<p dir="ltr">Engine downsizing with the assistance of turbomachinery and/or energy storage system has been realized to be one of the most promising and cost-effective solutions in pursuit of cleaner and more efficient engine products. Fundamental challenges however, exist in terms of control and energy management of advanced powertrain featuring turbocharged engines due to their complex dynamics, inherent coupling nature, and strict emission regulations concerning environmental preservation. For the purpose of addressing those challenges, this dissertation develops an integrated framework for modeling, robust coordinated control, and power management of advanced powertrains featuring turbocharged engines.</p><p dir="ltr">This dissertation first studies an advanced turbocharged lean-burn SI natural gas engine manufactured by Caterpillar, and develops an intuitive physics-based, control-oriented model. The obtained control-oriented model is validated against a high-fidelity truth-reference model and serves as the basis on which a robust coordinated control system is developed. The dissertation then proposes a comprehensive procedure for synthesizing a robust coordinated control system applying optimization-based H_infinity control theory. Specifically, this framework outlines a methodology of modeling uncertainties to account for system robustness, and providing valuable insights into the tuning of general coordinated control system design. For performance testing, the synthesized robust coordinated control system is implemented on the high-fidelity truth-reference model. A parallel closed-loop simulation strategy is adopted so that direct comparison between the robust coordinated control system and benchmark production control system (composed of multiple fine-tuned PID controllers) developed by Caterpillar can be carried out. Simulation results manage to demonstrate the merit of utilizing the robust coordinated control system, with better performances observed in terms of steady-state tracking, transient response, and disturbance attenuation.</p><p dir="ltr">The second part of this dissertation focuses on the development of a proposed novel hybrid electric wheel loader which features a downsized engine assisted by turbocharger and an energy storage system. Research efforts documented in this dissertation involve system configuration, controller design (both component-level and supervisory-level), simulation development (both software-in-the-loop and hardware-in-the-loop) and simulated validation for the proposed novel wheel loader. Inspired by the successful simulation results, John Deere assembled a real demo vehicle with the proposed powertrain and conducted some in-field testing, from which encouraging experimental results are observed.</p>

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In searching for more efficient vehicles with lower carbon emissions, researchers have invested enormous time and resources in designing new materials, components, systems, and control methods. The result is not only an immense volume of publications and patents but also a true electrification revolution in the transportation sector. Although the advancements are remarkable, much is still to be developed. Energy management systems are often designed to fulfil drive cycles that represent just a fraction of the actual use of the vehicles, disregarding essential factors such as driving conditions that may vary in real life. Furthermore, control algorithms should not ignore one of the most relevant driving aspects, comfort. Driving should be a pleasant activity since we spend much time of our lives performing this task. This research proposes a novel algorithm for managing energy consumption in electrified vehicles, the regen-based equivalent consumption minimization strategy (R-ECMS). Its suitability for solving the power-split problem is evaluated. Experiments emulating labelling schedules are conducted considering an example application. Robustness to different drive cycles and flexibility of the algorithm to various modes of operation are assessed. Furthermore, the method is integrated into an autonomous longitudinal control. The function leverages vehicle dynamics and journey mapping to assure energy efficiency and adequate drivability. Finally, the tests are conducted using human-driven cycles leveraging driving simulation technology. That allows for including driver subjective feelings in the design and assessing the algorithm's performance in realistic driving conditions. / Thesis / Doctor of Philosophy (PhD)

<p>The world transportation sector has been relying on the oil industry for more than a hundred years, accounting for the largest oil consumption and one third of the greenhouse gas emissions. However, with the boosting demand, escalating national energy security concerns and emerging environmental issues, reducing and displacing petroleum fuel in transportation sector has become an urging global target. As a result, hybrid electric vehicles evolve as one solution to displace petroleum fuel by utilizing vehicle onboard electrical systems, achieving higher fuel economy and less emissions by vehicle electrification and hybridization.</p> <p>However, since hybrid electric vehicles add additional electrical components and systems to realize better fuel economy, the system complexity increases and thus the cost increases. Hence, it is an objective of this thesis research to focus on the integrations and optimizations, aiming to simplify and optimize the hybrid power-trains in both system level and component level.</p> <p>This thesis contributes to a novel integrated electro-mechanical hybrid transmission that is potentially more compact and more operational flexible with fewer components compared to the GM Allison Two-Mode hybrid transmission. Comprehensive commercialized power-train transmissions are reviewed and analyzed to serve as background information for comparison. It also contributes to a family of double-rotor switched reluctance machines that are more integrated and suitable for hybrid electric vehicle applications. A prototype double-rotor switched reluctance machine has been built and tested for concept proving. Detailed machine design process is reported with the emphasis on design novelties. Finite element analysis and optimization techniques are applied and the accuracy is confirmed by the experiments. In addition, methods of machine loss analysis, thermal analysis and drive analysis are established; manufacturing and testing procedures are documented in detail that can be used for future machine designs guidance.</p> / Doctor of Philosophy (PhD)

The purpose of this study was to determine consumers' attitudes toward and perceptions of global warming and hybrid cars and examine the car purchasing behavior in Singapore. The benefits of the study will provide marketers with insight of consumers' demand for cars in Singapore. Findings will help automakers develop more effective, consumer-oriented advertising plans for cars in Asia as Singapore consists of diverse Asian ethnic backgrounds- Chinese, Indian, and Malaysain.

In today’s world of volatile fuel prices and climate concerns, there is little study on the relation between vehicle ownership patterns and attitudes toward potential policies and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s household-fleet evolution. Results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are vehicle purchase price, type/class, and fuel economy (with 30%, 21% and 19% of respondents placing these in their top three). Most (56%) respondents also indicated that they would seriously consider purchasing a Plug-In Hybrid Electric Vehicle (PHEV) if it were to cost $6,000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings. 25-year simulations suggest that 19% of Austin’s vehicle fleet could be comprised of Hybrid Electric Vehicles (HEVs) and PHEVs under adoption of a feebate policy (along with PHEV availability in Year 1 of the simulation, and current gas prices throughout). Under all scenarios vehicle usage levels (in total vehicle miles traveled [VMT]) are predicted to increase overall, along with average vehicle ownership levels (per household, and per capita); and a feebate policy is predicted to raise total regional VMT slightly (just 4.43 percent, by simulation year 25), relative to the trend scenario, while reducing CO2 emissions only slightly (by 3.8 percent, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 17% and CO2 emissions by 22% (relative to trend). Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. And HEVs, PHEVs and Smart Cars are estimated to represent a major share of the fleet’s VMT (25%) by year 25 under the feebate scenario. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet), yet feebate-policy receipts exceed rebates in each simulation year. A 15% reduction in the usage levels of SUVs, CUVs and minivans is observed in the $5/gallon scenario (relative to trend). Mean use levels per vehicle of HEVs and PHEVs are simulated to have a variation of 753 and 495 across scenarios. In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have even more significant effects on energy dependence and greenhouse gas emissions. / text

Transportation fleet emissions have a dominant role in air quality because of their significant contribution to ozone precursor and greenhouse gas emissions. Regulatory policies have emphasized improvements in vehicle fuel economy, alternative fuel use, and engine and vehicle technologies as approaches for obtaining transportation systems that support sustainable development. This study examined the air quality impacts of the partial electrification of the transportation fleet and the use of biofuels for the Austin Metropolitan Statistical Area under a 2030 vision of regional population growth and urban development using the Comprehensive Air Quality Model with extensions (CAMx). Different strategies were considered including the use of Plug-in Hybrid Electric Vehicles (PHEVs) with nighttime charging using excess capacity from electricity generation units and the replacement of conventional petroleum fuels with different percentages of the biofuels E85 and B100 along or in combination. Comparisons between a 2030 regional vision of growth assuming a continuation of current development trends (denoted as Envision Central Texas A or ECT A) in the Austin MSA and the electrification and biofuels scenarios were evaluated using different metrics, including changes in daily maximum 1-hour and 8-hour ozone concentrations, total area, time integrated area and total daily population exposure exceeding different 1-hour ozone concentration thresholds. Changes in ozone precursor emissions and predicted carbon monoxide and aldehyde concentrations were also determined for each scenario. Maximum changes in hourly ozone concentration from the use of PHEVs ranged from -8.5 to 2.2 ppb relative to ECT A. Replacement of petroleum based fuels with E85 had a lesser effect than PHEVs on maximum daily ozone concentrations. The maximum reduction due to replacement of 100% of gasoline fuel in light and heavy duty gasoline vehicles by E85 ranged from -2.1 to 2.8 ppb. The magnitude of the effect was sensitive to the biofuel penetration level. Unlike E85, B100 negatively impacted hourly ozone concentrations relative to the 2030 ECT A case. As the replacement level of petroleum-diesel fuel with B100 in diesel vehicles increased, hourly ozone concentrations increased as well. However, changes due to the penetration of B100 were relatively smaller than those due to E85 since the gasoline fraction of the fleet is larger than the diesel fraction. Because of the reductions in NOx emissions associated with E85, the results for the biofuels combination scenario were similar to those for the E85 scenario. Also, the results showed that as the threshold ozone concentration increased, so too did the percentage reductions in total daily population exposure for the PHEV, E85, and biofuel combination scenarios relative to ECT A. The greatest reductions in population exposure under higher threshold ozone concentrations were achieved with the E85 100% and 17% PHEV with EGU controls scenarios, while the B100 scenarios resulted in greater population exposure under higher threshold ozone concentrations. / text

<div>Plug-in hybrid electric vehicles (PHEVs) are being considered as an alternative to conventional medium-duty (MD) and heavy-duty (HD) commercial vehicles to reduce fuel consumption and tailpipe emissions. Lithium ion batteries, which are used in PHEVs due to their high energy density, are expensive. The battery contributes significantly towards the life-cycle cost of MD/HD PHEVs, as these vehicles, due to high mass and aggressive battery usage, require multiple battery replacements over their lifetime. Smaller batteries increase the fuel consumption and need more replacements, while bigger batteries increase the initial system cost. Powertrain design from a life-cycle cost perspective is required to explore this trade-off and maximize the economic gains obtained from PHEVs. </div><div><br></div><div>Powertrain design entails component sizing, control strategy selection as well as architecture selection. Different powertrain designs yield different lifetime economic gains. A variety of applications exist for MD/HD vehicles, which differ in their ways of powertrain usage, due to variations in required acceleration, available braking, and average and maximum speeds. Therefore, different powertrain designs are needed depending on the application and usage scenario. The powertrain design space needs to be explored, and solutions that maximize the economic gains within the specified constraints need to be chosen.</div><div><br></div><div>This dissertation compares the economic viability of two PHEV applications (MD Truck and HD Transit Bus), with options of series and parallel hybrid architectures, over multiple drivecycles, for four economic scenarios (years 2015, 2020, 2025 and 2030). It is shown that hybridizing the transit bus achieves payback sooner than hybridizing the truck. Further, the results for the transit bus application, over the Manhattan drivecycle, show that implementation of the parallel architecture is economically viable in the 2015(present) scenario, while the series architecture becomes viable in 2020, due to significantly lower initial costs involved in the parallel architecture.</div><div><br></div><div>A methodology to select a solution out of the explored design space that maximizes the economic gains is demonstrated. Variations in the economic and vehicle usage conditions for which this solution is designed, can be expected. It is therefore necessary to check the robustness of this solution to change in external factors such as vehicle mass, annual vehicle miles travelled (AVMT), component and fuel costs. It is shown that the economic gains are affected by the battery cost, fuel cost, AVMT and vehicle mass, while the number of battery replacements are affected by AVMT and vehicle mass. </div><div><br></div><div>A probability-based approach is demonstrated to obtain confidence in the economic and battery life predictions. Specifically, probability-based variations are provided to variables such as miles traveled between recharge, recharge C-rate and battery temperature. It is shown that battery life is affected the most by battery temperature.</div><div><br></div><div>A battery heating/cooling system is required to maintain constant battery temperature of operation during all seasons, but these systems incur additional fuel costs. A framework that utilizes just the Coefficient of Performance (COP) of the heating/cooling system to calculate the excess fuel cost is proposed and demonstrated. An increase of 0.9-1.8\% in fuel consumption is shown, depending on the drivecycle and ambient temperature.</div><div><br></div><div>Further, the well-to-wheel (WTW) fuel-cycle emissions from conventional and PHEV transit buses operating in Indiana and California are assessed using the ``Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation'' (GREET) Model 2017, developed by Argonne National Labs. It is shown that 59% and 63% greenhouse gas (GHG) reductions can be achieved in Indiana and California respectively, along with reduction in carbon monoxide (CO), nitrogen oxides NOx, particulate matter with diameter less than 2.5 microns PM2.5 and volatile organic compounds (VOC) emissions for both the states. However, an increase in sulfur oxides SOx emissions for both the states, and particulate matter with diameter less than 10 microns PM10 increase for Indiana, are observed. </div><div><br></div>