1,720,962 research outputs found
Adaptive control for non-linear test bench dynamometer systems
No full textEngine-in-the-loop (EiL) setups need accurate and fast dynamometer control systems. An accurate test bench model is a demand approach that also offers a significant potential to provide an excellent reproducibility of test runs. The paper presents a novel EiL approach for ASM (Asynchronous Machine) automotive test bench applications. The non-linearity of an ASM is treated with advanced control techniques defining specific parameters to control and model the machine. The integration of adaptive control on the vehicle under test strongly increases the accuracy of each test. The results demonstrate the improved performance obtained with EiL approach and the significant benefits regarding adaptive control
Supervising MHEV's control system with GPS data and fuzzy logic to optimize fuel economy
No full textIn recent years, the automotive industry requests, even more, the possibility to test the prototyped vehicles on real operating conditions. The integration of sensors and the optimized control strategy have led to more reliable systems. In this paper, a fuzzy logic supervisor to compensate background non-linearities and noises is presented. Authors investigate the resilience of the system using simulations of the full car blocks and the environment reaction. The simulation clearly shows that this controller can maintain excellent performance, can compensate in real-time the noises effect, and can keep the pollutant emission low
Advanced control strategies on nonlinear testbench dynamometer system for simulating the fuel consumption
No full textThe adoption of Engine-in-the-loop technology shows real behaviour. This study presents a test runs simulation platform with real engine data. In addition, a test bench model is a demand approach that offers a significant potential to provide an excellent reproducibility of test runs. The platform includes the data integration to upgrade tests run and a comparison with previous results using the advancing control techniques designed. The dynamometer system presents significantly non-linearity. The adaptive control approach, integrated into the Model Predictive Control on the vehicle, allows increasing the tests run performance. The results show how the real data can improve performance and the validation of the system integrating the updated driving cycle and maintaining EiL approach. The conclusion showed the significant benefits regarding the control methods used
Optimize the Mild Hybrid Electric Vehicles control system to reduce the Emission
No full textIn the last decade virtual system integration and electrification have enabled an important change in automotive. The new technology and the attention about the environment, and renewable energy an increase in the use of electric power on road transports. The electrification process represents an important growth, and the introduction of Mild Hybrid Electric Vehicles (MHEVs) is an effective solution to minimize and control the emission. In this paper, authors present the architecture used and the significant parameter considered. The preliminary results include the simulation of emission based on the New European Urban Cycle (NEDC) chosen as target testing cycle
Advanced control strategies to improve nonlinear automotive dynamical systems consumption
Full text linkElectric motors and Internal Combustion Engine test benches allow for testing, under various conditions, the behavior of the Electric Vehicles and they are essential in the automotive field development. In this paper, we introduce the state-of-art of the control algorithms and their validation over different test runs, on the standard driving cycles. Ad-hoc simulations and test benches designed for the issue offer a significant opportunity to reduce costs. The modelling of automotive systems is a non-trivial problem due to the non-linearities. The paper presents a linearized solution and an adaptive control scheme to improve model performances starting from real data, and also discusses the behavior of the proposed system and the control law reporting emissions of the considered virtual vehicle when compared with the target emission regulations
GPS data integration to reduce driving emissions of MHEVs in real operating conditions
No full textIncreasingly emission reduction requests and environmental pollution cut require improved optimization of current transportations. Control strategies and latest vehicles technologies developed in the automotive industry must be optimized, taking into account more information is possible from cars sensors to save energy and reduce emissions. The paper presents a possible strategy for reducing emissions with integration of GPS data in a Mild Hybrid Electric Vehicle simulator. In this study, real GPS data are evaluated to improve the system and introduce real environmental conditions in the system. The data obtained are analysed selectively in the paper. This paper is aimed to investigate the impact of real conditions on fuel consumption. Through theoretical analysis, the conclusion will be drawn that GPS technology is attractive to reduction of emissions
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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