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

Promising Techniques of Automotive Engine Lubrication Oil Monitoring System – A Critical Review towards Enhancement

Engine lubricant plays a significant role in reducing internal friction between the piston and shear of moving mechanical parts to further improve the engine performance and efficiency. Rapid developments of engine oil monitoring systems has taken place to determine the engine lubricant degradation level in reducing unnecessary engine power loss and maintenance cost. This paper critically reviews the invention and an innovation pertaining to the subject before a smart innovation is developed in near future

A methodology to study oil-coking problem in small turbochargers

[EN] In compliance with oncoming emission directives, turbocharging and increasing complexity in the turbocharger system demands a great effort from researchers on the development of effective procedures and tools to cope with the new technological exigencies. This article describes a methodology for studying oil-coking influence in turbocharger performance. A preliminary evaluation and calibration is done. The aim of this work focuses on the development of methodologies and tools that help to evaluate and understand the consequences that degraded oils can generate in the bearing system during enhanced oil-coking procedure. Several experimental tests have been carried out in an engine test bench and using an independent lubrication system that only feeds the turbocharger. The test campaign is done under a specific engine cycle and using oil artificially contaminated at two different levels. The work is divided into two parts. The first part provides a description and definition of test conditions for measuring of the maximum temperature in the bearing system and the second part tackles the measurement and post-processing of the main instantaneous parameters defining the engine and turbocharger behavior.The authors would like to acknowledge the Apoyo para la investigación y Desarrollo (PAID) grant for doctoral studies (FPI-2016-S2-1354). This work was partially supported by FEDER and the Spanish Ministry of Economy and Competitiveness through Grant Number TRA2016-79185-R.Serrano, J.; Tiseira, A.; García-Cuevas González, LM.; Rodriguez-Usaquen, YT.; Guillaume, M. (2020). A methodology to study oil-coking problem in small turbochargers. International Journal of Engine Research. 21(7):1193-1204. https://doi.org/10.1177/1468087418803197S11931204217Giakoumis, E. G. (2016). Review of Some Methods for Improving Transient Response in Automotive Diesel Engines through Various Turbocharging Configurations. Frontiers in Mechanical Engineering, 2. doi:10.3389/fmech.2016.00004Nguyen-Schäfer, H. (2012). Rotordynamics of Automotive Turbochargers. doi:10.1007/978-3-642-27518-0Brouwer, M. D., Sadeghi, F., Lancaster, C., Archer, J., & Donaldson, J. (2013). Whirl and Friction Characteristics of High Speed Floating Ring and Ball Bearing Turbochargers. Journal of Tribology, 135(4). doi:10.1115/1.4024780Addison J, Needelman W. Diesel engine lubricant contamination and wear. New York: Pall Corporation, 1986, p.12.Serrano, J. R., Olmeda, P., Tiseira, A., García-Cuevas, L. M., & Lefebvre, A. (2013). Theoretical and experimental study of mechanical losses in automotive turbochargers. Energy, 55, 888-898. doi:10.1016/j.energy.2013.04.042Galindo, J., Lujan, J. M., Guardiola, C., & Lapuente, G. S. (2006). A method for data consistency checking in compressor and variable-geometry turbine maps. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 220(10), 1465-1473. doi:10.1243/09544070jauto82Serrano, J. R., Arnau, F. J., Dolz, V., & Piqueras, P. (2009). Methodology for characterisation and simulation of turbocharged diesel engines combustion during transient operation. Part 1: Data acquisition and post-processing. Applied Thermal Engineering, 29(1), 142-149. doi:10.1016/j.applthermaleng.2008.02.011Ghazikhani, M., Davarpanah, M., & Shaegh, S. A. M. (2008). An experimental study on the effects of different opening ranges of waste-gate on the exhaust soot emission of a turbo-charged DI diesel engine. Energy Conversion and Management, 49(10), 2563-2569. doi:10.1016/j.enconman.2008.05.012Jun, H.-B., Kiritsis, D., Gambera, M., & Xirouchakis, P. (2006). Predictive algorithm to determine the suitable time to change automotive engine oil. Computers & Industrial Engineering, 51(4), 671-683. doi:10.1016/j.cie.2006.06.017Owrang, F., Mattsson, H., Olsson, J., & Pedersen, J. (2004). Investigation of oxidation of a mineral and a synthetic engine oil. Thermochimica Acta, 413(1-2), 241-248. doi:10.1016/j.tca.2003.09.016Serrano, J. R., Olmeda, P., Arnau, F. J., Reyes-Belmonte, M. A., & Tartoussi, H. (2015). A study on the internal convection in small turbochargers. Proposal of heat transfer convective coefficients. Applied Thermal Engineering, 89, 587-599. doi:10.1016/j.applthermaleng.2015.06.053Serrano, J. R., Olmeda, P., Arnau, F. J., Dombrovsky, A., & Smith, L. (2014). Analysis and Methodology to Characterize Heat Transfer Phenomena in Automotive Turbochargers. Journal of Engineering for Gas Turbines and Power, 137(2). doi:10.1115/1.402826

Overview of telematics-based prognostics and health management systems for commercial vehicles

Prognostics and Health Management/Monitoring (PHM) are methods to assess the health condition and reliability of systems for the purpose of maximising operational reliability and safety. Recently, PHM systems are emerging in the automotive industry. In the commercial vehicle sector, reducing the maintenance cost and downtime while also improving the reliability of vehicle components can have a major impact on fleet performance and hence business competitiveness. Nowadays, telematics and GPS are used mainly for fleet tracking and diagnostics purposes. Increased numbers of sensors installed on commercial vehicles, advancement of data analytics and computational intelligence methods, increased capabilities for on-board data processing as well as in the cloud, are creating an opportunity for PHM systems to be deployed on commercial vehicles and hence improve the overall operational efficiency

Artificial Intelligence for Predictive Maintenance of Armoured Fighting Vehicles Engine

Armoured Fighting Vehicles (AFVs) also called as Tanks play a critical role in modern warfare, providing mobility, protection and firepower on the battlefield. However, maintaining these complex machines and ensuring their operational readiness is a significant challenge for military organizations. Traditional maintenance practices are often reactive, resulting in unexpected failures, increased downtime, and operational inefficiencies. This paper focuses on the application of Artificial Intelligence (AI) for predictive maintenance of Armoured Fighting Vehicles. By harnessing the power of AI algorithms and advanced data analytics, predictive maintenance aims to anticipate and address potential equipment failures before they occur. This proactive approach enables military organizations to optimize resource allocation, improve operational planning and extend the lifespan of AFVs. The integration of AI in predictive maintenance involves collecting and analysing data from various sensors installed on the AFV engine. These sensors monitor key parameters, such as engine performance, temperature, vibration and fluid levels to detect anomalies and deviations from normal operating conditions. AI algorithms process this data, utilizing machine learning techniques to identify patterns, correlations, and potential failure indicators. The benefits of AI-based predictive maintenance for AFVs are multifaceted. Firstly, it enhances equipment readiness by reducing unexpected failures and maximizing operational availability. Secondly, it enables optimized resource allocation, ensuring that maintenance activities are scheduled efficiently, minimizing downtime, and improving overall operational efficiency. Thirdly, the predictive capabilities of AI help military planners in better decision-making allowing for improved mission planning and execution. However, the successful implementation of AI for predictive maintenance of AFV engine requires overcoming several challenges. These include data collection and integration from diverse sensors, ensuring data accuracy and quality, establishing robust communication infrastructure, and addressing cyber security concerns to protect sensitive vehicle data. This paper underscores the growing importance of AI in revolutionizing maintenance practices for Armoured Fighting Vehicles. By shifting from reactive maintenance to predictive strategies, military organizations can enhance their operational capabilities, reduce costs, and ensure the optimal performance and longevity of their AFV fleet.Lattice Science Publication (LSP) © Copyright: All rights reserved

TOOL FOR THE SYNTHESIS OF MECHANISMS OF NEW ENGINES BASED ON DASY

Článek se zabývá prezentací nástroje pro syntézu mechanismů motoru založený na DASY a jeho využití při návrhu parametrů experimentálního jednoválcového motoru. Nástroj obsahuje parametrický model motoru založený na DASY. Model umožní simulovat termodynamiku motoru a jeho mechanismy. Skládá ze submodelů, které řeší termodynamiku, kinematiku a dynamiku rozvodového mechanismu, jeho řemenový pohon a hydraulický okruh natáčení vačkových hřídelí. Metodik syntézy mechanismů bylo využito pro nalezení hodnot kalibračních parametrů. Následně byly parametry submodelů validovány experimentálními daty a jejich hodnoty jsou obsaženy v DASY. Ze submodelů byl sestaven model experimentálního jednoválce, který ověřuje jeho konstrukci, umožňuje optimalizovat jeho parametry a předpovídat jeho chování v různých simulovaných stavech. The article presents a tool for the synthesis of engine mechanisms based on DASY and the use thereof for designing the parameters of an experimental single‐cylinder engine. The tool includes a parametric engine model based on DASY. The model will make it possible to simulate the engine thermodynamics and its mechanisms. It consists of sub‐models which deal with the thermodynamics, kinematics and dynamics of the valve timing mechanism, its belt drive, and hydraulic circuit for camshaft adjustment. The methodologies of synthesis of mechanisms were used to determine the values of the calibration parameters. The parameters of the sub‐models were subsequently validated by experimental data, and the values thereof are included in DASY. The sub‐models were used to assemble the model of an experimental single‐cylinder engine which validates the design thereof, makes it possible to optimize its parameters and predict its behavior in different simulated conditions

Studies on SI engine simulation and air/fuel ratio control systems design

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.More stringent Euro 6 and LEV III emission standards will immediately begin execution on 2014 and 2015 respectively. Accurate air/fuel ratio control can effectively reduce vehicle emission. The simulation of engine dynamic system is a very powerful method for developing and analysing engine and engine controller. Currently, most engine air/fuel ratio control used look-up table combined with proportional and integral (PI) control and this is not robust to system uncertainty and time varying effects. This thesis first develops a simulation package for a port injection spark-ignition engine and this package include engine dynamics, vehicle dynamics as well as driving cycle selection module. The simulations results are very close to the data obtained from laboratory experiments. New controllers have been proposed to control air/fuel ratio in spark ignition engines to maximize the fuel economy while minimizing exhaust emissions. The PID control and fuzzy control methods have been combined into a fuzzy PID control and the effectiveness of this new controller has been demonstrated by simulation tests. A new neural network based predictive control is then designed for further performance improvements. It is based on the combination of inverse control and predictive control methods. The network is trained offline in which the control output is modified to compensate control errors. The simulation evaluations have shown that the new neural controller can greatly improve control air/fuel ratio performance. The test also revealed that the improved AFR control performance can effectively restrict engine harmful emissions into atmosphere, these reduce emissions are important to satisfy more stringent emission standards

Improvement of powertrain mechatronic systems for lean automotive manufacturing

In recent years, the increasing severity of emission standards forced car manufacturers to integrate vehicle powertrains with additional mechatronic elements, consisting in sensors, executors and controlling elements interacting with each other. However, the introduction of the best available ecological devices goes hand in hand with the legislation and/or limitations in different regional markets. Thus, the designers adapt the mechatronic system to the target emission standards of the produced powertrain. The software embedded into the Engine Control Unit (ECU) is highly customized for the specific configurations: variability in mechatronic systems leads to the development of several software versions, lowering the efficiency of the design phase. Therefore the employment of a standard for the communication among sensors, actuators and the ECU would allow the development of a unique software for different configurations; this would be beneficial from a manufacturing point of view, enabling the simplification of the design process. Obviously, the new software must still guarantee the proper level of feedbacks to the ECU to ensure the compliance with different emission standards and the proper engine behavior. The general software is adapted to the powertrain: according to the specific target emission standard, some control elements may not be necessary, and a part of the software may be easily removed. In this paper, starting from a real case-study, a more general methodology is proposed for configurations characterized by different powertrain sets and manufacturing line constraints. The proposed technique allows to maintain the accuracy of the control system and improve process efficiency at the same time, ensuring lean production and lowering manufacturing costs. A set of mathematical techniques to improve software efficacy is also presented: the resulting benefits are enhanced by software standardization, because the design effort may be shared by the largest possible number of applications

Model-Guided Data-Driven Optimization and Control for Internal Combustion Engine Systems

The incorporation of electronic components into modern Internal Combustion, IC, engine systems have facilitated the reduction of fuel consumption and emission from IC engine operations. As more mechanical functions are being replaced by electric or electronic devices, the IC engine systems are becoming more complex in structure. Sophisticated control strategies are called in to help the engine systems meet the drivability demands and to comply with the emission regulations. Different model-based or data-driven algorithms have been applied to the optimization and control of IC engine systems. For the conventional model-based algorithms, the accuracy of the applied system models has a crucial impact on the quality of the feedback system performance. With computable analytic solutions and a good estimation of the real physical processes, the model-based control embedded systems are able to achieve good transient performances. However, the analytic solutions of some nonlinear models are difficult to obtain. Even if the solutions are available, because of the presence of unavoidable modeling uncertainties, the model-based controllers are designed conservatively