Engine Modeling and Simulation

Stricter emission norms and increasing pollution have motivated researchers to find an optimal way to explore and deploy advanced engine technology and alternative fuels. Engine combustion is a complex process that is yet to understand significantly. Computational modelling has enabled the researcher to understand complex underlying processes quickly and economically. This book covers major aspects of internal combustion (IC) engine modelling. The first two sections of this book focus on various engine models, mathematical modelling of injection processes, and spray breakup modelling. The third section of this book is dedicated to the modelling of diesel engine combustion. Emphasis has been made on soot and NOx modelling. The fourth section of this book is dedicated to model the spark ignition engine processes. Various 1D and 3D tools that are currently used by the automotive community are discussed in detail. The last section of this book covers the prediction of exhaust heat recovery from IC engines. Overall, this book emphasises mathematical modelling of the different processes involved in IC engines.

The engine block is a crucial component of internal combustion engines since it provides the source of power for the vehicle. The engine block is a solid cast element that contains the cylinders and their related components inside a cooled and lubricated crankcase. The majority of engine blocks are cast iron, a brittle rich material that can sustain greater variations and weights while also being vibration resistant. Energy is changed from potential chemical energy to mechanical energy in this step, which is heat produced from burning fuel in the form of mechanical energy. A large amount of energy may be lost during the firing of an engine. This must be assessed using CFD prediction techniques. For starters, significant thermal and structural stresses may be produced over the cylinder blocks and pistons. Prior to the fabrication of the specific Internal Combustion engine, the structural and thermal analysis aids in the failure analysis. The solid modeller Parametric-Creo is used to create the current and new engine block models. This technical chapter will cover the simulation and analysis of the structural and thermal consequences of each specified bore piston and cylinder block model. The effective stress and temperature analysis using the finite element method will be performed using current tools such as ANSYS workbench, ADSL, and Deform 3D, with the processes and analytical functions described utilising supplementary literature theories, which can be found here.

In a diesel engine, the injection phenomenon is vital because it impacts fuel spray characteristics and mixture formation process. Accurate control of operating fuel injection parameters (injection timing, flow rate shaping and fuel in-line pressure) is necessary as it affects mixture formation method of air and fuel. If the energy content of fuel is less, to sustain the desired power output, the injection duration would increase. The increased injection duration would affect the important combustion parameter predominantly the combustion duration. So, the optimization of the injection system is needed for a diesel engine for better performance and emission characteristic. The fuel atomization characteristics, and subsequently spray development compete a crucial part in the progress of better combustion and engine performance, as it affects the mixture formation in the combustion chamber. There are studies and models available for diesel fuel spray with and without swirl. If the bulk modulus of fuel is higher, the fuel inline pressure increases significantly. The bulk modulus implies compressibility of a fuel. The longer fuel spray penetration observed with rise in the fuel inline pressure further it also increases the chances of wall impingement. It is one of the main durability issues of a diesel engine. On the other hand, it is important to note that the rise in pressure of injection is a useful approach to enhance fuel atomization characteristics and to enhance mixing of air and fuel. The higher bulk modulus of fuel results in advanced injection timing which further leads to high NOx emission. Furthermore, the increased spray penetration increases NOx emission which forms generally around periphery of spray. Therefore, it is necessary to evaluate the spray development and fuel atomization characteristics for reduction of exhaust emissions and subsequently, enhance the efficiency of the engine. The current research work is aimed at the extent review of computational/mathematical models of spray characteristics and empirical models of injection and spray process of engine. The challenges for modeling of spray characteristics are also highlighted. Numerous research works have been referred and analyzed for the effect of injection parameters and fuel properties on injection and spray characteristics of the engine.

Rising concerns about emissions have led to a significant tightening of pollution norms for internal combustion (IC) engines. High-pressure direct injection (HPDI) technologies have been adopted for most on-road and off-road engines to meet the global demand for clean and efficient powertrains. Higher fuel efficiency, superior combustion, and lower pollutant formation are the characteristic features of the HPDI. The introduction of alternative fuels, modified combustion geometry, and novel combustion concepts demand continuous improvement in fuel injection equipment (FIE). The complicated physics of HPDI and its modelling is an active area of research among researchers and engine developers. Fuel-injected in the combustion chamber breaks up into a spray of fine droplets, evaporating, mixing with ambient air, and forming a fuel–air mixture, greatly affecting the engine combustion and emission characteristics. Therefore, it is necessary to study the fuel breakup phenomenon under different engine conditions comprehensively. Detailed understanding of the spray breakup phenomenon is unavailable due to difficulties in optical access, highly dense sprays, complex processes, etc. However, recent advances in measurement technologies and computational tools have made it feasible for researchers. This chapter attempts to capture widely used spray breakup models and research studies involving IC engines. Fundamental spray breakup and atomization have been discussed at the beginning of the chapter. Subsequently, the basis and fundamentals of popular spray models have been discussed. Finally, the authors have comprehensively discussed the key contributions in sprays to provide an overall idea about the spray models and their application for IC engine studies. Various spray breakup models such as Blob Model, Linear Instability Sheet Atomization (LISA) Model, Kelvin–Helmholtz (KH) Model, Kelvin–Helmholtz-Aerodynamics Cavitation Turbulence (KH-ACT) Model, RT (Rayleigh–Taylor) Model, Hybrid/Modified Kelvin–Helmholtz Rayleigh–Taylor (KH-RT) Model, Taylor Analogy Breakup (TAB) Model, Enhanced TAB breakup model (ETAB) are discussed briefly in this chapter. Towards the end, a summary of the contents of the chapter is provided, which covers highlights and significant observations.

A four-stroke IC engine cycle undergoes the following processes—intake, compression, combustion, expansion and exhaust, which are governed by complex fluid dynamics, chemical kinetics and heat transfer phenomena and occur in milli/nanosecond timescales inside the engine cylinder making it difficult to visualize experimentally. A better understanding of the in-cylinder phenomena helps design better engines in terms of performance, fuel consumption and emissions. Optimization of the engine processes through physical testing can be time and cost intensive. CFD analysis helps visualize the various in-cylinder processes, analyze them better and evaluate various engine optimization parameters without having to test on an actual engine, hence it is comparatively effortless to do back-to-back comparisons to identify the effect of a single parameter, which reduces the engine development time and cost drastically. CFD analysis of Diesel engines is particularly useful since there are many in-cylinder optimization parameters in a diesel engine in comparison with a conventional gasoline engine, due to the direct injection and heterogeneous nature of combustion. This chapter aims to give an overview of the general methodology followed in performing CFD simulations in diesel engines towards the objective of enhancing the performance and minimizing the fuel consumption and emissions. Here a comprehensive coverage of the complete process of modeling and simulation is attempted, starting with the basic input data required, typical assumptions used, fundamental governing equations and discretization, model formulation, initial conditions, boundary conditions, model validation, various sub-models used and the analysis of results. The effect of in-cylinder techniques like combustion chamber geometry, injection timing, multiple injections and exhaust gas recirculation on performance and emissions is discussed through a brief review of published literature. It is hoped that the reader will get an insight into the procedure followed in diesel engine CFD analysis and some of its applications in the optimization through various in-cylinder techniques.

Accurate, reliable, and computationally inexpensive models of the dynamic state of combustion engines are a fundamental tool to investigate new engine designs, develop optimal control strategies, and monitor their performance. The use of those models would allow to improve the engine cost-efficiency trade-off, operational robustness, and environmental impact. To address this challenge, two state-of-the-art alternatives in literature exist. The first one is to develop high fidelity physical models (e.g., mean value engine, zero-dimensional, and one-dimensional models) exploiting the physical principles that regulate engine behaviour. The second one is to exploit historical data produced by the modern engine control and automation systems or by high-fidelity simulators to feed data-driven models (e.g., shallow and deep machine learning models) able to learn an accurate digital twin of the system without any prior knowledge. The main issues of the former approach are its complexity and the high (in some case prohibitive) computational requirements. While the main issues of the latter approach are the unpredictability of their behaviour (guarantees can be proved only for their average behaviour) and the need for large amount of historical data. In this work, following a recent promising line of research, we describe a modelling framework that is able to hybridise physical and data driven models, delivering a solution able to take the best of the two approaches, resulting in accurate, reliable, and computationally inexpensive models. In particular, we will focus on modelling the dynamic state of a four-stroke diesel engine testing the performance (both in terms of accuracy, reliability, and computational requirements) of this solution against state-of-the-art physical modelling approaches on real-world operational data.

Diesel engines find applications in many areas such as transportation of passengers/goods, farm machines, Generators, and construction equipment. The number of diesel-fueled engines is very large and is expected to increase further with time. However, diesel engines are responsible for anthropogenic NOx and soot emissions. To comply with the stringent future emission regulations, ways of inhibiting the formation of these emissions need to be explored further. Low-temperature combustion (LTC) strategies such as homogeneous charge compression ignition (HCCI), reactivity controlled compression ignition (RCCI), partially premixed charge compression ignition (PCCI) have the capabilities of ultra-low NOx and Soot emission formation. These LTC strategies improve the fuel–air mixing and reduce the peak combustion temperature, leading to low NOx and Soot emissions. These combustion strategies face challenges in controlling combustion, maintaining combustion stability, and operating the engine at a high load. Engine modelling could play a role in predicting Soot and NOx emissions from these complex combustion strategies. In this chapter, an effort has been made to understand the fundamentals of soot and NO_x modelling. It is essential to understand the chemical mechanisms of NOx and soot formation for accurate modelling. Empirical and phenomenological models for soot and NO_x formation mechanisms, factors affecting them, Zeldovich mechanism, and prompt NOx formation mechanisms are discussed. Hiroyasu-NSC model, Waseda model, Gokul model, and Dalian model to understand the soot formation and their capabilities are discussed in detail. The two most fundamental semi-empirical models for NO_x formation based on the Zeldovich mechanism and the prompt NO_x (Fenimore mechanism) are also discussed.

Strict emission norms, fewer complex emissions prediction models forces to develop a numerical model which actively control both combustion phase as well as after-treatment systems. This study is focused on the simulation and experimental investigation of simplified model for prediction of NO_x emissions along with unburned zone, burned zone, adiabatic flame temperatures and species concentration especially atomic oxygen [O], Nitrogen [N₂] and nitric oxide [NO]. Burned flame temperature and thermal NO concentrations were simulated by enthalpy balance and Zeldovich mechanism respectively. The simulated results were validated with experimental result of Turbocharged direct injected Diesel engine at steady-state operating conditions. The maximum temperature (T_max) simulated within burned zone at 2200 rpm and 100% load is 2917 K while at 75% load, and 50% load it reduces to 2853 K, and 2776 K respectively. It was also observed that the equilibrium concentrations of [O], [NO] and [N₂] were directly proportional to burned zone temperature. The accuracy of proposed model was tested at 2200 rpm rated speed and also at 1400 rpm with full load, 75% load, and 50% load. NOx reduces with speed for identical operating conditions.

The advancement of technologies has led researchers to explore new ways to comply with stringent emission norms globally and fulfil the energy requirements. The trends in engine development favour computational studies for initial investigations due to lesser time demand and economy. In a spark ignition (SI) engine, ignition of the fuel–air mixture is achieved by the spark discharge across the spark plug electrodes. The discharge is of very high intensity for a very short interval, providing sufficient energy in the form of plasma kernel to initiate chemical reactions necessary to generate a self-sustaining flame. Direct injection SI combustion system is considered an upcoming next-generation technology capable of meeting stringent emission norms with improved engine performance. Conventional spark plug system undergoes various issues such as erosion of spark plug, heat losses at the electrodes, hindrance in working at high in-cylinder pressures, and fixed spark location. Therefore, the researchers explore alternate ignition concepts/ systems that provide greater flexibility than conventional ignition systems. These alternate ignition concepts/ systems include laser ignition, turbulent jet ignition, corona ignition, and microwave ignition. These all are also referred to as advanced ignition systems. Advanced ignition has emerged as an alternative way to ignite leaner fuel–air mixture owing to higher engine performance and lower emissions. These systems offer significant advantages; however, they are still under research, and many challenges need to be overcome before they are commercialized. In this chapter, the evolution of the spark ignition systems has been discussed. Modelling aspects of spark ignition engines using 1D and 3D simulation tools have been summarised. The working of these advanced ignition systems has been discussed in detail, and their challenges are also summarised.

This chapter reports on a workflow aimed at obtaining deeper insights into spark ignition engines using thermodynamic modelling. This workflow is divided into two steps: (i) Auto-calibration of combustion and heat transfer models using AVL Boost^® and AVL Design Explorer; and (ii) in-cylinder exergy analysis using Wolfram Mathematica^®. Model calibration is usually based on experimental pressure curve and combustion data. However, there is a gap in methods that generate accurate simulation results, while calibrating the combustion and heat transfer models without prior experimental results. Thus, the authors proposed an approach in their earlier work to address this gap. In this chapter, this proposed approach has been complemented with exergy analysis to form a complete workflow for engine research using simulation. This workflow was applied to a 4-cylinder gasoline engine template model as a case study. First, the combustion and heat transfer models are parametrized and used as design variables of an optimization problem. The objective functions in this problem are the combustion phasing, here defined as the crank angle in which the peak cylinder pressure occurs CA_pp, and the mechanical load, here defined as the indicated mean effective pressure IMEP. The appropriate temperature constraints were included to guarantee that the engine model was representative of the physical problem. The optimization problem is then solved for a target IMEP and CA_pp and the results are analyzed. Afterwards, we begin the exergy analysis of the engine to obtain deeper insights. The resulting curves for the thermodynamic state properties and species’ molar fraction are exported from the simulation software to a program in Wolfram Mathematica that does the exergy analysis of the engine, providing deeper insights into the useful work available in the engine, losses due to heat transfer, losses in the exhaust gases, and combustion irreversibilities. This analysis can be very useful in determining the best fuel mixture, operating conditions, and areas for improvement.

The engine researchers and auto makers are putting out significant effort to develop an alternative to petroleum fueled internal combustion (IC) engines for the production of energy in the automotive. Various emerging technologies like electric vehicles (EVs), fuel cells, hydrogen fueled engines etc. are being used as alternative option for IC engines. Biofuels utilization have shown advantages in terms of minimum modification in the existing engine technologies. On the other hand, spark ignition (SI) engine is being used for two-wheelers, lawn movers, aircraft engines, pumping and electricity generating engines and it may be challenging to replace these working engines in short time and it is expected that SI engine would continue to serve as power generating unit for the coming couple of decades. Alcohols have been treated as alternative fuel for internal combustion engines for a long time especially in SI engines by blending. However, alcohols have a lot of potential to be utilized independently in SI engines. In the present study, a detailed modeling work would be performed to investigate the effect of injection timings on the methanol fueled direct injection (DI) SI engine through one dimensional (1-D) simulations. This study suggested as the start of injection (SOI) situation retarded, the heat release rate (HRR) curve shifted to the left. There is hardly any difference in NOx emission depending on injection timing. With a −31° CA SOI at 3.5 kJ fuel energy content, there is a significant quantity of HC observed due to lower fuel efficiency at much advanced SOI conditions.

This study aims at energy harvesting mufflers that utilize thermoelectric generators (TEG) to convert waste heat from the engine exhaust into electricity and simultaneously reduce engine noise. The recovered electricity can be used to power the auxiliary units in the automobile and can effectively improve the overall efficiency of the system. In this study, an automotive exhaust thermoelectric generator (AETEG) unit is fabricated to extract the waste exhaust heat from the engine. To further enhance the performance of AETEG unit, changes in the internal geometry of the unit are proposed, and a systematic computational study is carried. Investigation results indicate that transformations in the internal geometry enhance the heat transfer rate due to lower flow stratification and induced turbulence. This shows increasing potential for higher electricity generation. However, an increase in backpressure due to flow obstruction remains a problem with increasing baffle count. The internal geometry with six baffles gave the best thermal performance with backpressure within acceptable limits for the studied cases. Additionally, that AETEG unit serves as a noise muffler and attenuates the exhaust noise by 53 dBA.

Diesel engines are widely used for road and marine transports. Stationary diesel engines are also used for off-grid supply of electricity for households or to run the auxiliary equipment such as pump, compressor, etc. A significant portion of the thermal energy input to diesel engines is ultimately rejected as waste heat. Exhaust flue gas from marine diesel engines are at about 300 °C. On the other hand, jacket cooling water and scavenging air cooling water are available at below 100 °C. Available waste heat from road transport system may be utilized to produce cooling/heating effect for conditioning of the cabin environment. The waste heat may also be used in turbo chargers for a higher power density. In marine applications, the waste heat may drive a bottoming power cycle to supply the auxiliary power. Waste heat available form a stationary diesel power plant can even be used to run a cogeneration/polygeneration unit satisfying some of the localized energy needs. In the present chapter, simulation results of possible schemes and effects of waste heat recovery from diesel engines have been explored. Finally, generalized principles for the simulation of diesel engine waste heat recovery have been discussed.