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Data maps are easy to put in place and require very low calculation time. As a consequence they are often valued over fully physic-based models. This is particularly true when it is question of turbochargers. However, even if these maps are directly provided by the manufacturer, they usually do not cover the entire engine operating range and are poorly discretized. That's why before implementing them into any model they need to be interpolated and extrapolated. This paper introduces a new interpolation/extrapolation method based on the idea of integrating more physics into the widespread Jensen and Kristensen's method [6]. It essentially relies on the turbo machinery equation analysis performed by Martin during his PhD thesis [9, 10, 11] and the interpolation and extrapolation strategies that he proposed. In most cases the new strategies presented in this paper rely on improvements of the models he proposed.

This paper presents a new 0D phenomenological approach to predict the combustion process in diesel engines operated under various running conditions. The aim of this work is to develop a physical approach in order to improve the prediction of in-cylinder pressure and heat release. The main contribution of this study is the modeling of the premixed part of the diesel combustion with a further extension of the model for multi-injection strategies. In phenomenological diesel combustion models, the premixed combustion phase is usually modeled by the propagation of a turbulent flame front. However, experimental studies have shown that this phase of diesel combustion is actually a rapid combustion of part of the fuel injected and mixed with the surrounding gas. This mixture burns quasi instantaneously when favorable thermodynamic conditions are locally reached. A chemical process then controls this combustion.

Model-based tuning is a way followed by car manufacturers to reduce development costs. In this context, a new methodology has been developed in order to adapt a tur-bocharged diesel engine in the case of non-standard external conditions. Indeed, variable geometry turbine and fuel injection command laws are developed for standard conditions (20°C, altitude=0m). Turbocharger and fuel injection actuators pre-positioning maps should be adjusted regarding the inducted air mass density (influenced by the external temperature and pressure), in order to meet thermal, mechanical and pollutant emissions constraints. In order to reduce the use of climatic tests bench and extreme conditions tests in foreign countries, a model of a turbocharged diesel engine coupled to an optimization loop has been used to take into account the effect of non-standard external conditions on pre-positioning maps.

A convenient way of modelling turbochargers is based on data maps. These models are easy to put into place, require low CPU charge and are control-oriented. Data relative to compressor and turbine are read from tables: pressure ratio and efficiency are determined as functions of mass flow rate and rotary speed on two distinct data maps. Nevertheless, this type of model has drawbacks: Usually, only higher turbocharger speed data are mapped (> 90000 rpm) although the low rpm zone is the most useful zone for normalized driving cycles simulations. Moreover, maps are poorly discretized, leading to the use of specific extra-interpolation methods (many are identified in [5]). These methods are purely mathematical, which gives inaccurate results in extrapolation zones. Relation between pressure ratio and efficiency is then broken (i.e., if one implements a pumping model for the compressor, the pressure ratio will be affected, but not the efficiency).