Engine Generator Set Research Articles

Research on load-resistant enhancement control optimization of composite energy power supply system based on deep reinforcement learning

Abstract To solve the problem of insufficient inertia in the power electronics components under the development trend of power electronics in the transmission system of heavy-duty electric vehicles, combined with the composite energy power supply mode and control method, voltage-based feedback channels and virtual capacitor branches are designed for both engine-generator sets and DCDC control loops. These innovations compensate for system inertia and introduce a TD3 deep reinforcement learning-based adaptive regulation component to manage electrical systems in response to DC voltage fluctuations. This approach enhances the stability of the entire system in the face of load disturbances. Strategy validations demonstrate that this method ensures stable system operation, significantly mitigates DC voltage fluctuations during sudden load changes and is highly adaptable without relying on system models.

A physics-informed learning algorithm in dynamic speed prediction method for series hybrid electric powertrain

Engine-generator set (EGS) is an important energy supply component of high-voltage microgrid in series hybrid electric powertrain (SHEP). Sustained and steady energy supply from EGS is one of the conditions for the balanced energy between supply and demand. In some high-power processes, the balanced energy would be broken and the dynamic speed of EGS would be out of expectation, which can result in unstable working states of EGS. If the unstable working states of EGS can be known prior, it is significant for the research of unstable state identification and avoidance. Predicting rotational speed of EGS can warn of the previous issue in advance, while the insufficient data of unstable states would encounter overfitting problems in common prediction methods, so it is a challenge to improve the prediction effect of dynamic speed and then accurately predict the unstable states. Base on the above problems, a physics-informed learning algorithm with adaptive mechanism is proposed for EGS rotational speed prediction in this paper. First, a prediction problem related to the stability of SHEP running state is studied, which is found from engineering knowledge. Second, a new mechanism is proposed for physics-informed learning algorithm, and the physical information adopted to learning algorithm is more selective. Third, a professional adaptive function is originally formed according to speed characteristics, which bridge the information between physics and learning algorithm. By importing the experimental data, the prediction accuracy of proposed method in one of the test cycles is better than the results of baseline methods, specifically 27.11% and 3.49%, 11.90% and 7.94%, 53.83% and 27.62%. In summary, the proposed method can have better predictions against other baseline methods.

Optimal sizing of hybrid PV–diesel–biomass gasification plants for electrification of off-grid communities: An efficient approach based on Benders’ decomposition

Nowadays, millions of people in remote areas do not enjoy an uninterrupted power supply due to the lack of connectivity to the main power grid. Under such circumstances, the only feasible way to access electricity is typically local power generation, often relying on diesel engine–generator sets or photovoltaic arrays. However, on many occasions, this configuration does not fully exploit all available local resources, including biomass. Indeed, most isolated areas have access to local biomass production from agricultural activities, which can be used for local electricity generation through gasification. This paper addresses this challenge by developing an innovative optimal sizing tool for hybrid power plants integrating biomass gasifiers, specifically designed for isolated areas with access to local biomass production. The novel approach models the particular features of biomass gasification technologies, including long on/off times or restrictive ramping limits. To this end, an efficient methodology based on representative weeks is proposed, which is combined with a solution strategy based on the multi-cut Benders’ decomposition, thus resulting in a tractable framework that can deal with a huge amount of data efficiently. One of the most salient features of the new proposal is the consideration of local biomass production, which is included in the methodology through an original algorithm. Accordingly, a certain amount of biomass is sourced locally, leading to more accurate and reliable results. The new methodology is applied to a benchmark off-grid community in Ghana. The results demonstrate that the use of gasifiers reduces the project cost notably (by 90%) driven by the reduced biomass cost, which can be supplemented by locally generated biomass from agricultural activities. In addition, this technology constitutes a clean source of energy, reducing the total CO2 emissions by 83% compared to a baseline case in which only diesel generators are used. Moreover, it is demonstrated that biomass gasification can effectively act as base load power generation technology to reliably cover most of the local demand, thereby enabling a clean and inexpensive dispatchable local power generation. Finally, a sensitivity analysis reveals that the economic feasibility of the plant is more sensitive to the biomass cost than the selling price of biochar, resulting in a 33% increment in the total project cost when the price of biomass increases from 0 to 0.4 $/kg. Nevertheless, gasification remains as the predominant power generation technology even under unfavorable prices.

The Interaction between Short- and Long-Term Energy Storage in an nZEB Office Building

The establishment of near-autonomous micro-grids in commercial or public building complexes is gaining increasing popularity. Short-term storage capacity is provided by means of large battery installations, or, more often, by the employees’ increasing use of electric vehicle batteries, which are allowed to operate in bi-directional charging mode. In addition to the above short-term storage means, a long-term storage medium is considered essential to the optimal operation of the building’s micro-grid. The most promising long-term energy storage carrier is hydrogen, which is produced by standard electrolyzer units by exploiting the surplus electricity produced by photovoltaic installation, due to the seasonal or weekly variation in a building’s electricity consumption. To this end, a novel concept is studied in this paper. The details of the proposed concept are described in the context of a nearly Zero Energy Building (nZEB) and the associated micro-grid. The hydrogen produced is stored in a high-pressure tank to be used occasionally as fuel in an advanced technology hydrogen spark ignition engine, which moves a synchronous generator. A size optimization study is carried out to determine the genset’s rating, the electrolyzer units’ capacity and the tilt angle of the rooftop’s photovoltaic panels, which minimize the building’s interaction with the external grid. The hydrogen-fueled genset engine is optimally sized to 40 kW (0.18 kW/kWp PV). The optimal tilt angle of the rooftop PV panels is 39°. The maximum capacity of the electrolyzer units is optimized to 72 kW (0.33 kWmax/kWp PV). The resulting system is tacitly assumed to integrate to an external hydrogen network to make up for the expected mismatches between hydrogen production and consumption. The significance of technology in addressing the current challenges in the field of energy storage and micro-grid optimization is discussed, with an emphasis on its potential benefits. Moreover, areas for further research are highlighted, aiming to further advance sustainable energy solutions.

ANALISA PERFORMA HEAT EXCHANGER DENGAN PENAMBAHAN VORTEX GENERATOR TIPE WIRECOIL GUNA MENCEGAH ICING PADA KARBURATOR

This study aims to evaluate the influence of vortex wirecoil generators with different pitch variations on heat transfer coefficients, pressure drop, and heat exchanger effectiveness. The method involves experiments with a prototype heat exchanger simulation utilizing exhaust gas from a genset engine to address carburetor freezing issues in aircraft with piston engines, with a parallel flow configuration. The solution proposed involves using vortex generators and shell-and-tube heat exchangers. Shell and tube heat exchangers aim to improve heat exchange efficiency because the fluid flow in the pipes bends, creating significant secondary flow and enhancing heat transfer. This study involves various tools and components, including steel wire as the vortex wirecoil generator with size variations of 1.5, 2.5, and 3.5 cm. Other components consist of galvanized iron cells and copper tubes, as per the research plan. The research results indicate that pitch variations of wirecoil inserts in concentric pipes create turbulent flow that maximizes heat transfer to the air inside the cell. The 3.5 cm wirecoil yields the highest heat transfer coefficient U0 with an average value of 10.4. Additionally, adding variations of vortex wirecoil generators in concentric pipes increases the heat release from the hot fluid in the exhaust gas, enhancing heat exchanger effectiveness. The best effectiveness performance is achieved with a 2.5 cm wirecoil with an average value of 70.09.However, adding pitch variations of wirecoil inserts also disrupts the flow, changing it from laminar to turbulent, with the highest pressure drop occurring with the 3.5 cm wirecoil, with an average value of 17.89 Pa. These findings provide insights into improving efficiency and altering flow in heat exchangers through vortex wirecoil generator variations.

Time-delay-aware power coordinated control approach for series hybrid electric vehicles

Series hybrid electric vehicles (S-HEVs) have attracted extensive attention thanks to the simple structure and excellent efficiency, which power transfer rely on high-voltage microgrids consisting of engine-generator set, battery, motor, and other actuators. However, with possible communication time delays (CTDs), the interaction between the actuators and control unit in terms of state and control command is desynchronize, resulting in the unstable operation of S-HEVs, such as engine stalls and bus voltage jitter. This presents a great challenge to the power coordinated control approach (PCCA) design that controls different actuators. Motivated by the mentioned above, this paper presents a time-delay-aware PCCA to achieve the stable driving of S-HEVs. First, an integrated powertrain control-oriented model that incorporates communication is built. Second, an increment model predictive control method (MPC) is designed. And then by leveraging the Lyapunov-Razumikhin stability theorem, a stability condition is derived by defining a parameterization weight matrix and known upper bound of CTDs, reducing the complexity of parameter designing. Additionally, an adaptive mechanism is designed to extend application of the proposed approach in unknown CTDs condition. Finally, the hardware-in-the-loop experiment is performed, and the results demonstrate that the presented approach in the mean and root mean square of the engine speed error and DC-bus voltage error decrease 39.87%, 43.85%, 44.67%, and 79.94% than nominal MPC in one period CTDs condition, respectively. And for the larger CTDs condition, the proposed method also shows efficient robustness. These substantiate that the proposed control method effectively improves vehicle running stability when encountering CTDs.

High Temperature Biomass Fired Stirling Engine (HTBS)

Biomass is an important resource for the utilisation of renewable energy not only in Germany, but in many other countries. Being sufficient to provide base load it is capable to stabilise electricity grids besides contributing to climate change precaution. Additionally it is essential that the applications for heat, power and fuel feature high conversion efficiencies. There fore the on-site generation of electricity is a crucial contribution to renewable energy supply, especially in real small-scale applications. The project “HTBioStir” - development of a high temperature heat exchanger for the coupling of biomass boiler and Stirling engine - is designed and realized as a fundamental research project focusing on important mechanisms of heat transfer. The basic approach to generate electricity and heat implies the transfer of enthalpy on high temperature levels from the flue gases of a wood chip operated fire tube boiler to the working fluid helium through the heater head of a Stirling engine generator set. Using an indirect heat transfer mechanism, air as the carrier, an innovative heat exchanger with surface structured industrial power tube bundle and upstream a similar recuperative air-preheater by which an α-type SOLO 2V is operated to gene rate electricity. The leaving air at a much lower temperature level serves then as preheated oxidant in the furnace, while the flue gases produce hot water in the boiler. At present measure ment campaigns were carried out to establish energy and mass balances of the fire tube boiler as well as the Stirling engine.

Technical aspects of the selection of an engine-generator set for a dual-drive locomotive

The use of dual-drive rolling stock is a relatively new solution on the railway market. Vehicle with such type of powertrain is more versatile because it combines the advantages of using diesel vehicles and electric vehicles that consume energy from overhead electric traction. The concept of using such vehicles is highly innovative and has many advantages, however, the design and construction process is more complicated and requires more work than in the case of conventional systems. This article presents the methodology and process of selecting an engine-generator set for a dual-drive locomotive. Indicators and procedures, crucial in the process of selecting a dual-drive system for a locomotive, were described and evaluated. All above mentioned in the work were used during the real design process of a fully Polish locomotive with both diesel and electric drives. The locomotive in Diesel mode was to have an output power of circa 1,560 kW for cargo transport. Calculations for the locomotive's power balance are included, showing power losses in the system and for locomotive's own needs. It has been shown that in cargo transport 77% of the maximum engine power is used as tractive power, and in passenger transport 58.6%.

Energy Management System in Smart Micro-Grid

This paper focuses on discussing an energy management system (EMS) for a smart microgrid integrating multiple renewable sources. The task of the EMS is to efficiently balance power generation and consumption by controlling various energy sources, including photovoltaic systems, energy storage units, engine generator set and the utility grid. An EMS optimizes power flow between the microgrid components and keeps the micro-grid stable, by using different control strategies. In this microgrid, the PV system serves as the primary energy source, while the other sources of electrical energy act as backups. The energy management system prioritizes supplying load demand from either the PV system or the other sources, with load shedding during peak hours if the supplied energy is insufficient. The approaches based on StateMachine and StateFlow are discussed in this paper for enhancing the energy management system's performance.

Experimental Assessment of Genset Performance for PCCI-DI Combustion Engine

Applying the PCCI-DI combustion concept which can yield low emissions is tried for vehicular applications. However, much work has not been carried out on the genset engine which is a constant speed application. The PCCI can be achieved by various methods like port injection, late direct injection, early direct injection, and multiple direct injections to name a few. However in this case, it is achieved using the port injection. The two different port injection quantities are tried out. The first is with 3 ms pulse and the other with 5 ms pulse of port injection. In this study, PCCI-DI engine is assembled with the alternator to form a genset. The genset is tested for assessing its behavior in real-world conditions. The main trials to simulate the realworld condition are the load throw-on and load throw-off trials. The extreme case of these trials is to load the engine from no load to full load during the throw-on trials and reverse in throw-off trials. The results indicate the best performance in the case of pure DI combustion. With the use of port injection, the genset performance decorates. This is due to the fuel being injected in the port and it takes a finite time for the reaction to sudden loading and de-loading of the engine. The higher the amount of port fuel injection the higher the deterioration in response is observed. The result gives the actual performance and the response in all three combustion configurations. All three cases met the ISO 8528-5 G3 class requirements.

흡입구와 유동각의 변경에 따른 디젤발전기 인클로저의 최적화 연구

흡입구와 유동각의 변경에 따른 디젤발전기 인클로저의 최적화 연구

Experimental investigation to evaluate the performance profile of a small-scale standalone concentrated solar parabolic dish Stirling system

In this study, a small-scale solar parabolic dish Stirling system (SPDSS) is designed, developed and experimentally operated to generate electricity. The developed system is composed of a solar concentrator, a Stirling engine-generator set, and dual-axis tracking mechanism. The locally assembled Stirling engine is air-filled, double-acting gamma, with a nominal power rating of 40 W. There are six essential output parameters including engine displacer temperature, average engine speed, generator terminal voltage, load current, electrical power and overall efficiency of the system, which have been measured experimentally to assess global performance of the system. The experimental results revealed that the developed system could yield a maximum engine displacer temperature of 275°C, average engine speed of 261 RPM, peak generator no-load terminal voltage of 31.3 V, maximum load current of 2.67 amps, maximum electrical power of 17 W and overall efficiency of 3.4%. The experimental results, for the purpose of validation, have also been compared with simulation results and found in good agreement.

Multiobjective Intelligent Energy Management for Hybrid Electric Vehicles Based on Multiagent Reinforcement Learning

This paper proposes a multi-objective energy management strategy (EMS) based on multi-agent reinforcement learning (MARL) for a hybrid electric vehicle equipped with an engine-generator set (EGS) and a hybrid energy storage system (HESS, consisting of a battery and ultracapacitor). First, besides improving fuel economy, maintaining battery state of charge (SOC), reducing battery degradation and constraint on ultracapacitor SOC are also taken into consideration, formulating multi-objective energy management. Then, the problem is solved using MARL which combines game theory and reinforcement learning. In this framework, EGS and HESS are viewed as two intelligent agents respectively, and their interactions are described as a general-sum stochastic game. Following the principle of MARL, the two agents can learn the optimal control policy which guarantees the Nash equilibrium of multiple objectives, thus achieving a satisfactory balance among them. In the simulation, the MARL-based EMS is compared with single-agent reinforcement learning (SARL) which ignores the relations of different agents, and dynamic programming (DP) which integrates various targets into a single cost function with weight coefficients. The simulation results verify the superiority of the proposed EMS in optimizing multiple objectives.

Control design-oriented modeling and µ-synthesis-based robust multivariate control of a turbocharged natural gas genset engine

This paper describes a comprehensive framework for the development and validation of a model-based robust multivariate controller, which is used to regulate the gas exchange processes of an advanced turbocharged natural gas genset engine. The natural gas genset engine involved in this study features a multi-input and multi-output structure and is highly nonlinear, making it a challenge for which to design a controller. A control design-oriented model describing the dynamics of the studied engine is first developed and validated, using modeling techniques commonly employed for modeling of turbocharged engines. A novel robust model-based multivariate controller is then synthesized to incorporate the significant coupling between the engine actuators (throttle valve, bypass valve, and fuel valve) and the desired control objectives (engine speed, throttle differential pressure, and air-to-fuel ratio). To verify the effectiveness of the synthesized controller, it is compared to a benchmark production controller using an experimentally-validated simulation model. Simulation results indicate the merits of the synthesized robust multivariate controller in terms of better tracking performance (robust multivariate controller reduces steady-state error of engine speed, throttle differential pressure, and AFR at most by 100%, 58.9%, and 100% respectively, compared to benchmark production controller), faster transient response (robust multivariate controller reduces settling time of engine speed, throttle differential pressure, and AFR at most by 74.5%, 47.8%, and 71.2% respectively, compared to the benchmark production controller), and finer coordination among multiple interacted actuators when faced with multifacted control objectives.

Influence of aluminum oxide nanoparticles addition with diesel fuel on emissions and performance of engine generator set using response surface methodology

The present study investigates the effect of small-sized aluminum oxide nanoparticle concentration and engine load on the emissions and performance parameters of a single-cylinder diesel engine connected to an AC generator. Response surface methodology (RSM) based on central composite design (CCD) was employed to simulate the design of the experiment. The ultrasonication-assisted preparation method has been used to mix the diesel (D) with two different concentrations of aluminum oxide, namely 50 ppm and 100 ppm. The tested fuels are called D, (D + 50AL2O3), and (D + 100AL2O3) accordingly. The tests were carried out at various engine loads of 0.9, 1.8, and 2.7 kW at a rated speed of 3000 rpm without engine modification. The evaluated characteristics were nitrogen oxide (NOx), hydrocarbons (HC), carbon dioxide (CO2), carbon monoxide (CO), brake-specific fuel consumption (BSFC), brake thermal efficiency (BTE), and exhaust gas temperature (EGT). According to the analysis of variance (ANOVA) results, the experimental outputs were found to be in good agreement with that of the predicted. Furthermore, the results revealed that the tested fuel D + 50Al2O3 favorably reduced the harmful emissions at all loads investigated. For instance, NOx, HC, and CO emissions decreased by 32.28%, 21.74%, and 20%, respectively. In addition, the BTE improved by 4.91% at 2.7 kW compared to pure diesel. The aforementioned potential results revealed that aluminum oxide nanoparticles could effectively reduce emissions parameters and enhance engine performance. Furthermore, the small nanoparticle size of 11 nm and low concentration of only 50 ppm (mixed with diesel) revealed positive technical, environmental, and economic perspectives on the applicability of the proposed nanofuel.

PCCI-DI Combustion Simulation for Significant Reduction of NOX and PM for GENSET Engine

Improvements in engine combustion are required due to the stringent pollution norms. This can be achieved either by making improvements in the combustion or by equipping after-treatment devices to control engine emission levels. PCCI is one of the popular techniques used to enhance the combustion. In this work, Diesel-RK software is used for the simulation. The main and pre-injection timings are altered to give the benefits in power and emissions. Based on a literature survey, the fourth and fifth modes are finalized for PCCI combustion simulation. The amount of total fuel injected was kept the same to compare the performances in DI and PCCI modes. The simulation results show the reduction in soot (PM) and NOx simultaneously with the help of PCCI concept at lower BMEP levels. The results show a decrease in PM by up to 26%, a reduction in NOx by up to 30% and an increase in power by 2%.

Characterisation of particulates and trace metals emitted by a dimethyl ether-fuelled genset engine prototype

Diesel-fuelled CI engines are the primary sources of particulate matter (PM) emissions which harm human health and the urban environment. Elevated PM emission levels can cause respiratory diseases and deteriorate urban air quality and atmospheric visibility. DME, a carbon-neutral and oxygenated fuel, is fast merging as a strong alternative to diesel to reduce PM emissions. The absence of a direct carbon-carbon bond in the molecular structure of DME improves combustion and reduces PM emissions to negligible levels. DME and baseline diesel are experimentally evaluated in a single-cylinder CI genset engine prototype to find the particulate number-size, surface area-size and mass-size distributions. In addition, total particulate number (TPN), total particulate mass (TPM), count mean diameter (CMD) of particulates, particulate morphology and trace metals were assessed. DME genset engine emitted higher numbers of smaller diameter particles, with lower surface area and mass distribution than baseline diesel. For DME, total PM mass emission and CMD of particulates were lower due to particles being finer. Morphological analysis of particulates showed the presence of larger particles from diesel and less bunched agglomerates of nucleation mode particles from the DME genset engine prototype. The trace metal analysis of particulates showed higher presence of trace metals such as Si, Ca, and Na in DME-fuelled engine than in diesel. As an alternative to diesel, DME can reduce PM emissions from genset engines, significantly enhance urban air quality, and minimise the threat of respiratory diseases.

Experimental assessment of a pilot-scale gasification plant fueled with olive pomace pellets for combined power, heat and biochar production

This research work examines the performance of an experimental gasification plant fueled with exhausted olive pomace pellets for the concurrent production of electricity, heat and biochar in the olive oil industry. The gasification plant consists of an air-blown downdraft fixed-bed gasifier that generates a lean fuel gas, termed producer gas, in a self-sustaining autothermal process. After conditioning of the producer gas in a cooling and cleaning unit, a four-stroke spark-ignition engine coupled to an electric generator is eventually used as power generation unit. An extensive experimental assessment of this facility was performed under partial and nominal load operation and was supplemented by a physicochemical analysis of the carbonaceous solid material discharged from the gasifier. The mass and energy balances of the gasification plant were calculated, including the carbon conversion efficiency and diverse energy conversion efficiencies. The results revealed an overall stable operation of the gasification plant in terms of composition and heating value of the producer gas and cogenerative production of electricity and heat in the engine–generator set. Under nominal operating conditions, the net electrical efficiency of the gasification plant was 12%–13%, with an average carbon conversion efficiency of the biomass feedstock into producer gas just above 80% and an average cold gas efficiency close to 70%.

Efficiency enhancement strategy implementation in hybrid electric vehicles using sliding mode control

Introduction. Hybrid electric vehicles are offering the most economically viable choices in today's automotive industry, providing best solutions for a very high fuel economy and low rate of emissions. The rapid progress and development of this industry has prompted progress of human beings from primitive level to a very high industrial society where mobility used to be a fundamental need. However, the use of large number of automobiles is causing serious damage to our environment and human life. At present most of the vehicles are relying on burning of hydrocarbons in order to achieve power of propulsion to drive wheels. Therefore, there is a need to employ clean and efficient vehicles like hybrid electric vehicles. Unfortunately, earlier control strategies of series hybrid electric vehicle fail to include load disturbances during the vehicle operation and some of the variations of the nonlinear parameters (e.g. stator’s leakage inductance, resistance of winding etc.). The novelty of the proposed work is based on designing and implementing two robust sliding mode controllers (SMCs) on series hybrid electric vehicle to improve efficiency in terms of both speed and torque respectively. The basic idea is to let the engine operate only when necessary keeping in view the state of charge of battery. Purpose. In proposed scheme, both performance of engine and generator is being controlled, one sliding mode controllers is controlling engine speed and the other one is controlling generator torque, and results are then compared using 1-SMC and 2-SMC’s. Method. The series hybrid electric vehicle powertrain considered in this work consists of a battery bank and an engine-generator set which is referred to as the auxiliary power unit, traction motor, and power electronic circuits to drive the generator and traction motor. The general strategy is based on the operation of the engine in its optimal efficiency region by considering the battery state of charge. Results .Mathematical models of engine and generator were taken into consideration in order to design sliding mode controllers both for engine speed and generator torque control. Vehicle was being tested on standard cycle. Results proved that, instead of using only one controller for engine speed, much better results are achieved by simultaneously using two sliding mode controllers, one controlling engine speed and other controlling generator torque.

Effect of Diesterol blends on the noise vibration and harshness of a Genset engine

The present investigations deal with the combined effect of Diesterol blends (B20D75E5, B20D70E10, and B20D65E15) on the performance, combustion, noise, and vibration characteristics of a compression ignition Genset engine. Studies were carried out to make the fuel blend homogeneous and stable as ethanol is immiscible in diesel/biodiesel due to its chemical structure. It is found that the Diesterol blend becomes stable when biodiesel is used as a bonding agent between ethanol and diesel. However, the higher concentration of ethanol has stronger bonding, which resulted in poor stability. The stable blends were used to study the performance characteristics of the Genset engine. The results showed that the brake thermal efficiency increased by 10.4% by adding 5% ethanol in diesel–biodiesel compared to the 15% ethanol in diesel–biodiesel blends. The brake-specific fuel consumption was found to increase by 10% due to the decrease in calorific value with the addition of ethanol. The peak value of the in-cylinder pressure gradually increases up to 10% ethanol share and further addition in the fuel blend decreases the cylinder peak pressure, which may be due to a reduction in the lower calorific value of the blended fuel when compared to conventional diesel. The water content in the blends reduced the combustion activity and caused a slight increase in vibration due to the increased instant heat release rate in 10% and 15% ethanol share. The maximum vibration reduction was observed for the 5% ethanol blend by 1.83%. On the other hand, adding 15% ethanol decreased the engine noise by 2.7% compared to the 5% ethanol blend.