Compressed Natural Gas Engine Research Articles

Feasibility and Performance Analysis of Cylinder Deactivation for a Heavy-Duty Compressed Natural Gas Engine

Feasibility and Performance Analysis of Cylinder Deactivation for a Heavy-Duty Compressed Natural Gas Engine

Thermoeconomic performance of supercritical carbon dioxide Brayton cycle systems for CNG engine waste heat recovery

The supercritical carbon dioxide (S–CO2) Brayton cycle is a potential technology for recovering waste heat from compressed natural gas (CNG) engines. To choose suitable cycle configurations is important considering the complex operating characteristics of CNG engines. The traditional evaluation models of the S–CO2 cycles configuration are relatively one-sided without the comprehensive considerations of evaluation metrics. On the basis of the analytic hierarchy process and information entropy theory, this paper proposes a multi-dimensional comprehensive evaluation method for S–CO2 cycles from three perspectives: thermodynamic, economic, and environmental performance. A thermoeconomic performance optimization is conducted using a non-dominated genetic algorithm Ⅱ. Unlike most of the existing researches that use a single stable operating condition, this paper considers the full operating conditions of engines. Results show that the recompression cycle has the best overall performance among the investigated cycles with an exergy efficiency and electricity production cost of 67.20 % and 0.45 $/kWh, respectively. The efficiency improvement of the CNG engine coupled with the WHR system can reach up to 6.31 %. This study can provide a new reference for the comprehensive multidimensional evaluation and performance characteristics and optimal performance acquisition under full engine operating conditions of the S–CO2 cycle.

Evaluation and Simulation Analysis of Mixing Performance for Gas Fuel Direct Injection Engine under Multiple Working Conditions

Gas fuel direct injection (DI) technology can improve the control precision of the in-cylinder mixing and combustion process and effectively avoid volumetric efficiency reduction in a compressed natural gas (CNG) engine, which has been a tendency. However, compared with the port fuel injection (PFI) method, the former’s mixing path and duration are shortened greatly, which often leads to poor mixing uniformity. What is worse, the in-cylinder mixing performance would be seriously affected by engine working conditions, such as engine speed and load. Based on this situation, the fluid mechanics software FLUENT is used in this article, and the computational fluid dynamics (CFD) model of the injection and mixing process in a gas-fueled direct injection engine is established. A quantitative evaluation mechanism of the in-cylinder mixing performance of the CNG engine is proposed to explore the influencing rule of different engine speeds and loads on the mixing process and performance. The results indicate that phase space analysis can accurately reflect the characteristics of the mixture mixing process. The gas fuel mixture rapidly occupies the cylinder volume in the injection stage. During the transition stage, the gas fuel mixture is in a highly transient state. The diffusion stage is characterized by the continuous homogenization of the mixture. The in-cylinder mixing performance is linearly dependent on the engine’s working condition in the phase space.

Numerical analysis of performance, combustion, and emission characteristics of PFI gasoline, PFI CNG, and DI CNG engine

Compressed natural gas (CNG) has gained widespread acceptance in the automobile industry due to its clean-burning properties, lower emissions, and superior anti-knock properties. Typically, CNG is used in bi-fuel mode, where it partially replaces gasoline in a conventional gasoline engine. However, because of its gaseous nature, CNG displaces intake air, which reduces the engine's overall power output. One possible solution is to directly inject CNG into the cylinder during the late intake stroke or at the beginning of the compression stroke, which increases the engine's volumetric efficiency and power output. In a previous study, we examined the impact of injection timing on the performance of direct injection (DI) CNG engines under various engine load and speed conditions. However, the intrinsic combustion process, such as flame speed and flame front propagation, could not be investigated. In this study, we attempted to understand DI CNG engines' in-cylinder flame speed and propagation behavior. We developed a combustion model for the DI CNG engine using computational fluid dynamics. We used methane as the surrogate fuel and six cylindrical nozzles with inlet velocity boundary conditions for CNG direct injection. We studied the CNG combustion process and flame speed propagation using a validated chemical mechanism and a look-up table. We made comparisons to evaluate the numerical model against experimental reference data. We also conducted a comparative simulation of DI CNG, port fuel injection (PFI) CNG, and gasoline engines to assess combustion behavior. The combustion duration was longer for the PFI CNG engine than the gasoline engine, but it was reduced for the DI CNG engine. This was due to the DI CNG engine's 40% higher turbulent flame speed than the PFI CNG engine. The combustion of the air-fuel charge was completed within 40° CA after spark ignition. As a result, DI CNG requires a retard in ignition timing. The DI CNG engine showed a 7% higher power output with a 10% increase in volumetric efficiency compared to the PFI CNG engine. However, the power output was still lower than that of the PFI gasoline engine. The DI CNG engine emitted lower NOx and CO emissions than the PFI CNG engine. This study demonstrates the higher turbulent flame speed and rapid flame front propagation characteristics of DI CNG engines over PFI CNG engines, increasing engine efficiency.

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.

Thermoelectric Generation From Exhaust Heat in Electrified Natural Gas Trucks: Modeling and Analysis of an Integrated Engine System Performance Improvement

AbstractUsing thermoelectric generators (TEG) to reduce exhaust heat loss from internal combustion engines can improve emissions and the fuel economy of conventional and electrified vehicles. However, TEG potentials have not been investigated in hybridized, compressed natural gas (CNG), twin-turbocharged, and spark-ignited (SI) engines. This work demonstrates TEG's effectiveness in boosting a hybridized 3.0 L CNG engine using model-based development. TEG experiments are performed to measure thermal performances under different inlet gas conditions for model validations. Simplified user-defined functions of flow friction and heat transfer coefficients are used to calibrate the model. A fast-calibration model can reproduce measured heat transfer, pressure drop, and thermal performances. The engine performances are validated against measured 35 steady-state conditions from the production engine used in light-duty CNG trucks under the JE05 drive cycle. Next, the model is connected to the turbocharging system downstream of the well-calibrated four-cylinder SI engine model. Under the peak performance condition (peak brake thermal efficiency BTE at 2400 RPM and 102 kW load), the results show that the engine BTE is improved by 0.56% using a 7 × 9 TEG module arrangement (three-sheet TEG with 1.5× A4 size). A 9 × 10 arrangement can enhance the BTE to 0.8%. Effective electrical power is generated up to 1.168 kW from the TEG, depending on the JE05 operating regions, without significant brake power loss.

Comprehensive Performance Assessment of Dual Loop Organic Rankine Cycle (DORC) for CNG Engine: Energy, Thermoeconomic and Environment

The improvement of the overall utilization rate of compressed natural gas (CNG) engine fuel is the basis of efficient energy utilization. On the foundation of heat balance theory of internal combustion engines, this study fully considers the operation characteristics of CNG engines and systematically analyzes the distribution characteristics of different waste heat under variable working conditions. The nonlinear relationship between speed and intercooler heat source becomes evident with the increasing of intake mass flow rate. In accordance with the structural characteristics, the thermodynamic model, heat transfer model and environmental model of dual-loop organic Rankine cycle (DORC) are constructed. The system potential in full working environments is systematically evaluated. Compared with the speed, airmass flow has a significant effect on comprehensive performance of loop. The maximum power, heat transfer area and power output of per unit heat transfer area (POPA) of DORC are 36.42 kW, 23.34 m2, and 1.75 kW/m2, respectively. According to the operating characteristics of different loops, the variation laws of loop performance under the influence of multiple parameters are analyzed. The synergistic influence laws of multiple variables on system performance are also analyzed.

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.

Towards tailpipe sub-23 nm solid particle number measurements for heavy-duty vehicles regulations

A heavy-duty engine is type-approved in engine dynamometers, while its in-service conformity is controlled on the road. In the first case, laboratory particle number systems (LABS) sample from a full dilution tunnel or a proportional partial flow dilution system (PFDS). In the second case portable emissions measurements systems (PEMS) measure directly from the tailpipe. Permitting in the regulation LABS sampling directly from the tailpipe would simplify testing and would improve their comparability with PEMS. In this study PEMS and LABS, both sampling from the tailpipe and measuring solid particles >10 nm, were compared with references systems (i.e. LABS from PFDS). One compressed natural gas (CNG) engine, and three diesel engines, all Euro VI step E, with or without urea injection, and with or without crankcase ventilation connected to the tailpipe, challenged the systems with different emission levels and particle sizes and properties. The results showed that the differences of the LABS to the references were in most cases within ±25%, with a few exceptions. The PEMS were within ±50%. There was no or small effect on the differences from engine technology, urea injection or crankcase ventilation. The inclusion of sub-23 nm particles increased 100% to 250% the particle number emissions. The urea injection increased the >10 nm emissions 300–600% (2–5 × 1010 p/kWh). Connecting the crankcase ventilation to the tailpipe further increased the >10 nm particle number emissions 340–560% (1.4–2.5 × 1011 p/kWh), bringing the >10 nm levels of the engines to approximately half of the current particle number limit, applicable to particles >23 nm.

Experimental Study on CNG Engine with Different Ventury Configuration

Low carbon to hydrogen ratio of compressed natural gas (CNG) is counted as one of the better potential as an alternate fuel instead of conventional fuel for an internal combustion engine. CNG engines have very low particulate emission and lower brake specific fuel consumption compared to conventional fuelled IC engines. Design of carburetion system plays vital role in both conventional CNG engines as well as in dual fuel engines in consideration of better performance and emissions. The restriction barrel named venturi governs the crucial operation of the carburetor. In the presented study, main intention was to achieve an optimum ratio by suitably designing a venturi type gas mixer which mixes the CNG gas with incoming air. Fulfilling the design need, three venturi type gas mixer were designed by varying number of holes, hole size and throat diameter. A four stroke, single cylinder, VCR research engine was used to trial with different venturi configuration for engines carburetion system and their performance as well as exhaust emissions were compared. According to the experimental results, venturi 2 with 23 mm throat diameter and 8 numbers of holes was resulted the most optimal venturi design. During the experimentation at full load, air–fuel equivalence ratio was found close to 1 and equivalence ratio to 0.88, which is the need of CNG engines to run smoothly. This satisfies the venturi type gas mixer design requisite for CNG engine. It is also observed that optimized number of holes improves the engine performance and emission as well.

Dynamic Response Characteristics Analysis and Energy, Exergy, and Economic (3E) Evaluation of Dual Loop Organic Rankine Cycle (DORC) for CNG Engine Waste Heat Recovery

Frequent fluctuations of CNG engine operating conditions make the waste heat source have uncertain, nonlinear, and strong coupling characteristics. These characteristics are not conducive to the efficient recovery of the DORC system. The systematic evaluation of the CNG engine waste heat source and the comprehensive performance of the DORC system is conducive to the efficient use of waste heat. Based on the theory of internal combustion (IC) engine thermal balance, this paper analyzes the dynamic characteristics of compressed natural gas (CNG) engine waste heat energy under full operating conditions. Then, based on the operating characteristics of the dual loop organic Rankine cycle (DORC) system, thermodynamic models, heat transfer models, and economic models are constructed. The dynamic response characteristics analysis and energy, exergy, and economic (3E) evaluation of the DORC system under full operating conditions are carried out. The results show that the maximum values of net power output, heat exchange area, and the minimum values of EPC (electricity production cost) and PBT (payback time) are all obtained under rated condition, which are 174.03 kW, 25.86 kW, 37.54 kW, 24.76 m2, 0.15 $/kW·h and 3.46 years. Therefore, the rated condition is a relatively ideal design operating point for the DORC system. The research in this paper not only provides a reliable reference for the comprehensive analysis and evaluation of the performance of the DORC system, but also provides useful guidance for the selection of appropriate DORC system design operating points.

Upgrading the performance of a six-cylinder CNG Engine with the induction of Turbocharger for HCV application

The world is having catastrophe of environmental pollution and fossil fuel depletion. Adaptation of alternative fuels is a healthy solution in reducing exhaust emissions in the automobile sector. Compressed Natural Gas (CNG) as a fleet fuel has played a vital role in the HCV sector. Many developmental and optimization work has been taken place for the CNG engines in the recent times. Due to the recent upsurge in diesel prices, the HCV sector is moving towards the CNG fuel vehicle. The HCV sector requires a heavy performance engine for its day-to-day application. In this research paper a baseline six-cylinder, naturally aspirated CNG engine used for bus application is selected to upgrade its power and torque performance. Based on the baseline CNG engine data, an appropriate turbocharger for the engine is selected with the help of M/s Garrett turbocharger manual. A 2-D simulation of the turbine is also carried out to understand the pressure and temperature distribution profile inside the turbine. The experimental results showing the increase in power, torque, volumetric efficiency, BMEP and thermal efficiency is illustrated in the research work below.

Thermodynamic analysis and high-dimensional evolutionary many-objective optimization of dual loop organic Rankine cycle (DORC) for CNG engine waste heat recovery

The complex and changeable working conditions of compressed natural gas (CNG) engines have brought great challenges to the efficient recovery of waste heat energy. The dual loop organic Rankine cycle (DORC) system can effectively recover and utilize CNG engine waste heat due to its structural advantages. Determining the nonlinear variations between operating parameters and thermodynamic performance serves as the basis for obtaining the thermodynamic performance limits of the DORC system. However, traditional analysis methods have obvious limitations in this area. Based on the bilinear interpolation algorithm, this paper comprehensively analyzes and evaluates the nonlinear and strong coupling characteristics between operating parameters and net power output, thermal efficiency, and exergy destruction. In addition, the comprehensive thermodynamic performance limits of the DORC system have a critical effect on its engineering application yet have not been thoroughly and comprehensively optimized. Therefore, this paper proposes an equilibrium-based thermodynamic high-dimensional evolutionary many-objective optimization (EMO) method for the DORC system. The optimal thermal efficiency, net power output, and total exergy destruction of the DORC system reached 37.11 kW, 14.27%, and 104.58 kW, respectively. Based on the optimization results under equilibrium and unequilibrium weight, the dominant relationship between the different thermodynamic performances of the DORC system is then analyzed. This research can provide a direct reference for analyzing and optimizing the comprehensive thermodynamic performance of the DORC system.

Development of in-use engine speed/torque heat maps across multiple heavy-duty commercial vehicle vocations

The U.S. Department of Energy (DOE) established the SuperTruck program with the goal of achieving brake thermal efficiency (BTE) greater than or equal to 55% as demonstrated in an operational heavy-duty (HD) diesel engine at a 65-miles-per-hour (mph) cruise point. Beyond the line-haul application, HD engines operate in a wide range of speed and torque conditions that are unlikely to yield the same efficiency under real-world operation. Thereby, the in-use engine heat maps described in this paper are a valuable tool to illustrate whether the engine-efficiency “sweet spot” matches the most frequent operating conditions. In this study, NREL developed engine heat maps to quantify the important operating points for various vocations using our Fleet DNA database of commercial fleet vehicle operations data. These heat maps clearly show that high-frequency operating points vary significantly according to vehicle vocation, while only a few of them match the sweet spot. Beyond the illustration, engine in-use heat maps can also be leveraged to build up reduced-order engine-efficiency models, needed by many rapid powertrain simulations. As case studies, nine reduced-order models – including line-haul truck, transfer truck, transit bus, transit bus with compressed natural gas (CNG) engine, drayage, refuse pickup, local delivery, utility truck, and school bus with CNG engine – using a trust-region reflective algorithm to fit the on-road data extracted based on the engine in-use heat maps.

Effect of compression ratio on engine knock, performance, combustion and emission characteristics of a bi-fuel CNG engine

Compressed natural gas (CNG) is considered one of the most promising alternative fuel used in the transport sector. CNG has high octane number, wide flammability limit, and high H/C ratio, brings in important aspects regarding its feasibility as a fuel for internal combustion engines. It is necessary to have a dedicated engine rather than retrofitted, bi-fuels or dual-fuel ones to exploit the full potential of CNG properties. Most vehicles use the CNG in bi-fuel mode, where the fuel system is modified to operate either on gasoline or CNG. Therefore, the engine's compression ratio (CR) needs to be determined according to gasoline fuel requirement. However, CNG can be used at a higher CR, and the performance of the engine can be improved. The aim of this study is to investigate the effect of CR on knock intensity, performance, combustion, and emissions of a spark ignition (SI) engine fuelled with gasoline and CNG. Gasoline and CNG engine's performance were compared at different CRs and stoichiometric air-fuel ratio. The results show that the knock intensity was high at CR 12 and 7 bar indicated mean effective pressure (IMEP) for the gasoline-fueled engine. The maximum CR was limited to 12 for the gasoline engine. However, Knock was not observed even at CR 16 for the CNG engine. The engine was successfully operated at CR 16 with CNG. The performance and emission of the engine were also compared and presented. Fuel consumption and thermal efficiency were improved for CNG at higher CR compared to the gasoline engine.

Thermodynamic, economic, and environmental analysis and multi-objective optimization of a dual loop organic Rankine cycle for CNG engine waste heat recovery

• Thermodynamic, economic, and environmental analysis are presented. • Proposing a multi-model driven NSGA-III method for DORC performance optimization. • A tradeoff appears among thermal efficiency, payback period and CO 2 emission. Waste heat energy exists in the exhaust, intercooler, and coolant during the operation of the compressed natural gas (CNG) engine. The cascade utilization of the waste heat energy of the CNG engine can be realized considering the structural advantages of the dual loop organic Rankine cycle (DORC) system. Operating parameters have an important influence on DORC system performance. Traditional analysis methods have limitations in analyzing the relationship between operating parameters and system performance, and little attention is paid to the environmental impact of the system. The environmental performance of the system plays an important role in saving energy and protecting the environment. Therefore, the bilinear interpolation algorithm is introduced to analyze the waste heat sources of the CNG engine and the thermodynamic, economic, and environmental performances of the DORC system. In addition, the comprehensive operating performance of the DORC system has not been thoroughly and comprehensively optimized. Therefore, this study proposes a multi-model driven NSGA-III method for DORC comprehensive performance optimization. Results show that the optimal thermal efficiency, payback period (PB), and emissions of CO 2 equivalent (ECE) are 11.98%, 4.02 years, and 43.74 ton CO 2,eq , respectively. Moreover, decreasing the thermal efficiency of the system will significantly decrease ECE and increase PB at the same time. This research provides a reliable reference for the analysis, design, evaluation, and optimization of the comprehensive performance of the DORC system.

Effect of Hydrogen Addition on the Energetic and Ecologic Parameters of an SI Engine Fueled by Biogas

The global policy solution seeks to reduce the usage of fossil fuels and greenhouse gas (GHG) emissions, and biogas (BG) represents a solutions to these problems. The use of biogas could help cope with increased amounts of waste and reduce usage of fossil fuels. Biogas could be used in compressed natural gas (CNG) engines, but the engine electronic control unit (ECU) needs to be modified. In this research, a spark ignition (SI) engine was tested for mixtures of biogas and hydrogen (volumetric hydrogen concentration of 0, 14, 24, 33, and 43%). In all experiments, two cases of spark timing (ST) were used: the first for an optimal mixture and the second for CNG. The results show that hydrogen increases combustion quality and reduces incomplete combustion products. Because of BG’s lower burning speed, the advanced ST increased brake thermal efficiency (BTE) by 4.3% when the engine was running on biogas. Adding 14 vol% of hydrogen (H2) increases the burning speed of the mixture and enhances BTE by 2.6% at spark timing optimal for CNG (CNG ST) and 0.6% at the optimal mixture ST (mixture ST). Analyses of the rate of heat release (ROHR), temperature, and pressure increase in the cylinder were carried out using utility BURN in AVL BOOST software.

Quantitative and qualitative analysis of thermodynamic process of a bi‐fuel compressed natural gas spark ignition engine

AbstractA comparative energy and exergy analysis was experimentally performed using a bi‐fuel compressed natural gas (CNG) spark ignition engine. The experiments were conducted for gasoline and CNG fuel at 1700 rpm and different operating loads from 5 to 30 Nm. The experiments were performed under stoichiometric air‐fuel ratio and maximum brake torque ignition timing. Quantitative and qualitative analysis were conducted using the first and second law of thermodynamics, respectively. The effect of engine operating load on various energy and exergy parameters was compared for both the fuels. Output energy with respect to engine load was found higher for CNG compared to gasoline. Engine wall heat transfer was also higher in the CNG engine case due to its high combustion chamber temperature and lower burning velocity. The difference in heat transfer energy fraction between gasoline and CNG gradually increased with engine load. The exhaust energy was found maximum in the case of CNG under low operating load and reduced to a minimum at higher engine operating load. The unaccounted energy fraction was found lower for the CNG engine and reduced with respect to engine load. CNG exhibits the highest exergy efficiency (26.80%) compared to gasoline (25.50%) at 30 Nm load. On average, a 2% higher exergy efficiency was observed with the CNG engine at all operating load conditions. This indicates CNG has a higher potential to convert chemical energy present in the fuel into useful work output. CNG shows lower exergy destruction at all operating loads compared to gasoline, and it reduces significantly at higher engine loads. In all operating loads, exergy transfer due to exhaust gas and heat transfer to the wall was higher in the case of CNG.

Real-world activity, fuel use, and emissions of heavy-duty compressed natural gas refuse trucks

Over 50% of new refuse truck sales have been compressed natural gas (CNG). Compared to diesel, CNG is less expensive on diesel gallon equivalent (dge) basis. This study quantifies the real-world fuel use and tailpipe exhaust emissions from three front- and three side-loader refuse trucks, each with a spark ignition CNG engine, three-way catalyst, and similar gross weight. Measurements were made at 1 Hz using a portable emissions measurement system (PEMS). Inter-cycle and inter-vehicle variability is quantified. Effect of vehicle weight was analyzed and comparisons were made with MOVES predicted cycle average emission rates. In total, about 220,000 s of data covering 490 miles of operation were recorded. The average fuel economy was 1.9 miles per dge. On average the trucks spent 53% of time in idle, which includes trash collection activity. The average speeds were 10 mph and 5 mph, for front- and side-loader trucks, respectively. Overall, compared to side-loader trucks, front-loader trucks had 55% better fuel economy and 60% lower emission rates. Compared to diesel trucks, CNG truck cycle average NOx and PM emission rates, at 1.2 g/mile and 0.006 g/mile respectively, were substantially lower while CO and HC rates, at 29 g/mile and 6 g/mile respectively, were considerably higher. Fuel use and CO2 emissions rates increased by 10% due to increase in truck weight during trash collection, while CO emissions rates increased by up to 30%. Compared to measured values, MOVES estimated cycle average fuel use and CO2 emissions were 25% lower, CO emissions are 70% lower, and NOx emissions were 200% higher. Results from this study can be used to improve solid waste life cycle and tailpipe emission factor models and, when combined with previous studies on diesel refuse trucks, evaluate the effect on fuel use and emissions from adoption of CNG refuse trucks.

Implementation of fuel additive MAZ 100 for performance enhancement of compressed natural gas engine converted from in-used gasoline engine

ABSTRACT Compressed Natural Gas (CNG) has been applied worldwide for in-used engines, especially CNG engines that are converted from the conventional engines. However, it encounters the problem related to the low power and high fuel consumption of the conventional engine fueled by CNG. This paper presents an experimental study on performance enhancement of a CNG engine converted from the spark-ignition engine by the implementation of fuel additive Maz 100. In experimental work, a fuel additive supplying system was developed to impose a certain amount of fuel additive to the intake manifold of the test engine. The study results show that when using Maz 100, the brake power of the test engine improves approximately 6.75% on average at full load conditions. The brake specific fuel consumption (BSFC) reduces 6.49% on average at full load and 3.53% on average at partial load condition. In addition, besides the benefit of performance enhancement, exhaust emissions of the test engine in the case of operating with fuel additive have changed considerably. Particularly, the CO emission reduces 36.1% at full load and 18.4% on average at partial load conditions. The HC emission reduces 37.1% at full load and 35.0% on average at partial load conditions. The NOx emission increases slightly in low-speed regimes and reduces in high-speed regimes when the engine operates at the full opened throttle condition. At partial load condition and speed of 3000 rpm, the NOx emission reduces 22.6% on average. Implications: This paper presents a solution for performance enhancement and emission reduction of natural gas engine by using fuel additive. Performance and emission characteristics of the natural gas engine fueled with fuel additive have been assessed in the laboratory. The performance of the test engine improves remarkably. The brake power of the test engine improves approximately 6.75% on average at full load conditions when the engine operates with fuel additive. The brake specific fuel consumption reduces 3.53% on average at partial load condition. The emission of pollution has different trends. The CO and HC emission reduces at testing conditions. The NOx emission increases slightly in low-speed regimes and reduces in high-speed regimes when the engine operates at the full opened throttle condition. The implementation of fuel additive is a potential solution for power improvement and emission reduction of natural gas engine.