1
Development of PHM Algorithm of e-Latch to Prepare for The Era
of Autonomous Driving
Mooseok Kwak
1
, Jinwoo Nam
1
, Kyoungtaek Kwak
1
, Geunsoo Kim
1
, Dongwook Choi
1
, Jinsang Jung
1
, Jungho Han
1
,
Gwanhee Kang
1
, Kyeongjun Lim
1
, Youngsoo Byun
2
, Jungmin Eum
2
, Michael H. Azarian
3
, and Namkyung Lee
3
1,
Hyundai Motor Company, Hwaseong-si, 18280, Korea
stheskys@hyundai.com
njw@hyundai.com
avetaek@hyundai.com
nothing@hyundai.com
closuremecha@genesis.com
keyset@hyundai.com
hanjungho@hyundai.com
gkang@hyundai.com
lkj8653@hyundai.com
2
Daedong Door Hi-lex, Incheon-si,21991, Korea
soobyun@hi-lex.co.kr
jmeom@Hi-Lex.co.kr
3
The University of Maryland, College Park, MD 20742, United States
mazarian@umd.edu
nklee@umd.edu
ABSTRACT
In self-driving vehicles linked with mobility electrification,
system failures that occur suddenly in situations where
customers are unaware of signs of failure are directly related
to customer injuries. Securing the durability and safety of
closure automation system is necessary to increase the
customer's safety value so PHM technology makes it possible
to predict failures and remaining life in advance during
system operation. In addition, since not only various forms of
new concept design styling but also innovative new handle
designs are applied, it is obviously seen that e-Latch system
is widely equipped in the mobility. Thus, in this paper, the
study to predict the failure of e-Latch and closure system is
implemented via data-driven and physics-driven method, and
the algorithm for PHM to estimate remaining life of e-Latch
system is also introduced.
1. INTRODUCTION
In the era of autonomous driving linked with the
electrification of mobility, diverse opening and closing
mechanisms are implemented, and the system's
electronification becomes common in future mobility. In this
context, sudden system failures, which occur without the
customer's awareness of fault signs, are directly related to
customer injuries. Particularly in cases where the vehicle's
owner and user are different, such as PBVs (Purpose Built
Vehicles), even if fault signs appear, users may not share
these signs with the owners. This leads to a lack of preventive
maintenance and increases the risk of customer injuries due
to vehicle malfunctions. Therefore, ensuring the durability
and safety of closure automation systems is crucial for
maximizing customer safety value. Prognostics and Health
Management (PHM) technology, which predicts faults and
estimates remaining useful life, is considered a key
technology for future autonomous driving era closure
systems. In the case of B2B shared autonomous vehicles
connected with Fleet Management Systems (FMS), the
application of this technology is expected to be highly
beneficial not only for ensuring customer safety but also for
maximizing the durability and minimizing maintenance costs
of mobility. Thus, understanding the principles of PHM
