The progressive reduction of authorized emission levels in automotive Diesel engine standards has motivated the development of numerous technologies (exhaust gas recirculation (EGR), high pressure injection systems, sophisticated boosting systems, after-treatment devices, etc.) which, in turn, drastically increases the complexity of engine calibration. In this context the development of reliable simulation tools can help reduce the cost and time required for calibration. After a short introduction analysing the main currently existing models for evaluating engine emissions, this paper presents a novel 0D semi-physical model to assess engine-out NO_x and soot emissions. The combustion process is modelled via Barba’s approach, while a thermodynamic two-zone calculation is used to evaluate adiabatic flame temperature. Emissions are modelled with semi-physical sub-models. This rather original approach does not evaluate emission on a crank-angle basis but only at exhaust valve opening (EVO), thus saving calculation time. The main physical parameters influencing pollutant formation are evaluated by the high-frequency 0D model and used as inputs for pollutant sub-models. NO_x evaluation relies on a cartography linking NO_x to O₂ concentration and maximum values of in-cylinder bulk temperature and adiabatic flame temperature. Soot evaluation relies on a global equation, linking soot concentration to the main factors influencing formation and oxidation processes, in particular O₂ concentration, in-cylinder pressure, temperatures and durations of some specific phases of the heat release rate (HRR), as well as turbulence intensity. The calibration of the models is thus quite easy and is described in the paper. The results of the models are then compared with measurements (different from those used for model calibration). NO_x predictions are within ±20% of measured values for 95% of the tested operating points, with a R² of 0.99, while for soot prediction a R² coefficient of 0.93 is obtained and 96% of the tested points are within ±0.005 mg/cycle. Moreover, engine parameters sweeps (at constant engine speed and load) involving EGR rate, boost pressure, injection pressure and timing are performed for five operating points. The agreement with experiments is good on both qualitative and quantitative points of view, as long as a conventional combustion mode is achieved. Although simple and fast, these models are not only able to interpolate between the training points but also to extrapolate with a reasonable accuracy when the engine calibration parameters are changed. This latter property is rarely demonstrated in existing models.

汽车柴油发动机标准中许可排放水平的逐步降低促使许多技术（排气再循环（EGR），高压喷射系统，复杂的增压系统，后处理装置等）的发展，这些技术反过来又大幅度地发展了增加了发动机标定的复杂性。在这种情况下，可靠的仿真工具的开发可以帮助减少校准所需的成本和时间。在简短介绍了目前评估发动机排放的主要模型之后，本文提出了一种新颖的0D半物理模型来评估发动机排放的NO _x和烟尘排放。燃烧过程通过Barba方法建模，而热力学两区计算用于评估绝热火焰温度。用半物理子模型对排放进行建模。这种相当原始的方法不基于曲柄角评估排放，而仅评估排气门开度（EVO），从而节省了计算时间。通过高频0D模型评估影响污染物形成的主要物理参数，并将其用作污染物子模型的输入。NO _x评估依赖于将NO _x与O ₂链接的制图缸内体温和绝热火焰温度的浓度和最大值。烟灰评估依赖于一个全局方程，将烟灰浓度与影响形成和氧化过程的主要因素联系在一起，特别是O ₂浓度，缸内压力，温度和放热率（HRR）某些特定阶段的持续时间，以及作为湍流强度。因此，模型的校准非常容易，并在本文中进行了介绍。然后将模型的结果与测量结果进行比较（与用于模型校准的结果不同）。对于95％的测试工作点，NO _x预测值在测量值的±20％以内，R ²为0.99，而对于烟灰预测，R ²获得0.93的系数，并且96％的测试点在±0.005 mg /循环内。此外，针对五个工作点执行了涉及EGR率，增压压力，喷射压力和正时的发动机参数扫描（在恒定的发动机转速和负载下）。只要可以实现常规燃烧模式，从定性和定量的角度来看，与实验的一致性都很好。尽管简单快速，但是这些模型不仅能够在训练点之间进行插值，而且还可以在更改发动机校准参数时以合理的精度进行插值。后一种属性很少在现有模型中得到证明。