INITIAL RESULTS ON A NEW LIGHT-DUTY 2.7L OPPOSED-PISTON GASOLINE COMPRESSION IGNITION MULTI-CYLINDER ENGINE

Gasoline compression ignition (GCI) is a cost-effective approach to achieving diesel-like efficiencies with low emissions. The fundamental architecture of the two-stroke Achates Power Opposed-Piston Engine (OP Engine) enables GCI by decoupling piston motion from cylinder scavenging, allowing for flexible and independent control of cylinder residual fraction and temperature leading to improved low load combustion. In addition, the high peak cylinder pressure and noise challenges at high-load operation are mitigated by the lower BMEP operation and faster heat release for the same pressure rise rate of the OP Engine. These advantages further solidify the performance benefits of the OP Engine and emonstrate the near-term feasibility of advanced combustion technologies, enabled by the opposed-piston architecture. This paper presents initial results from a steady state testing on a brand new 2.7L OP GCI multi-cylinder engine designed for light-duty truck applications. Successful GCI operation calls for high compression ratio, leading to higher combustion stability at low-loads, higher efficiencies, and lower cycle HC+NOX emissions. Initial results show a cycle average brake thermal efficiency of 31.7%, which is already greater than 11% conventional engines, after only ten weeks of testing. Emissions results suggest that Tier 3 Bin 160 levels can be achieved using a traditional diesel after-treatment system. Combustion noise was well controlled at or below the USCAR limits. In addition, initial results on catalyst light-off mode with GCI are also presented.

Experimental Investigation of Direct Fuel Injection into Low-Oxygen Recompression Interval in a Homogenous Charge Compression Ignition Engine

This work analyzed measured data from a single-cylinder engine operated under gasoline direction injection homogenous charge compression ignition (GDI-HCCI) mode. The experiments were conducted at a 0.95 equivalence ratio (φ) under 0.5 MPa indicated mean effective pressure and 1500RPM. A side-mounted injector delivered primary reference fuel (octane number 90) into the combustion chamber during negative valve overlap (NVO). Advanced combustion phase CA50 were observed as a function of the start of injection (SOI) timings. Under φ=0.95, peak NVO in-cylinder pressures were lower than motoring for single and split injections, emphasizing that NVO reactions were endothermic. Zero-dimensional kinetics calculations showed classical reformate species (C3H6, C2H4, CH4) from the NVO rich mixture increased almost linearly due to SOI timings, while H2 and CO were typically low. These kinetically reformed species shortened predicted ignition delays. This work also analyzed the effects of intake pressure and single versus double pulses injections on CA50, burn duration, peak cylinder pressure, combustion noise, thermal efficiency, and emissions. Advanced SOI (single-injection) generated excessive combustion noise metrics over constraint limits, but the double-pulse injection could significantly reduce the metrics (Ringing Intensity ≤ 5 MW/m2, Maximum Pressure Rise Rate = 0.6 MPa/CA) and NOx emission. The engine's net indicated thermal efficiency reached 41% under GDI-HCCI mode against 36% under SI mode for the same operating conditions. Under GDI-HCCI mode and without spark-ignition, late fuel injection in the intake stroke could reduce NOx to a single digit.

Delay Identification in Thermoacoustics

The stability of thermoacoustic systems is often regulated by the time delay between acoustic perturbations and corresponding heat release fluctuations. An accurate estimate of this value is of great importance in applications, since even small modifications can introduce significant changes in the system behavior. Different studies show that the nonlinear delayed dynamics typical of these systems can be well captured with low-order models. In the present work, a method is introduced to estimate the most likely value of the time delay of a single thermoacoustic mode from a measured acoustic pressure signal. The mode of interest is modeled by an oscillator equation, with a nonlinear delayed forcing term modeling the deterministic flame contribution and an additive white Gaussian noise to embed the stochastic combustion noise. Additionally, other thermoacoustic relevant parameters are estimated. The model accounts for a flame gain, for a flame saturation coefficient, for a linear acoustic damping and for the background combustion noise intensity. The pressure data time series is statistically analyzed and the set of unknown parameters is identified. Validation is performed with respect to synthetically generated time series and low order model simulations, for which the underlying delay is known a priori. A discussion follows about the accuracy of the method, in particular a comparison with existing methods is drawn.

Confidence in Flame Impulse Response Estimation From Les with Uncertain Thermal Boundary Conditions

Thermoacoustic stability analysis is an essential part of the engine development process. Typically, thermoacoustic stability is determined by hybrid approaches. These approaches require information on the flame dynamic response. The combined approach of advanced System identification (SI) and Large Eddy Simulation (LES) is an efficient strategy to compute the flame dynamic response to flow perturbation in terms of the Finite Impulse Response (FIR). The identified FIR is uncertain due in part to the aleatoric uncertainties caused by applying SI on systems with combustion noise and partly due to epistemic uncertainties caused by lack of knowledge of operating or boundary conditions. Carrying out traditional uncertainty quantification techniques, such as Monte Carlo, in the framework of LES/SI would be computationally prohibitive. As a result, the present paper proposes a methodology to build a surrogate model in the presence of both aleatoric and epistemic uncertainties. Specifically, we propose a univariate Gaussian Process (GP) surrogate model, where the final trained GP takes into account the uncertainty of SI and the uncertainty in the combustor back plate temperature, which is known to have considerable impact on the flame dynamics. The GP model is trained on the FIRs obtained from the LES/SI of turbulent premixed swirled combustor at different combustor back plate temperatures. Due to the change in the combustor back plate temperature the flame topology changes, which in turn influences the FIR. The trained GP model is successful in interpolating the FIR with confidence intervals covering the "true" FIR from LES/SI.

Validation setup for the investigation of aeroacoustic and vibroacoustic sound emission of confined turbulent flows

Confined flows induce sound at certain flow conditions, which can be annoying in electric vehicles due to the absence of combustion noise. Noise in internal flow may occur due to unfavorable flow-guiding geometries caused by the complex packaging required in engine compartments of modern vehicles. The flow-induced sound is emitted at duct openings (e.g., ventilation inside the passenger cabin). It also originates from the vibroacoustic emissions of the flow-guiding structure excited by the flow. We propose a modular validation procedure for aeroacoustic simulations of confined flows. The experimental setup includes the vibroacoustic emission of the involved flow-guiding structure. The test rig consists of a sensor system, a high-pressure blower, modular pipe sections, and absorbers, which decouple the system from blower noise and avoid acoustic reflections at the pipe exit. A sufficiently long straight inlet section ensures fully developed flow conditions entering the investigated region. For capturing the vibroacoustic sound radiation of the flow-guiding structure, the measurement object and the surrounding microphones are encapsulated in a wooden box, lined with micro-perforated plates. Measurement results of a straight pipe and a pipe with a half-moon-shaped orifice are presented. Additionally, the sound generation is reproduced by Lighthill's aeroacoustic analogy applying a hybrid approach.

Mechanism of thermal efficiency improvement in twin shaped semi-premixed diesel combustion

Improvements of the thermal efficiency in twin shaped semi-premixed diesel combustion mode with premixed combustion in the primary stage and spray diffusive combustion in the secondary stage with multi-stage fuel injection were investigated with experiments and 3D-CFD analysis. For a better understanding of the advantages of this combustion mode, the results were compared with conventional diesel combustion modes, mainly consisting of diffusive combustion. The semi-premixed mode has a higher thermal efficiency than the conventional mode at both the low and medium load conditions examined here. The heat release in the semi-premixed mode is more concentrated at the top dead center, resulting in a significant reduction in the exhaust loss. The increase in the cooling loss is suppressed to a level similar to the conventional mode. In the conventional mode the rate of heat release becomes more rapid and the combustion noise increases with advances in the combustion phase as the premixed combustion with pilot and pre injections and the diffusive combustion with the main combustion occurs simultaneously. In the semi-premixed mode, the premixed combustion with pilot and primary injections and the diffusive combustion with the secondary injection occurs separately in different phases, maintaining a gentler heat release with advances in the combustion phase. The mechanism of the cooling loss suppression with the semi-premixed mode at low load was investigated with 3D-CFD. In the semi-premixed mode, there is a reduction in the gas flow and quantity of the combustion gas near the piston wall due to the suppression of spray penetration and splitting of the injection, resulting in a smaller heat flux.

Delay Identification in Thermoacoustics

The stability of thermoacoustic systems is often regulated by the time delay between acoustic perturbations and corresponding heat release fluctuations. An accurate estimate of this value is of great importance in applications, since even small modifications can introduce significant changes in the system behavior Different studies show that the nonlinear delayed dynamics typical of these systems can be well captured with low-order models. In the present work, a method is introduced to estimate the most likely value of the time delay of a single thermoacoustic mode from a measured acoustic pressure signal. The mode of interest is modeled by an oscillator equation, with a nonlinear delayed forcing term modeling the deterministic flame contribution and an additive white Gaussian noise to embed the stochastic combustion noise. Additionally, other thermoacoustic relevant parameters are estimated. The model accounts for a flame gain, for a flame saturation coefficient, for a linear acoustic damping and for the background combustion noise intensity. The pressure data time series is statistically analyzed and the set of unknown parameters is identified. Validation is performed with respect to synthetically generated time series and low order model simulations, for which the underlying delay is known a priori. A discussion follows about the accuracy of the method, in particular a comparison with existing methods is drawn.

Confidence in Flame Impulse Response Estimation From LES With Uncertain Thermal Boundary Conditions

Thermoacoustic stability analysis is an essential part of the engine development process. Typically, thermoacoustic stability is determined by hybrid approaches such as network models or Helmholtz solvers. These approaches require information on the flame dynamic response. The combined approach of advanced System identification (SI) and Large Eddy Simulation (LES) is an efficient strategy to compute the flame dynamic response to flow perturbation in terms of the Finite Impulse Response (FIR). The identified FIR is uncertain due in part to the aleatoric uncertainties caused by applying SI on systems with combustion noise and partly due to epistemic uncertainties caused by lack of knowledge of operating or boundary conditions. Carrying out traditional uncertainty quantification techniques, such as Monte Carlo, in the framework of LES/SI would be computationally prohibitive. As a result, the present paper proposes a methodology to build a surrogate model in the presence of both aleatoric and epistemic uncertainties. More specifically, we propose a univariate Gaussian Process (GP) surrogate model, where the final trained GP takes into account the uncertainty of SI and the uncertainty in the combustor back plate temperature, which is known to have considerable impact on the flame dynamics. The GP model is trained on the FIRs obtained from the LES/SI of turbulent pre-mixed swirled combustor at different combustor back plate temperatures. Due to the change in the combustor back plate temperature the flame topology changes, which in turn influences the FIR. The trained GP model is successful in interpolating the FIR with confidence intervals covering the “true” FIR from LES/SI.