Effects of Ethanol–Gasoline Blends on the Performance and Emissions of a Vehicle Spark-Ignition Engine

Abstract

This article presents experimental results related to the influence of bioethanol content in fuel blends on the performance and emissions of a spark-ignition engine. Tests were conducted for six ethanol–gasoline mixtures (ranging from 0% to 100% ethanol) under three engine control strategies: factory settings, a fuel dose increased by 10%, and a fuel dose increased by 20%—both with an ignition timing adjustment of +3°. Measurements included engine power and torque, as well as emissions of CO, CO₂, HC, O₂, and particulate matter, all performed under a full engine load. The results revealed the strong dependence of engine behavior on ethanol content. Increasing the ethanol concentration significantly reduced CO and HC emissions, as well as markedly lowering particulate emissions—particularly at 30% ethanol. Conversely, pure ethanol led to substantial reductions in power (up to 28%) and torque (up to 32%) compared to conventional gasoline. Adjustments to the fuel dose and ignition timing partially mitigated these losses. Emissions of CO₂ and oxygen content in exhaust gases varied depending on the blend, highlighting the complex nature of the combustion process. The findings contribute to the understanding of renewable fuel behavior in SI engines and underscore the influence of both fuel composition and control strategies on performance and emission characteristics.

1. Introduction

Modern transportation faces a serious challenge in terms of selecting the right power source for vehicles equipped with combustion engines. In the face of stricter environmental regulations and global efforts to reduce greenhouse gas emissions, alternative fuels, including biofuels, are playing an increasingly important role. Their development represents a response to the need to reduce the negative impact of transportation on the environment while maintaining the accessibility and functionality of conventional drive systems based on internal combustion engines.

Biofuels are liquid or gaseous energy carriers obtained through the processing of biomass or waste substances. In Poland, interest in these fuels dates back to 1929, but it is only in recent decades, in the context of efforts to achieve sustainable development, that the topic has gained significant practical importance.

The most commonly used liquid biofuels include bioethanol, which is primarily produced by the fermentation of sugars derived from crops such as corn, sugarcane, or lignocellulosic biomass, followed by distillation and dehydration. The application of ethanol as a fuel component is part of broader EU decarbonization strategies in transport, as defined in documents such as COMMISSION IMPLEMENTING REGULATION (EU) 2023/1777; biodiesel, obtained from vegetable oils or animal fats; and biomethanol, produced from lignocellulosic biomass. Among gas biofuels, biogas stands out; it is obtained from biodegradable fractions of organic waste (after purification, it can be used as natural gas), as well as biohydrogen, which is produced from biomass through fermentation or thermochemical processes [1].

Among these fuels, bioethanol has taken on particular importance as an additive to motor gasoline. Its use modifies the course of the combustion process and affects pollutant emissions. Standard ethanol–gasoline blends are defined as follows: E0—pure gasoline, E10—10% ethanol, E30—30% ethanol, E50—50% ethanol, and E100—pure ethanol. In the European Union, commercially available fuels typically include E5 and E10, while higher-ethanol blends such as E30, E50, and E100 are used primarily for research and adaptation purposes. Studies indicate that an increase in the share of bioethanol in the fuel mixture can lead to a reduction in carbon monoxide emissions by as much as 20–30%, as well as a reduction in hydrocarbon emissions by approximately 10% [2]. However, it should be emphasized that the increasing ethanol content may simultaneously adversely affect the engine’s performance parameters, including a decrease in power. These effects depend not only on the composition of the mixture, but also on the engine control parameters, such as the fuel dosage and ignition advance angle.

In the context of identifying optimal fuel mixtures, experimental studies comparing bioethanol formulations of varying complexity are also important. An example of this is the experiment conducted by Qadri U., who compared a traditional gasoline mixture with 15% ethanol with a microemulsion containing 90% gasoline, 8% ethanol, and 2% hydrogen peroxide. Tests performed on a three-cylinder spark ignition engine showed that, in both cases, emissions of pollutants such as HC, CO, and NO were significantly reduced in comparison with the combustion of pure gasoline. At the same time, however, a decrease in engine power was noted; this confirms the need to find a compromise between environmental aspects and the performance of the power unit [3].

An analysis of the literature shows that the addition of ethanol to gasoline can contribute to an increase in torque and engine power, simultaneously reducing emissions of carbon monoxide (CO), nitrogen oxides (NO_x), and hydrocarbons (HC) [4]. Researchers also emphasize that fuel mixtures containing ethanol allow for an increase in the compression ratio without the risk of knocking combustion, which translates into an improvement in overall engine efficiency. Other literature reviews point to numerous benefits resulting from the use of ethanol as a biofuel, including improved energy efficiency and the reduced emissions of pollutions, but they also highlight operational difficulties such as cold start problems and possible technical complications [5].

The issue of nitrogen oxide (NO_x) emissions in the context of the use of ethanol–gasoline mixtures remains ambiguous. Some studies indicate that there are no clear conclusions regarding the impact of ethanol content on NOx emissions, which highlights the need to conduct more detailed research under various load and operating conditions [6]. Other studies prove that an increase in the proportion of ethanol in fuel can improve engine power and thermal efficiency, while reducing volumetric efficiency and the emissions of harmful gases [7].

The literature also contains analyses concerning more complex mixtures, such as combinations of ethanol, methanol and gasoline. Their synergistic effect is identified, which enables the simultaneous reduction of CO emissions and unburned hydrocarbons (UHC) while maintaining favorable power and torque parameters [8]. Some of this research extends the scope of the analysis to two-stroke engines, which is an important addition to the prevailing literature focusing on four-stroke engines [9]. Further work confirms that an increase in the ethanol content of the mixture leads to an increase in the octane rating of the fuel, which has a positive effect on power and reduces CO and HC emissions. At the same time, there is an observed increase in carbon dioxide (CO₂) emissions resulting from the more complete combustion process [10]. Other studies indicate that hydrous ethanol may offer higher power at higher speeds compared to gasoline–ethanol mixtures, but this is accompanied by an increase in NOx emissions, highlighting the need for a compromise between performance and exhaust gas cleanliness [11]. These results are consistent with analyses showing an improvement in efficiency and a reduction in emissions at low ethanol mixtures to around 10% [12], while the addition of 20% ethanol to gasoline constitutes an optimal solution in terms of fuel consumption, efficiency, and emission levels, confirming the validity of further testing mixtures with medium bioethanol concentrations [13]. Modern predictive methods, including machine learning algorithms, are increasingly being used in research to model the behavior of engines powered by ethanol–gasoline mixture fuels. These techniques enable more effective and faster adjustment of the engine power unit parameters to changing operating conditions [14,15].

Among the less explored areas, there is the impact of bioethanol on the noise level generated by the engine. There are studies indicating that an increase in the share of ethanol and modification of the fuel dose can significantly affect noise emissions; however, this issue has not yet been comprehensively linked to the analysis of exhaust gas emissions and performance, which constitutes a research gap [16].

Despite the wide range of available data on the impact of the fuel mixture composition on emissions and fuel consumption [17,18], there is a noticeable lack of detailed analyses covering the simultaneous impact of the modification of the ignition advance angle and changes in fuel dosages at different ethanol concentrations. This particularly applies to engines with small capacities and simplified injection systems. Analyses of the literature also draw attention to the need for studies on the stability of fuel mixtures and their impact on combustion characteristics, especially with regard to specific engine configurations for which experimental data are lacking [19,20]. Experimental studies are also emerging regarding the possibility of optimizing the combustion process by adding hydrogen to ethanol–benzine fuel mixtures. Although the preliminary results are promising, these studies are still few in number and do not take into account the full range of engine operating parameter adjustments [21]. Within the framework of assessing the emissions and performance of turbocharged engines powered by ethanol–gasoline mixtures, computer simulations have been conducted, suggesting potential directions for extending numerical analyses to higher-performance engines [22]. Recent research by A. Rimkus [23] has shown that increasing the ethanol content in gasoline up to E70 can improve the brake thermal efficiency of the engine by approximately 1.7% and reduce CO, HC, and NOx emissions under fixed speed and load conditions. In this study, we expand on that topic by analyzing a broader range of ethanol–gasoline blends in a passenger vehicle engine, while also accounting for the effects of ignition timing adjustments and partial-load operations. This approach allows for a more comprehensive evaluation of bioethanol’s potential under real-world driving conditions. In parallel with the development of renewable fuels, other studies highlight the importance of optimizing combustion parameters and the tribological properties of engine components in reducing pollutant emissions. As demonstrated in another study [24], the appropriate selection of materials and operating parameters in diesel engines can significantly reduce particulate matter and harmful gases, which remains relevant for the advancement of spark-ignition engine technologies.

An analysis of the available sources confirms that the use of bioethanol as an additive to gasoline confers numerous benefits, particularly in terms of reducing carbon monoxide (CO) and hydrocarbon (HC) emissions, as well as improving the operating parameters of spark ignition engines. Nevertheless, most studies focus on a limited range of ethanol concentrations and standard fuel system settings, which does not provide a complete picture of its impact on engine performance under various operating conditions. The research gap is particularly evident in relation to analyses involving the simultaneous variation of the ignition advance angle and fuel dosage across a wide range of ethanol concentrations. Unlike many earlier studies, this research presents results obtained under full-load conditions using a chassis dynamometer and a mass-produced vehicle with standard ECU, increasing the practical relevance of the findings.

This study attempts to fill this gap by comprehensively evaluating six fuel mixtures with varying bioethanol content (0%, 10%, 30%, 50%, and 100%) in three kinds of engine setting. The analysis took into account both mechanical parameters (power, torque) and exhaust gas emissions (CO, CO₂, HC, O₂, and particulate matter).

The objective of this article is to determine the impact of bioethanol content in fuel mixtures and fuel supply parameters on the performance characteristics of engines, as well as identifying the optimal operating conditions for different ethanol proportions. Such an assessment is important in the context of the practical implementation of biofuels in road transport and in shaping emission reduction strategies in the automotive sector.

2. Research Plan and Program

The objective of the study was to determine the effect of bioethanol content in the fuel mixture on engine operating parameters and toxic engine exhaust gas emissions. For this purpose, an experimental test was carried out under laboratory conditions using a DynoTech DS04 2WD load-bearing chassis dynamometer with an electric brake and Dynotech^™ v9.6 software. The schematic of which is shown in Figure 1, providing a graphical supplement to the technical description of the chassis dynamometer and enhancing the clarity of the article, with the parameters described in

Table 1. Parameters of the stationary dynamometer.

Type of Dynamometer	DC 2WD Single-Axle Dynamometer
Weight	1180 kg
Width	3600 mm
Length	1120 mm
Height	350 mm
Maximum speed	260 km/h
Elevator lift capacity	3.5 T
Roller diameter	323.9 mm
Roller weight	88 kg
Power supply	230 V
Control	Electronic

.

The test vehicle was a Fiat Panda equipped with a naturally aspirated FIRE 1.2 8V gasoline engine, engine code 188A4000. The engine is a four-cylinder, inline, OHC type, with a displacement of 1242 cm³, a maximum power output of 44 kW, and torque of 102 Nm. It uses multipoint fuel injection and spark ignition. The compression ratio is 9.8:1. The manufacturer recommends gasoline with a minimum octane rating of RON 95.

The tests were conducted under a full engine load, after first warming up the engine to a coolant temperature of 75 °C. The ambient air temperature was 15 °C and the atmospheric pressure was 1000.4 kPa. In order to ensure repeatability of the results, a series of measurements was performed for each fuel configuration; on this basis, the average value of a given parameter was calculated.

Six fuel blends with different bioethanol content were used for the tests: 0%, 10%, 30%, 50%, and 100%. The kinematic viscosity of the tested fuel mixtures at 20 °C ranged from 1.2 mm²/s for E0 to 1.07 mm²/s for E100. The density changed from 789 kg/m³ for E0 to 775 kg/m³ for E100. These mixtures were fed into the engine using a specially adapted fuel system equipped with an additional 5 dm³ tank and a return pipe, as shown in Figure 2, where the vehicle is visible on the test bench. After each fuel change, the engine operated for approximately 10 min for the purpose of flushing the fuel system.

The experimental research was carried out in three distinct engine operation modes: under the factory engine control unit (ECU) settings with the factory spark timing (10° before top dead center—BTDC), which represents the baseline value specified in the official FIAT service documentation; a configuration with the fuel injection increased by 10% combined with an ignition advance angle correction of +3° (13° BTDC); and a third variant with a 20% increase in the fuel dose and the same ignition advance correction of +3° (13° BTDC). These settings were selected to evaluate the adaptability of the engine to ethanol-blended fuels under modified combustion conditions.

The independent variables in the tests were the ethanol content in the fuel blend—specifically 0%, 10%, 30%, 50%, and 100%—and the engine operation mode as defined above. The dependent variables measured included key engine performance parameters (torque and power), as well as emissions-related indicators: concentrations of carbon monoxide (CO), carbon dioxide (CO₂), hydrocarbons (HC), oxygen (O₂), and the amount of particulate matter (PM).

All tests were conducted at a full engine load, under stabilized environmental conditions of 15 °C ambient temperature and 1000.4 kPa atmospheric pressure. Prior to testing, the engine underwent maintenance, including the replacement of the engine oil, oil filter, and air filter. The fuel filter was removed to eliminate the risk of residual fuel contamination, and all test fuels were pre-filtered before being added to a dedicated 5 dm³ external fuel tank.

The recorded data for each test point represent average values calculated from a series of repeated measurements, ensuring the reliability and repeatability of results.

3. Research Methodology

The measurement of exhaust gas emissions and particulate matter was carried out using two devices: the MAHA MGT-5 exhaust gas analyzer and the MAHA MPM-4 particulate matter analyzer, as shown in Figure 3, illustrating the view of the measuring station with the installed devices.

The vehicle was immobilized on a dynamometer with stabilizing straps, which ensured its complete stability during testing. The connected devices allowed for the accurate determination of the concentration of individual exhaust gas components emitted by the engine while operating in different modes and with different fuel mixtures.

The MAHA MGT-5 exhaust gas analyzer enabled the measurement of the following gas contents:

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Hydrocarbons (HC)—organic compounds present in exhaust gases, resulting from incomplete fuel combustion;

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Oxygen (O₂)—indicator of oxygen content in exhaust gases, which allows the quality of the combustion process to be assessed;

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Carbon monoxide (CO)—a harmful gas generated by the incomplete combustion of fuel;

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Carbon dioxide (CO₂)—a gas that is a product of complete combustion, used to assess the energy efficiency of an engine.

Particulate matter measurements were performed using a MAHA MPM-4 analyzer (MAHA Maschinenbau Haldenwang GmbH & Co. KG, Haldenwang, Germany), which uses an optical method to measure the number and size distribution of particulate matter. Particulate matter generated during engine operation consists mainly of carbon and soot particles, which are released during incomplete combustion. The particulate matter analyzer uses an electronic particle counter to determine the number and size distribution, which allows the degree of particulate matter emissions to be assessed. Particles with dimensions exceeding 100 mm were detected during the experiments.

The measurement of the torque and power of the engine was conducted using a DynoTech 2WD chassis dynamometer (manufactured by DynoProjekt, Warsaw, Poland) equipped with an electric brake. This dynamometer was selected due to its measurement precision, flexibility in the selection of operating modes, and ability to operate under various load conditions, making it particularly useful for both diagnostic and research purposes. The device allows for operations in acceleration mode (inertial), which allows for quick measurements with minimal engine load, preventing it from overloading. On the other hand, the load mode with controlled, constant rotations and variable load enables the precise tuning of fuel supply systems, which is particularly important when analyzing the impact of changes in fuel mixture parameters, such as the bioethanol content, fuel dose, or ignition advance angle. The dynamometer automatically recorded the torque and power generated by the engine under various operating conditions. The measurements were performed under maximum engine loads, which ensured the repeatability and accuracy of the results for all the tested configurations. The data were collected in real time and recorded using the dynamometer control system, enabling their direct analysis and visualization. An additional advantage of the dynamometer is its simple operation, quick measurement configuration, and low labor intensity, allowing for the efficient performance of a series of tests with different proportions of ethanol in the fuel mixture.

The remaining emission parameters, such as CO₂, O₂, HC, and particulate matter, were recorded during each measurement, and the highest values obtained after the stabilization of the rotational speed were used for the calculations.

The accuracy of the measurements depended on the measuring devices and the conditions under which the tests were conducted.

The precision of the measuring equipment used during the study was in accordance with the specifications provided by the manufacturers. The MAHA MGT-5 exhaust gas analyzer features a measurement accuracy of ±0.1% of the indicated value for carbon monoxide (CO), carbon dioxide (CO₂), and oxygen (O₂) concentrations. For hydrocarbon (HC) emissions, the device provided a precision of ±1 ppm, ensuring high reliability in gas composition analysis. The MAHA MPM-4 particulate matter analyzer demonstrated an accuracy of ±5% for measuring particles within the size range of 1 to 100 µm. Additionally, the device ensured a particle count tolerance of ±1% relative to the total number of recorded particles. These tolerances guaranteed consistent and repeatable results across all tested fuel blends and engine settings.

All the measurements were carried out in line with calibration procedures, ensuring their high accuracy. The data were recorded in real time using a dynamometer system and exhaust gas analyzers. For further analysis, the highest measured power and torque values recorded during each measurement were used. The exhaust gas composition was measured throughout the entire measurement cycle, and the highest values obtained after the rotational speed stabilized were used for the analysis.

4. Analysis of the Results

Table 2. Average results obtained during the tests.

Mode	Ethanol [%]	Power [kW]	Torque [Nm]	Particulate Matter [mg/m3]	CO [%]	CO2 [%]	HC [ppm]	O2 [%]
Factory/default ignition settings	0	46.5	100.9	143	2.3	10.6	334	2.3
	10	46.3	100.8	104	0.89	12.7	292	0.76
	30	46.8	102.4	70.8	0.25	11.5	356	6.6
	50	45.0	101.2	121	0.3	9.7	183	8.3
	100	25.4	68.6	101	0.08	10	142	5.87
Dose +10%/Ignition +3°	0	47.7	102.3	117	1.21	12.7	398	3.6
	10	46.9	101.6	89	3.63	11.8	190	1.17
	30	46.6	103.4	130	0.97	13.3	96.5	1.5
	50	46.0	102.7	101	0.05	14.9	125.6	4.4
	100	34.3	85.4	99.1	0.04	11.1	55.7	5.74
Dose +20%/Ignition +3°	0	48.2	103.8	112	1.12	13.1	245	1.86
	10	46.8	101.3	97	1.65	11.6	263	3.69
	30	47.2	102.8	123	3.34	10.4	403	5.28
	50	47.7	103.3	116	0.99	11.5	155	4.39
	100	40.8	93.7	109	0.08	12	55	7.01

presents the average values of the obtained results. The obtained results were subjected to statistical analysis using the Statistica program. An analysis of variance was performed for the significance level of 0.05.

As shown in Figure 4, we changed the settings of the fuel dose by increasing it by 20% and adjusting the ignition advance angle by 30 for an engine powered by fuel not containing bioethanol; this resulted in a power increase of over 3.5%. Similar changes in power were measured for fuel with a 50% content, with a power increase of 5.8%. For the cases of fuel with 10 and 30% content, no statistically significant changes in power were observed.

With factory settings for fuel dosage and ignition, a decrease in power was observed across the entire test range as the ethanol content in the fuel increased. However, statistically significant differences only occurred when the ethanol content in the fuel exceeded 30%. In the analyzed range, for an ethanol content of 50%, a power decrease of 1.5 kW (3%) was observed compared to fuel without ethanol. For fuel containing 100% ethanol, the power decrease was 21.1 kW (28.7%). For controller settings where the fuel dose was increased by 10% and the ignition advance angle was increased by 30, a decrease in power was observed, but it was only statistically significant for ethanol content higher than 30%. The power output of the engine powered by fuel containing 100% bioethanol was 34.3 kW, which was more than 26% lower than the nominal power output (for an engine powered by gasoline with factory settings). Compared to the power obtained for identical settings (the fuel dose increased by 10% and the ignition advance angle increased by an additional 30), the power drop when using fuel containing 100% bioethanol was 28%. For an engine powered by fuel containing 100% bioethanol, with a 20% increase in fuel dosage and a 30° increase in ignition advance, the power reduction compared to fuel without bioethanol additive was over 15%.

As shown in Figure 5, changes in maximum torque, depending on the bioethanol content in the fuel and the controller settings, were dependent on both the settings and the fuel composition. For an engine powered by fuel not containing bioethanol, the value for setting (III) was 2.9% lower than for the factory settings. With the increasing ethanol content in the fuel up to a bioethanol content of 50%, no statistically significant changes in torque were found. Only when the torque was measured for fuel containing 100% bioethanol was a decrease of 32% observed. For setting (II), the decrease in torque was 16%, and, for a fuel dose increased by 20%, the decrease was 9.7%. The presented values indicate the beneficial effect of modifying the fuel dose and ignition angle in compensating for torque losses resulting from the use of fuels with a high ethanol content.

The content of particulate matter in the exhaust gases varied unevenly. The highest amount of particulate matter was measured for factory settings and fuel without bioethanol additive and amounted to 143 ppm. The lowest amount of particulate matter in the exhaust gases was found for fuel containing 30% bioethanol, amounting to 70.8 ppm, which was 50.0 lower than the maximum. As shown in Figure 6, with factory settings, the particulate matter content in the exhaust gas decreased with an increasing fuel dose. Similarly, the decrease in particulate matter decreased with factory settings for bioethanol content in the fuel increasing to 30%. At bioethanol contents of 50% and 100%, the amount of particulate matter was lower than for the factory settings and fuel without bioethanol additive.

As shown in Figure 7, the carbon monoxide (CO) content in the exhaust gases reached its highest value (3.63%) for fuel containing 10% bioethanol and settings increasing the fuel dose by 10%. The lowest carbon monoxide content in exhaust gases was measured for all settings when using fuel containing 100% bioethanol (0.08–0.04%). The differences in carbon monoxide content for fuel with 100% bioethanol did not differ significantly. For factory settings, the carbon monoxide content in the exhaust gases decreased non-linearly as the bioethanol content in the fuel increased, reaching the lowest value for fuel containing 100% bioethanol. For the case of fuel with a composition of 30 and 50% bioethanol, no statistically significant differences were found.

As presented in Figure 8, for factory settings, the highest carbon dioxide content in exhaust gases, amounting to 14.9%, was measured for fuel containing 50% bioethanol and settings increasing the fuel dose by 10% and the ignition advance angle by 30, amounting to 14.9%. This corresponds to the lowest carbon monoxide content in the exhaust gas. This indicates complete combustion of the fuel. The lowest carbon dioxide content (9.7%) was measured for factory settings and fuel containing 50% bioethanol. Such low carbon dioxide content in exhaust gases is not offset by reduced carbon monoxide content, but it is associated with an increased amount of particulate matter. This may indicate the incomplete combustion of the injected fuel.

In Figure 9, it is shown that the highest hydrocarbon content was measured for setting (II) and fuel without bioethanol additive, and setting (III) and fuel with 30% bioethanol content. The lowest hydrocarbon content was measured for fuel containing 100% bioethanol for settings (II) and (III). A relatively small but nearly two times higher hydrocarbon content was also measured for the fuel containing 30% bioethanol under setting II (with a 10% increase in fuel dosage). It should be noted that the highest hydrocarbon concentration was more than seven times greater than the lowest measured value.

The analysis of the oxygen (O₂) content in exhaust gases, depending on the proportion of ethanol and fuel supply parameters, is presented in Figure 10. Oxygen content in the exhaust gases exhibited nonlinear relationships. The highest oxygen content in exhaust gases was measured for fuel containing 50% bioethanol at factory settings. The lowest oxygen content was measured for fuel containing 10% bioethanol and factory settings. On average, the highest oxygen content in exhaust gases was found for fuel containing 100% bioethanol, for all settings. The combustion of alcohols requires less oxygen. A higher oxygen content in the exhaust gases usually indicates an excess of air (oxygen) in the air–fuel mixture. It is known that, with an air–fuel ratio coefficient exceeding 1.4 relative to the stoichiometric demand, ignition and fuel combustion problems in the engine arise. It is worth noting that, for the fuel containing 100% bioethanol, during the conducted tests, the lowest power and torque developed by the engine were observed for settings that did not increase the fuel dosage. This may indicate the achievement of the limiting value of the air excess coefficient. This is confirmed by the measured minimal carbon monoxide content in the exhaust gases (0.08%).

5. Conclusions

Based on our investigation of the impact of bioethanol content in fuel mixtures on the operating parameters of spark ignition engines and pollutant emissions, it was found that modifying the fuel supply system, such as by increasing the fuel dose and changing the ignition advance angle, can significantly compensate for the performance losses resulting from the use of alternative fuels. The analysis of the results indicates that bioethanol, as a component of motor fuel, affects both the performance and environmental parameters of the power unit. An increase in bioethanol content caused significant changes in the values of power, torque, and harmful emissions. The average values collected and analyzed during the experiment allowed for the assessment of trends and the following key observations to be made:

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Ethanol content significantly affects engine power and torque, especially at higher concentrations (≥50%). With 100% bioethanol content, a power reduction of up to 28.7% was recorded in comparison to gasoline fuel with factory settings.

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Torque was less sensitive to changes in fuel composition than power. Decreases were mainly observed for 100% bioethanol (even up to 32%), while, for blends up to 50%, the changes were not statistically significant.

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Emissions of carbon monoxide (CO) decreased significantly as the bioethanol content increased, reaching the lowest values at E100. These results suggest an improvement in combustion efficiency in terms of toxicity.

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Carbon dioxide (CO₂) emissions were varied and indicate that an increase in CO₂ does not always mean better combustion; at low CO₂ levels, an increase in particulate matter was observed, which may indicate incomplete combustion.

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When using bioethanol, a reduction in particulate matter emissions was observed, particularly at a concentration of E30, suggesting that this fuel composition may be a good compromise between exhaust gas cleanliness and efficiency.

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The highest hydrocarbon (HC) emissions were observed in mixtures without ethanol or with a 30% ethanol content—HC emissions were lowest for E100.

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The oxygen content in exhaust gases increased together with the increase in ethanol content, which results from the presence of oxygen in the bioethanol molecule and may support the combustion process.

Based on the above analysis, it can be concluded that, in many respects, a fuel mixture with 30% ethanol content is the most favorable solution, especially for setting II (with a 10% increase in the fuel dosage). This configuration resulted in satisfactory, practically unchanged power and torque values, along with a noticeable decrease in the emission of harmful compounds. Only the particulate matter content did not show a significant reduction, which may be caused by an unfavorable fuel combustion distribution process. In practice, this means that the engine can be adapted to run on an E30 mixture without significant operational losses, which provides a strong argument for considering the implementation of biofuels in real-world conditions.

In further studies, we recommend extending the scope of the research to include other ignition advance angles (e.g., +6°, +9°). It is also worth testing other types of power units, e.g., with turbocharging, direct injection systems or higher compression ratios, in order to assess the behavior of bioethanol in more advanced systems. In addition, it is advisable to conduct an analysis of the impact of fuel change—in particular ethanol–gasoline blends—in terms of the noise generated during engine operations. At the same time, it will be useful to analyze the results in terms of cost-effectiveness: comparing the cost of fuel with different bioethanol content levels in relation to the effects obtained, such as improved power, torque, or reduced emissions, taking into account different weightings of priorities (e.g., whether power or ecology is more important to the user).

Further research will include the evaluation of emissions under dynamic conditions, such as the start–stop cycles typical of hybrid and urban vehicles. These operating modes have a significant impact on the exhaust composition, especially during cold start phases. Other studies [25,26] provide valuable references for modeling such systems. It is also considered important to conduct research in a setup similar to the one presented in this study, but with the inclusion of investigations into in-cylinder processes such as temperature and pressure. The authors are preparing an appropriate test bench for this purpose.

In addition, the use of artificial intelligence methods is being considered to model and predict the emission of harmful compounds based on fuel composition and engine operating parameters. An example of such an approach is presented in a previous study [27], where machine learning algorithms were used to optimize emissions.