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

Trustworthiness in Mobile Cyber Physical Systems

Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS

A Wireless Driving Cycle Test Observation Method for Electric Vehicles

In the course of the ongoing debate about the limited availability of fossil fuels and environmental impact of internal combustion engine powered vehicles, battery electric vehicles have been receiving increasing attention as an eco-friendly alternative. With the increase of the vehicles with smart units, it can be ensured that the vehicles communicate with the environment and other vehicles. This study focuses on the combination of two major trends, electric vehicles and vehicle to everything communications technology. On the Controller Area Network communication line of the vehicle, a gateway is physically implemented to transmit and receive the necessary signals of the vehicle wirelessly. Another gateway is located at a certain distance from the vehicle and allows the vehicle to be monitored in real time in driving cycles defined in EU regulations

Index to 1981 NASA Tech Briefs, volume 6, numbers 1-4

Short announcements of new technology derived from the R&D activities of NASA are presented. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This index for 1981 Tech Briefs contains abstracts and four indexes: subject, personal author, originating center, and Tech Brief Number. The following areas are covered: electronic components and circuits, electronic systems, physical sciences, materials, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

Investigation of superturbocharger performance improvements through steady state engine simulation

2010 Fall.Includes bibliographical references.An integrated supercharger/turbocharger (SuperTurbo) is a device that combines the advantages of a supercharging, turbocharging and turbocompounding while eliminating some of their individual disadvantages. High boost, turbocompounding, and advanced controls are important strategies in meeting impending fuel economy requirements. High boost increases engine power output while many losses remain constant, producing an overall efficiency gain. Turbocompounding increases engine efficiency by capturing excess exhaust turbine power at high speed and torque. Supercharging increases low speed high torque operating performance. Steady state performance gains of a Superturbocharger equipped engine are investigated using engine simulation software. The engine simulation software uses a 1-D wave flow assumption to model the engine's unsteady flow behavior through one dimensional pipes. With these pipes connected to other engine components the overall performance of the engine can be modeled. GT-Power was chosen to run the simulations due to an already correlated engine model being available. This software is used to 'tune' an existing stock engine model to approximate stock engine data over the full speed and torque range. The SuperTurbo is added to the model and simulations are performed over the full engine speed and torque range for direct comparison with the stock engine. The model results show turbocompounding to be most effective at high speeds and torques in the area above 10 bar BMEP in the 3000 - 4000 RPM range and above 5 bar BMEP in the 500 - 6000 RPM range. In addition to turbocompounding there are fuel savings due to the reduced use of the compressor when it is not needed. With the stock configuration there is boost pressure created by compressor power that is then restricted by the throttle in the 2500 RPM range in the 8-12 bar BMEP range on up to 6000 RPM in the 2-10 bar BMEP range. The control of compressor speed to produce no boost at these locations improves efficiency by not wasting energy creating boost that is not needed

Challenges of micro/mild hybridisation for construction machinery and applicability in UK

In recent years, micro/mild hybridisation (MMH) is known as a feasible solution for powertrain development with high fuel efficiency, less energy use and emission and, especially, low cost and simple installation. This paper focuses on the challenges of MMH for construction machines and then, pays attention to its applicability to UK construction machinery. First, hybrid electric configurations are briefly reviewed; and technological challenges towards MMH in construction sector are clearly stated. Second, the current development of construction machinery in UK is analysed to point out the potential for MMH implementation. Thousands of machines manufactured in UK have been sampled for the further study. Third, a methodology for big data capturing, compression and mining is provided for a capable of managing and analysing effectively performances of various construction machine types. By using this method, 96% of data memory can be reduced to store the huge machine data without lacking the necessary information. Forth, an advanced decision tool is built using a fuzzy cognitive map based on the big data mining and knowledge from experts to enables users to define a target machine for MMH utilization. The numerical study with this tool on the sampled machines has been done and finally realized that one class of heavy excavators is the most suitable to apply MMH technology

Ground terminal expert (GTEX). Part 2: Expert system diagnostics for a 30/20 Gigahertz satellite transponder

A research effort was undertaken to investigate how expert system technology could be applied to a satellite communications system. The focus of the expert system is the satellite earth station. A proof of concept expert system called the Ground Terminal Expert (GTEX) was developed at the University of Akron in collaboration with the NASA Lewis Research Center. With the increasing demand for satellite earth stations, maintenance is becoming a vital issue. Vendors of such systems will be looking for cost effective means of maintaining such systems. The objective of GTEX is to aid in diagnosis of faults occurring with the digital earth station. GTEX was developed on a personal computer using the Automated Reasoning Tool for Information Management (ART-IM) developed by the Inference Corporation. Developed for the Phase 2 digital earth station, GTEX is a part of the Systems Integration Test and Evaluation (SITE) facility located at the NASA Lewis Research Center

Deep Learning based Model Predictive Control for Compression Ignition Engines

Machine learning (ML) and a nonlinear model predictive controller (NMPC) are used in this paper to minimize the emissions and fuel consumption of a compression ignition engine. In this work machine learning is applied in two methods. In the first application, ML is used to identify a model for implementation in model predictive control optimization problems. In the second application, ML is used as a replacement of the NMPC where the ML controller learns the optimal control action by imitating or mimicking the behavior of the model predictive controller. In this study, a deep recurrent neural network including long-short term memory (LSTM) layers are used to model the emissions and performance of an industrial 4.5 liter 4-cylinder Cummins diesel engine. This model is then used for model predictive controller implementation. Then, a deep learning scheme is deployed to clone the behavior of the developed controller. In the LSTM integration, a novel scheme is used by augmenting hidden and cell states of the network in an NMPC optimization problem. The developed LSTM-NMPC and the imitative NMPC are compared with the Cummins calibrated Engine Control Unit (ECU) model in an experimentally validated engine simulation platform. Results show a significant reduction in Nitrogen Oxides (\nox) emissions and a slight decrease in the injected fuel quantity while maintaining the same load. In addition, the imitative NMPC has a similar performance as the NMPC but with a two orders of magnitude reduction of the computation time.Comment: Submitted to Control engineering Practice (Submission date: March 9, 2022) Revised version (Submission date: June 18, 2022) Accepted on July 30, 202