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The transportation sector still depends on conventional engines in many countries as the alternative technologies are not mature enough to reduce carbon footprints in society. The four-stroke diesel engines, primarily used for heavy-duty applications, need either high intake boosting or a large bore to produce higher torque and power output. There is an alternative where a four-stroke engine operated in two-stroke mode with the help of a fully flexible variable valve actuation (VVA) system can achieve similar power density without raising the intake boosting or engine size. A fully flexible VVA is required to control the valve events (lift, timing, and durations) independently so that the four-stroke events can be completed in one cycle. In this study, 1D-3D CFD coupled simulations were performed to develop a gas exchange process for better air entrapment in the cylinder and evacuate the exhaust products simultaneously.

This paper investigates the tire-road interaction for tires equipped with two different solid rubber material definitions within a Finite Element Analysis virtual environment, ESI PAMCRASH. A Mixed Service Drive truck tire sized 315/80R22.5 is designed with two different solid rubber material definitions: a legacy hyperelastic solid Mooney-Rivlin material definition and an Ogden hyperelastic solid material definition. The popular Mooney-Rivlin is a material definition for solid rubber simulation that is not built with element elimination and is not easily applicable to thermal applications. The Ogden hyperelastic material definition for rubber simulations allows for element destruction. Therefore, it is of interest and more suited for designing a tire model with wear and thermal capabilities.

The present work discusses the potential benefits of using computational fluid dynamics (CFD) simulation and artificial intelligence (AI) in the design and optimization of hydrogen internal combustion engines (H2ICEs). A Machine Learning (ML) model is developed and applied to the CFD simulation data to identify optimal injection system parameters on the Sandia H2ICE Engine to improve the mixing. This approach can aid in developing predictive ML models to guide the design of future H2ICEs. For the current engine configuration, it is observed that hydrogen (H2) gas injection contributes mixing of H2 with air. If the injector parameters are optimized, mixture preparation is better and eventually combustion. A base CFD model is validated from the Sandia H2ICE engine data against Particle Image Velocimetry (PIV) data for velocity and Planar Laser Induced Fluorescence (PLIF) data for H2 mass fraction.

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).

Executable Digital Twins (xDT) are starting a revolution in the industry, where high fidelity simulation models extend their usage from the design and validation phases to in-operation and service phase. Two critical technology blocks in this revolution are Model Order Reduction and Smart Virtual Sensing. The former allows the high-fidelity models to be represented in compact forms and the latter allows to extend the limits of physical sensors and provide full field data combining simulation models and test data in a real-time estimator framework. The smart virtual sensing technology leverages a state-of-the-art Kalman filtering approach to combine the simulation and physical testing. This allows to virtually measure locations that are not accessible with physical sensors due to e.g. physical constrains or high temperatures.

Exhaust aftertreatment systems are essential components in modern powertrains, needed to reach the low legislated levels of NOx and soot emissions. A well designed diesel engine exhaust aftertreatment system can have NOx conversion rates above 95%. However, to achieve high conversion the aftertreatment system must be warm. Because of this, large parts of the total NOx emissions come from cold starts where the engine has been turned off long enough for the aftertreatment system to cool down and loose its capacity to reduce NOx. It is therefore important to understand how the aftertreatment cools down when the engine in turned off. Experimental data for a catalyst cool-down process is presented and analyzed. The analysis shows that it is important to capture the spatial distribution of temperatures both in axial and radial directions. The data and analysis are used to design a catalyst thermal model that can be used for model based catalyst temperature monitoring and control.

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.

This work utilizes previously developed VSB2 (VSB2 Stochastic Blob and Bubble) multicomponent fuel spray model to study significance of using non-ideal thermodynamics for droplet evaporation under direct injection engine like operating conditions. Non-ideal thermodynamics is used to account for vapor-liquid equilibrium arising from evaporation of multicomponent fuel droplets. In specific, the evaporation of ethanol/iso-octane blend is studied in this work. Two compositions of the blend are tested, E-10 and E-85 respectively (the number denotes percentage of ethanol in blend). The VSB2 spray model is implemented into OpenFoam CFD code which is used to study evaporation of the blend in constant volume combustion vessel. Liquid and vapor penetration lengths for the E-10 case are calculated and compared with the experiment. The simulation results show reasonable agreement with the experiment. Simulation is performed with two methods- ideal and non-ideal thermodynamics respectively.

In this paper, computation fluid dynamics (CFD) simulations are employed to describe the effect of flow parameters on the formation of soot and NOx in a heavy duty engine under low load and high load. The complexity of diesel combustion, specially when soot, NOx and other emissions are of interest, requires using a detailed chemical mechanism to have a correct estimation of temperature and species distribution. In this work, Multiple Representative Interactive Flamelets (MRIF) method is employed to describe the chemical reactions, ignition, flame propagation and emissions in the engine. A phenomenological model for soot formation, including soot nucleation, coagulation and oxidation with O2 and OH is incorporated into the flamelet combustion model. Different strategies for modelling NOx are chosen to take into account the longer time scale for NOx formation. The numerical results are compared with experimental data to show the validity of the model for the cases under study.

Exterior turbulent flow is an important source of automobile cabin interior noise. The turbulent flow impacts the windows of the cabins to excite the structural vibration that emits the interior noise. Meanwhile, the exterior noise generated from the turbulent flow can also cause the window vibration and generate the interior noise. Side-view mirrors mounted upstream of the windows are one of the predominant body parts inducing the turbulent flow. In this paper, we investigate the interior noise caused by a generic side-view mirror. The interior noise propagates in a cuboid cavity with a rectangular glass window. The exterior flow and the exterior noise are computed using advanced CFD methods: compressible large eddy simulation, compressible detached eddy simulation (DES), incompressible DES, and incompressible DES coupled with an acoustic wave model. The last method is used to simulate the hydrodynamic and acoustic pressure separately.

In this paper, the turbulent flow induced by a production side-view mirror assembled on a full-scale production truck is simulated using a compressible k-ω SST detached eddy simulation (DES) approach -- the improved delayed DES (IDDES). The truck configuration consists of a compartment and a trailer. Due to the large size and geometric complexity of the configuration, some simplifications are applied to the simulation. A purpose of this work is to investigate whether the simplifications are suitable to obtain the reasonable properties of the flow near the side-view mirror. Another objective is to study the aerodynamic performances of the mirror. The configuration is simplified regarding two treatments. The first treatment is to retain the key exterior components of the truck body while removing the small gaps and structures. Furthermore, the trailer is shaped in an apex-truncated square pyramid.

This paper focuses on predicting the rolling resistance and hydroplaning of a wide base truck tire (Size: 445/50R22.5) on dry and wet surfaces. The rolling resistance and hydroplaning are predicted at various inflation pressures, loads, velocities, and water depths. The wide base truck tire was previously modeled and validated using Finite Element Analysis (FEA) technique in virtual performance software (Pam-Crash). The water is modeled using Smoothed-Particle Hydrodynamics (SPH) method and Murnaghan equation of state. A water layer is first built on top of an FEA rigid surface to represent a wet surface. The truck tire is then inflated to the desired pressure. A vertical load is then applied to the center of the tire. For rolling resistance tests variable constant longitudinal speeds are applied to the center of the tire. The forces in the vertical and longitudinal directions are computed, and the rolling resistance is calculated.

Owing to increased interest in blended fuels for automotive applications, a great deal of understanding is sought for the behavior of multicomponent fuel sprays. This sets a new requirement on spray model since the volatility of the fuel components in a blend can vary substantially. It calls for careful solution to implement the differential evaporation process concerning thermodynamic equilibrium while maintaining a robust solution. This work presents the Volvo Stochastic Blob and Bubble (VSB2) spray model for multicomponent fuels. A direct numerical method is used to calculate the evaporation of multicomponent fuel droplets. The multicomponent fuel model is implemented into OpenFoam CFD code and the case simulated is a constant volume combustion vessel. The CFD code is used to calculate liquid penetration length for surrogate diesel (n-dodecane)-gasoline (iso-octane) blend and the result is compared with experimental data.

When developing new combustion concepts, CFD simulations is a powerful tool. The modeling of spray formation is a challenging but important part when it comes to CFD modelling of non-premixed combustion. There is a large difference in the accuracy and robustness among different spray models and their implementation in different CFD codes. In the work presented in this paper a spray model, designated as VSB2 has been implemented in OpenFOAM. VSB2 differ from traditional spray models by replacing the Lagrangian parcels with stochastic blobs. The stochastic blobs consists of a droplet size distribution rather than equal sized droplets, as is the case with the traditional parcel. The VSB2 model has previously been thoroughly validated for spray formation and combustion of n-heptane. The aim of this study was to validate the VSB2 spray model for ethanol spray formation and combustion as a step in modelling dual-fuel combustion with alcohol and diesel.

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.

Quantification of heat exchanger performance in its operative environment is in many engineering applications an essential task, and the air flow rate through the heat exchanger core is an important optimizing parameter. This paper explores an alternative method for quantifying the air flow rate through compact heat exchangers positioned in the underhood of a passenger car. Unlike conventional methods, typically relying on measurements of direct flow characteristics at discrete probe locations, the proposed method is based on the use of load-cells for direct measurement of the total force acting on the heat exchanger. The air flow rate is then calculated from the force measurement. A direct comparison with a conventional pressure based method is presented as both methods are applied on a passenger car’s radiator tested in a full scale wind tunnel using six different grill configurations. The measured air flow rates are presented and discussed over a wide range of test velocities.

Presented are results from numerical investigations of buoyancy driven flow in a simplified representation of an engine bay. A main motivation for this study is the necessity for a valid correlation of results from numerical methods and procedures with physical measurements in order to evaluate the accuracy and feasibility of the available numerical tools for prediction of natural convection. This analysis is based on previously performed PIV and temperature measurements in a controlled physical setup, which reproduced thermal soak conditions in the engine compartment as they occur for a vehicle parked in a quiescent ambient after sustaining high thermal loads. Thermal soak is an important phenomenon in the engine bay primarily driven by natural convection and radiation after there had been a high power demand on the engine. With the cooling fan turned off and in quiescent environment, buoyancy driven convection and radiation are the dominating modes of heat transfer.

This article presents Computational Fluid Dynamics (CFD) simulations fo one period of a louvered fin, for a crossflow compact finned heat exchanger, where the incoming airflow was inclined relative to its core. Four inclinations were investigated: 90°, which was when the air flowed perpendicular to the heat exchanger, 60°, 30° and 10° angles relative to the vertical plane. The study included three heat exchanger designs, where two of them had symmetrical louvered fins and a thickness of 19mm and 52mm. The third had a thickness of 19mm and had the louvers angled in one direction. All heat exchangers have been simulated when the airflow entered both from above and below relative to the horizontal plane. Simulations have also been carried out when the airflow entered from the side, illustrating the heat exchanger to be angled relative to the vertical axis. Two air speeds have been investigated for each configuration, where the results were compared to experimental data.

The current work investigates a method in 1D modeling of cooling systems including discretized cooling package with non-uniform boundary conditions. In a stacked cooling package the heat transfer through each heat exchanger depends on the mass flows and temperature fields. These are a result of complex three-dimensional phenomena, which take place in the under-hood and are highly non-uniform. A typical approach in 1D simulations is to assume these to be uniform, which reduces the authenticity of the simulation and calls for additional calibrations, normally done with input from test measurements. The presented work employs 3D CFD simulations of complete vehicle in STAR-CCM+ to perform a comprehensive study of mass-flow and thermal distribution over the inlet of the cooling package of a Volvo FM commercial vehicle in several steady-state operating points.

Annual fuel use for long-haul truck rest period idling is estimated at 667 million gallons in the United States. The U.S. Department of Energy's National Renewable Energy Laboratory's CoolCab project aims to reduce heating, ventilating, and air conditioning (HVAC) loads and resulting fuel use from rest period idling by working closely with industry to design efficient long-haul truck climate control systems while maintaining occupant comfort. Enhancing the thermal performance of cab/sleepers will enable smaller, lighter, and more cost-effective idle reduction solutions. In order for candidate idle reduction technologies to be implemented at the original equipment manufacturer and fleet level, their effectiveness must be quantified. To address this need, a number of promising candidate technologies were evaluated through experimentation and modeling to determine their effectiveness in reducing rest period HVAC loads.