OBD-II and raspberry Pi technology to diagnose car’s machine current condition: study literature
| Pages | 15-21 |
| Published date | 04 December 2017 |
| Date | 04 December 2017 |
| DOI | https://doi.org/10.1108/LHTN-06-2017-0041 |
| Author | Sonya Rapinta Manalu,Jurike Moniaga,Dionisius Andrian Hadipurnawan,Firda Sahidi |
| Subject Matter | Library & information science,Librarianship/library management,Library technology,Library & information services |
OBD-II and raspberry Pi technology to
diagnose car’s machine current condition:
study literature
Sonya Rapinta Manalu, Jurike Moniaga, Dionisius Andrian Hadipurnawan and
Firda Sahidi
Introduction
The whole world is going mobile.
Phones, computers and media devices now
fit in our pockets and can connect us to a
variety of information sources and enable
communication nearly everywhere we go.
There is considerable interest in exploiting
the almost universal appeal and abundance
of these technologies for their educational
use (Naismith et al., 2004a). There are
estimated to be 1.5 billion mobile phones in
the world today (Naismith et al., 2004b). A
first step in postulating a theory of mobile
learning is to distinguish what is special
about mobile learning compared to other
types of learning activities. An obvious, yet
essential, difference is that it starts from the
assumption that learners are continually on
the move (Sharples et al., 2005).
Mobile services are now available for
arranging ad hoc face-to-face meetings
with friends, finding driving directions,
dating, games and even chatting with
unknown people (Tamminen et al., 2004).
Almost no company can get by these days
without a mobile presence supporting their
business (Unhelkar and Murugesan, 2010).
The technology industry has been leading
the US economy in job creation, business
development and innovation for more than
20 years (Coleman and Robb, 2010). In the
technology industry, mobile software
applications are increasing in popularity
and creating economic opportunities for
application businesses (Anthes, 2011).
Whether a new mobile application will
develop into a successful product or service
is always uncertain (Wang et al., 2012).
The use of wireless, mobile, portable
and handheld devices is gradually
increasing and diversifying across
every sector of education and across
both the developed and developing
worlds. It is gradually moving from
small-scale, short-term trials to larger
more sustainable ones.
Recent publications, projects and
trials are drawn upon to explore the
possible future and nature of mobile
education (Traxler, 2009)(Figure 1).
The basic concept of automotive
On-Board Diagnostic (OBD) systems is
to result in malfunction indicator light
(MIL) illumination after a fault has been
detected on two consecutive driving
cycles. Pending fault codes are stored on
the first detection and altered to “active”
or “confirmed” codes once the MIL
comes on. An error is considered to
progress to a fault when it leads to
produced emission that exceeds a
pre-specified threshold (Mohammadpour
et al., 2012). An On-Board Diagnostic, or
OBD, system is a computer-based system
for diagnosing operational errors and to
monitor the performance of various
engine components including emission
controls (Graham, 2008). Testing
vehicles with advanced emission control
systems with OBD checks introduces a
relatively simple inspection process that
addresses the shortcomings of current test
procedures and best practices (Chambliss
et al., 2016).
Current OBD systems (OBD-II) were
proposed in 1996 and all vehicles are
required to be equipped with OBD-II
under EPA regulations in the USA (Chen
et al., 2015). The regulations that added
OBD-II controls to some new vehicles in
1994, 1995 and all 1996 and later models
sold in the USA. Unlike OBD-I, OBD-II
is designed to detect electrical, chemical
and mechanical failures in the vehicles
emission control levels. Almost all the
problem with the vehicle can be detect by
OBD-II, such as exhaust manifold, ABS
brake function, airbag (iSRS & SRS),
idle performance and so on. OBD-II takes
the next logical step in emission control.
It uses all of the previous diagnostic
features and adds a monitor to test the
chemical action of the catalyst.
Beginning in 2010, implementation of
OBD is mandatory for all the heavy-duty
engine applications in the USA. The
process involves a strong interdependency
on base engine emissions, controls and
regulations. The recent demands to
minimize the development process have
pushed the envelope on methodologies
used in developing the strategies and the
calibration for robust monitoring
(Nanjundaswamy et al., 2011)(Figure 2).
To process emissions data, a
microcontroller is needed. A
microcontroller is a microprocessor
system that is installed on a chip.
Microcontrollers are already filled with
supporting minimal component systems,
such as memory and an I/O interface
(Lipovski, 2004). In contrast,
microprocessors are usually only filled by
the CPU (Nurfalah, 2014). Both
microprocessors and microcontrollers
contain a central processing unit. The
CPU executes instructions that perform
the basic logic, math and data-moving
functions of a computer. To make a
complete computer, a microprocessor
requires memory for storing data and
programs and an input/output (I/O)
interface for connecting external devices
such as keyboards and displays.
Microcontrollers are actually a single-
chip computer because it contains
memory and I/O interfaces in addition to
the CPU. Because the amount of memory
and interfaces that can fit on a single chip
is limited, microcontrollers tend to be
used in smaller systems and a few
support components (Ibrahim, 2002).
We chose two of the popular
microcontroller models and compared
their features: the Arduino Uno and
Raspberry Pi. Raspberry Pi and
LIBRARY HITECH NEWS Number 10 2017, pp. 15-21, © Emerald Publishing Limited, 0741-9058, DOI 10.1108/LHTN-06-2017-0041 15
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