• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4123-4141
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• 2019

Autonomous driving technology is divided into 0~5 levels. Of these, Level 5 is a fully autonomous vehicle that does not require a person to drive at all. The automobile industry has been trying to develop Level 5 to satisfy safety, but commercialization has not yet been achieved. In order to commercialize autonomous unmanned vehicles, there are several problems to be solved for driving safety. To solve one of these, this paper proposes 'A Deep Learning Part-diagnosis Platform(DLPP) based on an In-vehicle On-board gateway for an Autonomous Vehicle' that diagnoses not only the parts of a vehicle and the sensors belonging to the parts, but also the influence upon other parts when a certain fault happens. The DLPP consists of an In-vehicle On-board gateway(IOG) and a Part Self-diagnosis Module(PSM). Though an existing vehicle gateway was used for the translation of messages happening in a vehicle, the IOG not only has the translation function of an existing gateway but also judges whether a fault happened in a sensor or parts by using a Loopback. The payloads which are used to judge a sensor as normal in the IOG is transferred to the PSM for self-diagnosis. The Part Self-diagnosis Module(PSM) diagnoses parts itself by using the payloads transferred from the IOG. Because the PSM is designed based on an LSTM algorithm, it diagnoses a vehicle's fault by considering the correlation between previous diagnosis result and current measured parts data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.267-270
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• 2021

In order to diagnose a vehicle, it is achieved by collecting diagnostic data within the ECU or between ECUs and managing the diagnostic data by utilizing various communication methods through an electronic device composed of an ECU(Electronic Control Unit), which is an automotive electronic device. As communication methods, LIN, CAN, FlexRay are mainly used. Recently, wired/wireless communication is being used based on Ethernet. In order to perform vehicle diagnosis, it is necessary to know the diagnosis code generated by the ECU and to collect diagnosis data using diagnosis communication. In addition, diagnostic data can be managed from the ECU only when the application software required for vehicle diagnosis is configured. If many automobile manufacturers are manufacturing ECUs based on the AUTOSAR standard, which is an automotive electronic standard, the software structure is also configured to be applied according to the standard. In this paper, we understand the vehicle diagnosis communication method of the AUTUSAR standard, study the configuration and processing method of diagnosis data, and study the contents of software components, diagnosis communication, and diagnosis event processing.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.1
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• pp.99-111
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• 2016

This paper presents an integrated fault diagnosis algorithm for driving motor of In-wheel independent drive electric vehicle. Especially, this paper proposes a method that integrated the high level fault diagnosis and the low level fault diagnosis in order to improve a robustness and performance of the fault diagnosis system. The high level fault diagnosis is performed using the vehicle dynamics analysis and the low level fault diagnosis is carried using the motor system analysis. The validity of the high level fault diagnosis algorithms was verified through $Carsim^{(R)}$ and MATLAB/$Simulink^{(R)}$ cosimulation and the low level fault diagnosis's validity was shown by applying it to a MATLAB/$Simulink^{(R)}$ interior permanent magnet synchronous motor control system. Finally, this paper presents a fault diagnosis strategy by combining the high level fault diagnosis and the low level fault diagnosis.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.1
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• pp.216-221
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• 2004

This paper describes a fault detection and fault handling algorithm to be used in a longitudinal vehicle cruise control systems. The fault diagnosis system consists of two structures to generate proper residuals and to find that which component has a fault. A systematic design of the fault diagnosis system using model-based techniques is presented. A linear observer is used to create a set of signals sensitive to faults in a radar sensor. The fault handling system consists of two structures to compensate for faults and degraded system performance. Simulation results show that the algorithm is effective for a fault diagnosis and handling in a longitudinal vehicle cruise control system.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.1
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• pp.215-215
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• 2004

This paper describes a fault detection and fault handling algorithm to be used in a longitudinal vehicle cruise control systems. The fault diagnosis system consists of two structures to generate proper residuals and to find that which component has a fault. A systematic design of the fault diagnosis system using model-based techniques is presented. A linear observer is used to create a set of signals sensitive to faults in a radar sensor. The fault handling system consists of two structures to compensate for faults and degraded system performance. Simulation results show that the algorithm is effective for a fault diagnosis and handling in a longitudinal vehicle cruise control system.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.3
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• pp.243-251
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• 2016

Autonomous Underwater Vehicles (AUVs) generally work in complex marine environments. Any fault in AUVs may cause significant losses. Thus, system reliability and automatic fault diagnosis are important. To address the actuator failure of AUVs, a fault diagnosis method based on the Gaussian particle filter is proposed in this study. Six free-space motion equation mathematical models are established in accordance with the actuator configuration of AUVs. The value of the control (moment) loss parameter is adopted on the basis of these models to represent underwater vehicle malfunction, and an actuator failure model is established. An improved Gaussian particle filtering algorithm is proposed and is used to estimate the AUV failure model and motion state. Bayes algorithm is employed to perform robot fault detection. The sliding window method is adopted for fault magnitude estimation. The feasibility and validity of the proposed method are verified through simulation experiments and experimental data.

• International Journal of Automotive Technology
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• v.7 no.2
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• pp.201-208
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• 2006

This paper describes the control philosophy of ESP(Electronic Stability Program) which consists of the stability control the fault diagnosis and the fault tolerant control. Besides the functional performance of the stability control, robustness of control and fault diagnosis is focused to avoid the unnecessary activation of the controller. The look-up tables are mentioned to have the accurate target yaw rate of the vehicle and obtained from vehicle tests for the whole operation range of the steering wheel angle and the vehicle speed. The wheel slip control with a design goal of wheel slip invariance is implemented for the yaw compensation and the target wheel slip is determined by difference between the target yaw rate and actual yaw rate. Since the ESP has a high severity level and the robust control is required, the robustness margin for the stability control is determined according to several uncertainties and the robust fault diagnosis is performed. Both computer simulation and test results are shown in this paper.

• Journal of Drive and Control
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• v.9 no.4
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• pp.8-13
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• 2012

Recently, researches about the eco-friendly vehicles such as hybrid electric vehicle, fuel cell vehicle and electric vehicle have been actively carried out. The regenerative braking system is a key technology to improve the vehicle energy utilization efficiency because it transforms the kinetic energy to the electric energy through the electric motor. This new braking system requires cooperative control between electric controlled brake and regenerative brake. Therefore, it is necessary to establish fault-diagnosis and fail-safe evaluation criteria to secure reliability of the regenerative braking system. In this paper, the failure types and causes in regenerative braking system were analyzed. The transient behavior characteristics were examined based on fault-diagnosis and fail-safe upon failure of regenerative braking system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4576-4582
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• 2010

Because most of vehicle provide users with the very limited information regarding the performance of vehicle, it is quite difficult for users to drive vehicles safe, and to maintain and repair vehicles properly. In order to solve the above-mentioned problems, several ways of research and development for the vehicle control and diagnosis system have been recently carried out. However, a lot of complicated problems and difficulties were arising due to the complexity of the developed system, degradation of the reliability for the vehicle performance control system, operational malfunction and so on. In this paper, for the purpose of solving the difficult problems and technical limitations, a system for vehicle performance which might be able to diagnose the reliability of vehicle performance by measuring and analyzing the real time performance of vehicle using the satellite telemetry technology was conmance oly defined and deehiced.hihe results derived from the cormance ofdvehiclactivities in this study shall be used as not only fundamental data but also materials for the detailed design for the implementation of vehicle performance diagnosis system in the near future.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.2
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• pp.72-77
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• 2011

In this paper, we propose effective diagnosis algorithm for hub bearing fault in driving vehicle using acceleration signal and wheel speed signal measured in hub bearing unit or knuckle. This algorithm consists of differential, envelope and power spectrum method. We developed diagnosis system for realizing proposed algorithm. This system consists of input device including acceleration sensor and wheel speed sensor, calculation device using Digital Signal Processor (DSP) and display device using Personal Digital Assistant (PDA). Using this diagnosis system, a driver can see hub bearing fault(flaking) from the vibration in driving vehicle. With early repairing, he can keep good ride feeling and prevent accident of vehicle resulting from hub bearing fault.