Position self-learning method of automotive actuator

Abstract

The invention discloses a self-learning method for the position of an automotive actuator, which comprises the following steps: collecting M groups of sensor limit signal value combination samples for sensors of the actuator; Signal average Calculates the screening reference value MSE for each set of sensor limit signal value combinations i ;Retain the screening reference value MSE from the combined samples of the M groups of sensor limit signal values i The smallest N groups of samples; calculate the maximum retained position signal mean value and the retained minimum position signal mean value of the combination of N groups of sensor limit signal values ​​Calculate the stroke signal ratio parameter Scale and the stroke signal offset value according to the retained maximum position signal mean value and the retained minimum position signal mean value The parameter Offset, the electronic control unit saves the Scale value and the Offset value. The self-learning method of the present invention enables the electronic control unit to control the actuator to perform actions more accurately.

Description

technical field [0001] The invention relates to an automotive actuator technology, in particular to a position self-learning method for an automotive actuator. Background technique [0002] With the continuous improvement of the degree of electronic control of modern automobiles, there are more and more various actuators set in the automobile, such as throttle valve actuators, EGR valve actuators, variable area supercharger actuators, exhaust gas actuators, etc. Air brake valve actuators, etc., the electronic control unit of the car can control each actuator to implement actions through the control circuit, so as to realize the coordinated operation of the vehicle as a whole. [0003] However, the position signal of the actuator sensor often has some deviation relative to the standard signal value, and this deviation is unavoidable. For this reason, before the electronic control unit of the car controls the actuator, it must first adaptively learn the sensor signal of the a...

AI Technical Summary

Problems solved by technology

[0005] For now, the maximum signal value and the minimum signal value of the sensor based on the calculation of the stroke signal ratio parameter Scale and the stroke signal offset value parameter Offset are one sample value among multiple acquisition samples, and the sample value has not been optimized. It is directly used as the basis for the calculation of the stroke signal ratio parameter Scale and the stroke signal offset value parameter Offset. This unoptimized sensor signal value will inevitably be inaccurate due to disturbance by external factors. Therefore, As a result, the calculated stroke signal ratio parameter Scale and the stroke signal offset value parameter Offset are inaccurate, thus affecting the precise control of the actuator by the electronic control unit

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