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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.

A model-based control approach is proposed to give proper reference for the feed-forward combustion control of Partially Pre-mixed Combustion (PPC) engines. The current study presents a simplified first principal model, which has been developed to provide a base estimation of the ignition properties. This model is used to describe the behavior of a single-cylinder heavy-duty diesel engine fueled with a mix of bio-butanol and n-heptane (80vol% bio-butanol and 20 vol% n-heptane). The model has been validated at 8 bar gross Indicated Mean Effective Pressure (gIMEP) in PPC mode. Inlet temperature and pressure have been varied to test the model capabilities. First the experiments were conducted to generate reference points with BH80 under PPC conditions. And then CFD simulations were conducted to give initial parameter set up, e.g. fuel distribution, zone dividing, for the multi-zone model.

Diesel spray mixture formation is investigated at target conditions using multiple diagnostics and laboratories. High-speed Particle Image Velocimetry (PIV) is used to measure the velocity field inside and outside the jet simultaneously with a new frame straddling synchronization scheme. The PIV measurements are carried out in the Engine Combustion Network Spray A target conditions, enabling direct comparisons with mixture fraction measurements previously performed in the same conditions, and forming a unique database at diesel conditions. A 1D spray model, based upon mass and momentum exchange between axial control volumes and near-Gaussian velocity and mixture fraction profiles is evaluated against the data.

Green zones are challenging problems for the thermal management systems of hybrid vehicles. This is because within the green zone the engine is turned off, and the only way to keep the aftertreatment system warm is lost. This means that there is a risk of leaving the green zone with a cold and ineffective aftertreatment system, resulting in high emissions. A thermal management strategy that heats the aftertreatment system prior to turning off the engine, in an optimal way, to reduce the NOx emissions when the engine is restarted, is developed. The strategy is also used to evaluate under what conditions pre-heating is a suitable strategy, by evaluating the performance in simulations using a model of a heavy-duty diesel powertrain and scenario designed for this purpose.

Multiple injection strategies are commonly used in conventional Diesel engines due to the flexibility for optimizing heat-release timing with a consequent improvement in fuel economy and engine-out emissions. This is also desirable in low-temperature combustion (LTC) engines since it offers the potential to reduce unburned hydrocarbon and CO emissions. To better utilize these benefits and find optimal calibrations of split injection strategies, it is imperative that the fundamental processes of multiple injection combustion are understood and computational fluid dynamics models accurately describe the flow dynamics and combustion characteristics between different injection events. To this end, this work is dedicated to the identification of suitable methodologies to predict the multiple injection combustion process.

Reactivity Controlled Compression Ignition (RCCI) combines very high thermal efficiencies with ultra-low engine out NOx and PM emissions. Moreover, it enables the use of a wide range of fuels. As this pre-mixed combustion concept relies on controlled auto-ignition, closed-loop combustion control is essential to guarantee safe and stable operation under varying operating conditions. This work presents a coordinated air-fuel path controller for RCCI operation in a multi-cylinder heavy-duty engine. This is an essential step towards real-world application. Up to now, transient RCCI studies focused on individual cylinder control of the fuel path only. A systematic, model-based approach is followed to design a multivariable RCCI controller. Using the Frequency Response Function (FRF) method, linear models are identified for the air path and for the combustion process in the individual cylinders.

The accepted model of conventional diesel combustion [1] assumes a rich premixed flame slightly downstream of the maximum liquid penetration. The soot generated by this rich premixed flame is burnt out by a subsequent diffusion flame at the head of the jet. Even in situations in which the centre of combustion (CA50) is phased optimally to maximize efficiency, slow late stage combustion can still have a significant detrimental impact on thermal efficiency. Data is presented on potential late-stage combustion improvers in a EURO VI compliant HD engine at a range of speed and load points. The operating conditions (e.g. injection timings, EGR levels) were based on a EURO VI calibration which targets 3 g/kWh of engine-out NOx. Rates of heat release were determined from the pressure sensor data. To investigate late stage combustion, focus was made on the position in the cycle at which 90% of the fuel had combusted (CA90). An EN590 compliant fuel was tested.

With the adoption of the Worldwide harmonized Light Vehicles Test Procedure (WLTP) and the Real Driving Emissions (RDE) regulations for testing and monitoring the vehicle pollutant emissions, as well as CO2 and fuel consumption, the gap between real world and type approval performances is expected to decrease to a large extent. With respect to CO2, however, WLTP is not expected to fully eliminate the reported 40% discrepancy between real world and type approval values. This is mainly attributed to the fact that laboratory tests take place under average controlled conditions that do not fully replicate the environmental and traffic conditions experienced over daily driving across Europe. In addition, any uncertainties of a pre-defined test protocol and the vehicle operation can be optimized to lower the CO2 emissions of the type approval test. Such issues can be minimized in principle with the adoption of a real-world test for fuel consumption.

Post-injection strategies prove to be a valuable option for reducing soot emission, but experimental results often differ from publication to publication. These discrepancies are likely caused by the selected operating conditions and engine hardware in separate studies. Efforts to optimize not only engine-out soot, but simultaneously fuel economy and emissions of nitrogen oxides (NOx) complicate the understanding of post-injection effects even more. Still, the large amount of published work on the topic is gradually forming a consensus. In the current work, a Design-of-Experiments (DoE) procedure and regression analysis are used to investigate the influence of various operating conditions on post-injection scheduling and efficacy. The study targets emission reductions of soot and NOx, as well as fuel economy improvements. Experiments are conducted on a heavy-duty compression ignition engine at three load-speed combinations.

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.

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.

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.

In-cylinder visualization, combustion stratification, and engine-out particulate matter (PM) emissions were investigated in an optical engine fueled with Haltermann straight-run naphtha fuel and corresponding surrogate fuel. The combustion mode was transited from homogeneous charge compression ignition (HCCI) to conventional compression ignition (CI) via partially premixed combustion (PPC). Single injection strategy with the change of start of injection (SOI) from early to late injections was employed. The high-speed color camera was used to capture the in-cylinder combustion images. The combustion stratification was analyzed based on the natural luminosity of the combustion images. The regulated emission of unburned hydrocarbon (UHC), carbon monoxide (CO) and nitrogen oxides (NOX) were measured to evaluate the combustion efficiency together with the in-cylinder rate of heat release.

Second generation biomass is an attractive renewable feedstock for transport fuels. Its sulfur content is generally negligible and the carbon cycle is reduced from millions to tens of years. One hitherto non-valorized feedstock are so-called humins, a residual product formed in the conversion of sugars to platform chemicals, such as hydroxymethylfurfural and methoxymethylfurfural, intermediates in the production of FDCA, a building block used to produce the polyethylene furanoate (PEF) bottle by Avantium. The focus of this study is to investigate the spray combustion behavior of humins as a renewable alternative for heavy fuel oil (HFO) under large two-stroke engine-like conditions in an optically accessible constant volume chamber.

To meet future emission targets, it becomes increasingly important to optimize the synergy between engine and aftertreatment system. By using an integrated control approach minimal fluid (fuel and DEF) consumption is targeted within the constraints of emission legislation during real-world operation. In such concept, the on-line availability of engine-out NOx emission is crucial. Here, the use of a Virtual NOx sensor can be of great added-value. Virtual sensing enables more direct and robust emission control allowing, for example, engine-out NOx determination during conditions in which the hardware sensor is not available, such as cold start conditions. Furthermore, with use of the virtual sensor, the engine control strategy can be directly based on NOx emission data, resulting in reduced response time and improved transient emission control. This paper presents the development and on-line implementation of a Virtual NOx sensor, using in-cylinder pressure as main input.

Advanced Computational Fluid Dynamics (CFD) modeling of reacting sprays provides access to information not available even applying the most advanced experimental techniques. This is particularly evident if the combustion model handles detailed chemical kinetic models efficiently to describe the fuel auto-ignition and oxidation processes. Complex chemistry also provides the temporal evolution of key species closely related to emissions formation, such as polycyclic aromatic hydrocarbons (PAHs) that are well-known as soot precursors. In this framework, present investigation focuses on the analysis of the so-called Spray-A combustion characteristics using two different flamelet-based combustion models. Both Reynolds-Averaged Navier-Stokes (RANS) and Large-Eddy Simulation (LES) predictions are combined to study not only the averaged spray characteristics, but also the relevance of different realizations in this particular problem.

The optimal fuel for partially premixed combustion (PPC) is considered to be a gasoline boiling range fuel with an octane number around 70. Higher octane number fuels are considered problematic with low load and idle conditions. In previous studies mostly the intake air temperature did not exceed 30 °C. Possibly increasing intake air temperatures could extend the load range. In this study primary reference fuels (PRFs), blends of iso-octane and n-heptane, with octane numbers of 70, 80, and 90 are tested in an adapted commercial diesel engine under partially premixed combustion mode to investigate the potential of these higher octane number fuels in low load and idle conditions. During testing combustion phasing and intake air temperature are varied to investigate the combustion and emission characteristics under low load and idle conditions.

Partially premixed compression ignition combustion is one of the low temperature combustion techniques which is being actively investigated. This approach provides a significant reduction of both soot and NOx emissions. Comparing to the homogeneous charge compression ignition mode, PPCI combustion provides better control on ignition timing and noise reduction through air-fuel mixture stratification which lowers heat release rate compared to other advanced combustion modes. In this work, CFD simulations were conducted for a low and a high air-fuel mixture stratification cases on a light-duty optical engine operating in PPCI mode. Such conditions for PRF70 as fuel were experimentally achieved by injection timing and spray targeting at similar thermodynamic conditions.

Gasoline-ethanol-methanol (GEM) blends, with constant stoichiometric air-to-fuel ratio (iso-stoichiometric blending rule) and equivalent to binary gasoline-ethanol blends (E2, E5, E10 and E15 in % vol.), were defined to investigate the effect of methanol and combined mixtures of ethanol and methanol when blended with three FACE (Fuels for Advanced Combustion Engines) Gasolines, I, J and A corresponding to RON 70.2, 73.8 and 83.9, respectively, and their corresponding Primary Reference Fuels (PRFs). A Cooperative Fuel Research (CFR) engine was used under Spark Ignition and Homogeneous Charge Compression Ignited modes. An ignition quality tester was utilized in the Compression Ignition mode. One of the promising properties of GEM blends, which are derived using the iso-stoichiometric blending rule, is that they maintain a constant octane number, which has led to the introduction of methanol as a drop-in fuel to supplement bio-derived ethanol.

The modeling of fuel sprays under well-characterized conditions relevant for heavy-duty Diesel engine applications, allows for detailed analyses of individual phenomena aimed at improving emission formation and fuel consumption. However, the complexity of a reacting fuel spray under heavy-duty conditions currently prohibits direct simulation. Using a systematic approach, we extrapolate available spray models to the desired conditions without inclusion of chemical reactions. For validation, experimental techniques are utilized to characterize inert sprays of n-dodecane in a high-pressure, high-temperature (900 K) constant volume vessel with full optical access. The liquid fuel spray is studied using high-speed diffused back-illumination for conditions with different densities (22.8 and 40 kg/m3) and injection pressures (150, 80 and 160 MPa), using a 0.205-mm orifice diameter nozzle.