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At least 19 records

Mixing-Controlled Combustion of Ethanol Enabled by Prechamber Ignition (PC-MCC): A Preliminary Experimental Demonstration

This experimental study presents preliminary investigations of prechamber-enabled mixing-controlled combustion (PC-MCC) at −2 bar brake mean effective pressure (BMEP) and 2200 rpm with fuel-grade ethanol (E98). Experimental results are conducted on a prechamber retrofitted single-cylinder Caterpillar C9.3B test engine. First, a series of prechamber-only experiments were conducted with a motored engine to evaluate the salient combustion trends in response to relevant prechamber operating parameters. Under firing conditions, the prechamber operating strategy was assessed with respect to the impact on ignition assistance of direct-injected E98 and overall engine performance. The preliminary results indicate the jet-induced ignition process is robust and prompts diffusion combustion of E98 at diesel-like boundary conditions. Here, the effect of external exhaust gas recirculation (EGR) on the residual tolerance of the prechamber combustion process was also investigated and showed stable combustion in both the main chamber and prechamber up to 30% EGR. Experiments were also conducted with the stock diesel engine for baseline comparison. At matched combustion phasing, mixing-controlled combustion of ethanol enabled by prechamber ignition was able to achieve heightened gross thermal efficiency while simultaneously reducing NOx and practically eliminating smoke emissions relative to diesel combustion. In addition, the covariance of load and standard deviation of combustion phasing was diesel-like and less than 2% and 1 CAD, respectively.

PC-MCC↗

Combustion control using spiking neural networks

A system that controls a combustion engine stores network vectors in a memory that represent diverse and distinct spiking neural networks. The system decodes the network vectors and trains and evaluates the spiking neural networks. The system duplicates selected network vectors and crosses-over the duplicated network vectors that represent modified spiking neural networks. The system mutates the crossed-over duplicated network vectors by randomly modifying one or more portions of the crossing-over duplicated network vectors. The system meter exhaust gas into an intake manifold when an engine temperature exceeds a threshold, an engine load exceeds a threshold, an engine's rotation-per-minute rate exceeds a threshold, and a fuel flow exceeds a threshold. The system modifies fuel flow into an engine's combustion chamber on a cycle-to-cycle basis by the trained spiking neural network.

Puente, Brian P. Maldonado↗

Development of prechamber enabled mixing-controlled combustion strategy for ultra-low methane emissions from lean burn natural gas engines

This numerical study explores the optimization of Prechamber Enabled Mixing-Controlled Combustion (PC-MCC) using natural gas in heavy-duty engines, aiming to enhance combustion efficiency to minimize methane slip and NOx emissions. The approach involves a prechamber ignition system, distinct from conventional spark ignition (SI) systems, to initiate combustion of direct injected natural gas. By leveraging the robust ignition characteristics of the prechamber, the PC-MCC method demonstrates significant potential in achieving efficient combustion akin to diesel engines but with lower greenhouse gas emissions. The research evaluates the effects of various geometric and operational parameters on the combustion process and emissions, including prechamber volume, nozzle diameter, direct injector (DI) geometry, and engine operating strategies. Computational Fluid Dynamics (CFD) simulations are utilized, focusing on a heavy-duty, single-cylinder engine modeled after the Caterpillar C9.3B engine. Key findings indicate that a prechamber volume of 3 cc, coupled with a nozzle diameter of 2.75 mm for two prechamber holes, strikes an optimal balance between combustion efficiency and emissions reduction. This configuration ensures robust combustion across a range of operating conditions while maintaining methane slip within targeted limits. Further investigation into DI geometry shows the significance of the injector umbrella angle and nozzle diameter in shaping the fuel-air mixing and combustion dynamics. An umbrella angle of 130° and a nozzle diameter of 300 microns are identified as optimal, promoting rapid and efficient combustion with minimized methane and NOx emissions. The study also investigates the impact of injection timing and pressure, highlighting their roles in controlling combustion timing and influencing emissions levels. Advanced injection timing is found to be crucial in achieving the desired low methane slip, whereas retarded injection timing assists to reduce NOx emissions while having a slight increase in methane emissions. Operating strategies incorporating various levels of Exhaust Gas Recirculation (EGR) are assessed for their effectiveness in further reducing emissions. The research demonstrates that a judicious combination of internal hot EGR and careful calibration of DI pressure and SOI timing can achieve significant reductions in NOx emissions while keeping methane slip under control. Specifically, an internal EGR level of 15%–25%, combined with DI pressures of 200–300 bar and injection timings at or after top dead center, is recommended. These findings contribute valuable insights into the development of advanced combustion techniques for natural gas engines, offering a viable pathway to reduce methane slip without compromising engine efficiency or performance. The PC-MCC system presents a promising solution for the future of heavy-duty natural gas engine technology to reduce methane emissions.

Nsaif, Osama↗

Model predictive combustion control of a Gasoline Compression Ignition engine

Gasoline Compression Ignition is a novel combustion concept that derives its superiority from the high compression ratio of a compression ignition engine as well as the properties of gasoline fuel, such as longer ignition delay and higher volatility compared to diesel. Here, this combustion concept was experimentally tested on a 12.4L Class 8 truck engine. Based on these experimental data, prior efforts by the authors focused on the development of an engine model for a heavy-duty engine operating on a low-reactivity fuel. This engine model was leveraged within this study to investigate a combustion control strategy at different engine conditions and injection methods and was augmented to incorporate cycle-to-cycle combustion variations. State estimation is performed by means of a Kalman filter which feeds into a model predictive controller. The model predictive controller chooses control actions based on a predefined cost function under consideration of bounds reflecting physical constraints. The engine model was utilized to establish a state-space model that serves the Kalman filter and model predictive controller for estimation and prediction. A comparative study investigating control actions and engine behavior was performed with and without limiting in-cylinder peak pressure as well as combustion noise, which is of particular interest for early pilot injection strategies. In addition, the proposed control architecture was investigated at two different levels of cycle-to-cycle variations and compared to the performance of a control structure with input disturbance rejection. For increased cycle-to-cycle variations, disturbance estimation reduces state fluctuations and control effort. In general, this investigation highlights control aspects specific to a compression-ignited combustion regime with low-reactivity fuel. The control algorithm is able to maintain the desired references for brake mean effective pressure and combustion phasing while controlling peak in-cylinder pressure and combustion noise.

42 ENGINEERING↗

Numerical investigation of equivalence ratio effects on Flex-Fuel mixing controlled combustion enabled by prechamber ignition

There is interest in adapting renewable and low-carbon intensity fuels to heavy-duty engines to help displace criteria and greenhouse gas emissions associated with diesel combustion. Low-carbon fuels have inherently low cetane numbers and thus pose a significant challenge when considering direct substitution in diesel combustion systems. Use of an actively fueled prechamber as an ignition source to initiate mixing-controlled combustion (PC-MCC) of low-cetane fuels is becoming an attractive combustion mode to alleviate the identified reactivity deficit. This work focuses on the utilization of an active prechamber to facilitate diesel-like combustion of bioethanol-gasoline fuel blends in a heavy-duty engine. Recent results in this emerging technology suggest that ignition quality is uniquely coupled to prechamber equivalence ratio. In this numerical study, the fundamental implications of prechamber equivalence ratio on the ignition performance of direct injected fuels ranging from E10 to E100 are investigated using CONVERGE. Parametric studies of the prechamber operating strategy were assessed at diesel-like conditions to characterize the performance trends relative to a diesel baseline at the same boundary conditions. Simulation results indicate that PC-MCC is flex-fuel capable and achieves diesel-like ignition qualities and combustion processes for all fuels considered under stoichiometric and rich prechamber conditions. To characterize the equivalence ratio trends observed, a novel inflow boundary modeling technique was utilized to prescribe turbulent jets in place of the prechamber where selective speciation of the jet composition was conducted to isolate the ignition contributions of radical and reacting species in lean, stoichiometric, and rich jets. The inflow boundary modeling suggests that excess fuel and combustion intermediates present in jets produced from stratified and fuel-rich prechamber operation promotes higher jet temperatures and as such are superior ignition sources. Relative to a lean prechamber jet, the peak temperature of a reacting jet from a rich prechamber was up to 600 K hotter at fixed distances from the orifice exit. Furthermore, radicals also demonstrated an influence on the ignition process, but the combustion mode was identified to be thermally dominant.

33 ADVANCED PROPULSION SYSTEMS↗

Assessment of design and location of an active prechamber igniter to enable mixing-controlled combustion of ethanol in heavy-duty engines

Here, this numerical study focuses on assessing the key design parameters of interest for use of an active prechamber igniter as an ignition assistance device to enable mixing-controlled combustion (MCC) of ethanol (E100) in a heavy-duty Caterpillar C9.3B engine. Computational fluid dynamic (CFD) simulations of a baseline diesel and prechamber retrofitted C9.3B at a gross indicated mean effective pressure (IMEPg) of 5 bar and 1800 rpm are carried out using CONVERGE. In particular, the sizing of the prechamber volume, sizing of total orifice cross sectional area (orifice diameter), and location of the prechamber relative to a centrally mounted common rail direct injector are varied to discern the appropriate operational and design characteristics to achieve robust ignition assistance at the selected conditions. Simulation results indicate that use of an active prechamber igniter with E100 as a standalone fuel source can replicate ignition delays and thermal efficiencies similar to diesel combustion at the same engine boundary conditions, thus not requiring any changes to the engine’s air handling system. Igniter mounting location, orifice sizing, and jet targeting were found to have the strongest influence on ignition assistance with preference toward larger orifice diameters that appropriately located heating contributions in near vicinity to the direct injector.

33 ADVANCED PROPULSION SYSTEMS↗

Development of a Flex-Fuel Mixing Controlled Combustion System for Gasoline/Ethanol Blends Enabled by Prechamber Ignition

This project demonstrated a heavy-duty engine converted from using diesel fuel to a flex-fuel engine that can use any blend of gasoline and ethanol. The combustion system is an innovative concept that allows very low cetane fuels to be used in a conventional mixing-controlled combustion (MCC) strategy without auxiliary heating, changes to the basic engine structure, or advanced controls.

09 BIOMASS FUELS↗

Characterization of Flex-Fuel Prechamber Enabled Mixing-Controlled Combustion With Gasoline/Ethanol Blends at High Load

This numerical study focuses on the characterization of prechamber-enabled mixing-controlled combustion (PC-MCC) at ~18 bar brake mean effective pressure (BMEP) and 2200 rpm with 10% by volume ethanol-gasoline blend (E10) and pure ethanol (E100). Computational fluid dynamic (CFD) simulations of a stock and prechamber retrofitted single-cylinder Caterpillar C9.3B are carried out using CONVERGE. Prechamber equivalence ratio at spark timing, prechamber spark timing advance, and main chamber injection strategy are assessed with respect to their impact on ignition assistance performance and emissions characteristics relative to a diesel baseline at the same boundary conditions. Simulation results indicate that PC-MCC is flex-fuel capable and operates well for both E10 and E100 at the operating conditions considered. The results demonstrate that the use of a pilot-main injection strategy enables spark timing in the prechamber to be advanced and thus reduces spark plug firing pressure while maintaining robust ignition assistance. Results also indicate that the rich prechamber operation is favored for improved ignition assistance capabilities. Furthermore, the findings of this work suggest that a heavy-duty vehicle using a PC-MCC engine can utilize any blend of gasoline and ethanol, up to including pure ethanol, with no major sacrifices in performance relative to the diesel engine.

33 ADVANCED PROPULSION SYSTEMS↗

Dilute Combustion Control Using Spiking Neural Networks

Dilute combustion with exhaust gas recirculation (EGR) in spark-ignition engines presents a cost-effective method for achieving higher levels of engine efficiency. At high levels of EGR, however, cycle-to-cycle variability (CCV) of the combustion process is exacerbated by sporadic occurrences of misfires and partial burns. Previous studies have shown that temporal deterministic patterns emerge at such conditions and certain combustion cycles have a significant influence over future events. Due to the complexity of the combustion process and the nature of CCV, harnessing all the deterministic information for control purposes has remained challenging even with physics based 0-D, 1-D, and high-fidelity computational fluid dynamics (CFD) models. In this study, we present a data-driven approach to optimize the combustion process by controlling CCV adjusting the cycle-to-cycle fuel injection quantity. Readily available data from in-cylinder pressure was used to train a spiking neural network (SNN) which learns the optimal way to manage fuel injection in order to reduce CCV while maintaining acceptable levels of fuel consumption. SNNs are particularly well suited for powertrain control applications due to their ability to be deployed on FPGA-based neuromorphic hardware which are small, inexpensive, and have a low power demand. The high-performance computing (HPC) resources of Oak Ridge National Laboratory were used to run an evolutionary-based training approach for choosing the best SNN configuration that minimizes the size of the network while achieving the desired goal. The neuromorphic hardware with the optimized SNN deployed was connected to the rapid prototyping engine control system for real-time control implementation and tested on a single cylinder version of a GM LNF 4-cylinder engine. The results show a significant reduction of CCV with a small percentage of additional fuel used to stabilize the charge.

33 ADVANCED PROPULSION SYSTEMS↗

FLEX-FUEL MIXING CONTROLLED COMBUSTION ENABLED BY PRECHAMBER IGNITION

There is an imminent need to displace fossil diesel fuel with cleaner burning, domestically produced, renewable fuels for use in heavy-duty engines. Bioethanol is a prime candidate as it widely adopted in the U.S. as a gasoline additive ranging in volume percentage from 10% (E10) up to 85% (E85). Direct substitution of market available ethanol-gasoline blends for diesel fuel is not plausible as the stark reactivity differences would not constitute the same ignition quality nor achieve auto-ignition at all. This work focuses on the development of prechamber enabled mixing-controlled combustion (PC-MCC) as an advanced combustion strategy to facilitate reliable ignition and diffusion style combustion ethanol-gasoline fuel blends. PC-MCC involves integration of an actively fueled prechamber (PC) into a conventional compression ignition combustion system. When ignited, the PC ejects hot turbulent jets into the main combustion chamber that then interact with the direct injected fuel, prompting immediate ignition. The PC jet flames provide a robust thermal ignition source that allows the engine to operate agnostic of fuel composition, or flex-fuel. Computational fluid dynamics (CFD) modeling was used to assess critical design features of the PC while garnering insights into the ignition strategies that facilitate robust performance. A key finding was the ignition performance benefits of fuel-rich PC operation which yield exothermic jets. Based on the numerical findings, a prototype igniter was tested experimentally on both single and multi-cylinder engine platforms at a variety of operating conditions. The experimental results indicate flex-fuel PC-MCC is well capable of diesel-like combustion processes by demonstrating matched or improved gross thermal efficiencies and load variability within 2%. Fuel grade ethanol (E98) exhibited consistently lower NOx and immeasurable soot across the load space. E98 also demonstrated a significant improvement in thermal efficiency at light loads.

Zeman, Jared↗

Learning reference governor for cycle-to-cycle combustion control with misfire avoidance in spark-ignition engines at high exhaust gas recirculation–diluted conditions

Cycle-to-cycle feedback control is employed to achieve optimal combustion phasing while maintaining high levels of exhaust gas recirculation by adjusting the spark advance and the exhaust gas recirculation valve position. The control development is based on a control-oriented model that captures the effects of throttle position, exhaust gas recirculation valve position, and spark timing on the combustion phasing. Under the assumption that in-cylinder pressure information is available, an adaptive extended Kalman filter approach is used to estimate the exhaust gas recirculation rate into the intake manifold based on combustion phasing measurements. The estimation algorithm is adaptive since the cycle-to-cycle combustion variability (output covariance) is not known a priori and changes with operating conditions. A linear quadratic regulator controller is designed to maintain optimal combustion phasing while maximizing exhaust gas recirculation levels during load transients coming from throttle tip-in and tip-out commands from the driver. During throttle tip-outs, however, a combination of a high exhaust gas recirculation rate and an overly advanced spark, product of the dynamic response of the system, generates a sequence of misfire events. In this work, an explicit reference governor is used as an add-on scheme to the closed-loop system in order to avoid the violation of the misfire limit. The reference governor is enhanced with model-free learning which enables it to avoid misfires after a learning phase. Experimental results are reported which illustrate the potential of the proposed control strategy for achieving an optimal combustion process during highly diluted conditions for improving fuel efficiency.

42 ENGINEERING↗

System and method for engine control with pressure reactive device to control combustion timing

The present disclosure relates to a system for controlling ignition of an intake charge directed into an internal combustion engine. The system may have a movable component operably associated with at least one of a piston of the engine or a combustion chamber of the engine. The movable component may be tuned to deflect in response to a predetermined pressure being reached in a cylinder in which the piston is housed. The movable component operates to deflect in response to the predetermined pressure being reached in the cylinder as the piston travels toward top dead center during its compression stroke, to change a compression ratio of the engine.

Killingsworth, Nicholas↗

Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators

Dilute combustion using exhaust gas recirculation (EGR) presents a cost-effective method for increasing the efficiency of spark-ignition (SI) engines. However, the maximum amount of EGR that can be used at a given condition is limited by a rapid increment of cycle-to-cycle variability (CCV). This study describes a methodology to design a model-based stochastic optimal controller to adjust the cycle-to-cycle fuel injection quantity in order to reduce CCV and further extend the dilute limit. Given the complexity and chaotic nature of combustion events, the controller was enhanced with online learning in order to identify the statistical properties of combustion efficiency, which are needed to generate predictions for next-cycle events. This study showed that a kernel density estimator (KDE) can be used to learn the combustion properties in real time and can be incorporated into the feedback policy in order to calculate the optimal control command. Experimental results suggested that the dilute limit can be extended from 18.5% to 21% EGR fraction at an operating condition relevant for highway cruising. Additionally, the proposed controller can achieve a large CCV reduction with less fuel enrichment compared to previous methods, overall contributing to an increase in 0.2% indicated fuel conversion efficiency.

33 ADVANCED PROPULSION SYSTEMS↗

Reinforcement learning applied to dilute combustion control for increased fuel efficiency

To reduce the modeling burden for control of spark-ignition engines, reinforcement learning (RL) has been applied to solve the dilute combustion limit problem. Q-learning was used to identify an optimal control policy to adjust the fuel injection quantity in each combustion cycle. A physics-based model was used to determine the relevant states of the system used for training the control policy in a data-efficient manner. The cost function was chosen such that high cycle-to-cycle variability (CCV) at the dilute limit was minimized while maintaining stoichiometric combustion as much as possible. Experimental results demonstrated a reduction of CCV after the training period with slightly lean combustion, contributing to a net increase in fuel conversion efficiency of 1.33%. To ensure stoichiometric combustion for three-way catalyst compatibility, a second feedback loop based on an exhaust oxygen sensor was incorporated into the fuel quantity controller using a slow proportional-integral (PI) controller. The closed-loop experiments showed that both feedback loops can cooperate effectively, maintaining stoichiometric combustion while reducing combustion CCV and increasing fuel conversion efficiency by 1.09%. Finally, a modified cost function was proposed to ensure stoichiometric combustion with a single controller. In addition, the learning period was shortened by half to evaluate the RL algorithm performance on limited training time. Experimental results showed that the modified cost function could achieve the desired CCV targets, however, the learning time was reduced by half and the fuel conversion efficiency increased only by 0.30%.

33 ADVANCED PROPULSION SYSTEMS↗

A high-temperature mixed potential CO gas sensor for in situ combustion control

An in situ, accurate and robust sensor that can sustain a high temperature of above 1000 °C is needed for on-site combustion monitoring because it can give real-time and local data to the control system to adjust the overall combustion efficiency. In this work, we find that nickel oxide (NiO) is a promising sensing material for CO which is a direct indicator of the status of the combustion process of a power plant. Under the conditions of 0.5–3% O 2 and 1000 °C, the fabricated yttrium-stabilized zirconia (YSZ)-based mixed potential sensor using porous NiO demonstrates good sensitivity to CO, showing a signal as high as 36 mV to 1000 ppm CO. The effects of gas transport, structure and geometry of the NiO electrode on the sensing performance are studied. Results show that fast gas transport is much beneficial to improved sensitivity. NiO having a porous structure is much more sensitive to CO than that having a dense structure. But the t90 (time to achieve 90% final signal magnitude) of the former is much longer due to slower gas diffusion inside the pores. It's worth noting that the NiO sensor exhibits a positive relationship with the CO content, opposite to other reported results of mixed potential sensors to detect CO. We find that this might be due to the electrochemical reduction, instead of oxidation of CO during the interaction with NiO at 1000 °C. Selectivity tests on how CO 2 , CH 4 and steam affect CO sensing are also demonstrated. NiO is insensitive to even 10% CO 2 . CH 4 does not shift the average value of the CO sensing response. However, it makes the sensing signal fluctuate more intensively. 2% steam exerts a great influence on NiO sensitivity to CO: it magnifies the sensitivity of the porous NiO electrode to a low CO range of 0–100 ppm, but inhibits its sensitivity to a CO range of 100 ppm to 1000 ppm. Lastly, an 11 day stability test demonstrates the promising stability property of the proposed NiO-based YSZ sensor.

20 FOSSIL-FUELED POWER PLANTS↗

Methanol mixing controlled combustion process enabled by methanol dehydration to dimethyl ether

This work demonstrates an initial proof-of-concept approach for operating a compression ignition off-road and marine relevant engine using neat methanol. The approach utilizes mixing controlled compression ignition (MCCI) of methanol that is enabled by a homogeneous charge compression ignition (HCCI) pre-burn of premixed dimethyl ether (DME). Although two fuels are used, this work explores and evaluates the opportunity and performance to generate the premixed fuel via. methanol catalytic dehydration over an alumina catalyst at engine relevant temperatures, pressures, and space velocities. Conversion purity and species output results from catalytic dehydration bench flow reactor studies were coupled with single cylinder experiments of the characterized output species for pre-burn HCCI performance. Subsequent initial methanol MCCI performance is also evaluated and compared relative to conventional diesel combustion. The detailed flow reactor results show that the catalytic dehydration conversion efficiency of methanol to DME is a function of system pressure, temperature, and space velocity. The engine results demonstrate that a 100% conversion of methanol to DME is not required for successful pre-burn HCCI, and the water formed during the dehydration process does not need to be removed to achieve the desired HCCI event from this pre-burn mixture. Subsequent methanol MCCI combustion results show that the level of methanol slip in the dehydration process affects the pre-burn HCCI phasing, low temperature heat release process, and magnitude of energy released, all of which can dictate the available window for direct injection of methanol for MCCI combustion.

Jatana, Gurneesh [ORNL] (ORCID:0000000288903225)↗

Smokeless Chimney using Smoke Opacity as a Combustion Control Parameter (CRADA Final Report)

If operated poorly, wood burning heaters can produce large amounts of particulate matter (PM). Although several instruments are available to monitor PM, most require dilution air and are unable to sample directly from a flue due to the high PM concentrations and temperatures. Opacity sensors can measure color, opacity and smoke density from wood heater stacks. They operate by transmitting a light beam through the emission source and measuring the amount of light intensity lost (opacity) and light not reflected (color). Although opacity sensors are used in several areas, none have been thoroughly evaluated or optimized for measuring smoke from wood heaters.

47 OTHER INSTRUMENTATION↗