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This paper describes a novel design and verification process for analytical methods used in the development of advanced combustion strategies in internal combustion engines (ICE). The objective was to improve brake thermal efficiency (BTE) as part of the US Department of Energy SuperTruck program. The tools and methods herein discussed consider spray formation and injection schedule along with piston bowl design to optimize combustion efficiency, air utilization, heat transfer, emission, and BTE. The methodology uses a suite of tools to optimize engine performance, including 1D engine simulation, high-fidelity CFD, and lab-scale fluid mechanic experiments. First, a wide range of engine operating conditions are analyzed using 1-D engine simulations in GT Power to thoroughly define a baseline for the chosen advanced engine concept; secondly, an optimization and down-select step is completed where further improvements in engine geometries and spray configurations are considered.

This paper describes the development of a novel data model for storing and sharing data obtained from engine experiments, it then outlines a methodology for automatic model development and applies it to a state-of-the-art engine combustion model (including chemical kinetics) to reduce corresponding model parameter uncertainties with respect engine experiments. These challenges are met by adopting the latest developments in the semantic web to create a shared data model resource for the IC engine development community. The relevant data can be extracted and then used to set-up simulations for parameter estimation by passing it to the relevant application models. A methodology for incorporating experimental and model uncertainties into the model optimization procedure is presented.

A previously presented robust and fast diagnostic NOx model was modified into a predictive model. This was done by using simple yet physically-based models for fuel injection, ignition delay, premixed heat release rate and diffusion combustion heat release rate. The model can be used both for traditional high temperature combustion and for high-EGR low temperature combustion. It was possible to maintain a high accuracy and calculation speed of the NOx model itself. The root mean square of the relative model error is 16 % and the calculation speed is around one second on a PC. Combustion characteristics such as ignition delay, CA50 and the general shape of the heat release rate are well predicted by the combustion model. The model is aimed at real time NOx calculation and optimization in a vehicle on the road.

A performance investigation of Front Underride Protection Devices (FUPDs) with varying collision interface is presented by monitoring occupant compartment intrusion of Toyota Yaris and Ford Taurus FEA models in LS-DYNA. A newly proposed simplified dual-spring system is developed and validated for this investigation, offering improvements over previously employed fixed-rigid simplified test rigs. The results of three tested collision interface profiles were used to guide the development of two new underride protection devices. In addition, these devices were set to comply with Volvo VNL packaging limitations. Topology optimization is used to aid engineering intuition in establishing appropriate load support paths, while multi-objective optimization subject to simultaneous quasi-static loading ensures minimal mass and deformation of the FUPDs.

Partially premixed combustion (PPC) has shown to produce high gross indicated efficiencies while yielding lower pollutant emissions, such as oxides of nitrogen and soot, than conventional diesel combustion. Gasoline fuels with a research octane number (RON) of 60-70 have been proposed as optimal for PPC as they balance the trade-off between ensuring good combustion stability at low engine loads and avoiding excessive peak pressure rise rates at high loads. However, measures have to be taken when optimizing the engine operating parameters to avoid soot emissions. In contrast, methanol has a much lower propensity for soot formation. However, due to a higher RON of methanol the required intake temperature is higher for the same engine compression ratio to ensure auto-ignition at an appropriate timing. Increasing the compression ratio allows a lower intake temperature and improves combustion stability as well as engine brake efficiency.

This paper will review several different emission control systems for heavy duty diesel (HDD) applications aimed at future legislations. The focus will be on the (DOC+CSF+SCR+ASC) configuration. As of today, various SCR technologies are used on commercial vehicles around the globe. Moving beyond EuroVI/US10 emission levels, both fuel consumption savings and higher catalyst system efficiency are required. Therefore, significant system optimization has to be considered. Examples of this include: catalyst development, optimized thermal management, advanced urea dosing calibrations, and optimized SCR inlet NO:NO2 ratios. The aim of this paper is to provide a thorough system screening using a range of advanced SCR technologies, where the pros and cons from a system perspective will be discussed. Further optimization of selected systems will also be reviewed. The results suggest that current legislation requirements can be met for all SCR catalysts under investigation.

One promising method for reducing fuel consumption and emissions, particularly in heavy duty trucks, is platooning. As the distance between vehicles decreases, the following vehicles will experience less aerodynamic drag on the front of the vehicle. However, reducing the velocity of the air contacting the front of the vehicle could have adverse effects on the temperature of the engine. To compensate for this effect, the energy consumption of the engine cooling system might increase, ultimately limiting the overall improvements obtained with platooning. Understanding the coupling between drag reduction and engine cooling load requirement is key for successfully implementing platooning strategies. Additionally, in a Connected and Automated Vehicle (CAV) environment, where information of the future engine load becomes available, the operation of the cooling system can be optimized in order to achieve the maximum fuel consumption reduction.

Heavy-duty vehicles are primarily powered by diesel fuel, emitting CO2 emissions regardless of the exhaust after-treatment system. Contrastingly, a hydrogen engine has the potential to decarbonize the transportation sector as hydrogen is a carbon free, renewable fuel. In this study, a multi-physics 1D simulation tool (GT-Power) is used to model the gas exchange process and performance prediction of a two-stroke hydrogen engine. The aim is to establish a maximum torque-level for a four-stroke hydrogen engine and then utilize different methods for two-stroke modeling to achieve similar torque by optimizing the gas exchange process. A camless engine is used as base, enabling the flexibility to utilize approximately square valve lift profiles. The preliminary step is the GT-Power model validation, which has been done using diesel and hydrogen engines (single-cylinder heavy-duty) experiments at different operating points (871 rpm, 1200 rpm, 1259 rpm, and 1508 rpm).