Turbine Maps Research Articles

Turbocharger turbine map scaling for virtual engine use

Emissions requirements, performance expectations, and expanding range of fuels for off-road engines are broadening engine air system requirements. As part of reducing engine development cost and risk, virtual engine simulation is used to select architecture and components capable of covering a broad range of requirements through low risk changes to the turbocharger turbine. A method is presented for predicting turbine performance changes due to turbine housing area change, the most effective of these low risk changes, from available turbine map data. The method, developed from a mean line model, learns four simplified geometry parameters, three loss coefficients, and two maximum efficiency rotor inlet incidence coefficients from a training turbine map data set, then predicts a scaled turbine map for changes to a simplified geometry parameter associated with housing area. Reduced mass flow RMS errors less than 4.3% and efficiency RMS errors less than 5.2% are expected when generating scaled turbine maps with this method, which is additional 2% error for flow and 3% error for efficiency over that expected when modeling actual turbine map data.

An improved model for primary prediction of performance map for turbocharger radial turbine

In the contemporary landscape, possessing an intricate understanding of the performance characteristics of turbocharger radial turbine proves invaluable during engine development phases, to improve predictive capabilities of calculation codes and enhance the critical process of matching engines with turbochargers. This research deals with offering two precise yet straightforward analytical functions intended to generate comprehensive performance maps of turbocharger turbines. This is achieved through a refined adjustment of a preexisting analytical function, after introducing an inventive multiplication factor that aligns numerical calculations with experimental data to predict the turbine’s expansion ratio. Besides, a second analytical function forecasts the turbine’s thermo-mechanical efficiency by establishing a power balance equation between the turbine and supplied compressor map. The outcome of the developed model is compared with existing method on two distinct turbochargers, encompassing various rotational speeds. Additionally, a sensitive analysis aiming to detect the most important factors affecting our developed model while exploring it possible validity range for different thermodynamic parameters. The results indicate that the two functions yield reliable estimations of turbine performance, with maximum; root mean square error, R2, and mean absolute percentage error indices find around 9.47%, 0.993, and 9.03% for the turbine expansion ratio, and about 4.42%, 0.612, and 19.78% for efficiency prediction. This novel model enhances simulation accuracy while preserving user-friendliness and robustness based on the prerequisite of limited geometric and thermodynamic parameters at the turbocharger boundaries. Finally, the main advantages of the proposed model is its adaptability for the implementation in calculation codes, turbomachinery optimization strategies and assessments of the design and performance, addressing scenarios where the original turbine maps are rarely provided by turbocharger manufacturers.

Research on speculation method for compressor map of PG9351FA gas turbine

A compressor map is usually represented by a limited number of feature points to speculate the entire operating range. Also, accurate compressor map models can be obtained quickly by using the appropriate methods. In this paper, 9351FA gas turbine is used as the research object, and a set of targeted compressor map speculation scheme is proposed. At 15 data points, high-precision compressor maps are obtained based on BP neural network, and this method is suitable for a large number of data points. At 6 data points, compressor maps are obtained based on the parameter estimation method, and this method is suitable for a small number of data points. The mean square deviation of the compressor map obtained by the neural network is about 0.002, while the minimum mean square deviation of the results of the parameter estimation method is 0.026 and the maximum mean square deviation is 0.088. Since the corrected speed line of 106.4 is almost vertical, the maximum error mean squared deviation and the maximum standard deviation occur on this line. Both methods are suitable for different sample sizes, and the speculated compressor maps are more reliable. The combination of the two methods can provide a set of reference methods for compressor map speculation.

A novel day-ahead regional and probabilistic wind power forecasting framework using deep CNNs and conformalized regression forests

Regional forecasting is crucial for a balanced energy delivery system and for achieving the global transition to clean energy. However, regional wind forecasting is challenging due to uncertain weather prediction and its high dimensional nature. Most solutions are limited to single-turbine or farm/park forecasting; therefore, this work proposes a day-ahead regional wind power forecasting framework using deep Convolutional Neural Networks (CNN) with context-aware turbine maps and Conformal Quantile Regression (CQR) to generate quantile forecasts with valid coverage.Additionally, this work introduces the use of the Split Conformal Predictive System (SCPS) to generate valid prediction distributions, which has not yet been proposed for wind power forecasting in general. As well as a new method to generate calibrated prediction distributions based on SCPS and Quantile Regression Forests (QRF). This new method, named Split Conformal Distribution Regression Forests (SCDRF), allows for conditional conformal predictive distribution that increases efficiency compared to SCPS while maintaining valid coverage. SCDRF, together with CNNs and context-aware turbine maps, outperforms the existing models on the evaluated dataset, reducing the pinball loss by 5.89% while having more flexibility due to the generation of prediction distributions that can be used to generate any quantile prediction without retraining the model.

A Probabilistic Approach to Turbine Uncertainty

Abstract Efficiency is an essential metric for assessing turbine performance. Modern turbines rely heavily on numerical computational fluid dynamics (CFD) tools for design improvement. With more compact turbines leading to lower aspect ratio airfoils, the influence of secondary flows is significant on performance. Secondary flows and detached flows, in general, remain a challenge for commercial CFD solvers; hence, there is a need for high-fidelity experimental data to tune these solvers used by turbine designers. Efficiency measurements in engine-representative test rigs are challenging for multiple reasons; an inherent problem to any experiment is to remove the effects specific to the turbine rig. This problem is compounded by the narrow uncertainty band required to detect the incremental improvements achieved by turbine designers. Efficiency measurements carried out in engine-representative turbine rigs have traditionally relied upon assumptions such as constant gas properties and neglecting heat loss. This research presents an uncertainty framework that combines inputs from experiments and computational tools. This methodology allows quantifying uncertainty for high-fidelity efficiency data in engine-representative turbine facilities. This paper presents probabilistic sampling techniques to allow for uncertainty propagation. The effect of rig-specific effects, such as heat transfer and gas properties, on efficiency is demonstrated. Sources of uncertainty are identified, and a framework is presented which divides the sources into bias and stochastic. The framework allows the combination of experimental and numerical uncertainty. Gaussian regression models are developed to obtain speed-lines for the turbine map using the uncertainty of the measured efficiency.

A Surge/Stall-Capable Dynamic Performance Simulation Methodology for a Turbojet Engine

Abstract A lumped-parameter dynamic performance model for a single-spool turbojet engine is presented in this paper. This model can handle pre and poststall transients under forward and reverse-flow conditions. The inter-component volume technique is employed instead of the standard matching technique to be able to handle high-frequency transients and reverse-flow conditions. Inspired by Greitzer's lumped-parameter surge model, momentum (duct) and volume elements are placed within the flow path to handle surge dynamics. Compressor and turbine maps are extended to low-flow and reverse-flow regions using a combination of the guidelines presented by Kurzke, the cubic axisymmetric characteristics of Moore and Greitzer, and a quadratic function guess for in-stall characteristics. Combustor efficiency, stability limits, and delay are taken from the literature. Poststall behavior of the model is validated using the data available in the literature for a Rolls-Royce Viper engine. A good match is observed with a correct prediction of poststall behaviors, which transition from surge after locked stall to multiple surge cycles around 80% speed and multiple surge cycles to surge after flameout around 95% speed. The effects of different modeling choices and modeling parameters on the obtained results are discussed. The produced model can be calibrated for a specific engine with surge tests, and it can be used for hard-to-test scenarios like surge after shaft breakage. Different surge/stall-causing events, such as fuel spiking, in-bleeding, and shaft breakage, are simulated to see the capabilities of the model.

Off-design performance of micro-scale solar Brayton cycle

A novel methodology to design a micro-scale, solar-only, air-breathing, open Brayton cycle and assess its on- and off-design performance. The methodology is applied to generate and assess six thermodynamic layouts over a range of solar irradiation levels. All plants have the same on-design requirements to create a baseline to compare their off-design performance. PyCycle, a thermodynamic cycle modeling library to model jet engine performance, is revised to transform the jet engine performance modeling to solar thermal plant performance modeling and used to create a volumetric receiver component. A response surface surrogate model of the receiver is created for design optimization to maximize the component-level efficiency. The compressor and turbine maps are scaled for the balance of the plant. Off-design efficiency, mass flow rate, operation range, turbomachinery maps, and maximum power output are presented. Since the methodology can be adapted to all plant sizes, the results are normalized to on-design condition. The outcome of this study demonstrates the impact of the thermodynamic configuration on off-design performance and provides a methodology to design plants that are more robust across a range of solar irradiation levels and can be operated in a more flexible manner. Compared to single shaft configuration, solar radiation operation range is improved by 5%, with 6% less mass flow, and operates more efficiently than the benchmark case over 85% of the operating regime.

Starting and windmilling simulations using compressor and turbine maps

Starting and windmilling simulations with a normal gas turbine performance program require extended compressor and turbine maps which include sub-idle corrected speeds down to say 5–10% of the design value. During such simulations certain specific phenomena which are insignificant in the normal operating range between idle and full power must be considered. For example, while starting a low bypass ratio mixed flow turbofan, flow reversal in the bypass duct can occur. This paper illustrates a general understanding of what happens from when the starter is activated to when stabilized idle operation is reached. Operating lines in the compressor and turbine maps are predicted depending on starter torque, starter power, burner light-up and starter cut-off speed. It is explained why knowing combustor efficiency precisely is not required for that. Simulating engine starting and windmilling is not a magical art. The laws of physics still apply at these somewhat exotic operating conditions.

Assessment of the impact of the number and the arrangement of cylinders of the KAMAZ disel engines on their fuel efficiency

Most of the natural aspirated truck diesel engines had an eight-cylinder V-twin (V8) configuration. Modern turbocharged diesel engines have a six-cylinder in-line configuration (L6), although some V8 diesel engines continue to be produced. A comparison was made of the performance of the KAMAZ-740 (V8) diesel engine with two turbochargers and KAMAZ-910 (L6) diesel engines with one turbocharger, having almost the same displacement with the same pattern of torque along the full load characteristic. The AVL BOOST software and experimental compressor and turbine maps were used. The factors influencing fuel efficiency were analyzed: indicated efficiency, friction and gas exchange losses, turbocharger efficiency. The L6 diesel engine had a uniform pressure pulsation in the exhaust manifold and at the turbine inlet. In the V8 diesel engine, the pulsations were uneven and had higher amplitude, which led to higher gas exchange losses and a decrease in turbine efficiency. The L6 diesel engine had a higher indicated efficiency but also higher friction losses. On average, the brake specific fuel consumption of the L6 diesel engine was by 5.5 % lower than that of the V8 diesel engine. Keywords V8 and P6 diesel engines; modeling in AVL BOOST; pressure pulsations in the exhaust system; turbocharger efficiency; friction and gas exchange losses

Analysis of Measured and Predicted Turbine Maps From Start-Up to Design Point

Abstract This paper describes a coupled experimental and computational fluid dynamics (CFD) campaign conducted on a 1.5 intermediate turbine stage in the full range of operating conditions, from start-up to design point under variable expansion ratio and physical speed. The test maintains engine similitude conditions and allows direct comparison with CFD data to assess the predictions accuracy. The choice of variables to describe the speedlines is also addressed by using both measured and predicted data. A discussion on velocity ratio versus corrected speed illustrates the advantages of the former parameter the adoption of which produces constant shape curves in a very wide range of operating conditions. The comparison between measurements and predictions suggests that CFD, in conjunction with performance correlations, is a viable tool to predict speedlines in a fairly wide range of conditions, provided that geometrical and operational details are carefully matched.

Experimental Methods for Evaluating Components of Turbomachinery, for Use in Automotive Fuel Cell Applications

This paper describes methods and test beds for components of turbomachinery, for use in automotive fuel cell applications at the Ostfalia University of applied sciences. Turbomachinery for use in fuel cell applications is subject to different requirements than those of conventional turbochargers. Therefore, the turbine and the air bearings of an electrical turbocharger will be subject to evaluation. The different boundary conditions in comparison to conventional turbochargers, with less heat and high humidity from the fuel cell, are especially of interest. Air bearings affect the friction and the vibrations/oscillations of the shaft. The methods and test beds need to fulfill the requirements of these types of turbomachinery. The friction test bed is modified with a new coupling solution, to ensure that the driving electric motor in combination with the shaft of the test component complies with the strict tolerances. For this, a magnetic coupling, for use in high-speed applications, is developed and tested on the friction test bed. The fuel cell turbine was adapted to the hot gas test bed and extended turbine maps are determined. To reach high humidity conditions of a fuel cell application, a water injection system is integrated into the test bed.

Optimization and off-design calculations of a turbojet engine using the hybrid ant colony – particle swarm optimization method

PurposeThe purpose of the paper is to present component matching and off-design calculations using generic components maps.Design/methodology/approachMulti objective hybrid optimization code is integrated with turbojet function code. Both codes are developed for the research study. Initially, methodology is applied on a numerical propulsion system simulation (NPSS) example engine cycle calculations. Effect of matching constants are shown. Later, component matching and application is done on JetCat engine. Calculations are compared with measured test data. And additional operating conditions are calculated using the matched component constants.FindingsObtained matching constants provided very good results with NPSS example and also JetCat test measurements. Optimization algorithm is practical for turbojet engine component matching and off-design calculations. Off-design matching provides information about the turbine and exhaust areas of an unknown turbine engine. Thus it is possible to perform off design calculations at various operating conditions. Finding detailed turbine maps is difficult than finding compressor maps. In that case characteristic turbine curve may be a good alternative.Research limitations/implicationsSelected component maps and the target engine components should be similar characteristics. For a one/two stage turbine, characteristic curves can be applied. Validation should be extended on different type of compressor and turbines.Practical implicationsOperators and researchers usually need more information about the available turbojet engines for increasing the effective usage. Generally, manufacturers do not provide such detailed information to public. This study introduces an alternative methodology for engine modeling by using generic component maps and thus obtaining information for off-design calculations. User is flexible for selecting/scaling the compressor and turbine maps.Originality/valueA hybrid optimization code is used as a new approach. It can be used with other engine functions; for instance functions corresponding to turboshaft or turbofan engines, by modifying the engine function. Number of input parameters and objective functions can be modified accordingly.

Model-based dynamic performance simulation of a microturbine

Microturbines can be used not only in models and education but also to propel UAVs. However, their wider adoption is limited by their relatively low efficiency and durability. Validated simulation models are required to monitor their performance, improve their lifetime, and design engine control systems. The aim of this study is to develop a numerical model of a micro gas turbine for engine performance predictions and prognostics. To build a reliable zero-dimensional model, the available compressor and turbine maps were scaled to available test bench data with the least-squares method, to meet the performance of the engine achieved during bench and flight tests. A steady-state aeroengine model was then developed and compared with experimental operating points. Selected flight data were then used as input for the transient engine model. The EGT temperature and the fuel flow were chosen as the two key parameters to validate the model, comparing the numerical predicted values with the correspondent experimental ones. The observed difference between the model and flight data was lower than 3% for both EGT and fuel flow.

Model-Based Dynamic Performance Simulation of a Microturbine Using Flight Test Data

Microturbines can be used not only in models and education but also to propel UAVs. However, their wider adoption is limited by their relatively low efficiency and durability. Validated simulation models are required to monitor their performance, improve their lifetime, and to design engine control systems. This study aims at developing a numerical model of a micro gas turbine intended for prediction and prognostics of engine performance. To build a reliable zero-dimensional model, the available compressor and turbine maps were scaled to the available test bench data with the least squares method, to meet the performance of the engine achieved during bench and flight tests. A steady-state aeroengine model was implemented in the Gas turbine Simulation Program (GSP) and was compared with experimental operating points. The selected flight data were then used as input for the transient engine model. The exhaust gas temperature (EGT) and fuel flow were chosen as the two key parameters to validate the model, comparing the numerical predicted values with the experimental ones. The observed difference between the model and the flight data was lower than 3% for both EGT and fuel flow.

Roadmap to Profitability for a Speed-Controlled Micro-Hydro Storage System Using Pumps as Turbines

Storage technologies are an emerging element in the further expansion of renewable energy generation. A decentralized micro-pumped storage power plant can reduce the load on the grid and contribute to the expansion of renewable energies. This paper establishes favorable boundary conditions for the economic operation of a micro-pump storage (MPS) system. The evaluation is performed by means of a custom-built simulation model based on pump and turbine maps which are either given by the manufacturer, calculated according to rules established in studies, or extended using similarity laws. Among other criteria, the technical and economic characteristics regarding micro-pump storage using 11 pumps as turbines controlled by a frequency converter for various generation and load scenarios are evaluated. The economical concept is based on a small company (e.g., a dairy farmer) reducing its electricity consumption from the grid by storing the electricity generated by a photovoltaic system in an MPS using a pump as a turbine. The results show that due to the high specific costs incurred, systems with a nominal output in excess of around 22 kW and with heads beyond approximately 70 m are the most profitable. In the most economical case, a levelized cost of electricity (LCOE) of 29.2 €cents/kWh and total storage efficiency of 42.0% is achieved by optimizing the system for the highest profitability.

Performance of a microjet using component map scaling

PurposeThis paper aims to investigate the cycle performance of a small size turbojet engine used in unmanned aerial vehicles at 0–5,000 m altitude and 0–0.8 Mach flight speeds with real component maps.Design/methodology/approachThe engine performance calculations were performed for both on-design and off-design conditions through an in-house code generated for simulating the performance of turbojet engines at different flight regimes. These calculations rely on input parameters in which fuel composition are obtained through laboratory elemental analysis.FindingsExemplarily, according to comparative results between in-house developed performance code and commercially available software, there is 0.25% of the difference in thrust value at on-design conditions.Practical implicationsOnce the on-design performance parameters and fluid properties were determined, the off-design operation calculations were performed based on the compressor and turbine maps and scaling methodology. This method enables predicting component maps and fitting them to real conditions.Originality/valueA method to be used easily by researchers on turbojet engine performance calculations which best fits to real conditions.

An Integrated Turbocharger Matching Program for Internal ‎Combustion Engines

Following the global environmental concerns, many automobile manufacturers intend to produce smaller ‎engines, aiming to lower emissions and fuel consumption. As compensation for performance reduction, these ‎engines are equipped with turbochargers. One of the challenges is to select the right turbocharger for a specific ‎engine. In this regard, an integrated zero-dimensional turbocharger and engine simulation program is ‎developed, employing a quasi-steady compressible flow method. The program gives the designer the ‎possibility of observing the performance of different compressor-turbine combinations on an internal ‎combustion engine. Engine details such as fuel, cylinder geometry, heat transfer conditions, valve timing, and ‎spark timing are considered within the engine modeling, and the designer can investigate their effects on the ‎overall performance of the system. Compressor and turbine performances are predicted by their previously ‎provided performance maps (steady-state characteristic curves) and special inter- and extrapolation methods. ‎A new algorithm for turbocharger matching is suggested, and its logics, basic convergence loops, and ‎thermodynamic equations have been described in detail. A database containing digitized compressor and ‎turbine maps and details provided by different manufacturers is created and integrated into the program. An ‎existing turbocharged engine has been tested and also simulated by the program. The accuracy of the program ‎results is evaluated by comparing them with experimental results. The maximum error of modeling the engine ‎and the whole simulation is 1.5% and 16%, respectively. Two other compressor-turbine combinations have ‎been evaluated using the program, one of which is suggested as an alternative‎‎.

Evaluation of a Double-Entry Turbine Model Coupled With a One-Dimensional Calibrated Engine Model at Engine Full Load Curves

Turbocharging is one of the foremost ways of engine downsizing and represents the leading technology for reducing the engine CO2emission standards in gasoline engine application. Turbocharger turbine always faces high unsteadiness of flow coming from the reciprocating internal combustion engines. Besides, increasing levels of engine downsizing include rising degrees of pulse charging. Utilization of pulse energy in the engine exhaust and reducing the interferences between the cylinders using the double-entry turbines is a vital element in solving the low-end-torque targets and improving rated power in highly boosted four-cylinder engines. The present paper describes a model of double-entry turbines. The model’ aim is to accommodate an efficient boundary condition to turbocharged engine models with zero and one-dimensional gas dynamic codes. The model is based on the simple procedure of testing and systematizing the performance maps of these turbines with different flow admission conditions. However, the described model in the present paper is capable of extrapolating operating conditions that differ from those included in the turbine maps because a turbocharger turbine with an engine usually works instantaneously and away from the narrow range of data that are measured in the gas stand. The described model has been implemented in a one-dimensional gas dynamic code and has been used to calculate unsteady operating conditions coming from the engine. The results obtained from the whole engine simulation show that the model can produce all the full load engine variables such as air mass flow and brake torque in a reasonable degree of agreement with the experimental data that are obtained from the engine test bench.

A strategy for the robust forecasting of gas turbine health subjected to fouling

Fouling represents a major problem for Gas Turbines (GTs) in both heavy-duty and aero-propulsion applications. Solid particles entering the engine can stick to the internal surfaces and form deposits. Components' lifetime and performance can dramatically vary as a consequence of this phenomenon. These effects impact the whole engine in terms of residual life, operating stability, and maintenance costs. In the High-Pressure Turbine (HPT), in particular, the high temperatures soft the particles and promote their adhesion, especially in the short term. Unfortunately, predicting the GT response to this detrimental issue is still an open problem for scientists. Furthermore, the stochastic variations of the components operating conditions increase the uncertainty of the forecasting results. In this work, a strategy to predict the effects of turbine fouling on the whole engine is proposed. A stationary Gas Path Analysis (GPA) has been performed for this scope to predict the GT health parameters. Their alteration as a consequence of fouling has been evaluated by scaling the turbine map. The scaling factor has been found by performing Computational Fluid Dynamic (CFD) simulations of a HPT nozzle with particle injection. Being its operating conditions strongly uncertain, a stochastic analysis has been conducted. The uncertainty sources considered are the circumferential hot core location and the turbulence level at the inlet. The study enables to build of confidence intervals on the GT health parameters predictions and represents a step forward towards a robust forecasting tool.

Effects of Turbocharger Rotation Inertia on Instantaneous Turbine Efficiency in a Turbocharged-Gasoline Direct Injection (T-GDI) Engine

Abstract The effects of turbocharger rotation inertia on instantaneous turbine efficiency were analyzed in a 2.0 L four-cylinder twin-scroll turbocharged gasoline direct injection (T-GDI) engine. Two turbochargers of different weights were prepared for comparison purposes: base T/C and light T/C. In order to evaluate the instantaneous efficiency of each turbocharger, a combination of engine tests and a 1D simulation was conducted. In the experiments, the instantaneous exhaust gas pressures, upstream and downstream of the turbine, were measured. The instantaneous turbocharger rotation speed was also measured. The instantaneous temperature and mass flow rate of the exhaust gas were taken from the 1D simulation results. Through a combination of measuring and simulating exhaust gas states for the turbines, the instantaneous turbine blade speed ratio (BSR), total-to-static turbine efficiency (ηts), reduced mass flow rate (φ), and reduced turbine speed (Nred) were calculated. The light T/C showed higher fluctuations in the instantaneous turbine rotation speed compared to the base T/C. This greater response from the light T/C is due to experiencing less inertia loss, this leads to higher fluctuations in the instantaneous Nred, BSR, ηts, and φ. As a result, the light T/C shows higher turbine efficiency at certain points after the start of the exhaust gas pulse cycle. This is because the greater response of the light T/C lead the operating conditions of the turbine to more efficient regions in the turbine map.