Stefano D'AMbrosio

The present paper proposes a novel approach for the estimation of the in-cylinder pressure and heat release in diesel engines from basic testbed measurements (i.e., brake mean effective pressure (BMEP), gross indicated mean effective pressure (IMEP360), peak firing pressure (PFP), crank angle at which 50% of fuel mass has burnt (MFB50) and exhaust gas temperature (T_exh). The method exploits a previously developed low-throughput combustion model, based on the accumulated fuel mass approach, which has been tuned by a genetic algorithm (GA) optimizer. The latter adjusts the main combustion model parameters to minimize an objective function, which depends on the prediction errors of BMEP, IMEP360, PFP, MFB50 and T_exh. Several scenarios were evaluated in which different subsets of the four previous quantities were assumed to be known from experimental activities. The proposed method is particularly useful when in-cylinder pressure traces are unavailable and only basic testbed data exist. The results show that the in-cylinder pressure and heat release profiles are estimated with a high level of accuracy, since the root mean squared error is of the order of 1–2.5 bar and 2–2.7 × 10⁻² kJ, respectively, depending on the considered scenario, while requiring a modest computational effort which is of the order of 3–6 min per test. Moreover, the low-throughput nature of the method makes it straightforward for other researchers to implement and reproduce results on different engines. The approach is also fuel-independent and can be applied to engines running on alternative/zero-carbon fuels, which are currently being extensively studied as potential ways to reduce the environmental impact of internal combustion engines.

The present paper investigates two different strategies for model-based calibration and control of tailpipe nitrogen oxide emissions in a light-duty 3.0 L diesel engine equipped with an aftertreatment system (ATS). The latter includes a diesel oxidation catalyst (DOC), a diesel particulate filter (DPF), and an underfloor selective catalytic reduction (SCR) device, in which the injection of diesel exhaust fluid (DEF), marketed as ‘AdBlue’, is also taken into account. The engine was modeled in the GT-SUITE environment, and a previously developed model-based combustion controller was integrated in the model, which is capable of adjusting the start of injection of the main pulse and the total injected fuel mass, in order to achieve desired targets of engine-out nitrogen oxide emissions (NOx) and brake mean effective pressure (BMEP). First, a model-based calibration strategy consisting of the minimization of an objective function that takes into account fuel consumption and AdBlue injection was developed and assessed by exploring different weight factors. Then, a direct model-based controller of tailpipe nitrogen oxide emissions was designed, which exploits the real-time value of the SCR efficiency to define engine-out NOx emission targets for the combustion controller. Both strategies exploit the model-based combustion controller and were tested through a Model-in-the-Loop (MiL) under steady-state and transient conditions. The advantages in terms of tailpipe NOx emissions, fuel consumption, and AdBlue injection were finally discussed.

This study examines the effects on combustion, engine performance and exhaust pollutant emissions of a modern Euro 6, dual-loop EGR, compression ignition engine running on regular EN590-compliant diesel and hydrotreated vegetable oil (HVO). First, the potential of HVO as a “drop-in” fuel, i.e., without changes to the original, baseline diesel-oriented calibration, was highlighted and compared to regular diesel results. This showed how the use of HVO can reduce engine-out emissions of soot (by up to 67%), HC and CO (by up to 40%), while NO_x levels remain relatively unchanged. Fuel consumption was also reduced, by about 3%, and slightly lower combustion noise levels were detected, too. HVO has a lower viscosity and a higher cetane number than diesel. Since these parameters have a significant impact on mixture formation and the subsequent combustion process, an engine pre-calibrated for regular diesel fuel could not fully exploit the potential of another sustainable fuel. Therefore, the effects of the most influential calibration parameters available on the tested engine platform, i.e., high-pressure and low-pressure EGR, fuel injection pressure, main injection timing, pilot quantity and dwell-time, were analyzed along single-parameter sweeps. The substantial reduction in engine-out soot, HC and CO levels brought about by HVO could give the possibility to implement additional measures to limit NO_x emissions, combustion noise and/or fuel consumption compared to diesel. For example, higher proportion of LP EGR and/or smaller pilot quantity could be exploited with HVO, at low load, to reduce NO_x emissions to a greater extent than diesel, without incurring penalties in terms of incomplete combustion species. Conversely, at higher load, delayed main injection timings and reduced rail pressure could reduce combustion noise without exceeding soot levels of the baseline diesel case.

The contribution of the tire-road slip of traction wheels to the total resistance opposing the motion of a light-duty commercial vehicle has been investigated through the simulation of several homologation and custom driving cycles. The calculation of the contribution of the tire slip losses was based on the estimation of the longitudinal tire slip, by means of Pacejka’s MF5.2 tire model. In this work, the computational steps required to evaluate this contribution were implemented in a previously developed fuel consumption simulation tool. Simulations were performed under several vehicle loading conditions and tire inflation pressures on traction and non-traction wheels, and considering different tire-road adherence conditions, in order to obtain a characterization of the tire slip losses over a wide range of working conditions. An analysis of the results shows that, although the contribution of tire slip losses to the total vehicle energy demand and fuel consumption may be relevant – especially under low-load, low adherence conditions – the sensitivity of the average on-cycle vehicle energy/fuel consumption to changes in the tire inflation pressure is only affected slightly by tire slip losses. Therefore, tire slip losses can be neglected in practice, when the aim of a simulation is to optimize the tire pressure to achieve average vehicle working conditions over a driving cycle.

The paper investigates the effect of tire inflation pressure on the lateral dynamics of a passenger car, and presents a possible control-oriented methodology aimed at adapting tire pressure to the current vehicle loading condition targeting a reference characteristic. Starting from the tire characteristics at several inflation pressure levels, the paper investigates the effect of changing selectively tire pressure on each of the two axles, through theoretical calculation of the curvature gain based on the computation of the derivatives of stability, and compares the obtained sensitivity to the results of a multibody simulation model validated through on-track tests. Finally, the work presents a possible algorithm that could be implemented on-board vehicle ECU to provide, for the current loading condition of the vehicle, a tire pressure combination that targets a specific lateral dynamics characteristic. The algorithm is intended as part of the control logic of an intelligent Central Tire Inflation System (CTIS) able to adjust automatically tire pressure according to the actual vehicle working conditions.

In the present paper, a model-based controller of engine torque and engine-out Nitrogen oxide (NOx) emissions, which was previously developed and tested by means of offline simulations, has been validated on a FPT F1C 3.0 L diesel engine by means of rapid prototyping. With reference to the previous version, a new NO_x model has been implemented to improve robustness in terms of NO_x prediction. The experimental tests have confirmed the basic functionality of the controller in transient conditions, over different load ramps at fixed engine speeds, over which the average RMSE (Root Mean Square Error) values for the control of NO_x emissions were of the order of 55–90 ppm, while the average RMSE values for the control of brake mean effective pressure (BMEP) were of the order of 0.25–0.39 bar. However, the test results also highlighted the need for further improvements, especially concerning the effect of the engine thermal state on the NO_x emissions in transient operation. Moreover, several aspects, such as the check of the computational time, the impact of the controller on other pollutant emissions, or on the long-term engine operations, will have to be evaluated in future studies in view of the controller implementation on the engine control unit.

Diesel powertrains will remain an indispensable energy carrier to meet the CO₂ emission targets in the short-term for both light-duty and heavy-duty applications. As the legislation limits become more and more stringent, innovative solutions are developed in order to meet them. The recent advances in the performance of Electronic Control Units (ECUs) and sensors made it possible to use model-based control strategies rather than the classical map-based approach. In this paper, two different closed loop controllers of the air-path of a heavy-duty diesel engine have been designed and compared through the Model-in-the-Loop (MiL) technique by using the GT-Power software as engine simulator. The design of the controllers was carried out by using a model-based approach. In particular, a detailed model of the engine, realized using the GT-Power 1D commercial code, was simplified and linearized at 5 selected engine points using the ARX black-box identification approach. These linearized models were then used to tune the developed controllers. The whole design has the goal of ensuring the correct engine functioning while affecting the formation of NO_x emissions. The behavior of two control structures, PID and Eigenvalue placement, has been compared. The actuated variables are the positions of EGR and VGT actuators while the controlled ones are the oxygen concentration in the intake manifold and the boost pressure. The choice of the intake oxygen concentration as control variable is directly connected to its strict correlation with the pollutant emissions (in particular, with NO_x emissions), in order to control them in a more effective way, especially in transient operation.

A model-based technique for the control of BMEP (Brake Mean Effective Pressure) and NOx (Nitrogen Oxide) emissions has been developed and then assessed on a FPT F1C Euro VI diesel engine for light-duty applications. The model-based technique requires the adoption of a predictive combustion model to simulate the heat release rate and BMEP, on the basis of the injection pattern, from which NOx emissions can be calculated. The heat release model is based on the accumulated fuel mass approach which needs as inputs the start of injection of the different pulses and the injected fuel mass quantities. The in-cylinder pressure is then simulated using a single-zone approach. The model-based controller defines the optimal values of SOI_main and q_f,inj that allow the desired targets of BMEP and NOx to be reached cycle-by-cycle. The controller has been developed and assessed by means of Model-in-the-Loop (MiL), by coupling a fast running engine model developed in GT-Power environment with the combustion controller developed in Simulink environment. Several load ramps for different engine speeds were simulated in MiL to verify the functionality of the controller. The activity was carried out within a research project in collaboration with FPT Industrial. It was shown that the developed algorithm has a good potential in controlling NOx emissions and BMEP and features real-time capability. Therefore, it is suitable for the subsequent implementation on the engine through rapid prototyping.