Browse Topic: Gas engines
Hexagon Agility announced a collaboration with Norwegian EV transmission supplier Brudeli Green Mobility at the 2024 ACT Expo in Las Vegas. The partnership's goal is the integration of Hexagon Agility's CNG/RNG (compressed/renewable natural gas) systems with Brudeli's plug-in PowerHybrid system. This technology will reportedly offer fleets the capability to maintain diesel ICE duty cycles while providing fuel cost savings and help OEMs achieve global decarbonization goals. “The Brudeli PowerHybrid enables fleet owners to retain the power, performance and fuel cost savings offered by natural gas engines, while simultaneously harnessing the efficiencies of electric,” said Eric Bippus, EVP sales & systems development, Hexagon Agility. “We believe hybrids could play a role in commercial trucking in the future, and we are excited to take an active role bringing that to the market
The study demonstrates the possibility and in particular the method to derive the efficiency of the entire fuel cell power system by measuring specific data of the recirculation path of the anode circuit of a fuel cell system. The results demonstrate the capabilities of the existing test rig and enable investigations on the suitability of auxiliary components. This study focuses on the hydrogen recirculation path equipped with multiple sensors and a needle valve to enable the required operating conditions of the fuel cell. Running a startup load profile without reaching the equilibrium state at all steps, the dynamic of the system and the requirements to the sensor parameters, such as sampling rate and precision, was seen. Additionally, it became obvious that the recirculation pump used is oversized, but a load point shift compensated this artifact. In detail, the stoichiometry and the efficiency of the entire system was evaluated. It was seen that the hydrogen concentration is
In response to global climate change, there is a widespread push to reduce carbon emissions in the transportation sector. For the difficult to decarbonize heavy-duty (HD) vehicle sector, hybridization and lower carbon-intensity fuels can offer a low-cost, near-term solution for CO2 reduction. The use of natural gas can provide such an alternative for HD vehicles while the increasing availability of renewable natural gas affords the opportunity for much deeper reductions in net-CO2 emissions. With this in consideration, the US National Renewable Energy Laboratory launched the Natural Gas Vehicle Research and Development Project to stimulate advancements in technology and availability of natural gas vehicles. As part of this program, Southwest Research Institute developed a hybrid-electric medium-HD vehicle (class 6) to demonstrate a substantial CO2 reduction over the baseline diesel vehicle and ultra-low NOx emissions. The development included the conversion of a 5.2 L diesel engine to
The widely accepted best practice for spark-ignition combustion is the four-valve pent-roof chamber using a central sparkplug and incorporating tumble flow during the intake event. The bulk tumble flow readily breaks up during the compression stroke to fine-scale turbulent kinetic energy desired for rapid, robust combustion. The natural gas engines used in medium- and heavy-truck applications would benefit from a similar, high-tumble pent-roof combustion chamber. However, these engines are invariably derived from their higher-volume diesel counterparts, and the production volumes are insufficient to justify the amount of modification required to incorporate a pent-roof system. The objective of this multi-dimensional computational study was to develop a combustion chamber addressing the objectives of a pent-roof chamber while maintaining the flat firedeck and vertical valve orientation of the diesel engine. A new combustion chamber was designed based on a commercial 11-liter natural gas
Cummins announced its seventh-generation series HE250 and HE300 waste-gate turbochargers for medium displacement on- and off-highway commercial engines. The turbos are sized for 5.5- to 8-liter medium-duty diesel engines and 8- to 11-liter natural-gas engines. Cummins states that the HE250 and 300 were designed to meet the global emissions regulations from 2024 onwards including the upcoming China Stage IV FE 2024, NSVII 2026 and Euro VII 2027. Cummins claims significant improvements in performance and durability compared to the outgoing models. Both turbos reportedly offer a 6-7% gain in overall efficiency as well as enhanced low-speed performance, which translates to additional low-end torque and better compatibility with engine start/stop systems
Engine manufacturers are increasingly concerned about oil consumption due to its implications for operating costs, emissions, and durability in both diesel and natural gas-powered engines. As future engines aim for low or near-zero emissions while utilizing low/zero carbon fuels, lubricant oil consumption will play a critical role in achieving decarbonization and emissions targets. Hydrogen-fuelled engines, in particular, will be more vulnerable to oil droplet and oil ash-based pre-ignition. Traditionally, the influence of key design parameters on oil consumption has been determined during the validation phase of an engine development program, which entails extensive testbed hours and time-consuming hardware iterations. As a result, development programs may be unable to optimize oil consumption due to cost and time constraints. The need to reduce oil consumption, along with these constraints, has prompted the adoption of more efficient development approaches, such as using virtual
In an engine system, the piston pin is subjected to high loading and severe lubrication conditions, and pin seizures still occur during new engine development. A better understanding of the lubricating oil behavior and the dynamics of the piston pin could lead to cost- effective solutions to mitigate these problems. However, research in this area is still limited due to the complexity of the lubrication and the pin dynamics. In this work, a numerical model that considers structure deformation and oil cavitation was developed to investigate the lubrication and dynamics of the piston pin. The model combines multi-body dynamics and elasto-hydrodynamic lubrication. A routine was established for generating and processing compliance matrices and further optimized to reduce computation time and improve the convergence of the equations. A simple built-in wear model was used to modify the pin bore and small end profiles based on the asperity contact pressures. The model was then applied to a
Digitalization offers a variety of promising tools for improving large internal combustion engine technology. This also includes the inspection of important engine components such as cylinder liners. Modern concepts for condition monitoring of the inner surfaces of cylinder liners are often based on indirect methods such as lubricating oil or vibration condition monitoring. However, a position-based inspection of roughness and lubrication properties of the liner surface is currently not possible during operation, nor is it feasible during engine standstill. For large engines in particular, the evaluation of surface properties currently requires disassembly and cutting of the inspected liner, followed by a sophisticated microscopic surface depth measurement. Although this process provides a high-resolution three-dimensional surface model, such measurement methods are destructive and costly. The goal of the research presented here is to develop a simpler and nondestructive method for
This study investigated the exhaust particle and unregulated emissions emanating from a heavy duty six-cylinder natural gas engine with CNG and HCNG fuels. Experiments were performed at different speeds (1000, 1500, 2000 and 2500 rpm) and load conditions (30%, 50%, 75% and 100%). Exhaust gas samples at each speed-load combination were analyzed for particle number concentration and particle size distribution using engine exhaust particle sizing spectrometer. Unregulated emissions were also measured using FTIR (Fourier Transform Infrared) analyzer. The results indicated that particle number (PN) concentration in exhaust is comparatively lower with HCNG fuel than CNG and it increases with increase in engine speed-load. At higher speed-load condition, engine emits high nucleation mode particles (NMP) and ultrafine particles (UFP). Total PN concentration in the NMP range is comparatively higher than UFP and accumulated mode particles (AMP) for both the test fuels. The surface area of
This paper presents a sensitivity-based input selection algorithm and a layered modeling approach for improving Gaussian Process Regression (GPR) modeling with hyperparameter optimization for engine model development with data sets of 120 training points or less. The models presented here are developed for a Pilot-Ignited Direct-Injected Natural Gas (PIDING) engine. A previously developed GPR modeling method with hyperparameter optimization produced some models with normalized root mean square error (nRMSE) over 0.2. The input selection method reduced the overall error by 0.6% to 18.85% while the layered modeling method improved the error for carbon monoxide (CO) by 52.6%, particulate matter (PM) by 32.5%, and nitrogen oxides (NOX) by 29.8%. These results demonstrate the importance of selecting only the most relevant inputs for machine learning models. This also shows that a layered approach to modeling could be implemented to further refine the inputs and provide a reduction in
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