Impact of Embedded Carbon Fiber Heating Panel on the Structural/Mechanical Performance of Roadway Pavement

INE/AUTC 12.3

Meta-heuristic algorithms in car engine design: a literature survey

Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system

Propulsion Controls and Diagnostics Research in Support of NASA Aeronautics and Exploration Mission Programs

The Controls and Dynamics Branch (CDB) at National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced propulsion controls and diagnostics technologies that will help meet the challenging goals of NASA programs under the Aeronautics Research and Exploration Systems Missions. This paper provides a brief overview of the various CDB tasks in support of the NASA programs. The programmatic structure of the CDB activities is described along with a brief overview of each of the CDB tasks including research objectives, technical challenges, and recent accomplishments. These tasks include active control of propulsion system components, intelligent propulsion diagnostics and control for reliable fault identification and accommodation, distributed engine control, and investigations into unsteady propulsion systems

Modelling and control of hybrid electric vehicles (a comprehensive review)

The gradual decline in global oil reserves and presence of ever so stringent emissions rules around the world, have created an urgent need for the production of automobiles with improved fuel economy. HEVs (hybrid electric vehicles) have proved a viable option to guarantying improved fuel economy and reduced emissions.The fuel consumption benefits which can be realised when utilising HEV architecture are dependent on how much braking energy is regenerated, and how well the regenerated energy is utilized. The challenge in developing an HEV control strategy lies in the satisfaction of often conflicting control constraints involving fuel consumption, emissions and driveability without over-depleting the battery state of charge at the end of the defined driving cycle.To this effect, a number of power management strategies have been proposed in literature. This paper presents a comprehensive review of these literatures, focusing primarily on contributions in the aspect of parallel hybrid electric vehicle modelling and control. As part of this treatise, exploitable research gaps are also identified. This paper prides itself as a comprehensive reference for researchers in the field of hybrid electric vehicle development, control and optimization