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The aim of this work is to apply an innovative adaptive ℒ1 techniques to control flutter phenomena affecting highly flexible wings and to evaluate the efficiency of this control algorithm and architecture by performing the following tasks: i) adaptation and analysis of an existing simplified nonlinear plunging/pitching 2D aeroelastic model accounting for structural nonlinearities and a quasi-steady aerodynamics capable of describing flutter and post-flutter limit cycle oscillations, ii) implement the ℒ1 adaptive control on the developed aeroelastic system to perform initial control testing and evaluate the sensitivity to system parameters, and iii) perform model validation and calibration by comparing the performance of the proposed control strategy with an adaptive back-stepping algorithm. The effectiveness and robustness of the ℒ1 adaptive control in flutter and post-flutter suppression is demonstrated.

The Weapon Combat Effectiveness (WCE) analytics is very expensive, time-consuming, and dangerous in the real world because we have to create data from the real operations with a lot of people and weapons in the actual environment. The Modeling and Simulation (M&S) of many techniques are used for overcoming these limitations. Although the era of big data has emerged and achieved a great deal of success in a variety of fields, most of WCE research using the Defense Modeling and Simulation (DM&S) techniques studied have considered a lot of assumptions and limited scenarios without the help of big data technologies. Furthermore, WCE analytics using previous methodologies cannot help but get the bias results. This paper reviews and combines the basic knowledge for the new WCE analytics methodology using big data and M&S to overcome these problems of bias. Then this paper reviews the general overview of WCE, DM&S, and big data.

The clutch is that mechanical part located in an internal combustion engine vehicle which allows the torque transmission from the shaft to the wheels, permitting at the same time gear shifting and supporting engine revolutions while the car is idling. This component exploits friction as working principle, therefore heat generation is in its own nature. The comprehension of all the critical issues related to thermal emission, and also of the principal physical parameters driving the phenomena are a must in design phases. The subject of this paper is the elaboration of an accurate, but also easy to use and easily replicable, methodology to simulate thermal behavior of a clutch operating inside its usual environment. The present methodology allows to prevent corrective actions in the last phase of the projects (real testing), such as changes in gear ratios, that likely worsen CO2 emissions, permitting to achieve the wished thermal performance of the clutch avoiding late changes.

Vehicle dynamics estimation has been the subject of study for some years now. If on-board vehicle control systems can be provided with information such as side slip angle, lateral force etc. then stability of the vehicle can be improved. To estimate these dynamic variables different observers have been used e.g., sliding mode, fuzzy logic, neural networks etc. In this article the authors propose an extended Kalman filter to estimate vehicle side slip angle. Roll angle is estimated using vertical loads as input. First, a linear Kalman filter is used to filter out the vertical forces and estimate roll angle. This information is then used to estimate the vehicle side slip angle. To take into account the nonlinearities concerning lateral vehicle dynamics, Pacejka magic formula is used to model lateral forces. Estimated results are then compared with simulations, showing good accuracy.

A method for estimating the vehicle mass in real time is presented. Traditional mass estimation methods suffer due a lack of knowledge of the vehicle parameters, the road surface conditions and most importantly the effect of the vehicle transmission. To resolve these issues, a method independent of a vehicle model is utilized in conjunction with a drivetrain output torque observer to obtain the estimate of the vehicle mass. Simulations and experimental track tests indicate that the method is able to accurately estimate the vehicle mass with a relatively fast rate of convergence compared to traditional methods.

Active Roll Control (ARC) is one of the most promising active systems to improve vehicle comfort and handling. This paper describes the simulation based procedure adopted to conceive a double-channel Active Roll Control system, characterized by the hydraulic actuation of the stabilizer bars of a sedan. The first part of the paper presents the vehicle model adopted for this activity. It is Base Model Simulator (BMS), the 14 Degrees-of-Freedom vehicle model by Politecnico di Torino. It was validated through road tests. Then the paper describes the development of the control algorithm adopted to improve the roll dynamics of the vehicle. The implemented control algorithm is characterized by a first subsystem, capable of obtaining the desired values of body roll angle as a function of lateral acceleration during semi-stationary maneuvers.

The term driveability describes the driver's complex subjective perception of the interactions with the vehicle. One of them is associated to longitudinal acceleration aspects. A relevant contribution to the driveability optimization process is, nowadays, realized by means of track tests during which a considerable amount of driveline parameters are tuned in order to obtain a good compromise of longitudinal acceleration response. Unfortunately, this process is carried out at a development stage when a design iteration becomes too expensive. In addition, the actual trend of downsizing and supercharging the engines leads to higher vibrations that are transmitted to the vehicle. A large effort is therefore dedicated to develop, test and implement ignition strategies addressed to minimize the torque irregularities. Such strategies could penalize the engine maximum performance, efficiency and emissions. The introduction of the dual mass flywheel is beneficial to this end.

The term “productivity” all too often has becomes a buzz-word, ultimately diminishing its perceived importance. However, productivity is the major concern of any team, and therefore must be defined to gain an appropriate understanding of how a system is actually working. Here, productivity means the level of contribution to the throughput of a system such as defined in the Theory of Constraints. In the field of space exploration, the throughput is the number of milestones of the mission accomplished as well as the potential survival during extreme events (due to failures or other unplanned events). For a time tasks were accomplished by expert individuals (e.g., an astronaut), but recently team structures have become the norm. It is clear that with increased mission complexity, “no single entity can have complete knowledge of or the abilities to handle all matters” [10].

The efficiency in energy consumption of an electric vehicle (EV) has significant value to both vehicle manufacturers and vehicle owners. Such efficiency will directly impact the cost of energy and vehicle range while relieving the stringent requirements on the DC motor and battery specs. Nowadays, with the development of advanced driver assistance systems (ADAS), such as adaptive cruise control (ACC) or cooperative adaptive cruise control (CACC), drivers enjoy a much safer driving experience. ADAS capabilities in sensory, computing and communication can be leveraged in EVs for the purpose of optimizing energy consumption. This paper introduces an energy-optimized ACC platform, which utilizes a forecast of the speed profile of the host vehicle in a short (few seconds) horizon. Such speed information can be available through ADAS or similar systems. This paper focuses on optimization in longitudinal tracks.

In this paper, we introduce the use of ontologies to implement the information developed and organized by resource planning tools into standard project management documents covering integrated cost, resource modeling and analysis, and visualization. The basic upper ontology used for NASA Space Operations is explained and the results obtained are discussed. This ontology-centered approach is looking for tighter connections between software, hardware, and systems engineering.

The potential of an electric assisted turbocharger for a heavy-duty diesel engine has been analyzed in this work, in order to evaluate the turbo-lag reductions and the fuel consumption savings that could be obtained in an urban bus for different operating conditions. The aim of the research project was to replace the current variable geometry turbine with a fixed geometry turbine, connecting an electric machine which can be operated both as an electric motor and as an electric generator to the turbo shaft. The electric motor can be used to speed up the turbocharger during the acceleration transients and reduce the turbo-lag, while the generator can be used to recover the excess exhaust energy when the engine is operated near the rated speed, in order to produce electrical power that can be used to drive engine auxiliaries. In this way the engine efficiency can be improved and a kind of “electric turbocompounding” can be obtained.

Plug-in Hybrid Electric Vehicles (PHEVs) are one of the main technology options for reducing vehicle CO2 emissions and helping vehicle manufacturers (OEMs) to meet the CO2 targets set by different Governments from all around the world. In Europe OEMs have introduced a number of PHEV models to meet their CO2 target of 95 g/km for passenger cars set for the year 2021. Fuel consumption (FC) and CO2 emissions from PHEVs, however, strongly depend on the way they are used and on the frequency with which their battery is charged by the user. Studies have indeed revealed that in real life, with poor charging behavior from users, PHEV FC is equivalent to that of conventional vehicles, and in some cases higher, due to the increased mass and the need to keep the battery at a certain charging level.

In this study we consider the coordinated exploration of an unfamiliar Martian landscape by a swarm of small autonomous rovers, called Swarmies, simulated in a distributed setting. With a sustainable program of return missions to and from Mars in mind, the goal of said exploration is to efficiently prospect the terrain for water meant to be gathered and then utilized in the production of rocket fuel. The rovers are tasked with relaying relevant data to a home base that is responsible for maintaining a mining schedule for an arbitrarily large group of rovers extracting water-rich regolith. For this reason, it is crucial that the participants maintain a wireless connection with one another and with the base throughout the entire process. We describe the architecture of our simulation which is composed of HLA-compliant components that are visualized via the Distributed Observer Network tool developed by NASA.

In this paper a test bench for measuring the Static Transmission Error of two mating gears is presented and a comparison with the results obtained with the commercial software GeDy TrAss is shown. Static Transmission Error is considered as the main source of overloads and Noise, Vibration and Harshness issues in mechanical transmissions. It is defined as the difference between the theoretical angular position of two gears under load in quasi-static conditions and the real one. This parameter strictly depends on the applied torque and the tooth macro and micro-geometry. The test bench illustrated in this work is designed to evaluate the actual Static Transmission Error of two gears under load in quasi-static conditions. In particular, this testbed can be divided in two macro elements: the first one is the mechanism composed by weights and pulleys that generates a driving and a braking torque up to 500 Nm.

The trend towards powertrain electrification is expected to grow significantly in the next future also for super-cars. The aim of this paper is therefore to assess, through numerical simulation, the impact on both fuel economy and performance of different 48 Volt mild hybrid architectures for a high-performance sport car featuring a Turbocharged Direct Injection Spark Ignition (TDISI) engine. In particular the hybrid functionalities of both a P0 (Belt Alternator Starter - BAS) and a P2 (Flywheel Alternator Starter - FAS) architecture were investigated and optimized for this kind of application through a global optimization algorithm. The analysis pointed out CO2 emission reductions potential of about 6% and 25% on NEDC, 7% and 28% on WLTC for P0 and P2 respectively. From the performance perspective, a 10% reduction in the time-to-torque was highlighted for both architectures in a load step maneuver at 2000 RPM constant speed.

This study introduces a new practical calibration approach of ductile fracture models by performing square punch tests on metal sheets. During square punch tests, ductile fracture occurs at either the corner of die or punch radius when applying different clamping loads and lubrication conditions. At the corner of die radius, in-plane pure shear is induced at the intersection between the side-walls and the flange by combined tension and compression. On the other hand, the material at the corner of the punch radius is under combined bending and biaxial tension. The material studied in this paper is advanced high strength steel (AHSS) DP780 from ArcelorMittal. Isotropic J2 plasticity model with mixed Swift-Voce hardening rule is calibrated from uniaxial tensile tests.

This paper deals with the design and development of an innovative airship concept which is remotely-controlled and intended to be used for monitoring, surveillance, exploration and reconnaissance missions. Two potential solutions have been analyzed: the first consists of a double-hull configuration, characterized by the presence of a primary support structure connected by appropriated bindings to a couple of twin inflatable hulls. The second architecture is a soap-shaped exoskeleton configuration which features a single inflated section, incorporating two separate elements held internally by a system of ribs. The aim of this study is to analyze and compare the two configurations, to determine the most appropriate solution in terms of performance, cost and maneuvering capabilities

The making of a quilt is an interesting process. Historically, a quilt is a canvas of work made from old pieces of cloth cut into squares or whatever shape that make a nice connected pattern and then stitched together. The quilt could be random pieces that is not related to each other. In most recent years and more common cases, a quilt is made of different pieces of patches that are connected and laid out in a special way to tell a story. Not only does it portray a story that is put together in a certain sequence, but it also stiches the pieces of the quilt into a nice and complete narrative. A story that one can understand just by looking at the quilt spread and unfolded. Much like the making of a quilt that has a story to tell, a Product Digital Quilt will tell the story of a product. The Digital Product Quilt replaces the conventional way of telling a product story. The traditional product story is a method that is serially connecting multiple product life cycle silos together.

The application of Statistical Process Control and Design of Experiment methods in the research laboratory can lead to significant gains in the Powertrain development process. Empirical methods such as Design of Experiments, Regression, and Neural Network techniques can be applied to help researchers gain better understanding of the cause and effect relationships of emission, alternative fuel source, performance, fuel economy, and engine management system - calibration studies. The use of these empirical modeling techniques along with model based Genetic Algorithm, Gradient, or Constraint based solution search methods will help identify the “process settings” that improve fuel economy, improve performance, and reduce pollutants. Since empirical methods are fundamentally based on the acquired test data, it is vitally important that the laboratory measurements are repeatable, consistent, and void of sources of variance that have a significant effect on the acquired test data.

This paper intends to analyze the simultaneous impact of speed and acceleration on exhaust pollutant emissions. For this purpose, actual driving recording were used. Kinematic sequences were randomly selected amongst the recorded data, in order to constitute a representative set of driving conditions. For each sequence, average levels of speed and positive acceleration were calculated. Instantaneous and integrated pollutant emissions were calculated using an existing emission model, developed for calculating pollutant emissions and fuel consumption as functions of instantaneous speed and acceleration. This model is based on instantaneous emission measurements on a chassis dynamometer using actual driving cycles, over a sample of 150 European cars. Emissions of CO, CO2, HC, NOx were analyzed considering the average speed and positive acceleration, for different categories of vehicles Diesel, conventional and catalyst vehicles.