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Cooperative Mandatory Lane Change for Connected Vehicles on Signalized Intersection Roads

Clemson University-Zhiyuan Du, Bin Xu, Pierluigi Pisu
  • Technical Paper
  • 2020-01-0889
To be published on 2020-04-14 by SAE International in United States
This paper presents a hierarchical control architecture to coordinate a group of connected vehicles on signalized intersection roads, where the vehicles are allowed change lane to follow a prescribed path. The hierarchical control strategy consists of two levels of controllers. The higher level controller acts as a centralized controller, while the lower level controller implemented in each individual car is designed as decentralized controller. In the hierarchical control architecture, the centralized intersection controller estimates the target velocity for each approaching connected vehicle to avoid red light stop based on the signal phase and timing (SPAT) information. Each connected vehicle as a decentralized controller utilizes Model Predictive Control (MPC) to track the target velocity in a fuel efficient manner. The main objective is this paper is to consider mandatory lane changing. As in the realistic scenarios, vehicles are not necessary required to drive in single lane. More specifically, they more likely change their lanes prior to signals. Hence, the vehicle decentralized controllers are prepared to cooperate with the vehicle which has mandatory lane change request (host…
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Simulation of SACI Autoignition Phasing Sensitivity for Production Controls Strategies

Clemson University-Dennis Robertson, Robert Prucka
  • Technical Paper
  • 2020-01-1145
To be published on 2020-04-14 by SAE International in United States
Spark-assisted compression ignition (SACI) is a combustion strategy that leverages flame propagation to trigger autoignition. The autoignition event is highly sensitive to several parameters, and thus, achieving SACI in production demands a robust response to variations in conditions. However, limited research is available to quantify the combustion response of SACI to these variations. A simulation study is performed to identify the sensitivity in autoignition timing as ethanol content, fuel RON, air-fuel ratio, EGR level, and the phasing of flame propagation are swept. An experimentally-validated one-dimensional simulation model provides the composition, state, and flow metrics at BDC. The results are applied to the Leeds diagram to ensure the conditions are viable for flame propagation. The conditions at BDC are then transferred to a chemical kinetics solver, where autoignition is modeled using a detailed chemical kinetics mechanism. These results are used to explore the SACI combustion controls space. The range of CA50 control authority is particularly important as combustion phasing is used to perform rapid torque changes. The steady-state combustion control authority is evaluated, and potential controls…
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A Preliminary Method of Delivering Engineering Design Heuristics

Clemson University-Mohammad M. Hussain, Christiaan Paredis
  • Technical Paper
  • 2020-01-0741
To be published on 2020-04-14 by SAE International in United States
This paper argues the importance of engineering heuristics and introduces an educational data-driven tool to help novice engineers develop their engineering heuristics more effectively. The main objective in engineering practice is to identify opportunities for improvement and apply methods to effect change. Engineers do so by applying ‘how to’ knowledge to make decisions and take actions. This ‘how to’ knowledge is encoded in engineering heuristics. In this paper, we describe a tool that aims to provide heuristic knowledge to users by giving them insight into heuristics applied by experts in similar situations. A repository of automotive data is transformed into a tool with powerful search and data visualization functionalities. The tool can be used to educate novice automotive engineers alongside the current resource intensive practices of teaching engineering heuristics through social methods such as an apprenticeship. The tool can do so by providing novices with powerful search and data visualization capabilities which will allow them to understand tradeoffs between vehicle attributes, to make assumptions from initial information, and to benchmark the vehicle design.
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The Effects of Thick Thermal Barrier Coatings on Low-Temperature Combustion

Clemson University-Ziming Yan, Brian Gainey, Benjamin Lawler
Stony Brook University-James Gohn, Deivanayagam Hariharan, John Saputo, Carl Schmidt, Felipe Caliari, Sanjay Sampath
  • Technical Paper
  • 2020-01-0275
To be published on 2020-04-14 by SAE International in United States
An experimental study was conducted on a Ricardo Hydra single-cylinder light-duty diesel research engine. Start of Injection (SOI) timing sweeps from -350 deg aTDC to -210 deg aTDC were performed on a total number of five pistons including two baseline metal pistons and three coated pistons to investigate the effects of thick thermal barrier coatings (TBCs) on the efficiency and emissions of low-temperature combustion (LTC). A fuel with a high latent heat of vaporization, wet ethanol, was chosen to eliminate the undesired effects of thick TBCs on volumetric efficiency. Additionally, the higher surface temperatures of the TBCs can be used to help vaporize the high heat of vaporization fuel and avoid excessive wall wetting. A specialized injector with a 60° included angle was used to target the fuel spray at the surface of the coated piston. Throughout the experiments, the equivalence ratio, ϕ, was maintained constant at 0.4; the combustion phasing was consistently matched at 6.8 ± 0.4 deg aTDC. It can be concluded that the thick TBC cases achieved 1 to 2 percentage points…
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An Electric Motor Thermal Bus Cooling System for Vehicle Propulsion – Design and Test

Clemson University-Shervin Shoai Naini, Richard Miller, John Wagner
CCDC Ground Vehicle Systems Center-Katherine Sebeck
  • Technical Paper
  • 2020-01-0745
To be published on 2020-04-14 by SAE International in United States
Automotive and truck manufacturers are introducing electric propulsion systems into their ground vehicles to reduce fossil fuel consumption and harmful tailpipe emissions. The mobility shift to electric motors requires a compact thermal management system that can accommodate heat dissipation demands with minimum energy consumption in a confined space. An innovative cooling system design, emphasizing passive cooling methods coupled with a small liquid system, using a thermal bus architecture will be explored. The laboratory experiment features an emulated electric motor interfaced to a thermal cradle and multiple heat rejection pathways to evaluate the transfer of generated heat to the ambient surroundings. The thermal response of passive (e.g., carbon fiber, high thermal conductivity material, thermosyphon) and active cooling systems are investigated for two operating scenarios. The test results demonstrate significant improvements can be achieved in cooling system energy consumption while maintaining a target e-motor temperature of 70℃. The governing thermal system dynamics will be reviewed in discussion of the experimental observations.
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Obstacle Avoidance using Model Predictive Control: A Detailed Analysis using Scaled Vehicles

Clemson University-Ardashir Bulsara, Adhiti Raman, Srivatsav Kamarajugadda, Matthias Schmid, Venkat N Krovi
  • Technical Paper
  • 2020-01-0109
To be published on 2020-04-14 by SAE International in United States
Over the last decade, tremendous amount of research and progress has been made towards developing smart technologies for autonomous vehicles such as adaptive cruise control, lane keeping assist, lane following algorithms, decision making algorithms for lane changing, adaptive control etc. One of the fundamental objectives for the development of such technologies is to enable autonomous vehicles with the capability to avoid obstacles and maintain safety. Automobiles are intricate systems and increasing autonomy in vehicles increases their complexity by several folds; especially since the dynamics of the vehicle needs to be considered. Model predictive control is a powerful tool that is used extensively to control the behavior of complex, dynamic systems. As a model-based approach, the fidelity of the model and selection of model-parameters plays a role in ultimate performance. In this paper, we use model predictive control to comparatively study controller performance for obstacle avoidance strategy using scaled-vehicles (1/10th scale). The assessment is conducted initially in simulation and planned to be evaluated in a hardware-in-loop framework.
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Single vs Double Stage Partial Flow Dilution System: Automobile PM Emission Measurement

Clemson University-Chirag Basrur
Cummins Technical Center-Yusuf Khan, Chet Mun Liew
  • Technical Paper
  • 2020-01-0366
To be published on 2020-04-14 by SAE International in United States
California Air Resource Board already introduced LEV III PM emission regulation (1mg/mi by 2028). It will be challenging to quantify such ultra-low PM by using conventional full flow Constant Volume Sampling (CVS) system. Sampling technique alternative to a CVS such as a Partial Flow Dilution System (PFDS) has already been introduced. Collecting PM on a single filter by using flow weighting is one options to load traceable amount of PM (Preferably more than 100 micrograms) on filter. Lower Dilution Ratios (DR) and higher Filter Face Velocity (FFV) are options to load traceable amount of PM on filter media in case of Light Duty Vehicle (LDV) testing. On the other hand Heavy Duty Engine (HDE) testing requires higher DR and lower FFV is to keep the amount of PM on filter less than 400 micrograms. PFDS with a single dilution tunnel cannot support both the LDV and HDE testing where a wide range of FFV and DR are required. A new PFDS with 2-stage dilution has been developed in the previous study. Two identical dilution tunnel…
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Experimental Investigation of Low Cost, Low Thermal Conductivity Thermal Barrier Coating on HCCI Combustion, Efficiency, and Emissions

Clemson University-Sean Moser, Tom Powell, Zoran Filipi
Auburn University-Mark Hoffman
  • Technical Paper
  • 2020-01-1140
To be published on 2020-04-14 by SAE International in United States
In-cylinder surface temperature is of heightened importance for Homogeneous Charge Compression Ignition (HCCI) combustion, as the combustion mechanism is thermo-kinetically driven. Thermal Barrier Coatings (TBCs) selectively manipulate the in-cylinder surface temperature, providing an avenue for improving thermal and combustion efficiency. This thermal phenomenon sidesteps charge preheating during gas exchange, while a surface temperature swing during combustion/expansion reduces heat transfer losses, leading to more complete combustion and reduced emissions. The magnitude and profile of the dynamic surface temperature swing was found to be affected by the material properties and TBC thickness. This study is the continuation of the author’s work to systematically engineer coatings that are best suited for HCCI. A parametric study was used to assess the impacts of various TBC material properties (density, specific heat, thermal conductivity) on the temperature swing effect. Previous work investigated the effect of reducing TBC density via increased porosity, however fuel entrapment and durability concerns found this route initially unattractive for robust TBC performance. Shifting focus to the remaining material properties, this study experimentally investigates the impact of lower…
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Driver Physiological Drowsiness Behavior Detection and Analysis using Vision-based Multimodal Features for Driving Safety

Clemson University-Rui Li, Howard Brand, Aditya Gopinath, Srivatsav Kamarajugadda, Bing Li
Montclair State University-Weitian Wang
  • Technical Paper
  • 2020-01-1211
To be published on 2020-04-14 by SAE International in United States
Driving safety has always been a fundamental concern in transportation systems. Driving inattention caused by drowsiness has been a significant reason for vehicle crash accidents according to United States Traffic Safety Culture Index report, and there is an essential need to improve assistance driving safety by understanding the driver behaviors. Towards real-time drowsy driving monitoring, we propose an in-vehicle driver assistant system to monitor driver states for drowsiness behavior recognition and analysis. First, an infrared camera is deployed inside the vehicle to capture the driver’s facial and head information, in which scenarios, the driver is allowed to wear glasses or sunglasses during driving. Second, vision-based multimodal features, facial landmarks and head pose are extracted efficiently by the ensemble of regression trees based facial landmarks estimation method and a convolutional neural network (CNN) recognition model. Finally, an extreme learning machine (ELM) model is proposed to fuse the facial landmark, recognition model and pose orientation for drowsiness detection. The system gives promptly warning to the driver once a drowsiness event is detected. The proposed machine learning recognition…
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A High-Fidelity Human Factors Study System for Autonomous Vehicles

Clemson University-Haotian Su, Yunyi Jia
  • Technical Paper
  • 2020-01-1034
To be published on 2020-04-14 by SAE International in United States
Autonomous vehicles are leading to a new paradigm for our future transportation systems and they have been extensively studied by both academia and industries. Currently, most efforts have been focused on safety and efficiency development. However, human factors, an important topic in autonomous vehicles, have not been extensively studied. Human factors may seriously affect the comfort and user acceptance of autonomous vehicles even though their safety and efficiency are granted. To address this problem, a capable autonomous driving platform with appropriate human and vehicle information acquisitions and cost-effective implementations is needed. At current stage when there is no well-developed autonomous vehicle that can serve as full autonomous driving experimental platform for human factors study, an in-lab autonomous driving simulation system is needed for research on human factors in autonomous vehicles. Motivated by this, a high-fidelity autonomous driving simulation system is developed with multiple data collection devices for human factors research. The simulation system can generate immersive high-fidelity driving experience for the participants and consists of an autonomous driving controller, a 6-degree-of-freedom-motion seat, and multimodal visual/audio…