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For years the trend in the automotive industry has been toward more complex electronic control systems. The number of electronic control units (ECUs) in vehicles is ever increasing as is the complexity of communication networks among the ECUs. Increasing fuel economy standards and the increasing cost of fuel is driving hybridization and electrification of the automobile. Achieving superior fuel economy with a hybrid powertrain requires an effective and optimized control system. On the other hand, mathematical modeling and simulation tools have become extremely advanced and have turned simulation into a powerful design tool. The combination of increasing control system complexity and simulation technology has led to an industry wide trend toward model based control design. Rather than using models to analyze and validate real world testing data, simulation is now the primary tool used in the design process long before real world testing is possible. Modeling is used in every step from architecture selection to control system validation before on-road testing begins. The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech is participating in the 2011-2014 EcoCAR 2 competition in which the team is tasked with re-engineering the powertrain of a GM donated vehicle. The primary goals of the competition are to reduce well to wheels (WTW) petroleum energy use (PEU) and reduce WTW greenhouse gas (GHG) and criteria emissions while maintaining performance, safety, and consumer acceptability. This paper will present systematic methodology for using model based design techniques for architecture selection, control system design, control strategy optimization, and controller validation to meet the goals of the competition. Simple energy management and efficiency analysis will form the primary basis of architecture selection. Using a novel method, a series-parallel powertrain architecture is selected. The control system architecture and requirements is defined using a systematic approach based around the interactions between control units. Vehicle communication networks are designed to facilitate efficient data flow. Software-in-the-loop (SIL) simulation with Mathworks Simulink is used to refine a control strategy to maximize fuel economy. Finally hardware-in-the-loop (HIL) testing on a dSPACE HIL simulator is demonstrated for performance improvements, as well as for safety critical controller validation. The end product of this design study is a control system that has reached a high level of parameter optimization and validation ready for on-road testing in a vehicle. / Master of Science

This paper is an investigation into a quantitative selection process of either a mechanical or electrical system architecture for the transmission of propulsion power in naval combatant vessels. A database of historical naval ship characteristics was statistically analyzed to determine if there were any predominant ship parameters that could be used to predict whether a ship should be designed with a mechanical power transmission system or an electric one. A Principal Component Analysis was performed to determine the minimum number of dimensions required to define the relationship between the propulsion transmission architecture and the independent variables. Combining the results of the statistical analysis and the PCA, neural networks were trained and tested to separately predict the transmission architecture or the installed electrical generation capacity of a given class of naval combatant.

Durant la phase de conception, les différentes équipes d’ingénierie procèdent à de multiples simulations par éléments finis traitant les comportements physiques variés afin d’assurer la vérification et la validation.Cependant, les résultats insatisfaisants engendrent des changements tardifs et par conséquent de longues itérations et des coûts croissants.Pour répondre à cette problématique, il est essentiel de prendre en considération les contraintes géométriques et multi-physiques dès la phase de préconception.En effet, un processus appelé SAMOS est développé visant à sélectionner l’architecture multi-physique 3D la plus adéquate tout en garantissant une collaboration efficace entre les équipes d’ingénieurs. D’ailleurs, il est basé sur deux extensions en SysML permettant l’enrichissement de l’architecture par des informations géométriques et multi-physiques.D’autre part, cette thèse se focalise sur l’étude des contraintes magnétiques et du couplage magnétique-thermique.Comme cette phase ne supporte pas les simulations par éléments finis, les modèles analytiques basés sur des géométries simplifiées sont suffisants pour fournir des résultats approximatifs satisfaisants.Dans ce contexte, différents modèles analytiques sont étudiés et validés à travers des simulations par éléments finis et des mesures pour plusieurs cas tels que les aimants permanents en Néodyme. En fait, l’augmentation de température ne fait pas seulement diminuer la densité du flux magnétique rémanente mais il est capable de causer des pertes irréversibles. En effet, lorsqu’on revient à la température initiale, les caractéristiques de l’aimant sont modifiées. Les différents facteurs affectant le processus de démagnétisation sont examinés.De plus, l’impact de la température sur les performances d’un moteur sans balais est étudié étant donné que ce dispositif représente un système mécatronique complexe. / During the design phase, the different engineering teams make multiple FE simulations dealing with various physical behaviours in order to ensure both verification and validation.However, the unsatisfactory results lead to late changes and hence to long iterations and increasing costs.In order to tackle this problem, it is essential to take into account the geometrical and multi-physical constraints in the complex system architecture since the conceptual design phase.In fact, a process called SAMOS is developed aiming at selecting the most adequate 3D multi-physical architecture while ensuring an efficient collaboration between the engineering teams. Moreover, this framework is based on two SysML extensions which allow the enrichment of the architecture with geometrical and multi-physical data.Furthermore, this thesis focuses on magnetic constraints and magnetic-thermal coupling.Since this phase does not support long FE simulations, the analytical models based on simplified geometries are sufficient to provide satisfactory approximate results.In this context, different analytical models are studied and validated through FE simulations and measures for several cases such as NdFeB permanent magnets. Indeed, the temperature rise does not only decrease the remanent flux density but is able also to cause irreversible losses. In fact, once we go back to the initial temperature, the characteristics of the magnet are modified. The different factors impacting the demagnetization process are discussed.Besides, the temperature impact on brushless motors’ performances is studied since this device represents a complex mechatronic system.

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