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Morgan, Christopher
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Utilization of vehicle connectivity for improved energy consumption of a speed harmonized cohort of vehicles.

Michigan Technological University-Christopher Morgan, Darrell Robinette, Pruthwiraj Santhosh, John Bloom-Edmonds
  • Technical Paper
  • 2020-01-0587
To be published on 2020-04-14 by SAE International in United States
Improving vehicle response through advanced knowledge of traffic behavior can lead to large improvements in energy consumption for the single isolated vehicle. This energy savings across multiple vehicles can even be larger if they travel together as a cohort in harmonization. Additionally, if the vehicles have enough information about their immediate path of travel, and other vehicles’ in that path (and their respective critical forward looking information), they can safely drive close enough to each other to share aerodynamic load. These energy savings can be upwards of multiple percentage points, and are dependent on several criteria. This analysis looks at criteria that contributes to energy savings for a cohort of vehicles in synchronous motion, as well as describes a study that allows for better understanding of the potential benefits of different types of cohorted vehicles in different platoon arrangements. The basis of this study is a precursor to developing a connected vehicle application that safely allows for fully controlled platooning on open highway for multi-destination vehicles. In this study, two types of light duty passenger…
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A Connected Controls and Optimization System for Vehicle Dynamics and Powertrain Operation on a Light-Duty Plug-In Multi-Mode Hybrid Electric Vehicle

Michigan Technological University-Joseph Oncken, Joshua Orlando, Pradeep K. Bhat, Brandon Narodzonek, Christopher Morgan, Darrell Robinette, Bo Chen, Jeffrey Naber
  • Technical Paper
  • 2020-01-0591
To be published on 2020-04-14 by SAE International in United States
This paper presents an overview of the connected controls and optimization system for vehicle dynamics and powertrain operation on a light-duty plug-in multi-mode hybrid electric vehicle developed as part of the DOE ARPA-E NEXTCAR program by Michigan Technological University in partnership with General Motors Co. The objective is to enable a 20% reduction in overall energy consumption and a 6% increase in electric vehicle range of a plug-in hybrid electric vehicle through the utilization of connected and automated vehicle technologies. Technologies developed to achieve this goal were developed in two categories, the vehicle control level and the powertrain control level. Tools at the vehicle control level include Eco Routing, Speed Harmonization, Eco Approach and Departure and in-situ vehicle parameter characterization. Tools at the powertrain level include PHEV mode blending, predictive drive-unit state control, and non-linear model predictive control powertrain power split management. These tools were developed with the capability of being implemented in a real-time vehicle control system. As a result, many of the developed technologies have been demonstrated in real-time using a fleet of…
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PHEV Real World Driving Cycle Energy and Fuel and Consumption Reduction Potential for Connected and Automated Vehicles

Michigan Technological University-Darrell Robinette, Eric Kostreva, Alexandra Krisztian, Anthony Lackey, Christopher Morgan, Joshua Orlando, Neeraj Rama
Published 2019-04-02 by SAE International in United States
This paper presents real-world driving energy and fuel consumption results for the second-generation Chevrolet Volt plug-in hybrid electric vehicle (PHEV). A drive cycle, local to Michigan Technological University, was designed to mimic urban and highway driving test cycles in terms of distance, transients and average velocity, but with significant elevation changes to establish an energy intensive real-world driving cycle for assessing potential energy savings for connected and automated vehicle (CAV) control. The investigation began by establishing baseline and repeatability of energy consumption at various battery states of charge. It was determined that drive cycle energy consumption under a randomized set of boundary conditions varied within 3.6% of mean energy consumption regardless of initial battery state of charge. After completing 30 baseline drive cycles, a design for six sigma (DFSS) L18 array was designed to look at sensitivity of a range of parameters to energy consumption as related to connected and automated vehicles to target highest return on engineering development effort. The parameters explored in the DFSS array that showed the most sensitivity, in order of…
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Determination of Vehicle Frontal Area Using Image Processing

General Motors Company-Christopher Morgan
Michigan Technological University-Drew D. Brennan, Jeremy Worm
Published 2013-04-08 by SAE International in United States
The projected frontal area of a vehicle has a significant impact on aerodynamic drag, and thus is an important parameter, for vehicle development, benchmarking, and modeling. However, determining vehicle frontal area can be tedious, time consuming, expensive, or inaccurate. Existing methods include analysis of engineering drawings, vehicle projections, 3D scanners, planimeter measurements from photographs, and estimations using vehicle dimensions. Currently accepted approximation methods can be somewhat unreliable.This study focuses on introducing a method to find vehicle frontal area using digital images and subtraction functions via MATLABs' Image Processing Toolbox. In addition to an overview of the method, this paper describes several variables that were examined to optimize and improve the process such as camera position, surface glare, and vehicle shadow effects.
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