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A virtual diesel aftertreatment exhaust line is presented comprising DOC, DPF, SCR models and a unique Ammonia Oxidation catalyst model. All models are one dimensional models based on first principles. These models offer an attractive compromise between speed, accuracy and complexity for a variety of model applications: off-line simulation, control strategy development, Hardware in the Loop applications and model-based calibration. The implemented models are fast and suitable for real-time applications. Use of these virtual exhaust line models in a product development process has the potential of saving time and resources. The aftertreatment models are fitted based on specifically designed engine dynamometer experiments, which can be performed in a limited time frame. The effective test time required on a validated test setup is estimated on the order of 12 days in total. Specifically developed software tools facilitate the model fit process.

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.

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.

Self-learning energy management is a promising concept, which optimizes real-world system performance by automated, on-line adaptation of control settings. In this work, the potential of self-learning capabilities related to optimization is studied for energy management in Plug-in Hybrid Electric Vehicles (PHEV). These vehicles are of great interest for the transport sector, since they combine high fuel efficiency with last mile full-electric driving. We focus on a specific use case: PHEV operation through future Zero Emission (ZE) zones of cities. As a first step towards self-learning control, we introduce a novel, adaptive supervisory controller that combines modular energy and emission management (MEEM) and deals with varying constraints and system uncertainty. This optimal control strategy is based on Pontryagin’s Minimum Principle and maximizes overall energy efficiency.

Two major trends can be identified for powertrain control in the next decade. The legislation will more and more focus on in-use emissions. Together with the global trend to reduce the CO₂ emissions, this will lead to an integral drive train approach. To develop and validate this integral drive train approach, the need for a new chapter in powertrain testing arises. The climatic-altitude chamber, suited for heavy vehicles, serves a wide variety of testing needs. Ambient temperature can be controlled between -45°C and +55°C and ambient pressure can be reduced up to a level found at an altitude to 4000 meters. The chamber's dynamometers enable transient testing of heavy-duty engines and vehicles and the chamber is equipped with a comprehensive array of emission measurement capabilities, working under extreme conditions.

The impact of comfort is becoming increasingly important. On one hand, manufacturers use comfort to distinguish their products from their competitors. On the other hand, more cars than ever are used professionally. The prolonged sitting in automotive conditions of professional drivers introduced new physical complaints, resulting in high social costs. However, the cause of these complaints is not well understood. The use of virtual testing tools can contribute to both speeding up and reducing the costs of the development process of new more comfortable cars and the research in the causes of the new complaints. Vibration loading has often been identified as a source of discomfort. In literature, several human models developed for prediction of human resonance behaviour in vibrations were described. In most of these human body models, the muscles are represented in a simplified way.

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.

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.

Two of the main design objectives for car interiors are comfort and safety. These aspects are both determined by the seating position of the occupant. Seat manufacturers use the SAE Three-Dimensional H-Point Machine™ to measure seating positions to design, audit, and benchmark seats. The seating positions measured with the H-Point Machine form the basis of a seat design, including comfort and safety aspects. Currently, the seat design process is largely based on prototype testing, which makes this process time-consuming and expensive. Consequently, there is a large demand for efficient design tools that enable an optimal combination of seating comfort and safety aspects. Numerical modeling provides an efficient means to optimally combine various seat design characteristics prior to prototype testing, thereby reducing design costs and time-to-market.

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.

In 1998, Rouhana et al. described development of a new device, called the IR-TRACC (InfraRed - Telescoping Rod for Assessment of Chest Compression). In its original concept, the IR-TRACC uses two infrared LEDs inside of a telescoping rod to measure deflection. One LED serves as a light transmitter and the other as a light receiver. The output from the receiver LED is converted to a linear function of chest compression using an analog circuit. Tests have been performed with IR-TRACC units at various labs around the world since 1998. A first-generation IR-TRACC system was retrofit into a Q3 dummy by TNO. Similarly, a mid sized male Hybrid III dummy thorax and a small female Hybrid III dummy thorax have been designed by First Technology Safety Systems (FTSS) such that each contains 4 second-generation IR-TRACC units. The second-generation IR-TRACC is the result of continued development by FTSS, especially in the areas of the analysis circuit, manufacturing and calibration methods.

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.

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.