Title: Dispersed Remote Vehicle Diagnostic System

Year of Publication: Feb - 2016
Page Numbers: 1-7
Authors: YoungJin Go, ByongOk Jung, Buhm Lee, Wangrim Choi, JaeHak Shim, HwangWoo Byun, Kyoung-Min Kim
Conference Name: The Second International Conference on Electrical and Electronic Engineering, Telecommunication Engineering, and Mechatronics (EEETEM2016)
- Philippines

Abstract:


There are a large number of devices that conduct diagnosis for abnormality of vehicle in the market. However, those devices support only C-CAN signal among the vehicle signals; therefore, it is not possible to diagnose parts that use B-CAN signal. A majority of vehicle parts generate analog signal in order to operate sensor and actuator. On that account, it is essential to collect electric signal for an accurate diagnosis. However, it is required to connect a number of individual devices in order to diagnose by using the existing equipment; thus, the level of reliability of collected data will be reduced. Moreover, it is also required for an user to undergo data extraction process manually in order to extract valid data from the collected data. As a result, it takes a lot of time and the efficiency of overall inspection and verification will be reduced. Those conventional vehicle diagnostic devices are used when a vehicle is not running. However, the frequency of abnormal signal of an actual vehicle is high while a vehicle is running. The time of occurrence is not uniform either. In general, the critical part is to monitor multiple vehicles simultaneously and finding abnormality of vehicle in this situation in terms of improving the quality of vehicle substantially. This paper developed the dispersed remote vehicle diagnostic system that would collect and analyze C-CAN, B-CAN and analog signal. Also, this study secured the reliability of vehicle data with the differentiated performance from the conventional equipment through the synchronization with CAN communication and analog signal. The developed diagnostic system is able to diagnose abnormality of parts and search the cause hereof through the linked analyzed of synchronized AI signal and the segmented diagnosis. It is also able to reduce the unit cost of a purchaser by integrating a large number of individual diagnostic devices. Moreover, it is installed in an actually running vehicle as a system allowing for a small-scale long-hour test. As a result, it is possible to identify the cause in a daily life. It is also believed that it can contribute to the development of vehicle and improvement in research reliability since it facilitates a remote test on vehicle status for a long time.