Date of Award

2020

Document Type

Open Access Master's Report

Degree Name

Master of Science in Mechanical Engineering (MS)

Administrative Home Department

Department of Mechanical Engineering-Engineering Mechanics

Advisor 1

Darrell L. Robinette

Committee Member 1

Jeffrey D. Naber

Committee Member 2

Bo Chen

Abstract

This report presents an analysis on energy consumption of a Gen II Chevrolet Volt PHEV and its energy savings potential in Real World Driving scenarios with the help of vehicle connectivity. The research on the energy consumption analysis and optimization using connectivity will focus on four main areas of contribution which includes 1.) vehicle testing on a pre-defined drive cycle and alternative routing near the Michigan Tech campus and APS research center that is a continuation of previous students' works, 2) the energy savings potential of vehicle platooning and various vehicle platoon configurations, 3) the updating of a PHEV implementation of a charge depleting-charge sustaining energy blending optimization algorithm and 4) the development of an IC Engine start-stop prediction algorithm for HEV and PHEV's using connectivity data. The first part of the report discusses the development of a Real World Drive Cycle called Reverse MTU Drive Cycle which is the successor of MTU Drive Cycle, a drive cycle previously developed local to the Michigan Technological University. The energy consumption of the PHEV on the R-MTUDC is analyzed and the baseline characteristics of the drive cycle is setup. A set of baseline drive cycle characteristics was developed and tests on the drive cycle proved that the energy consumption on the real-world drive route is consistent with variability less than 3%. The next part of the report investigates the energy savings potential of the cars when they are traveling in a platoon rather than independently. Various tests have been conducted to investigate energy savings under different platoon scenarios, like variable gap settings, variable speeds, inclusion of a vehicle with aero-modifier and effect of moving collinearly in a platoon. A platoon wide savings as high as 8.3% was achieved in the study. After that, the report discusses the on-road implementation of a Route Based Blended Mode Optimizer, in PHEVs, which comes up with an optimal control matrix using Dynamic Programming and Cost-To-Go matrix, to make use of the Hold mode capability of the Volts, to operate the cars in Charge Sustaining mode at sections of Drive Cycles where it is most efficient to be operated. Upto, 5% savings in energy was obtained using the optimizer. Some of the runs didn't provide the desired results and this is also investigated. Finally, the report presents the development of two kinds of Engine Start-Stop Optimizers, which utilizes vehicle connectivity and vehicle energy consumption model to come up with an optimal control map of regions on the predicted driving route where the engine should be turned On and Off for minimizing energy consumption in HEVs and PHEVs. The first optimizer uses vehicle and route characteristics to predict engine starts and stops and then optimizes these signals based on decisions made from energy calculations. The second optimizer uses Dynamic Programming to create a matrix of engine On and Off signals based on the route characteristics. These controllers are shown to provide energy savings as high as 8% on some routes.

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