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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.

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.

The operation of a dual fuel combustion engine using combustion mode-switching offers the benefit of higher thermal efficiency compared to single-mode operation. For various fuel combinations, the engine research community has shown that running dual fuel engines in Reactivity Controlled Compression Ignition (RCCI) mode, is a feasible way to further improve thermal efficiency compared to Conventional Dual Fuel (CDF) operation of the same engine. In RCCI combustion, also ultra-low engine-out NOx and soot emissions have been reported. Depending on available hardware, however, stable RCCI combustion is limited to a certain load range and operating conditions. Therefore, mode-switching is a promising way to implement RCCI in practice on short term. In this paper, a model-based development approach for a dual fuel mode-switching controller is presented. Simulation results demonstrate the potential of this controller for a heavy-duty engine running on natural gas and diesel.

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.

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.

Initiatives have been and will be taken to define very strict emission limitations for Heavy-Duty (HD) urban transport vehicles in Europe. This will probably led to a class of very clean, so-called, Enhanced Environmentally friendly Vehicles (EEV). This paper presents an overview of the current and the (expected) future emission legislation for this type of vehicle together with the different technology that can be used for the development of internal combustion engines for these vehicles. A number of engine concepts, based on the experience of developing these concepts, are described and compared both from a technological and economic standpoint. It can be concluded that EEV emission limits can be achieved with advanced diesel engine concepts as well as with gas engines. From the economical viewpoint it can be concluded that gas engines can compete with diesel engines.

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.

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.

Active safety systems are increasingly becoming available in trucks and passenger vehicles. Developments in the field of active safety are shifting from increasing driver comfort towards increasing occupant safety. Furthermore, this shift is seen within active safety systems: safety functions are added to existing comfort systems, rather than adding new safety systems to the vehicle. Comfort systems such as cruise control are extended via ACC to pre-crash braking systems. Testing of active safety systems must follow these developments. Whereas standardized test programs are available for passive safety systems, such test programs are hardly available yet for active safety systems. Furthermore, test programs for passive safety systems consist of only a handful of scenarios. Test programs for active safety systems, however, should consist of much more scenarios, as those systems should function well in many different situations.

This paper presents the identification and validation of a dynamic Waste Heat Recovery (WHR) system model. Driven by upcoming CO₂ emission targets and increasing fuel costs, engine exhaust gas heat utilization has recently attracted much attention to improve fuel efficiency, especially for heavy-duty automotive applications. In this study, we focus on a Euro-VI heavy-duty diesel engine, which is equipped with a Waste Heat Recovery system based on an Organic Rankine Cycle. The applied model, which combines first principle modeling with stationary component models, covers the two-phase flow behavior and the effect of control inputs. Furthermore, it describes the interaction with the engine on both gas and drivetrain side. Using engine dynamometer measurements, an optimal fit of unknown model parameters is determined for stationary operating points.

Plasma-assisted PM removal is examined in a packed-bed plasma system. This study focuses on the effect of plasma power, space velocity and exhaust gas composition on PM filtration. Experiments are done on an engine dynamometer with a VW 1.2l TDI engine. During these experiments, the airflow is throttled so large smoke levels are realized. Then, absolute filtration effects can better be observed. For relatively small space velocities, 90% filtration efficiency based on smoke measurements is determined at an energy density of 25 J/l (i.e. plasma power per exhaust gas volume flow). In the studied operating point, the filtration efficiency is not further increased for larger energy densities. Based on these results, we conclude that the available plasma power has to be increased for full flow experiments. In cases without airflow throttling, the plasma has no effect on PM filtration. Application of a 10 kV bias to enhance electrostatic precipitation is also seen to be ineffective.

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.