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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.

Many accidents occur today when distant objects or roadway impediments are not quickly detected. To help avoid these accidents, longer-range safety systems are needed with real-time detection capability and without requiring a line-of-sight (LOS) view by the driver or sensor. Early detection at intersections is required for obstacle location around blind corners and dynamic awareness of approaching vehicles on intersecting roadways. Many of today's vehicular safety systems require short LOS distances to be effective. Such systems include forward collision warning, adaptive cruise control, and lane keeping assistance. To operate over longer LOS distances and in Non-LOS (NLOS) conditions, cooperative wireless communications systems are being considered. This paper describes field results for LOS and NLOS radio links for one candidate wireless system: 5.9GHz Dedicated Short Range Communications (DSRC).

In automotive electronics on-board diagnostics does the fault diagnosis and reporting. It provides the level of robustness required for the control electronics against various faults. The amount of diagnostic information available via on board diagnostics are depends on the type of vehicle. Pre-supply fuel pump is the component in the common rail hydraulic system. It pumps the fuel from the fuel tank to the inlet valve of the high pressure fuel pump. Electronic control unit synchronizes its operation with high pressure fuel pump. A dedicated driver module in the ECU controls the operation of pre-supply fuel pump. The driver module consist of an ASIC with internal voltage, current monitoring modules for the fault diagnosis and the pre-drivers to control external HS and LS power stages. The software part of the OBD programmed in the internal memory of the ASIC. The “Rds_on” of the power MOSFETs are used for the fault detection purpose.

The migration of automotive companies to model based engineering for the software development of electronic control units, ECU’s, has been driven largely by three potential benefits; cycle time reduction, quality improvement, and defect reduction. Through an examination of the process and methodology used during an actual project with an automotive OEM, this paper shall discuss some of the lessons learned during the project implementation phase. It will also explore how the deployment of an effective model based engineering process framework, process components, and methodology can assist an organization in realizing the documented benefits of model based engineering.

Mathematical modeling and control of artificial ecosystems, such as MELISSA, require first the study of physical and biological characteristics in optimal and limiting conditions. Following the previous determination of the stoichiometric equations (Spirulina compartment) and regarding the two phototrophic compartments of MELISSA (Rhodospirillaceae and Spirulina), we have first to focus our control study on the growth kinetics for the light source. In this paper, we recall the theoretical equations of microbial growth kinetics and emphasise the problem of the light transfer in a photobioreactor. We present their adaptations to our pilot plant taking into account technological and biological specifics (lamp spectrum, working illuminated volume, growth rate,…). We then develop the principles and structure of the control system and describe tests of both the hardware and software for several steady state configurations.

This paper describes the application of statistical techniques known as Design of Experiments (D.O.E.) to efficiently use the results of numerical analysis data in order to improve the configuration of automotive systems. The general framework of these techniques is presented in a format aiming at the design engineer as their end user. Besides, a case study is presented with the purpose of illustrating their practical use. The first step of the case study is to build predictive models for the behaviour of the automotive system being developed by means of the Response Surface Method (RSM), using the proper D.O.E. options. Once these predictive models are available, automatic numerical optimization algorithms are used to improve the responses of interest for given operating conditions. Finally, the automotive systems are robust designed taking into account that the operating conditions vary randomly.

This paper is an extension of our previous work on the CHASE (Classification by Holistic Analysis of Scene Environment) algorithm, that automatically classifies the driving complexity of a road scene image during day-time conditions and assigns it an ‘Ease of Driving’ (EoD) score. At night, apart from traffic variations and road type conditions, illumination changes are a major predominant factor that affect the road visibility and the driving easiness. In order to resolve the problem of analyzing the driving complexity of roads at night, a brightness detection module is incorporated in our end-to-end nighttime EoD system, which computes the ‘brightness factor’ (bright or dark) for that given night-time road scene. The brightness factor along with a multi-level machine learning classifier is then used to classify the EoD score for a night-time road scene. Our end-to-end ‘Night-time EoD system’ is a real-time onboard system implemented and tested on road scene data collected in Japan.

The objective of the development of the aerodynamic drag predictive tool CDaero was for use as a module for the Automobile Design Support System (AutoDSS). CDaero is an empirically based drag coefficient predictive tool based initially on the MIRA (Motor Industry Research Association) algorithm. The development philosophy was to be able to predict the aerodynamic drag coefficient of an automobile with knowledge of the features of the surface geometry control curves. These are the curves that control the 3-dimensional geometry as seen in the profile, plan and front and rear views. CDaero has been developed in a computing environment using the equation solver TKSolver™. Fifty-one input feature values are first determined from the automobile geometry and then entered into the program. CDaero models the drag coefficient with thirteen different components covering the basic body, as well as additional components such as the wheels, mud flaps, etc.

This paper discusses the use of electromechanical devices as the kinematic portions of a microprocessor based gas turbine control system. Specific applications are: 1. An electric motor driven, positive displacement pump, which provides metered high pressure fuel to the distribution manifold. Fuel metering to be provided by varying the motor angular velocity. 2. An electric motor driven lube oil pump. 3. Electromechnical actuators for motion and control of compressor and power turbine variable geometry. 4. A starter/generator integral with the gas generator. Topics covered include: Comparison to conventional hydro-mechanical systems. Response characteristics of the fuel pump and actuator systems. Brushless D.C. motor characteristics. Power electronics requirements for brushless D.C. motors. Control electronics interface with brushless D.C. motor systems. Reliability and maintainability issues. Diagnostic/prognostic enhancements.

Propulsion system control algorithms covering the functional needs of xEV propulsion (‘x’ donates P0-P4 configurations) systems are presented in this paper. The scope and foundation are based on generic well-established HEV controller architectures. However, unlike conventional HEV (series, parallel and power split) powertrains, the next generation of integrated electric propulsion configurations will utilize a single micro controller that supports multiple control functions ranging from the electric machines, inverters, actuators, clutch solenoids, coolant pumps, etc. This presents a unique challenge to architect control algorithms within the AUTOSAR framework while satisfying the complex timing requirements of motor/generator-inverter (MGi) control and increased interface definitions between software components to realize functional integration between the higher level propulsion system and its sub-systems.

Mobility is in the midst of an electric revolution, propelled by industry innovators such as magniX. Headquartered in Redmond, Washington, the magniX team is focused on revolutionizing electric motors for commercial aviation applications.

Nowadays automobiles are getting smart and there is a growing need for the physical behavior to become part of its software. This behavior can be described in a compact form by differential equations obtained from modeling and simulation tools. In the offline simulation domain the Functional Mockup Interface (FMI) [3], a popular standard today supported by many tools, allows to integrate a model with solver (Co-Simulation FMU) into another simulation environment. These models cannot be directly integrated into embedded automotive software due to special restrictions with respect to hard real-time constraints and MISRA compliance. Another architectural restriction is organizing software components according to the AUTOSAR standard which is typically not supported by the physical modeling tools. On the other hand AUTOSAR generating tools do not have the required advanced symbolic and numerical features to process differential equations.

eBrake® (1, 2) - a new “brake-by-wire” technology, was developed at the German Aerospace Centre, DLR e.V.. It is based on an electric powered controlled friction brake with high self-reinforcement capability. To avoid jamming the brake a special control technology was developed. Thus, by intelligently controlling a brake wedge, the kinetic energy of a vehicle is transformed into braking power. Furthermore an advanced design was found to deal with a broad variation of the friction coefficient. The physical effects involved lead to a significant reduction of energy consumption of the brake actuator compared to “conventional” brake-by-wire systems.

With the increase in demand for energy sustainability projects over the last few years, the Brazilian commercial vehicle industry was guided to develop projects based on ESG policies. Aligned with this need, an initiative that ended up becoming a reality was the “e-Sys” electrification solution, by the company Suspensys. This solution includes a power source (battery), an e-powertrain (motors, inverters and drive axle) and an intelligent control system (VCU with embedded code and sensors). The main motivational drive was the hybridization of semi-trailers, in order to generate a reduction in fuel consumption in cargo transport in Brazil, in addition to the consequent reduction in the emission of particles into the environment and promoting the safety of the operation. It was also adopted, as a premise of the project, that the electrification system was totally independent of the truck’s electronic system (stand alone system), in order to facilitate the operation of the fleet owner.

The permanently increasing number of convenience and safety functions leads to higher complexity of in-car electronics and the rapidly growing amount of sensors, actuators and electronic control units places higher demands on high- speed data communication protocols. Safety-critical systems need deterministic protocols with fault-tolerant behavior. The need for on-board diagnosis calls for flexible use of bandwidth and an ever-increasing number of functions necessitates a flexible means of extending the system. None of the communication solutions available on the market until now (like CAN or TTP) have been able to fulfill all these demands. To solve these problems, BMW together with several semiconductor companies has developed a new protocol for safety-critical applications in automotive vehicles.

A “next generation” condensing heat exchanger for space systems has to satisfy demanding operational requirements under variable thermal and moisture loads and reduced gravity conditions. Mathematical models described here are used to investigate transient behavior of wetting and de-wetting dynamics in the binary porous system of porous tubes and porous cold plate. The model is based on the Richard's equation simplified for the zero-gravity conditions. The half-saturation distance or the zone of influence of the porous annular suction tubes on the cold-plate porous material will be in the range of 1 to 10 cm for the time scales ranging from 100 to 10,000 seconds and moisture diffusivity in the range of D = 10-4 to 10-6 m2/s.

The preceeding presentation explained the compositions of the zinc alloys. Now we can examine the properties that these combinations give rise to. In doing so, we must first understand the importance of each property to the design of any component. One must consider each of the properties individually so as to gain an understanding of cumulative effects and the relative importance of each property to the final application. The most effective way to attack the problem is to analyze the part's requirements with respect to applied stresses, environmental and operating conditions and economic constraints. While there are many mathematical models available to enable numerical analysis of property evaluations, they all rely on the same basic principle: The Total Systems Approach. That is, the consideration of all aspects of design. Properties evaluation is a critical step in this process.

Recent developments in the commercialization of mobility services have brought unprecedented connectivity to the automotive sector. While the adoption of connected features provides significant benefits to vehicle owners, adversaries may leverage zero-day attacks to target the expanded attack surface and make unauthorized access to sensitive data. Protecting new generations of automotive controllers against malicious intrusions requires solutions that do not depend on conventional countermeasures, which often fall short when pitted against sophisticated exploitation attempts. In this paper, we describe some of the latent risks in current automotive systems along with a well-engineered multi-layer defense strategy. Further, we introduce a novel and comprehensive attack and performance test framework which considers state-of-the-art memory corruption attacks, countermeasures and evaluation methods.

As the demand for more complex system development and the ever-increasing requirement for improvement in software productivity, the need for graphical programming or Zero-Hand Coding for automatic generation of controller software becomes highly desirable. The graphical programming must not be limited to the algorithm development which consists of the application modules but must be extended to the microcontroller platform, which include the middleware (i.e. operating system, I/O device drivers) and hardware. Automatic code generation is very important for programming the complex microcontroller internal parameters and registers. The combined software tool chain is to generate the final target specific executable code. This approach is very beneficial for system development, reduction of the development cycle and bridges the gap between control and software engineers reducing time, effort and cost of the production software.

This paper describes the development of a set of algorithms that find the takeoff gross weight of an aircraft for given vehicle and engine characteristics, and mission requirements. A major objective was to find the most elementary set that would still yield useful answers. The result was a set that could be encoded on an inexpensive programmable pocket calculator with only 24 lines of code. Results are compared with actual characteristics of an executive jet and its derivative versions.