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Cylinder pressure-based combustion control is widely introduced for passenger cars. Benefits include enhanced emission robustness to fuel quality variation, reduced fuel consumption due to more accurate (multi-pulse) fuel injection, and minimized after treatment size. In addition, it enables the introduction of advanced, high-efficient combustion concepts. The application in truck engines is foreseen, but challenges need to be overcome related to durability, increased system costs, and impact on the cylinder head. In this paper, a new single cylinder pressure sensor concept for heavy-duty Diesel engines is presented. Compared to previous studies, this work focuses on heavy-duty Diesel powertrains, which are characterized by a relatively flexible crank shaft in contrast to the existing passenger car applications.

The Reactivity Controlled Compression Ignition concept for dual-fuel engines has multiple challenges of which some can be overcome using Variable Valve Actuation approaches. For various fuel combinations, the engine research community has shown that running dual-fuel engines in RCCI mode, improves thermal efficiency and results in ultra-low engine-out nitrous oxides and soot. However, stable RCCI combustion is limited to a certain load range, depending on available hardware. At low loads, the combustion efficiency can drop significantly, whereas at high loads, the maximum in-cylinder pressure can easily exceed the engine design limit. In this paper, three VVA measures to increase load range, improve combustion efficiency, and perform thermal management are presented. Simulation results are used to demonstrate the potential of these VVA measures for a heavy-duty engine running on natural gas and diesel.

Complying to both the increasingly stringent pollutant emissions as well as (future) GHG emission legislation - with increased focus on in-use real-world emissions - puts a great challenge to the engine/aftertreatment control development process. Control system complexity, calibration and validation effort has increased dramatically over the past decade. A trend that is likely to continue considering the next steps in emission and GHG emission legislation. Control-oriented engine models are valuable tools for efficient development of engine monitoring and control systems. Furthermore, these (predictive) engine models are more and more used as part of control algorithms to ensure legislation compliant and optimized performance over the system lifetime. For these engine models, it is essential that simulation and prediction of system variables during non-nominal engine operation, such as non-standard ambient conditions, is well captured.

Increasing efforts to minimize global warming has led to regulation of greenhouse gas (GHG) emissions of automotive applications. The US is frontrunner regarding implementation of GHG related legislation with the introduction of GHG phase 1 and phase 2, ultimately targeting a 40% fuel consumption reduction in 2027 compared to 2010 on vehicle level. More specific, engines are required to reduce CO2 emissions by 6% compared to GHG phase 1 levels. Next to the GHG emission legislation, more stringent legislation is anticipated in the US to further reduce NOx emissions: a further 90% reduction is targeted as soon as 2024 compared to 2010 standard. Meeting these anticipated ultra-low NOx standards within the GHG phase 2 constraints on CO2 poses a great challenge. This paper presents an overview of the main challenges and key aspects regarding meeting ultra-low NOx requirements within the constraints on CO2 and N2O set by GHG phase 2 regulations.

For natural gas (NG)-diesel RCCI, a multi-zonal, detailed chemistry modeling approach is presented. This dual fuel combustion process requires further understanding of the ignition and combustion processes to maximize thermal efficiency and minimize (partially) unburned fuel emissions. The introduction of two fuels with different physical and chemical properties makes the combustion process complicated and challenging to model. In this study, a multi-zone approach is applied to NG-diesel RCCI combustion in a heavy-duty engine. Auto-ignition chemistry is believed to be the key process in RCCI. Starting from a multi-zone model that can describe auto-ignition dominated processes, such as HCCI and PCCI, this model is adapted by including reaction mechanisms for natural gas and NOx and by improving the in-cylinder pressure prediction. The model is validated using NG-diesel RCCI measurements that are performed on a 6 cylinder heavy-duty engine.

Up to now, reduction of fuel consumption of vehicles equipped with CVT transmission has not been exploited to its full potential due to the reduced driveability when driving the optimum efficiency engine operating points. An ISG system with torque boost capabilities can be used to restore this driveability. This paper discusses the goals, the CAE simulation tool, the methodology used in the preparative study for evaluation and dimensioning of a CVT-ISG concept, as well as the simulation results. The conclusions, generated from numerous simulations, provide vital information for the component selection, and for the development of the powertrain management system.

This article describes a NOx sensor based urea dosing control strategy for heavy-duty diesel aftertreatment systems using Selective Catalytic Reduction. The dosing control strategy comprises of a fast-response, model-based ammonia storage control system in combination with a long-timescale tailpipe-feedback module that adjusts the dosing quantity according to current aftertreatment conditions. This results in a control system that is robust to system disturbances such as biased NOx sensors and variations in AdBlue concentrations. The cross-sensitivity of the tailpipe NOx sensor to ammonia is handled by a novel, smart signal filter that can reliably identify the contributions of NOx and NH3 in the tailpipe sensor signal, without requiring an artificial perturbation of the dosing signal.

Heavy-duty diesel engines are used in a wide range of applications. For varying operating environments, the engine and aftertreatment system must comply with the real-world emission legislation limits. Simultaneously, minimal fuel consumption and good drivability are crucial for economic competitiveness and usability. Meeting these requirements takes substantial development and calibration effort, and complying with regulations results in a trade-off between emissions and fuel consumption. TNO's Integrated Emission Management (IEM) strategy finds online, the cost-optimal point in this trade-off and is able to deal with variations in operating conditions, while complying with legislation limits. Based on the actual state of the engine and aftertreatment system, an optimal engine operating point is computed using a model-based optimal-control algorithm.

Heavy-duty diesel engines are used in different application areas, like long-haul, city distribution, dump truck and building and construction industry. For these wide variety of areas, the engine performance needs to comply with the real-world legislation limits and should simultaneously have a low fuel consumption and good drivability. Meeting these requirements takes substantial development and calibration effort, where an optimal fuel consumption for each application is not always met in practice. TNO's Integrated Emission Management (IEM) strategy, is able to deal with these variations in operating conditions, while meeting legislation limits and obtaining on-line cost optimization. Based on the actual state of the engine and aftertreatment, optimal air-path setpoints are computed, which balances EGR and SCR usage.

CO2 regulations on heavy-duty transport are introduced in essentially all markets within the next decade, in most cases in several phases of increasing stringency. To cope with these mandates, developers of engines and related equipment are aiming to break new ground in the fields of combustion, fuel and hardware technologies. In this work, a novel diesel fuel injector, Delphi’s DFI7, is utilized to experimentally investigate and compare the performance of ramped injection rates versus traditional square fueling profiles. The aim is specifically to shift the efficiency and NOx tradeoff to a more favorable position. The design of experiments methodology is used in the tests, along with statistical techniques to analyze the data. Results show that ramped and square rates - after optimization of fueling parameters - produce comparable gross indicated efficiencies.

In the past decade, SCR deNOx technology with urea injection has grown to maturity. European OEMs will apply SCR deNOx to meet future heavy-duty emissions legislation starting with EURO-4 (2005/2006). Numerous research programs in Europe and the US have shown a variety of system layouts and control strategies. The main differences are formed by: the engine-out NOx calibration the application of an NO to NO2 catalyst open-loop or closed-loop urea dosage control. This paper gives an overview of possible SCR system configurations that are required for different stages of future emission legislation. Engine-out NOx emission is strongly influenced by ambient conditions. Projections in this study show that a combination of cold climate and a wintergrade fuel is the most severe: it may lead to 30% lower engine-out NOx emission with respect to laboratory conditions.

The next generation off-road vehicles will see additional exhaust gas aftertreatment systems, ranging from DOC-SCR only to full DOC-DPF-SCR-AMOX systems. This will increase system complexity and development effort significantly. Emission requirements and the high number of vehicle configurations within the off-road industry will require a new process for development and validation. The introduced model-based approach using physical models of aftertreatment can reduce development effort and cost, improve performance robustness and help to identify performance issues early in the development process. A method to investigate and optimize a large matrix of variations by simulation is introduced. This can lead to a significant reduction in the number of required calibrations and can assist in the development of design specifications for the aftertreatment system. A case study for SCR calibration successfully demonstrates the potential of model-based development.

To meet 2010 emission targets, optimal SCR system performance is required. In addition, attention has to be paid to in-use compliance requirements. Closed-loop control seems an attractive option to meet the formulated goals. This study deals with the potential and limitations of closed-loop SCR control. High NOx conversion in combination with acceptable NH3 slip can be realized with an open-loop control strategy. However, closed-loop control is needed to make the SCR system robust for urea dosage inaccuracy, catalyst ageing and NOx engine-out variations. Then, the system meets conformity of production and in-use compliance norms. To demonstrate the potential of closed-loop SCR control, a NOx sensor based control strategy with cross-sensitivity compensation is compared with an adaptive surface coverage/NH3 slip control strategy and an open-loop strategy. The adaptive surface coverage/NH3 slip control strategy shows best performance over simulated ESC and ETC cycles.

A new cost-based control strategy is presented that optimizes engine-aftertreatment performance under all operating conditions. This Integrated Emission Management strategy minimizes fuel consumption within the set emission limits by on-line adjustment of air management based on the actual state of the exhaust gas aftertreatment system. Following a model-based approach, Integrated Emission Management offers a framework for future control strategy development. This approach alleviates calibration complexity, since it allows to make optimal trade-offs in an operational cost sense. The potential of the presented cost-optimal control strategy is demonstrated for a modern heavy-duty Euro VI engine. The studied diesel engine is equipped with cooled EGR, Variable Geometry Turbocharger, and a DPF-SCR aftertreatment system.

This paper presents a model-based control and calibration design method for online cost-based optimization of engine-aftertreatment operation under all operating conditions. The so-called Integrated Emission Management (IEM) strategy online minimizes the fuel and AbBlue consumption. Based on the actual state of engine and aftertreatment systems, optimal air management settings are determined for EGR-SCR balancing. Following a model-based approach, the strategy allows for a systematic control design and calibration procedure for engine and aftertreatment systems. The potential of this time efficient method is demonstrated by experiments for a heavy-duty Euro-VI engine. The Integrated Emission Management strategy is developed and calibrated offline over a cold and hot World Harmonized Transient Cycle (WHTC) for the set emission targets. The total IEM development and calibration process takes approximately 20 weeks from model identification to the acceptance tests.

Premixed combustion concepts like PCCI and RCCI have attracted much attention, since these concepts offer possibilities to reduce engine out emissions to a low level, while still achieving good efficiency. Most RCCI studies use a combination of a high-cetane fuel like diesel, and gasoline as low-cetane fuel. Limited results have been published using natural gas as low-cetane fuel; especially full scale engine results. This study presents results from an experimental study of diesel-CNG RCCI operation on a 6 cylinder, 8 l heavy duty engine with cooled EGR. This standard Tier4f diesel engine was equipped with a gas injection system, which used single point injection and mixed the gaseous fuel with air upstream of the intake manifold. For this engine configuration, RCCI operating limits have been explored. In the 1200-1800 rpm range, RCCI operation with Euro-VI engine out NOx and soot emissions was achieved between 2 and 9 bar BMEP without EGR.

The application of SCR deNOx aftertreatment was studied on two about 12 liter class heavy-duty diesel engines within a consortium project. Basically, the system consists of a dosage system for aqueous urea injection and a vanadia based SCR catalyst, without an upstream or downstream oxidation catalyst. The urea injection system for a DAF and a Renault V.I. (Véhicules Industriels) diesel engine was calibrated on the engine test bench taking into account dynamic effects of the catalyst. For both engine applications NOx reduction was 81% to 84% over the ESC and 72% over the ETC. CO emission increased up to 27%. PM emission is reduced by 4 to 23% and HC emission is reduced by more than 80%. These results are achieved with standard diesel fuel with about 350 ppm sulfur. The test engines and SCR deNOx systems were built into a DAF FT95 truck and a Renault V.I. Magnum truck.

In this study a microwave assisted particulate trap regeneration system has been developed. Microwave technology typically shows uneven temperature distribution in a trap. In this research an innovative technique is introduced: a so-called circular polarizer for generating a more even energy distribution in the trap. Experimental work has been performed on a 1.2 l TDI engine on an engine dynamometer. A cordierite wall-flow trap was located in the exhaust pipe. Experiments have been performed with variation of temperature at the start of regeneration, energy input duration and external combustion air flow. It has been observed that the exhaust gas flow of the engine, even at idle, is too high for maintaining propagating flame fronts. It can be concluded that microwave regeneration with a low-power microwave generator of about 1 kW must be applied in a multiple branch trap system or regeneration events must be applied in periods when the engine is not running.

SCR on Filter (SCRoF) is an efficient and compact NOX and PM reduction technology already used in series production for light-duty applications. The technology is now finding its way into the medium duty and heavy duty market. One of the key challenges for successful application is the robustness to real world variations. The solution to this challenge can be found by using model-based control algorithms, utilizing state estimation by physics-based catalyst models. This paper focuses on the development, validation and real time implementation of a physics-based control oriented SCRoF model. An overview of the developed model will be presented, together with a brief description of the model parameter identification and validation process using engine test bench measurement data. The model parameters are identified following a streamlined approach, focusing on decoupling the effects of deNOx and soot phenomena.

The performance of a three-way catalytic converter under transient operation can be improved by controlling the level of oxygen stored on ceria at some optimal level. A model-based controller, with the model estimating the level of ceria coverage by oxygen, can achieve this goal. A simple, dynamic model is based on step responses of the converter and is used to train the controller off-line. The controller is a neuro-fuzzy approximation of a model predictive controller. Thus, it retains a high performance while being less computationally involving. The system performance has been experimentally tested by a specially designed, highly transient test cycle.