Hydrogen Enriched Compressed Natural Gas Research Articles

Performance, emissions and combustion analysis of hydrogen-enriched compressed natural gas spark ignition engine by optimized Gaussian process regression and neural network at low speed on different loads

The transportation industry is increasingly focused on hydrogen based fuel as a promising alternative due to its potential for reduced emissions and enhanced performance. The purpose of this study is to improve efficiency and reduce emissions on low speed on different loads for heavy duty vehicles. This study can be impactful to train the electronic control unit (ECU) for heavy duty vehicles working on aforementioned conditions. This study investigates the effect of hydrogen ratios (0%–40 %) in HCNG, (0%–15 %) exhaust gas recirculation (EGR) ratios, and spark timing (8°-34o CA bTDC) at low and high loads (15 % & 75 %) under stoichiometric conditions at low speed (700 rpm). Performance, emissions and combustion parameters were thoroughly analysed across these conditions. Brake thermal efficiency increases by 20.7 % & 19.4 % by the addition of (0 %–40 %) hydrogen at low and high load at 14o CA bTDC running on 5 % and 0 % EGR respectively. NOx emissions reduces by 11.9 % & 17.9 % by the addition of (0 %–15 %) EGR and increases by 46.1 % & 46.4 % by increasing the amount of hydrogen in HCNG at low and high load at 14o CA bTDC at 0 % EGR respectively. Coefficient of variation reduces 13.8 % by (0 %–40 %) hydrogen addition at 11 % EGR at 16o CA bTDC. Optimized Gaussian process regression (GPR) and neural network (NN) machine learning techniques were applied to the dataset, and found GPR matern 5/2 is best one. The findings can be utilized in the development of HCNG engine.

Optimal Scheduling of Integrated Energy System Considering Hydrogen Blending Gas and Demand Response

In the context of carbon neutrality and carbon peaking, in order to achieve low carbon emissions and promote the efficient utilization of wind energy, hydrogen energy as an important energy carrier is proposed to mix hydrogen and natural gas to form hydrogen-enriched compressed natural gas (HCNG). It is also injected into the natural gas pipeline network to achieve the transmission and utilization of hydrogen energy. At the same time, the participation of demand response is considered, the load’s peak and trough periods are adjusted, and the large-scale consumption of renewable energy and the reduction in carbon emissions are achieved. First of all, a fine model of hydrogen production and hydrogen use equipment is established to analyze the impact of adding hydrogen mixing on the economy and the low-carbon property of the system. With green certificates and demand response, the utilization rate of hydrogen energy is improved to further explore the energy utilization rate and emission reduction capacity of the system. Secondly, on the basis of modeling, the optimal scheduling strategy is proposed with the sum of energy purchase cost, equipment operation cost, carbon emission cost, wind curtailment cost, and green certificate income as the lowest objective function. Considering the constraints such as hydrogen blending ratio and flexible load ratio of the pipeline network, a low-carbon economic scheduling model of hydrogen mixed natural gas was established. The model was linearized and solved by using MATLAB 2021a and CPLEX solver. By comparing different scenarios, the superiority of the model and the effectiveness of the strategy are verified.

Optimal operation of electric-heat-gas-hydrogen integrated energy system considering source-load uncertainty

Faced with the threat of global climate change crisis, increasing the use of hydrogen-enriched compressed natural gas (HCNG) and the utilization rate of renewable energy can both reduce the carbon emissions of the integrated energy system (IES). This paper establishes an electric-heat-gas-hydrogen integrated energy system (EHGH-IES) framework considering source-load uncertainty, and the natural gas pipe network in the traditional IES is transformed into a HCNG pipe network with a certain hydrogen blending ratio. An optimal operation model of the EHGH-IES considering source-load uncertainty is proposed in this paper. The chance constrained programming method is adopted to deal with source-load uncertainty. We pay attention to comparing different confidence coefficient and hydrogen blending ratio in terms of the changes in the cost of the IES. The results show that the total cost of the EHGH-IES will increase by considering source-load uncertainty and using HCNG pipeline, but will bring some stability and environmental benefits to the IES by them.

An Optimal Dispatch Method of Integrated Electricity and Gas Systems Incorporating Hydrogen Injection Flexibility

Hydrogen enriched compressed natural gas provides a promising way of decarbonizing integrated electricity and gas systems. Considering the flexible characteristics of hydrogen enriched compressed natural gas, this paper proposes an optimal dispatch method for integrated electricity and gas systems incorporating hydrogen injection. A hydrogen blending transmission model is developed for hydrogen enriched compressed natural gas. The dynamic characteristics and the line pack are captured considering the impacts of hydrogen injection on pipeline transmission and line pack parameters. From the overall system operation aspect, a detailed energy flow model of hydrogen enriched compressed natural gas involving pipeline, compressor, and nodal gas flow balance is established incorporating the coupling relationship with hydrogen volume fraction. This model allows for the consideration of the impacts of time-varying hydrogen volume fractions on the optimal dispatch of systems. A novel estimation model is proposed to effectively determine the hydrogen volume fraction, which considers the impacts of line pack on hydrogen enriched compressed natural gas. Based on the proposed energy flow model, the line pack and the flexible adjustment of hydrogen volume fraction are aggregated into the flexible characteristics of hydrogen enriched compressed natural gas. A low-carbon dispatch method incorporating these flexible characteristics is developed to decarbonize integrated electricity and gas systems. Case studies on two test systems are presented to validate the effectiveness and applicability of the proposed model and method. The simulation results demonstrate that the accommodation levels of renewable energy and green hydrogen injection can be largely enhanced.

Co-adsorption of H2+nCO+mO2 on α-Fe (110): Effect on hydrogen adsorption, dissociation and diffusion

Hydrogen enriched compressed natural gas contains CO and O2 impurities, which have a coupling effect on hydrogen adsorption, dissociation and diffusion. First principles plane wave calculations have been used to study the co-adsorption and mutual interaction of H2+nCO + mO2 on Fe (110) plane. The results show that it’s easier for pre-adsorbed nCO + mO2 to form high surface coverage compared with pre-adsorbed nCO or mO2. The CO and O2 increased H2 dissociation barrier (Edis−b), and high coverage of nCO, mO2 and nCO + mO2 increased the hydrogen dissociation activation energy (Edis). With the coverage increased, the diffusion barrier (Edif) of H atom into Fe (110) decreased from 1.01eV to 0 by nCO and increased from 1.01eV to 2.14eV by mO2. The Edif was controlled by CO under low coverage and was controlled by O2 under high coverage when nCO + mO2 pre-adsorbed: the deformation charge density and state density analysis show that in H2+nCO + mO2 system, H atom is in an electron gain state at low coverage, which is similar to H in pre-adsorbed nCO, and H is in an electron loss state at high coverage, which is similar to H in pre-adsorbed mO2.The Edif probably related to the charge interaction of Hx− and Hy+ with Fez+.The C, O and H formant peaks from density of states show the influence of C and O on hydrogen invasion in orbital energy.

The weakening effect of the inhibition of CO2 on the explosion of HCNG with the increase of hydrogen: Experimental and chemical kinetic research

To explore the inhibitory effect of CO2 on HCNG (Hydrogen enriched compressed natural gas) explosion and its chemical kinetic mechanism, the explosion pressure and flame of CO2/HCNG/Air (hydrogen ratio: 0–0.6, CO2 addition: 3 vol%, 6 vol%, and 9 vol%) were tested in a 20 L spherical explosion tank at normal temperature and normal pressure. The experiment results shown that: as the addition of CO2 increases, the inhibition effect on HCNG explosion flame and pressure becomes more obvious. The larger the H2 ratio, the more difficult it is to inhibit HCNG explosion flame and pressure. To explore the chemical kinetics reasons for the above laws, the chemical kinetic parameters (such as free radical formation rate and temperature sensitivity coefficient) of the explosion reaction under the above conditions were calculated by CHEMKIN-PRO. The results indicate that CO2 mainly acts as a stable third body in the reaction system, thereby slowing down the growth of explosion chain reactions. In addition, as the main product of the CH4 oxidation reaction, CO2 has a certain weakening effect on the CH4 oxidation reaction. As the proportion of H2 increases, the elementary reactions such as 3# and 84# that generate ·H radicals are promoted, increasing the concentration of ·H radicals in the reaction system. Therefore, the dominant role of 38# on the temperature rise of the reaction system is enhanced, and the contribution of the CH4 oxidation reaction to the temperature rise of the reaction system is weakened. This is the chemical kinetic reason that CO2 has a weak inhibitory effect on the energy release of the HCNG explosion reaction when the proportion of H2 is large. The research results can provide a theoretical basis for the development of HCNG explosion prevention and control technology.

Stochastic optimal scheduling of electricity–hydrogen enriched compressed natural gas urban integrated energy system

Hydrogen blended gas turbines (HBGTs) are pivotal for the carbon emission reduction (CER) of urban integrated energy systems (UIESs). However, the traditional rough modeling performed in the existing research on optimal scheduling is not suitable for the implementation of HBGTs. To reflect the influence of hydrogen blending on the operation performance of HBGTs, a novel HBGT model is developed in this study based on the multidisciplinary integration modeling methodology with chemical reaction kinetics and system thermodynamics. This model can describe carbon emission and co-combustion power generation properties of HBGT. When the tracking of hydrogen-enriched compressed natural gas (HCNG) composition is considered, the model can be further applied to the stochastic optimal scheduling of electricity–HCNG UIESs with internal and external uncertainties to solve the carbon emission and renewable energy source (RES) consumption problems of UIESs. The simulation results demonstrate that the proposed HBGT modeling method has low-carbon economy and offers accurate operation performance. Furthermore, HBGT power generation can reduce the carbon emissions of an electricity–HCNG UIES by 22.62%. Meanwhile, the economy and wind power consumption are improved by more than 0.71% and 6.53%, respectively. The proposed optimal scheduling model considering multiple uncertainties is more reliable with the improvement of confidence level, which is an important guide for obtaining the optimal hydrogen blending ratio and promoting the CER of UIES.

Computational analysis of performances for a hydrogen enriched compressed natural gas engine’ by advanced machine learning algorithms

The support vector machine along with particle swarm optimization and artificial neural network have already been implemented for the regression study of a hydrogen enriched compressed natural gas (HCNG) fueled spark ignition engine. The main issues were that the support vector machine along with particle swarm optimization requires more computational time while the artificial neural network is sensitive to the hidden layers. Therefore, these algorithms are not effectively suitable for online control of the electronic control unit. The theme of this study is to evaluate the multiple mathematical engine’ models with respect to swiftness and accuracy. The experiments have been conducted under a wide range of operating conditions in a heavy-duty SI engine to obtain the data sets. The brake specific fuel consumption, engine torque and NOx emissions have been trained and analyzed by eight different machine learning algorithms along with nineteen sub-models. The effectiveness of these algorithms has been evaluated with respect to the root mean squared error and prediction time. The analysis indicate that the gaussian process regression (GPR) is optimal with respect to the computational efficiency (i.e., RMSE = 0.3823 g/kWh) and time (t < 16.019 sec). Furthermore, it operates without the iteration of the hidden layers. The mean simulation time for the gaussian process regression is 20,192 times lower as compared to the support vector machine along with particle swarm optimization algorithm. Since the gaussian process regression (GPR) is fast, optimal and insensitive to the hidden layers, so it is an ideal tool for online calibration of the electronic control unit.

Techno-economic review assessment of hydrogen utilization in processing the natural gas and biofuels

The automobile sector dominated by conventional fossil fuels greatly impacted human lives and strengthened the economy of many countries. However, the harmful emissions from the engines have contaminated the environment and induced severe climate changes; hence the emphasis is being laid on low carbon fuels that emit lower emissions and greenhouse gases. In this regard, hydrogen (H2) is considered as a no-carbon fuel; however, safety and storage are the main concerns. Therefore, the H2 can be potentially utilized with compressed natural gas (CNG) to form hydrogen-enriched compressed natural gas (HCNG) and processed with biofuels to produce hydrogenated biofuels. HCNG emits 20% lower carbon dioxide, 30% less carbon monoxide and 25% reductions in NOx emissions compared with CNG. The hydrogenated biodiesel fuels exhibit higher cetane number and better storage stability. However, the practical challenge is to render them economically affordable with minimum carbon footprints. Thus, the current review is aimed to provide comprehensive detail on the potential of hydrogen in fuel formulation techniques and their effect on engine performance, emission characteristics and various hydrogen production methods viz. blue and green hydrogen. Further, this review highlights the techno-economic characteristics of hydrogen utilization and economic characteristics of the low carbon fuels (both liquid and gaseous fuels) for sustainable mobility.

Regression prediction of hydrogen enriched compressed natural gas (HCNG) engine performance based on improved particle swarm optimization back propagation neural network method (IMPSO-BPNN)

Artificial neural network (ANN) methods have been rapidly developed and applied in solving nonlinear small sample problems. In this paper, an improved particle swarm algorithm optimized back propagation neural network (IMPSO-BPNN) method was proposed and used for the regression analysis and prediction of 20% (volume fraction) hydrogen enriched compressed natural gas (HCNG) engine performance. Meanwhile, various ANN and support vector machine (SVM) methods were also utilized for a comparative study. The experimental results show that the HCNG engine has the highest combustion efficiency, the maximum output torque and the minimum brake specific fuel consumption (BSFC) when operating at the maximum brake torque (MBT) timing, and the brake specific NOx (BSNOx) is also at a relatively low level. Through the comparison of multiple methods, the prediction accuracy and generalization ability of the IMPSO-BPNN model are the best overall. For example, the mean absolute percentage error (MAPE) of the optimal IMPSO-BPNN model (0.771%) is 5.85%, 12.62%, 17.96%, 7.57% and 7.88% less than that of the PSO-BPNN, GA-BPNN, BPNN, PSO-SVM and GA-SVM models (0.819%, 0.882%, 0.940%, 0.834% and 0.837%), respectively; and the correlation coefficient (R) is also higher than that of other models (0.99986). Secondly, the method shows visible superiority in the temporal dimension compared with the methods optimized by genetic algorithm and SVM method. For example, the CPU running time of the optimal IMPSO-BPNN model is reduced by 1773.32%, 149.74% and 1231.34% compared to that of the optimal GA-BPNN, PSO-SVM and GA-SVM models, respectively. Since the IMPSO-BPNN method is a flexible and general method, it is a new idea for the study of engine electronic control calibration tools.

Multi‐stage flexible planning of regional electricity‐HCNG‐integrated energy system considering gas pipeline retrofit and expansion

The development of hydrogen-enriched compressed natural gas (HCNG) can make full use of the existing natural gas infrastructure, thereby alleviating the economic and technical pressure on the development of pure hydrogen. This paper proposes a multi-stage flexible planning method for the regional electricity-HCNG-integrated energy system (E-HCNG-IES), which considers the medium and long-term dynamic characteristics of the E-HCNG-IES. For each sub-regional energy station, an energy-hub type model including hydrogen/HCNG-related equipment and facilities is established. Considering the influence of hydrogen blending on the energy delivery capacity and line pack of pipelines, a hydrogen-resistant retrofit model for existing natural gas pipelines between sub-regions is proposed. Meanwhile, the model for newly constructed hydrogen pipelines is also presented. Subsequently, a series of flexibility evaluation indicators are proposed to support the performance analysis of planning schemes. The lateral comparison of sub-cases in Changzhou, China demonstrates that considering the hydrogen-resistant retrofit of natural gas pipelines can reduce the construction cost of hydrogen pipelines by about 37.12%. The peak shaving capacity of underground hydrogen storage (UHS), the energy recycling ability of turbo expander (TE), and the space-time decoupling ability of hydrogen in energy supply and demand have also been confirmed.

Hydrogen-Enriched Compressed Natural Gas Network Simulation for Consuming Green Hydrogen Considering the Hydrogen Diffusion Process

Transporting green hydrogen by existing natural gas networks has become a practical means to accommodate curtailed wind and solar power. Restricted by pipe materials and pressure levels, there is an upper limit on the hydrogen blending ratio of hydrogen-enriched compressed natural gas (HCNG) that can be transported by natural gas pipelines, which affects whether the natural gas network can supply energy safely and reliably. To this end, this paper investigates the effects of the intermittent and fluctuating green hydrogen produced by different types of renewable energy on the dynamic distribution of hydrogen concentration after it is blended into natural gas pipelines. Based on the isothermal steady-state simulation results of the natural gas network, two convection–diffusion models for the dynamic simulation of hydrogen injections are proposed. Finally, the dynamic changes of hydrogen concentration in the pipelines under scenarios of multiple green hydrogen types and multiple injection nodes are simulated on a seven-node natural gas network. The simulation results indicate that, compared with the solar-power-dominated hydrogen production-blending scenario, the hydrogen concentrations in the natural gas pipelines are more uniformly distributed in the wind-power-dominated scenario and the solar–wind power balance scenario. To be specific, in the solar-power-dominated scenario, the hydrogen concentration exceeds the limit for more time whilst the overall hydrogen production is low, and the local hydrogen concentration in the natural gas network exceeds the limit for nearly 50% of the time in a day. By comparison, in the wind-power-dominated scenario, all pipelines can work under safe conditions. The hydrogen concentration overrun time in the solar–wind power balance scenario is also improved compared with the solar-power-dominated scenario, and the limit-exceeding time of the hydrogen concentration in Pipe 5 and Pipe 6 is reduced to 91.24% and 91.99% of the solar-power-dominated scenario. This work can help verify the day-ahead scheduling strategy of the electricity-HCNG integrated energy system (IES) and provide a reference for the design of local hydrogen production-blending systems.

Numerical analysis of performance and emissions behavior of a bi-fuel engine with compressed natural gas enriched with hydrogen using variable compression ratio strategy

The increase in the compression ratio reduces the fuel consumption and improves the performance. These effects of compression ratio could be observed in all of the engines, such as compression or spark ignition engines. Moreover, due to the compression ratio constraint based on the knocking phenomenon in spark ignition engines, there will always be an optimal compression ratio, which is one of the most fundamental factors in engine design. The optimum compression ratio could be achieved depending on the type of fuel, but in the case of bi-fuel engines, since the nature of each fuel is different, the design must be relatively optimal for both fuels. In this work, by using the VCR (variable compression ratio) strategy, the bi-fuel EF7 engine performance, combustion, and emissions were investigated in different compression ratios when the engine uses gasoline or HCNG (hydrogen enriched compressed natural gas) as fuel. The results revealed that by changing the compression ratio from 11.05 (actual compression ratio of engine) to 11.80 in HCNG mode, an increase of 13% in power could be achieved. Also CO formation, at the compression ratio of 11.80, was slightly lower (7%) than the compression ratio of 11.05. In addition, by reducing the compression ratio from 11.05 to 10.50 in gasoline mode, there was a significant increase in emissions; that was 44% for the NOx and 16% for the CO, which could be one of the limiting factors of the advance in spark timing. Moreover, due to the VCR strategy and the significant optimization of the compression ratio, the combinatory method of VCR – HCNG can be used as an effective method for the bi-fuel engines in order to improve the performance and reduce emissions.

Experimental study on combustion stability and performance of hydrogen-enriched compressed natural gas of a free-piston linear generator

Free Piston linear Generator (FPLG) engine fueled by compressed natural gas (CNG) has recently gained increased research attention. However, due to the low-velocity burning and poor lean limit of CNG fuel, the FPLG engine combustion stability, performance, and efficiency are still low. Hydrogen has a greater burning velocity with wider flame limits that could extend the lean burn limits and combustion characteristics of CNG. This paper compares pure CNG and 10% hydrogen-enriched CNG at various ignition speeds (0.6 ms, 0.8 m/s, and 1 m/s), injection positions (0 mm, 5 mm, 10 mm and 15 mm), and lambda ratios (0.9, 1.4 and 1.7) on the combustion characteristics, performance, and conversion efficiency are duly discussed. The findings show that the FPLG combustion stability limits increase with the hydrogen addition into the CNG. The CNG in-cylinder pressure increases significantly when the injection position is advanced, whereas the hydrogen addition reduces the influence of the injection position. The heat release rate increases by 15.62% and 23.72% with hydrogen addition, corresponding to the advanced and retarded injection positions. Consequently, the hydrogen addition increases the power RMS to 209.21 W and 232.64 W with an increment of 3.46% and 3.13%, respectively. Conclusively, the hydrogen addition into the CNG evidently shortens the combustion duration while improving the heat release rate, combustion stability, power RMS, Cycle-to-Cycle variation, and conversion efficiency.

Green Hydrogen-Compressed natural gas (bio-H-CNG) production from food waste: Organic load influence on hydrogen and methane fusion

Biogenic hydrogen (bioH2) enriched compressed natural gas (bio-H-CNG or biohythane) is emerging interest due to its feasibility to use in the existing transportation infrastructure with induced environmental benefits. This study evaluated the production of bioH2and biomethane (bioCH4) towards bio-H-CNG formation at a varying organic load (OL: 30,40,50 g COD/L) of food waste (FW). Acidogenic reactor operated with FW at 40 g COD/L showed the highest cumulative bioH2production while elevated OL (50 g COD/L)showedhigher cumulative bioCH4production (CMP: 11.92 L) from the methanogenic reactor. BioH2 and bioCH4 produced at different time intervals were combined to assess bio-H-CNG. The nature of biocatalyst and OLsignificantly regulated the composition of bio-H-CNG varying between 0.1 and 0.3 of H2/(H2+CH4) ratio accounting for5–12.6 kJ/g COD. Chain elongation, converting short (C2-C4) to medium-chain fatty acids(Caproic acid,1.16 g/L) was specifically observed during the acidogenic process.

Effect of hydrogen enrichment of compressed natural gas on combustible limit and flame kernel evolution in a constant volume combustion chamber using laser ignition

Laser ignition of hydrogen-enriched compressed natural gas (HCNG) enables lean-burn combustion, a key technology for future emissions norms compliance for internal combustion (IC) engines. HCNG overcomes the limitations of low volumetric energy density and lowers the flame speed of CNG fueled spark ignition (SI) engine-powered vehicles. In this study, laser beam profile and beam quality (M2) of a Q-switched Nd: YAG laser at fundamental wavelength of 1064 nm, having 6–9 ns pulse duration, were characterized. During the Constant volume combustion chamber (CVCC) experiments, relative air-fuel ratio (λ) of different HCNG blends were varied to identify the lean-burn limits, and observe flame kernel evolution, pressure–time history, and detect the start of combustion (SoC). At 10 bar initial chamber filling pressure, lean flammability limit increased due to hydrogen (H2) enrichment of CNG. It was found to be λ = 1.6, 1.8, 1.9, 2.0, and 2.1 for CNG, 10HCNG (10% v/v hydrogen and balance CNG), 20HCNG, 30HCNG, and 40HCNG respectively. Flame kernel displacement (Early stages of flame initiation and its development in µs time-scale) was the highest for λ = 1.1 for all HCNG mixtures, irrespective of the test fuel composition. Knocking or two-stage combustion increased with lowering λ at 10 bar initial chamber filling pressure. SoC advanced and combustion duration (CD) decreased with increasing H2 enrichment of CNG. Increased H2 enrichment of CNG accelerated the flame kernel evolution and made it a predominantly a 3D combustion phenomenon (volumetric combustion). Lower λ and higher H2 enriched CNG mixtures were effective in reducing the CD.

Numerical investigation of the effect of two-step injection (direct and port injection) of hydrogen blending and natural gas on engine performance and exhaust gas emissions

The present work investigates the effect of two-step fuel injection on a four-cylinder engine which has been altered from port injection to direct injection. Hydrogen enriched compressed natural gas (HCNG) blend has been utilized as a substitute in replacement of gasoline. Initially, CNG as a 10% of the total fuel mass fraction is injected into the air manifold and the remaining 90% fuel is HCNG which is injected into the cylinder by direct injection. Primarily, the CNG was injected at 160° BTDC with 20° stroke duration. HCNG fuel was injected at 130° BTDC with a 50° stroke duration being injected from (0%–40%) step.AVL software has been utilized for this investigation to inspect the engine performance, efficiency, fuel consumption, and exhaust emissions. The collected data indicates that by injecting 30% HCNG blend, the brake power, brake thermal efficiency, and in-cylinder pressure is increased from 8% to 13.64%, and the specific fuel consumption is reduced from 6.2% to 18% due to a rise in flame propagation speed in the combustion chamber. The addition of hydrogen has decreased carbon monoxide and unburned hydrocarbons by up to 14% on a complete combustion. NOx has been increased due to the increase in the exhaust gas temperature.

Experimental evaluation of laser ignited hydrogen enriched compressed natural gas fueled supercharged engine

Laser-induced ignition could be the most promising alternative to conventional spark ignition, in order to reduce engine-out emissions. A single-cylinder naturally aspirated, water-cooled, direct injection diesel engine (Kirloskar, DM-10) was adapted/ modified to supercharged spark ignition (SI)/ laser ignition (LI), port fuel injection (PFI) gaseous fueled engine operation at a compression ratio (CR) of 11, and the experiments were conducted at a constant engine speed of 1500 rpm. Compressed natural gas (CNG), Hydrogen (H2) and HCNG mixtures (CNG & H2 mixed on a volume basis) were used as test fuels in this study. Comparison of LI vs. SI mode of ignition was investigated for combustion, performance, and emission characteristics of different HCNG mixtures under identical maximum brake torque (MBT) timing of 31°CA bTDC with an increased boost. For HCNG experiments, a dynamic HCNG mixing system was designed and developed, which delivered HCNG mixtures of desired composition on demand dynamically to the engine. It was observed that during supercharging or boosting the engine, 0.1 bar boost was optimum boost. At optimum boost, engine torque increased in LI mode compared to SI mode and it varied from 29 Nm to 32.5 Nm for CNG and from 20 Nm to 24 Nm for H2. Maximum peak in-cylinder pressure (Pmax) reduced with H2 enrichment of CNG. Pmax was 47.62 bar for CNG, which reduced to 39.77 bar for 40HCNG. At optimum boost, LI mode improved brake thermal efficiency (BTE) from 36.9% to 37.82% for CNG and from 37.7% to 38.6% for 40HCNG. Brake specific fuel consumption (BSFC) in LI mode reduced from 0.20 kg/kWh for CNG to 0.180 kg/kWh for 40HCNG. In LI mode, exhaust gas temperature (EGT) reduced. In LI mode at 0.15 bar boost, BSCO, and BSNOx emissions reduced with H2 enrichment.

Development and comparative experimental investigations of laser plasma and spark plasma ignited hydrogen enriched compressed natural gas fueled engine

A customized port-fuel-injection (PFI) SI engine was operated in spark ignition (SI) and laser ignition (LI) modes at varying brake mean effective pressure (BMEP) and relative air-fuel ratio (λ) under naturally aspirated conditions. Test fuel used were hydrogen enriched compressed natural gas (HCNG) mixtures and results were compared with baseline CNG. For H2 enrichment of CNG, a customized dynamic fuel mixing system was developed. For LI, a solid state Q-switched Nd:YAG laser (200 mJ; 30 Hz; 6–9 ns) was used, and the laser beam was focused using a converging lens of 50 mm focal length. Experiments of HCNG fueling exhibited relatively higher peak pressure (Pmax) with its peak shifted closer to the top dead center (TDC). H2 enrichment of CNG led to increase in peak in-cylinder Pmax (by ∼2.9 bar), RoPR (by ∼0.72 bar/deg) and HRR (by ∼7.2 kJ/m3.deg) for 40HCNG compared to baseline CNG. The maximum BTE was observed to be ∼42.8% (at λ = 1.4) in LI mode for 30HCNG fueled engine. The lowest BSFC obtained were at λ = 1.2 for HCNG in SI mode, while corresponding value in LI mode was obtained at λ = 1.4. BSHC emissions were always lower for LI mode than the SI mode. At 3.96 bar BMEP, BSHC emissions reduced from 0.54 g/kWh (for CNG) to 0.35 g/kWh (for 40HCNG), which further reduced to 0.21 g/kWh (for H2) in LI mode. BSNOx emissions increased with increasing BMEP but reduced from 0.89 g/kWh at λ = 1.5 for CNG to 0.17 g/kWh for 30HCNG at λ = 1.7 at 30 Nm load.

Study of laminar burning speed and calibration coefficients of quasi-dimensional combustion model for hydrogen enriched compressed natural gas fueled internal combustion engine along with exhaust gas recirculation

Utilization of hydrogen fuel in internal combustion engine is regarded as a good choice due to its zero-carbon emission. The experiments have been performed under a wide range of operating conditions and the traces of in-cylinder pressures are obtained. The authors have formulated five laminar burning speed correlations (HCNG/N2, HCNG/N2/P, HCNG/CO2/T, HCNG/CO2/P & HCNG/CO) from the previous experimental work [25,31,33,34,38] while, two correlations (HCNG/N2/O2/T & HCNG/CO/CO2/T) have been imported from the earlier research work [32,35]. The iterations of these models have been staged in the quasi-dimensional combustion program of HCNG engine along with the exhaust gas recirculation but, results were un-satisfactory.Therefore, another laminar burning speed correlation (HCNG/N2/CO2/T) has been developed to improve the quasi-dimensional combustion model of HCNG fuel mixture along with the EGR technique. The kinetic GRI Mech3.0 mechanism has been utilized for the prediction of laminar burning speed of HCNG fuel mixtures at different hydrogen fractions 0 to 20% by volume in compressed natural gas, EGR ratios (0–0.3) and inlet temperatures (300–350 K). The effect of EGR ratio on the laminar burning speed in HCNG fuel mixture is introduced as the simultaneous impact of CO2 and N2 dilution of gases according to the balance chemical equation at stoichiometric condition. The presented model (HCNG/N2/CO2/T) is best suited for the quasi-dimensional combustion code of HCNG fuel mixture along with the exhaust gas recirculation as mean of the sample points of Taylor length & turbulent intensity coefficients are closer to 1 and minimum absolute percentage error for the indicated mean effective pressure.