US 11,951,965 B2
System and method for upgrading metamodel for friction coefficient prediction of brake pad, and brake control system using the metamodel
Sung Hyun Cho, Yongin-si (KR); and Sung Hoon Bang, Seoul (KR)
Assigned to Hyundai Motor Company, Seoul (KR); and Kia Corporation, Seoul (KR)
Filed by HYUNDAI MOTOR COMPANY, Seoul (KR); and KIA CORPORATION, Seoul (KR)
Filed on Oct. 1, 2021, as Appl. No. 17/491,948.
Claims priority of application No. 10-2021-0061090 (KR), filed on May 12, 2021.
Prior Publication US 2022/0363227 A1, Nov. 17, 2022
Int. Cl. B60T 8/172 (2006.01); B60T 8/171 (2006.01); B60T 8/58 (2006.01); B60T 17/22 (2006.01); G06N 20/00 (2019.01); F16D 66/00 (2006.01)
CPC B60T 8/172 (2013.01) [B60T 8/171 (2013.01); B60T 8/58 (2013.01); B60T 17/221 (2013.01); G06N 20/00 (2019.01); F16D 2066/001 (2013.01); F16D 2066/003 (2013.01); F16D 2066/005 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A system of upgrading a metamodel for friction coefficient prediction of a brake pad, the system comprising:
a data preprocessor configured to preprocess raw data including a rotation speed, a temperature and a pressure of a brake disc to validate the raw data;
a derivative parameter preprocessor configured to generate derivative parameters from basic parameters, as output by the data preprocessor, including the rotation speed, the temperature and the pressure of the brake disc; and
a metamodel processor configured to generate the metamodel for friction coefficient prediction by performing machine learning according to the derivative parameters output by the derivative parameter preprocessor,
wherein the derivative parameter preprocessor is configured to define the derivative parameters as principal factors influencing a change in a friction coefficient by analyzing relations between the basic parameters and the friction coefficient at a point in time when a friction coefficient difference occurs under an identical condition of each of the basic parameters preprocessed by the data preprocessor.