Day 2 :
Keynote Forum
Kiyotaka Atsumi
LAC Co., Ltd., Japan
Keynote: Smart CAN cable, another IPS for CANBUS network
Biography:
Kiyotaka Atsumi pursued his PhD from Toyohashi University of Technology, Japan. He is currently the Director of IoT Technology Laboratory of LAC Co Ltd, Japan, the oldest security vendor in Japan. Currently, he is engaged in research of managed security service for connected-cars and of the threat analysis on model-based development for IoT.
Abstract:
We propose a new IPS (Intrusion Prevention System) for CAN BUS, one of the popular in-vehicle network. This shape is like a cable with connectors. We call it "Smart CAN Cable." The most important function of Smart CAN Cable is to find a compromised ECU (Electronic Control Units) who sends an illegal message on CAN BUS. A CSIRT (Computer Security Incidence Response Team) must identify a compromised computer and/or network systems at first when they detect that an attacker crack the system. In an office environment, it is to identify a compromised laptop by tracing an IP address. There is a need to solve the cybersecurity problem and to take down the attacker. Many ideas of IDS for CAN BUS were already proposed. Most of them can only detect anomaly CAN message, and they cannot identify which ECU is compromised because any ECUs cannot identify the ECU who sends illegal messages because of the specification of CAN protocol. The Smart CAN cable has two kinds of functions. One is to identify an illegal message; another is to memorize and identify a sender ECU when it sends a message. This paper shows how the Smart CAN cable works, and its advantages and disadvantages.
Keynote Forum
Lara A Carlson
University of New England, USA
Keynote: The driver athlete: More than just turning
Biography:
Lara A Carlson is currently an Associate Professor in the Department of Physical Therapy at the University of New England, Maine (USA). She is also a faculty appointment with the US Department of Veterans Affairs. She is a US ranked hammer thrower qualifying for four USA Outdoor Track and Field National Championships. She is a Fellow of the American College of Sports Medicine; a Recipient of the New England ACSM (NEACSM) Honor Award and was elected President of the NEACSM for an unprecedented second term in their history. Her research interests include the effects of exercise on immune responses, and motorsports physiology.
Abstract:
Race car drivers are highly skilled athletes who experience tremendous physical challenges during high-speed racing. Drivers are also exposed to significant G forces and high ambient temperatures for long periods of time with no timeouts. All of this is complicated by the fact that they are also encapsulated in protective gear and clothing. Furthermore, fluid losses during competitive racing can be significant. Without a fluid replacement strategy, fluid losses for these drivers may exceed three percent body weight, which could negatively impact driving performance. Research has been established in other sports to show the detrimental impact thermal stress and fluid loss can have on athletic performance, especially by straining the cardiovascular system. Similar effects are likely during races where drivers need to circulate blood efficiently to dissipate heat, ward off fatigue to maintain their ability to mentally concentrate and rely on quick reaction times and precise hand-eye coordination. And much of this, including G tolerance to some degree, is adaptable by systematic physical training and preparedness. Advocacy is warranted to ensure the sports medicine and motorsports communities are doing all they can to protect the drivers and pit crew athletes. Like other serious competitors, motorsports athletes are looking for sound advice to improve their performance. Sports medicine professionals are poised to offer a great deal of expertise to offer motorsports athletes who face similar (dehydration, thermal strain) and unique (G-forces) challenges compared to other sports.
- Emerging Trends in Automotive Engineering | Vehicular Automation and Automatic Driving | Automotive vehicles and design technologies | Automotive cyber Security | Automotive Safety | Computer-aided design & manufacturing CAD & CAM | Automotive Ergonomics
Session Introduction
Kamyar Mehran
Queen Mary University of London, England
Title: Multi-physics sensor fusion for power module prognostics in xEVs
Biography:
Kamyar Mehran is a Lecturer in Power Engineering at Queen Mary University of London. His research interests include energy storages, DC/AC microgrids, SiC-based inverters, control and energy management systems with a number of publications and book chapters in the field. He recently recieves research grants totalling £600K on condition monitoring of xEV battery modules. He has prior academic experince in the universities of Warwick and Newcastle in UK and 10 years of industrial experience including CTO position for a university spin-off. He received his B.Sc. (Tehran, 99), M.Sc. (Newcastle, 2004) and Ph.D. (Newcastle, 2010) all in electronic and electrical engineering.
Abstract:
Power electronics underpins modern xEVs allowing efficient energy transfer between the vehicle battery system and the drive motors. These vehicles have to operate in a wide range of climates and geographies meaning that the electrical systems have to be designed to withstand significant overstresses, particularly from self-heating and sudden loading during normal operation. As a result, the power electronics are significantly over-designed to ensure sufficient reliability given the harsh operating conditions. To simplify construction, reduce costs and increase reliability, manufacturers are seeking ever-tighter system integration. In the future, wide-bandgap semiconductor materials such as SiC will allow significant improvements in power density and volumetric efficiency by closely coupling the signal and power stages and allowing the power stage to be integrated within the electrical machine, sharing the same cooling circuit. This level of integration poses a number of significant challenges as the heat transfer paths are interlinked and significantly more complex. In addition, the close thermal coupling with the machine will greatly increase the stress on the electrical and mounting connections, leading to bond wire degradation and unwanted stresses in the interface layer between the semiconductor material and the substrate. To address these challenges, we propose a multi-physics sensor fusion technique to provide accurate prognostics for highly integrated power electronic converters for electric vehicles. The real-time prognostics, accurately estimating state of health and the true age of the converter, will allow the vehicle management system to intelligently adjust the available power and cooling requirements.
Jahng Hyon Park
Hanyang University, South Korea
Title: Steering Angle Decision and Control for Lane Keeping Using LSTM neural networks
Biography:
J.H. Park has completed his PhD from Massachusetts Institute of Technology and has been a faculty member at the Department of Automotive Engineering, Hanyang University in Seoul, Korea. His acedemic interests include mobile robot, autonomous vehicles, and intelligent control.
Abstract:
Lane keeping Assistance Systems (LKAS) is one of the advanced driver assistance systems (ADAS) and have used mostly approaches of model based control for lane keeping functions. This kind of method requires precise vehicle dynamic models and they are highly nonlinear and complicated resulting in the complicated process for control design.
In order to alleviate the efforts for modeling, neural networks could be employed for the LKAS. However, since car driving is a highly dynamic, the long short-term memory (LSTM) recurrent neural networks (RNN) is a better candiadate for computing of the steering angle for the lane keeping system. The LSTM RNN prediction model is one of the artificial intelligence techniques that incorporate the time series without having to use the complicated vehicle model.
The input values of LSTM-RNN are the time-series array of the road coefficients obtained by processing the data from the vision sensor and the IMU sensor, and the output of the network is the vehicle steering angle. The actual steering angles obtained during the real road driving by human drivers are used for the network training. The implicit relation between the inputs and output is trained over time. After the LSTM-RNN prediction model is implemented and tained, the performance of the steering angle prediction is tested. The acquired steering angle from the network is given to the steering control system as a reference input. The effectiveness of the newapproach is verified through simulation.
Acknowledment
This work was supported by the Technology Innovation Program (10076338, Fault Detection and Diagnosis for ADAS-Sensors and Hazardous Analysis and Development of Fault Management Strategy) funded By the Ministry of Trade, Industry & Energy (MOTIE, Korea).
Shun Hattori
Doshisha University, Japan
Title: Change of Force between Shafts and Winding Pitch Radius of Chain Type Continuously Variable Transmission at Steady State
Biography:
Shun Hattori is a graduate student of Doshisha University, Kyoto, in Japan. His major is mechanical engineering. He is studying on power transmission mechanism of chain belt type continously variable transmissions. His dream is to get married with tender girl in a loving home with a productive work for developing new mechanical power transmission after completion of master course.
Abstract:
The objective of this study is to clarify the mechanism for changing axial force and winding pitch radius of a chain type CVT at steady state. Pulley thrust, input rotational speed, and speed ratio were kept constant during experiment, while input torque was steadily increased from 0 Nm up to the state of sliding slip. The axial force was measured by a load cell. In addition, strain on the surface of rocker pin was measured by strain gauges. Nonlinear decrease of pitch radius of the chain belt was observed at the entrance of driving pulley while nonlinear increase of that was oppositely observed at the exit. The estimated results of radial displacement of the chain belt calculated with geometrical relationship were agreed with the experimental data, when the tilt of movable sheave was considered. It was shown that radial displacement of the chain belt was dominated by the change of observed wedge angle of driving pulley due to the tilt of movable sheave. In addition, large transmittable torque was measured when a rigid pulley was applied to driving pulley, compared with that when a movable pulley was used. It was suggested that contact arc in driving pulley was decreased due to the change of pitch radius of chain belt. It was found that the axial forces were changed with the change of winding pitch radius of chain belt because total of reaction forces in contraction direction was changed by the change of practical contact arc between chain belt and pulley.
Biography:
Dr. Mabuma has completed his doctoral study/PhD in Engineering from a joint research programm a t University Stuttgart/RWTH University Aachen/Leibniz University Hannover. He has published different scientific papers in reputed journals and has supported companies and research institutes such as Robert Bosch GmbH. He is now working as technical leader and key account manager in the automotive industry.
Abstract:
The main goal of this contribution is to introduce an application of the rules of platform thinking to conceive profitable products or services in aftersales of the automotive industry. Platform thinking can be defined as the art of conceptualizing and implementing inclusive places (physical or virtual) where different actors can interact, communicate, co-create and share. A successful platform is able to attract platform users, facilitate the interaction and exchange of information and foster co-creation of value.
To create a successful platform it is crucial to decide which platform users or target groups need to be brought together. Potential target groups are car drivers, car dealers, fleet managers and third parties such as car insurance companies and towing services.
The challenge is then to visualize a possible interaction between these groups which can lead to creation of value for each group during an exchange of information. We have to define which information is attractive to a platform user in order to specifically address the needs of another platform user. For instance, information about the mileage is a great deal to a car insurance company in order to create value for its own business.
Finally, the pricing model for using the platform has to be well thought out in order to ensure profitability for the platform owner. A few alternatives would be to charge fees for each login on the platform or each data package transferred between users depending on the user´s behavior.