본 발명은 전동식 조향장치 및 그 제어방법이 개시된다. 본 발명의 전동식 조향장치는, 차량의 주행 중 차량상태를 입력받는 차량상태 입력부; 차량의 전방 및 운전자를 촬영하는 ADAS 카메라; 차량상태 입력부로부터 입력된 차속과 컬럼토크를 기반으로 기본 보타력을 산출하고, 차량상태와 ADAS 카메라로부터 입력된 전방 촬영영상을 기반으로 도로 상태 및 주변 환경에 기초한 딥러닝을 이용하여 조향 무게감을 조절하기 위한 보상값을 예측하고, 기본 보타력에 보상값을 적용하여 최종 보타력으로 조향구동부를 제어하는 제어부; 및 제어부에서 도로 상태와 주변 환경에 기초하여 예측한 보상값의 학습결과를 저장하는 저장부;를 포함하는 것을 특징으로 한다.

    The present invention discloses an electric steering apparatus and a control method thereof. The electric steering apparatus of the present invention comprises: a vehicle status input unit for receiving a vehicle status while a vehicle is being driven; an ADAS camera to photograph the front of the vehicle and a driver; a control unit for calculating a basic coercive force based on a vehicle speed and column torque input from the vehicle status input unit, calculating a compensation value based on a road status and a surrounding environment based on the vehicle status and a front captured image input from the ADAS camera, and controlling a steering drive unit with a final coercive force by applying the compensation value to the basic coercive force; and a storage unit for storing a learning result of the compensation value calculated by the control unit based on the road status and the surrounding environment. An objective of the present invention is to provide the electric steering apparatus, which compensate for and provide a coercive force, and the control method thereof.


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    Title :

    MOTOR DRIVEN POWER STEERING AND CONTROL METHOD THEREOF


    Additional title:

    전동식 조향장치 및 그 제어방법


    Publication date :

    2025-01-20


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Korean


    Classification :

    IPC:    B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen



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