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Transformational Technologies Reshaping Transportation – An Academia Perspective

Ohio State University-Giorgio Rizzoni, Qadeer Ahmed, Mukilan Arasu, Pradeep Sharma Oruganti
  • Technical Paper
  • 2019-01-2620
To be published on 2019-09-20 by SAE International in United States
No Abstract Available.
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Turbocharger Centrifugal Compressor Casing Treatment for Improved BPF Noise Using Computational Fluid Dynamics

Ohio State University-Rick Dehner, Ahmet Selamet
Ford Motor Company-Ahsanul Karim, Chris Tiernan, Keith Miazgowicz, Ted Mull
Published 2019-06-05 by SAE International in United States
The conventional ported shroud recirculation casing treatment elevates narrowband noise at blade pass frequency. A new ported shroud recirculating casing treatment was implemented in Ford’s 3.5L turbo gas engine as Noise Vibration and Harshness (NVH) counter measure to reduce whoosh (broadband flow noise) noise without elevating narrowband noise at blade pass frequency. The new ported shroud design incorporates holes between the main and secondary recirculating passage and a slight cross-sectional area reduction just upstream of the impeller. These design features reduce whoosh noise without elevating the first order and the sixth order tonal noise at blade pass frequency. The new ported shroud design decreases narrowband tonal noise sound pressure level by 3-6 dB in the low to mid flow region compared to the baseline design. Computational Fluid Dynamics (CFD) tools were used to develop this casing treatment design.
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Prediction of Broadband Noise in an Automotive Centrifugal Compressor with Three-Dimensional Computational Fluid Dynamics Detached Eddy Simulations

Ohio State University-Rick Dehner, Ahmet Selamet
Published 2019-06-05 by SAE International in United States
Centrifugal compressors for automotive turbochargers must operate over wide speed and flow ranges to provide the required air pressure and mass flow rate to the intake manifold of the internal combustion engines. At a fixed rotational speed, the flow field near the inducer of the impeller becomes increasingly unstable with decreasing flow rate, as the incidence angle grows between the air flow approaching the impeller, relative to the tangent of the main impeller blades at the leading edge. Flow field measurements conducted earlier have revealed that once the incidence angle exceeds a critical value (nearly independent of rotational speed) of approximately 15°, reversed flow near the periphery (blade tips) starts penetrating upstream of the impeller, with a high tangential velocity in the direction of impeller rotation. As the incidence angle is increased towards this critical value, whoosh noise elevates, where it remains high for a significant portion of the mid-flow operating range, before decreasing at further elevated incidence angles. To understand this phenomenon further, a detailed, three-dimensional (3D) computational fluid dynamics (CFD) model of the…
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Driver’s Response Prediction Using Naturalistic Data Set

SAE International Journal of Advances and Current Practices in Mobility

Ohio State University-Venkata Raghava Ravi Lanka, Dennis Guenther
SEA, Ltd.-Gary Heydinger
  • Journal Article
  • 2019-01-0128
Published 2019-04-02 by SAE International in United States
Evaluating the safety of Autonomous Vehicles (AV) is a challenging problem, especially in traffic conditions involving dynamic interactions. A thorough evaluation of the vehicle’s decisions at all possible critical scenarios is necessary for estimating and validating its safety. However, predicting the response of the vehicle to dynamic traffic conditions can be the first step in the complex problem of understanding vehicle’s behavior. This predicted response of the vehicle can be used in validating vehicle’s safety.In this paper, models based on Machine Learning were explored for predicting and classifying driver’s response. The Naturalistic Driving Study dataset (NDS), which is part of the Strategic Highway Research Program-2 (SHRP2) was used for training and validating these Machine Learning models. Various popular Machine Learning Algorithms were used for classifying and predicting driver’s response, such as Extremely Randomized Trees and Gaussian Mixture Model based Hidden Markov Model, which are widely used in multiple domains.For classifying driver’s response, longitudinal acceleration vs lateral acceleration plot (Ax-Ay plot) was divided into nine different classes and selected Machine Learning models were trained for predicting…
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Model Order Reduction for x-In the Loop (xIL) Simulation of Automotive Transmissions

Ohio State University-Clayton Thomas, Punit Tulpule, Shawn Midlam-Mohler
Published 2019-04-02 by SAE International in United States
Increasing complexity of automotive systems along with growing safety and performance requirements, is causing development cycle costs to swell. A common solution is to use a Model-Based Design (MBD) approach, particularly using x-In the Loop (xIL) simulation methods for Validation and Verification (V&V). MBD allows efficient workflow from offline control design using high-fidelity models to real time V&V using Hardware-in-the-Loop (HIL) simulations. It is very challenging to reduce the complex non-linear high-fidelity models to real-time capable models for HIL simulation. Current literature does not provide a standard approach for obtaining the HIL-capable reduced model for complex non-linear systems. In this paper we present an approach to perform model reduction in light of HIL-level requirements. The approach is presented using an example of a 10-speed automatic transmission. The system constitutes three subsystems - the hydraulic network, mechanical gearbox, and torque converter. In the first step, a high-fidelity model for each subsystem is built up from the component level using one-dimensional mechanics and zero-dimensional hydraulic fluid flow. Secondly, the model is reduced gradually to meet the real-time…
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Determine 24 GHz and 77 GHz Radar Characteristics of Surrogate Grass

Ohio State University-Chi-Chih Chen
Indiana University; Purdue University-Jun Lin, Stanley Chien, Qiang Yi, Yaobin Chen
Published 2019-04-02 by SAE International in United States
Road Departure Mitigation System (RDMS) is a new feature in vehicle active safety systems. It may not rely only on the lane marking for road edge detection, but other roadside objects This paper discusses the radar aspect of the RDMS testing on roads with grass road edges. Since the grass color may be different at different test sites and in different seasons, testing of RDMS with real grass road edge has the repeatability issue over time and locations. A solution is to develop surrogate grass that has the same characteristics of the representative real grass. Radar can be used in RDMS to identify road edges. The surrogate grass should be similar to representative real grass in color, LIDAR characteristics, and Radar characteristics. This paper provides the 24 GHz and 77 GHz radar characteristic specifications of surrogate grass.
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Evaluation of Harness Tightening Procedures for Child Restraint System (CRS) Sled Testing

Ohio State University-Julie Mansfield, Gretchen Baker, John Bolte
Published 2019-04-02 by SAE International in United States
Sled testing procedures should reflect a rigorous level of repeatability across trials and reproducibility across testing facilities. Currently, different testing facilities use various methods to set the harness tension for child restraint system (CRS) sled tests. The objective of this study is to identify which harness tightening procedure(s) produce tensions within a reasonable target range while showing adequate reproducibility, repeatability, and ease-of-use. Five harness tightening procedures were selected: A) FMVSS 213 procedure, B) a 3-prong tension gauge, C) ECE R44/R129 procedure, D) two finger method, and E) pinch test. Two CRS models were instrumented with a tension load cell in the harness system. Seven sled room operators were recruited to perform each of the five harness tightening procedures for ten repetitions apiece on both instrumented CRS using a Hybrid III 3-year-old. The static harness tension measured by the load cell was recorded after each procedure was completed. Data were analyzed for mean, variance, reproducibility, and repeatability. Operator feedback surveys were used to quantify ease-of-use.The ECE R44/R129 procedure produced harness tensions which were quite low. The…
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Design of a Grid-Friendly DC Fast Charge Station with Second Life Batteries

Ohio State University-Matilde D'Arpino, Massimo Cancian
Published 2019-04-02 by SAE International in United States
DC-fast charge (DCFC) may be amenable for widespread EV adoption. However, there are potential challenges associated with implementation and operation of the DCFC infrastructures. The integration of energy storage systems can limit the scale of grid installation required for DCFC and enable more efficient grid energy usage. In addition, second-life batteries (SLBs) can find application in DCFC, significantly reducing installation cost when compared to solutions based on new battery packs. However, both system architecture and control strategy require optimization to ensure an optimal use of SLBs, including degradation and thermal aspects. This study proposes an application of automotive SLBs for DCFC stations where high power grid connection is not available or feasible. Several SLBs are connected to the grid by means of low power chargers (e.g. L2 charging station), and a DC/DC converter controls the power to the EV power dispenser. The architecture of the DC bus, the size and state of health of the battery system determine efficiency, cost, and reliability of the station. A technical and economic comparison is proposed, evaluating solutions with…
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Ultra-Low NOx Emission Prediction for Heavy Duty Diesel Applications Using a Map-Based Approach

Ohio State University-Kyle Hickey
Navistar Inc.-Navtej Singh, Brad Adelman, Srinivasulu Malagari
Published 2019-04-02 by SAE International in United States
As vehicle emissions regulations become increasingly stringent, there is a growing need to accurately model aftertreatment systems to aid in the development of ultra-low NOx vehicles. Common solutions to this problem include the development of complex chemical models or expansive neural networks. This paper aims to present the development process of a simpler Selective Catalytic Reduction (SCR) conversion efficiency Simulink model for the purposes of modeling tail pipe NOx emission levels based on various inputs, temperature shifts and SCR locations, arrangements and/or sizes in the system. The main objective is to utilize this model to predict tail pipe NOx emissions of the EPA Federal Test Procedures for heavy-duty vehicles. The model presented within is focused exclusively on heavy-duty application compression ignition engines and their corresponding aftertreatment setups. The accuracy of the model depends heavily on the ability to gain precise and repeatable test cell data to calculate an expansive SCR conversion efficiency map for the given aftertreatment system. This conversion efficiency map is verifiable based on expected/known chemical and physical properties of SCR aftertreatment systems.…
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Cooperative Collision Avoidance in a Connected Vehicle Environment

Ohio State University-Sukru Yaren Gelbal, Sheng Zhu, Gokul Arvind Anantharaman, Bilin Aksun Guvenc, Levent Guvenc
Published 2019-04-02 by SAE International in United States
Connected vehicle (CV) technology is among the most heavily researched areas in both the academia and industry. The vehicle to vehicle (V2V), vehicle to infrastructure (V2I) and vehicle to pedestrian (V2P) communication capabilities enable critical situational awareness. In some cases, these vehicle communication safety capabilities can overcome the shortcomings of other sensor safety capabilities because of external conditions such as 'No Line of Sight' (NLOS) or very harsh weather conditions. Connected vehicles will help cities and states reduce traffic congestion, improve fuel efficiency and improve the safety of the vehicles and pedestrians. On the road, cars will be able to communicate with one another, automatically transmitting data such as speed, position, and direction, and send alerts to each other if a crash seems imminent. The main focus of this paper is the implementation of Cooperative Collision Avoidance (CCA) for connected vehicles. It leverages the Vehicle to Everything (V2X) communication technology to create a real-time implementable collision avoidance algorithm along with decision-making for a vehicle that communicates with other vehicles. Four distinct collision risk environments are…
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