The output equation of the lifting order expansion state observer is as follows: ; 、 And Is that The supercharging pressure change rate at the moment and the first derivative thereof an estimate of the second derivative.
  6. 6. The engine boost pressure control method based on nonlinear algebraic filtering and lifting order observation according to claim 1, wherein in the step 4, the form of the active disturbance rejection control law is as follows: ; Is that Time-of-day smoothed tracking error , In order for the controller to gain, For proportional gain, the gain of the gain, preferably, , , The bandwidth is desired for a closed loop system, In order to achieve a damping ratio, Is an estimated value of the first derivative of boost pressure at time t, Parameters in the dynamic model of the boost pressure of the electric booster Is used to estimate the value of the real-time estimate of (c), Is that An estimate of the rate of change of boost pressure at time.
  7. 7. The control device of the electric supercharger is characterized by comprising a processor and a memory, wherein the memory is used for storing program codes and transmitting the program codes to the processor; The processor is configured to execute the engine boost pressure control method according to any one of claims 1 to 6 based on nonlinear algebraic filtering and lifting order observation according to instructions in the program code.
  8. 8. A computer readable storage medium storing computer executable instructions which, when executed, are adapted to implement the method for controlling boost pressure of an engine based on nonlinear algebraic filtering and lifting order observation according to any one of claims 1 to 6.
  9. 9. An electric supercharger comprising an electric supercharger body and the control apparatus of claim 7.
  10. 10. An engine comprising the electric supercharger of claim 8.

Description

Engine boost pressure control method based on nonlinear algebraic filtering and ascending and descending order observation Technical Field The invention belongs to the technical field of internal combustion engine electric control, and particularly relates to an engine boost pressure control method based on nonlinear algebraic filtering and lifting order observation, in particular to an intelligent control method combining the nonlinear algebraic filtering and a lifting order expansion state observer, which is suitable for improving the dynamic response, disturbance rejection capability and steady state stability of a boost system. Background The evolution of internal combustion engine technology is converging towards high efficiency and deep electrification. Under the background, the electric supercharger (eTurbo) is developed as a revolutionary technology, and by coaxially integrating a high-speed motor into a traditional turbocharger, the quick establishment and independent control of the supercharging pressure are realized, so that the inherent turbo hysteresis problem of the traditional exhaust gas turbocharger is effectively solved, the low-speed torque output and transient response capability of an engine are obviously improved, and the electric supercharger is a key component of a modern high-efficiency internal combustion engine and a hybrid power system. In the prior art, researches are focused on improving the dynamic performance of a supercharging system through system architecture optimization, for example, an electric auxiliary turbine double-supercharging system is adopted by a 'diesel engine constant-speed rapid torque increasing system and control method' with the application number of CN202110722029.0, and the scheme combines variable gas distribution and fuel injection cooperative control to realize rapid torque increasing, so that the scheme shows the potential of electrified supercharging and multi-system cooperation in the aspect of improving the transient performance of an engine. However, the high performance potential of eTurbo systems is highly dependent on the precision of their electronic control systems. The system faces a series of interleaving challenges in engineering implementation, which place near-stringent requirements on the robustness, response speed and steady-state accuracy of the control algorithm. ETurbo the control system is in a highly dynamic and uncertain operating environment. The method is characterized in that the source of disturbance is complex and various, turbine input torque is severe and fluctuates at high frequency due to periodic exhaust pulses of an engine, the action of other actuators (such as a throttle valve) in an air inlet system can cause abrupt change of air inlet flow, a high-speed rotor system has complex nonlinear friction effects (coulomb friction, viscous friction and the like), system rotational inertia and motor parameters (such as flux linkage and resistance) can drift along with temperature and working point changes, and a boost pressure sensor signal for feedback control is inevitably mixed with high-frequency measurement noise. The strong dynamic disturbance and high-frequency noise are mutually coupled, so that the perception and judgment of the real state of the system by the controller are seriously interfered, and the observation precision and the steady-state performance of closed-loop control are directly influenced. To suppress measurement noise, a linear low-pass filter is typically used in engineering to pre-process the sensor raw signal. For example, the application number CN202411442689.3 is "an optimal control method for target boost pressure", which is to process the characteristic coefficient of EGR rate through first-order low-pass filtering, and dynamically optimize the target boost pressure, so as to improve the stability of boost closed-loop control and the EGR response accuracy. While this approach can smooth the signal to some extent, its inherent disadvantage is amplified in systems such as eTurbo where the dynamic performance requirements are extremely high, the linear filter necessarily introduces a non-negligible phase lag within the passband while filtering noise. This lag may result in the filtered signal failing to truly reflect the instantaneous state of the system, resulting in delays in state observations and feedback control actions based on the signal, requiring an increase in the cut-off frequency of the filter to reduce the effects of phase lag on dynamics, but which may impair its noise suppression capability, whereas a decrease in the cut-off frequency to obtain a cleaner signal may introduce greater phase lag, compromising the quick response capability and stability margin of the system. This contradiction is difficult to reconcile within the traditional linear filtering framework. Active Disturbance Rejection Control (ADRC) and its core, the Extended State Observer (ESO), are of interest in the