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

Dual-layered Multi-Objective Genetic Algorithms (D-MOGA): A Robust Solution for Modern Engine Development and Calibrations

Heavy-duty (HD) diesel engines are the primary propulsion systems used within the freight transportation sector and are subjected to stringent emissions regulations. The primary objective of this study is to develop a robust calibration technique for HD engine optimization in order to meet current and future regulated emissions standards during certification cycles and off-cycle vocation activities. Recently, California - Air Resources Board (C-ARB) has also shown interests in controlling off-cycle emissions from vehicles operating in California by funding projects such as the Ultra-Low NOx study by Sharp et. al [1]. Moreover, there is a major push for the complex real-world driving emissions testing protocol as the confirmatory and certification testing procedure in Europe and Asia through the United Nations - Economic Commission for Europe (UN-ECE) and International Organization for Standardization (ISO). This calls for more advanced and innovative approaches to optimize engine operation to meet the regulated certification levels.;A robust engine calibration technique was developed using dual-layered multi-objective genetic algorithms (D-MOGA) to determine necessary engine control parameter settings. The study focused on reducing fuel consumption and lowering oxides of nitrogen (NOx) emissions, while simultaneously increasing exhaust temperatures for thermal management of exhaust after-treatment system. The study also focused on using D-MOGA to develop a calibration routine that simultaneously calibrates engine control parameters for transient certification cycles and vocational drayage operation. Several objective functions and alternate selection techniques for D-MOGA were analyzed to improve the optimality of the D-MOGA results.;The Low-NOx calibration for the Federal Test Procedure (FTP) which was obtained using the simple desirability approach was validated in the engine dynamometer test cell over the FTP and near-dock test cycles. In addition, the 2010 emissions compliant calibration was baselined for performance and emissions over the FTP and custom developed low-load Near-Dock engine dynamometer test cycles. Performance and emissions of the baseline calibrations showed a 63% increase in engine-out brake-specific NOx emissions and a proportionate 77% decrease in engine-out soot emissions over the Near-Dock cycle as compared to the FTP cycle. Engine dynamometer validation results of the Low-NOx FTP cycle calibration developed using D-MOGA, showed a 17% increase brake-specific NOx emissions over the FTP cycle, compared to the baseline calibrations. However, a 50% decrease in engine-out soot emissions and substantial increase in exhaust temperature were observed with no penalties on fuel consumption.;The tools developed in this study can play a role in meeting current and future regulations as well as bridging the gap between emissions during certification and real-world engine operations and eventually could play a vital role in meeting the National Ambient Air Quality Standards (NAAQS) in areas such as the port of Los Angeles, California in the South Coast Air Basin

Model-based multiobjective evolutionary algorithm optimization for HCCI engines

Modern engines feature a considerable number of adjustable control parameters. With this increasing number of degrees of freedom (DoFs) for engines and the consequent considerable calibration effort required to optimize engine performance, traditional manual engine calibration or optimization methods are reaching their limits. An automated and efficient engine optimization approach is desired. In this paper, interdisciplinary research on a multiobjective evolutionary algorithm (MOEA)-based global optimization approach is developed for a homogeneous charge compression ignition (HCCI) engine. The performance of the HCCI engine optimizer is demonstrated by the cosimulation between an HCCI engine Simulink model and a Strength Pareto Evolutionary Algorithm 2 (SPEA2)-based multiobjective optimizer Java code. The HCCI engine model is developed by Simulink and validated with different engine speeds (1500-2250 r/min) and indicated mean effective pressures (IMEPs) (3-4.5 bar). The model can simulate the HCCI engine's indicated specific fuel consumption (ISFC) and indicated specific hydrocarbon (ISHC) emissions with good accuracy. The introduced MOEA optimization is an approach to efficiently optimize the engine ISFC and ISHC simultaneously by adjusting the settings of the engine's actuators automatically through the SPEA2. In this paper, the settings of the HCCI engine's actuators are intake valve opening (IVO) timing, exhaust valve closing (EVC) timing, and relative air-to-fuel ratio $lambda$. The cosimulation study and experimental validation results show that the MOEA engine optimizer can find the optimal HCCI engine actuators' settings with satisfactory accuracy and a much lower time consumption than usual

Non-weighted aggregate evaluation function of multi-objective optimization for knock engine modeling

In decision theory, the weighted sum model (WSM) is the best known Multi-Criteria Decision Analysis (MCDA) approach for evaluating a number of alternatives in terms of a number of decision criteria. Assigning weights is a difficult task, especially if the number of criteria is large and the criteria are very different in character. There are some problems in the real world which utilize conflicting criteria and mutual effect. In the field of automotive, the knocking phenomenon in internal combustion or spark ignition engines limits the efficiency of the engine. Power and fuel economy can be maximized by optimizing some factors that affect the knocking phenomenon, such as temperature, throttle position sensor, spark ignition timing, and revolution per minute. Detecting knocks and controlling the above factors or criteria may allow the engine to run at the best power and fuel economy. The best decision must arise from selecting the optimum trade-off within the above criteria. The main objective of this study was to proposed a new Non-Weighted Aggregate Evaluation Function (NWAEF) model for non-linear multi-objectives function which will simulate the engine knock behavior (non-linear dependent variable) in order to optimize non-linear decision factors (non-linear independent variables). This study has focused on the construction of a NWAEF model by using a curve fitting technique and partial derivatives. It also aims to optimize the nonlinear nature of the factors by using Genetic Algorithm (GA) as well as investigate the behavior of such function. This study assumes that a partial and mutual influence between factors is required before such factors can be optimized. The Akaike Information Criterion (AIC) is used to balance the complexity of the model and the data loss, which can help assess the range of the tested models and choose the best ones. Some statistical tools are also used in this thesis to assess and identify the most powerful explanation in the model. The first derivative is used to simplify the form of evaluation function. The NWAEF model was compared to Random Weights Genetic Algorithm (RWGA) model by using five data sets taken from different internal combustion engines. There was a relatively large variation in elapsed time to get to the best solution between the two model. Experimental results in application aspect (Internal combustion engines) show that the new model participates in decreasing the elapsed time. This research provides a form of knock control within the subspace that can enhance the efficiency and performance of the engine, improve fuel economy, and reduce regulated emissions and pollution. Combined with new concepts in the engine design, this model can be used for improving the control strategies and providing accurate information to the Engine Control Unit (ECU), which will control the knock faster and ensure the perfect condition of the engine

Marine dual fuel engines modelling and optimisation employing : a novel combustion characterisation method

Dual fuel (DF) engines have been an attractive alternative of traditional diesel engines for reducing both the environmental impact and operating cost. The major challenge of DF engine design is to deal with the performance-emissions trade-off via operating settings optimisation. Nevertheless, determining the optimal solution requires large amount of case studies, which could be both time-consuming and costly in cases where methods like engine test or Computational Fluid Dynamics (CFD) simulation are directly used to perform the optimisation. This study aims at developing a novel combustion characterisation method for marine DF engines based on the combined use of three-dimensional (3D) simulation and zero-dimensional/one-dimensional (0D/1D) simulation methods. The 3D model is developed with the CONVERGE software and validated by employing the measured pressure and emissions. Subsequently, the validated 3D model is used to perform a parametric study to explore the engine operating settings that allow simultaneous reduction of the brake specific fuel consumption (BSFC) and NOx emissions at three engine operation conditions (1457 r/min, 1629 r/min and 1800 r/min). Furthermore, the derived heat release rate (HRR) is employed to calibrate the 0D Wiebe combustion model by using Response Surface Methodology (RSM). A linear response model for the Wiebe combustion function parameters is proposed by considering each Wiebe parameter as a function of the pilot injection timing, equivalence ratio and natural gas mass. The 0D/1D model is established in the GT-ISE software and used to optimise the performance-emissions trade-off of the reference engine by employing the Nondominated Sorting Genetic Algorithm II (NSGA II). The obtained results provide a comprehensive insight on the impacts of the involved engine operating settings on in-cylinder combustion characteristics, engine performance and emissions of the investigated marine DF engine. By performing the settings optimisation at three engine operating points, settings that lead to reduced BSFC are identified, whilst the NOx emissions comply with the Tier III NOx emissions regulation. The proposed novel method is expected to support the combustion analysis and enhancement of marine DF engines during the design phase, whilst the derived optimal solution is expected to provide guidelines of DF engine management for reducing operating cost and environmental footprint.Dual fuel (DF) engines have been an attractive alternative of traditional diesel engines for reducing both the environmental impact and operating cost. The major challenge of DF engine design is to deal with the performance-emissions trade-off via operating settings optimisation. Nevertheless, determining the optimal solution requires large amount of case studies, which could be both time-consuming and costly in cases where methods like engine test or Computational Fluid Dynamics (CFD) simulation are directly used to perform the optimisation. This study aims at developing a novel combustion characterisation method for marine DF engines based on the combined use of three-dimensional (3D) simulation and zero-dimensional/one-dimensional (0D/1D) simulation methods. The 3D model is developed with the CONVERGE software and validated by employing the measured pressure and emissions. Subsequently, the validated 3D model is used to perform a parametric study to explore the engine operating settings that allow simultaneous reduction of the brake specific fuel consumption (BSFC) and NOx emissions at three engine operation conditions (1457 r/min, 1629 r/min and 1800 r/min). Furthermore, the derived heat release rate (HRR) is employed to calibrate the 0D Wiebe combustion model by using Response Surface Methodology (RSM). A linear response model for the Wiebe combustion function parameters is proposed by considering each Wiebe parameter as a function of the pilot injection timing, equivalence ratio and natural gas mass. The 0D/1D model is established in the GT-ISE software and used to optimise the performance-emissions trade-off of the reference engine by employing the Nondominated Sorting Genetic Algorithm II (NSGA II). The obtained results provide a comprehensive insight on the impacts of the involved engine operating settings on in-cylinder combustion characteristics, engine performance and emissions of the investigated marine DF engine. By performing the settings optimisation at three engine operating points, settings that lead to reduced BSFC are identified, whilst the NOx emissions comply with the Tier III NOx emissions regulation. The proposed novel method is expected to support the combustion analysis and enhancement of marine DF engines during the design phase, whilst the derived optimal solution is expected to provide guidelines of DF engine management for reducing operating cost and environmental footprint

Development of a Genetic Algorithm Based Search Strategy Suited For Design Optimisation of Internal Combustion Engines

Engine design optimisation is a multi-objective, multi-domain problem in a discontinuous design space. The state of the art of optimisation techniques shows that only methods of direct and adaptive search are appropriate for this type of problem. These include, adaptive random search, simulated annealing, evolution strategies and genetic algorithms. Ofthese methods, the genetic algorithms have been shown to be the most suited for the optimisation of multi-modal response functions in a discontinuous design space. This paper considers the important characteristics of genetic algorithms and their adaptation for use in parametric design optimisation of internal combustion engines. In order to verify the basicfunctionality of the proposed optimisation strategy, a genetic algorithm based, optimisation software was developed and tested on a number of analytical functions, selected from optimisation literature, with satisfactory results

Development of a virtual methodology based on physical and data-driven models to optimize engine calibration

Virtual engine calibration exploiting fully-physical plant models is the most promising solution for the reduction of time and cost of the traditional calibration process based on experimental testing. However, accuracy issues on the estimation of pollutant emissions are still unresolved. In this context, the paper shows how a virtual test rig can be built by combining a fully-physical engine model, featuring predictive combustion and NOx sub-models, with data-driven soot and particle number models. To this aim, a dedicated experimental campaign was carried out on a 1.6 liter EU6 diesel engine. A limited subset of the measured data was used to calibrate the predictive combustion and NOx sub-models. The measured data were also used to develop data-driven models to estimate soot and particulate emissions in terms of Filter Smoke Number (FSN) and Particle Number (PN), respectively. Inputs from engine calibration parameters (e.g., fuel injection timing and pressure) and combustion-related quantities computed by the physical model (e.g., combustion duration), were then merged. In this way, thanks to the combination of the two different datasets, the accuracy of the abovementioned models was improved by 20% for the FSN and 25% for the PN. The coupled physical and data-driven model was then used to optimize the engine calibration (fuel injection, air management) exploiting the Non-dominated Sorting genetic algorithm. The calibration obtained with the virtual methodology was then adopted on the engine test bench. A BSFC improvement of 10 g/kWh and a combustion reduction of 3.0 dB in comparison with the starting calibration was achieved

Effects of EGR transient operation on emissions and performance of automotive engines during RDE cycles

[ES] Hoy en día, las regulaciones sobre emisiones de los automóviles se están haciendo más estrictas. Además de los ciclos de homologación estándar, actualmente se están empezando a considerar nuevos métodos de homologación que tienen en cuenta las condiciones reales que se dan en la carretera. Los sistemas de Recirculación de Gases de Escape (EGR) son estrategias que han demostrado ser efectivas durante estacionarios y que también pueden ser usadas en ese tipo de ciclos dinámicos que corresponden a condiciones reales de conducción. Esta tesis se centra en la implementación de diferentes sistemas EGR para su uso en condiciones dinámicas en motores diésel turbosobrealimentados. En primer lugar, se lleva a cabo un análisis del ciclo de conducción para identificar las operaciones específicas de tipo transitorio más frecuentes en los ciclos dinámicos como WLTC y RDE. Los resultados muestran que la frecuencia en la que se producen fuertes transitorios en carga es mayor que en la que se producen transitorios de velocidad. Entre ellos, el número de operaciones de tipo Tip-out es superior a las de tipo Tip-Ins, especialmente en el rango de 1250-2000 rpm. Estos fuertes transitorios se repiten en el banco de ensayos de motor equipado con analizadores de gas de alta frecuencia, de forma que se registran la concentración instantánea de CO2 y NOx. También se ha realizado un estudio paramétrico de la actuación de la válvula de EGR durante la operación de varios transitorios fuertes, cuantificando el retraso en el transporte, la concentración de NOx y las partículas. El lazo de EGR de baja presión, LPEGR, ha resultado ser más efectivo cuando se operaba a plena carga, así como durante los transitorios, comparado con el lazo de EGR de alta presión, HPEGR. De esta forma, se propone la válvula de control más adecuada para LPEGR, lo que puede ser útil para la calibración de los transitorios de los motores diésel turbosobrealimentados. Además de ello, se señala el compromiso entre rendimiento y emisiones durante los transitorios de EGR. Al implementar la recirculación de los gases de escape a lo largo de todo el mapa del motor se minimiza la aparición de picos inesperados de emisión de NOx. Concretamente, las estrategias LPEGR consiguen reducir alrededor de un 20-60% los NOx emitidos durante los primeros pocos segundos con menos de un 5% de penalización en el rendimiento. Adicionalmente, en el documento también se presentan las simulaciones que se han realizado de los modelos unidimensionales de los transitorios. El control de la turbina de geometría variable juega un papel importante a la hora de calibrar el modelo para transitorios de EGR. Además de ello, se lleva a cabo una optimización de la separación de EGR para varios puntos estacionarios por medio de simulaciones que están basadas en el compromiso entre rendimiento y emisiones. Además, se propone un algoritmo para optimizar la separación de EGR, reduciendo en alrededor de un 80% el tiempo de cálculo de un DOE o un método de algoritmo genético. Finalmente, se crea un modelo simple de NOx 3D cuasi-estacionario para predecir las emisiones durante el transitorio en condiciones de conducción reales. La tasa de EGR, como tercera entrada del modelo, muestra una mejora significativa a la hora de predecir el transitorio de NOx con respecto al modelo 2D.[EN] The automotive emission regulations are getting more stringent these days. New methods of homologation are being considered other than standard cycles considering the real driving behavior on road. The EGR system is one of the proven and well tested strategies in steady state which can be used on those dynamic real driving conditions too. This dissertation focuses on implementation of different EGR systems during dynamic operations of turbocharged diesel engine. Firstly, a driving cycle analysis is carried out to identify the specific and frequent transient operations on dynamic cycles like WLTC and RDE. The results show that, the frequency of harsh load transients is higher than speed transients. Among them, the number of Tip-Out operations outnumber the Tip-Ins with higher density in 1250-2000 RPM range. Therefore, these harsh transients are repeated separately on the dynamic engine test bench equipped with high frequency gas analyzers to track the instantaneous CO2 and NOx concentration. A parametric study is carried out with EGR valve actuation during various severe load transients, quantifying the transportation delays, NOx concentration and particulate matter. The LPEGR is found to be more effective at the full load as well as during transient operations compared to HPEGR. The best suited LPEGR valve control is proposed, which can be helpful for transient calibration of a turbocharged diesel engine. Moreover, the trade-off between the performance and emission during EGR transients is also pointed out. The implementation of EGR all over the engine map minimizes the unexpected NOx peaks during transients. Specifically, LPEGR strategies manages to reduce around 20-60% of NOx in first few seconds with less than 5% of penalty in performance. Additionally, 1D model simulation results of load transient operations are presented in the document. The VGT control plays important role to calibrate the model for transient operations with EGR. Apart from this, the EGR split optimization on various steady points is carried out by simulations following the trade-off between performance and emissions. Furthermore, an algorithm to search the optimum split is proposed, reducing around 80% of the calculation time consumed by DOE or genetic algorithm method. Finally, a simple 3D quasi steady NOx model is created to predict the transient emissions in real driving conditions. EGR rate, as 3rd input in model shows significant improvement in prediction of transient NOx over the 2D model.[CA] En els darrers temps, les regulacions sobre emissions contaminants dels vehicles s'han fet més estrictes. A més dels cicles d'homologació estàndards, actualment s'estan començant a considerar nous mètodes d'homologació que tinguen en compte les condicions reals que es donen en la carretera. Els sistemes de Recirculació de Gasos d'Escapament (EGR) són estratègies que s'han demostrat com a efectives durant condicions estacionàries i que també poden ser emprades en aquest tipus de cicles dinàmics, que corresponen a condicions reals de conducció. Aquesta tesi està centrada en la implementació de diferents sistemes EGR per al seu ús en condicions dinàmiques en motors dièsel turbosobrealimentats. En primer lloc, es du a terme un anàlisi del cicle de conducció per a identificar les operacions específiques de tipus transitori més freqüents en els cicles dinàmics WLTC i RDE. Els resultats mostren que la freqüència a la que s'obtenen forts transitoris de càrrega és major que en aquella en la que es produeixen transitoris de velocitat. Entre aquestos, el nombre d'operacions de tipus Tip-out és superior a les del tipus Tip-ins, especialment en l'interval de 1250-2000 rpm. Aquestos forts transitoris es repeteixen en el banc d'assajos de motor equipat amb analitzadors de gasos d'alta freqüència, de manera que es registren les concentracions de CO2 i NOx. També s'ha realitzat un estudi paramètric de l'actuació de la vàlvula d'EGR durant l'operació de diversos transitoris forts, quantificant el retard en el transport, la concentració de NOx i les partícules. El llaç d'EGR de baixa pressió, LPEGR, ha resultat ser més efectiu quan s'operava a plena càrrega, així com durant els transitoris, comparat amb el llaç d'EGR d'alta pressió, HPEGR. D'aquesta forma, es proposa la vàlvula de control més adequada per a LPEGR, el que pot resultar útil per a la calibratge dels transitoris dels motors dièsel turbosobrealimentats. A banda d'això, s'ha assenyalat el compromís entre rendiment i emissions durant els transitoris d'EGR. Al implementar la recirculació dels gasos d'escapament a tot arreu del mapa del motor es minimitza l'aparició de pics inesperats d'emissió de NOx. Més concretament, les estratègies LPEGR aconsegueixen reduir al voltant d'un 20-60% els NOx emesos durant els primers pocs segons amb menys d'un 5% de penalització en el rendiment. Addicionalment, en el document també es presenten les simulacions que s'han realitzat dels models unidimensionals dels transitoris. El control de la turbina de geometria variable juga un paper important a l'hora de calibrar el model per a transitoris d'EGR. A més d'això, s'ha dut a terme una optimització de la separació d'EGR en diversos punts estacionaris per mitjà de simulacions que estan basades en el compromís entre rendiment i emissions. També es proposa un algoritme per a optimitzar la separació d'EGR, reduint al voltant d'un 80\% el temps de càlcul d'un DOE o un mètode d'algoritme genètic. Finalment, es crea un model simple de NOx 3D quasi-estacionari per a predir les emissions durant el transitori en condicions de conducció real. La taxa d'EGR, com a tercera entrada del model, mostra una millora significativa a l'hora de predir el transitori de NOx respecte al model 2D.Patil, CY. (2020). Effects of EGR transient operation on emissions and performance of automotive engines during RDE cycles [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/149498TESI

Optimal control of a motor-integrated hybrid powertrain for a two-wheeled vehicle suitable for personal transportation

The present research aims to propose an optimized configuration of the motor integrated power-train with an optimal controller suitable for small power-train based two wheeler automobile which can increase the system level efficiency without affecting drivability. This work will be the foundation for realizing the system in a production ready vehicle for the two wheeler OEM TVS Motor Company in India. A detailed power-train model is developed (from first principles) for the scooter vehicle, which is powered by a 110 cc spark ignition (SI) engine and coupled with two types of transmission, a continuous variable transmission (CVT) and a 4-speed manual transmission (MT). Both models are capable of simulating torque and NOx emission output of the SI engine and dynamic response of the full power-train. The torque production and emission outputs of the model are compared with experimental results available from TVS Motor Company. The CVT gear ratio model is developed using an indirect method and an analytical model. Both types of powertrain models are applied to perform a simulated study of fuel consumption, NOx emission and drivability study for a particular vehicle platform. In the next stage of work, the mathematical model for a brush-less direct current machine (BLDC) with the drive system and Li-Ion battery are developed. The models are verified and calibrated with the experimental results from TVS Motor Company. The BLDC machine is integrated with both the CVT and MT powertrain models in parallel hybrid configurations and a drive cycle simulation is conducted for different static assist levels by the electrical machines. The initial test confirms the need of optimal sizing of the powertrain components as well as an optimal control system. The detailed model of the powertrain is converted to a control-oriented model which is suitable for optimal control. This is followed by multi-objective optimization of different components of the motor-integrated powertrain using a single function as well as Pareto-Optimal methods. The objective function for the multi-objective optimization is proposed to reduce the fuel consumption with battery charge sustainability with least impact on the increase of financial cost and weight of the vehicle. The optimization is conducted by a nested methodology that involves Particle Swarm Optimization and a Non-dominated sorting genetic algorithm where, concurrently, a global optimal control is developed corresponding to the multi-objective design. The global optimal controller is designed using dynamic programming. The research is concluded with an optimal controller developed using the hp-collocation method. The objective function of the dynamic programming method and hp-collocation method is proposed to reduce fuel consumption with battery charge sustainability.Open Acces

Development of Automated Calibration Methodology for Last Generation of Diesel Automotive Powertrains

L'abstract è presente nell'allegato / the abstract is in the attachmen