Optimization of Second-Generation Biodiesel Blends to Enhance Diesel Engine Performance and Reduce Pollutant Emissions

Abstract

In recent years, the global demand for energy has been continuously increasing. Biodiesel as a replacement for fossil fuels holds strategic importance for sustainable economic development, mitigating the environmental impact, and managing air pollution. The utilization of second-generation biodiesel has garnered significant research interest due to its physical and chemical characteristics that are comparable to diesel, its elevated cetane number, and its reduced viscosity. This study will transform the TBD234v6 fuel system, transforming the original diesel fuel system into a second-generation biodiesel/diesel hybrid fuel system. This study examined the impacts of second-generation biodiesel on combustion, performance, and emissions in diesel engines, as well as the influence of the deoxygenation rate on second-generation biodiesel. Grey decision-making was used to determine the optimal mixing ratio and deoxygenation rate. The results indicated that the optimal blend comprises 10% second-generation biodiesel and 90% diesel fuel. In dual-fuel mode at this blend ratio, there is a 3% increase in maximum pressure compared to running on pure diesel. Moreover, the fuel consumption rate decreases by approximately 5.6%. Nitrogen oxide (NO_x) and soot emissions decreased by 4.7% and 4.9%, respectively.

1. Introduction

Since the onset of the Industrial Revolution, there has been a close relationship between economic development and energy demand. As industrialization and urbanization approach completion, per capita energy consumption tends to saturate. Expanding industrial sectors has led to intensified environmental challenges [1,2,3,4,5,6]. The shipping sector is pivotal in global transportation and is characterized by substantial energy consumption [7,8]. According to the regulations of the International Maritime Organization (IMO), vessels involved in international commerce and exceeding 5000 total tonnage are required to submit their fuel consumption data to the flag state. In 2021, the IMO received fuel consumption reports from 94.4% of these vessels, forecasting an estimated international fuel demand of 224.8 million tons, reflecting a 3.8% annual growth. However, the operation of diesel engines leads to the emission of exhaust gases that contribute to irreversible harm to the environment and human health [9,10,11].

Researchers are exploring alternative fuels to mitigate fossil fuel consumption and curb emissions from marine diesel engines [12,13,14]. Shaimaa Seyam et al. have studied a new marine engine with a horizontal cost rate of USD 228 per hour, reducing carbon emissions by 35~61% [15]. Using hydrogen fuel cells and new engines has significantly optimized exhaust emissions [16,17]. However, challenges remain in the storage and transport of hydrogen fuel, and its economic feasibility requires further enhancement. A dedicated cohort of experts and scholars is actively researching more cost-effective, eco-friendly energy alternatives [18,19].

Numerous studies indicate that biodiesel has a wide range of raw materials and a cleaner combustion process. Biofuels comprise 75% of the world’s renewable energy [20]. Biodiesel is categorized into three types based on production methods: the first type, or first-generation biodiesel, is derived from renewable sources like plant seeds, animal fats, and used cooking oil; the second type, or second-generation biodiesel, is produced mainly through hydrogenation and deoxygenation of animal and plant fats; the third type, or third-generation biodiesel, is generated from straw, sawdust, solid waste, and microbial oils using methods like biomass gasification and microbial oil extraction [21,22,23]. First-generation biodiesel exhibits a slightly higher cetane number than diesel, offering enhanced combustibility and cost efficiency [24]. However, this biodiesel variant demonstrates corrosiveness, potentially damaging the rubber and plastic components in fuel pipelines [25,26]. The second generation of biodiesel has reduced the use of edible oil in terms of raw materials [27]. Furthermore, second-generation biodiesel is recognized for its desirable properties, such as a high cetane number and low sulfur content, positioning it as an environmentally friendly fuel on a global scale [27,28]. Third-generation biodiesel production is still in its developmental stages, contributing only a small fraction of the global biodiesel output [29]. Second-generation biodiesel and diesel exhibit similar physical and chemical properties, allowing for blending in any proportion [30]. Mohamed Qinawy et al. found that mixing a certain proportion of biodiesel can improve the combustion and emission performance of diesel engines [31]. The energy consumption for producing biodiesel is only 25% of that for producing petroleum diesel, and its biodegradation rate reaches 98%, doubling that of petroleum diesel [32]. Utilizing biodiesel in diesel engines holds significant potential in mitigating energy scarcity, the greenhouse effect, and other environmental challenges [33]. Dariusz Kurczyński’s team conducted bench tests on first-generation biodiesel, second-generation biodiesel, and diesel on the Perkins 1104D-44TA diesel engine. The test results showed that second-generation biodiesel resulted in lower emissions of harmful exhaust gases than first-generation biodiesel, thereby decreasing carbon dioxide, hydrocarbons, and particulate matter levels in the exhaust [34]. Vergel Ortega M et al. revealed that incorporating less than 4% ethanol into biodiesel can effectively reduce the emission levels of pollutants, including carbon moNO_xide (CO), carbon dioxide (CO2), NO_x, hydrocarbons (HC), and smoke opacity [35]. Zuo et al. explored various fuel injection strategies while substituting diesel with a biodiesel–ethanol dual fuel, discovering that the operation with biodiesel–ethanol resulted in NO_x and soot emissions that were 12.15% and 121% lower than those from diesel, respectively [12]. Zhong et al. utilized a blend of biodiesel and second-generation biodiesel in a six-cylinder direct injection diesel engine and found that the mixture of biodiesel shortened the ignition delay of the diesel engine and reduced NO_x and particulate matter (PM) emissions [36]. Nabi et al. observed a significant reduction in CO and HC emissions using a biodiesel mixture [37]. Despite these findings, the research corpus on the application of deoxygenated biodiesel in marine diesel engines remains incomplete, necessitating further comprehensive investigations by experts and scholars. This paper aims to investigate the effects of blending a specific proportion of deoxygenated biodiesel on the combustion and emission performance of diesel engines at a constant speed, considering the broad potential applications of second-generation biodiesel in shipbuilding. Given the high calorific value of second-generation biodiesel, the blending ratio was a crucial factor studied during the research. Additionally, the deoxygenation treatment of biodiesel has been noted in previous research to impact diesel engine performance. The study employed a grey decision-making theory mathematical model to determine the optimal blending ratio and deoxygenation level suitable for this diesel engine type.

2. Materials and Methods

2.1. Test Fuels

In this study, second-generation biodiesel was derived from first-generation biodiesel through the hydrogenation and deoxidation processes using a NiMo bimetallic catalyst, (Xiamen University, Xiamen, China) resulting in straight-chain alkanes. The obtained alkanes were then processed through hydroisomerization using a SAPO-11 catalyst (Xiamen University, Xiamen, China), with their physicochemical properties presented in

Table 1. Test fuels.

Physical and Chemical Properties	Second-Generation Biodiesel	Diesel Oil
Cetane number	80	46
Density/kg/m3/(20 °C)	780	840
Lower calorific value (MJ/kg)	43.61	42.05
Flash point (°C)	60	55
Sulfur content (%)	5.0 × 10−6	0.18
Kinematic viscosity 4 °C (mm2/s)	2.46	3.5
Ash content (%)	0.004	0.012

. To ensure the accuracy of the experiment, it is recommended to promptly utilize the mixed fuel during its preparation to prevent stratification due to prolonged storage, which could impede combustion within the cylinder, lead to testing inaccuracies, and jeopardize the reliability of the test outcomes [38]. The biodiesel mixture used in this experiment was prepared on site, as shown in Figure 1.

2.2. Test Engine

This study was conducted on the TBD234V6 four-stroke direct injection diesel engine, with relevant engine parameters detailed in

Table 2. The parameters of the test engine.

Project	Parameter
Number of cylinders	6
Bore [mm] × Store [mm]	128 × 140
Displacement [L]	10.8
Rated power [kW]	186
Speed [r/min]	1500
Compression ratio [−]	15:1
Maximum explosive pressure [MPa]	15
Rated cycle fuel supply [mg]	151

. This type of diesel engine is equipped with an NCK2010 automatic measurement and control system, which can achieve real-time adjustment of the diesel engine’s speed and torque to achieve the specified load. The fuel consumption rates were monitored in real time using the HZB2000 single-valve fuel consumption meter. The Kibox2 combustion analyzer (Kistler, Winterthur, Switzerland) was employed to collect and analyze data from cylinder pressure and other sensors. Particulate matter levels in the exhaust were measured using the AVL439 opaque opacimeter while emissions of NO, NO₂, CO, and HC were assessed using the HORIBA MEXA-1600DS exhaust analyzer (HORIBA, Munich, Germany). The second-generation biodiesel/diesel hybrid fuel tank was installed in this experiment, and the modified TBD234V6 diesel engine (China Henan Diesel Heavy Industry Co., Zhongzhou, China) test bench setup is depicted in Figure 2.

2.3. Test Scheme

This study used a second-generation biodiesel blend fuel with a deoxygenation ratio of 100% and pure diesel as the test fuel. The elevated calorific value of second-generation biodiesel can lead to heightened cylinder pressure in the diesel engine when blended in significant proportions, potentially resulting in cylinder failure [38]. Accordingly, the formulated biodiesel blend consisted of second-generation biodiesel and diesel in volume ratios of 2.5%, 5%, 7.5%, and 10%. Dry bulb temperature was 22 °C, wet bulb temperature was 16 °C, and relative humidity was 42.5% at the time of the test. The experimental conditions for the diesel engine testing were determined based on various load characteristics, with load levels set at 25%, 50%, 75%, and 100%. The resulting power and torque data are detailed in

Table 3. Load characteristic experiment working condition allocation.

Load [%]	25	50	75	100
Speed [r/min]	1500	1500	1500	1500
Power [kW]	46.5	93	139.5	186
Torque [N·m]	296	592	888	1184

.

This research also examined the influence of varying deoxygenation rates of biodiesel on the combustion process, engine performance, and emissions of diesel engines. The study predominantly focused on second-generation biodiesel with deoxygenation rates of 100%, 98%, 96%, and 94% for comparative analysis.

3. Results and Discussion

3.1. Performance

The fuel consumption rate of mixed fuels is calculated using Equation (1).

$$b_e={\displaystyle \frac{H_{uD}{X}_D+H_{uHIO}{X}_{HIO}}{H_{uD}}}{b}_i$$

(1)

$b_i$ is the actual fuel consumption rate measured by the fuel consumption meter, $b_e$ is the fuel consumption rate of the mixed fuel, $H_{uD}$ and $H_{uHIO}$ represent the calorific values of the test diesel and second-generation biodiesel, respectively, and $X_D$ and $X_{HIO}$ are the volume fractions of diesel and second-generation biodiesel in the mixed fuel [39]. Figure 3 illustrates the fuel consumption rates for H0, H2.5, H5, H7.5, and H10 blends. Under identical load conditions, diesel exhibits the highest fuel consumption rate. Compared to mixed fuels, diesel has a higher kinematic viscosity and poorer atomization effect, which could be more conducive to the full combustion of the fuel. During the diffusion combustion stage, fuel combustion is slower, resulting in lower combustion efficiency and an increased fuel consumption rate [40]. Compared with diesel, the fuel consumptions of mixed fuels H2.5, H5, H7.5, and H10 at the same load are slightly lower, and as the blending ratio increases, the fuel consumption decreases. Under the rated operating conditions of the diesel engine, the fuel consumptions of H2.5, H5, H7.5, and H10 decreased by 0.2%, 2.6%, 3.4%, and 5%, respectively.

Figure 4 shows the thermal efficiency of five different test fuels at four operating points. As the load increased, the thermal efficiency curves of all five test fuels increased. The bar graph shows that the thermal efficiency of the fuel added with biodiesel was improved compared to diesel fuel. Under full load conditions, the thermal efficiency values of H2.5, H5, H7.5, and H10 increased by 8.5%, 11.2%, 13.4%, and 14.5% compared to diesel.

3.2. Combustibility

Figure 5 illustrates the variations in in-cylinder gas pressure relative to crank angle changes for five tested fuels across loads ranging from 25% to 100%. With consistent load parameters, the peak pressure within a diesel engine cylinder rises in tandem with an escalated second-generation biodiesel blend ratio. Notably, at 25% and 50% loads, a substantial increase in peak pressure occurs that is attributable to the influences of the physicochemical properties of the blended fuel [38]. The peak pressure demonstrates a positive correlation with the second-generation biodiesel blending ratio. At elevated loads, the peak pressure rise is marginal with increased blending ratios due to the reduced excess air coefficient in the cylinder and the augmented injection of mixed fuel, which mitigates the mixed fuel’s physicochemical properties’ beneficial impact on combustion [41]. Therefore, the blending ratio of second-generation biodiesel has a minimal impact on cylinder pressure at high loads, resulting in a deceleration of the change in cylinder pressure. Figure 6 depicts the instantaneous heat release rate curve for the second-generation biodiesel with various blending ratios under optimal operating conditions. The curve demonstrates a bimodal heat release pattern, clearly indicating the presence of both premixed and diffusion combustion phases. Under full load conditions, the peak heat release rate of the second-generation biodiesel blend exhibits a marginal increase compared to diesel, with a slight advancement in the peak occurrence time [42,43].

3.3. Emissions

As the load continues to increase, the fuel injection increases, the air–fuel ratio decreases, and the oxygen concentration in the cylinder decreases, which is not conducive to CO oxidation, and therefore, the CO continues to increase. The CO generation of biodiesel blended in different ratios increased as compared to diesel fuel. The main reason for this is that biodiesel is an uNO_xygenated fuel and there are some oxygen-deficient regions at medium-to-high loads where the oxidation rates of incomplete combustion products are lower than their generation rates, leading to an increase in CO emissions. In addition, biodiesel has a high cetane number, which shortens the ignition delay period of the blend and reduces the volume of premixed combustible gases produced, leading to under-combustion and increased CO emissions at low loads [44].

Figure 7 displays the changes in HC emissions as the load increased [45]. HC emissions tended to decrease as the load increased. This was due to the lower in-cylinder temperatures at low loads, poorer combustion quality, and lower fuel injections. As the blending ratio rose, HC emissions also increased. Specifically, under 25% load conditions, the HC emissions for blends containing 2.5%, 5%, 7.5%, and 10% of biodiesel increased by 30.1%, 48.7%, 44.2%, and 50.1%, respectively. When the load was larger, the mixture ignition delay period was shortened, and the larger injection volume reduces the number of thin gas areas in the cylinder; with an increase in the load, the temperature and pressure in the cylinder increased and improved the fuel injection and atomization, and the combustion situation, so the HC emissions were reduced.

Figure 7 depicts the NO_x emissions variations from 25% to 100% loads. NO_x emissions gradually increased between 25% and 75% loads, and decreased a little with a 100% load, mainly because the load conditions in the cylinder temperature were low, and the oxidation reaction to generate NO needs to be carried out at high temperatures, and generates less NO; with the load gradually increased to 75%, the temperature in the cylinder rose significantly, and the amount of NO generation increased; and when the load reached 100%, even though the cylinder temperature was further increased, the injection volume was larger at high loads, but more oxygen was needed for combustion, which made NO_x emissions lower. When the load reached 100%, although the in-cylinder temperature was further increased, the injection volume was larger under a high load, which required more oxygen for combustion, and the relative oxygen concentration in the cylinder restricted the generation of NO, resulting in lower NO_x emissions.

Soot emissions were minimal at a 25% load, with deviations for H2.5, H5, H7.5, H10, and diesel at 6.5%, 29.0%, 35.5%, and 38.7%, respectively. The soot content was the least at a low load, which may be attributed to the lower temperature in the cylinder and the oxygen in the cylinder being more sufficient, which could effectively inhibit the formation of particulate precursors and reduce particulate emissions. With an increase in the load, the soot emissions gradually increased; the reason for this was that the temperature in the cylinder continued to rise, and the injection volume became larger; the excess air coefficient decreased, the oxygen concentration in the cylinder gradually decreased, and the high-temperature aNO_xic area became larger, so the soot generation became more [46].

4. Performance Evaluation and Optimal Blending Ratio Decision

4.1. Grey Decision-Making

Integrating classic decision-making principles and techniques, the grey decision analysis method exhibits high efficiency and precision in addressing uncertain issues within decision-making systems [47,48]. Marine diesel engines commonly face challenges related to power, economy, and emissions during actual maritime navigation, with typical issues including insufficient power, a poor fuel economy, high soot emissions, and excessive NO_x emissions at low loads [49]. Therefore, it is vital to investigate the optimal blending ratio of second-generation biodiesel across various loads following experimental completion to enhance diesel engine performance [50]. This section aims to develop a grey decision-making multi-objective optimization model, utilizing experimental data to ascertain the comprehensive optimization effect values for different second-generation biodiesel blending ratios under varied loads. The objective is to identify the optimal blending ratio for second-generation biodiesel and examine its influence on the comprehensive performance of the TBD234V6 diesel engine at this optimal ratio.

4.2. Constructing a Multi-Objective Grey Decision-Making Model

The construction of a multi-objective grey decision model comprises five key components: the situation set, decision objectives, corresponding effect sample matrix for each objective, effect measurement matrix, and comprehensive effect measurement matrix. The process of establishing a model involves the following steps:

(1) Establish a situation set and decision objectives

Construct a situation set by combining the event set and countermeasure set, with the event set as A = {a₁, a₂…a_n}, the countermeasure set as B = {b₁, b₂…b_m} and the countermeasure set as $s=\left\{s_{ij}=\left(a_i,b_j\right)|a_i\in A,b_j\in B\right\}$. Let $u_{ij}^{\left(k\right)}i=1,2\dots n;j=1,2\dots m$. Define the effect value of the situation set under decision objective k. A = {a1} represents the second-generation biodiesel blended with diesel engines as the event; B = {b1, b2… b6} encompasses different blending ratios of the second-generation biodiesel as the countermeasure values. Based on the above experimental data, the highest cylinder pressure fuel consumption rate and CO, HC, NO_x, and soot emission concentrations are set as decision objectives k; $u_{ij}^{\left(k\right)}$ is the experimental data value corresponding to various decision-making objectives under different blending ratios of the second-generation biodiesel.

(2) Improve effect measurement

The decision objective needs to establish an effect measure, and there are three ways to determine the effect measure under decision objective k: the upper limit effect measure, lower limit effect measure, and moderate effect measure. When the decision target value necessitates an increase, the upper-limit effect measure is illustrated in Equation (2). Conversely, when a decrease in the decision target value is required, the lower-limit effect measure is depicted in Equation (3). For cases where a moderate range within the decision values is sought, the moderate effect measure is presented in Equation (4).

$$r_{ij}^{\left(k\right)}={\displaystyle \frac{u_{ij}^{\left(k\right)}}{\underset{i}{max}\underset{j}{max}\left\{u_{ij}^{\left(k\right)}\right\}}}$$

(2)

$$r_{ij}^{\left(k\right)}={\displaystyle \frac{\underset{i}{min}\underset{j}{min}{u}_{ij}^{\left(k\right)}}{u_{ij}^{\left(k\right)}}}$$

(3)

$$r_{ij}^{\left(k\right)}={\displaystyle \frac{u_{i_0{j}_0}^{\left(k\right)}}{u_{i_0{j}_0}^{\left(k\right)}+\left|u_{ij}^{\left(k\right)}-u_{i_0{j}_0}^{\left(k\right)}\right|}}$$

(4)

To enhance the overall performance of diesel engines, this paper establishes effectiveness measures for various decision objectives. The upper limit effectiveness measure pertains to the maximum cylinder pressure while the lower limit effectiveness measure encompasses the fuel consumption rate and CO, HC, NO_x, and soot emission concentrations.

(3) Building an effect measurement matrix

The effectiveness measures differ for various decision objectives. Based on the corresponding experimental data, obtain a consistent effectiveness measure matrix for the situation set under decision objective k, as shown in Equation (5).

$$R^{\left(k\right)}=\left(r_{ij}^{\left(k\right)}\right)=\left[\begin{array}{c}{r}_{11}^{\left(k\right)}{r}_{12}^{\left(k\right)}\cdot \cdot \cdot r_{1m}^{\left(k\right)}\\ r_{21}^{\left(k\right)}{r}_{22}^{\left(k\right)}\cdot \cdot \cdot r_{2m}^{\left(k\right)}\\ \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \\ r_{n1}^{\left(k\right)}{r}_{n2}^{\left(k\right)}\cdot \cdot \cdot r_{nm}^{\left(k\right)}\end{array}\right]$$

(5)

Among them, the consistent effect measure vector of situation a is $r_{ij}=\left(r_{ij}^{\left(1\right)},r_{ij}^{\left(2\right)},\cdot \cdot \cdot ,r_{ij}^{\left(n\right)}\right)$.

(4) Calculate the comprehensive effect measurement matrix

Let ${\eta }_k\left(k=1,2,\cdot \cdot \cdot s\right)$ and ${{\displaystyle \sum }}_{k=1}^s{\eta }_k=1$.The comprehensive effect measure of situation a, denoted as measure b, is derived by calculating the decision weight as described in Equations (6) and (7), which present the comprehensive effect measurement matrix.

$$R=\left(r_{ij}\right)=\left[\begin{array}{c}{r}_{11}{r}_{12}\cdot \cdot \cdot r_{1m}\\ r_{21}{r}_{22}\cdot \cdot \cdot r_{2m}\\ \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \cdot \\ r_{n1}{r}_{n2}\cdot \cdot \cdot r_{nm}\end{array}\right]$$

(6)

$$r_{ij}={{\displaystyle \sum }}_{k=1}^s{\eta }_k\cdot r_{ij}^{\left(k\right)}$$

(7)

4.3. Method of Assigning Decision Weights to Decision Objectives

This paper adopts a nuanced approach for weighting each decision objective, combining subjective and objective methods. This approach involves assigning subjective weights to primary decision objectives and objective weights to secondary ones. This strategy mitigates the potential biases inherent in subjective or objective weighting methods. Considering the insufficient power performance when the diesel engine is at low load, the core decision objective is the maximum cylinder pressure, with weight assignment ${\alpha }_1$ = 0.35, and the subordinate decision-making objectives are the fuel consumption rate and NO_x, soot, CO, and HC emission concentrations. Conversely, diesel engines exhibit poor emission performance at medium-to-high loads, particularly in terms of high NO_x emissions. Therefore, the core decision-making objective shifts to NO_x emissions, differing from the low-load scenario. Due to the differences in the NO_x emission concentration at medium-to-high loads, the weight of NO_x emissions at medium loads is assigned ${\alpha }_3$ = 0.4. Weight assignment of NO_x emissions at high loads ${\alpha }_3$ = 0.5. The remaining five objectives serve as subordinate decision objectives.

We determine the degree of correlation between the primary and secondary decision-making objectives using the grey correlation analysis method for ${\varphi }_{12}$, ${\varphi }_{13}$ and ${\varphi }_{14}$. We calculate formula 8 as follows:

$${\phi }_{ij}={\displaystyle \frac{1+\left|s_i\right|+\left|s_j\right|}{1+\left|s_i\right|+\left|s_j\right|+\left|s_i-s_j\right|}}$$

(8)

Then, the entropy weight method is used to eliminate the subjective human factors introduced by weighting the core decision objective, and the objective weight ${\epsilon }_i$ under the decision objective is obtained. Based on Equation (9), the final weight ${\eta }_i$ of each decision objective is calculated.

$${\eta }_i={\displaystyle \frac{a_i{\beta }_i}{\sum \stackrel{\underset{n}{i=1}}{a_i{\beta }_i}}}$$

(9)

4.4. Determination and Evaluation Analysis of the Optimal Blending Ratio

To manage the extensive computations involved in determining the optimal blending ratio of second-generation biodiesel across all operating conditions, the analysis was simplified by selecting representative operating points. Specifically, 25% load serves as the low-load condition, 50% load represents medium-load scenarios, and 100% load stands for high-load situations.

(1) 25% load

The primary objective for decision-making and the initial weight for a 25% load characteristic was the highest cylinder pressure, ${\alpha }_1$ = 0.35. The comprehensive performance optimization effect matrix of the diesel engine resulting from calculations was as follows:

$$R_{Z25\%}={\eta }_{25\%}·R_{25\%}=\left|0.8930, 0.8449, 0.8861, 0.9091, 0.9306\right|$$

Analysis of the calculations revealed that under the 25% load condition and specific load characteristics, a blending ratio of 10% for second-generation biodiesel yielded the highest comprehensive performance optimization value of 0.9306, indicating the favorable overall performance of the diesel engine under this configuration. The TBD234V6 diesel engine demonstrated superior overall performance optimization at low loads with a second-generation biodiesel blending ratio of 10%. Compared to a second-generation biodiesel blend ratio of 0, the maximum cylinder pressure increased by approximately 8.7%, reducing the fuel consumption by about 5.4%. Moreover, NO_x emissions decreased by approximately 13.4%, soot emissions decreased by around 38.7%, CO increased by about 21.6%, and HC increased by approximately 50.1% [51].

(2) 50% load

The core decision-making objective of 50% load differed from that of 25% load, and this was the NO_x emission concentration with an initial weight of ${\alpha }_3$ = 0.4. At this time, the comprehensive performance optimization effect matrix of the diesel engine was as follows:

$$R_{Z50\%}={\eta }_{50\%}·R_{50\%}=\left|0.9428, 0.9162, 0.9448, 0.9703, 0.9761\right|$$

The comprehensive performance optimization matrix results demonstrated a gradual enhancement in the overall performance of the diesel engine as the blending ratio of second-generation biodiesel increased to 50% at a characteristic operating point load. The performance reached its optimal level when the second-generation biodiesel blending ratio was 10%. At this optimal blending ratio, the maximum cylinder pressure of the diesel engine increased by approximately 1.7% compared to a 0% blending ratio. Furthermore, the fuel consumption rate decreased by about 4.5%, NO_x emission concentration reduced by 9.1%, soot emission concentration decreased by 11.3%, CO emission concentration increased by 8.1%, and HC emission concentration rose by approximately 21.6%. The research findings suggest that employing a 10% blending ratio of second-generation biodiesel in a diesel engine results in superior comprehensive performance at medium load characteristics.

(3) 100% load

When the load characteristic was 100%, the core decision-making objective was the NO_x emission concentration, which remained consistent with that at 50% load, and the initial weight was also ${\alpha }_3$ = 0.4. The comprehensive performance optimization matrix of the diesel engine under these conditions was as follows:

$$R_{Z100\%}={\eta }_{100\%}·R_{100\%}=\left|0.9521, 0.9156, 0.9438, 0.9573, 0.9959\right|$$

The analysis of the calculated results revealed that the most effective blending ratio for second-generation biodiesel blending remained at 10% when operating at full load. Compared with diesel engines fueled with pure diesel, the engine using a 10% biodiesel blend exhibited a 3% increase in the highest cylinder pressure. Additionally, there was a 5.6% reduction in the fuel consumption rate, a 4.7% decrease in NO_x emissions, a 4.9% reduction in soot emissions, a 1.2% increase in CO emissions, and a 4% rise in HC emissions. This optimal blending ratio enhanced the combustion and emission performance of the diesel engine, as well as its economic efficiency under full load conditions. Specifically, the TBD234V6 diesel engine’s test results at 90% and 100% operating conditions under high load underscored that a 10% biodiesel blend optimized the comprehensive performance of the engine. Therefore, for high-load conditions, the second-generation biodiesel’s 10% blending ratio maximized the engine’s overall performance.

The research demonstrates that under various load conditions, blending second-generation biodiesel at a 10% ratio with diesel significantly enhances the comprehensive performance of the diesel engine. At operating points from 10% to 75% loads, while there is a slight trade-off in emissions, the engine experiences notable improvements in economy and power performance. In the higher load range, specifically between 90% and 100%, the engine shows substantial enhancements in combustion and emission performance, along with a moderate improvement in economic efficiency [52]. Consequently, the overall performance optimization effect is more pronounced, indicating that a 10% second-generation biodiesel blend is optimal for balancing performance, emissions, and efficiency across a broad spectrum of operating conditions.

5. Research on Optimizing the Performance by Changing the Deoxygenation Ratio

5.1. Deoxygenation Ratio

The previous research utilized fully deoxygenated second-generation biodiesel. Since the fuel oxygen content contributes to increased NO_x emissions and enhances combustion and cylinder combustion effects [53], this study aimed to refine the diesel engine’s overall performance. This study aimed to optimize the oxygen content of the mixed fuel quantitatively using deoxygenation treatment and to analyze the resulting changes in various performance parameters of a diesel engine through bench tests. The goal was to identify the optimal deoxygenation ratio scheme that fulfilled the emission performance requirements of diesel engines while enhancing power and economic efficiency. The selection of the deoxygenation ratio for second-generation biodiesel is critical as it significantly impacts the physical and chemical properties of the fuel. Variations in the deoxygenation ratio can lead to changes such as a decrease in the cetane number, an increase in viscosity, and a decrease in the calorific value, all of which influence the operational performance of the diesel engine. Therefore, we examined deoxidation ratios of 100%, 98%, 96%, and 94% for the second-generation biodiesel.

5.2. Performance

Figure 8 illustrates a bar chart showing the fuel consumption rate for mixed fuels with a 10% blending ratio and deoxygenation ratios of 100%, 98%, 96%, and 94%. Across various operating conditions, the fuel consumption rate increased as the deoxygenation ratio decreased. This trend is attributed to the lower calorific value of the mixed fuels, necessitating higher fuel consumption to achieve the desired power output. Additionally, as the deoxygenation ratio decreased, the cetane number of the mixed fuel decreased, impeding complete fuel combustion. Consequently, the fuel combustion efficiency decreased, leading to higher fuel consumption rates.

5.3. Combustion

Figure 9 depicts the cylinder pressure curves of biodiesel/diesel blend fuels with a 10% blending ratio and deoxygenation ratios of 100%, 98%, 96%, and 94% under various operating conditions at a constant speed of 1500 rpm. The figure shows that the diesel engine’s maximum cylinder pressure gradually diminishes with the decrease in the deoxygenation ratio of the mixed fuel. Additionally, the peak cylinder pressure is delayed and exhibits a declining trend.

Figure 10 shows the instantaneous heat release rate curve of a diesel engine under rated operating conditions of 1500 rpm and 186 kW. Analysis of the curve revealed that under these rated operating conditions, the peak heat release rate of the diesel engine fueled with second-generation biodiesel at varying deoxygenation ratios decreased. Additionally, there was a slight backward shift in the peak scale of the curve.

5.4. Emissions

(1) CO

Figure 11 displays the CO emission curves of biodiesel/diesel blends with a 10% blending ratio and deoxygenation ratios of 100%, 98%, 96%, and 94%. The results indicate that as the deoxygenation ratio gradually decreases, CO emissions exhibit a declining trend under identical operating conditions. This trend arises from the increased oxygen content in the fuel as the deoxygenation rate decreases, facilitating more complete combustion reactions.

As the load increases, the fuel injection quantity increases, requiring more oxygen for combustion. The incomplete combustion caused by low oxygen content in the cylinder promotes the generation of CO, and the increase in cylinder pressure and temperature also decreases compared to medium and low loads. Therefore, the CO emissions of mixed fuels increase under high loads.

(2) HC

The images indicate consistent trends in HC emissions for the four fuel types under varying load characteristics. Fuels with lower deoxygenation ratios exhibit reduced HC emissions under identical operating conditions. This trend arises because lower deoxygenation ratios correspond to lower cetane numbers, which impede the continuous oxidation of HC. However, a higher oxygen content in the fuel promotes the complete combustion of the mixed fuel. Therefore, a trade-off exists between these two factors. Experimental results demonstrate that a higher oxygen content in the fuel facilitates the further oxidation of unburned HC, ultimately leading to reduced HC emissions.

(3) NO_x

The image suggests that as the deoxygenation ratio of the mixed fuel decreases, the NO_x emissions of diesel engines increase under identical operating conditions, particularly under load characteristics. The primary factors contributing to NO_x emissions include high temperatures during fuel combustion, oxygen enrichment, and the duration the fuel remaining at elevated temperatures. Decreasing the deoxygenation ratio increases the oxygen content within the fuel, thereby promoting NO_x generation. Consequently, the NO_x emissions of diesel engines also rise accordingly.

(4) Soot

Figure 11 displays the emission curve of soot, revealing that diesel engines fueled with a lower deoxygenation ratio of mixed fuel exhibit lower soot emissions. This difference is particularly pronounced at high loads.

5.5. The Optimal Deoxygenation Ratio of Biodiesel

The author continues to employ the grey decision mathematical model to determine the optimal deoxygenation ratio that aligns with the comprehensive performance optimization of diesel engines. Given the varying impacts of deoxygenation ratios on cylinder pressure and NO_x emissions when blending second-generation biodiesel with diesel engines, with a particularly significant reduction in the peak cylinder pressure observed at low loads, this section adopts the highest cylinder pressure as the core decision-making objective for low loads. Conversely, NO_x emissions constitute the core decision-making objective under medium-to-high loads. Specifically, the representative operating points selected are 25% load for low-load, 50% for medium-load, and 100% for high-load scenarios.

(1) 25% load

The comprehensive performance optimization effect matrix of the diesel engine obtained through calculation is as follows:

$$R_{Z25\%}={\eta }_{25\%}·R_{25\%}=\left|0.9711, 0.9709, 0.9797, 0.9687\right|$$

According to the matrix results, the optimal deoxygenation ratio at a 25% load is 96%, with an effect value of 0.9797. Compared to the second-generation biodiesel with a 10% blending ratio and a 100% deoxygenation ratio, the highest cylinder pressure of a diesel engine fueled with a 96% deoxygenation ratio of the second-generation biodiesel/diesel blend fuel is reduced by 2.8%, the fuel consumption rate is increased by 1.9%, CO emissions are reduced by 8.1%, HC emissions are reduced by 3.7%, NO_x emissions are increased by 1.9%, and soot emissions are reduced by 8%. Compared with diesel, the maximum cylinder pressure has increased by 5.4%, the t fuel consumption rate has decreased by 3.6%, CO emissions have increased by 9%, HC emissions have increased by 44.5%, NO_x emissions have decreased by 11.7%, and soot emissions have decreased by 43.6%. Overall, the diesel engine’s comprehensive performance, power, and economic efficiency have improved. Furthermore, certain emission aspects, such as soot emissions, have shown significant enhancement.

(2) 50% load

The comprehensive performance optimization effect matrix of the diesel engine obtained through calculation is as follows:

$$R_{Z50\%}={\eta }_{50\%}·R_{50\%}=\left|0.9646, 0.9607, 0.9728, 0.9792\right|$$

Based on the calculation results of this matrix, the optimal effect value is 0.9792, indicating that the optimal deoxygenation ratio for burning the second-generation biodiesel/diesel blend fuel with a 10% blending ratio at 50% load is 94%. Compared with a deoxygenation ratio of 100%, the maximum cylinder pressure of a diesel engine is reduced by 1.2%, the fuel consumption rate is increased by 3.4%, CO emissions are reduced by 12.3%, HC emissions are reduced by 12.1%, NO_x emissions are increased by 2.6%, and soot emissions are reduced by 8.8%. Compared with diesel, the maximum cylinder pressure has increased by 0.4%, fuel consumption has decreased by 1.2%, CO emissions have decreased by 19.4%, HC emissions have increased by 6.9%, NO_x emissions have decreased by 6.7%, and soot emissions have decreased by 19.2%. This analysis demonstrates that adopting blended combustion deoxygenation second-generation biodiesel technology in diesel engines has markedly enhanced economic and power performance. Despite a slight increase in HC emissions, there have been significant reductions in CO, soot, and NO_x emissions.

(3) 100% load

The comprehensive performance optimization effect matrix of the diesel engine obtained through calculation is as follows:

$$R_{Z100\%}={\eta }_{100\%}·R_{100\%}=\left|0.9615, 0.9724, 0.9704, 0.9762\right|$$

According to the calculation results of this matrix, it is evident that under a 100% load, the optimal deoxygenation ratio of second-generation biodiesel with a 10% blending ratio in the diesel engine remains at 94%. Compared with biodiesel with a 100% deoxygenation rate, the maximum cylinder pressure of the diesel engine is reduced by 4.4%, the fuel consumption rate is increased by 2.7%, CO emissions are reduced by 7%, HC emissions are reduced by 27.9%, NO_x emissions are increased by 1.5%, and smoke and dust emissions are reduced by 5.7%. Compared with diesel fuel, the peak cylinder pressure and fuel consumption rate slightly decrease, CO emissions decrease, and NO_x emissions increase. The economic performance of diesel engines has been improved to a certain extent, with significant enhancements in emission performance.

6. Conclusions

The study conducted experiments on the TBD234V6 engine, examining the combustion, economy, and emission performance of five test fuels under various load characteristics (25%, 50%, 75%, and 100%). This article has also explored the optimization effect of the optimal blending ratio and deoxygenation ratio of biodiesel. The key findings are summarized as follows:

(1) The fuel consumption of second-generation biodiesel decreases as the load increases. Specifically, under standard operating conditions, second-generation biodiesel exhibits lower fuel consumption compared to diesel, with further reductions as the blending ratio increases. In this study, at full load, the fuel consumption for diesel engines using blends of H2.5, H5, H7.5, and H10 decreased by 0.2%, 2.6%, 3.4%, and 5%, respectively, resulting in an overall improvement in the economic performance of the engines.

(2) With increasing load, the ignition timing of diesel engines fueled with second-generation biodiesel is advanced, particularly notable at higher loads. Compared to diesel, the peak heat release rates for blends of H2.5, H5, H7.5, and H10 occur 0.5°CA, 0.9°CA, 1.3°CA, and 1.6°CA earlier, respectively.

(3) Diesel engines using second-generation biodiesel exhibit a 1.7% reduction in maximum cylinder pressure, a 3% decrease in the fuel consumption rate, a reduction of 5.9% in CO emissions, a significant decrease of 30.9% in HC emissions, and an increase of 4.9% in NO_x emissions compared to diesel fuel.

(4) Utilizing a grey decision mathematical model, the study determined the optimal blending ratio of biodiesel to be 10% and the optimal deoxygenation ratio to be 94%, resulting in the best comprehensive performance.

The experimental results focused only on the TBD234V6 engine. It would be useful to study the possibilities of using the results for other types of engines, especially for those widely used in the marine industry.