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Combustion engines in hybrid vehicles turn on and off several times during a typical passenger car trip. Each engine restart may pose a risk of excessive tailpipe emissions in real-drive conditions if the after-treatment system fails to maintain an adequate temperature level during zero flow. In view of the tightening worldwide tailpipe emissions standards and real-world conformity requirements, it is important to detect and resolve such risks via cost-effective engineering tools relying on accurate 3d analysis of the thermal and chemical behavior of exhaust systems. In this work, we present a series of experiments to examine the impact of zero-flow duration on the exhaust system cooling and subsequent emissions risk. We also present a catalyst model calibrated to predict the 3d thermal and chemical behavior under normal and zero flow conditions. Particular emphasis is given to the phenomena of free convection and thermal radiation dominating the heat transfer at zero flow.

The growing global adoption of electric vehicles (EVs) emphasizes the pressing need for a comprehensive understanding of thermal runaway in lithium-ion batteries. Prevention of the onset of thermal runaway and its subsequent propagation throughout the entire battery pack is one of the pressing challenges of lithium-ion batteries. In addition to generating excess heat, thermal runaway of batteries also releases hazardous flammable gases, posing risks of external combustion and fires. Most existing thermal runaway models in literature primarily focus on predicting heat release or the total amount of vent gas. In this study, we present a model capable of predicting both heat release and the transient composition of emitted gases, including CO, H2, CO2, and hydrocarbons, during thermal runaway events. We calibrated the model using experimental data obtained from an 18650 cell from the literature, ensuring the accuracy of reaction parameters.

The global transition to alternative power sources, particularly fuel cells, hinges on the cost-effective production and distribution of hydrogen fuel. While green hydrogen produced through water electrolysis using renewable energy sources holds immense promise, it currently falls short of meeting the burgeoning demand for hydrogen. To address this challenge, alternative methods, such as steam reforming and partial oxidation of hydrocarbon fuels with integrated carbon capture, are poised to bridge the gap between supply and demand in the near to midterm. Steam reforming of methane is a well-established technology with a proven track record in the chemical industry, serving as a dependable source of hydrogen feedstock for decades. However, to meet the demand for efficient hydrogen storage, handling, and onboard reforming, researchers are increasingly exploring liquid hydrocarbon fuels at room temperature, such as methanol and ethanol.

Hydrogen-based fuel cell electric vehicles are a promising alternative to pure battery electric vehicles (BEV) in heavy-duty (HD) truck applications, due to lower weight penalty on the cargo mass, a higher range, and a lower refueling time. The overall drivetrain optimization (including battery and fuel cell sizing) requires an efficient and robust energy management concept, capable of exploiting the maximum system fuel saving potential, while considering critical component health metrics. In recent years, the Equivalent Consumption Minimization Strategy (ECMS) has demonstrated its capability to meet those requirements when applied to passenger car hybrid powertrains. In a traditional implementation, the ECMS-based control policy is typically calculated a-priori, based on steady state operating conditions. The solutions are then implemented as look up tables in the final dynamic model.

Fuel economy improvement of Class 8 long-haul trucks has been a constant topic of discussion in the commercial vehicle industry due to the significant potential it offers in reducing GHG emissions and operational costs. Among the different vehicle categories in on-road transportation, Class 8 long-haul trucks are a significant contributor to overall GHG emissions. Furthermore, with the upcoming 2027 GHG emission and low-NOx regulations, advanced powertrain technologies will be needed to meet these stringent standards. Connectivity-based powertrain optimization is one such technology that many fleets are adopting to achieve significant fuel savings at a relatively lower technology cost. With advancements in vehicle connectivity technologies for onboard computing and sensing, the full potential of connected vehicles in reducing fuel consumption can be realized through V2X (Vehicle-to-Everything) communication.

Numerical simulation of in-cylinder processes can significantly reduce the development and refinement costs of engines. While it can be argued that higher fidelity models improve accuracy of prediction, it comes at the expense of high computational cost. In this respect, a 3D analysis of in-cylinder processes may not be feasible for evaluating large number of design and operating conditions. The situation can be more foreboding for transient simulations. In the current work a phenomenological combustion modeling approach is explored that can be implemented in a lower fidelity modeling framework and can approach the accuracy of higher dimensional models with significant reduction in computational cost. The proposed model uses transported probability density function (tPDF) method within a 0D framework to provide a computationally efficient solution while capturing the essential physics of in-cylinder combustion.

The requirements set for the next-generation powertrain systems (e.g. performance and emissions) are becoming increasingly stringent with ever-shortening time-to-markets at reduced costs. To remain competitive automotive companies are progressively relying on model-driven development and virtual testing. Virtual test benches, such as HiL (Hardware-in the-Loop) simulators, are powerful tools to reduce the amount of physical testing and speed up engine software calibration process. The introduction of these technologies places new, often conflicting demands (such as higher predictability, faster simulation speed, and reduced calibration effort) upon simulation models used at HiL test benches. The new models are also expected to offer compliance to industry standards, performance and usability to further increase the usage of virtual tests in powertrain development.

In this paper, a fuel tank evaporation/condensation model was developed, which was suitable for calculation of evaporative emissions in a fuel tank. The model uses a diffusion-controlled mass transfer approach in the form of Fick's second law in order to calculate the average concentration of fuel vapor above the liquid level and its corresponding evaporation rate. The partial differential equation of transient species diffusion was solved using a separation of variables technique with the appropriate boundary conditions for a fuel tank. In order to simplify the solution, a quasi-steady assumption was utilized and justified. The fuel vapor pressure was modeled based on an American Petroleum Institute (API) procedure using either a distillation curve or a Reid Vapor Pressure (RVP) as an experimental input for the specific fuel used in the system.

The present paper aims at developing an innovative procedure to create a one-dimensional (1D) real-time capable simulation model for a heavy-duty diesel engine. The novelty of this approach is the use of the top-level engine configuration, test cell measurement data, and manufacturer maps as opposite to common practice of utilizing a detailed 1D engine model. The objective is to facilitate effective model adjustments and hence further increase the application of Hardware-in-the-Loop (HiL) simulations in powertrain development. This work describes the development of Fast Running Model (FRM) in GT-SUITE simulation software. The cylinder and gas-path modeling and calibration are described in detail. The results for engine performance and exhaust emissions produced satisfactory agreement with both steady-state and transient experimental data.

In order to meet emissions and power requirements, modern engine design has evolved in complexity and control. The cost and time restraints of calibration and testing of various control strategies have made virtual testing environments increasingly popular. Using Hardware-in-the-Loop (HiL), Volvo Penta has built a virtual test rig named VIRTEC for efficient engine testing, using a model simulating a fully instrumented engine. This paper presents an innovative Artificial Neural Network (ANN) based model for engine simulations in HiL environment. The engine model, herein called Artificial Neural Network Engine (ANN-E), was built for D8-600 hp Volvo Penta engine, and directly implemented in the VIRTEC system. ANN-E uses a combination of feedforward and recursive ANNs, processing 7 actuator signals from the engine management system (EMS) to provide 30 output signals.

Particulate matter emissions from gasoline direct injection engines are a concern due to the health effects associated with ultrafine particles. This experimental study investigated sources of particulate matter emissions variability observed in previous tests and also examined the effect of ethanol content in gasoline on particle number (PN) concentrations and particle mass (PM) emissions. FTIR measurements of gas phase hydrocarbon emissions provided evidence that changes in fuel composition were responsible for the variability. Exhaust emissions of toluene and ethanol correlated positively with emitted PN concentrations, while emissions of isobutylene correlated negatively. Exhaust emissions of toluene and isobutylene were interpreted as markers of gasoline aromatic content and gasoline volatility respectively.

Large-scale emergency or off-grid power generation is typically achieved through diesel or natural gas generators. To meet governmental emission requirements, emission control systems (ECS) are required. In operation, effective control over the generator’s acoustic emission is also necessary, and can be accomplished within the ECS system. Plug flow mufflers are commonly used, as they provide a sufficient level of noise attenuation in a compact structure. The key design parameter is the transmission loss of the muffler, as this dictates the level of attenuation at a given frequency. This work implements an analytically decoupled solution, using multiple perforate impedance models, through the transfer matrix method (TMM) to predict the transmission loss based on the muffler geometry. An equivalent finite element model is implemented for numerical simulation. The analytical results and numerical results are then evaluated against experimental data from literature.

This study investigates the life cycle greenhouse gas (GHG) emissions of a set of vehicles using two real-world gliders (vehicles without powertrains or batteries); a steel-intensive 2013 Ford Fusion glider and a multi material lightweight vehicle (MMLV) glider that utilizes significantly more aluminum and carbon fiber. These gliders are used to develop lightweight and conventional models of internal combustion engine vehicles (ICV), hybrid electric vehicles (HEV), and battery electric vehicles (BEV). Our results show that the MMLV glider can reduce life cycle GHG emissions despite its use of lightweight materials, which can be carbon intensive to produce, because the glider enables a decrease in fuel (production and use) cycle emissions. However, the fuel savings, and thus life cycle GHG emission reductions, differ substantially depending on powertrain type. Compared to ICVs, the high efficiency of HEVs decreases the potential fuel savings.

Biodiesel and other renewable fuels are of interest due to their impact on energy supplies as well as their potential for carbon emissions reductions. Waste animal fats from meat processing facilities, which would otherwise be sent to landfill, have been proposed as a feedstock for biodiesel production. Emissions from biodiesel fuels derived from vegetable oils have undergone intense study, but there remains a lack of data describing the emissions implications of using animal fats as a biodiesel feedstock. In this study, emissions of NOx, unburned hydrocarbons and particulate matter from a compression ignition engine were examined. The particulate matter emissions were characterized using gravimetric analysis, elemental carbon analysis and transmission electron microscopy. The emissions from an animal fat derived B20 blend were compared to those from petroleum diesel and a soy derived B20 blend.

TPO is being used to make automotive parts for its number of advantages: i) low temperature flexibility and ductility, ii) excellent impact/stiffness/flow balance, iii) excellent weatherability, and iv) free-flowing pellet form for easy processing, storage, and handling. However, by foaming TPO, due to its higher rigidity-to-weigh ratio, it would offer additional advantages over the solid counterparts in terms of reduced weight, reduced material cost, and decreased fuel usage without compromising their performance. Since a major component in TPO is polypropylene (PP), understanding PP foaming behaviours is an important step towards understanding TPO foaming. For foam materials, cell density and cell size are two significant parameters that affect their material properties. In this research, we observed the cell nucleation and initial growth behaviours of PP foams blown with CO2 under various experimental conditions in a batch foaming simulation system.

This paper presents an experimental study on the foaming behavior of recyclable high-melt-strength (HMS) branched polypropylene (PP) with CO2 as a blowing agent. The foamability of branched HMS PP has been evaluated using a tandem foaming extruder system. The effects of CO2 and nucleating agent contents on the final foam morphology have been thoroughly investigated. The low density (i.e., 12~14 fold), fine-celled (i.e., 107–109 cells/cm3) PP foams were successfully produced using a small amount of talc (i.e., 0.8 wt%) and 5 wt% CO2.

This paper demonstrates the effects of nano-clay on the microcellular foam processing of nylon. First, Nylon 6 nanocomposites with 1 wt% clay were prepared by a twin screw extruder. The nanocomposite structures were characterized by XRD and TEM. Nylon and its nanocomposites were foamed in extrusion using CO2. The cell morphologies of nylon and its nanocomposite foams were investigated. It appeared that the nano-clay not only enhanced cell nucleation, but also suppressed cell deterioration in the microcellular foaming of nylon.

Eco-efficient and cost effective natural fibre - thermoplastic composites have gained attention to a great extent in the automotive industry. Most of the OEM specifications for automotive interior parts, for example, instrument panels, recommend the composite should have a minimum flexural modulus of 1900 MPa, a notched Impact strength greater than 150 J/m at room temperature and a melt flow index of 5 g/10min and above [1, 2 and 3]. The objective of this work was to develop a high performance hybrid composite by injection molding process of the composites made from natural fibre in combination with glass fibre or calcium carbonate in a thermoplastic matrix to meet the specifications required for automotive interior parts applications. Mechanical properties, such as tensile and flexural strengths and moduli of the composites prepared, were found to be highly promising.

A comparison of scanning mobility particle sizer (SMPS) and laser-induced incandescence (LII) measurements of diesel particulate matter (PM) was performed. The results reveal the significance of the aggregate nature of diesel PM on interpretation of size and volume fraction measurements obtained with an SMPS, and the accuracy of primary particle size measurements by LII. Volume fraction calculations based on the mobility diameter measured by the SMPS substantially over-predict the space-filling volume fraction of the PM. Correction algorithms for the SMPS measurements, to account for the fractal nature of the aggregate morphology, result in a substantial reduction in the reported volume. The behavior of the particulate volume fraction, mean and standard deviation of the mobility diameter, and primary particle size are studied as a function of the EGR for a range of steady-state engine speeds and loads for a turbocharged direct-injection diesel engine.

Crevices in the combustion chamber are the main source of hydrocarbon (HC) emissions from spark ignition (SI) engines fuelled by natural gas (NG). Instantaneous in-cylinder and engine exhaust port HC concentrations were measured simultaneously using a Cambustion HFR400 fast response flame ionization detector (FRFID) concentrated on the post-flame period. The raw data was reconstructed to account for variation in the FFRID sample transit time and time constant due to fluctuating in-cylinder pressure. HC concentration development during the post-flame period is discussed. Comparison is made of the post-flame in-cylinder and exhaust port HC concentrations under different engine operating conditions, which gives a better understanding of the mechanism by which HC emissions form from crevices in SI engines.