The sensitivity of transient response prediction of a turbocharged diesel engine to turbine map extrapolation

Mandated pollutant emission levels are shifting light-duty vehicles towards hybrid and electric powertrains. Heavy-duty applications, on the other hand, will continue to rely on internal combustion engines for the foreseeable future. Hence there remain clear environmental and economic reasons to further decrease IC engine emissions. Turbocharged diesels are the mainstay prime mover for heavy-duty vehicles and industrial machines, and transient performance is integral to maximizing productivity, while minimizing work cycle fuel consumption and CO2 emissions. 1D engine simulation tools are commonplace for "virtual" performance development, saving time and cost, and enabling product and emissions legislation cycles to be met. A known limitation however, is the predictive capability of the turbocharger turbine sub-model in these tools. One specific concern is accurate extrapolation of turbine performance beyond the narrow region populated by supplier-measured data to simulate non-steady conditions, be it either to capture pulsating exhaust flow or, as is the focus here, engine transient events. Extrapolation may be achieved mathematically or by using physics-based correlations, sometimes in combination. Often these extrapolation rules are the result of experience. Due to air system dynamic imbalance, engine transients force instantaneous turbine mass flow and pressure ratio into regions well away from the hot gas bench test data, necessitating great trust in the extrapolation routine. In this study, a 1D heavy-duty turbocharged diesel engine model was used to simulate four transient events, employing a series of performance maps representing the same turbine but with increasing levels of extrapolation, using commonly-adopted methodologies. The comparison was enabled by measuring real turbine performance on the dynamometer at Imperial College London. This testing generated a wide baseline dataset which was used to produce corresponding transient response predictions, and against which cases of increasing degrees of extrapolation could be compared. This paper studies the sensitivity of response time to the degree and technique of the extrapolation applied, demonstrating its importance for reliable transient engine simulations

Non-adiabatic pressure loss boundary condition for modelling turbocharger turbine pulsating flow

This paper presents a simplified methodology of pulse flow turbine modelling, as an alternative over the meanline integrated methodology outlined in previous work, in order to make its application to engine cycle simulation codes much more straight forward. This is enabled through the development of a bespoke non-adiabatic pressure loss boundary to represent the turbine rotor. In this paper, turbocharger turbine pulse flow performance predictions are presented along with a comparison of computation duration against the previously established integrated meanline method. Plots of prediction deviation indicate that the mass flow rate and actual power predictions from both methods are highly comparable and are reasonably close to experimental data. However, the new boundary condition required significantly lower computational time and rotor geometrical inputs. In addition, the pressure wave propagation in this simplified unsteady turbine model at different pulse frequencies has also been found to be in agreement with data from the literature, thereby supporting the confidence in its ability to simulate the wave action encountered in turbine pulse flow operation

Radial turbine sound and noise characterisation with acoustic transfer matrices by means of fast one-dimensional models

This is the author's version of a work that was accepted for publication in International Journal of Engine Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published as https://doi.org/10.1177/1468087419889429.[EN] Estimating correctly the turbine acoustics can be valuable during the engine design stage; in fact, it can lead to a more optimised design of the silencer and aftertreatment, as well as to better prediction of the scavenging effects. However, obtaining the sound and noise emissions of radial turbocharger turbines with low computational costs can be challenging. To consider these effects in a time-efficient manner, the acoustic response of single-entry radial turbines can be characterised by means of acoustic transfer matrices that change with the operating conditions. Exploiting the different time-scales of the acoustic phenomena and the change in the operating point of the turbine, lookup tables of acoustic transfer matrices can be computed. Then, the obtained characterisation can be used in mean-value engine models. This article presents a method for generating these lookup tables by means of fast one-dimensional simulations of thoroughly validated fidelity, in terms of both acoustics and extrapolation capabilities. Due to the inherent behaviour of radial turbines, the number of computations needed to fill the lookup tables is relatively small, so the method can be used as a simple preprocessing phase before mean-value simulation campaigns.Torregrosa, AJ.; García-Cuevas González, LM.; Inhestern, LB.; Soler-Blanco, P. (2021). 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A flow and loading coefficient-based compressor map interpolation technique for improved accuracy of turbocharged engine simulations

Internal combustion engines are routinely developed using 1D engine simulation tools. A well-known limitation is the accuracy of the turbocharger compressor and turbine sub-models, which rely on hot gas bench-measured maps to characterize performance. Such discrete map data is inherently too sparse to be used directly in simulation, and so a preprocessing algorithm interpolates and extrapolates the data to generate a wider, more densely populated map. Methods used for compressor map interpolation vary. They may be mathematical or physical in nature, but there is no unified approach, except that they typically operate on input map data in SAE format. For decades it has been common practice for turbocharger suppliers to share performance data with engine OEMs in this form. This paper describes a compressor map interpolation technique based on the nondimensional compressor flow and loading coefficients, instead of SAE-format data. It compares the difference in compressor operating point prediction accuracy when using this method against the standard approach employing dimensional parameters. This is done by removing a speed line from a dataset, interpolating for the removed speed using the two methods, and comparing their accuracy to the original data. Three maps corresponding to compressor diameters of 54, 88, and 108 mm were evaluated. In some cases, the residual sum of squares between the interpolated and original data demonstrated an order of magnitude improvement when using the nondimensional coefficients. When evaluated in a simple engine model, this manifests as a slight shift in interpolated turbocharger speed, resulting in a difference in predicted compressor efficiency of up to 0.89 percentage points. This paper shows how the use of truly nondimensional interpolation techniques can improve the accuracy of processed turbocharger compressor maps, and consequently the value of 1D engine simulations as a reliable performance development tool, at virtually no additional effort or cost

Design methodology for radial turbo expanders in mobile organic Rankine cycle applications

Future vehicles for clean transport will require new powertrain technologies to further reduce CO2 emissions. Mobile organic Rankine cycle systems target the recovery of waste heat in internal combustion engines, with the exhaust system identified as a prime source. This article presents a design methodology and working fluid selection for radial turbo expanders in a heavy-duty off-road diesel engine application. Siloxanes and Toluene are explored as the candidate working fluids, with the latter identified as the preferred option, before describing three radial turbine designs in detail. A small 15.5. kW turbine design leads to impractical blade geometry, but a medium 34.1. kW turbine, designed for minimum power, is predicted to achieve an isentropic efficiency of 51.5% at a rotational speed of 91.7. k. min-1. A similar 45.6. kW turbine designed for maximum efficiency yields 56.1% at 71.5. k. min-1. This emphasizes the main design trade-off - efficiency decreases and rotational speed increases as the power requirement falls - but shows reasonable radial turbine efficiencies and thus practical turbo expanders for mobile organic Rankine cycle applications are realizable, even considering the compromised flow geometry and high speeds imposed at such small scales

Adaptive turbo matching: radial turbine design optimization through 1D engine simulations with meanline model in-the-loop

Turbocharging has become the favored approach for downsizing internal combustion engines to reduce fuel consumption and CO 2 emissions, without sacrificing performance. Matching a turbocharger to an engine requires a balance of various design variables in order to meet the desired performance. Once an initial selection of potential compressor and turbine options is made, corresponding performance maps are evaluated in 1D engine cycle simulations to down-select the best combination. This is the conventional matching procedure used in industry and is passive' since it relies on measured maps, thus only existing designs may be evaluated. In other words, turbine characteristics cannot be changed during matching so as to explore the effect of design adjustments. Instead, this paper presents an adaptive' matching methodology for the turbocharger turbine. By coupling an engine cycle simulation to a turbine meanline model (in-the-loop'), adjustments in turbine geometry are reflected in both the exhaust boundary conditions and overall engine performance. Running the coupled engine-turbine model within an optimization framework, the optimal turbine design evolves. The methodology is applied to a Renault 1.2 L turbocharged gasoline engine, to minimize fuel consumption over given full- and part-load operating points, while meeting performance constraints. Despite the current series production turbine being a very good match already, and with optimization restricted to a few turbine geometric parameters, the full-load case predicted a significant cycle-averaged BSFC reduction of 3.5 g/kWh, while the part-load optimized design improved BSFC by 0.9 g/kWh. No engine design parameters were changed, so further efficiency gains would be possible through simultaneous engine-turbocharger optimization. The proposed methodology is not only useful for improving existing designs; it can also develop a bespoke turbine geometry in new engine projects where there is no previously available match. For these reasons, adaptive' turbo matching will become the standard approach in the automotive industry

One-dimensional pulse-flow modeling of a twin-scroll turbine

This paper presents a revised one-dimensional (1D) pulse flow modeling of twin-scroll turbocharger turbine under pulse flow operating conditions. The proposed methodology in this paper provides further consideration for the turbine partial admission performance during model characterization. This gives rise to significant improvement on the model pulse flow prediction quality compared to the previous model. The results show that a twin-scroll turbine is not operating at full admission throughout the in-phase pulse flow conditions. Instead, they are operating at unequal admission state due to disparity in the magnitude of turbine inlet flow. On the other hand, during out-of-phase pulse flow, a twin-scroll turbine is working at partial admission state for majority of the pulse cycle. An amended mathematical correlation in calculating the twin-scroll turbine partial admission characteristics is also presented in the paper. The impact of its accuracy on the pulse flow model prediction is explored

Multi-objective optimization of turbocharger turbines for low carbon vehicles using meanline and neural network models

Due to slow turnover of the global vehicle parc internal combustion engines will remain a primary means of motive power for decades, so the automotive industry must continue to improve engine thermal efficiency to reduce emissions, since savings will be compounded over the long lifetime of millions of vehicles. Turbochargers are a proven efficiency technology (most new vehicles are turbocharged) but are not optimally designed for real-world driving. The aim of this study was to develop a framework to optimize turbocharger turbine design for competing customer objectives: minimizing fuel consumption (and thus emissions) over a representative drive cycle, while minimizing transient response time. This is achieved by coupling engine cycle, turbine meanline, and neural network inertia models within a genetic algorithm-based optimizer, allowing aerodynamic and inertia changes to be accurately reflected in drive cycle fuel consumption and transient performance. Exercising the framework for the average new passenger car across a drive cycle representing the Worldwide harmonized Light vehicles Test Procedure reveals the trade-off between competing objectives and a turbine design that maintains transient response while minimizing fuel consumption due to a 3 percentage-point improvement in turbine peak efficiency, validated by experiment. This optimization framework is fast to execute, requiring only eight turbine geometric parameters, making it a commercially viable procedure that can refine existing or optimize tailor-made turbines for any turbocharged application (whether gasoline, diesel, or alternatively fuelled), but if applied to turbocharged gasoline cars in the EU would lead to lifetime savings of 290,000 tonnes per production year, and millions of tonnes if deployed worldwide