Physical-Based Algorithms for Interpolation and Extrapolation of Turbocharger Data Maps

Hadef, Jamil El; Colin, Guillaume; Chamaillard, Yann; Talon, Vincent

doi:10.4271/2012-01-0434

Cited by 41 publications

(32 citation statements)

References 13 publications

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“…Usually, for calculation time considerations, it relies on extrapolated manufacturer's data maps. The goal of this study is to confirm that new physics-based extrapolation algorithms (El Hadef et al, (2012)) implemented in classical zero dimension engine models (usually implemented using commercial software or in any programming language) lead to accurate results, without increasing the calibration effort. The results for two different models are presented in this paper: first, a reference simulator implemented using the commercial software LMS AMESim, then, a Matlab code designed to be embedded in a control law.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

New Physics-Based Turbocharger Data-Maps Extrapolation Algorithms: Validation on a Spark-Ignited Engine

Hadef

Colin²,

Talon³

et al. 2012

IFAC Proceedings Volumes

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Objectives in terms of pollutant emissions and fuel consumption reduction, as well as development costs and time to market reduction, has led car manufacturers to use more and more system simulation. However, among all the fields in which it has enabled to achieve these goals, the control development stage is one of those, in which major improvements can still be achieved. In this context and with the increasing penetration of downsized engines, turbocharger modeling has become one of the biggest challenges in engine simulation. This paper focuses on the validation of compressor and turbine data maps, extrapolated using new physics-based extrapolation algorithms. The study led to excellent prediction performances for two classical control-oriented models. Conclusions stresses: 1-The improvement of the extrapolation robustness, in particular in the low turbocharger rotational speeds zone. 2-The possibility to keep a low calculation time as well as maintaining the same calibration effort.

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Section: Introductionmentioning

confidence: 99%

“…These data-maps are extrapolated from manufacturer's steady state data points. An innovative physical-based extrapolation strategy has been developed and is presented in section 5 (El Hadef et al, (2012)). …”

Section: Air Path Calibrationmentioning

confidence: 99%

New Physics-Based Turbocharger Data-Maps Extrapolation Algorithms: Validation on a Spark-Ignited Engine

Hadef

Colin²,

Talon³

et al. 2012

IFAC Proceedings Volumes

View full text Add to dashboard Cite

show abstract

“…However, the optimization of turbocharging system control is very difficult, especially for turbochargers working over a wide operating range and coupled to engines with a reduced number of cylinders. The first issue to be addressed is the fact that maps provided by the turbocharger manufacturer usually do not cover the lowest rotational speeds, that become predominant in normalized driving cycles [2]. In addition, the most important limit to be taken into account is the lack of information on turbocharger unsteady flow performance, since only steady flow maps are usually available for both compressor and turbine [3].…”

Section: Introductionmentioning

confidence: 99%

Non-Intrusive Methodology for Estimation of Speed Fluctuations in Automotive Turbochargers under Unsteady Flow Conditions

Ponti¹,

Ravaglioli²,

Corti³

et al. 2014

SAE Int. J. Engines

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The optimization of turbocharging systems for automotive applications has become crucial in order to increase engine performance and meet the requirements for pollutant emissions and fuel consumption reduction. Unfortunately, performing an optimal turbocharging system control is very difficult, mainly due to the fact that the flow through compressor and turbine is highly unsteady, while only steady flow maps are usually provided by the manufacturer. For these reasons, one of the most important quantities to be used onboard for optimal turbocharger system control is the rotational speed fluctuation, since it provides information both on turbocharger operating point and on the energy of the unsteady flow in the intake and exhaust circuits.This work presents a methodology that allows determining the instantaneous turbocharger rotational speed through a proper frequency processing of the signal coming from one accelerometer mounted on the turbocharger compressor. Consequently, the developed algorithm can be used to determine both rotational speed mean value and the amplitude of speed fluctuations that are caused by unsteady flows. From this last evaluated quantity, it is also possible to obtain an estimation of power delivered by the turbine, that might be used for control and diagnostic purposes.The whole estimation algorithm has been developed and validated for a light duty turbocharged Diesel engine installed in a test cell at the University of Bologna. This paper reports the experimental layout used in this work and the accuracy obtained applying the speed fluctuations estimation procedure to the turbocharged Diesel engine under study.

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“…Watson and Janota [9] and Benson [10] used a constant eff for all conditions, whilst Payri et al [11] allowed for changes in eff with red and PR, deriving a relation in which eff varies exponentially with BSR. Intermediate approaches have been proposed by El Hadef [5,12] and Martin [8], and [13]. In the former cases, a purely numerical model is developed for eff , whose coefficients are fitted polynomial functions with the PR.…”

Section: Background To Turbine Modellingmentioning

confidence: 99%

“…Simulation of typical engine duty cycles therefore still necessitates the extrapolation of the measured performance data, to model the turbine off-design. As will be seen a variety of techniques have been developed to address this problem; some physics-based [5], others numerical [6,7], and some combinations of both [8]. It seems pertinent to expect that different modelling strategies, test rig setups, data integrity and coverage of the measured data, ought to affect predicted cycle-to-cycle engine performance during a transient.…”

Section: Introductionmentioning

confidence: 99%

The Sensitivity of Transient Response Prediction of a Turbocharged Diesel Engine to Turbine Map Extrapolation

Mason

Costall

McDonald

2017

SAE Technical Paper Series

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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.

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Physical-Based Algorithms for Interpolation and Extrapolation of Turbocharger Data Maps

Cited by 41 publications

References 13 publications

New Physics-Based Turbocharger Data-Maps Extrapolation Algorithms: Validation on a Spark-Ignited Engine

New Physics-Based Turbocharger Data-Maps Extrapolation Algorithms: Validation on a Spark-Ignited Engine

Non-Intrusive Methodology for Estimation of Speed Fluctuations in Automotive Turbochargers under Unsteady Flow Conditions

The Sensitivity of Transient Response Prediction of a Turbocharged Diesel Engine to Turbine Map Extrapolation

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