COMPUTATIONAL INVESTIGATION OF ROTARY ENGINE HOMOGENEOUS CHARGE COMPRESSION IGNITION FEASIBILITY

Transcription

1 COMPUTATIONAL INVESTIGATION OF ROTARY ENGINE HOMOGENEOUS CHARGE COMPRESSION IGNITION FEASIBILITY A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Engineering By Michael Irvin Resor B.S., Wright State University, Wright State University

2 WRIGHT STATE UNIVERSITY GRADUATE SCHOOL December 9, 2014 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY Michael Irvin Resor ENTITLED Computational Investigation of Rotary Engine Homogeneous Charge Compression Ignition Feasibility BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science in Engineering. Committee of Final Examination George Huang, Ph.D. Thesis Director Haibo Dong, Ph.D. Co-Advisor George Huang, Ph.D. George Huang, Ph.D. Chair Department of Mechanical and Materials Engineering College of Engineering and Computer Science Greg Minkiewicz, Ph.D. Scott Thomas, Ph.D. Zifeng Yang, Ph.D. Robert E. W. Fyffe, Ph.D. Vice President for Research and Dean of the Graduate School

3 Abstract Resor, Michael Irvin. M.S. Egr., Department of Mechanical and Materials Engineering, Wright State University, Computational Investigation of Rotary Engine Homogeneous Charge Compression Ignition Feasibility. The Air Force Research Laboratory (AFRL) has been investigating the heavy fuel conversion of small scale Unmanned Aerial Vehicles (UAV). One particular platform is the Army Shadow 200, powered by a UEL Wankel rotary engine. The rotary engine historically is a proven multi-fuel capable engine when operating on spark ignition however, little research into advanced more efficient compression concepts have been investigated. A computational fluid dynamics model has been created to investigate the feasibility of a Homogeneous Charge Compression Ignition (HCCI) rotary engine. This research evaluates the effects, rotor radius to crankshaft eccentricity ratio, known as K factor, equivalence ratio, and engine speed and how they affect the response of horsepower, maximum temperature, and peak pressure to determine the feasibility of HCCI operation. The results show that the advanced HCCI strategy is promising to significantly improve efficiency of the rotary engine. iii

4 TABLE OF CONTENTS Chapter 1: Introduction... 1 Background... 1 Rotary Engine... 1 High Temperature Combustion (SI and CI)... 3 Low Temperature Combustion (HCCI/PCCI)... 5 Research Objective... 7 Methodology... 8 Literature Review... 9 Thesis Outline Chapter 2: Validation Z19DTH - Piston Engine Modeling and Meshing Solver Models and Numerical Settings Combustion Turbulence and Wall Heat Flux Results Chapter 3: Rotary Engine Model iv

5 Modeling and Meshing Boundary and Initial Conditions Solver Settings Chapter 4: Parametric Study on LTC Performance Rotary Homogeneous Charge Compression Ignition (HCCI) Parameters Responses Held Constant Factors Results of 3 3 Factorial Best Fit Case Results from 3 3 Factorial Equivalence Ratio Single Factor Fitting Best Fit Case Equivalence Ratio Single Factor Fitting Chapter 5: Conclusions Chapter 6: Future Work References v

6 LIST OF FIGURES Figure 1 Rolls Royce Diesel Engine [1]... 2 Figure 2 Rotary engines of different K factors [2]... 3 Figure 3 The four diesel combustion phases [4]... 5 Figure 4 Combustion Strategies on Φ - T Diagram [7]... 7 Figure 5 2D Piston Pocket Cross Section Figure 6 Solidworks Sector Geometry at Intake Port Close Figure 7 Mesh Sector Geometry at Intake Port Close Figure 8 Z19DTH CFD Model Wall Conditions Figure 9 Graphical Representation of PDF [23] Figure 10 Pressure Trace of Z19DTH Validation Figure 11 Circular arc approximation of Rotor Flank Figure 12 Rotary Engine Geometries and Meshes Figure 13 Epitrochoidal Path Figure 14 Rotary Engine Thermal Boundary Conditions Figure 15 Design Table Figure 16 Summary of fit and ANOVA table for Pressure Rise Rate Figure 17 Summary of fit and ANOVA table for Maximum Temperature Figure 18 Summary of fit and ANOVA table for Horsepower Figure 19 Actual by Predicted Plots Figure 20 Parameter Estimates vi

7 Figure 21 Plots of Residuals of Pressure Rise Rate plotted verses factors Figure 22 Plots of Residuals of Max Temperature plotted verses factors Figure 23 Plots of Residuals of Horsepower plotted verses factors Figure RPM Profiler Plot with Desirability Figure RPM Profiler Plot with Desirability Figure RPM Profiler Plot with Desirability Figure RPM Profiler Plot Figure RPM Profiler Plot Figure RPM Profiler Plot Figure RPM Data Fit Figure RPM Data Fit Figure RPM Data Fit Figure RPM Output Plots of Temperature, Pressure and PV Figure RPM Output Plots of Temperature, Pressure and PV Figure RPM Output Plots of Temperature, Pressure and PV Figure 36 Temperature vs Crank Angle for K Factor RPM Figure 37 Pressure vs Crank Angle for K Factor RPM Figure 38 Pressure vs Volume for K Factor RPM Figure 39 Temperature vs Crank Angle for K Factor RPM Figure 40 Pressure vs Crank Angle for K Factor RPM Figure 41 Pressure vs Volume for K Factor RPM Figure 42 Temperature vs Crank Angle for K Factor RPM Figure 43 Pressure vs Crank Angle for K Factor RPM Figure 44 Pressure vs Volume for K Factor RPM vii

8 Figure 45 Temperature vs Crank Angle for K Factor RPM Figure 46 Pressure vs Crank Angle for K Factor RPM Figure 47 Pressure vs Volume for K Factor RPM Figure 48 Temperature vs Crank Angle for K Factor RPM Figure 49 Pressure vs Crank Angle for K Factor RPM Figure 50 Pressure vs Volume for K Factor RPM Figure 51 Temperature vs Crank Angle for K Factor RPM Figure 52 Pressure vs Crank Angle for K Factor RPM Figure 53 Pressure vs Volume for K Factor RPM Figure 54 Temperature vs Crank Angle for K Factor RPM Figure 55 Pressure vs Crank Angle for K Factor RPM Figure 56 Pressure vs Volume for K Factor RPM Figure 57 Temperature vs Crank Angle for K Factor RPM Figure 58 Pressure vs Crank Angle for K Factor RPM Figure 59 Pressure vs Volume for K Factor RPM Figure 60 Temperature vs Crank Angle for K Factor RPM Figure 61 Pressure vs Crank Angle for K Factor RPM Figure 62 Pressure vs Volume for K Factor RPM viii

9 LIST OF TABLES Table 1 Z19DTH Engine Parameters [13] Table 2 Validation Models Table 3 Chamber volume at intake port closed Table 4 Common Initial Conditions Table 5 Equivalence ratio and mixture fraction Table 6 Numerical Settings Table 7 JMP Selected Parameters for Best Fit Cases Table 8 CFD Best Fit Cases Results Table 9 Percent Error of JMP to CFD Table 10 Selected Parameters for Best Fit Cases and predicted results Table 11 CFD Best Fit Cases Results Table 12 Percent Error of Best Fit Cases to CFD ix

10 Nomenclature ANOVA Analysis of Variance ATDC After Top Dead Center BTDC Before Top Dead Center CI Compression Ignition CR Compression Ratio DUFL Diesel Unsteady Flamelet EGR Exhaust Gas Recirculation HCCI Homogeneous Charge Compression Ignition ICE Internal combustion Engine K factor Rotor Radius to Crankshaft Eccentricity LTC Low Temperature Combustion MPCI Multiple Premixed Compression Ignition PCCI Premixed Charge Compression Ignition PDF Probability Density Function RPM Revolutions per Minute x

11 SI Spark Ignition SOI Start of Injection TDC Top Dead Center UDF User Defined Functions xi

12 Acknowledgements I would first like to thank my advisors Dr. Haibo Dong and Dr. George Huang for their guidance and commitment to see me through this project. Thank you both for the long distance collaboration, without it I wouldn t have been able to complete my thesis. Thanks to the flow simulation research group I was fortunate to be funded to work on engine related research projects in both my undergraduate and graduate years at Wright State University. I would also like to thank Greg Minkiewicz of Wright Patterson Air Force Base. His determination and vision to improve all aspects of Air Force propulsion made way for this heavy fuel related project. This will be the 4 th thesis funded by his heavy fuel Rotary engine project. With every thesis that he has funded different combustion technologies were studied to improve performance and efficiency of the Rotary engine. My best friend, Alex, throughout college we both focused on thermal/fluid dynamics. Although we didn t always see eye to eye, I couldn t have asked for a better friend with whom to study engineering. Last but not least I would like to thank my wife Mackenzie and our two children Mika and Marek Thank you for your continued support and understanding. I promise I ll have more free time to spend with all of you soon. xii

13 Chapter 1: Introduction Background Rotary Engine Invented by Dr. Felix Wankel, the Wankel rotary engine has been the only long term competitor to the reciprocating piston engine. Dr. Wankel later partnered with NSU to develop the engine into what we know today as the modern rotary engine. A rotary engine uses three main components to complete the four strokes of the Otto Cycle. These parts include a triangular rotor, eccentric shaft, and epitrochoidal housing. Opposed to the conventional reciprocating engine the rotary engine does not use valves to allow air in and out of the chamber; instead the rotor oscillates within the epitrochoidal housing in a planetary motion, classifying this engine as a planetary rotating engine. Although many companies began research and development (R&D) on the rotary engine, the following companies have made the largest contributions to the rotary engine development, Toyo Kogyo (Mazda), Curtis Wright Corporation, and John Deere [1]. The Japanese developments at Mazda under the leadership of Kenichi Yamamoto focused the automotive market, while US development by Curtis Wright and John Deere focused on aircraft application. During the R&D period through the 1980 s, much of the fundamentals that are known about the rotary engine were discovered. Downstream flame propagation, operation of heavy fuels, charge motion, and rotor radius to crankshaft eccentricity ratio (K factor) effects. 1

14 To date only Rolls Royce is the only company that has built a Diesel rotary engine. This diesel engine has never made it out of the R&D phase. The engine featured a large rotor feeding air into a smaller rotor, Figure 1 [1], [2]. A single rotor CI Wankel engine is impractical, the K factor need to produce the compression ratio need for auto-ignition results in a very long and thin combustion chamber at TDC. A long and thin combustion chamber experiences high heat losses, quenching of the flame, and excessive fuel wall wetting. Traditionally engineering factors such as engine size, combustion chamber, and apex seal leaning angle has kept K factors in range of 6 to 10 [2]. Furthermore, no research efforts have attempted Homogeneous Charge Compression Ignition (HCCI) mode on the Wankel engine. Figure 1 Rolls Royce Diesel Engine [1] 2

15 Figure 2 Rotary engines of different K factors [2] High Temperature Combustion (SI and CI) Traditionally the internal combustion engine operates on one of two cycles, the Otto or Diesel Cycle. Each of these cycles has a unique combustion process known as spark ignition and compression ignition respectfully. The spark ignited engine draws in an air-fuel mixture that is compressed, when the piston approaches TDC, an electrical current is sent to the spark plug to initiate combustion. The developed plasma spark kernel grows until a turbulent flame is generated. This flame propagates in a uniform manner throughout the combustion chamber, consuming the air-fuel mixture until it reaches a wall and is extinguished. Typically, a spark ignited engine has a lower compression than that of a diesel cycle. By selecting the proper compression ratio it is possible for the flame to propagate thought the combustion chamber without encountering abnormal combustion, known as knock. Knock is defined as the rapid auto 3

16 ignition of the unburnt air-fuel mixture ahead of the flame front. The mixture ahead of the flame front is known as the end gas. However, the diesel cycle will never encounter knock [3]. From the stand point of a gasoline based engine there is a clear separation between injection and combustion events both events can be discussed separately, but this is not the case for diesel engines. Since we rely on the energy in the compression charge to initiate a chemical reaction, the combustion and injection events overlap. Unlike the spark ignition engine, turbulence has little effect on the burning velocity; fuel mixture determines the combustion rate. Diesel is more efficient than the spark ignition cycle, and operates with a leaner fuel mixture than the spark ignition engine, to reduce soot particulates [3]. The diesel combustion process has four combustion phases of compression ignition, shown in Figure 3. Stage one is known as the ignition delay phase. This phase is characterized as the time between Start Of Injection (SOI) and the first increase in the pressure rise rate. Stage two is sudden pressure increase, ranging from the start of combustion to the peak pressure. Stage three is the main combustion phase covering the range from peak pressure to peak temperature. Stage four is the delayed post-combustion starting at peak pressure, there is no defined limit to the end of this phase. However, one safe suggestion is to use the end of heat release to define the end of combustion to end the fourth stage [4]. 4

17 Figure 3 The four diesel combustion phases [4] Both of the combustion strategies, SI and CI, release the fuel s chemical energy through a flame, turbulent and diffused respectfully. The flame is the hottest part of the combustion process, allowing for NOx and soot chemical reactions to occur at a higher rate, increasing emissions. Internal cylinder temperatures are higher than if the flame could be removed. Low Temperature Combustion (HCCI/PCCI) Low temperature combustion was first discovered by Shigera Ohnishi at Nippon Clean Engine Research Institute Co., Ltd in the late 1970 s. The combustion process known as Active Thermo-Atmosphere Combustion (ATAC) is process where a lean premixed charge is consumed by auto-ignition rather than deflagration flame front. The rapid auto-ignition of the fuel without a flame results in lower cylinder temperatures. Ohnishi found this new combustion offered benefits to fuel consumption and engine emissions [5]. Figure 4, shows the work of Kamimoto which was later updated by Sun. The diagram shows the soot and NOx production ranges on the Φ - T diagram [6], [7]. Conventional combustion is in the range where soot and NOx are 5

18 produced, and Low Temperature Combustion (LTC) strategies operate below the threshold of these emissions [7]. The ATAC process is known today as HCCI and has been the study of numerous papers to reduce engine emissions. The HCCI process also offers engine efficiency similar to the diesel engine [8]. The HCCI method does have negative effects. Uncontrolled start of ignition, the combustion phasing can vary cycle to cycle, the rapid rate of heat release can cause high peak pressures, and oscillating pressure waves, similar to knock, can limit the maximum load achievable to an HCCI engine [9]. The most common way to overcome HCCI problems is to mix the fresh air charge with Exhaust Gas Recirculation (EGR). The premixed hot EGR gases have been found to have two major effects on HCCI combustion, first ignition timing will be advanced and the species found in EGR affect the heat release rate and lower combustion temperatures [10]. Another approach developed by Yang called Multiple Premixed Compression Ignition (MPCI) raises the low load limit of HCCI. This method has a lean mixture into the chamber, combusts, injects, and mixes a second spray of fuel and combusts again. The two combustion events are completely separate; two smaller heat releases can be controlled to reduce the maximum pressure [11]. 6

19 Figure 4 Combustion Strategies on Φ - T Diagram [7] Research Objective A traditional rotary engine cannot produce sufficient compression for auto-ignition due to geometric constraints. The combustion chamber near TDC is not well suited for flame propagation due to flame quenching. However, the recent work of Sher, studied the scalability limits of an engine operating in HCCI mode. Sher found that an engine as small as 0.3cc displacement with 20:1 compression ratio is possible [12]. To understand what the clearance height between the piston and chamber, we can make a few assumptions. First, assume this engine is square, where the bore and stroke are equal. Then, using Equation 1 for calculating Compression Ratio (CR), we can find the clearance height would be approximately 0.38mm. Equation 1 By understanding that HCCI can work in chambers where a flame cannot, SI and CI, design parameters for the rotary engine can now be explored, even though they were once thought to 7

20 be impractical. My research aims to study the feasibility of operating the rotary engine in HCCI mode and to find the optimal K factor for full Revolution per Minute (RPM) range operation. Methodology In order to save time and money Computational Fluid Dynamics (CFD) is often used to evaluate and explore a design space before turning to traditional experimental methods. The design exploration can be used to select parameter ranges to study experimentally, or can be used to derive an optimized geometric shape, or used test conditions for Internal Combustion Engine (ICE) development. In this work a 3D CFD model of a rotary engine is used to evaluate the feasibility of HCCI operation. Due to the complex flow and combustion phenomena of an ICE, a 3D CFD model is need to accurately represent and study these processes. To date, no HCCI rotary engine exists, therefore, model and solver settings need to be validated from experimental data to that of a piston type engine. This method is not ideal, but it s sufficient because both are positive displacement engines and operate on the HCCI/PCCI cycle. Validation data is used from the work of Lee s [13] Ph.D. dissertation from the University of Wisconsin Madison s Engine Research Center. The work presented here examines the full factorial effects that three engine speeds (RPM), three equivalence ratios, and three geometric K factors have on HCCI performance, which is a 27 case design study. Three response factors are used to evaluate rotary engine HCCI engine performance; these factors are peak pressure, pressure rise rate, and indicated power. For the K factor geometries selected, the intake port closing position is the same for all engines presented in this research and the engine displacement is the same. By doing so, uncontrolled and negligible factors have been eliminated from the study yield better parameter correlations. Furthermore, the mass of air and fuel for a given equivalence ratio for the different RPM and K factors will be the same. 8

21 Literature Review The work of Ohnishi [5], discovered the HCCI combustion process at Nippon Clean Engine Research Institute C. Ltd in the mid to late 1970 s and they called it Active Thermo-Atmosphere Combustion (ATAC). Ohnishi noted a lower peak pressure than SI, on the two stroke engine operation. His work mentioned that this worked if the scavenged residuals are setup correctly; that EGR plays a significant role in HCCI combustion. Ohnishi went on to discuss the ideal engine has large displacement with low surface area to volume ratio, and that a high RPM operation is necessary to decrease thermal losses and to have high thermal efficiency. In Aceves paper, HCCI Combustion: Analysis and Experiments highlights two methods of analyzing HCCI combustion using single and multi zone models. The single zone model can accurately predict the start of ignition and is a good indicator of peak pressure. However, the single zone model cannot predict Hydrocarbon and Carbon Monoxide emissions, but a multizone model can be used to predict these emissions. Scalability of HCCI engines is mentioned as well ranging from small motorcycle to large ship engines. Fundamentals of the combustion process were explained when HCCI is dominated by localized reactions in the absences of a propagating flame. Aceves discussed that if HCCI is truly Homogeneous, then turbulences will have little effect on combustion, and would affect temperature gradients more than anything. Finally, key conditions that affect HCCI operation are considered; these include equivalence ratio, percent EGR, and intake conditions. In Chen s paper, A computational study into the effect of EGR on HCCI combustion in IC engine fuelled with Methane. This paper points out that two effects occur by adding EGR, ignition delay and peak temperature reduction. This is caused by thermal and chemical effects. Another important aspect of this paper is the calculation of species mass fraction and premixed 9

22 temperature with a given percent EGR recirculation. This work also notes that compression ratios as high as 21:1 with gasoline fuel have been achieved. With EGR recirculation it is believed that the HCCI range of operation can be extended [10]. In the paper Fuel octane effects on gasoline multiple premixed compression ignition (MPCI) mode by Yang. This paper was more applicable to gasoline fuel, but showed a mode that was able to inject-combust, then inject-combust a second time to extend the load range of HCCI. Traditionally, diesel fuel would not be able to run on this type of mode due to the short ignition delay time. [11] Miniaturization limits of HCCI internal combustion engines by Sher discusses that HCCI will allow for small scale engine operation, to engine size of 0.3 cubic centimeters. Since there is a lack of a flame front, HCCI will allow complete combustion in regions of high quenching. This paper showed that engines with high heat transfer can also support HCCI [12]. In the paper by Olsson, Boosting for High Load HCCI, he discusses the benefits of fuel economy and low emissions of the HCCI mode. However, to achieve low emissions the cylinder charge needs to be very dilute, boosting was studied to overcome the high load limit. It was found that high load HCCI is possible with reduced brake thermal efficiency and that peak pressure will be the limiting factor to the engine load [14]. From the paper Understanding HCCI Characteristics in Mini HCCI Engines by Collair, the small engines studied showed that the pressure rise rate and peak pressures were affected by the thermal stratification. The strong thermal gradient within the CFD model showed that the combustion would cascade within the chamber, allowing for a gradual combustion instead of a rapid combustion [15]. 10

23 The work of Muroki at Mazda published a paper Mazda Rotary Engine Technology. In this paper, it was found that in the spark ignition engine the combustion would not propagate below the narrow of the epitrochoidal housing. With proper care two separate stable combustion zones could occur at the same time within the chamber. This combustion is a fundamental aspect of the rotary engine sweeping volume combustion chamber that is commonly overlooked [16]. Andreae s work entitled On HCCI Engine Knock, studied knock in the HCCI mode. His findings were audible knock transmission was caused by the radiation of structural vibrations. Also, cylinder pressure would oscillate even in the absence of knock, due to the rapid heat release rate. Andreae found that 5 MPa/ms is suitable limit for pressure rise rate for the engine studied [17]. The work performed by Dempsey at Wisconsin Madison s Engine Research Center titled Computational Optimization of a Heavy-Duty Compression Ignition Engine Fueled with Conventional Gasoline, found that HCCI combustion leads to high pressure oscillations within the chamber limiting load in a reciprocating engine. He found that Partial Premixed Compression Ignition (PPCI) allows for low NOx with 50% gross indicated thermal efficiency at high load, but due to the large variations of equivalence ratio soot particulates were increased [18]. Thesis Outline Chapter two covers model creation and numerical settings for the validation study, with the GM Z19DTH diesel engine. Chapter three covers rotary engine model creation and a case study for selecting the optimal K factor, using pressure rise rate, peak pressures, and indicated power as selection criteria. Chapters four and five cover the conclusions and future work respectfully. Finally, chapter six is a list of references. 11

24 Chapter 2: Validation Z19DTH - Piston Engine Lee [13] investigated PCCI effects on a Z19DTH Diesel Engine at Engine Research Center (ERC) of Wisconsin Madison operating on N-Heptane research fuel. Using his data from the Nov4_016 test a CFD model has been created to validate model and solver settings for this thesis rotary engine study. Validation engine operating conditions are given in the Table 1. Table 1 Z19DTH Engine Parameters [13] Displacement Bore Stroke L 82 mm 90.4 mm Compression Ratio 16:1 Swirl Ratio 1.83 Engine Speed Injector Orifice Diameter 2000 RPM 133 micron Number of Orifice 8 Injection Pressure Included Angle SOI Fuel Temperature 150 MPa 120 o 35 o BTDC 55 o C 12

25 Fuel Flow Rate Intake Pressure Intake Temperature mg/cycle 151 kpa 360 K EGR Rate 55 % Modeling and Meshing Modeling the Z19DTH engine was complicated as this engine is not available in the United States. However from the Lee s dissertation, ruled images of the 2D piston geometry were available, and are shown in Figure 5. The geometry data was digitized and together with the engine parameters from Table 1 the cylinder volume was created in Solidworks. Due to the periodic nature of this piston engine, fuel distribution and combustion method, the model was reduced to a 60 degree sector to save computational time, Figure 6. No inlet or outlets are used in this model. This is only possible because the swirl ratio is know from the experimental data, see Table 1, and that only the reacting part of the cycle is of interest for this research. The swirl ratio is the measure of the rotation of the cylinder charge about the cylinders axis. The mesh was created with Ansys meshing software resulting in prism layers with a max skewness of 0.84, shown in Figure 7. Wall Identification can be seen in Figure 8, notice all the faces are walls except for two, these are used for the periodic boundary conditions. 13

26 Figure 5 2D Piston Pocket Cross Section Figure 6 Solidworks Sector Geometry at Intake Port Figure 7 Mesh Sector Geometry at Intake Port Close Close 14

27 Piston Wall Cylinder Wall Cylinder Head Wall Periodic Figure 8 Z19DTH CFD Model Wall Conditions Solver Models and Numerical Settings This section reviews the models and settings used for HCCI simulations. An overview of the major models used are outlined in Table 2, more information on most of the models are covered in the following sub sections, except for the particle break-up model, for more information please see reference [19]. Table 2 Validation Models Chemical Reactions n-heptane mechanism [20] Combustion Model DUFL Particle Break-up Model Wave [19] Turbulence Model k-ε RNG [21] Wall Heat Transfer Han-Reitz [22] 15

28 Combustion The engine model is setup using the Diesel Unsteady Flamelet (DUFL) model to handle the chemical reaction and turbulence-chemistry interaction. The chemical reaction can be solved using a flamelet approach, with reaction kinetics. The Reaction and thermal database is provided by [20] and is available from the ERC website. The kinetics file consists of 76 species and 349 reactions, and is suitable for n-heptane auto ignition and soot precursor simulation. The generated flamelet is dependent on two variables, mixture fraction and strain rate. The flamelet s information is updated and stored in a tabulated lookup table which significantly reduces computational cost. Flamelet information is shared with the turbulence chemistry interaction, which aims to predict the fluctuation in the flow variable s scalar quantities. These fluctuations are found by using Probability Density Function (PDF) approach for model closure, a PDF can be thought of as the fraction of time that the fluid spends in the vicinity of the state. See Figure 9 for graphical representation a PDF [23]. Figure 9 Graphical Representation of PDF [23] 16

29 Turbulence and Wall Heat Flux Many turbulence models are available in Ansys Fluent, selecting the best model to represent a project is very important. Of all the models available the k-ε model was selected for its robust ability and computational time. Specifically, the renormalized group (RNG) variation was selected; this model is derived from the instantaneous Navier-Stokes equations [23]. Internal combustion engines undergo a large change in density due to compression and combustion. The work of Han and Reitz suggests to better model engine flows the RNG model needs to be extended to include compressibility effects [21]. However, the version of the model in fluent does account for density variations just like the Han and Reitz model and it is used in the work presented in this paper and, no modifications appear to be needed. Han and Reitz have also suggested that a standard heat flux function is insufficient in calculating wall heat transfer. This heat flux function needs to be considered during a varying density flows for ICE simulations [22]. The proposed heat flux function is shown in Equation 2. Good agreement was found in the results to experimental engines and many researchers use this method for calculating heat flux [13], [24], [25]. The heat flux function was implemented into fluent via a User Defined Function (UDF) and is attached in the Appendix., [22] Equation 2 Results The results from the validation study are compared against the experimental data and another published set of CFD data. In this study the model validation is performed by comparing pressure histories from in-cylinder measurements to computational data. The data compared in 17

30 Figure 10, shows that there is good agreement, between this CFD Validation and the Experiment and Reference CFD data and can conclude that the numerical models and settings have been validated. Figure 10 Pressure Trace of Z19DTH Validation 18

31 Chapter 3: Rotary Engine Model Modeling and Meshing Rotary engine fluid volume geometries were created 360 degrees Before Top Dead Center (BTDC). These geometries were created using Solidworks and were meshed using Ansys Meshing. The model was simplified to represent the apex seals as a simple planar surface. Many methods can be used to generate the rotor s curved arc. This study used a modified method outline in Ansdale s book [26] of using a circular arc approximation. The method is shown in Figure 11. The modification made to this method allows for a clearance distance of 0.442mm between the epitrochoidal surface and the rotor flank at point (H). The pervious works of [27], [28], [19] used three chambers in order to simulate combustion on all flanks of the rotor to account for chamber interaction. This work follows Abraham s work that only one chamber is needed to access cycle performance [29]. Performance is done by evaluating power by calculating the work per cycle by PdV instead of rotational torque. For this to be valid we assume that all chambers produce the same power, while ignoring any chamber interactions. 19

32 Figure 11 Circular arc approximation of Rotor Flank K=9.5 K=10.5 K=11.5 Rotor Radius (mm) Eccentricity (mm) Compression Ratio Rotor Width (mm) K=9.5 K=10.5 K=

33 Figure 12 Rotary Engine Geometries and Meshes K=9.5 K=10.5 K=11.5 Number of Elements Max Skewness Min Orthogonality Due to combustion modeling constraints each chamber in Fluent is defined as a separate fluid zone. This means that it is not sufficient to move just the rotor which is the case in the physical engine. Therefore, the positions of both the rotor and housing need to updated together to maintain the closed volume. This complex update is performed in Ansys Fluent via a User Defined Function (UDF), where movement of the nodes on the rotor and housing surfaces are controlled by the parametric equations that describe the motion of the apex seals around the epitrochoidal housing. The equations shown below are simply a super position of two rotations; a geometric explanation can be seen in Figure 13. Due to the large expansion and contraction of the fluid zone the side wall and fluid interior is allowed to deform and remesh, while placing control limits on element size and skewness. Mesh motion is setup using the built in-cylinder options in Ansys Fluent, where engine speed and time step size are setup. 21

34 Figure 13 Epitrochoidal Path Boundary and Initial Conditions Simplifications to this rotary engine model have reduced the boundary conditions to only thermal conditions, and the wall thermal conditions are shown in Figure 14. Side Housing, T=560K Rotor, T=580K Housing, T=560K Figure 14 Rotary Engine Thermal Boundary Conditions+ As previously mentioned, turbulence has little to no effect on HCCI combustion, if the mixture is truly Homogeneous. For this reason, the computational mesh was advanced to intake port closed position. The intake port position can be defined with respect to the housing or to crankshaft position; for the work presented here intake port closed position will be defined with 22

35 respect to the crankshaft. By starting simulations from this point, it saves computation time and ensures that the same mass of air and fuel is present for each K factor studied. Tabulated values of chamber volume at intake port closed position are shown in Table 3; the maximum difference of volume between the K factors is cc or 0.36 percent. Table 3 Chamber volume at intake port closed K factor Chamber intake port closed (cc) The common initial conditions for each case can be seen in the Table 4. The only case specific initial condition is the equivalence ratio of 0.1, 0.25, and However, fluent needs this condition to be given in terms of mixture fraction. Mixture fraction is calculated by Equation 3, where φ is the desired equivalence ratio and r is the stoichiometric equivalence for the given fuel. The stoichiometric equation for n-heptane is given by Equation 4, which results in an air fuel ratio of :1. Tabulated results of the calculated mixture fractions are shown in Table 5. Table 4 Common Initial Conditions Gauge Pressure (Pa) 0 X Velocity (m/s) 0 Y Velocity (m/s) 0 Z Velocity (m/s) 0 Turbulent Kinetic Energy (m 2 /s 2 ) 1e-05 23

36 Turbulent Dissipation Rate (m 2 /s 3 ) 1e-05 Temperature (K) 300 Mixture Fraction Variance 0 Equation 3 [23] 1C 7 H (O N 2 ) -> 7CO 2 + 8H 2 O N 2 Equation 4 Table 5 Equivalence ratio and mixture fraction Equivalence Ratio Mixture Fraction Solver Settings The same models and model settings are used in the Rotary model as were used for the validation model. The results of the numerical settings are shown in Table 6. With the importance of the finite rate chemistry to model the chamber conditions, a Least Squares Cell Base Gradient was selected even though it is computationally Gradient Scheme. The equation discretization of at least a second order upwind was selected for all equations except for the turbulence equations. As previously mentioned turbulence is not as important to a perfectly Homogeneous HCCI combustion. 24

37 Table 6 Numerical Settings Gradient Pressure Density Momentum Turbulent Kinetic Energy Turbulent Dissipation Rate Energy Mean mixture Fraction Mixture Fraction Variance Least Squares Cell Based Standard Second Order Upwind Second Order Upwind First Order Upwind First Order Upwind Second Order Upwind Second Order Upwind Second Order Upwind 25

38 Chapter 4: Parametric Study on LTC Performance Rotary Homogeneous Charge Compression Ignition (HCCI) In order to identify the feasibility of a rotary engine operating in the HCCI mode, a parametric study is needed to understand how engine parameters affect engine performance. Parameters selected are essential to HCCI and performance measures to determine their importance to successful operation. Parameters Identification of key parameters is needed to narrow the countless parameters available to internal combustion engines. Much research in this field has been conducted on HCCI for piston engines and the lessons learned from publications have narrowed the search down. The work of Ryan and Callahan found that compression ratio, equivalence ratio, and EGR rate are significant parameters to control a HCCI engine [30]. Traditionally, the rotary engine operates on the SI mode, but does not have a sufficient compression ratio for auto ignition. Therefore, the first parameter identified for this study is the compression ratio. Unlike reciprocating engines, significant changes to a rotary engine s compression ratio are not as simple. The most effective way to alter the rotary engine s compression ratio is to change the K factor. K factor changes will result in redesigning the entire engine and is a costly parameter and important to study. In order to optimize the K factor the acceptable range must be determined by means of a design exploration. As previously mentioned in Chapter 1 K factors typically range from 6 to 10, 26

39 compression ratios were calculated over this range and beyond to a K factor of The next step in the process of narrowing the K factor s range included running simple CFD cases to check for auto-ignition. By starting with a K factor of 11.5 and decreasing by 1.0, when K factor of 8.5 was reached auto-ignition was no longer present. The results of this design exploration established the K factors selected for this study to be 9.5, 10.5, and To eliminate erroneous factors from affecting the results, each engine s displacement has been kept the same, by changing the rotors width. The engine geometry used in this study is based on an UEL 741 rotary engine. The parameters used from this engine include engine displacement, crankshaft eccentricity, and port opening positions. As previously stated HCCI combusts in the absence of a flame, therefore a rotor pocket is no longer necessary and is removed from this study. The equivalence ratio is important in controlling HCCI operation and is the second parameter used in this study. Traditionally, equivalence ratio used for reciprocating HCCI engines ranges from 0.1 to 0.4 [30]. Since no information can be found on rotary engine HCCI, this study is evaluated three equivalence ratios of 0.10, 0.25, and 0.5. This range covers typical equivalence ratios and will better evaluate the equivalence ratio that will result in a maximum chamber temperature of 1800K and will account for any response curvature. To further evaluate the engines feasibility of HCCI operation, it is important to understand how the engine will perform at different engine speeds. Typical engine speeds of 2000, 4000, and 6000 revolutions per minute have been selected for this study as the final evaluation parameter. Responses The engine s response to each parameter requires quantitative measures to evaluate their effects on performance. Theses response measures are used to evaluate optimal settings in this feasibility study. 27

40 The first parameter to evaluate the response is gross indicated work, because of the simplifications of removing the inlet and outlet ports, net indicated work cannot be calculated. The gross indicated work is used to calculate gross power for the engine assuming that each chamber has equal performance. Engine power is an important measure, it allows manufacturers of automobiles and aircraft to select the engine that will meet their desired project goals. An important limiting factor for the operating range of HCCI in reciprocating engines is the pressure rise rate; this rate is like the shock loading of the engine. If the combustion process causes a pressure rise rate too large, it will result in an engine that will become damaged. Research has shown that typical reciprocating engines range between 1.5 to 8 bar/degree, this is used as a guide for this rotary engine study and will try to be minimized [31]. A fundamental characteristic of HCCI is low temperature combustion, specifically temperature bellow 1800 K [31]. To insure that the engine meets this requirement, it is included as the final response to quantify engine performance. This condition will also serve as a second constraint to limit power, this limited power will aid in evaluating the feasibility of operating a rotary engine on the HCCI mode. Held Constant Factors Factors held constant in this study include, engine displacement, intake and exhaust opening and closing positions. These factors are held constant to allow for a more direct comparison of the different K factors across the engine operation range. Results of 3 3 Factorial CFD cases were selected to yield a full factorial design study. All completed case data is postprocessed to calculate power, maximum temperature, and the maximum pressure rise rate, and 28

41 input to the JMP design table. The completed design table is shown in Figure 15 and plots of temperature vs crank angle, pressure vs crank angle, and pressure vs volume. Plots for this data are located in the appendix. Figure 15 Design Table This study aims is to evaluate the feasibility of the rotary engine operating in HCCI cycle. Statistically analyzing only horsepower is the narrow of a focus, the analysis known limitations of HCCI operation is included to weigh in on the feasibility. Three effects analysis are presented and the prediction profiles are used to evaluate optimal settings. The results of the Summary of Fit and ANOVA table analysis of all three responses, Pressure Rise Rate, Maximum Temperature, and Horsepower are shown in Figure 16, Figure 17, and Figure 18 respectfully. The reported R Square values show the degree of fit for the predicted model is the response data. This analysis reported values of , , and for Pressure Rise Rate, Maximum Temperature, and Horsepower respectfully. Values closer to one of these data 29

42 points are ideal for a good model prediction. However the large error values from the ANOVA analysis shows that there may be some uncontrolled factor causing low model correlation. The implication of the low fit is a weak confidence in the models response predicting power those optimal cases need to be run to confirm performance. The ANOVA analysis shows us that a factor or interaction of factors are statistically important in each analysis by the values of Prob >F being smaller than Due to the statistical importance of each analysis it is important to look at the parameter estimates from all three analyses to understand which parameters or parameters interactions are relevant to this study. Figure 16 Summary of fit and ANOVA table for Pressure Rise Rate Figure 17 Summary of fit and ANOVA table for Maximum Temperature 30

43 Figure 18 Summary of fit and ANOVA table for Horsepower Examination of the Actual by Predicted Plots, shown in Figure 19, shows the model s low correlation. These plots will aid in the understanding of any prediction trends that exist. Figure 19 Actual by Predicted Plots The Parameter Estimate Plots show which parameters are statistically significant to the response of each analysis. Statistical significance is determined by any parameter that extends beyond the parallel blue lines in the results from all three responses shown in Figure 20. Equivalence ratio is shown to be the most significant first order the response of pressure rise rate, maximum temperature, and horsepower. RPM is another first order parameter that significantly affects horsepower; horsepower is also affected the higher order interaction of equivalence ratio and RPM. It was initially expected that compression ratio would have a more significant effect on the responses; however the effect may be less significant within the range 31

44 tested. If the k factor range is extended below the threshold of auto-ignition, one can expect the significance of this parameter to increase. Figure 20 Parameter Estimates Response residuals are analyzed by plotting the residual error of each response by each factor. The plots allow for visual inspection of equal variance and any grouping trends. The data shown in Figure 21, Figure 22, and Figure 23, shows similar trends of variance and grouping for residuals plotted against the same factors. However, the residuals of equivalence ratio exhibit the largest range of unequal variance and grouping. The equivalence ratio has the most irregular residuals, and has fewer accurate predictions about the equivalence factor. 32

45 Figure 21 Plots of Residuals of Pressure Rise Rate plotted verses factors 33

46 Figure 22 Plots of Residuals of Max Temperature plotted verses factors 34

47 Figure 23 Plots of Residuals of Horsepower plotted verses factors Further investigation of the feasibility of HCCI operation requires selection of the optimal parameters within the constrained problem and the evaluation of the response. Using the prediction profilers within JMP software, the range of the parameters is evaluated to select a K factor, and the equivalence ratio over the entire engine speed range (RPM). Keeping in mind that the optimal solution may not be within the range presented, the response range previously discussed in this chapter is important to know where the engine will fail to operate beyond these ranges. Since the K factor must be fixed for all engine speeds selection, the K factor was 35

48 the first to be determined. Evaluation K factors across the RPM and equivalence range, as the model predicted K factors effect on the response is very low. However, a trend of that the higher compression engine has better response at the low RPM, and the low compression engine has a better response at the high RPM. Evaluation of the response is weighted first by pressure rise rate and secondly by horsepower. This trend from the prediction profiler shows that the K factor of 10.5 has a medium effect on the desirable parameter plots for the entire engine speed range. The Profiler Plots with Desirability plots used to select the K factor are shown in Figure 24, Figure 25, and Figure 26. Further tailoring of the K factor is possible and should be revaluated to match the intended operating speed range of the engine. Figure RPM Profiler Plot with Desirability 36

49 Figure RPM Profiler Plot with Desirability Figure RPM Profiler Plot with Desirability Simply using the equivalence values from the desirability plots is not possible, since the result in engine pressure rise rates that either do not support combustion or destroy the engine. By turning off the desirability plots and using the selected K factor of 10.5, the best equivalence 37

50 ratio is selected for the 2000, 4000, and 6000 RPM as shown in Figure 27, Figure 28, and Figure 29 respectfully. The equivalence ratio selected for each speed range predicts that the pressure rise rate is below 6.5 bar/degree. The variance of the prediction ranges is as high as ± 10 bar/degree. The large variance is expected for the low model fit discussed earlier. Final parameter selection and response is shown in Table 7. With the low model fit it is good practice to run the best case simulations and compare the results to the JMP analyses. Figure RPM Profiler Plot 38

51 Figure RPM Profiler Plot Figure RPM Profiler Plot Table 7 JMP Selected Parameters for Best Fit Cases Case K RPM Equivalence Pressure Rise Max Power # Factor Ratio Rate (bar/deg) Temperature (K) (HP)

52 Best Fit Case Results from 3 3 Factorial Reusing the same solver settings and inputting new equivalence ratios for each of the three selected engine speeds. Results from the final cases are shown in Table 8. The case results produced less power and lower pressure rise rates than the JMP model prediction. The pressure rise rates are so low in cases 2 and 3 that it is possible to increase the equivalence ratio to gain more power without damaging the engine. A complete listing of the percent error between each predicted value and the CFD results are shown in Table 9. The error results are higher than preferred, and once again is the result of the low statistical fit. Interesting results of maximum temperature is less than 10.5 percent error for all cases, and are approximately 0.25 percent lower than any other error. Another interesting result is the high RPM pressure rise rate, reciprocating HCCI engines have a high load limit imposed by pressure rise rates [9]. While these results are well within the acceptable range, further data reduction may improve the results to locate the best fit case. Table 8 CFD Best Fit Cases Results Case K RPM Equivalence Pressure Rise Max Power # Factor Ratio Rate (bar/deg) Temperature (K) (HP)