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LIGHT WEIGHTING OF ADDITIVE MANUFACTURED PARTS FOR AUTOMOTIVE PRODUCTION APPLICATIONS THROUGH TOPOLOGY OPTIMIZATION TECHNIQUES

General Motors Technical Center India-Abhijith Naik, T Sujan, Suraj Desai, Saravanakumar Shanmugam
  • Technical Paper
  • 2019-28-2544
To be published on 2019-11-21 by SAE International in United States
Rapidly enhancing engineering techniques to manufacture components in quick turnaround time have gained importance in recent time. Manufacturing strategies like Additive Manufacturing (AM) are a key enabler for achieving them. Unlike traditional manufacturing techniques such as injection molding, casting etc., AM unites advanced materials, machines, and software which will be critical for Industry 4.0. Successful application of AM involves a specific combination and understanding of these three key elements. In this paper the AM approach used is Fused Deposition Modelling (FDM). Since material costs contribute to 60% of the overall FDM costs, it becomes a necessity to optimize the material consumption of the produced parts. This paper reports case studies of 3D printed parts used in an Automobile plant’s production aids, which utilize computational methods(CAE), topology optimization and FDM constrains (build directions) to manufacture the part in the most optimal way. These methodologies were used to validate the current operating conditions, optimize the design, increase the stiffness of the original part and reduce the material costs. The newly optimized designs were verified by successfully passing…
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Vision based solution for auto- maneuvering of vehicle for emerging market

General Motors Technical Center India-Chandraprakash lalwani
General Motors Technical Center-Souvik Bose, Ashwani Kumar Singh, D V Ram Kumar Singampalli
  • Technical Paper
  • 2019-28-2517
To be published on 2019-11-21 by SAE International in United States
Vision based solution for auto- maneuvering of vehicle for emerging market: Author/Co-Author: Singh Ashwani, SDV Ram Kumar, Bose Souvik, Lalwani Chandraprakash General Motors Technical Centre India Key words: Image Processing, Gap finding, virtual/Imaginary lines, Advance Driver Assist System (ADAS), Vehicle to vehicle(V2V)/Vehicle to Infrastructure(V2I/V2X) Research & Engineering Objective: For the various levels of autonomous, the current perception algorithms involve considerable number of sensor inputs like cameras, radars and Lidars and their fusion logics. The planning route for the vehicle navigation is done through map information which is highly volatile and keep changing many at times. Existing steering assist feature during a curve is available by combining additional driver monitoring camera & 360 degree camera. The complexity is very high in the implementation and computation of these algorithm. These solutions are not cost-effective for emerging markets. Non-availability of required infrastructure in developing countries is one of the additional constrain. Feature unavailability due to road infrastructure (ex: poor or no lane markings), bad weather will lead to higher customer dissatisfaction. The objective is to develop a logic/study…
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Changes in user experiences of electric vehicles

General Motors Technical Center India-Rudrappa Madagunki
General Motors LLC-Pandurang Baliga, Tulasi KL
  • Technical Paper
  • 2019-28-2489
To be published on 2019-11-21 by SAE International in United States
Research Objective The objective of the paper is to research what are the changes in experiences being brought about due to the advent of Electric Vehicles (EVs). EVs are silent, have less complex propulsion system, and have free space under the hood, amongst other things. Each change brings about both good and bad experiences across the spectrum of users. Some of the bad experiences can be safety incidents leading to death as well. Researching the areas that are harmful to end users, including pedestrians, will be our focus area. Methodology Our methodology will look at the changes at the vehicle architecture level which are inherent to the EV design. Research how are the experiences so far due to these changes. Are these just inconveniences or safety hazards? EVs have excellent NVH characteristics. A farmer may love a silent tractor, but a racing enthusiast may not like a relatively silent sports car. A silent armored vehicle may be what the army needs, but a silent car’s approach may be a last-minute surprise to an unsuspecting pedestrian,…
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SELF EXPRESSIVE & SELF HEALING CLOSURES HARDWARES FOR AUTONOMOUS AND SHARED MOBILITY

General Motors Technical Center India-Vijayasarathy Subramanian, Biju Kumar, Masani Sivakrishna, Anandakumar Marappan
  • Technical Paper
  • 2019-28-2525
To be published on 2019-11-21 by SAE International in United States
Shared Mobility is changing the trends in Automotive Industry and its one of the Disruptions. The current vehicle customer usage and life of components are designed majorly for personal vehicle and with factors that comprehend usage of shared vehicles. The usage pattern for customer differ between personal vehicle, shared vehicle & Taxi. In the era of Autonomous and Shared mobility systems, the customer usage and expectation is high. The vehicle needs systems that will control customer interactions (Self-Expressive) & fix the issues on their own (Self-Healing). These two systems / methods will help in increasing customer satisfaction and life of the vehicle. We will be focusing on vehicle Closure hardware & mechanisms and look for opportunities to improve product life and customer experience in ride share and shared mobility vehicles by enabling integrated designs, which will Self-Express & Self-Heal. Vehicle closures having direct human interfaces with components like closures, handle & other hardware's will be tracked for their performance parameters and usage pattern. The performance parameters will be tracked for every customer and mapped to…
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ENHANCE STRENGTH, ACCURACY AND PRECISION OF THE 3D PRINTED ASSEMBLY AID GAUGES

General Motors Technical Center India-Ramesh Kavalur, Raghavendra Rao
  • Technical Paper
  • 2019-28-2568
To be published on 2019-11-21 by SAE International in United States
ENHANCE STRENGTH, ACCURACY AND PRECISION OF THE 3D PRINTED ASSEMBLY AID GAUGES Ramesh Kavalur1, Raghavendra Rao 1 1 Body in White, Manufacturing Engineering, General Motors Technical Centre India Pvt. Ltd, India, Keywords - Additive manufacturing, assembly aid gauges, 3D printer. Research Objective - Automotive manufacturing impressively implementing 3D printed jigs and fixtures. Traditional manufacturing of metal assembly aid gauges have limitations such as lead time and causes dent and rough marks on the outer panel of the body. On the other hand, 3D printed jigs and fixtures, demands more time (depends on complexity), have low level of precision and they offer lower strength. It is observed that this occurs because of the inefficient design and manufacturing without understanding the functionality and capability of the 3D printer. The primary objective of this study is to examine, design & develop 3D printed jigs and fixture to optimize the product, achieve required precision and functionality with improvement in the strength of the product. Methodology - In order to examine, detail examination of existing 3D printed part were studied.…
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Proposed Model to Implement a Blockchain for Secure Vehicle to Vehicle Communication

General Motors Technical Center India-Surya P. Palavalasa
  • Technical Paper
  • 2019-28-2433
To be published on 2019-11-21 by SAE International in United States
This paper proposes a model to implement a blockchain network that can host a system of autonomous vehicles which communicate through generic V2V protocols like DSRC and CV2X. The blockchain will be designed to function like a global database for V2V communication. The purpose behind the proposal of this model was to ensure a transparent and secure network between all autonomous vehicles which indirectly leads to reduced traffic congestion and takes us a step closer to zero crashes. This is made possible by the blockchain ledger’s enhanced encryption systems.
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STATISTICAL ANALYSIS OF LOW CYCLE FATIGUE PROPERTIES IN METALS FOR ROBUST DESIGN

General Motors Technical Center India-Karthigan Ganesan, Biswajit Tripathy
General Motors Global Technical Center-Abolhassan Khosrovaneh
  • Technical Paper
  • 2019-28-2576
To be published on 2019-11-21 by SAE International in United States
Objective: In ground vehicle industry, strain life approach is commonly used for predicting fatigue life. This approach requires use of fatigue material properties such as fatigue strength coefficient (σf'), fatigue strength exponent (b), fatigue ductility coefficient (εf'), fatigue ductility exponent (c), cyclic strength coefficient (K′) and cyclic strain hardening exponent (n′). These properties are obtained from stable hysteresis loop of constant amplitude strain-controlled uniaxial fatigue tests. Usually fatigue material properties represent 50th percentile experimental data and doesn't account possible material variation in the fatigue life calculation. However, for robust design of vehicle components, variation in material properties need to be taken into account. In this paper, methodology to develop 5th percentile (B5), 10th percentile (B10) and 20th percentile (B20) fatigue material properties are discussed. Possible material variation in fatigue life prediction is included as B5, B10 and B20 fatigue material properties. Methodology: Fatigue strength coefficient (σf') and fatigue strength exponent (b) are obtained by performing a linear regression on true stress amplitude (∆σ/2) versus reversals to failure (2Nf) in log-log scale. Fatigue ductility coefficient (εf')…
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Design of Additive Manufactured Thermoplastic Component as FMVSS 201U Countermeasure

General Motors Technical Center India-Swaroop Kavi
  • Technical Paper
  • 2019-28-2547
To be published on 2019-11-21 by SAE International in United States
Research and/or Engineering Questing/Objectives: Safety of the occupant in passenger cars is one of the regulatory requirements in many developed countries. This includes upper interior head impact load case of the unbelted occupant during crash (FMVSS 201U) as one of them. During a crash event the occupant head can collide with the interior parts of the vehicle, such as a headliner, pillar trim and other subsequent components in the loading direction. Injury on the head is quantified in terms of the Head Injury Criterion of a crash test dummy (HIC(d)) value which should be less than 1000 per standard. Several ways can be adopted to reduce the HIC(d) value. These include a change in the design of ribs in the safety plastic components, headliner profile change, use of countermeasure foam between headliner and the exterior sheet metal parts, or a combination of any of these to absorb the energy of impact. Recent developments in the field of manufacturing, such as the Additive Manufacturing (AM) method, have provided an opportunity to design and manufacture components with…
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Electrification System Modeling with Machine/Deep Learning for Virtual Drive Quality Prediction

General Motors Technical Center India-Brijesh Borkar, John Bosco Maria Francis, Pankaj Arora
  • Technical Paper
  • 2019-28-2418
To be published on 2019-11-21 by SAE International in United States
A virtual 'model' is generally a mathematical surrogate of a physical system and when well correlated, serves as a basis for understanding the physical system in part or in entirety. Drive Quality defines a driver's 'experience' of a blend of controlled responses to an applied input. The 'experience' encompasses physical, biological and bio-chemical perception of vehicular motion by the human body. In the automotive domain, many physical modeling tools are used to model the sub-components and its integration at the system level. Physical Modeling requires high domain expertise and is not only time consuming but is also very 'compute-resource' intensive. In the path to achieving 'vDQP (Virtual Drive Quality Prediction)' goal, one of the requirements is to establish 'well-correlated' virtual environments of high fidelity with respect to standard test maneuvers. This helps in advancing many developmental activities from a Controls and Calibration aspect. Recently, machine/deep learning have proven to be very effective in pattern recognition, classification tasks and human-level control to model highly nonlinear real world systems. This paper investigates the effectiveness of deep learning…
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SIMULATION OF SOFTENING AND RUPTURE IN MULTILAYERED FUEL TANK MATERIAL

General Motors Technical Center India-Vijaya Kumar R L, Biswajit Tripathy, Jayaraj Radhakrishnan
  • Technical Paper
  • 2019-28-2557
To be published on 2019-11-21 by SAE International in United States
Research and/or Engineering Questions/Objective Plastic automotive fuel tanks made up of blow molded, multi-layered, high-density polyethylene (HDPE) material can take complex shapes with varying thickness. Accidental drop of fuel tank from a height during handling can lead to development of cracks. Damage can also occur due to an impact during a crash. This can be catastrophic due to flammability of the fuel. The objective of this work is to characterize and develop a failure model for the fuel tank material to simulate damage and enhance predictive capability of CAE for chassis and safety load cases. Methodology Different aspects were considered to develop a characterization and modelling strategy for the HDPE fuel tank. Material properties can be influenced by factors such as, service temperature, rate of deformation, state of stress etc. Hence, samples cut-out from different regions of the fuel tank were subjected to a variety of tests such as tensile test at different strain rates viz. 0.01/s, 0.1/s, 1/s, 10/s and 100/s, compression, shear, flexure and instrumented dart impact tests at different temperatures, -40°C, 23°C…