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The use of state-of-the-art model-based calibration tools generate only limited benefits for seamless validation in powertrain calibration due to the often neglected system-level simulation of a closed-loop vehicle environment. This study presents a Hardware-in-the-Loop (HiL)-based virtual calibration approach to establish an accurate virtual calibration platform using physical plant models. It is based on a customisable real-time HiL simulation environment. The use of physical models to predict the behaviour of a complete powertrain makes the HiL test bench particularly suited for Engine Control Unit (ECU) calibration. With the virtual test rig approach, the calibration for the critical extended driving and ambient conditions of the new Real Driving Emissions (RDE) requirements can efficiently be optimised. This technique offers a clear advantage in terms of reducing calibration time and costs.

In this paper, a new physics-based model for the prediction of NOx emissions produced by diesel engines is presented. The aim of this work is to provide a reference model for the validation of control strategies and NOx estimators. The model describes the NOx production in the burned gas zone where the burned gas temperature sub-model is adapted to be generic and tunable. The model consists of three main sub-models for the estimation of the burned gas temperature, the concentration of the species in the burned gases and the NOx formation, respectively. A new model for estimating the burned gas temperature, known to have a strong impact on thermal NOx formation rate, is proposed. The model depends on the intake burned gas ratio and the combustion phasing computed from the cylinder pressure. This model has a limited number of calibration parameters identified so that NOx model output matches with experimental data measured in a four-cylinder, four-stroke, direct-injection diesel engine.

The design and the supervision of hybrid electric vehicles (HEV) are strongly coupled. The mutual influence between the optimal components sizing and the optimal operating points choice makes the problem complex. This was previously exposed in literature for spark ignition (SI) HEV. In this paper, we address the same issue for diesel HEV. In this case, the energy management strategy must take nitrogen oxides (NOx) emissions into account in addition to fuel consumption. This paper presents an optimal supervision strategy and its impact on the electric components sizing. The energy management strategy is based on the equivalent consumption minimization strategy (ECMS) using Pontryagin's minimum principle. It allows an adjustable trade-off between NOx and fuel consumption to be minimized. It was validated experimentally with a hardware-in-the-loop test bed.

Future pollutant emissions legislations are expected to be increasingly stringent. To reduce Nitrogen Oxides (NOx) emissions produced by Diesel engines, advanced combustion technologies - like Low Temperature Combustion (LTC) -, vehicle hybridization and NOx after-treatment systems - such as Selective Catalytic Reduction (SCR) systems - can be considered, leading to a growing demand for NOx models. In this paper, we present a state-of-art of the different existing NOx models, from the black-boxes to the three-dimensional Computational Fluid Dynamics (CFD) codes. A way to classify these models is proposed. The paper also introduces the current applications for each subgroup of models. Then, a black-box and two grey-box NOx models are studied regarding their accuracy and their sensitivity to model inputs. These models are validated for two Diesel engines on steady-state operating points as well as on transient operations. The semi-physical models accurately predict NOx emissions.