
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)13638-9
10.1016/j.heliyon.2024.e37607
e37607
Research Article
Exergetic investigation of the influence of injector location in HCCI engines utilizing DEE as pilot fuel and biogas as primary fuel
Samavedam Aditya Sai a
C.V. Prasshanth a
Sreekanth Manavalla ab
Khan T.M. Yunus cd
Almakayeel Naif ce
M Feroskhan feroskhan.m@vit.ac.in
a⁎
a School of Mechanical Engineering, Vellore Institute of Technology Chennai, Chennai, 600127, India
b Electric Vehicles Incubation, Testing and Research Centre, Vellore Institute of Technology Chennai, Chennai, 600127, India
c Central Labs, King Khalid University, AlQura'a, Abha, P.O. Box 960, Saudi Arabia
d Department of Mechanical Engineering, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia
e Department of Industrial Engineering, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia
⁎ Corresponding author. feroskhan.m@vit.ac.in
07 9 2024
30 9 2024
07 9 2024
10 18 e3760730 5 2024
26 7 2024
6 9 2024
© 2024 The Authors
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
To address the global demand for sustainable energy, integrating biogas into internal combustion engines is becoming more important. Homogeneous Charge Compression Ignition (HCCI) engines, known for high efficiency and low emissions, offer a promising solution. This study investigates the optimal injector location for using biogas in HCCI engines, with diethyl ether (DEE) as the pilot fuel, evaluating three positions: (i) at the port, (ii) 6 cm away (Manifold 1), and (iii) 10 cm away (Manifold 2). Through experiments and simulations, the impact of injector location on engine performance is analyzed across various parameters, including methane fractions, engine loads, and exhaust gas compositions. Results show that port injection achieves the highest first law and exergy efficiencies but increases emissions of hydrocarbons (HC), carbon monoxide (CO), and smoke. At 15 Nm load, Manifold 1 shows a 27.34 % reduction in exergy efficiency compared to port injection, while Manifold 2 exhibits an 18.49 % decrease at higher loads. Despite lower efficiencies, Manifold 1 effectively reduces harmful emissions. The study also considers exergo-economic and sustainability aspects, highlighting that while port injection is optimal for efficiency, Manifold 1 excels in minimizing HC and CO emissions, with a 50 % reduction in HC and 71.43 % reduction in CO emissions at 15 Nm load compared to port injection. Manifold 2 achieves the lowest smoke emissions across all loads. This investigation provides crucial insights into optimizing HCCI engines for biogas utilization, emphasizing injector location, fuel composition, and operating parameters to enhance performance and reduce environmental impact.

Keywords

Homogeneous charge compression ignition engine (HCCI engine)
Biogas
Diethyl ether
Pilot fuel
Injector location
==== Body
pmc Nomenclature:

Symbol	Description	Unit	
c	Cost per unit of exergy	$/kW	
CxCO2	Cost of carbon dioxide emissions	$/hr	
DN	Depletion Number	–	
E˙x	Exergy	kW	
ExCCO2	Total cost of carbon dioxide emissions	$/hr	
Ef	Capital factor of investment	–	
f	Exergo-economic factor	–	
h	Specific enthalpy	kJ/kg	
Hu	Lower heating value	kJ/kg	
IP˙	Improvement Potential	kW	
i	Interest rate	–	
m	Mass	kg	
m˙	Mass flow rate	kg/s	
Mf	Engine maintenance factor	–	
n	Engine lifespan	years	
NCO2	Mass of carbon dioxide emissions	kg	
PCO2	Cost of carbon dioxide emissions	$/kg	
Pb	Brake power	kW	
Q	Heat transfer	kW	
R‾	Universal gas constant	kJ/kmol.K	
s	Specific entropy	kJ/kg.K	
SI	Sustainability Index	–	
T	Temperature	K	
tyear	Annual usage hours of engine	–	
ye	Mole fraction of components in reference environment	–	
Z	Initial investment cost	$	
Z˙	Investment cost ratio	$/hr	
ε˙	Specific exergy	kJ/kg	
φ	Exergy factor	–	
η2/Ψ	Exergy efficiency	–	
Subscripts	
0	Reference/dead state		
air	Air		
b	Brake		
chm	Chemical		
dest	Destroyed		
eg	Exhaust gases		
fuel	Fuel		
gen	Generated		
heat	Heat transfer		
in	Inlet		
loss	Losses		
m	Measured		
out	Outlet		
phy	Physical		
w	Work		

1 Introduction

The global urgency to transition towards sustainable and environmentally-friendly energy sources has never been more imperative, as the planet faces the pressing challenges of climate change and the depletion of finite fossil fuel reserves. In this shifting landscape, biogas emerges as a ray of hope a renewable energy source derived from organic matter through anaerobic digestion, poised to revolutionize the energy industry [1]. By integrating biogas into cutting-edge HCCI engines, a pathway towards enhanced energy efficiency, reduced emissions, and significant strides in environmental preservation is unlocked [2]. This study delves deep into the intricacies of utilizing biogas in HCCI engines, examining the challenges, opportunities, and transformative impacts enabled by technological advancements in shaping a sustainable future. Biogas, a mixture of methane, carbon dioxide, and various minor constituents like ammonia, hydrogen sulphide, and water vapour, boasts of unique combustion traits such as a high auto-ignition temperature and a relatively narrow flammability range [3]. These distinctive properties present a blend of opportunities and challenges when applied in the context of HCCI combustion. A profound understanding of these characteristics is essential for optimizing engine performance and emissions to meet stringent environmental standards. In this study, the focus is on identifying the optimal injector location in an HCCI engine using DEE as the pilot fuel alongside biogas. The analysis encompasses the evaluation of exergy output from the HCCI engine under varying methane fractions, different injector locations, diverse exhaust gas compositions, and varying engine load conditions. By delving into the intricacies of injector placement and its impact on combustion efficiency, insights aimed at enhancing the performance and sustainability of HCCI engines utilizing biogas as a fuel source are sought. Through meticulous examination and experimentation, the aim is to shed light on the intricate interplay between injector position, methane content, exhaust gas characteristics, and engine load within the HCCI combustion process. By uncovering the optimal configuration that maximizes exergy output and minimizes environmental impact across different load conditions, a contribution is made to the advancement of renewable energy utilization in the automotive sector.

In the evolving landscape of green combustion technologies, extensive research has been dedicated to unravelling the complexities of biogas utilization in engines, with a particular focus on HCCI and Compression Ignition (CI) engines. For Instance, Feroskhan et al. [4], conducted a meticulous study on HCCI engine operation with simulated biogas and DEE as primary and secondary fuels. Their investigation revealed that biogas could effectively substitute DEE, providing up to 60 % of the total energy input. Lower biogas flow rates and methane fractions were found to improve thermal efficiency, while HCCI operation exhibited low NOx and smoke emissions. The study emphasized the importance of manifold injection over port injection for optimizing engine output. Similarly, Srinivasan et al. [5], addressed challenges associated with using methane as a primary fuel in HCCI engines due to its high auto-ignition temperature. They proposed combining methane with DEE as a secondary fuel in HCCI mode. The study demonstrated that port injection yielded enhanced thermal efficiency at lower RPM, while manifold injection showed superiority at higher RPM, emphasizing the crucial role of injection strategy in engine performance optimization. In a related vein, Spanò et al. [6], proposed the utilization of e-fuels in HCCI engines, particularly exploring oxygen-enriched combustion to enhance reactivity and expand the operating range. Experimental findings indicated a significant reduction in intake temperature requirements with increased oxygen content, although challenges associated with high oxygen levels were acknowledged. Moreover, Mishra et al. [7], investigated the environmental advantages of biogas as an alternative fuel for HCCI engines. Their study revealed that port injection provided higher thermal efficiency, while manifold injections led to lower emissions. The study highlighted the versatility of HCCI engines in achieving improved control over NOx generation and enhanced thermal efficiency when using biogas. In another investigation, Feroskhan et al. [8], explored methane enrichment to enhance the performance of an HCCI engine using raw biogas and DEE. Their study showcased improved brake thermal efficiency, advanced combustion, and reduced emissions with methane enrichment. The significance of manifold injection of DEE was underlined in enhancing efficiency compared to port injection. Similarly, Jairam et al. [9], conducted Computational Fluid Dynamics investigations into homogeneity in air-fuel mixture formation in a Biogas-DEE HCCI engine. They demonstrated that port injection achieved better homogeneity, emphasizing the superiority of port injection in achieving optimal mixture homogeneity. Furthermore, Feroskhan and Ismail [10], compared dual fuel or HCCI modes with conventional diesel operation in utilizing biogas in CI engines. They revealed the potential of HCCI mode for simultaneous reduction in NOx and smoke emissions, while dual fuel operation offered high thermal efficiency and diesel substitution. Adding to this body of work, Polat et al. [11], aimed to expand the working range of HCCI engines by improving fusel oil properties with DEE. Increasing DEE ratio extended the operating range, improving indicated mean effective pressure and thermal efficiency, influencing combustion duration, emissions, and hydrocarbon levels, thereby enhancing HCCI engine performance. Moreover, Safieddin et al. [12], utilized the response surface method to investigate the performance and emissions characteristics of an HCCI engine fuelled with fusel oil/DEE. They identified optimal conditions leading to high torque, low COV imep, and minimal emissions, showcasing the effectiveness of the response surface method in optimizing engine working conditions. In parallel, Duan et al. [13], provided a comprehensive review focusing on effective techniques and controlling strategies in HCCI engines, highlighting strategies such as fuel management, homogeneous charge preparation, and exhaust gas recirculation. In the domain of green combustion technologies, researchers have delved deeper into the intricacies of engine operation and fuel utilization, expanding the knowledge base surrounding HCCI and CI engines.

Saxena et al. [14], initiated a comprehensive exploration of syngas-fuelled HCCI engines, employing a stochastic reactor model (SRM) for chemical kinetic simulation. Their study rigorously compared and evaluated the performance of various reaction mechanisms, ultimately validating a detailed reaction mechanism (CRECK-2014) with 173 reactions and 32 species against experimental combustion pressure data. Notably, the numerical simulation using this validated mechanism enabled the investigation of the HCCI engine at different operational conditions, resulting in the development of syngas HCCI maps based on combustion characteristics. Sarkar et al. [15], delved into the utilization of raw biogas as a renewable fuel in compression ignition engines, focusing on dual-fuel mode. Their investigation considered parameters such as global fuel-air equivalence ratio, intake charge preheating, and blends of liquid oxygenated fuels with diesel. Notably, the study identified diethyl ether (TB-DEE) blends as particularly effective in improving energy and exergy potential, achieving significant reductions in CO and unburnt hydrocarbon emissions at higher loads. The findings underscored the significance of preheating in enhancing overall engine performance. Freund et al. [16], ventured into the thermodynamics and economics of hydrogen production, power, and heat generation. They developed a Python model to analyse partial oxidation of methane in HCCI engines, including a comparison of two hydrogen separation technologies: pressure swing adsorption (PSA) and palladium membrane separation. Consistently, PSA outperformed the latter. The key contribution of the study laid in identifying optimal engine operating parameters and evaluating power and hydrogen costs, positioning the proposed polygeneration system as a promising alternative for hydrogen production. Natesan et al. [17], directed their focus toward investigating the performance, combustion, and emission behaviours of diethyl ether (DEE) and compressed natural gas (CNG) in a direct injection compression ignition engine. Their analysis considered various operating conditions and inlet charge temperatures, revealing a significant increase in maximum brake thermal efficiency in dual-fuel mode. Notably, the study emphasized the effectiveness of CNG in dual and HCCI modes for improving engine operation. In pursuit of a greener alternative, Maurya et al. [18], conducted numerical simulations for an HCCI engine fuelled with ethanol, utilizing a newly developed reduced ethanol oxidation mechanism. Their study, validated against experimental data, conducted a parametric study for combustion and emission characteristics. The developed HCCI operating maps based on combustion efficiency and maximum rate of pressure rise provided valuable insights into the operational range of the engine and areas of excessive exergy destruction. Advancing the exploration of HCCI engines, Djermouni et al. [19], presented a thermodynamic analysis of a system comprising a turbocharged HCCI engine, a mixer, a regenerator, and a catalytic converter. Their comprehensive study delved into the influence of various parameters, including compressor pressure ratio, ambient temperature, equivalence ratio, and engine speed, on the performance of the HCCI engine. The results indicated that thermal and exergetic efficiencies increased with the compressor pressure ratio, offering valuable insights for optimizing engine performance. Schröder et al. [20], studied a polygeneration system featuring a HCCI engine, a water-gas shift reactor (WGSR), and a palladium membrane for hydrogen separation. Their exergo-economic analysis highlighted the sensitivity of system costs to specific components investment costs. The study positioned the proposed system as a promising solution, providing hydrogen at competitive costs and emphasizing its potential in a sustainable energy landscape. Neshat et al. [21], addressed the inherent challenges of controlling combustion timing in HCCI engines by investigating the effect of reformer gas addition. Their study, utilizing a multi-zone model coupled with a detailed chemical kinetics mechanism, revealed a reduction in irreversibility and exergy loss due to convective heat transfer with reformer gas addition. The findings emphasized optimal reformer gas percentages for different primary reference fuels, contributing to the understanding of HCCI combustion control. In a detailed exploration of HCCI engines, Saxena et al. [22], conducted a comprehensive exergy analysis, providing a crank-angle resolved breakdown of mixture exergy and exergy destruction. Their study, incorporating a multizone HCCI simulation with detailed chemical kinetics, quantified the relative importance of various loss mechanisms. The proposed exergy analysis methodology emerged as a valuable tool for informing research and design processes in HCCI engines. Khaliq et al. [23], investigated the energy and exergy analyses of a hydrogen-operated HCCI engine integrated with an organic Rankine cycle (ORC). Their study revealed significant variations in energy and exergy efficiencies with changes in percent excess air and ambient temperature. The integration of ORC considerably increased exergy efficiency, providing quantitative insights into losses within the cycle and establishing clear trends for optimization. Similarly, Calam et al., presented a comprehensive analysis of the impact of various alternative fuels on the combustion, performance, and emissions characteristics of HCCI engines, highlighting ethanol (E25) for its high indicated mean effective pressure and naphtha (N25) for its extensive operating range and low emissions [24]. Additionally, Halis et al., presented an in-depth study on RCCI combustion in diesel engines, demonstrating that increasing intake air temperature improves exergy efficiency and decreases exergy destruction, with optimal thermal and exergy efficiencies achieved at 2000 rpm and 70 °C intake air temperature [25]. Many more studies have been conducted in the field of engine performance, as shown in Table 1.Table 1 Summary of research focus on alternative fuels and combustion technologies in engine systems.

Table 1Reference	Major Focus of Study	
[26]	Investigation of the combustion characteristics of biogas fuel in homogeneous charge compression ignition (HCCI) engines, assessing its viability as an alternative fuel source.	
[27]	Examination of the application of acetone-gasoline blends in spark-ignition engines, focusing on their potential to reduce exhaust emissions through advanced modeling and optimization techniques.	
[28]	Focus on multi-cycle modeling and control of a free piston engine equipped with an electrical generator, specifically under HCCI combustion conditions.	
[29]	Optimization of energy production from biogas in a closed landfill using artificial neural networks to enhance overall efficiency and output.	
[30]	Evaluation of the impact of exhaust gas recirculation (EGR) on the performance and emissions of a free-piston electrical generator fuelled by dimethyl ether (DME).	
[31]	Application of the Intelligent Grey Wolf Optimizer to improve performance metrics in compression ignition (CI) engines operating on emulsion diesel fuel blends.	
[32]	Exploration of the effects of hydrogen as a fuel additive on the combustion characteristics and emissions profiles in a free piston engine.	
[33]	Addressing optimal water addition in emulsion diesel fuel, employing machine learning techniques to minimize exhaust pollutants.	
[34]	Conducting a numerical investigation into the combustion characteristics of a single-cylinder linear engine fuelled by natural gas, emphasizing the influence of EGR.	
[35]	Examination of the effect of hydrogen sulfide content on the combustion characteristics of biogas fuel within HCCI engine systems.	
[36]	Assessment of the performance evaluation of a novel mechanism design for spark-ignition internal combustion engines.	
[37]	Evaluation of the performance and sensitivity of raw biogas combustion under HCCI conditions, aiming to optimize combustion efficiency.	
[38]	Exploration of emissions from HCCI engines using a newly proposed chemical reaction mechanism tailored for biogas fuel.	
[39]	Evaluation of the homogeneity of in-cylinder gas mixtures in natural gas HCCI free piston engines through three-dimensional computational fluid dynamics (3D-CFD) analysis.	

Notably, the current study on biogas utilization in HCCI engines stands out for its innovative approach and emphasis on exergy analysis to optimize engine performance. The novelty of this research lies in leveraging exergy data to identify the most effective injector location, a critical factor for enhancing combustion efficiency and reducing emissions. Specifically, three distinct injector locations within the HCCI engine were examined: at the port, 6 cm away from the original port position, and 10 cm away. By meticulously analyzing exergy output under varying methane fractions, injector positions, exhaust gas compositions, and engine load conditions, this study aims to pinpoint the injector location that maximizes engine efficiency while minimizing environmental impact. Furthermore, the research incorporates exergo-economic, exergo-enviro-economic, and sustainability analyses, enriching the understanding of the economic and environmental implications associated with different injector configurations.

The novelty aspects of the study are listed below.• Pioneering approach to leveraging exergy analysis for optimizing biogas utilization in HCCI engines, a novel concept in the field.

• Utilization of exergy data to determine the most effective injector location, a critical factor influencing combustion efficiency and emissions.

• Comprehensive examination of three distinct injector locations (port, 6 cm away, and 10 cm away) to unravel the optimal configuration for biogas utilization in HCCI engines.

• Meticulous analysis of exergy output under varying conditions, including methane fractions, biogas flow rates, and engine load conditions, to pinpoint the most efficient and environmentally friendly configuration.

• Incorporation of exergo-economic, exergo-enviro-economic, and sustainability analyses, providing a holistic understanding of the economic and environmental implications of different injector locations.

2 Experimental setup

The experimental setup employed in this study, as depicted in Fig. 1, embodies a seamless fusion of practical engineering principles and precise instrumentation. Initially, a Kirloskar 8 HP single-cylinder, four-stroke CI engine was selected, which underwent a transformation into a water-cooled HCCI engine tailored specifically for the research objectives. The primary aim focused on the utilization of simulated biogas, a mixture of methane (CH4) and carbon dioxide (CO2), stored separately in dedicated cylinders. To regulate the flow of biogas and fine-tune the ratio of CH4 to CO2 for optimal combustion parameters, flow control valves were paired with meticulously calibrated thermal mass flow meters. Before introduction into the engine, the biogas mixture underwent thorough blending with incoming air. Alongside the biogas mixture, DEE served as a pilot fuel, precisely delivered to the engine via injectors located in both the inlet port and manifold. This dual-injector setup ensured enhanced precision in fuel delivery. To monitor the performance of the engine meticulously throughout the experiments, an eddy current dynamometer and a digital weighing balance quantifying DEE consumption were integrated. Additionally, a 5-gas emission analyser and a smoke analyser were employed to scrutinize emissions profiles and combustion efficiency with a high degree of accuracy. For precise timing of DEE injection, crucial for synchronization of the combustion cycle of the engine, a sophisticated timing control circuit was incorporated. This ensured optimal fuel delivery alignment with the dynamic combustion process within the engine. The engine specifications are provided in Table 2.Fig. 1 Experimental setup used in this study.

Fig. 1

Table 2 Specifications of the engine.

Table 2Kirloskar 8 HP single-cylinder engine	
Parameters	Values/Specifications	
Engine Bore x Stroke	87.5 mm × 80 mm	
Operating cycle	4-stroke diesel	
Compression ratio	17	
Engine displacement	0.481 L	
Combustion principle	HCCI	
Peak pressure	7.5 MPa	
Maximum torque	25 Nm	
Maximum power	6 kW	
Fuel injection timing	4.5 ° bTDC	
DEE injection pressure	2.5 bar	

2.1 Controlling technique of the HCCI engine

The performance, emission, and combustion indices of the HCCI mode are meticulously investigated by manipulating the injection positions of the secondary fuel, diethyl ether (DEE). Specifically, the DEE is introduced via three ports: (i) port injection at the intake port and (ii) manifold1 injection, 6 cm upstream of the intake port, (iii) manifold2 injection, 10 cm upstream from the intake port.

2.1.1 Injection control and setup

The injection system is carefully designed to ensure homogeneity of the air-fuel mixture, critical for the HCCI mode operation. In-cylinder diesel injection is deactivated to avoid mixture heterogeneity. Instead, port fuel injection (PFI) injectors are utilized to introduce DEE stored in a leak-proof tank into either the port or the manifold at a pressure of 2.5 bar.

An Arduino-based electronic control unit governs the injection duration, ensuring precise control over the amount and timing of DEE injection. Injectors are mounted flush with the manifold wall, and the desired DEE injector is activated based on the selected method (port or manifold1 injection or manifold2 injection). The engine is then cranked using a DC starter motor via an electromagnetic clutch, achieving a cranking speed between 600 and 800 rpm. Once combustion initiates, the motor is disengaged using the clutch. Load is applied using the control system connected to the eddy current dynamometer.

2.1.2 Injection timing and duration

In the three injection methods—port injection, manifold injection 1, and manifold injection 2, the start of injection is set at 4.5° before top dead center (obTDC) during the suction stroke, coinciding with the beginning of the inlet valve opening. The duration of injection is dynamically adjusted using the Arduino controller to maintain a constant engine speed, accommodating variations in engine load and other operating conditions. This precise control is essential for achieving the desired combustion characteristics and maintaining engine stability.

2.2 Uncertainty and measurement precision of experimental parameters

The uncertainty in the experimental results was determined using Moffat's technique [40], which is widely recognized for its effectiveness in assessing uncertainties in experimental data. This technique involves a systematic approach to quantify the uncertainties associated with various measured parameters, ensuring the reliability and accuracy of the experimental findings.

2.2.1 Parameters and associated uncertainties

Several key performance and emission parameters were measured during the experiments, and the uncertainties for each were calculated as follows:1. Secondary Fuel Energy Ratio: The uncertainty in the secondary fuel energy ratio was found to be 1.33 %. This parameter indicates the proportion of energy contributed by the secondary fuel (DEE) relative to the total fuel energy released during combustion.

2. Brake Thermal Efficiency (BTE): The uncertainty in the brake thermal efficiency, which is a measure of the engine's efficiency in converting fuel energy into mechanical work, was calculated to be 2 %.

3. Equivalence Ratio: This ratio, which represents the ratio of the actual fuel-air mixture to the stoichiometric fuel-air mixture, had an uncertainty of 1.5 %.

4. Cylinder Pressure: The uncertainty in the cylinder pressure measurements was determined to be 2 %. Cylinder pressure is a critical parameter for analyzing the combustion process and engine performance.

5. Hydrocarbon (HC) Emissions: The uncertainty in HC emissions, which are indicative of unburned fuel in the exhaust, was found to be 3 %.

6. Carbon Monoxide (CO) Emissions: The uncertainty associated with CO emissions, a byproduct of incomplete combustion, was also calculated to be 3 %.

7. Nitrogen Oxides (NOx) Emissions: The uncertainty in NOx emissions, which are a significant contributor to air pollution and are formed at high combustion temperatures, was determined to be 1 %.

8. Smoke Emissions: The uncertainty in smoke emissions, measured using an opacity-based smoke meter, was found to be 1 %. Smoke emissions are a result of particulate matter in the exhaust gases.

2.2.2 Equipment and measurement instruments

As outlined in the previous subsections, the following equipment and instruments were utilized to achieve precise measurements and ensure accurate data collection:1. Eddy Current Dynamometer: An eddy current dynamometer with a least count of 0.1 Nm, connected to an electronic control unit, was used to set and measure the operating torque. The dynamometer provides accurate torque readings, essential for performance analysis.

2. AVL 5-Gas Emission Analyzer: Tail-pipe gaseous emissions, including CO, NOx, and HC, were detected using an AVL 5-gas emission analyzer. This analyzer offers high precision with the following least counts for transducers:• HC Emissions: 1 ppm

• CO Emissions: 0.01 %

• NOx Emissions: 10 ppm

3. Opacity-Based Smoke Meter: Smoke levels were measured using an opacity-based smoke meter, which has a least count of 0.1 %. This instrument helps in assessing the particulate matter content in the exhaust gases.

3 Methodology

During the course of this investigation, the engine was supplied with two distinct fuel sources: air and biogas. These were introduced into the combustion chamber through the inlet manifold. Additionally, a supplementary fuel, diethyl ether (DEE), was injected at one of three specific entry points, as depicted in Fig. 2 – namely the port, manifold1 (6 cm upstream from the intake valve), or manifold2 (10 cm upstream of manifold 1).Fig. 2 Layout of the experimental setup used in the study.

Fig. 2

Comprehensive evaluations of the engines performance metrics and emission characteristics for each of these DEE injection locations was performed. These assessments took into account varying parameters, including different biogas flow rates and methane concentrations, across a diverse range of operational conditions detailed in Table 3. Furthermore, the experimental setup maintained a consistent engine speed of 1800 revolutions per minute (rpm) throughout the testing phase. To ensure this, fixed rpm was upheld, the DEE flow rate was adjusted and varied as required.Table 3 Operating Parameters of the HCCI engine.

Table 3Intake Conditions	
Injector Position	Port injection, injection 6 cm away (Manifold1), injection 10 cm away (Manifold2).	
Methane Fraction	60 % Methane with 40 % Carbon Dioxide, 100 % Methane, 0 % Carbon Dioxide	
Load	5, 10, 15, 20 N m	
Intake Temperature	35 °C	
Coolant for Engine	Water at 35 °C	

3.1 Exergy, exergo-economic, exergo-enviro-economic and sustainability analysis

This section outlines the key equations utilized in the Exergy, Exergo-Economic, Exergo-Enviro-Economic, and Sustainability analyses conducted within this study.

3.1.1 Exergy analysis

Exergy, a term used in the analysis of internal combustion engines, refers to the maximum work achievable from the supplied fuel energy under given environmental conditions. In engine performance evaluations, exergy analysis proves valuable [41]. The exergy entering a control volume in such analyses primarily constitutes the chemical exergy of the fuel. For fuel blends, determining exergy necessitates closed formulae based on additive ratios. These ratios include hydrogen, carbon, sulphur, and oxygen content derived from fuel analysis. An exergy factor (φ) can be computed using these ratios as shown in Eq. (1).(1) φ=1.0401+0.1728hc+0.0432oc+0.2169αc(1−2.0628hc)

The exergy (Ex˙fuel) of blends can be found using the specific exergy (εfuel) and lower heating value as shown in Eqs. (2), (3).(2) εfuel=Huφ

(3) E˙xfuel=m˙fuelεfuel

Exergy, signifying the maximum potential for performing useful work, is an inherent presence within internal combustion engines, and its magnitude can never be negative [42]. In contrast to energy, the principle of exergy conservation does not apply. The cumulative exergy inflows entering a control volume is equal to the exergy outflow and the exergy destroyed, Eq. (4) shows this relation.(4) E˙xair+E˙xfuel=E˙xwork+E˙xeg+E˙xheat+E˙xdest

in the realm of exergy analysis, the environmental conditions serve as the reference state, typically set at a temperature of 298 K and a pressure of 1 atm, representing a state of minimal potential energy. As the air enters the engine from these conditions, the change in its exergy is considered negligible. The useful work extracted from the engine is equivalent to the exergetic power. To quantify the exergy released into the atmosphere through exhaust gases, the exergy of each combustion gas is determined. Both theoretical and actual combustion equations are employed to ascertain the mass flow rate of combustion products [43]. The results from emission tests are utilized to balance the actual combustion equation, enabling the calculation of the mass of each combustion product. The total mass is subsequently computed by summing the masses of the individual combustion products. The mass ratios of combustion products are obtained using Eq. (5) and Eq. (6). The mass flow rate of gases released into the atmosphere from the engine is the summation of the air and fuel flow rates, taking into account an approximate 2 % loss occurring in the exhaust gases released into the atmosphere [44].(5) mt=∑imi

(6) m˙eq=0.98(m˙air+m˙fuel)

In the comprehensive exergy analysis, the evaluation encompasses both the physical and chemical dimensions. The subscript “0″ signifies the equilibrium state, serving as the reference condition. Moreover, “s" represents the entropy, " R‾" denotes the universal gas constant, and “T0” signifies the ambient temperature in Eqs. (7)–(9). However, it is crucial to note that the thermodynamic properties are subject to fluctuations based on the systems operating conditions and the intrinsic characteristics of the working fluids or substances involved [45].(7) ε˙=ε˙phy+ε˙chm

(8) ε˙phy=[(h−h0)−T0(s−s0)]

(9) ε˙chm=R‾T0ln1ye

in this current study, it was assumed that all the output combustion gases behave as ideal gases, implying that all of the component gases exist in the atmosphere as a member of the ideal gas mixture. The chemical exergy of the resultant combustion gases was determined using the mole fraction of components in the reference environment. The exergy accompanying the heat transfer can be computed, utilizing the measured temperature (Tm) as shown in Eq. (10).

The exergy efficiency of the engine is determined by dividing the brake power output by the exergy input to the engine. In engines, exergy is consumed or destroyed due to losses and irreversibilities, these irreversibilities are directly proportional to the entropy generation within the engine. The values for Exergy destruction and entropy generation are determined using Eqs. (12), (13).(10) E˙xheat=∑(1−T0Tm)Q˙lost

(11) Ψ=η2=PbExin

(12) E˙xdest=E˙xfuel−(E˙xwork+E˙xeg+E˙xheat)

(13) s˙gen=Exdest˙T0

3.1.2 Exergo-economic analysis

In this study focusing on biogas and DEE blends in an HCCI engine, the economic analysis holds significant importance alongside performance and emission evaluations [46]. The economic performance of fuel blends was assessed using an exergo-economic analysis, incorporating a cost balance equation as shown in Eq. (14) and (15).(14) ∑cinE˙xin+Z˙=∑coutE˙out

(15) C˙air+C˙fuel=C˙w+C˙eg+C˙heat

In these equations, C˙ represents the costs entering and exiting while Z˙ is the investment cost ratio of the setup engine. Prior to the analysis, it was decided that the exergy of the air used in the engine would not be considered in this analysis as it was negligible, hence it was excluded from the cost balance. In the ensuing exergo-economic analysis performed below, the exergetic cost of the fuel blends is equated to the exergetic cost of exhaust and thermal losses as shown in Eqs. (16), (17)(16) cfuelC˙fuel=cwC˙w+cegC˙eg+cheatC˙heat

(17) cfuel=ceg=cheat

The cost of power carried out of the engine can be determined using the equations which are provided below (18–22). The cost ratio (C˙loss) of losses due to exhaust and heat transfer can also be calculated from Eqs. (18), (19). The investment cost ratio can also be calculated similarly using Eq. (20). Here, the initial investment cost is denoted as (Z), the capital factor of the investment is denoted by (Ef) while the engine maintenance factor and the annual usage hours of the engine are denoted by (Mf) and (tyear) respectively. On the other hand, interest rate is denoted by i and the engines lifespan is denoted by n [47].(18) cwE˙xw=cfuel(E˙xfuel−E˙xex−E˙xheat)+Z˙

(19) C˙loss=cfuel(E˙xdest+E˙xex+E˙xheat)

(20) Z˙=ZEfMftyear

(21) Ef=i(1+i)n(1+i)n−1

(22) f=Z˙Z˙+cfuel(Ex˙des+Ex˙exh+Ex˙loss)

3.1.3 Exergo-enviro-economic analysis

Carbon dioxide emissions from the HCCI engine operation contribute to global warming and climate change. Therefore, it is crucial to implement measures that can reduce these emissions. In the exergo-enviro-economic analysis of the daily HCCI engine operation with DEE pilot fuel and biogas, the carbon dioxide emissions were taken into consideration. The mass of carbon dioxide emissions released into the atmosphere can be determined through appropriate calculations. The economic value of the carbon dioxide emissions resulting from the DEE-biogas fuel blends was evaluated using equations (23), (24). For the economic assessment, a specific value for the cost of carbon dioxide emissions was utilized. In the economic evaluation, PCO2=0.0145 $/kgCO2 was taken [28].(23) CxCO2=NCO2E˙xintw

(24) ExCCO2=CxCO2PCO2

3.1.4 Sustainability analysis

Ensuring sustainability involves a delicate balance between meeting the needs of the present generation while preserving resources for future generations. This concept is rooted in three pillars: economic growth, environmental protection, and social development. One crucial aspect of achieving sustainability is the efficient consumption of energy resources. In this context, exergy analysis plays a vital role in sustainability assessment.

Exergy-based indicators provide valuable insights into the sustainability of processes. One such indicator is the Improvement Potential (IP), as shown in Eq. (25). The Improvement Potential represents the exergetic improvement potential of a process when its irreversibilities are minimized. It is determined by calculating the difference between the exergy of the fuel and the exergy of the product.

Another useful indicator for sustainability analysis is the Depletion Number (DN) shown in Eq. (26). This number offers researchers information about the efficiency of the fuel being utilized. The inverse of the Depletion Number is defined as the Sustainability Index (SI) as shown in Eq. (27). The Sustainability Index can be calculated by dividing the exergy of the product by the exergy of the fuel [48].(25) IP˙=(1−ψ)(Ex˙in−Ex˙out)

(26) DN=Ex˙destEx˙in=(1−ψ)

(27) SI=1DN

4 Results and discussion

This section outlines the trends observed in performance and emission characteristics as identified through the parametric studies.

4.1 Energy analysis

This section focuses on analysing the energy characteristics of the HCCI engine utilized in this study, employing biogas and DEE as the primary fuels.

4.1.1 1st law efficiency

The first law efficiency (η1) or brake thermal efficiency serves as a critical metric, indicating the ratio of useful work output to the input energy derived from the fuel consumed. In the context presented, the graphical representation (Fig. 3a) depicting the relationship between first law efficiency and load at various injector locations - with a consistent methane fraction of 100 % and a biogas mass flow rate of 12 L per minute (lpm) - offers valuable insights.Fig. 3a 1st law efficiency vs Load at different injector locations.

Fig. 3a

The data highlights a notable trend wherein the first law efficiency escalates in tandem with increasing load, aligning with fundamental principles. Furthermore, the graphical depiction distinctly illustrates that the port injection location consistently outperforms the Manifold 1 and Manifold 2 injector positions across all examined loads in terms of enhancing first law efficiency. This overarching superiority of the port injection setup implies more effective fuel distribution or combustion dynamics, potentially maximizing engine performance and efficiency. Moreover, it is worth noting that the graph also reveals that Manifold 1 consistently exhibits the lowest first law efficiency for all loads, indicating its relative inefficiency compared to the other two injector locations. Corroborating these findings, Fig. 3b, Fig. 3cb and c shows the graphs of first law efficiency versus load at various biogas flow rates and methane fractions for the superior port injection configuration.Fig. 3b 1st law efficiency vs load at various biogas flow rates for port injection.

Fig. 3b

Fig. 3c 1st law efficiency vs load at various methane fractions for port injection.

Fig. 3c

Notably, from Fig. 3b, we can observe that both biogas flow rates yield the same first law efficiency at a load of 5 N m, while at a load of 10 N m, 8 lpm biogas flow rate results in higher first law efficiency. At a load of 15 Nm, the peak first law efficiency of around 30 % is achieved with a 12 lpm biogas flow rate, but in the case of 8 lpm flow rate, engine knocking was recorded, hence the value was omitted. Similarly, from Fig. 3c, we can observe that at loads of 5 Nm and 10 Nm, both 60 % and 100 % methane fractions yield similar first law efficiencies. However, at a load of 15 Nm and 60 % methane fraction, engine knock was observed.

These findings underscore the significance of optimizing parameters such as injector location, biogas flow rate, and methane fraction to attain maximum first law efficiency while mitigating the occurrence of engine knock. This insight holds profound implications for enhancing engine performance, fuel efficiency, and potentially reducing emissions, thereby contributing to the development of sustainable and optimized energy systems.

4.1.2 Brake power output

The term brake power in engine mechanics signifies the amount of power output that an engine can deliver, representing the effective work produced by the engine. Within the scope of this research, the graphical representation in Fig. 4a delineates the relationship between brake power and varying loads across three injection locations, offering a distinct perspective compared to the one showcasing first law efficiency against load in Fig. 3a.Fig. 4 a. Graph of Brake power against Load at all injector locations.

Fig. 4

The data indicates that Manifold 2 injection yields a higher brake power output compared to both port and Manifold 1 injections, showcasing a different trend from the first law efficiency results. This disparity highlights the delicate interplay between thermal efficiency and power generation within engine performance. While port injection exhibited superior first law efficiency, Manifold 2 injection demonstrates a greater capability to harness the fuels energy for generating higher brake power output. Furthermore, it is evident that Manifold 1 injection yields the lowest brake power values, aligning with its inferior first law efficiency observed in Fig. 3a. This observation underscores the interconnectedness between injection location, thermal efficiency, and power output in engine operations. The strategic placement of the injector plays a crucial role in optimizing both efficiency and power generation, necessitating a careful balance between these two critical performance parameters.

It is essential to acknowledge that the graph in Fig. 4a represents data for a fixed biogas flow rate of 12 L per minute (lpm) and a methane fraction of 100 %. These specific conditions underscore the influence of injection location on brake power output under controlled gas composition parameters, providing valuable insights into optimizing engine performance and power generation. Notably, the variation in brake power trends across different injection locations highlights the potential for further investigation into the interplay between injection configuration, fuel composition, and combustion dynamics.

4.2 Exergy analysis

This section focuses on analysing the exergy characteristics of the HCCI engine utilized in this study, employing biogas and DEE as the primary fuels.

4.2.1 Exergy efficiency

Exergy efficiency (η2), or the second law efficiency of an engine, refers to the ratio between the output power and the exergy input. Exergy, a measure of the maximum useful work potential of a system, accounts for both the quantity and quality of energy, making it a more comprehensive metric than the first law efficiency. By considering the irreversibilities associated with the combustion process and heat transfer, exergy efficiency provides insights into the degree of thermodynamic perfection achieved by the engine.

Fig. 5a illustrates the relationship between exergy efficiency and load at all injector locations, with a fixed biogas flow rate of 12 lpm and a methane fraction of 100 %. The graph clearly demonstrates that port injection yields the highest exergy efficiency, while Manifold 1 injection results in the lowest exergy efficiency across all examined loads. This trend aligns with the observations from the first law efficiency analysis, further reinforcing the superior performance of the port injection configuration in terms of both energy utilization and thermodynamic effectiveness. Corroborating these findings, Fig. 5b, Fig. 5cb and c depict the exergy efficiency versus load graphs at various biogas flow rates and methane fractions, respectively, for the superior port injection setup. In Fig. 5b, it is evident that at a load of 5 Nm, both biogas flow rates of 8 lpm and 12 lpm yield the same exergy efficiency. However, at a load of 10 Nm, the 8 lpm biogas flow rate exhibits higher efficiency. Notably, at a load of 15 Nm and a biogas flow rate of 8 lpm, engine knocking was observed, indicating potential operational constraints. Conversely, with a 12 lpm flow rate, an exergy efficiency of approximately 29 % was achieved.Fig. 5a Exergy Efficiency vs load at different injector locations.

Fig. 5a

Fig. 5b Exergy Efficiency vs load at different biogas flow rates for port injection.

Fig. 5b

Fig. 5c Exergy Efficiency vs load at different methane fractions for port injection.

Fig. 5c

Similarly, Fig. 5c reveals that at loads of 5 Nm and 10 Nm, the exergy efficiency is nearly identical for methane fractions of 60 % and 100 %. However, at a load of 15 Nm and a methane fraction of 60 %, engine knock was observed, while a methane fraction of 100 % yielded an exergy efficiency of around 30 %, representing the optimal fuel composition for higher loads.

4.2.2 Exergy destroyed

Exergy destruction is a crucial parameter in an engine, as it quantifies the irreversibilities and thermodynamic imperfections associated with the combustion process and heat transfer. A high level of exergy destruction indicates significant losses in the quality and maximum useful work potential of the energy input, ultimately leading to reduced overall efficiency and performance of the engine.

In Fig. 6a, which illustrates exergy destruction versus load at various injector locations with a fixed biogas flow rate of 12 L per minute (lpm) and a methane fraction of 100 %, it is evident that the Manifold 2 configuration exhibits the highest levels of exergy destruction at loads of 5 Nm and 10 Nm. At a 15 Nm load, this configuration demonstrates the second-highest exergy destruction. This trend suggests that the Manifold 2 setup may experience greater thermodynamic inefficiencies, particularly under moderate loads. Conversely, the Port injection configuration consistently shows the least amount of exergy destruction across all three load cases. This finding points to the superior thermodynamic effectiveness of the Port injection method, which minimizes irreversibilities and enhances energy conversion efficiency.Fig. 6a Exergy destroyed vs load at various injector locations.

Fig. 6a

Fig. 6b, Fig. 6cb and c further elucidate the relationship between exergy destruction and engine parameters at different biogas flow rates and methane fractions, respectively, with a clear emphasis on the advantageous performance of the port injection setup. In Fig. 6b, comparing the 12 lpm biogas flow rate with the 8 lpm case reveals that the higher flow rate results in greater exergy destruction at nearly all loads, with the notable exception at 5 Nm. This suggests that the lower biogas flow rate of 8 lpm is more efficient overall, likely due to a better balance between fuel availability and combustion dynamics, leading to reduced losses.Fig. 6b Exergy destroyed vs load at various biogas flow rates for port injection.

Fig. 6b

Fig. 6c Exergy destroyed vs load at various methane fractions for port injection.

Fig. 6c

In Fig. 6c, the effects of methane fraction on exergy destruction are depicted at various loads. At loads of 0 Nm, 5 Nm, and 10 Nm, the configuration with a 60 % methane fraction shows higher exergy destruction compared to the 100 % methane fraction. This observation implies that a lower methane concentration may introduce additional inefficiencies at these loads. However, at higher loads of 15 Nm and 20 Nm, there is a significant drop in exergy destruction for the 60 % methane fraction, while the 100 % methane fraction exhibits higher exergy destruction. This shift indicates that the higher methane fraction may become less efficient at elevated loads due to increased combustion temperatures and pressures, which could exacerbate thermal losses.

Overall, these observations highlight that the port injection configuration, particularly when paired with a lower biogas flow rate of 8 lpm and a higher methane fraction of 100 %, represents the most favorable scenario for minimizing exergy destruction. This combination not only leads to reduced irreversibilities but also enhances thermodynamic efficiency and overall performance of the biogas-fuelled HCCI engine, especially under higher engine loads. By optimizing these parameters, it is possible to achieve significant improvements in engine.

4.3 Emissions analysis

This section focuses on analysing the emissions characteristics of the HCCI engine utilized in this study, employing biogas and DEE as the primary fuels.

4.3.1 Hydrocarbon emissions

Hydrocarbon emissions from an engine refer to the pollutants released into the environment in the form of unburned fuel compounds. High levels of hydrocarbon emissions are undesirable due to their negative impacts on air quality and human health. Elevated HC emissions indicate inefficient combustion, contributing to pollution and potentially forming harmful compounds in the atmosphere.

Conversely, low hydrocarbon emissions signify efficient combustion and better control of fuel consumption, leading to cleaner exhaust emissions. Engines with lower HC emissions are considered more environmentally friendly, meeting emission regulations and reducing their environmental impact.

In Fig. 7a, the relationship between HC emissions and varying loads across three injector locations is depicted. The graph illustrates that Manifold 1 injection initially results in the highest HC emissions at low loads compared to port and Manifold 2 injections. However, this trend reverses at higher loads, with Manifold 1 showcasing the lowest HC emissions. This observation suggests that Manifold 1 injection may be a suitable choice for engines operating at high loads. Moreover, the graph highlights that Manifold 2 not only minimizes HC emissions at low loads but also ranks second in terms of HC emission levels at higher loads, making it a viable option for engines operating at lower loads. Additionally, it is important to note that the data in Fig. 7a is based on a fixed biogas flow rate of 12 L per minute (lpm) and a methane fraction of 100 %.Fig. 7a Variation of HC emissions against Load at all injector locations.

Fig. 7a

Fig. 7b, Fig. 7cb and c depict the relationship between hydrocarbon (HC) emissions and engine load across various biogas flow rates and methane fractions within the port injection setup. These visualizations yield several noteworthy observations:Fig. 7b Variation of HC emissions against Load at all biogas flow rates for port injection.

Fig. 7b

Fig. 7c Variation of HC emissions against Load at all methane fractions for port injection.

Fig. 7c

Within the 60 % methane fraction, HC emissions are nearly absent, indicating efficient combustion. Conversely, the 100 % methane fraction exhibits significantly higher HC emissions at lower loads, gradually declining as load increases. This finding shows that at low loads, the fuel is not burnt fully, hence resulting in a lot of unburned hydrocarbons in the exhaust. Despite this trend for the 100 % methane fraction case, severe knocking occurs at higher loads in the case of 60 % methane fraction, highlighting a compromise between HC emissions and engine performance. When considering biogas flow rates, the 8 lpm flow rate demonstrates markedly lower HC emissions compared to the 12 lpm rate across various loads. However, at higher loads of 15 Nm and 20 Nm, engine knocking becomes evident, emphasizing the delicate balance required between biogas flow rates, combustion efficiency, and engine stability. These findings underscore the intricate relationship between methane fraction, biogas flow rates, HC emissions, and engine performance. Achieving optimal combustion efficiency while minimizing HC emissions and ensuring engine stability remains a multifaceted challenge in the realm of biogas-fuelled engine design and operation.

4.3.2 Carbon monoxide emissions

Carbon monoxide (CO) emissions from an engine arise from the incomplete combustion of carbon-containing fuels. CO is a colorless, odorless, and tasteless gas, making it particularly hazardous as it is challenging to detect without specialized monitoring equipment. The inhalation of CO can lead to serious health effects by impairing the blood's ability to transport oxygen. Symptoms of CO poisoning include dizziness, headaches, nausea, and in severe cases, it can result in death. Due to its insidious nature, CO is often labeled a “silent killer.” High levels of CO emissions from an engine are indicative of incomplete combustion, which can result from various factors such as poor engine tuning, an improper air-fuel mixture, or inefficient combustion processes. Conversely, lower CO emissions signify more efficient combustion, suggesting that the engine is utilizing fuel more completely and generating fewer harmful emissions.

In Fig. 8a, the variation of carbon monoxide emissions against engine loads is illustrated for all three injector locations, under a fixed biogas flow rate of 12 L per minute and a methane fraction of 100 %. The graph reveals a pronounced spike in CO emissions at lower load values, indicating that operating the engine at higher loads is beneficial for minimizing CO emissions. Specifically, the Manifold 1 configuration consistently exhibits the lowest CO emissions across all load values, marking it as an effective choice for reducing CO emissions, particularly at elevated loads. This observation aligns with findings presented in Fig. 7a, where Manifold 1 also demonstrated the lowest hydrocarbon (HC) emissions at high loads, showcasing its overall effectiveness in mitigating harmful exhaust emissions. The data further reveals that the port injection configuration is associated with the highest HC emissions across all loads, suggesting it is less favorable in terms of emissions control. Manifold 2 occupies a middle ground in terms of HC emissions when compared to the other configurations, maintaining a trend similar to that observed in Fig. 7a.Fig. 8a Carbon Monoxide emissions against load for different injector locations.

Fig. 8a

Turning to Fig. 8b, Fig. 8cb and c, which present CO emissions in relation to load for the port injection configuration across varying biogas flow rates and methane fractions, we can glean further insights. In Fig. 8b, at loads of 5 Nm and 10 Nm, the data indicate that the 8 lpm biogas flow rate results in lower CO emissions compared to higher flow rates, demonstrating a more efficient combustion process at these specific loads. However, an interesting trend is noted at 0 Nm load, where the 8 lpm flow rate yields significantly higher CO emissions. This suggests that the engine operates less efficiently under no load conditions, likely due to suboptimal combustion dynamics at lower fuel flow rates. In contrast, the 12 lpm biogas flow rate showcases lower CO emissions at no load but displays increased emissions when the engine is under loads of 5 Nm and 10 Nm. This highlights a nuanced interaction between fuel flow rate and engine load, suggesting that while higher flow rates may facilitate better combustion under certain conditions, they can also lead to elevated CO emissions at intermediate loads. Moreover, at a load of 15 Nm, knocking is observed with the 8 lpm biogas flow rate. This phenomenon may indicate that the engine is operating at the threshold of optimal combustion conditions, where the lower flow rate struggles to provide adequate fuel to sustain efficient combustion, potentially leading to undesirable combustion characteristics. The analysis also extends to the influence of methane fraction on CO emissions. Notably, a 60 % methane fraction consistently results in lower CO emissions compared to a 100 % methane fraction across various loads. This suggests that blending in a lesser concentration of methane can lead to a more stable combustion environment, albeit with some trade-offs, as knocking is noted at higher loads for the 60 % methane fraction. This complexity reinforces the necessity for optimizing both biogas flow rates and methane fractions in order to enhance engine efficiency while minimizing harmful emissions.Fig. 8b CO emissions against load for different biogas flow rates for port injection.

Fig. 8b

Fig. 8c CO emissions against load for different methane fractions for port injection.

Fig. 8c

4.3.3 Carbon dioxide emissions

Carbon dioxide (CO2) is a well-known greenhouse gas present in the atmosphere that contributes significantly to global warming and climate change. Excessive CO2 emissions are harmful to both humans and the environment as they lead to the trapping of heat in the atmosphere, resulting in the warming of the Earth's surface, disruption of ecosystems, and adverse impacts on public health. High CO2 emissions from an engine can be a sign of inefficient combustion or fuel consumption processes, indicating that the engine is not operating optimally and is releasing more CO2 than necessary. This inefficiency not only contributes to environmental pollution but also signifies the wasteful use of fuel resources.

In Fig. 9a, the graph illustrates the relationship between CO2 emissions and load for all three injector locations at a fixed biogas flow rate of 12 L per minute and a methane fraction of 100 %. The data shows that Manifold 1 injection results in reduced CO2 emissions at low loads but exhibits a significant increase in CO2 emissions as the load on the engine increases. The graph highlights a clear trend where CO2 emissions spike at high loads and diminish at low loads. This pattern demonstrates a trade-off in emissions control – while reducing CO2 emissions by operating the engine at low loads, there is a noticeable increase in CO and HC emissions, and vice versa. Thus, achieving a balance in emission control becomes crucial to minimize the overall environmental impact of engine operations. Although Manifold 1 shows the lowest emissions for CO and HC as per Fig. 7a, Fig. 8aa, it demonstrates exceptionally high CO2 emissions, emphasizing the need for a careful and holistic approach to emissions management. This scenario underscores the complexity of optimizing engine performance to mitigate harmful emissions effectively while considering multiple pollutant outputs simultaneously.Fig. 9a Carbon dioxide emissions against load for different injector locations.

Fig. 9a

Examining Fig. 9b, Fig. 9cb and c, which illustrate the relationship between carbon dioxide (CO2) emissions and engine load across various biogas flow rates and methane fractions within the port injection setup, distinct patterns emerge. Initially, focusing on the biogas flow rates, it is evident that the 12 lpm flow rate results in higher CO2 emissions at 0 load, but at 5 and 10 Nm loads, emissions decrease. Conversely, the 8 lpm flow rate exhibits knocking at a load of 15 Nm. Transitioning to the methane fraction, a consistent trend is observed wherein the 60 % methane fraction consistently yields lower CO2 emissions compared to the 100 % methane fraction across all loads. However, similar to the biogas flow rate scenario, knocking occurs at a load of 15 Nm with the 60 % methane fraction. These insights underscore the intricate relationship between biogas flow rates, methane fractions, CO2 emissions, and engine performance. Achieving optimal combustion efficiency while minimizing CO2 emissions and ensuring engine stability remains a complex challenge in the optimization of biogas-fuelled engine operation.Fig. 9b Carbon dioxide emissions against load for different biogas flow rate for port injection.

Fig. 9b

Fig. 9c Carbon dioxide emissions against load for different methane fractions for port injection.

Fig. 9c

4.3.4 Smoke emissions

Smoke is a visible suspension of carbon and other particles in the air, typically resulting from the incomplete combustion of organic matter. It is a by-product of combustion processes and is considered a significant pollutant, especially in engines where it can have detrimental effects on both human health and the environment. In the context of engines, smoke can be directly defined as the visible particulate matter emitted from the exhaust as a result of incomplete combustion of fuel. This particulate matter consists of carbon, ash, and other contaminants that can pose serious health risks when inhaled. The harmful effects of smoke emissions from engines include respiratory issues, lung diseases, cardiovascular problems, and environmental pollution.

Fig. 10a depicts the relationship between smoke emissions and engine load for various injector locations under a constant biogas flow rate of 12 L per minute and a methane fraction of 100 %. The graph reveals that Manifold 2 consistently exhibits the lowest levels of smoke emissions across all loads, indicating a more efficient combustion process at that injector location. On the other hand, Manifold 1 shows slightly higher smoke emissions compared to Manifold 2 at all loads, suggesting some room for improvement in combustion efficiency. In contrast, port injection demonstrates the highest levels of smoke emissions at all loads, with a significant peak at higher loads, highlighting its inefficiency in minimizing visible particulate emissions. The data underscores that port injection may not be as effective in reducing smoke emissions compared to Manifold 1 and Manifold 2, which are relatively better options in terms of emission control. By selecting the injector location that minimizes smoke emissions, engine operators can help mitigate the environmental and health impacts associated with particulate pollution from combustion processes.Fig. 10a Smoke emissions vs load at different injector locations.

Fig. 10a

Examining Fig. 10b, Fig. 10cb and c, which depict the relationship between smoke emissions and engine load across various biogas flow rates and methane fractions within the port injection setup, discernible trends emerge. Initially, focusing on biogas flow rates, it is evident that at a load of 0 Nm, the 12 lpm flow rate yields higher smoke emissions compared to the 8 lpm flow rate. However, this trend shifts at a load of 5 Nm, where the 12 lpm flow rate results in lower smoke emissions than the 8 lpm flow rate. Yet, at a load of 10 Nm, a significant increase in smoke emissions occurs, reaching around 20 % of the entire exhaust gas composition. Notably, at a load of 15 Nm and with an 8 lpm biogas flow rate, engine knocking was observed, leading to the omission of data. Transitioning to the methane fraction, similar complexities arise. At a load of 0 Nm and with a 60 % methane fraction, misfiring is observed, highlighting operational challenges. Additionally, at higher loads of 15 Nm and 20 Nm, knocking is evident. Nevertheless, the graphs distinctly illustrate that the 60 % methane fraction consistently yields considerably lower smoke emissions compared to the 100 % methane fraction.Fig. 10b Smoke emissions vs load at various biogas flow rates for port injection.

Fig. 10b

Fig. 10c Smoke emissions vs load at various biogas flow rates for port injection.

Fig. 10c

4.4 Exergo-economic analysis

In this study focusing on biogas and DEE blends in an HCCI engine, an exergoeconomic analysis was conducted to assess the economic performance of the fuel blends. The analysis involved Eq. 14–22, where various cost components and investment factors were considered.

For the HCCI engine employed in the current study, the following parameters were adopted after thorough calculation of engine costs and anticipated annual operating hours, tailored to the specific application scenario:• Interest rate: 10 %

• Maintenance factor: 1.06

• Engine cost: 1810 USD

• Working hours per year: 730

• Engine lifetime: 15 years

Using these parameters, the Capital Recovery Factor (CRF), investment cost ratio, and other relevant values were calculated and tabulated in Table 4.Table 4 Table showcasing the values of cw and f as calculated in this study.

Table 4Injector location	Load (N.m)	Biogas flow rate (lpm)	Methane fraction (%)	cw (USD/hr)	f (%)	
Port	5	8	60	0.33	3.78	
Manifold 1	0.32	2.99	
Manifold 2	0.31	2.60	
Port	10	0.16	3.61	
Manifold 1	–	7.65	
Manifold 2	–	7.65	
Port	5	12	0.33	2.31	
Manifold 1	0.31	2.24	
Manifold 2	0.31	2.31	
Port	10	0.16	2.31	
Manifold 1	0.16	2.31	
Manifold 2	0.16	2.38	
Port	5	8	100	0.33	2.35	
Manifold 1	0.32	2.42	
Manifold 2	0.31	2.50	
Port	10	0.16	2.59	
Manifold 1	0.17	2.35	
Manifold 2	0.16	2.50	
Port	5	12	0.33	2.30	
Manifold 1	0.34	1.91	
Manifold 2	0.30	1.82	
Port	10	0.16	2.26	
Manifold 1	0.16	1.91	
Manifold 2	0.16	1.86	

The exergo-economic factor (f) provides insights into the cost-effectiveness and economic performance of a system by combining exergy analysis and economic principles. It indicates the contribution of non-exergy-related costs to the overall product cost. From Tables 3 and it can be observed that the exergoeconomic factor ranges from a maximum of 7.65 % to a minimum of 1.82 %. This wide range highlights:• Significant variations in cost distribution between exergy-related and non-exergy-related components across different operating conditions and injector locations.

• Certain conditions may lead to higher thermodynamic inefficiencies and irreversibilities, contributing to lower exergoeconomic factors.

• High exergoeconomic factors suggest a dominant role of non-exergy costs, potentially impacting economic viability.

• Opportunities for optimization by identifying conditions with low exergoeconomic factors to improve thermodynamic efficiency and reduce costs.

It is worth noting that the missing cw values in the table are attributed to engine knocking incidents during those instances, which prevented the measurement of Revolutions per Minute (RPM) of the engine.

4.5 Exergo-enviro-economic analysis

In the exergo-enviro-economic analysis of daily HCCI engine operation with DEE pilot fuel and biogas, the impact of carbon dioxide emissions on global warming and climate change was considered. Eqs. (23), (24) were utilized to calculate the mass of carbon dioxide emissions released and evaluate their economic value.

For this analysis, the following parameters was considered:• Cost of carbon dioxide emissions PCO2=0.0145 $/kgCO2.

Using this parameter, the economic value of carbon dioxide emissions resulting from the DEE-biogas fuel blends was determined. Table 5 presents the results of the exergo-enviro-economic analysis, including the mass of carbon dioxide emissions (NCO2), the economic value of carbon dioxide emissions (CxCO2), and the total cost of carbon dioxide emissions (ExCCO2). All relevant parameters were calculated according to equations (23), (24), (25).Table 5 Table showcasing the results of the Exergo-Enviro-Economic analysis.

Table 5Injector location	Load (N.m)	Biogas flow rate (lpm)	Methane fraction (%)	ExCCO2	
Port	5	8	60	0.26	
Manifold 1	0.30	
Manifold 2	0.33	
Port	10	0.21	
Manifold 1	–	
Manifold 2	–	
Port	5	12	0.20	
Manifold 1	0.43	
Manifold 2	0.05	
Port	10	0.18	
Manifold 1	0.29	
Manifold 2	0.19	
Port	5	8	100	0.34	
Manifold 1	0.25	
Manifold 2	0.22	
Port	10	0.24	
Manifold 1	0.23	
Manifold 2	0.19	
Port	5	12	0.29	
Manifold 1	0.32	
Manifold 2	0.32	
Port	10	0.23	
Manifold 1	0.38	
Manifold 2	0.22	

The ExCCO2 values in Table 3 represent the total cost associated with carbon dioxide emissions from the system. These values provide insights into the environmental impact and associated costs across different operating scenarios or conditions. A higher ExCCO2 value indicates a greater environmental impact and higher costs related to carbon dioxide emissions. Conversely, a lower ExCCO2 value suggests a lower environmental impact and cost. The wide range of ExCCO2 values, spanning from a maximum of 0.43 to a minimum of 0.05, with an approximate range of 0.38, highlights the significant variability in the environmental impact and associated costs across different scenarios or operating conditions. This variability underscores the importance of optimizing the systems operation to minimize carbon dioxide emissions and their associated costs, thereby reducing the overall environmental impact and improving sustainability. It is worth noting that some values are missing due to engine knocking incidents, which prevented the measurement of certain parameters for safety reasons.

4.6 Sustainability analysis

In the context of sustainability, exergy analysis provides crucial insights into the efficient utilization of energy resources. Two key exergy-based indicators, the Improvement Potential (IP) and the Depletion Number (DN), along with the derived Sustainability Index (SI), were employed to assess the sustainability of processes, particularly the operation of the HCCI engine with DEE pilot fuel and biogas.

Eq. (25) was utilized to calculate the Improvement Potential, representing the exergetic improvement potential of the process when irreversibilities are minimized. It quantifies the difference between the exergy of the fuel and the exergy of the product. Eq. (26) was used to determine the DN, offering insights into the efficiency of the test fuel. The SI is then derived as the inverse of the DN, as shown in Eq. (27), providing a measure of sustainability by comparing the exergy of the product to the exergy of the fuel.

Table 6 shows the Improvement Potential values for different injector locations and loads in the HCCI engine operation with biogas, where methane fraction data is available. The Improvement Potential values represent the exergetic improvement potential of the process when irreversibilities are minimized. Analysis of the data reveals variations in Improvement Potential across different injector locations and loads. For instance, at a load of 5 Nm with port injection, the Improvement Potential ranges from approximately 2.62 kW–7.27 kW. Similarly, at a load of 10 Nm with manifold 2 injection, the Improvement Potential varies from around 2.80 kW–7.24 kW. The SI is greater than one because it is defined as the inverse of the DN, which measures the efficiency of a process. Since DN is always less than one (as it represents the fraction of exergy destroyed in relation to the total input exergy), taking its inverse results in a value greater than one. This indicates that the process produces more useful exergy compared to the exergy being destroyed, signifying higher sustainability and efficiency. These results highlight the potential for improving the efficiency of the HCCI engine operation by optimizing injector location and load conditions, ultimately contributing to enhanced sustainability through more efficient consumption of energy resources.Table 6 Table showcasing Improvement potential for the HCCI engine in this study.

Table 6Injector location	Load (N.m)	Biogas flow rate (lpm)	Methane fraction (%)	Improvement potential (kW)	
Port	5	8	60	2.62	
Manifold 1	4.43	
Manifold 2	5.51	
Port	10	2.29	
Manifold 1	2.80	
Manifold 2	2.80	
Port	5	12	7.27	
Manifold 1	6.58	
Manifold 2	7.24	
Port	10	5.75	
Manifold 1	5.27	
Manifold 2	5.55	
Port	5	8	100	6.26	
Manifold 1	5.58	
Manifold 2	5.64	
Port	10	4.44	
Manifold 1	5.10	
Manifold 2	4.68	
Port	5	12	6.00	
Manifold 1	8.02	
Manifold 2	8.63	
Port	10	5.10	
Manifold 1	7.20	
Manifold 2	7.24	

5 Conclusion

The comprehensive study conducted an energy, emission, and exergy analysis of a biogas and DEE-fuelled HCCI engine has yielded insightful findings, shedding light on the intricate interplay between injector location, fuel composition, combustion efficiency, and emissions. Through a meticulous examination of various operating parameters, including methane fractions, biogas flow rates, engine loads, and exhaust gas compositions, the study has uncovered the optimal configurations for maximizing performance and minimizing environmental impact.

One of the key revelations from this investigation is the superiority of the port injection configuration in terms of enhancing both first law and exergy efficiencies across a wide range of operating conditions. The port injection setup consistently outperformed the Manifold 1 and Manifold 2 injector locations, indicating more effective fuel distribution and combustion dynamics, potentially leading to improved engine performance and efficiency. However, it is crucial to acknowledge the inherent trade-offs that emerge when optimizing for multiple performance and emissions parameters simultaneously. While the port injection configuration excelled in maximizing efficiencies, the Manifold 1 location demonstrated remarkable proficiency in minimizing harmful emissions, such as hydrocarbons (HC), carbon monoxide (CO), and smoke. Manifold 1 HC emission is 10.53 % higher than Port at 5 Nm load, and Manifold 2 HC emission is 10.53 % lower than Port. Although, At 15 Nm load, Manifold 1 HC emission is 50 % lower than Port, and Manifold 2 HC emission is 12.5 % lower than Port. Similarly, Manifold 1 CO emission is 11.11 % lower than Port at 5 Nm load, and Manifold 2 CO emission is 5.56 % lower than Port. At 15 Nm load, Manifold 1 CO emission is 71.43 % lower than Port, and Manifold 2 CO emission is 28.57 % lower than Port. This contrast underscores the delicate balance required between enhancing thermodynamic effectiveness and mitigating environmental impact.

Furthermore, the study unveiled the intricate relationship between biogas flow rates, methane fractions, and various emissions. Notably, lower biogas flow rates and higher methane fractions exhibited lower HC emissions but were susceptible to engine knocking at elevated loads. Conversely, higher biogas flow rates and lower methane fractions yielded reduced CO2 and smoke emissions, albeit at the expense of increased HC and CO emissions in certain load scenarios. To summarize the key findings and trade-offs, Table 7 provides a comprehensive overview.Table 7 The key findings of the study.

Table 7Injector Location	High Load Performance	Brake Power Output	Emissions Reduction	
Port Injection	Highest 1st law and exergy efficiencies, but higher HC, CO, and smoke emissions	Moderate	Least effective for emissions control	
Manifold 1	Moderate efficiencies, but lowest HC, CO, emissions at high loads and moderate smoke emissions at high loads.	Lowest	Most effective for emissions reduction, except for CO2	
Manifold 2	Moderate efficiencies, higher exergy destruction, but lowest smoke emissions across all loads	Highest	Effective for smoke reduction, but higher HC and CO emissions	

In addition to the exergy, energy and emissions analysis conducted in this study, this study also conducted exergo-economic, exergo-enviro-economic, and sustainability analyses to provide a holistic assessment of the systems performance, economic viability, and environmental impact. These analyses incorporated factors such as capital costs, operating expenses, and the cost of emissions, offering a comprehensive understanding of the systems overall sustainability and optimization potential.

The findings of this study provide significant insights into optimizing HCCI engines for biogas utilization. They highlight the critical influence of injector location, fuel composition, and operating parameters on enhancing efficiency and reducing environmental impact. Understanding these factors is essential for improving the performance of HCCI engines, particularly in the context of using renewable fuels like biogas. These insights can guide future advancements in renewable energy applications within the automotive sector, fostering the development of cleaner technologies and alternative fuel systems. The HCCI engine model itself represents a promising approach for integrating various fuels and optimizing combustion processes, making it relevant for addressing current environmental challenges. As the automotive industry increasingly seeks to reduce greenhouse gas emissions and reliance on fossil fuels, the optimization of HCCI engines emerges as a viable pathway toward achieving these goals. By effectively integrating biogas and other renewable fuels into engine design, we can contribute to a more sustainable energy landscape, supporting broader efforts in climate change mitigation and environmental stewardship.

CRediT authorship contribution statement

Aditya Sai Samavedam: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Prasshanth C.V.: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Manavalla Sreekanth: Writing – review & editing, Visualization, Validation, Supervision, Software, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. T.M. Yunus Khan: Writing – review & editing, Visualization, Validation, Supervision, Software, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Naif Almakayeel: Writing – review & editing, Visualization, Validation, Supervision, Software, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Feroskhan M: Writing – review & editing, Visualization, Validation, Supervision, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

The authors extend their appreciation to University Higher Education Fund for funding this research work under Research Support Program for Central labs at King Khalid University through the project number CL/CO/D/6.
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