3^rd International Conference and Exhibition on Automobile Engineering September 28-29, 2017 Berlin, Germany

Jana Dittmann has her expertise in Multimedia And Security Research. As a leader of the working group on multimedia and security, she has years of experience Research, Evaluation, Teaching and Administration with a special focus on the holistic evaluation of IT-security, including embedded systems of which automotivesystems are a prime example. Under her leadership, a model of the forensic process was established that is capable of identifying potential sources of data and which can aid in their integrity and authenticity preserving acquisition, investigation, analysis and documentation.

Modern cars are complex systems incorporating a wide range of actuators, sensors, ECUs (Electronic Control Units) and the means of connecting these components in order to implement basic functionality as well as advanced driver assistance systems. Generally, the firmware powering the ECUs is closed-source, which poses a serious challenge for investigators with the aim of event reconstruction. Several measures are taken by the manufacturers in order to prevent reverse engineering. This is mostly due to intellectual property protection but is also hindering or even preventing a successful investigation. With the growing interconnectivity between vehicles and their surroundings (both visible/easily identifiable such as cables and sockets and hidden channels, e.g. using the mobile phone/eCall subsystem for telemetrics) new possibilities and new attack vectors arise. Attacks on in-vehicle systems might aim at undermining the privacy of the user but might as well, given the fast-paced environment in which vehicles operate, and aim at the safety of occupants and bystanders. While various research, including the prevention and event reconstruction of such attacks, is being done on these security issues at the current time new challenges loom on the horizon. (Semi)autonomous vehicles carry a host of so far unanswered questions with them – like of the responsibility for a crash caused by a (Semi)autonomous vehicle. Discussing the deep ethical and legal implications of such a question is beyond the scope of this talk. Instead we want to focus on the question which impact (Semi-)autonomous vehicles and their growing interconnectivity have on the ability of a forensic investigator to determine the course of action and the root-causes of incidents involving modern day vehicles.

Benoit Boulet is an Associate Dean (Research & Innovation) of the Faculty of Engineering at McGill University and an Associate Professor in the Department of Electrical and Computer Engineering. He has completed his Bachelor's degree from Université Laval in 1990, and Master of Engineering degree from McGill University in 1992, and a PhD degree from the University of Toronto in 1996, all in electrical engineering. He is a registered Professional Engineer in the province of Québec. He is a member of the McGill Centre for Intelligent Machines and his research areas include the design and control of electric vehicles and green energy systems, robust control of biomedical systems, and robust industrial control.

As the story goes, Tesla tried to develop a two-speed ratio transmission for its Roadster around 2007. But after a series of failures that delayed production and almost tanked the company, a decision was made to use a single-speed-ratio transmission. Tesla’s ensued success with single-speed-ratio drivetrains, also adopted by other electric car manufacturers, leads to the question: Is there a need for multispeed drivetrains in electric vehicles? If so, for what class of vehicles? Is it economical? Our research has shown that the electrification of vehicles larger than class 3 is where multispeed transmissions may be considered, but perhaps not currently for smaller vehicles, apart for high-performance race cars or GTs. The cost question, while crucial in the automotive industry, is very difficult to settle for a new electric powertrain design because the production volumes are still very small. Given a set of performance specs for the vehicle, and assuming peak power is not the main constraint, is it better to choose a larger motor and power inverter for a single-speed-ratio architecture, or to select a smaller inverter and motor coupled to a two-speed transmission? To help resolve this question, we studied the cost-reliability-performance of EV powertrains to come up with formulas that could be used in a design optimization trading off the cost of the powertrain versus its performance and reliability. On the performance side, we designed a two-speed clutch-less automated manual transmission (AMT) and tested it on a compact electric car for dynamometer and road testing. Then, we studied friction in the synchromesh of an AMT to design a feedback controller for the synchronizer’s cone clutch. This was done to control friction at a favourable location in the mixed lubrication regime on the Stribeck curve that maximizes torque transfer while minimizing wear during gear shifts. A new type of two-speed transmission was also designed to alleviate the torque dip of the AMT while avoiding the use of a clutch. The resulting patented Dual Brake Transmission (DBT) has shown promise for high efficiency, high torque and smooth operation of EVs.

Jorge Varela Barreras has completed his Postdoctral degree in Engineering Science at University of Oxford, UK, with interests in novel electric vehicle concepts and lithium-ion battery modeling, simulation, emulation, iagnostics, prognostics and management. He pursued his PhD in Battery Management at Aalborg University, Denmark, where he also received MSc degree in Power Electronics. Previously, he received MSc degree in Electrical Engineering from University of Vigo, Spain, where he co-founded a photovoltaic consulting company. He is a founder member of the Danish Battery Society and the representative of the Oxford Research Staff Society in the Department of Engineering Science, University of Oxford. He serves in the Editorial Board of Frontiers in Energy Research. He has been a Guest Lecturer at University Carlos III (2016), Aalborg University (2014-16) and, Faculty of engineering of University of Porto (2015), University of Sfax (2016). From 2017,he is the major Lecturer in Engineering at the Oxford Tradition academic program, held in Pembroke College and Corpus Christi College.

A lithium-ion battery pack consists of a number of cells in a series-parallel arrangement. The series connection, like in any chain, makes the performance limited by the weakest cell. If the cells were identical, this would not be a problem. However, there are cell-to-cell differ  ences, which increase over battery lifetime, that lead to limited electrical performance and uneven temperature distributions. Nowadays, automotive industry overcomes this problem in the design of battery packs for Electric Vehicles partially by adopting the so-called passive balancing systems. These systems carry out selective discharge of cells during battery charging, allowing all the cells to be fully-charged at the end-of-charge. Thus, losses in useful capacity related to differences in initial stateof- charge are compensated. Active balancing systems have also been proposed. They conduct selective dis/charge of cells during dis/charging, allowing all cells to be always at a similar state-of-charge level. Thus, losses in useful capacity related to differences in state-of-charge at any time are minimized. However, they do not get the full endorsement of automotive industry, which usually considers the partial advantages offered to be insufficient to justify the extra costs and complexity. Our research aims to bring aparadigm shift, by improving the design and control of these systems. The goal is to overcome not some, but all the problems related with cell-to-cell variations, by developing a smart balancing system (SBS) that makes the performance of any battery pack virtually ideal. The SBS transfers the energy between cells in such a smart way that the temperatures are minimized and equalized, and the electrical performance is optimized, in terms of losses, power capability and useful capacity. Potential advantages in Electric Vehicle performance include extended driving range, extended operation without de-rating the max. available power and longer battery lifespan.

PV Aravind is an Associate Professor at Delft University of Technology, The Netherlands (Faculty of Mechanical,Maritime and Materials Engineering). He teaches  courses on Thermodynamics of Energy Conversion and Fuel Cell Systems. He also teaches at Technical University Munich in Germany and contributes to a course at KU Leuven in Belgium. He is/was involved in several national, European and international energy related research projects focusing on fuel cell systems. Currently, he supervises a team of ten PhD students, three Postdoctoral Researchers and several MSc students. He is a member of the International Energy Agency SOFC Annex and is also in the steering committee of European Energy Research Alliance for Hydrogen and Fuel Cells.

Automobile industry is expected to change significantly in the coming years and decades. A convenient, technically and economically viable and environmentally friendly transportation system for the future needs to be developed. This requires a comparison between different technical choices based on best possible designs achievable. The role of hydrogen and fuel cells in the future transportation systems is being widely debated. As they are getting continuously compared with other possible options, for example with battery vehicles, it is necessary that efficient system concepts for fuel cell based transportation systems are developed.In this paper, we present an approach to increase the efficiencies while using different fuels for  ransportation applications, by making use of different types of fuel cells. A concept is presented in which a high temperature fuel cell is used as an electricity producing fuel reformer, in this case a Solid Oxide Fuel Cell (SOFC) and low temperature fuel cells onboard for vehicle propulsion, in this case Proton Exchange Membrane Fuel Cells (PEMFC). A trigeneration system fed with natural gas and capable of producing electricity, heat, and hydrogen is proposed. Two modes are presented: a Car as Power Plant (CaPP) mode, in which fuel cell electric vehicles(FCEVs) act as energy and water producers while parked; and a pump mode, in which compressed hydrogen is produced and pumped to the vehicle’s fuel tank. Different reforming options are presented and compared, a catalytic reformer (CR), and a solid oxide fuel cell operating as reformer (SOFCR). Additionally, the option of integrating carbon capture and storage (CCS) is also presented. Results indicate that the SOFCR unit significantly reduces the energy destruction resulting a trigeneration energy efficiency of around 60%. Additionally, a brief presentation on applying the concept for other types of vehicles also is presented.

Siniša Šegvić completed his PhD degree in 2004 at the University of Zagreb. He has spent one year as a Postdoctoral Researcher at IRISA Rennes in 2006 and another year as a Postdoctoral Researcher at TU Graz in 2007. Currently, he is an Associate Professor at University of Zagreb. He is a program committee member of the VISAPP 2018 conference and an Associate Editor of the Journal of Computing and Information Technology. His research expertise is in the field of computer vision and deep learning, with special interest in applications for safe traffic. He published more than 50 national and international scientific papers

Semantic segmentation performs pixel-level image understanding by associating each image pixel with a meaningful class such as 'road', 'terrain', 'sidewalk' or 'person'. The resulting semantic map reveals the kind of surface terrain in front of the vehicle, and may be used to recover the traversability map required for motion planning. This capability makes semantic segmentation one of t he most important computer vision tasks in the automotive context. Today, state of the art semantic segmentation results are obtained with deep end-to-end trained convolutional models. However, direct application of popular and well understood image classification architectures would lead to poor semantic segmentation performance. The main obstacles are large variation of object scale, and strict memory limitations of contemporary GPUs. Recent works overcome these obstacles by careful architectural adaptations. As a result high semantic segmentation accuracy today can be achieved on large images in real-time, while more training data would likely further improve the results. Specifications of upcoming embedded hardware platforms promise low-power real-time onboardope ration and provide directions for exciting real-world applications.

H Can Koman works in Interior Quietness department of Ford Otosan, a joint venture to Ford motor company. His main work is focused on Aero-Acoustics, both experimental and computational. He has worked on light and heavy commercial vehicle projects from scratch to finish to deliver vehicles that would meet targeted customer expectations for flow related interior cabin noise.

As the powertrain noise of motor vehicles get silent, customers complain more of flow related noise (called wind noise in the industry) that is especially dominant at highway speeds. In order to produce silent vehicles, engineers need to make critical decisions at very early design phase to optimize the shape of the vehicle for least Aeroacoustic excitation. This poses a problem asexperimental methods are still dominant at this field and there is no physical bucks to conduct wind tunnel tests with at early design phaes. Moreover, companies that do not have a wind tunnel of their own face both financial and timing problems to conduct wind tunn l tests at outside facilities. For these reasons, applying computational methods to predict wind noise level over the side glass of a vehicle will help engineers to take actions at the very start of the design phase and decrease the amount of time that needs to be spent in the wind tunnel. This study aims at developing a reliable CFD based aero-acoustic simulation methodology for motor vehicles.Reliability of the methodology is tested by comparing calculation results with wind tunnel test results, which is done in two steps: In step one overall pressure fluctuations on the side glass of a light commercial vehicle are calculated and compared to the results of wind tunnel tests conducted with surface microphones. In step two: wooden obstacles are placed on a pillar of the same vehicle. Difference of surface pressure fluctuations on the side glass between base condition and the condition with the obstacle is both computationally calculated and tested in the wind tunnel. Two results are compared to understand methodology’s prediction capability for exterior surface changes.

Khaled R Asfar is a Professor of Mechanical Engineering at JUST University. He received his MSc and PhD degrees from Virginia Tech in 1980. He was a visitingscholar in Aerospace Engineering at Texas A & M University (2007-2008), and a visiting Professor at the School of Mechanical Engineering at Purdue University (2008-2010). He is the founder of The Center of Excellence for Innovative Projects and The Technological Incubator at JUST University. He received many scientific honors and awards such as the Hisham Hijjawi Award in 1995 and 2001, JUST Award for Scientific Distinction in 1997 and 2006, and the Alexander von Humboldt Research Fellowship in 1991-1992. He has published numerous articles in several fields and holds three US Patents and two US patent pending applications. He is an Associate Editor for the Journal of Vibration and Control, and editorial boards of three other journals.

In this work, an electro-mechanical direction sensor was designed and developed. The purpose of this electro-mechanical direction sensor is to measure the change in the heading angle for a wheeled ground vehicle. The mechanism used in our designed sensor is inspired from the ancient Chinese piece of mechanical art; The South Pointing Chariot. The south pointing chariot uses mechanical gears in a special arrangement in order to maintain a figure/pointer pointing to a fixed direction, whatever the chariot direction is The mechanical part of the South Pointing Chariot has been integrated with an electronic circuit to form the electro-mechanical direction sensor. The designed sensor can be used for vehicle guidance and control. The measured data of the electro-mechanical direction sensor has been compared to magnetic compass readings to validate its output. A test to drive a vehicle in a predefined path was performed using the feedback of the electro-mechanical direction sensor. The results showed good performance of the electromechanical direction sensor in measuring the change in the heading angle for a 3-wheeled vehicle and controlling it.

Statement of the Problem: The Vehicle Routing Problem (VRP) has various applications in real life. It illuminates in a wide field of transportation and  distribution, for example, transportation of people and things, movement service and garbage gathering.Subsequently, a proper choosing of vehicle routing has a broad impact factor to enhance the financial interests and fittingness of coordination’s planning. In this study the problem is as follows: have a number of vehicles which are used for transporting applications to instance place. Each vehicle starts from a main location at different times every day. The vehicle picks up applications from start locations to the instance place in many different routes and return back to the start location in at specific times every day, starting from early morning until the end of official working hours, on the following conditions: (1) Every location will be visited once in each route, and (2) The capacity of each vehicle is enough for all applications included in each route. Objectives: The proposed study attempt to find an optimal route results for VRP of any VRP using artificial intelligence methods. To achieve an optimal solution for VRP of VRP with the accompanying goals: To reduce the time consuming and distance for all routes.Which leads to the speedy transportation of customers to their locations, to reduce the transportation costs such as fuel utilization and additionally the vehicle upkeep costs, to implement the Capacitated Vehicle Routing Problem (CVRP) model for optimizing shuttle bus services. To implement the algorithm which can be used and applied for any problems in the like of VRP. Method: The Approach has been proposed based on two phases: firstly, find the shortest route for VRP to help anyorganization toreduce customer’s transportation costs by artificial intelligence methods is proposed to solve this problem as it is capable of solving many complex problems; secondly, identify The CVRP model is proposed for optimizing shuttle bus services. Finding: The findings outcome from this study have shown that: (1) A comprehensive listed of active artificial intelligence methods in solving vehicle routing problem for best transportation and distribution solutions; (2) Identified and established an evaluation criterion for artificial intelligence methods in solving vehicle routing problem for best transportation and distribution solutions; (3) Highlight the methods, based on hybrid crossover operation, for selecting the best route (4) artificial intelligence methods capable a shorter distance for routes. The proportion of reduction the distance for each route is relatively short, but the saving s in the distance becomes greater when calculating the total distances travelled by all buses daily or monthly. This applies also to the time factor thathas been reduced slightly based on the rate of reduction in the distances of the routes.

Sunil Pathak is specialized in gear engineering and advanced and hybrid manufacturing processes. He has been working in the field of gear engineering since last 7 years and advanced manufacturing and surface engineering over 5 years. He has conducted extensive research on advanced finishing of gears. He possesses specialized skills in gear finishing, gear metrology (micro, and macro-geometry) and measurement of gear accuracy. Presently he has been working in developing cold spray coatings as sustainable process for manufacturing of 3D additive manufacturing components and repair/remanufacturing engineering where he has specially gained experience in materials and remanufacturing engineering. He is also working on machining of difficult-to- machine materials using advanced machining processes such as EDM and WEDM. Dr. Pathak has published more than 15 International Journal Papers, 3 Book Chapters and 4 research articles in the proceedings of the international and national conferences

Gear is one of the most important mechanical elements, possibly even surpassing the wheel, of human civilization which is used to transmit motion and/or power mechanically and positively (i.e. without slip) with and without change in the direction and speed of rotation by the successive engagements of teeth cut on their periphery. Performance characteristics of a gear include its load carrying capacity, service life, operating performance, surface characteristics, wear characteristics, transmission characteristics and noise generation characteristics. All these are significantly affected by the surface characteristics of a gear which has two major components namely (i) surface quality which includes surface finish, micro-geometry (i.e. form and location errors), tooth flank topology and wear characteristics; and (ii) surface integrity aspects. The aim of the present work is discuss the effects of various parameters of micro-geometry on performance characteristics of a gear. Micro-geometry of a gear is evaluated in terms of form error and location error. Total profile error and total lead error are two components of form error while pitch error and run out are considered as two components of location error. Higher values of form error and location error in a gear lower its load carrying capacity and increases noise and errors in motion transfer during its use. In this paper authors presents a detailed description on the effects of micro-geometry parameters on performance of gears and also presents possible solution to avoid these flaws for noiseless and smooth performance of gears.

Andreea Balau has completed her PhD in System Engineering at Gheorghe Asachi Technical University of Iasi. As a PhD student,She worked in the framework of the EU co-financed BRAIN project “Invest in Intelligence”, her research focused on automotive driveline modelling and control and she was part-time teaching assistant on System Theory and Control Engineering topics. She is currently employed by TNO, the Dutch Organization of Applied Research, in the Powertrains

department. Her activities are related to after treatment modeling and control topics, predictive powertrain control topics and project leading roles. She is currently involved in different European projects like Transformers, EMC2, EcoDriver, HiFi-ELEMENTS and CERBERO.

The automotive market is currently undergoing two major transitions: Automation and Electrification, striving for cleaner and more efficient transportation solutions. As the vehicles transition from mostly mechanical systems to a complex mix of mechanical, electrical and software components, new challenges arise in the development processes around them. Advanced vehicle control strategies including automation, with their increasingly sophisticated ECU’s and sensors, pose challenges on development, verification and robustness, requiring advanced tools and facilities. These rely on various combinations of modelling and testing to accelerate complete development cycles. Vehicle electrification, together with green energy sources, offers a good outlook toward reducing the CO2 transport emission. Different battery technology defines the challenges for scaling up this technology. Battery prices drop significantly with new developments and wider usage. Whether the electrification of heavy duty transport targets full electric vehicles, already making their way on the market (e.g. electric buses and delivery trucks) or hybrid solutions (e.g. for long haul applications, although competing full-electric concepts are slowly emerging: e.g. Nikola One, Tesla Semi), a stronger focus on battery technology, modelling and control (including predictive thermal and charge management) is needed. This comes in the form of mixed simulation and testing, and requires strong links to the intended application. The pleanary speech will address these major transitions of the automotive world, and will provide more isight via a relevant case study.

Philipp Sandner is Head of the Frankfurt School Blockchain Center at the Frankfurt School of Finance and Management. The center was launched in February 2017 and analyzes implications of blockchain technology on companies and business models. It provides a platform for decision makers, startups, technology experts and industry professionals to exchange their knowledge and share their visions. He is a member of the FinTechRat of the Federal Ministry of Finance. His expertise in particular includes Blockchain Technology and its application in various industries but also concerns Digitization, Entrepreneurship and Innovation Management. Further, his core topics are Corporate Entrepreneurship, Digital Transformation, Fintech Startups and Intellectual Property Rights.

The sharing economy has gained in popularity in the recent years. More specifically, shared and on-demand goods such as bikes,cars, flat rooms or working spaces are increasing substantially in urban cities and promising solving optimization problems related to space, time and expenses, which are the most prevailing factors when living in a city. However, agency theory suggests that the relationship between service providers and governments comes with difficulties optimizing the merit model. This is where blockchain technology has a big potential to solve existing conflicts and inefficiencies by removing the need for intermediaries and substituting them with an automated, secure and self-sovereign transaction technology, such as Smart Contracts using the Ethereum blockchain. Additionally, embedding intelligence to shared products by connecting devices to the internet and “enabling them to sense, monitor, and authorize transfers between users, firms can economically participate in the collaborative consumption of their goods…”(Weber, T.A., 2017). This product intelligence, when used actively for collaborative consumption, can narrow down the gap between retail prices and the equilibrium, due to the tendency of decreasing ownership status. For now, retailers do profit most in the sharing economy from high-cost units and patient consumers. Also, a peer-to-peer economy tends to increase the consumer surplus and social welfare, which might become stronger when adding IoT and blockchain technology as additional components. Partly, this has socio-economically reasons and partly can be contributed to an improvement of environmental aspects. A study conducted with 363 car sharing participants in the Netherlands, has shown that there was a drop of 30% in car ownership as well as a 20% drop in car use. This has lead to a reduction of up to 390 kilograms of individual CO2 production per year.

Jared Moore is an independent energy consultant based in Washington DC advising on economy-wide decarbonization. He has published his papers in multiple peer reviewed journals including Environmental Science and Technology, Environmental Research Letters, Energy Procedia (GHGT-12), and the International Journal of Hydrogen Energy. He is also a contributing author of the book “Variable Renewable Energy and the Electricity Grid”. He has completed his BS in Mechanical Engineering from Rose-Hulman Institute of Technology in 2008 and a PhD in Engineering and Public Policy from Carnegie Mellon University in 2014.

Thermal Hydrogen is an energy economy engineered to enable economy-wide decarbonization through new chemical energy carriers. The economy is built upon the principle of using both byproducts of water (or CO2) electrolysis hydrogen (or CO) and pure oxygen. The pure oxygen is used to enable emissions free hydrocarbon utilization without “Carbon Capture”, just sequestration. The energy carrier produced from electrolysis is combined with the output of auto-thermal reforming to produce either methanol or ammonia. The methanol is envisioned to provide electric range for battery electric vehicles by using a solid oxide fuel cell (SOFC). The heat from the SOFC reforms the methanol back to syngas, and the syngas is oxidized and produces both electricity and heat. The purpose of using an SOFC is to enable oxidation of syngas rather than pure oxygen. SOFC’s also allow the products to be limited to CO2 and H2O, also known as carbonated water. Given the ease of handling carbonated water, it is envisioned to be stored onboard the vehicle and returned to the gas station for eventual sequestration and recycling. The advantage of plug-in hybrid SOFC vehicle is not limited to turning CO2 emissions into water production. Plug-hybrid SOFC vehicles require only a very small battery (for acceleration) and a very small fuel cell (for range). Just a 10-kWh battery is sufficient to provide acceleration (~110 kW) and range of ~50 km. The medium sized battery provides acceleration while the fuel cell provides heat and range with just a ~10 kW fuel cell.

Overall, the car provides the best of both electric and hydrocarbon worlds—lightweight, electric torque, and instantly refuellable.

Yasunori Ota is a value Engineering Trainer and has been practicing VE since 10 years. In relation to cost planning in particular, he took initiative in increasing

profitability by coordinating target value in the procurement, design, and production technology departments, providing a list of items for cost reduction, and

managing their progress.

This presentation introduces two specific approaches regarding the Value Engineering (VE) method - benchmarking VE and drawing VE. I have been concerned about how to come up with good ideas effectively. I have used various methods by trial and error in idea generation sessions. By doing so, I noticed two methods proved to be effective. One is benchmarking VE. It is used at the early development stage in order to coordinate the relationship between function and parts. Further, by applying this method to your competitors function and parts, you are able to ascertain the strengths and weaknesses of your company and you can think good idea from comparison contents. The other is drawing VE. It can be used before, during, and after production. Specifically, it reexamines the role of the instructions in the drawing (materials, dimensional tolerance, function of thickness, thickness of the board, post-processing). And you can think cost reduction idea from re-examines the role of the instructions in the drawing. Based on this, the method allows you to develop new solutions. I share these methods with other VE practitioners around the world in order to contribute to the promotion of VE.

Noise, Vibration, and Harshness (NVH) attribute is needed to be included in the vehicle structure design since improving the NVH characteristics enhances the ride quality experienced by the occupants. In this regard an efficient method to optimize the structural dynamic response of an automotive body is proposed considering the low-frequency NVH performances and the improvement of an automotive structure under the constraint of NVH behavior is investigated by using Design of Experiments (DOE) method. Design of experiments methodology is used for a screening of the design space and for the generation of approximation models while the thicknesses of plates consisting of a Body-In-Prime (BIP) of an automotive are employed as design variables for

optimisation whose objective is to increase the first torsional and bending natural frequencies. Central Composite Design (CCD) for DOE sampling and Response Surface Methodology (RSM) are employed to optimise the dynamic stiffness of an automotive body. Moreover, the effect of selected variables as well as their binary interactions, were modelled and the optimum conditions for rigidity improvement were obtained via the RSM. Furthermore, the validity of the proposed optimisation scheme is verified through CAE analysis. The results indicated that first torsion and bending natural frequency were improved without considerable increase in the body weight.

Tubular structures are one of the automotive frontal crash safety devices which can protect occupants during impact collisions apart from airbags and ABS braking system. These tubular energy absorbers are one-shot items, i.e., once plastically deformed, they are discarded and replaced. Thus, the design requirement for such device is usually to achieve high energy absorption with less weight, corresponding to high specific energy absorption (SEA), while keeping the reaction force low enough to minimize the injury and damage to people and cargos. Metal tubes with externally wrapped Glass fibers are one such candidate with notable high specific energy absorption capacity and mean crushing force compared with the metal tubes and hence proposed. Thus, this research work addresses the deformation behaviour and specific energy absorption capacity of combined geometry tubes made-up of aluminium overwrapped with glass fabric through static and impact experiments. The combined geometry tubes consist of cylindrical segment with end plain cap, hemispherical cap and shallow spherical cap which were fabricated using multi-stage deep drawing process. Hybrid composite aluminium tubes were prepared by wrapping glass fabric over the aluminium tubes with required thickness by hand lay up process. The energy absorption characteristics of different tube configurations were analyzed by varying thickness of the composite. Further, the performance of the hybrid tube was compared with bare aluminium tubes and it was found that the specific

energy absorption capacity of the hybrid tube is 10-20% higher than the aluminium bare tube. Overall, the study highlights the advantages of using hybrid tubes as best energy absorbers in automotive structures.

Taewon Park has expertise in analyzing mechanical system using computer aided design and simulation. He has developed a lot of multi-body dynamics (MBD)

programs based on rigid dynamics and flexible dynamics theories. The MBD program proposes an analytical model that can predict the dynamic behavior of the

system without making actual systems, which is of great significance in analyzing and evaluating the mechanical systems. Also, he proposed improved performance system based on optimization design and control design about analytical model.

The brake pads play a role in reducing the vehicle's velocity through frictional contact with a rotating disc. At this time, nonuniform contact pressure distribution is formed at the leading surface of the brake pad’s friction area. The non-uniform contact pressure distribution of the brake pads causes uneven wear of the brake pad. Therefore, the purpose of this study is to propose a design of a shape optimization method that minimizes the non-uniform contact pressure distribution. A phenomenon of the brake pad’s non-uniform contact pressure distribution was implemented from a coupled thermal-mechanical analysis using the finite element analysis model. Design variables and constraints were selected for shape optimization. The objective function is a quadratic regression model function that minimizes the non-uniform contact pressure distribution. The optimum value and the quadratic regression model function were verified through the analysis of variance table. Also, by using the verified quadratic regression model function, the non-uniform contact pressure distribution can be easily predicted by substituting design variable values without the coupled thermal-mechanical analysis. The amount of wear on the brake pads can be measured through brake dynamometer test. As a result of the test, the amount of wear at the leading surface of the friction area was high. Also, the uneven wear of the shapeoptimized pad was less than that of the original pad. In conclusion, the non-uniform contact pressure distribution of the brake pad was realized through the coupled thermal-mechanical analysis. The shape optimization was performed by deriving the quadratic regression model function which is the objective function using the analysis results. Finally, the reduction of the brake pad’s uneven wear was confirmed through the test.