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EDGE-QUALITY EFFECTS ON MECHANICAL PROPERTIES OF STAMPED NON-ORIENTED ELECTRICAL STEEL

General Motors Technical Center India-Virupakshappa Lakkonavar, Swaroop Kavi
General Motors LLC-Peggy Jones, Margarita Thompson, Yew Sum Leong, Paul Crepeau
  • Technical Paper
  • 2020-01-1072
To be published on 2020-04-14 by SAE International in United States
The market for electric vehicles and hybrid electric vehicles is expected to grow in the coming years, which is increasing interest in design optimization of electric motors for automotive applications. Under demanding duty cycles, the moving part within a motor, the rotor, may experience varying stresses induced by centrifugal force, a necessary condition for fatigue. Rotors contain hundreds of electrical steel laminations produced by stamping, which creates a characteristic edge structure comprising rollover, shear and tear zones, plus a burr. Fatigue properties are commonly reported with specimens having polished edges. Since surface condition is known to affect fatigue strength, an experiment was conducted to determine the effect of sample preparation in stamped specimens. Tensile properties were unaffected by polishing. In contrast, polishing was shown to increase fatigue strength by approximately 10-20% in the range of 105-107 cycles to failure.
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Machine Learning Approach To Predict Aerodynamics Performance of Under-Body Drag Enablers

General Motors Technical Center India-Pradip Dube, Sadashiv Hiravennavar
  • Technical Paper
  • 2020-01-0684
To be published on 2020-04-14 by SAE International in United States
Implementing stringent emission norm and fuel economy requirement in the coming decade will be very challenging to the whole automotive industry. Aerodynamic losses contributes upto 13% to overall fuel economy and aerodynamicists will be challenged to have optimum content on the vehicle to reduce this loss. Improving Aerodynamic performance of ground vehicles has already reached its peak and the industry is moving towards active mechanisms to improve performance. Calibrating or simulating these active mechanisms in the tunnel or in Computational Fluid Dynamics (CFD) would be very challenging as the model complexity increases. Computationally expensive CFD models are required to predict the transient behaviors of model complexity. To balance these complexities and to reduce cost, objective of this piece of work is to explore feasibility of statistical data analytics and machine learning methods to come up with good predictive meta-models with least data, which can help to make technical decisions. Machine Learning (ML) is the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying…
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Light-Weighting of Additive Manufactured Automotive Fixtures through Topology Optimization Techniques

General Motors Technical Center India-Abhijith Naik, T Sujan, Suraj Desai, Saravanakumar Shanmugam
  • Technical Paper
  • 2019-28-2544
Published 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 times. Manufacturing strategies like Additive Manufacturing (AM) are a key enabler for achieving them. Unlike traditional manufacturing techniques like injection molding, casting etc.; AM unites advanced materials, machines, and software which will be critical for the fourth industrial revolution known as 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 parts. This paper reports the case studies of 3D-printed Automotive Fixtures which utilize computational methods (CAE), topology optimization and FDM constrains (build directions) to manufacture the part. 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 successfully passing the Finite Element Analysis tests. The components have been printed and…
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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
Published 2019-11-21 by SAE International in United States
Advance Active Safety Systems play a preventive role in mitigating crashes and accidents by providing warning, additional assistance to the driver and maneuverability of vehicle by itself. Some of the features include forward collision warning system and lane departure warning system activate a warning alert when potentially dangerous situations are detected. These active safety features present in developed markets work with Fusion based algorithm combining Radar, Lidar, Camera, Ultrasonic sensor’s input. Application of these algorithms are Intelligent Cruise Control, Collision avoidance, parking assistance, identify pedestrian etc. The complexity of the algorithm, cost of the control unit and road infrastructure are hindrance to emerging market. The solution presented in this paper is towards camera-based solution, describing the method to determine the predictive path, that is obstacle free space and use the predictive space to navigate or steer. This paper focuses on vehicle maneuverability in poor road infrastructure (lane irregularities or no lane marking) by using only cameras.
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Self-Expressive & Self-Healing Closures Hardwares for Autonomous & Shared Mobility

General Motors Technical Center India-Vijayasarathy Subramanian, Biju Kumar, Masani Sivakrishna, Anandakumar Marappan
  • Technical Paper
  • 2019-28-2525
Published 2019-11-21 by SAE International in United States
Shared Mobility is changing mobility trends of 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 of vehicle condition on each & every ride of vehicle will be a vehicle in good condition on each ride. The vehicle needs systems that will guide or fix the issues on its own, to improve customer satisfaction. We also need a transformation in customer behavior pattern to use shared mobility vehicle as their personal vehicle to improve the life of vehicle hardwares & reduce warranty cost. We will be focusing on Vehicle Closure hardware & mechanisms as that will be the first and major interaction point for customers in vehicle. This gives us an opportunity to improve product life and customer experience in ride share and shared mobility…
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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
Published 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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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
Published 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 (DQ) 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 Analysis, Controls and Calibration standpoint. 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…
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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
Published 2019-11-21 by SAE International in United States
Multi-layered, high-density polyethylene (HDPE) fuel tanks are increasingly being used in automobiles due to advantages such as shape flexibility, low weight and corrosion resistance. Though, HDPE fuel tanks are perceived to be safer as compared to metallic tanks, the material properties are influenced by service temperature. At higher temperatures (more than 80oC), plastic fuel tanks can soften, sag and eventually spill out the fuel, while the extreme cold (less than -20°C) can lead to potential cracking problems. Damage may also occur due to accidental drop while handling or due to an impact from a flying shrapnel. 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 plastic fuel tank material to simulate damage and enhance predictive capability of CAE for chassis and safety load cases. Different factors influencing the material properties such as service temperature, rate of deformation, state of stress etc. were considered to develop a characterization and modelling strategy for the HDPE fuel tank material. Samples cut-out from…
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Effectiveness of Power-Law Profile Indentations on Structure-Borne Noise

General Motors Technical Center India-Pranoy Sureshbabu Nair, Nilankan Karmakar, Seshagiri Rao Maddipati
General Motors-Jeffrey Curtis
Published 2019-06-05 by SAE International in United States
A study on the effect of indenting power-law shaped profiles on the flexible structures for investigating the vibration damping characteristics using computational simulation method is discussed. The simulation results are checked to see the impact of such features on the damping behavior of flexible structures responsible for radiating noise when excited with fluctuating loads. Though the conventional remedies for solving Noise and vibration issues generally involves tuning of structure stiffness or damping treatment this paper gives an insight on the idea of manipulation of elastic waves within the flexible structure itself to minimize the cross-reflections of the mechanical waves. The simulation studies mentioned in this paper not only hovers over the effectiveness of such features but also will be helpful for the engineers to look through a different perspective while solving N&V issues using simulation tools. In this paper, different studies are discussed to see the impact of such features on the damping effect of the vibrating structure comparing mobility response and far-field sound pressure response as well. Propagation of waves within the structure is…
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After Market Portable Drag Enablers to Improve Fuel Economy of on Road Car

General Motors Technical Center India-Pawan Kumar, Irshad Mahammad
Published 2019-01-09 by SAE International in United States
Aerodynamic performance of on-road vehicle can be improved by using portable enablers on rear portion of the vehicle which can be attached or detached by the owner himself. Objective of this study is to explore the possibility of using such portable enablers to substantially reduce the drag of the vehicle. Enablers with specific convex shapes are created on various positions of rear portion of vehicle and simulated with CFD solver FLUENT. Compact sedan vehicle was considered in this study. Preprocessing is performed and specific fluid domains are captured. Generally, aerodynamic enablers are integrated parts of the vehicle. This paper emphasizes on consideration of portable enablers which can be used while cruising for longer distances. Drag improvement of ΔCD = 0.006~0.009 was achieved by introducing the specific enabler based on its position, shape and dimension. This paper also suggests methods of attachment of portable enabler to the vehicle. Simulation is performed using realizable k-ε model with non-equilibrium wall functions for turbulence modeling. Drag due to heat exchangers is included in the total drag of the vehicle.…
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