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One of the main challenges in internal combustion engine design is the simultaneous reduction of all engine pollutants like carbon monoxide (CO), total unburned hydrocarbons (THC), nitrogen oxides (NOx), and soot. Low-temperature combustion (LTC) concepts for compression ignition (CI) engines, e.g., premixed charged compression ignition (PCCI), make use of pre-injections to create a partially homogenous mixture and achieve an emission reduction. However, they present challenges in the combustion control, with the usage of in-cylinder pressure sensors as feedback signal is insufficient to control heat release and pollutant emissions simultaneously. Thus, an additional sensor, such as an ion-current sensor, could provide further information on the combustion process and effectively enable clean and efficient PCCI operation.

Powertrain electrification is becoming increasingly common in the transportation sector to address the challenges of global warming and deteriorating air quality. This paper introduces a novel “Build Your Hybrid” approach to experience and test various hybrid powertrain concepts. This approach is applied to the light commercial vehicles (LCV) segment due to the attractive combination of a Diesel engine and a partly electrified powertrain. For this purpose, a demonstrator vehicle has been set up with a flexible P02 hybrid topology and a prototype Hybrid Control Unit (HCU). Based on user input, the HCU software modifies the control functions and simulation models to emulate different sub-topologies and levels of hybridization in the demonstrator vehicle. Three powertrain concepts are considered for LCVs: HV P2, 48V P2 and 48V P0 hybrid. Dedicated hybrid control strategies are developed to take full advantage of the synergies of the electrical system and reduce CO2 and NOx emissions.

Renewable fuels, such as bio- and e-fuels, are of great interest for the defossilization of the transport sector. Among these fuels, methanol represents a promising candidate for emission reduction and efficiency increase due to its very high knock resistance and its production pathway as e-fuel. In general, reliable simulation tools are mandatory for evaluating a specific fuel potential and optimizing combustion systems. In this work, a previously presented methodology (Esposito et al., Energies, 2020) has been refined and applied to a different engine and different fuels. Experimental data measured with a single cylinder engine (SCE) are used to validate RANS 3D-CFD simulations of gaseous engine-out emissions. The RANS 3D-CFD model has been used for operation with a toluene reference fuel (TRF) gasoline surrogate and methanol. Varying operating conditions with exhaust gas recirculation (EGR) and air dilution are considered for the two fuels.

Future Diesel engines must meet extended requirements regarding air-fuel ratio, exhaust gas recirculation (EGR) capability, and tailored exhaust gas temperatures in the complete engine map to comply with the future pollutant emission standards. In this respect, parallel turbines combined with two separate exhaust manifolds have the potential to increase the exhaust gas temperature upstream of the exhaust aftertreatment system and reduce the catalyst light-off time. Furthermore, variable exhaust valve (EV) lifts enable new control strategies of the boosting system without additional actuators. Therefore, hardware robustness can be improved. This article focuses on the parallel-sequential boosting concept (PSBC) for a high-performance four-cylinder Diesel engine with separated exhaust manifolds combined with EV deactivation. One EV per cylinder is connected to one of the separated exhaust manifolds and, thus, connected to one of the turbines.

The increasingly stringent limits on pollutant emissions from internal combustion engine-powered vehicles require the optimization of advanced combustion systems by means of virtual development and simulation tools. Among the gaseous emissions from spark-ignition engines, the unburned hydrocarbon (HC) emissions are the most challenging species to simulate because of the complexity of the multiple physical and chemical mechanisms that contribute to their emission. These mechanisms are mainly three-dimensional (3D) resulting from multi-phase physics - e.g., fuel injection, oil-film layer, etc. - and are difficult to predict even in complex 3D computational fluid-dynamic (CFD) simulations. Phenomenological models describing the relationships between the physical-chemical phenomena are of great interest for the modeling and simplification of such complex mechanisms.

With Post Euro 6 emission standards in discussion, stricter particulate number (PN) targets as well as a decreased PN cut-off size from 23 to 10 nm are expected. Sub-23 nm particulates are considered particularly harmful to human health, but are not yet taken into account in the current vehicle certification process. Not considering sub-23 nm particulates during the development process could lead to significant additional efforts for Original Equipment Manufacturers (OEM) to comply with future Post Euro 6 PN emission limits. It is therefore essential to increase knowledge about the formation and filtration of particulates below 23 nm. In the present study, a holistic Gasoline Particulate Filter (GPF) characterization has been carried out on an engine test bench under varying boundary conditions and on a burner bench with a novel ash loading methodology.

To achieve the strict legislative restrictions for emissions from combustion engines, vast improvements in engine emissions and efficiency are required. Two major impacting factors for emissions and efficiency are the reliable generation of an effective mixture before ignition and a fast, stable combustion process. While the mixture of air and injected fuel is generated by highly three-dimensional, time-dependent flow phenomena during the intake and compression stroke, the turbulent flame propagation is directly affected by the turbulence level in the flow close to the advancing flame front. However, the flow field in the combustion chamber is highly turbulent and subject to cycle-to-cycle variations (CCV). To understand the fundamental mechanisms and interactions, 3D flow measurements with combined high spatial and temporal resolution are required.

Due to increasing environmental awareness, standards for pollutant and CO2 emissions are getting stricter in most markets around the world. In important markets such as Europe, also the emissions during real road driving, so called “Real Driving Emissions” (RDE), are now part of the type approval process for passenger cars. In addition to the proceeding hybridization and electrification of vehicles, the complexity and degrees of freedom of conventional powertrains with internal combustion engines (ICE) are also continuing to increase in order to comply with stricter exhaust emission standards. Besides the different requirements placed on vehicle emissions, the drivability capabilities of passenger vehicles desired by customers, are essentially important and vary between markets.

Exhaust aftertreatment systems must function sufficiently over the full useful life of a vehicle. In Europe this is currently defined as 160.000 km. With the introduction of Euro 7 it is expected that the required mileage will be extended to 240.000 km. This will then be consistent with the US legislation. In order to quantify the emission impact of exhaust system degradation, an Euro 7 exhaust aftertreatment system is aged by different accelerated approaches: application of the Standard Bench Cycle, the ZDAKW cycle, a novel ash loading method and borderline aging. The results depict the impact of oil ash on the oxygen storage capacity. For tailpipe emissions, the maximum peak temperatures are the dominant aging factor. The cold start performance is effected by both, thermal degradation and ash accumulation. An evaluation of this emission increase requires appropriate benchmarks.

Premixed charged compression ignition (PCCI) is an advanced combustion strategy, which has the potential to achieve ultra-low nitrogen oxide and soot emissions at high thermal efficiencies. PCCI combustion is characterized by a complex nonlinear chemical-physical process, which indicates that a physical description involves significant development times and also high computation cost. This paper presents a method to use cylinder pressure data and engine operations parameters for prediction of PCCI engine emissions by unsupervised learning and nonlinear identification techniques. The proposed method first uses principal component analysis (PCA) to reduce the dimension of the cylinder-pressure data. Based on the PCA analysis, a multi-input multi-out model was developed for nitrogen oxide and soot emission prediction by multi-layer perceptron (MLP) neural network.

Gasoline particulate filters (GPF) recently entered the market, and are already regarded a state-of-the-art solution for gasoline exhaust aftertreatment systems to enable EU6d-TEMP fulfilment and beyond. Especially for coated GPF applications, the prognosis of the emission conversion performance over lifetime poses an ambitious challenge, which significantly influences future catalyst diagnosis calibrations. The paper presents key-findings for the different GPF application variants. In the first part, experimental GPF ash loading results are presented. Ash accumulates as thin wall layers and short plugs, but does not penetrate into the wall. However, it suppresses deep bed filtration of soot, initially decreasing the soot-loaded backpressure. For the emission calibration, the non-linear backpressure development complicates the soot load monitoring, eventually leading to compromises between high safety against soot overloading and a low number of active regenerations.

Lean burn gasoline spark-ignition engines can support the reduction of CO2 emissions for future hybrid passenger cars. Very high efficiencies and very low NOx raw emissions can be achieved, if relative air/fuel ratios λ of 2 and above can be reached. The biggest challenge here is to assure a reliable ignition process and to enhance the fuel oxidation in order to achieve a short burn duration and a good combustion stability. This article aims at introducing an innovative combustion system fully optimized for ultra-lean operation and very high efficiency. Thereto, a new cylinder head concept has been realized with high peak firing pressure capability and with a low surface-to-volume ratio at high compression ratios. 1D and 3D simulations have been performed to optimize the compression ratio, charge motion and intake valve lift. Numerical calculations also supported the development of the ignition system.

In order to reduce pollutant and CO2 emissions and fulfill future legislative requirements, powertrain electrification is one of the key technologies. In this context, especially 48V technologies offer an attractive cost to CO2 reduction ratio. 48V mild hybrid powertrains greatly benefit from additional electric intake air compression (E-Charging) and direct torque assist by an electric machine (E-Boosting). Both systems significantly improve the transient engine behavior while reducing the low end torque drawbacks of extreme downsizing and downspeeding. Since E-Charging and E-Boosting have different characteristics concerning transient torque response and energy efficiency, application of model predictive control (MPC) is a particularly suitable method to improve the operating strategy of these functions. MPC requires fast running real-time capable models that are challenging to develop for systems with pronounced nonlinearities.

To achieve global market and brand specific drivability characteristics as unique selling proposition for the increasing number of passenger car derivatives, an objectified evaluation approach for the drivability capabilities of the various cars is required. Thereto, it is necessary to evaluate the influence of different engine concepts in various complex and interlinked powertrain topologies during engine load change maneuvers based on physical criteria. Such an objectification approach enables frontloading of drivability related engineering tasks by the execution of drivability development and calibration work within vehicle subcomponent-specific closed-loop real-time co-simulation environments in early phases of a vehicle development program. So far, drivability functionalities could be developed and calibrated only towards the end of a vehicle development program, when test vehicles with a sufficient level of product maturity became available.

Direct injection (DI) of compressed natural gas (CNG) is a promising technology to increase the indicated thermal efficiency of internal combustion engines (ICE) while reducing exhaust emissions and using a relatively low-cost fuel. However, design and analysis of DI-CNG engines are challenging because supersonic gas jet emerging from the DI injector results in a very complex in-cylinder flow field containing shocks and discontinuities affecting the fuel-air mixing. In this article, numerical simulations are used supported by validation to investigate the direct gas injection and its influence on the flow field and mixing in an optically accessible ICE. The simulation approach involves computation of the in-nozzle flow with highly accurate Large-Eddy Simulations, which are then used to obtain a mapped boundary condition. The boundary condition is applied in Unsteady Reynolds Averaged Navier-Stokes simulations of the engine to investigate the in-cylinder velocity and mixing fields.

Virtual system integration and testing using hardware-in-the-loop (HiL) simulation enables front-loading of development tasks, provides a safer and reliable testing environment and reduces prototype hardware costs. One of the greatest challenges to overcome when performing HiL simulations is assuring a high model accuracy under stringent real-time requirements with acceptable development effort. This article represents a novel solution by deriving the plant model for HiL directly from the existing detailed models from the component layout phase using co-simulation methodology. It provides an effective and efficient model implementation and validation process followed by detailed quantitative analysis of the test results referred to the engine test bench measurements.

Direct injection (DI) compressed natural gas (CNG) engines are emerging as a promising technology for highly efficient and low-emission engines. However, the design of DI systems for compressible gas is challenging due to supersonic flows and the occurrence of shocks. An outwardly opening poppet-type valve design is widely used for DI-CNG. The formation of a hollow cone gas jet resulting from this configuration, its subsequent collapse, and mixing is challenging to characterize using experimental methods. Therefore, numerical simulations can be helpful to understand the process and later to develop models for engine simulations. In this article, the results of high-fidelity large-eddy simulation (LES) of a stand-alone injector are discussed to understand the evolution of the hollow cone gas jet better.

Using a holistic 1D engine simulation approach for the modelling of full-transient engine operation, allows analyzing future engine concepts, including its exhaust gas aftertreatment technology, early in the development process. Thus, this approach enables the investigation of both important fields - the thermodynamic engine process and the aftertreatment system, together with their interaction in a single simulation environment. Regarding the aftertreatment system, the kinetic reaction behavior of state-of-the-art and advanced components, such as Diesel Oxidation Catalysts (DOC) or Selective Catalytic Reduction Soot Filters (SCRF), is being modelled. Furthermore, the authors present the use of the 1D engine and exhaust gas aftertreatment model on use cases of variable valve train (VVT) applications on passenger car (PC) diesel engines.

With the implementation of the “Worldwide harmonized Light duty Test Procedure” (WLTP) and the highly dynamic “Real Driving Emissions” (RDE) tests in Europe, different engineering methodologies from virtual calibration approaches to Engine-in-the-loop (EiL) methods have to be considered to define and calibrate efficient exhaust gas aftertreatment technologies without the availability of prototype vehicles in early project phases. Since different types of testing facilities can be used, the effects of test benches as well as real and virtual vehicle operators have to be determined. Moreover, in order to effectively reduce harmful emissions, the reproducibility of test cycles is essential for an accurate and efficient application of exhaust gas aftertreatment systems and the calibration of internal combustion engines.

In-use compliance under LEV III emission standards, GHG, and fuel economy targets beyond 2025 poses a great opportunity for all ICE-based propulsion systems, especially for light-duty diesel powertrain and aftertreatment enhancement. Though diesel powertrains feature excellent fuel-efficiency, robust and complete emissions controls covering any possible operational profiles and duty cycles has always been a challenge. Significant dependency on aftertreatment calibration and configuration has become a norm. With the onset of hybridization and downsizing, small steps of improvement in system stability have shown a promising avenue for enhancing fuel economy while continuously improving emissions robustness. In this paper, a study of current key technologies and associated emissions robustness will be discussed followed by engine and aftertreatment performance target derivations for LEV III compliant powertrains.