Current Projects

Confidential

Summary for Public Release

Michigan Technological University in partnership with General Motors will develop, validate and demonstrate on a fleet of eight model year 2016 Chevrolet Volts and a mobile connected cloud computing center, a model based vehicle and powertrain controller. The selected vehicle, the MY16 Volt contains a unique powertrain architecture and enables five distinct operating modes including all electric (EV), plug-in-electric hybrid (PHEV), and hybrid electric vehicles (HEV). The model based controller will encompass a full real-time physics based coupled powertrain vehicle dynamics model leveraging vehicle conductivity with vehicle-to-vehicle and infrastructure to vehicle communications with real-time traffic modeling and predictive speed horizons and eco-routing. The goal is to achieve at least a 20% reduction in energy consumption (electrical + fuel) and a 6% increase in electric range through the first ever implementation and connection of route planning, powertrain energy management model predictive controller algorithms. Connectivity data from other vehicles, infrastructure, GPS, traffic, and desired route planning combined with a physical model of the powertrain-vehicle system allows prediction of the vehicle’s future speed and enables forward looking powertrain mode selection and reduction of the energy utilization from the battery and fuel.

1. A method for obtaining instantaneous wave surface elevation information on a wave-by wave basis using a low-cost X-band Radar (the state of the art, as represented by the commercially available WaMOS system is optimized to provide spectral information.
2. A method for providing constrained near-optimal wave-by-wave control for maximizing the energy conversion by small wave energy converters.
3. Although the focus of the proposed research is wave energy converter technology, the results of this work are expected to find application in other forthcoming Navy developments. Wave-by-wave surface elevation prediction and near-optimal power absorption techniques demonstrated in this effort can be extended to facilitate critical mid-sea shipboard operations such as helicopter/ aircraft landing, cargo handling, etc. The techniques demonstrated as part of this research will also provide technology to enhance and optimize seakeeping characteristics of Navy ocean platforms.

Overview:

Success of numerous long-term robotic network missions in space, air, ground, and water is measured by the ability of the robots to operate for extended time in highly dynamic and potentially hazardous operating environments. The proposed work responds to the urgency for development of innovative mobile power distribution systems that lower deployment and operating costs, while simultaneously increasing mission efficiency, and supporting the network's need to be responsive to changing physical conditions. The overall CAREER goal is to develop a power distribution system that responds to individual robot needs, as well as, overall robotic network goals to guarantee persistence of long-term operation in uncertain and unstructured environments.

The proposed work is informed by the hypothesis that network persistence hinges on the ability to establish stable energy transfer cycles necessary to accomplish coverage specifications, while simultaneously dealing with physical and environmental constraints. To test this hypothesis and as an example of such a system, this work will focus on creating a reliable autonomous recharging system for autonomous underwater vehicles (AUVs) that enables continuous real-time marine observation and data collection in the presence of continuously changing underwater environmental circumstances. The key challenges are two-fold: there are fundamental hardware challenges connected to energy transfer in the harsh underwater environment, but more importantly there are basic network science needs that are novel to a mobile power network. The specific research thrusts for this CAREER work include: 1) Task and Energy Routing Scheduling for Persistent Mission Planning. 2) Efficient Network Path Planning and Coordination to Accomplish Persistent Mission Plan. 3) Experimental Validation through Test-bed Development. 4) Design-based, Research-integrated Education Plan for Broadening Underrepresented Participation in STEM.

Intellectual Merit:

This project builds a roadmap to achieve robust continuous marine autonomy that advances unmanned marine systems ability to perform autonomous long-term missions. More specifically the proposed work will provide: 1) resource based task scheduling, 2) path planning formation for mission and charging, and 3) integration tools for testing. Expected outcomes will overcome the current challenge of significant interruptions during underwater missions due to battery limitations and recharging needs. Through this CAREER proposal, the Pl will establish the theoretical, computational, and experimental foundation for mobile power delivery and onsite recharging capability for autonomous underwater vehicles (AUVs). The developed power distribution system will be able to reconfigure itself depending on the scope of the mission, as well as, the energy consumption needs of the network, the number of operational AUVs and required operation time, recharging specifications, communication and localization means, and environmental variables.

Such a system will play a vital role in real-time controlled applications across multiple disciplines, such as: sensor networks, robotics, and transportation systems where limited power resources and unknown environmental dynamics pose major constraints. All developed tools will be suited for the capabilities of not only low-cost AUVs with limited sensing and computational resources, but also high-tech AUVs with state of the art sensor packages.

Broader Impacts:

The developed active power distribution system focuses on underwater scenarios, but will be transferrable to space, air, and ground missions as well. This type of feasible power distribution solution can be used to optimize: 1) immediate high-risk disaster recovery missions like the Fukushima nuclear plant accident; 2) search missions that require vast underwater inspection and detection like the Malaysia MH370 passenger aircraft; and 3) long-term space observation and monitoring like that of the lunar skylight or Europa space mission. The findings from this project will be disseminated through publications, software sharing, and technology commercialization. The project provides interdisciplinary training opportunities for graduate, undergraduate, and pre-college students, including those from underrepresented groups. Research activities will be integrated with education through curriculum development, outreach and improved GUPPIE design.

MTU Consortium in Diesel Engine Aftertreatment Research

Starting from a well-established research program and as a result of a Dept. of Energy 3 year project, we have significantly enhanced our laboratory, experimental methods and procedures, and modeling/estimator capability. The faculty and students have produced thirteen publications from this research.

Consortium Goal:

The underling goal of the consortium is to develop and conduct precompetitive research on advanced aftertreatment systems through experimental engine methods, development and calibration of high fidelity models, and development and application of estimators and controllers. Achieving this goal will provide an improved understanding of the systems under dynamic and low temperature conditions characteristic of advanced medium and heavy duty diesel engines allowing the consortium members to apply this knowledge and models to improve system performance, reduce cost, and develop new approaches to diagnostics and increase robustness of their on-board-diagnostics.

Research Activities:

The existing facilities and an extensive model base will be used as developed in previous research including the current DOE program. This includes temperature controlled exhaust, positive torque drive cycles, and validated component models and estimators. Additionally we will add real-time functionality to perform aftertreatment estimation and control in the engine test cell.

The consortium research themes integrate fundamental and applied aspects of (1) Experimental Engine Studies (2) Modeling and Simulation and (3) Estimation, Control, and diagnostics. The proposed research is split into three major themes (I) Experimental, (II) Modeling, and (III) Estimation and Controls with a number of outcomes from the composite research program.

Areas of study will be determined based upon proposed research by MTU with input from the Partners to direct the research.

Based upon input from our partners and continuing some efforts from the DOE program, the following have been identified as key areas from which yearly research topics will be selected.

• Experimentally validated reduced order models and state estimation algorithms of aftertreatment components which are accurate for low temperature and dynamic operation.
• Quantify particulate matter (PM) maldistribution, loading, and NO2/PM ratio effects on passive and active regeneration, bio-fuel blends, and aging for catalyzed particulate filters (CPFs).
• Increased knowledge of ammonia (NH3) storage behavior, optimal NH3 loading, hydrocarbon (HC) poisoning, and aging for selective catalytic reduction (SCR) catalysts
• Understanding effect of sensor type/configuration on state estimation quality.
• Optimal reductant strategies for SCR operation and CPF regeneration.
• Integrated response and optimization of engine feedgas and aftertreatment systems
• Thermal control of the aftertreatment components for light-off, maintaining operational temperature, and regeneration relevant to engine low temperature operation and integration with exhaust energy recovery systems
• Fundamental studies of DEF introduction and functional responses – hydrolysis and pyrolysis
• Diagnostic concept development: Based upon existing virtual sensor and estimator work this will be translated into system and component diagnostics
• Sensor displacement by applying estimators and virtual sensors. For example, determining whether a NH ₃ sensor is needed if an accurate SCR NH ₃ storage model is available.
• Improved DPF PM estimation and measurement. Although systems are going to increase passive oxidation with engines moving to higher NO _X and lower PM, this is still an important research area to improve methods to accurately estimate CPF loading.
• Alternative and integrated aftertreatment technologies such as integrated SCR with PM filtration. Many fundamental questions remain about this technology including architecture of combining functions that still enable high passive PM oxidation and high NO _X conversion.
• PM Sampling and related diagnostic use. Quantifying the effect of sensor location on the ability to detect failures. does it matter where the sensor is and what the type of failure is. e.g. For example, how does the location of the PM sensor impact the speed of CPF melt down detection and can this speed of detection be optimized?