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In an earlier paper, the authors described how Model-Based System Engineering could be utilized to provide a virtual Hardware-in-the-Loop simulation capability, which creates a framework for the development of virtual ECU software by providing a platform upon which embedded control algorithms may be developed, tested, updated, and validated. The development of virtual ECU software is increasingly valuable in automotive control system engineering because vehicle systems are becoming more complex and tightly integrated, which requires that interactions between subsystems be evaluated during the design process. Variational analysis and robustness studies are also important and become more difficult to perform with real hardware as system complexity increases. The methodology described in this paper permits algorithm development to be performed prior to the availability of vehicle and control system hardware by providing what is essentially a virtual integration vehicle.

In this study, a molten salt-based high temperature nanofluid is explored for solar thermal energy conversion applications. The efficacy of the nanofluid as a heat transfer fluid (HTF) in concentrating solar power systems is explored in this study. The molten salt can enable higher operating temperature resulting in enhancement of the overall system efficiency for power generation (using, for example, a Rankine cycle or Stirling cycle). However, the usage of the molten salt as the HTF is limited due to their low specific heat capacity values (compared with, for example, water or silicone oils). The low specific heat of molten salt can be enhanced by doping small amount of nanoparticles. Solvents doped with minute concentration of nanoparticles are termed as "Nanofluids." Nanofluids are considered as attractive coolants for thermal management applications due to their anomalously enhanced thermal properties (compared with the neat solvent).

For a series plug-in hybrid electric vehicle (PHEV), it is critical that batteries be sized to maximize vehicle performance variables, such as fuel efficiency, gasoline savings, and zero emission capability. The wide range of design choices and the cost of prototype vehicles calls for a development process to quickly and systematically determine the design characteristics of the battery pack, including its size, and vehicle-level control parameters that maximize the net present value (NPV) of a vehicle during the planning stage. Argonne National Laboratory has developed Autonomie, a modeling and simulation framework. With support from The MathWorks, Argonne has integrated an optimization algorithm and parallel computing tools to enable the aforementioned development process. This paper presents a study that utilized the development process, where the NPV is the present value of all the future expenses and savings associated with the vehicle.

Model-based control system design improves quality, shortens development time, lowers engineering cost, and reduces rework. Evaluating a control system's performance, functionality, and robustness in a simulation environment avoids the time and expense of developing hardware and software for each design iteration. Simulating the performance of a design can be straightforward (though sometimes tedious, depending on the complexity of the system being developed) with mathematical models for the hardware components of the system (plant models) and control algorithms for embedded controllers. This paper describes a software tool and a methodology that not only allows a complete system simulation to be performed early in the product design cycle, but also greatly facilitates the construction of the model by automatically connecting the components and subsystems that comprise it.

A prototype packed bed convective dryer has been studied for use in an energy-efficient closed air-loop heat-pump drying system for astronaut cabin waste. This paper presents a transient continuum model for the heat and mass transfer between the air and wet ersatz trash in the cylindrical drying vessel. The model is based on conservation equations for energy and moisture applied to the air and solid phases and its formulation includes the unique waste characteristic of having both dry and wet solids. It incorporates heat and mass transfer coefficients for the system measured on an ersatz trash in the dryer vessel, and experimentally determined moisture sorption equilibrium relationship for the wet material. The resulting system of differential equations is solved by the finite-volume method as implemented by the commercial software COMSOL. The validated model will be used in the optimization of the entire closed-loop system consisting of dryer, condenser, and heat-recovery modules.

The addition of metal nanoparticles to standard coolant fluids dramatically increases the thermal conductivity of the liquid. The properties of the prepared nanofluids will allow for lighter, smaller, and higher efficiency spacecraft thermal control systems to be developed. Nanofluids with spherical or rod-shaped metal nanoparticles were investigated. At a volume concentration of 0.5%, the room temperature thermal conductivity of a 2 nm spherical gold nanoparticle-water solution was increased by more than 10% over water alone. Silver nanorods increased the thermal conductivity of ethylene glycol by 53% and water by 26%.

The operating pressure is one of the critical issues in designing a gasoline-fueled PEM fuel cell system for transportation applications. Pressurized (3atm) and atmospheric pressure (1atm) fuel cell systems are being considered by various developers for automotive applications. Systems analyses have been performed for the two systems using GCtool, a computer simulation code developed at Argonne National Laboratory. The two systems were designed for comparable overall system efficiencies at a rated design power of 50 kW. The characteristics and performance of the different components of the two systems were compared at the design power and at part-load operating conditions. Transient analyses were performed to investigate the dynamic response of the two systems during cold startup. The pros and cons of the two systems regarding their performance, size, and preliminary cost estimates are presented.

The crew diet in a bioregenerative lifesupport system will be a combination of foods grown and processed in’situ with resupplied prepackaged foods and ingredients. The ideal diet should be palatable, nutritionally adequate, varied and low in cost. This diet can be obtained by adopting an optimization strategy combining panel acceptance data, nutritional analyses and mission specific ESM (equivalent system mass) cost estimates for a large selection of foods and ingredients. A linear programming routine selects the lowest cost diet from the foods surveyed, subject to constraints on nutrient content, food acceptability, and variety. The rigor of these constraints is a key factor in determining the cost of the diet (s) they define. By varying individual constraints over several optimizations, we can estimate sensitivity of overall costs to a particular nutrient, or even an intangible quality such as acceptability, while controlling other aspects of the diet.

Jet Engines may experience severe vibration due to the sudden imbalance caused by blade failure. This research investigates employment of on board magnetic bearings or piezolectric actuators to cancel these forces in flight. This operation requires identification of the source of the vibrations via an expert system, determination of the required phase angles and amplitudes for the correction forces, and application of the desired control signals to the magnetic bearings or piezo electric actuators. This paper will show the architecture of the software system, details of the control algorithm used for the sudden imbalance correction project described above, and the laboratory test results.

New dc to dc converter topologies are presented which are suitable for high density high power supplies. Topological variations of the basic inverse dual converter (IDC) circuit such as the transformer coupled, the multiphase and the multipulse derivation of the single phase IDC have been analysed and some simulation results have been presented. It has been shown in a recent publication [1] that the single phase IDC offers a buck-boost operation over wide range without transformer, bidirectional power flow, and complementary commutation of the switches. The topologies examined in this paper have additional features such as lower device and component stresses, and smaller filter requirements, resulting in smaller size and weight. Some performance and possible applications are also examined. Finally the IDCs for serial and parallel power distribution, and ac tapping of the IDC are discussed.

Artificial Neural Network(ANN) techniques are used to develop a system to detect High Impedance Faults(HIFs) in electric power distribution lines. Encouraging results were observed with a simple Multi-layer Perceptron(MLP) trained with the backpropagation learning algorithm. Although the results are not significantly better than those reported with other algorithmic approaches, ANN techniques have potential advantages over the other approaches; namely, ability to train the system easily to accommodate different feeder characteristics, ability to adapt and so become a better detector with experience and better fault tolerance. When these features are incorporated, the system is expected to perform better than existing systems. The system we developed for the current phase, the training strategies used, the tests conducted and the results obtained are discussed in this paper. Also background discussions on existing HIF detection techniques, and ANN techniques can be found in this paper.