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<p>This masters thesis investigates the possibility to estimate the ethanol content in the fuel using ion currents. Flexible fuel cars can be run on gasoline-ethanol blends with an ethanol content from0 to 85 percentage. It is important for the engine control system to have information about the fuel. In todays cars the measurements of the fuel blend are done by a sensor. If it is possible to do this with ion currents this can be used to detect if the sensor is broken, and then estimate the ethanol content until the sensor gets fixed. The benefit</p><p>of using ion currents is that the signal is measured directly from the spark plug and therefore no extra hardware is needed. To be able to see how the ethanol ratio affects the ion currents, the dependencies of the operating point have been investigated. This has been done by a literature review and by measurements in a Saab 9-3. Engine speed, load, ignition timing, lambda and spark plugs effects on the ion currents are especially studied. A black box model for the ion currents dependence on operating point is developed. This model describes the engine speed, load and ignition timing dependencies well, but it can not be used to estimate the ethanol ratio.</p>

Multidisciplinary design optimization (MDO) is a technique that has found use in the field of aerospace engineering for aircraft design. It uses optimization to simultaneously solve design problems with several disciplines involved. In order to predict aircraft performance an engine performance simulation model, also called “rubber engine”, is vital. The goal of this project is to validate and integrate a rubber engine model into an MDO environment. A method for computer simulation of gas turbine aero engine performance was created. GasTurb v11, a commercial gas turbine performance simulation software, was selected for doing the simulation models. The method was validated by applying it to five different jet engines of different size, different type and different age. It was shown that the simulation engine model results are close to the engine manufacturer data in terms of SFC and net thrust during cruise, maximum climb (MCL) and take off (MTO) thrust ratings. The cruise, take off and climb SFC was in general predicted within 2% error when compared to engine manufacturer performance data. The take off and climb net thrust was in general predicted with less than 5% error. The integration of the rubber engine model with the MDO framework was started and it was demonstrated that the model can run within the MDO software. Four different jet engine models have been prepared for use within the optimization software. The main conclusion is that GasTurb v11 can be used to make accurate jet engine performance simulation models and that it is possible to incorporate these models into an MDO environment.

This masters thesis investigates the possibility to estimate the ethanol content in the fuel using ion currents. Flexible fuel cars can be run on gasoline-ethanol blends with an ethanol content from0 to 85 percentage. It is important for the engine control system to have information about the fuel. In todays cars the measurements of the fuel blend are done by a sensor. If it is possible to do this with ion currents this can be used to detect if the sensor is broken, and then estimate the ethanol content until the sensor gets fixed. The benefit of using ion currents is that the signal is measured directly from the spark plug and therefore no extra hardware is needed. To be able to see how the ethanol ratio affects the ion currents, the dependencies of the operating point have been investigated. This has been done by a literature review and by measurements in a Saab 9-3. Engine speed, load, ignition timing, lambda and spark plugs effects on the ion currents are especially studied. A black box model for the ion currents dependence on operating point is developed. This model describes the engine speed, load and ignition timing dependencies well, but it can not be used to estimate the ethanol ratio.

The aim of this thesis is to increase engine efficiency by studying the flow structures created in an engine cylinder during the intake phase and the effect of the subsequent compression. The invention of the combustion engine has enabled three centuries of economic growth fueled by energy stored as hydrocarbons. However, during the latter part of the twentieth century negative consequences on health and environment of the combustion engine were observed. In order to reduce emissions without increasing fuel consumption, improved knowledge of all physical processes occurring in the engine are necessary. The aim of this thesis is to increase the understanding of the flow prior to combustion, which can lead to reduced engine emissions and fuel consumption. Intake flow structures are studied using large eddy simulations and experiments on a steady swirl test rig. Flow acceleration was observed to reduce the swirl coefficient, and higher swirl coefficient was found during valve closing as compared to during valve opening. This implies that the rotation is stronger during the later part of the intake then what has been previously assumed. In addition, the computations show that the volume above the valves has a profound effect on the swirl created during the intake. To take this into account a novel way of calculating the swirl number was suggested. This approach gives a lower swirl number as compared to the commonly used Thien methodology. The effects of compression are studied using simulations of predefined flow structures undergoing compression. The peak turbulence levels were found to be increasing with tumble number and decreasing with swirl. It was noted that compression increased the turbulent fluctuations in the cylinder axis leading to anisotropic turbulence and that a small tilt angle was observed to have a significant effect on swirl homogeneity at top dead center.  In this thesis, a new methodology was proposed and validated for calculation of in-cylinder turbulence for a flat piston. The results of the thesis enhance the understanding of the dynamic effects encountered during intake as well recognizing that a small tumble component has a strong effect on the flow structures prior to combustion. These results can be used to improve the simplified computational methods used to optimize the engine. / <p>QC 20150420</p>

AN ABSTRACT OF THE THESIS OF AMIT SHRESTHA, for the Master of Science degree in MECHANICAL ENGINEERING, presented on July 6th 2009, at the Southern Illinois University at Carbondale. TITLE: DEVELOPMENT AND PERFORMANCE EVALUATION OF A MONO-VALVE ENGINE MAJOR PROFESSOR: Dr. Suri Rajan A new Mono-Valve engine head was fabricated and assembled for a standard 4-stroke single cylinder Two-Valve gasoline engine with an aim to achieve an improved air flow characteristics than that of the Two-Valve engine. The Mono-Valve engine has only one valve in the cylinder head with the intake and exhaust ports controlled by an auxiliary Rotary-Valve. The two engines were tested under cold flow motoring conditions at engine speeds ranging from 1000 to 2500 rpm under fully open and half open throttle conditions in order to study and compare their volumetric efficiencies. Variable intake pipe lengths of 8.25, 25.5 and 39 inches were used to study their effect on volumetric efficiencies and in-cylinder pressure characteristics of both the engines. The results of the experiments showed that the average in-cylinder peak pressure, intake and exhaust pressures characteristics are similar for both the engine heads. However, the volumetric efficiency of the new Mono-Valve engine head was found to be 2-7% less than that of the original Two-Valve engine head depending upon the length of the intake pipe. This is mainly due to the opening angle in the Rotary-Valve that mostly controls the duration of the intake and the exhaust processes, and also due to the timing of the opening and closing of the intake and exhaust ports.

Researchers are trying to find a solution for reducing the vibration of the engine with minimum changes to the engine mounts. Several researches and main giant car companies have presented valuable effort in these areas but still new research is needed to improve the control system. The present research carried out a comprehensive study of the state of art methods to suppress unwanted vibration from the engine to the passenger cars. This research was designed based on the objective of the Trelleborg Company to investigate the influence of Active Vibration Control (AVC) on the real engine. Therefore, this thesis tried to challenge the vibration problem with practical engineering approach by implementing different types of controllers experimentally and applying them on the real petrol engine. Inversing controlling technique and PID controller tuned with different methods (Ziegler Nichols and tyreus-luyben) have been tested here on two separate platforms; unbalanced DC motor and petrol engine. In addition, as a requirement of the study, the resonance frequency and related mode shapes of the system was investigated experimentally. It is also shown that using suitable filters can help elimination of high frequency noises in the control signals. This study experimentally tests PID controller with mentioned tuned methods on a real engine with this specific setup for the first time. A new scheme was developed with "mode shapes specific controller system", according to which the shaker position and the controller parameters were specified according to the system mode shapes. The result of applying controllers shows that both control methods have a similar effect on vibration reduction. A 33% - 37% reduction on DC motor achieved in different frequencies (20Hz, 37.5Hz and 46.2Hz) with different control methods, and about 10% reduction on petrol engine at resonance frequency while the shaker IV40 (with max 30N force) was placed on the chassis. For reducing the vibration transmitted from the engine to the chassis, for the first time the shaker was placed on the engine (unlike in previous studies where the shaker was placed on the chassis). Using shaker IV40 placed on the engine results in a 20% reduction in vibration transmission, which is a significant improvement in comparison with having the shaker on the chassis. The optimum result was achieved using shaker IV45 (Max 50N force), which yielded a vibration reduction of 33%.

Improving the efficiency of spectrum access and utilization under the umbrella of cognitive radio (CR) is one of the most crucial research areas for nearly two decades. The results have been algorithms called cognitive radio engines which use machine learning (ML) to learn and adapt the communication's link based on the operating scenarios. While a number of algorithms for cognitive engine design have been identified, it is widely understood that significant room remains to grow the capabilities of the cognitive engines, and substantially better spectrum utilization and higher throughput can be achieved if cognitive engines are improved. This requires working through some difficult challenges and takes an innovative look at the problem. A tenet of the existing cognitive engine designs is that they are usually designed around one primary ML algorithm or framework. In this dissertation, we discover that it is entirely possible for an algorithm to perform better in one operating scenario (combination of channel conditions, available energy, and operational objectives such as max throughput, and max energy efficiency) while performing less effectively in other operating scenarios. This arises due to the unique behavior of an individual ML algorithm regardless of its operating conditions. Therefore, there is no individual algorithm or parameter sets that have superiority in performance over all other algorithms or parameter sets in all operating scenarios. Using the same algorithm at all times may present a performance that is acceptable, yet may not be the best possible performance under all operating scenarios we are faced with over time. Ideally, the system should be able to adapt its behavior by switching between various ML algorithms or adjusting the operating ML algorithm for the prevailing operating conditions and goal. In this dissertation, we introduce a novel architecture for cognitive radio engines, with the goal of better cognitive engines for improved link adaptation in order to enhance spectrum utilization. This architecture is capable of meta-reasoning and metacognition and the algorithms developed based on this architecture are called metacognitive engines (meta-CE). Meta-reasoning and metacognitive abilities provide for self-assessment, self-awareness, and inherent use and adaptation of multiple methods for link adaptation and utilization. In this work, we provide four different implementation instances of the proposed meta-CE architecture. First, a meta-CE which is equipped with a classification algorithm to find the most appropriate individual cognitive engine algorithm for each operating scenario. The meta-CE switches between the individual cognitive engine algorithms to decrease the training period of the learning algorithms and not only find the most optimal communication configuration in the fastest possible time but also provide the acceptable performance during its training period. Second, we provide different knowledge indicators for estimating the experience level of cognitive engine algorithms. We introduce a meta-CE equipped with these knowledge indicators extracted from metacognitive knowledge component. This meta-CE adjusts the exploration factors of learning algorithms to gain higher performance and decrease training time. The third implementation of meta-CE is based on the robust training algorithm (RoTA) which switches and adjusts the individual cognitive engine algorithms to guarantee a minimum performance level during the training phase. This meta-CE is also equipped with forgetting factor to deal with non-stationary channel scenarios. The last implementation of meta-CE enables the individual cognitive engine algorithms to handle delayed feedback scenarios. We analyze the impact of delayed feedback on cognitive radio engines' performances in two cases of constant and varying delay. Then we propose two meta-CEs to address the delayed feedback problem in cognitive engine algorithms. Our experimental results show that the meta-CE approach, when utilized for a CRS engine performed about 20 percent better (total throughput) than the second best performing algorithm, because of its ability to learn about its own learning and adaptation. In effect, the meta-CE is able to deliver about 70% more data than the CE with the fixed exploration rate in the 1000 decision steps. Moreover, the knowledge indicator (KI) autocorrelation plots show that the proposed KIs can predict the performance of the CEs as early as 100 time steps in advance. In non-stationary environments, the proposed RoTA based meta-CE guarantees the minimum required performance of a CRS while it’s searching for the optimal communication configurations. The RoTA based meta-CE delivers at least about 45% more data than the other algorithms in non-stationary scenarios when the channel conditions are often fluctuating. Furthermore, in delayed feedback scenarios, our results show that the proposed meta-CE algorithms are able to mitigate the adverse impact of delay in low latency scenarios and relieve the effects in high latency situations. The proposed algorithms show a minimum of 15% improvement in their performance compared to the other available delayed feedback strategies in literature. We also empirically tested the algorithms introduced in this dissertation and verified the results therein by designing an over the air (OTA) radio setup. For our experiments, we used GNU Radio and LiquidDSP as free software development toolkits that provide signal processing blocks to implement software-defined radios and signal-processing systems such as modulation, pulse-shaping, frame detection, equalization, and others. We also used two USRP N200 with WBX daughterboards, one as a transmitter and the other as a receiver. In these experiments, we monitored the packet success rate (PSR), throughput, and total data transferred as our key performance indicators (KPI). Then, we tested different proposed meta-CE algorithms in this dissertation to verify the productivity of the proposed algorithms in an OTA real-time radio setup. We showed that the experiments’ outputs support our simulations results as well.

The efficiency of an internal combustion (IC) engine is governed by the thermodynamic cycle underpinning its operation. The thermodynamic efficiency of these devices is primarily determined by the temperature gradient created during the compression process. The final conversion efficiency also known as brake thermal efficiency (BTE) of IC engines, however, also depend on other processes associated with its operation. BTE is a product of the combustion, thermodynamic, gas-exchange, and mechanical efficiencies. The improvement of BTE through maximation of any one of the four efficiencies is reduced by its implication of the other three. Split-cycle engine provides an alternative method of improving the engine efficiency through over-expansion of combustion gases by transferring it to a cylinder of greater volume. The operation of split-cycle engines is based on either the Brayton or the Atkinson Cycles. Atkinson Cycle has been demonstrated in IC engines without the split-cycle architecture but is limited by the reduced energy density. Double Compression Expansion Engine (DCEE) provides a method of accomplishing the Atkinson Cycle without the constraints faced in conventional engine architectures. DCEE splits the compression and expansion processes in a vertical manner that enables the use of larger cylinder volumes for over-expansion as well as first-stage compression without much friction penalties. The present thesis explores the thermodynamic cycle of this novel engine architecture using well-validated 1-dimensional engine models solving for gas-exchange, real gas properties, and heat transfer provided in the GT-Power software tool. The effect of compression ratio, rate of heat addition, sensitivity to design and modeling parameters was assessed and contrasted against conventional engine architecture. The synergies of combining low-temperature combustion (LTC) concepts with DCEE was investigated using simulation and experimental data. DCEE relaxes many constraints placed the operation of an engine in Homogenous Charge Compression Ignition (HCCI) mode. The limitations of adopting Partially Premixed Combustion (PPC) concept is also alleviated by the DCEE concept. BTE improvement of above 10% points is achievable through the DCEE concept along with possibility to achieve very low emissions through use of LTC concepts and new after-treatment methods uniquely available to the DCEE.

Indiana University-Purdue University Indianapolis (IUPUI) / Stringent regulatory requirements and modern diesel engine technologies have engaged automotive manufacturers and researchers in accurately predicting and controlling diesel engine-out emissions. As a result, engine control systems have become more complex and opaquer, increasing the development time and costs. To address this challenge, Model-based control methods are an effective way to deal with the criticality of the system study and controls. And physics-based combustion engine modeling is a key to achieve it. This thesis focuses on development and validation of a physics-based model for both engine and emissions using model-based design tools from MATLAB & Simulink. Engine model equipped with exhaust gas circulation and variable geometry turbine is adopted from the previously done work which was then integrated with the combustion and emission model that predicts the heat release rates and NOx emission from engine. Combustion model is designed based on the mass fraction burnt from CA10 to CA90 and then NOx predicted using the extended Zeldovich mechanism. The engine models are tuned for both steady state and dynamics test points to account for engine operating range from the performance data. Various engine and combustion parameters are estimated using parameter estimation toolbox from MATLAB and Simulink by applying the least squared solver to minimize the error between measured and estimated variables. This model is validated against the virtual engine model developed in GT-power for Cummins 6.7L turbo diesel engine. To account for the harmonization of the testing cycles to save engine development time globally, a world harmonized stationary cycle (WHSC) is used for the validation. Sub-systems are validated individually as well as in a loop with a complete model for WHSC. Engine model validation showed promising accuracy of more than 88.4 percent on average for the desired parameters required for the NOx prediction. NOx estimation is accurate for the cycle except the warm-up and cool-down phase. However, NOx prediction during these phases is limited due to actual NOx measured data for tuning the model for real-time NOx estimation. Results are summarized at the end to compare the trend of NOx estimation from the developed combustion and emission model to show the accuracy of in-cylinder parameters and required for the NOx estimation.