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A 2007 Cummins ISL 8.9L direct-injection common rail diesel engine rated at 272 kW (365 hp) was used to load the filter to 2.2 g/L and passively oxidize particulate matter (PM) within a 2007 OEM aftertreatment system consisting of a diesel oxidation catalyst (DOC) and catalyzed particulate filter (CPF). Having a better understanding of the passive NO2 oxidation kinetics of PM within the CPF allows for reducing the frequency of active regenerations (hydrocarbon injection) and the associated fuel penalties. Being able to model the passive oxidation of accumulated PM in the CPF is critical to creating accurate state estimation strategies. The MTU 1-D CPF model will be used to simulate data collected from this study to examine differences in the PM oxidation kinetics when soy methyl ester (SME) biodiesel is used as the source of fuel for the engine.

Mechanisms of NH₃ generation using LNT-like catalysts have been studied in a bench reactor over a wide range of temperatures, flow rates, reformer catalyst types and synthetic exhaust-gas compositions. The experiments showed that the on board production of sufficient quantities of ammonia on board for SCR operation appeared feasible, and the results identified the range of conditions for the efficient generation of ammonia. In addition, the effects of reformer catalysts using the water-gas-shift reaction as an in-situ source of the required hydrogen for the reactions are also illustrated. Computations of the NH₃ and NOx kinetics have also been carried out and are presented. Design and impregnation of the SCR catalyst in proximity to the ammonia source is the next logical step. A heated synthetic-exhaust gas flow bench was used for the experiments under carefully controlled simulated exhaust compositions.

The effects of charge motion and laminar flame speeds on combustion and exhaust temperature have been studied by using an air jet in the intake flow to produce an adjustable swirl or tumble motion, and by replacing the nitrogen in the intake air by argon or CO₂, thereby increasing or decreasing the laminar flame speed. The objective is to examine the "Late Robust Combustion" concept: whether there are opportunities for producing a high exhaust temperature using retarded combustion to facilitate catalyst warm-up, while at the same time, keeping an acceptable cycle-to-cycle torque variation as measured by the coefficient of variation (COV) of the net indicated mean effective pressure (NIMEP). The operating condition of interest is at the fast idle period of a cold start with engine speed at 1400 RPM and NIMEP at 2.6 bar. A fast burn could be produced by appropriate charge motion. The combustion phasing is primarily a function of the spark timing.

The effects of using neat FAME (Fatty Acid Methyl Ester) in a modern small displacement passenger car diesel engine have been evaluated in this paper. In particular the effects on engine performance at full load with standard (i.e., without any special tuning) ECU calibration were analyzed, highlighting some issues in the low end torque due to the lower exhaust gas temperatures at the turbine inlet, which caused a remarkable decrease of the available boost, with a substantial decrease of the engine torque output, far beyond the expected engine derating due to the lower LHV of the fuel. However, further tests carried out after ECU recalibration, showed that the same torque levels measured under diesel operation can be obtained with neat biodiesel too, thus highlighting the potential for maintaining the same level of performance.

The aim of this work is to apply an innovative adaptive ℒ1 techniques to control flutter phenomena affecting highly flexible wings and to evaluate the efficiency of this control algorithm and architecture by performing the following tasks: i) adaptation and analysis of an existing simplified nonlinear plunging/pitching 2D aeroelastic model accounting for structural nonlinearities and a quasi-steady aerodynamics capable of describing flutter and post-flutter limit cycle oscillations, ii) implement the ℒ1 adaptive control on the developed aeroelastic system to perform initial control testing and evaluate the sensitivity to system parameters, and iii) perform model validation and calibration by comparing the performance of the proposed control strategy with an adaptive back-stepping algorithm. The effectiveness and robustness of the ℒ1 adaptive control in flutter and post-flutter suppression is demonstrated.

The current trend towards an increasing electrification of road vehicles brings to life a whole series of unprecedent design issues. Among these, the ageing process that affects the lifetime of lithium-ion based energy storage systems is of particular importance since it turns out to be extremely sensitive to the variation of battery operating conditions normally occurring especially in hybrid electric vehicles (HEVs). This paper aims at analyzing the impact of operating conditions on the predicted lifetime of a parallel-through-the-road plug-in HEV battery both from thermal and ageing perspectives. The retained HEV powertrain architecture is presented first and modeled, and the related energy management system is implemented. Dedicated numerical models are also discussed for the high-voltage battery pack that allow predicting its thermal behavior and cyclic ageing.

The battery of a vehicle with an electrified powertrain (Hybrid Electric Vehicle or Battery Electric Vehicle), is required to operate with highly dynamic power outputs, both for charging and discharging operation. Consequently, the battery current varies within an extensive range during operation and the battery temperature also changes. In some cases, the relationship between the current flow and the change in the electrical energy stored seems to be affected by inefficiencies, in literature described as current losses, and nonlinearities, typically associated with the complex chemical and physical processes taking place in the battery. When calculating the vehicle electrical energy consumption over a trip, the change in the electrical energy stored at vehicle-level has to be taken into account. This quantity, what we could call the vehicle electricity balance, is typically obtained through a time-based integration of the battery current of all the vehicle batteries during operation.

Hybrid electric vehicle (HEV) powertrains are characterized by a complex design environment as a result of both the large number of possible layouts and the need for dedicated energy management strategies. When selecting the most suitable hybrid powertrain architecture at an early design stage of HEVs, engineers usually focus solely on fuel economy (directly linked to tailpipe emissions) and vehicle drivability performance. However, high voltage batteries are a crucial component of HEVs as well in terms of performance and cost. This paper introduces a multitarget assessment framework for HEV powertrain architectures which considers both fuel economy and battery lifetime. A multi-objective formulation of dynamic programming is initially presented as an off-line optimal HEV energy management strategy capable of predicting both fuel economy performance and battery lifetime of HEV powertrain layout options.

New methodologies have been developed to optimize EGR rate and injection timing in diesel engines, with the aim of minimizing fuel consumption (FC) and NOx engine-out emissions. The approach entails the application of a recently developed control-oriented engine model, which includes the simulation of the heat release rate, of the in-cylinder pressure and brake torque, as well as of the NOx emission levels. The engine model was coupled with a C-class vehicle model, in order to derive the engine speed and torque demand for several driving cycles, including the NEDC, FTP, AUDC, ARDC and AMDC. The optimization process was based on the minimization of a target function, which takes into account FC and NOx emission levels. The selected control variables of the problem are the injection timing of the main pulse and the position of the EGR valve, which have been considered as the most influential engine parameters on both fuel consumption and NOx emissions.

The potential of internal EGR (iEGR) and external EGR (eEGR) in reducing the engine-out NOx emissions in a heavy-duty diesel engine has been investigated by means of a refined 1D fluid-dynamic engine model developed in the GT-Power environment. The engine is equipped with Variable Valve Actuation (VVA) and Variable Geometry Turbocharger (VGT) systems. The activity was carried out in the frame of the CORE Collaborative Project of the European Community, VII FP. The engine model integrates an innovative 0D predictive combustion algorithm for the simulation of the HRR (heat release rate) based on the accumulated fuel mass approach and a multi-zone thermodynamic model for the simulation of the in-cylinder temperatures. NOx emissions are calculated by means of the Zeldovich thermal and prompt mechanisms.

A real-time mean-value engine model for the simulation of the HRR (heat release rate), in-cylinder pressure, brake torque and pollutant emissions, including NOx and soot, has been developed, calibrated and assessed at both steady-state and transient conditions for a Euro 6 1.6L GM diesel engine. The chemical energy release has been simulated using an improved version of a previously developed model that is based on the accumulated fuel mass approach. The in-cylinder pressure has been evaluated on the basis of the inversion of a single-zone model, using the net energy release as input. The latter quantity was derived starting from the simulated chemical energy release, and evaluating the heat transfer of the charge with the walls. NOx and soot emissions were simulated on the basis of semi-empirical correlations that take into account the in-cylinder thermodynamic properties, the chemical energy release and the main engine parameters.

The selection and tuning of the Fuel Injection System (FIS) are among the most critical tasks for the automotive diesel engine design engineers. In fact, the injection strongly affects the combustion phenomena through which controlling a wide range of related issues such as pollutant emissions, combustion noise and fuel efficiency becomes feasible. In the scope of the engine design optimization, the simulation is an efficient tool in order to both predict the key performance parameters of the FIS, and to reduce the amount of experiments needed to reach the final product configuration. In this work a complete characterization of a solenoid ballistic injector for a Light-Duty Common Rail system was therefore implemented in a commercially available one-dimensional computational software called GT-SUITE. The main phenomena governing the injector operation were simulated by means of three sub-models (electro-magnetic, hydraulic and mechanical).

A model-based approach to control BMEP (Brake Mean Effective Pressure) and NOx emissions has been developed and assessed on a FPT F1C 3.0L Euro VI diesel engine for heavy-duty applications. The controller is based on a zero-dimensional real-time combustion model, which is capable of simulating the HRR (heat release rate), in-cylinder pressure, BMEP and NOx engine-out levels. The real-time combustion model has been realized by integrating and improving previously developed simulation tools. A new discretization scheme has been developed for the model equations, in order to reduce the accuracy loss when the computational step is increased. This has allowed the required computational time to be reduced to a great extent.

The increasing use of diesel and gasoline particulate filters requires advanced on-board diagnostics (OBD) to prevent and detect filter failures and malfunctions. Early detection of upstream (engine-out) malfunctions is paramount to preventing irreversible damage to downstream aftertreatment system components. Such early detection can mitigate the failure of the particulate filter resulting in the escape of emissions exceeding permissible limits and extend the component life. However, despite best efforts at early detection and filter failure prevention, the OBD system must also be able to detect filter failures when they occur. In this study, radio frequency (RF) sensors were used to directly monitor the particulate filter state of health for both gasoline particulate filter (GPF) and diesel particulate filter (DPF) applications.

One of the first steps in powertrain design is to assess its best performance and consumption in a virtual phase. Regarding hybrid electric vehicles (HEVs), it is important to define the best mode profile through a cycle in order to maximize fuel economy. To assist in that task, several off-line optimization algorithms were developed, with Dynamic Programming (DP) being the most common one. The DP algorithm generates the control actions that will result in the most optimal fuel economy of the powertrain for a known driving cycle. Although this method results in the global optimum behavior, the DP tool comes with a high computational cost. The charge-sustaining requirement and the necessity of capturing extremely small variations in the battery state of charge (SOC) makes this state vector an enormous variable. As things move fast in the industry, a rapid tool with the same performance is required.

The goal of this interview analysis was to explore and document the perceptions of two unique lane centering systems (S90’s Pilot Assist and CT6’s Super Cruise). Both systems offer a similar type of functionality (adaptive cruise control and lane centering), but have significantly different design philosophies and HMI (Human-Machine Interface) implementations. Twenty-four drivers drove one of the two vehicle models for a month as part of a field operational test (FOT) study. Upon vehicle return, drivers took part in a 60-minute semi-structured interview covering their perceptions of the vehicle’s various advanced driver-assistance systems (ADAS). Transcripts of the interviews were coded by two researchers, who tagged each statement with relevant system and perception code labels. For analysis, the perception codes were grouped into larger thematic bins of safety, comfort, driver attention, and system performance.

As an era of autonomous driving approaches, it is necessary to translate handling comfort - currently a responsibility of human drivers - to a vehicle imbedded algorithm. Therefore, it is imperative to understand the relationship between perceived driving comfort and human driving behaviour. This paper develops a methodology able to generate the information necessary to study how this relationship is expressed in highway overtakes. To achieve this goal, the approach revolved around the implementation of sensor Data Fusion, by processing data from CAN, camera and LIDAR from experimental tests. A myriad of variables was available, requiring individuating the key-information and parameters for recognition, classification and understanding of the manoeuvres. The paper presents the methodology and the role each sensor plays, by expanding on three main steps: Data segregation and parameter selection; Manoeuvre detection and processing; Manoeuvre classification and database generation.

In this study, a new EGR control technique, based on the estimate of the oxygen concentration in the intake manifold, was firstly investigated through numerical simulation and then experimentally tested, both under steady state and transient conditions. The robustness of the new control technique was also tested and compared with that of the conventional EGR control technique by means of both numerical simulation and experimental tests. Substantial reductions of the NOx emissions under transient operating conditions were achieved, and useful knowledge for controlling the EGR flow rate more accurately was obtained.

Different EGR system layouts (a Long Route, a Short Route, and a combination of the two) were evaluated by means of both numerical simulation and experimental tests. In particular, a one-dimensional fluid-dynamic engine model was built in order to evaluate the potential of a Long Route EGR system as well as the potential of different EGR combinations between Long and Short Route. By means of the one-dimensional model, used as a virtual test bench, the estimations of the NOx emissions, based on the Extended Zeldovich Mechanism (EZM), for the different solutions, were compared and valuable information for the calibration of the coordinated EGR LR, EGR SR and Variable Geometry Turbine (VGT) control systems was obtained.

In this work different internal and external EGR strategies, combined with extreme Miller cycles, were analyzed by means of a one-dimensional CFD simulation code for a Wärtsilä 6-cylinder, 4-strokes, medium-speed marine diesel engine, to evaluate their potential in order to reach the IMO Tier 3 NOx emissions target. By means of extreme Miller cycles, with Early Intake Valve Closures (up to 100 crank angle degrees before BDC), a shorter compression stroke and lower charge temperatures inside the cylinder can be achieved and thanks to the cooler combustion process, the NOx-specific emissions can be effectively reduced. EIVC strategies can also be combined with reductions of the scavenging period (valve overlap) to increase the amount of exhaust gases in the combustion chamber. However, the remarkably high boost pressure levels needed for such extreme Miller cycles, require mandatorily the use of two-stage turbocharging systems.