Search Results

Abstract This study demonstrates the defossilized operation of a heavy-duty port-fuel-injected dual-fuel engine and highlights its potential benefits with minimal retrofitting effort. The investigation focuses on the optical characterization of the in-cylinder processes, ranging from mixture formation, ignition, and combustion, on a fully optically accessible single-cylinder research engine. The article revisits selected operating conditions in a thermodynamic configuration combined with Fourier transform infrared spectroscopy. One approach is to quickly diminish fossil fuel use by retrofitting present engines with decarbonized or defossilized alternatives. As both fuels are oxygenated, a considerable change in the overall ignition limits, air–fuel equivalence ratio, burning rate, and resistance against undesired pre-ignition or knocking is expected, with dire need of characterization.

Abstract Driving schedule of every vehicle involves transient operation in the form of changing engine speed and load conditions, which are relatively unchanged during steady-state conditions. As well, the results from transient conditions are more likely to reflect the reality. So, the current research article is focused on analyzing the biofuel-like lemon peel oil (LPO) behavior under real-world transient conditions with fuel injection parameter MAP developed from steady-state experiments. At first, engine parameters and response MAPs are developed by using a response surface methodology (RSM)-based multi-objective optimization technique. Then, the vehicle model has been developed by incorporating real-world transient operating conditions. Finally, the developed injection parameters and response MAPs are embedded in the vehicle model to analyze the biofuel behavior under transient operating conditions.

Abstract The two-branch exhaust of an asymmetric twin-scroll turbocharged engine are asymmetrically and periodically complicated, which has great impact on turbine matching. In this article, a matching effect of turbine speed parameter on asymmetric twin-scroll turbines based on the exhaust pulse energy weight distribution of a heavy-duty diesel engine was introduced. First, it was built as an asymmetric twin-scroll turbine matching based on exhaust pulse energy distribution. Then, by comparing the average matching point and energy matching points on the corresponding turbine performance map, it is revealed that the turbine speed parameter of energy matching points was a significant deviation from the turbine speed parameter under peak efficiency, which leads to the actual turbine operating efficiency lower than the optimal state.

Abstract Asymmetric twin-scroll turbocharging technology, as one of the effective technologies for balancing fuel economy and nitrogen oxide emissions, has been widely studied in the past decade. In response to the ever-increasing demands for improved fuel efficiency and reduced exhaust emissions, extensive research efforts have been dedicated to investigating various aspects of this technology. Researchers have conducted both experimental and simulation studies to delve into the intricate flow mechanism of asymmetric twin-scroll turbines. Furthermore, considerable attention has been given to exploring the optimal matching between asymmetric twin-scroll turbines and engines, as well as devising innovative flow control methods for these turbines. Additionally, researchers have sought to comprehend the impact of exhaust pulse flow on the performance of asymmetric twin-scroll turbines.

Abstract Heavy-duty on-road engines are expected to conform to an ultralow NOx (ULNOx) standard of 0.027 g/kWh over the composite US heavy-duty transient federal test procedure (HD-FTP) cycle by 2031, a 90% reduction compared to 2010 emissions standards. Additionally, these engines are expected to conform to Phase 2 greenhouse gas regulations, which require tailpipe CO2 emissions under 579 g/kWh. This study experimentally demonstrates the ability of high fuel stratification gasoline compression ignition (HFS-GCI) to satisfy these emissions standards. Steady-state and transient tests are conducted on a prototype multi-cylinder heavy-duty GCI engine based on a 2010-compliant Cummins ISX15 diesel engine with a urea-SCR aftertreatment system (ATS). Steady-state calibration exercises are undertaken to develop highly fuel-efficient GCI calibration maps at both cold-start and warmed up conditions.

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Abstract Due to the incoming phase out of fossil fuels from the market in order to reduce the carbon footprint of the automotive sector, hydrogen-fueled engines are candidate mid-term solution. Thanks to its properties, hydrogen promotes flames that poorly suffer from the quenching effects toward the engine walls. Thus, emphasis must be posed on the heat-up of the oil layer that wets the cylinder liner in hydrogen-fueled engines. It is known that motor oils are complex mixtures of a number of mainly heavy hydrocarbons (HCs); however, their composition is not known a priori. Simulation tools that can support the early development steps of those engines must be provided with oil composition and properties at operation-like conditions. The authors propose a statistical inference-based optimization approach for identifying oil surrogate multicomponent mixtures. The algorithm is implemented in Python and relies on the Bayesian optimization technique.

Abstract The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen-based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This article introduces the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy-duty (HD) fuel cell electric commercial vehicles (FCEV).

Abstract Numerous researchers are committed to finding solutions to the path planning problem of intelligence-based vehicles. How to select the appropriate algorithm for path planning has always been the topic of scholars. To analyze the advantages of existing path planning algorithms, the intelligence-based vehicle path planning algorithms are classified into conventional path planning methods, intelligent path planning methods, and reinforcement learning (RL) path planning methods. The currently popular RL path planning techniques are classified into two categories: model based and model free, which are more suitable for complex unknown environments. Model-based learning contains a policy iterative method and value iterative method. Model-free learning contains a time-difference algorithm, Q-learning algorithm, state-action-reward-state-action (SARSA) algorithm, and Monte Carlo (MC) algorithm.

Abstract Certain advanced driver assistance systems (ADAS) have the potential to boost energy efficiency in real-world scenarios. This article details a radar-based driver assistance scheme designed to minimize fuel consumption for a commercial vehicle by predictively optimizing braking and driving torque inputs while accommodating the driver’s demand. The workings of the proposed scheme are then assessed with a novel integration of the driver assistance functionality in randomized traffic microsimulation. Although standardized test procedures are intended to mimic urban and highway speed profiles for the purposes of evaluating fuel economy and emissions, they do not explicitly consider the interactions present in real-world driving between the ego vehicle equipped with ADAS and other vehicles in traffic. This article presents one approach to address the drawback of standardized test procedures for evaluating the fuel economy benefits of ADAS technologies.

Abstract A modelling tool has been developed for the prediction of fuel effects on the performance and exhaust emissions of a heavy-duty diesel engine. Recurrent neural network models with duty-cycle, engine control, and fuel property parameters as inputs were trained with transient test data from a 15-liter heavy-duty diesel engine equipped with a common-rail fuel injection system and a variable geometry turbocharger. The test fuels were formulated by blending market diesel fuels, refinery components, and biodiesel to provide variations in preselected fuel properties, namely, hydrogen-to-carbon (H/C) ratio, oxygen-to-carbon (O/C) ratio, derived cetane number (CN), viscosity, and mid- and end-point distillation parameters. Care was taken to ensure that the correlation between these fuel properties in the test fuel matrix was minimized to avoid confounding model input variables.

Abstract Gasoline compression ignition (GCI) is a promising combustion technology that can help the commercial transportation sector achieve operational flexibility and meet upcoming criteria pollutant regulations. However, high-pressure fuel injection systems (>1000 bar) are needed to enable GCI and fully realize its benefits compared to conventional diesel combustion. This work is a continuation of previous durability studies that identified three key technical risks after running gasoline-like fuel through a heavy-duty, common rail injection system: (i) cavitation damage to the inlet check valve of the high-pressure pump, (ii) loss of injector fueling capacity, (iii) cavitation erosion of the injector nozzle holes. Upgraded hardware solutions were tested on a consistent 400- to 800-hour NATO durability cycle with the same gasoline-like fuel as previous studies. The upgraded pump showed no signs of abnormal wear or cavitation damage to the inlet check valve.

Abstract The development of a long-term sustainable hydrogen energy economy for commercial vehicle transportation will need to overcome key critical technical and logistics considerations in the near term. As compared to zero-emission powertrains, fossil-fuel-based powertrains provide mission flexibility and high uptime at a comparatively low total cost of ownership (TCO). While the incumbent carbon-intensive powertrains suffer from poor efficiency and are not sustainable to support global climate change initiatives in transportation decarbonization, techno-economic challenges continue to create complex barriers to the large-scale displacement of these with highly electrified powertrains architectures. This article specifically addresses opportunities that well-targeted subsidies would afford in achieving fuel cell electric powertrain financial parity with diesel powertrains in heavy-duty trucks (HDTs).

Abstract This article addresses the architecture development for a commercial vehicle fuel cell electric powertrain by establishing a clear multi-step formalized workflow that employs a unique technoeconomic solution for architecture selection. The power capability of the fuel cell, the energy capacity and chemistry of the electrical energy storage (battery), the DC-DC converter (including the input current rating and isolation resistance requirements), the traction drive solution, the on-board hydrogen storage solution, and the real-time power-split management of the fuel cell and the battery are all considered and developed in this effort. The methods were used to select architecture for Class 8 urban, regional, and line haul applications. When compared to traditional load-following power-split controllers, an energy management power-split controller can increase system energy efficiency by up to 19.5%.

Abstract Optical combustion phenomena investigation is a common tool for passenger car and automotive engines. Large-bore engines for stationary and mobile applications, on the other hand, have a lower optical examination density. This is mainly due to the technically more complex design of the optical accesses that have to provide a larger field of view and withstand high mechanical and thermal loads. Nevertheless, an optical investigation of in-cylinder phenomena in large-bore engines is essential to optimize efficient and environmentally friendly combustion processes using new sustainable e-fuels. To realize a simple optical access with maximum observability of the combustion chamber, a fisheye optic for the direct integration into internal combustion engines was developed and used for in-cylinder Mie-scattering investigations of diesel and Oxymethylene Ether (OME3-5) pilot fuel spray of natural gas dual-fuel combustion processes in a MAN 35/44DF single-cylinder research engine.

Abstract The sustainability of mines is becoming ever more important to reduce the greenhouse gas footprint and keep the resources extraction economically sustainable. Despite the electrification and hybridization trend of mining equipment, diesel engines are still expected to maintain their importance as a primary source of power especially for open pit equipment, thanks to their longer operating range. However, in order to keep high efficiency and minimize fuel consumption for the entire operating life it is crucial to understand and tackle the aging effect on the engine performance. In this research a 500-h durability test was performed on a Liebherr mining engine, with the aim of better understanding how aging affects the combustion process and engine performance (power and fuel consumption), and how this effect can be compensated. Experimental results show a 1% specific fuel consumption increase, ascribable to injector aging.

Abstract The demand for contactless, rapid manufacturing has increased over the years, especially during the COVID-19 pandemic. Additive manufacturing (AM), a type of rapid manufacturing, is a computer-based system that precisely manufactures products. It proves to be a faster, cheaper, and more efficient production system when integrated with cloud-based manufacturing (CBM). Similarly, the need for semiconductors has grown exponentially over the last five years. Several companies could not keep up with the increasing demand for many reasons. One of the main reasons is the lack of a workforce due to the COVID-19 protocols. This article proposes a novel technique to manufacture semiconductor chips in a fast-paced manner. An algorithm is integrated with cloud, machine vision, sensors, and email access to monitor with live feedback and correct the manufacturing in case of an anomaly.

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Abstract This study investigates the impact of converting a medium-duty conventional truck powertrain to a fuel cell electric type. The powertrain proposed in this study is purely powered up with the fuel cell without any battery to reduce the cost and weight. To compare the performance of the conventional and the fuel cell electric powertrains, both are numerically modeled and analyzed in AVL software for the Urban Driving Cycle (UDC) at various cargo loads. The final drive transmission (FDT) speed and input and output torques are first matched for both powertrains. The power distribution analysis is conducted to evaluate the power consumption and powertrain losses at various cruising speeds during the UDC. Furthermore, the equivalent fuel consumption of both powertrains is compared with each other. By converting the powertrain to a fuel cell, the power required to run the vehicle at low, moderate, and high cruising speeds decreased by almost 68%, 30%, and 7.12%, respectively.

Abstract The concurrent combustion of Diesel and hydrogen in a 1999 Cummins ISM 370 heavy-duty compression ignition engine was computationally investigated using a three-dimensional (3-D) computational fluid dynamics (CFD) solver and compared to literature reference data of the engine operated at 1200 rpm and 70% load. Multiple computational combustion models and chemical mechanisms spanning from global single-step kinetic reaction mechanisms, equilibrium reactions, to detailed reduced mechanisms of 118 to 128 reversible kinetic reactions were considered, along with several chemistry solvers of varying levels of sophistication. The results showed that all models based on single-step global kinetic Diesel mechanisms failed to accurately predict ignition timing, leading to significant overprediction of the maximum in-cylinder pressures.