Sviluppo di modelli motore e veicolo per l'analisi di strategie di controllo in applicazioni Software e Hardware In the Loop

This work describes the development of a simulation tool which allows the simulation of the Internal Combustion Engine (ICE), the transmission and the vehicle dynamics. It is a control oriented simulation tool, designed in order to perform both off-line (Software In the Loop) and on-line (Hardware In the Loop) simulation. In the first case the simulation tool can be used in order to optimize Engine Control Unit strategies (as far as regard, for example, the fuel consumption or the performance of the engine), while in the second case it can be used in order to test the control system. In recent years the use of HIL simulations has proved to be very useful in developing and testing of control systems. Hardware In the Loop simulation is a technology where the actual vehicles, engines or other components are replaced by a real time simulation, based on a mathematical model and running in a real time processor. The processor reads ECU (Engine Control Unit) output signals which would normally feed the actuators and, by using mathematical models, provides the signals which would be produced by the actual sensors. The simulation tool, fully designed within Simulink, includes the possibility to simulate the only engine, the transmission and vehicle dynamics and the engine along with the vehicle and transmission dynamics, allowing in this case to evaluate the performance and the operating conditions of the Internal Combustion Engine, once it is installed on a given vehicle. Furthermore the simulation tool includes different level of complexity, since it is possible to use, for example, either a zero-dimensional or a one-dimensional model of the intake system (in this case only for off-line application, because of the higher computational effort). Given these preliminary remarks, an important goal of this work is the development of a simulation environment that can be easily adapted to different engine types (single- or multi-cylinder, four-stroke or two-stroke, diesel or gasoline) and transmission architecture without reprogramming. Also, the same simulation tool can be rapidly configured both for off-line and real-time application. The Matlab-Simulink environment has been adopted to achieve such objectives, since its graphical programming interface allows building flexible and reconfigurable models, and real-time simulation is possible with standard, off-the-shelf software and hardware platforms (such as dSPACE systems).

Development of Hardware-In-the-Loop Simulation System for Hybrid Electric Vehicle Study

The development of embedded control systems for a Hybrid Electric Vehicle (HEV) is a challenging task due to the multidisciplinary nature of HEV powertrain and its complex structures. Hardware-In-the-Loop (HIL) simulation provides an open and convenient environment for the modeling, prototyping, testing and analyzing HEV control systems. This thesis focuses on the development of such a HIL system for the hybrid electric vehicle study. The hardware architecture of the HIL system, including dSPACE eDrive HIL simulator, MicroAutoBox II and MotoTron Engine Control Module (ECM), is introduced. Software used in the system includes dSPACE Real-Time Interface (RTI) blockset, Automotive Simulation Models (ASM), Matlab/Simulink/Stateflow, Real-time Workshop, ControlDesk Next Generation, ModelDesk and MotoHawk/MotoTune. A case study of the development of control systems for a single shaft parallel hybrid electric vehicle is presented to summarize the functionality of this HIL system.

A hardware in the loop design methodology for FPGA system and its application to complex functions

In this work, a unified algorithm-architecture-circuit co-design environment for complex FPGA system development is presented. The main objective is to find an efficient methodology for designing a configurable optimized FPGA system by using as few efforts as possible in verification stage, so as to speed up the development period. A proposed high performance FFT/iFFT processor for Multiband Orthogonal Frequency Division Multiplexing Ultra Wideband (MB-OFDM UWB) system design process is given as an example to demonstrate the proposed methodology. This efficient design methodology is tested and considered to be suitable for almost all types of complex FPGA system designs and verifications.

Development of hardware in the loop real-time control techniques for hybrid power systems involving distributed demands and sustainable energy sources

The future power grid will effectively utilize renewable energy resources and distributed generation to respond to energy demand while incorporating information technology and communication infrastructure for their optimum operation. This dissertation contributes to the development of real-time techniques, for wide-area monitoring and secure real-time control and operation of hybrid power systems. ^ To handle the increased level of real-time data exchange, this dissertation develops a supervisory control and data acquisition (SCADA) system that is equipped with a state estimation scheme from the real-time data. This system is verified on a specially developed laboratory-based test bed facility, as a hardware and software platform, to emulate the actual scenarios of a real hybrid power system with the highest level of similarities and capabilities to practical utility systems. It includes phasor measurements at hundreds of measurement points on the system. These measurements were obtained from especially developed laboratory based Phasor Measurement Unit (PMU) that is utilized in addition to existing commercially based PMU’s. The developed PMU was used in conjunction with the interconnected system along with the commercial PMU’s. The tested studies included a new technique for detecting the partially islanded micro grids in addition to several real-time techniques for synchronization and parameter identifications of hybrid systems. ^ Moreover, due to numerous integration of renewable energy resources through DC microgrids, this dissertation performs several practical cases for improvement of interoperability of such systems. Moreover, increased number of small and dispersed generating stations and their need to connect fast and properly into the AC grids, urged this work to explore the challenges that arise in synchronization of generators to the grid and through introduction of a Dynamic Brake system to improve the process of connecting distributed generators to the power grid.^ Real time operation and control requires data communication security. A research effort in this dissertation was developed based on Trusted Sensing Base (TSB) process for data communication security. The innovative TSB approach improves the security aspect of the power grid as a cyber-physical system. It is based on available GPS synchronization technology and provides protection against confidentiality attacks in critical power system infrastructures. ^

MODELING AND HARDWARE-IN-THE-LOOP SIMULATION OF POWER-SPLIT HYBRID ELECTRIC VEHICLES

Conventional vehicles are creating pollution problems, global warming and the extinction of high density fuels. To address these problems, automotive companies and universities are researching on hybrid electric vehicles where two different power devices are used to propel a vehicle. This research studies the development and testing of a dynamic model for Prius 2010 Hybrid Synergy Drive (HSD), a power-split device. The device was modeled and integrated with a hybrid vehicle model. To add an electric only mode for vehicle propulsion, the hybrid synergy drive was modified by adding a clutch to carrier 1. The performance of the integrated vehicle model was tested with UDDS drive cycle using rule-based control strategy. The dSPACE Hardware-In-the-Loop (HIL) simulator was used for HIL simulation test. The HIL simulation result shows that the integration of developed HSD dynamic model with a hybrid vehicle model was successful. The HSD model was able to split power and isolate engine speed from vehicle speed in hybrid mode.

Hardware-In-The Loop setup and test of an air spring control system

In this work, a Hardware-in-the-loop test bench is designed. The bench is used to test the behaviour of an electronic control unit used in Maserati to control the dynamics of an air spring system. First the mathematical model of the plant has been defined, then the simulation enviroment and the test environment have been set up. The performed tests succesfully highlighted some bugs in the device under test.

Hardware-in-the-loop implementation of single- and dual-phase shift control for dual active bridge converters in EV applications

Isolated DC-DC converters play a significant role in fast charging and maintaining the variable output voltage for EV applications. This study aims to investigate the different Isolated DC-DC converters for onboard and offboard chargers, then, once the topology is selected, study the control techniques and, finally, achieve a real-time converter model to accomplish Hardware-In-The-Loop (HIL) results. Among the different isolated DC-DC topologies, the Dual Active Bridge (DAB) converter has the advantage of allowing bidirectional power flow, which enables operating in both Grid to Vehicle (G2V) and Vehicle to Grid (V2G) modalities. Recently, DAB has been used in the offboard chargers for high voltage applications due to SiC and GaN MOSFETs; this new technology also allows the utilization of higher switching frequencies. By empowering soft switching techniques to reduce switching losses, higher switching frequency operation is possible in DAB. There are four phase shift control techniques for the DAB converter. They are Single Phase shift, Extended Phase shift, Dual Phase shift, Triple Phase shift controls. This thesis considers two control strategies; Single-Phase, and Dual-Phase shifts, to understand the circulating currents, power losses, and output capacitor size reduction in the DAB. Hardware-In-The-Loop (HIL) experiments are carried out on both controls with high switching frequencies using the PLECS software tool and the RT box supporting the PLECS. Root Mean Square Error is also calculated for steady-state values of output voltage with different sampling frequencies in both the controls to identify the achievable sampling frequency in real-time. DSP implementation is also executed to emulate the optimized DAB converter design, and final real-time simulation results are discussed for both the Single-Phase and Dual-Phase shift controls.

Analysis, Design, and Hardware-in-the-Loop Validation of Multi-Active Bridge Converters

This master's thesis investigates different aspects of Dual-Active-Bridge (DAB) Converter and extends aspects further to Multi-Active-Bridges (MAB). The thesis starts with an overview of the applications of the DAB and MAB and their importance. The analytical part of the thesis includes the derivation of the peak and RMS currents, which is required for finding the losses present in the system. The power converters, considered in this thesis are DAB, Triple-Active Bridge (TAB) and Quad-Active Bridge (QAB). All the theoretical calculations are compared with the simulation results from PLECS software for identifying the correctness of the reviewed and developed theory. The Hardware-in-the-Loop (HIL) simulation is conducted for checking the control operation in real-time with the help of the RT box from the Plexim. Additionally, as in real systems digital signal processor (DSP), system-on-chip or field programmable gate array is employed for the control of the power electronic systems, and the execution of the control in the real-time simulation (RTS) conducted is performed by DSP.

Virtual Calibration of CO2 and Pollutant Emissions of a High-Performance PHEV using Model-in-the-Loop Methodology

The study analyses the calibration process of a newly developed high-performance plug-in hybrid electric passenger car powertrain. The complexity of modern powertrains and the more and more restrictive regulations regarding pollutant emissions are the primary challenges for the calibration of a vehicle’s powertrain. In addition, the managers of OEM need to know as earlier as possible if the vehicle under development will meet the target technical features (emission included). This leads to the necessity for advanced calibration methodologies, in order to keep the development of the powertrain robust, time and cost effective. The suggested solution is the virtual calibration, that allows the tuning of control functions of a powertrain before having it built. The aim of this study is to calibrate virtually the hybrid control unit functions in order to optimize the pollutant emissions and the fuel consumption. Starting from the model of the conventional vehicle, the powertrain is then hybridized and integrated with emissions and aftertreatments models. After its validation, the hybrid control unit strategies are optimized using the Model-in-the-Loop testing methodology. The calibration activities will proceed thanks to the implementation of a Hardware-in-the-Loop environment, that will allow to test and calibrate the Engine and Transmission control units effectively, besides in a time and cost saving manner.

Aplications of Neural Networks to Find the Impact of Water in Different Berry Components in Grapes

Grape juice composition during the different stages of berry growth was compared. The analytical data collected were used to investigate the relationships between some of the different components studied in these berries during the ripening period. Our goal is to study, with neural networks, the impact of water availability on Vitis vinifera L. cv. Tempranillo grape yields and juice composition over a three-year period.

Neural Networks Diagnostics in Homeopath System

We suppose the neural networks for solution the problem of the diagnostic in Homeopath System and consider the algorithms of the training.

Optimization of the AZO dyes decoloration process through neural networks: Determination of the H2O2 addition critical point

The concentration of hydrogen peroxide is an important parameter in the azo dyes decoloration process through the utilization of advanced oxidizing processes, particularly by oxidizing via UV/H2O2. It is pointed out that, from a specific concentration, the hydrogen peroxide works as a hydroxyl radical self-consumer and thus a decrease of the system`s oxidizing power happens. The determination of the process critical point (maximum amount of hydrogen peroxide to be added) was performed through a ""thorough mapping"" or discretization of the target region, founded on the maximization of an objective function objective (constant of reaction kinetics of pseudo-first order). The discretization of the operational region occurred through a feedforward backpropagation neural model. The neural model obtained presented remarkable coefficient of correlation between real and predicted values for the absorbance variable, above 0.98. In the present work, the neural model had, as phenomenological basis the Acid Brown 75 dye decoloration process. The hydrogen peroxide addition critical point, represented by a value of mass relation (F) between the hydrogen peroxide mass and the dye mass, was established in the interval 50 < F < 60. (C) 2007 Elsevier B.V. All rights reserved.

Application of Neural Network Methods in the Prediction of Stock Markets

The purpose of the research is to define practical profit which can be achieved using neural network methods as a prediction instrument. The thesis investigates the ability of neural networks to forecast future events. This capability is checked on the example of price prediction during intraday trading on stock market. The executed experiments show predictions of average 1, 2, 5 and 10 minutes’ prices based on data of one day and made by two different types of forecasting systems. These systems are based on the recurrent neural networks and back propagation neural nets. The precision of the predictions is controlled by the absolute error and the error of market direction. The economical effectiveness is estimated by a special trading system. In conclusion, the best structures of neural nets are tested with data of 31 days’ interval. The best results of the average percent of profit from one transaction (buying + selling) are 0.06668654, 0.188299453, 0.349854787 and 0.453178626, they were achieved for prediction periods 1, 2, 5 and 10 minutes. The investigation can be interesting for the investors who have access to a fast information channel with a possibility of every-minute data refreshment.

Modeling and analysis of artificial neural networks applied in operations research

Artificial neural networks are dynamic systems consisting of highly interconnected and parallel nonlinear processing elements. Systems based on artificial neural networks have high computational rates due to the use of a massive number of these computational elements. Neural networks with feedback connections provide a computing model capable of solving a rich class of optimization problems. In this paper, a modified Hopfield network is developed for solving problems related to operations research. The internal parameters of the network are obtained using the valid-subspace technique. Simulated examples are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.