Reduction In Fuel Consumption Research Articles

Influence of the Reward Function on the Selection of Reinforcement Learning Agents for Hybrid Electric Vehicles Real-Time Control

The real-time control optimization of electrified vehicles is one of the most demanding tasks to be faced in the innovation progress of low-emissions mobility. Intelligent energy management systems represent interesting solutions to solve complex control problems, such as the maximization of the fuel economy of hybrid electric vehicles. In the recent years, reinforcement-learning-based controllers have been shown to outperform well-established real-time strategies for specific applications. Nevertheless, the effects produced by variation in the reward function have not been thoroughly analyzed and the potential of the adoption of a given RL agent under different testing conditions is still to be assessed. In the present paper, the performance of different agents, i.e., Q-learning, deep Q-Network and double deep Q-Network, are investigated considering a full hybrid electric vehicle throughout multiple driving missions and introducing two distinct reward functions. The first function aims at guaranteeing a charge-sustaining policy whilst reducing the fuel consumption (FC) as much as possible; the second function in turn aims at minimizing the fuel consumption whilst ensuring an acceptable battery state of charge (SOC) by the end of the mission. The novelty brought by the results of this paper lies in the demonstration of a non-trivial incapability of DQN and DDQN to outperform traditional Q-learning when a SOC-oriented reward is considered. On the contrary, optimal fuel consumption reductions are attained by DQN and DDQN when more complex FC-oriented minimization is deployed. Such an important outcome is particularly evident when the RL agents are trained on regulatory driving cycles and tested on unknown real-world driving missions.

Combustion and Exhaust Gas Characteristics of Residual Oil Mixed with Air-Fine Mixture in Medium-Speed Marine Diesel Engine

In the marine engineering field, research has been conducted to reduce fuel consumption and emissions of harmful exhaust gases from medium- and low-speed diesel engines by improving supercharging performance, scavenging efficiency, and introducing electronic control technology, etc., and these technologies have been put to practical use. However, most of these technologies have been applied to newly constructed vessels, and oxygen-containing fuels such as water-emulsion fuel and DME fuel have not yet been put to practical use. In this study, the effects of heating high viscosity residual oil and mixing air into the fuel as fine bubbles on the combustion and exhaust characteristics of the fuel were investigated using a practical medium-speed marine diesel engine. As a result, the fuel consumption reduction effect was confirmed when fine air bubbles were mixed in heated residual oil, as is the case with them being blended into marine diesel oil. In particular, the maximum reduction was 7% at 75% load and 0.2L/min air volume, and the average reduction was 3.2% at 75% load. In terms of the exhaust gas characteristics of the fuel, no significant reduction in NOx was observed when microbubbles were mixed, but smoke values were reduced by up to 33%.

A fuel consumption model for mixed traffic flow in multiple connected and autonomous scenarios

AbstractThe potential increase/decrease in energy consumption of traffic operation modes is a hot topic in the studies of connected and autonomous vehicles (CAVs), but there are few theoretical studies on the fuel consumption of human driving vehicles (HDVs) and CAV mixed platoon as a result of limited data. Based on the power distribution of light‐duty vehicles, this study developed a fuel consumption model for HDV and CAV mixed platoons by theoretical hypothesis considering the oscillation along with the platoon. Firstly, a vehicle‐specific power (VSP) distribution conforming to normal distribution is constructed with hypothesis‐based VSP standard deviation and constant VSP average value at each speed bin under different platoon arrangement conditions. Then, the fuel factors (mL/km) are calculated by weighted fuel rate (mL/s) according to the VSP distribution. Finally, a library of fuel consumption values for multiple penetration rates, platoon intensities, and speeds was established. In the case, at a speed of 30 km/h, the fuel consumption in the CAV group was reduced by 0.8–5%, 1.9–12.5%, 8.6–12%, and 12.4%, respectively, at the penetration rate of 20%, 50%, 80%, and 100%, compared to the HDV group. The fuel consumption reduction effect of CAV was negatively correlated with the speed.

Co-Optimization of Design and Control of Energy Efficient Hybrid Electric Vehicles Using Coordination Schemes

AbstractDesign and control co-optimization studies for hybrid vehicles have been proposed in the past. However, such works suffer from difficulties arising due to (a) diverse real- and integer-valued variables, (b) complex nonlinear powertrain dynamics and design interconnections, (c) conflicting objective functions with path constraints, and (d) high computational resources requirements. To meet these challenges, this study presents an efficient co-optimization framework for hybrid electric vehicles (HEVs) which is built using existing algorithms and coordination schemes. Particular emphasis is given to the simultaneous scheme and the decomposition-based scheme. The decomposition-based scheme with the problem decomposition proposed in this work can efficiently handle multitime scale state variables and both integer- and real-valued design and control optimization variables. This is demonstrated by solving the mixed-integer optimal design and control problem of a series hybrid vehicle over a 1-h long drive cycle with time discretization of 1 s. The problem complexity is elevated by using an increasing number of state variables (including battery state of charge, battery energy, and after-treatment system temperature), control variables (such as the engine power and engine on/off), and design parameters (such as the number of battery cells and the type and size of the engine). In addition, a multi-objective cost function is used to find a tradeoff solution between fuel consumption and emissions minimization. The results show that in terms of optimality of the solution, the decomposition-based scheme is comparable with the simultaneous but can give a 14% improvement in computational performance. The effectiveness of the proposed framework is demonstrated by comparing the co-optimization results against a baseline case in which only the optimal control problem is solved. The co-optimized solution yields up to 3.7% average genset efficiency improvement and a fuel consumption reduction to 1.6 kg from 2.5 kg, which is further reduced to 1.5 kg by adding the engine on-off control. Finally, a decision matrix is developed to provide guidance on the selection of the optimization algorithm and coordination scheme for any problem at hand.

THERMODYNAMIC AND ECONOMIC ANALYSIS OF A BIOGAS -FUELED MICRO GAS TURBINE WITH COMPRESSOR PHOTOVOLTAIC DRIVE

The increase in global and Brazilian energy demand plus environmental concern due to pollutant emissions are motivating investigation and development of sustainable energy sources and the interaction between them. In this context, electricity generation through solar and solid urban waste energy harnessing has become an effective option for Brazilian energy matrix diversification. Therefore, in order to ratify this trend, a thermodynamic analysis of a 200 kWe micro gas turbine using biogas as fuel and photovoltaic panels to drive compressor shaft is presented in this paper. In terms of methodology, Engineering Equation Solver (EES) Demo was used to run a classic steady state thermodynamic model and a parametric analysis to evaluate MGT performance with a PV system integrated in order to assess specific fuel consumption reduction (SFC) at Belo Horizonte, Minas Gerais, Brazil, operation. Radiasol 2 was the software used to acquire solar insolation data over the year. The fuel economy occurs since power produced in turbine does not need to be discounted to drive compressor shaft during periods when solar insolation is present or when energy generation during the day is sufficient to be credited as Brazilian legislation allows grid integrated systems. In cases that solar energy is not enough or absent, a transmission mechanism similar to a clutch should be considered as well as proposed in other studies to guarantee uninterrupted system operation. Futhermore, an economic analysis was performed to evaluate kWh cost for conventional and hybrid systems. Interest rate, inflation, construction period and amortization period are important parameters taken into account to calculated annuity factor that must be evaluated to predict energy cost. The thermodynamic results showed that SFC=0,718 kg/kWh for conventional operation and SFC=0,266 kg/kWh for hybrid operation for the best operating compressor pressures ratio. The economic results showed that payback time for MGT and MGT with compressor photovoltaic drive are lower than lifetime systems, and hybrid MGT electricity cost is lower when compared to paid ones nowadays.

The low power diesel-generator unit with electronically controlled fuel injection

BACKGROUND: Diesel engines, used in generator units, primarily operate in variable loading conditions. Therefore, their technical and economic performance generally deteriorate when the load decreases. It arises from the diesel engine fuel system feature, where pressure and quantity of the fuel, injected into a cylinder, reduces with the load decreasing. As a result, the injection becomes sluggish, the quality of mixing process and combustion becomes worse.
 AIMS: Improvement of effective indicators of the diesel-generator units with electronically controlled fuel injection.
 METHODS: Adjustment of operation modes of the diesel engine of the electrical power unit carried out with use of electronically controlled Denso solenoid, connected to the high-pressure fuel pump via an adapter.
 RESULTS: Results of the motor testing of the low power diesel-generator unit with electronically controlled fuel feed system are described in the article. The oscillograph charts of valve displacement and solenoid magnet winding current, presented in the article, confirm its operation efficiency. Sharp decrease in boost current at the stage of valve lift can be explained by onset of back EMF. Stable solenoid operation at diesel operation velocity of 30003100 min-1 is achieved by means of boost impulse supply to its winding. The boost impulse is supplied from a voltage upconverter and generated by discharge of preliminary charged booster capacitor.
 CONCLUSIONS: Separated fuel feed adjustment in each high-pressure pump section made possible to reduce intersectional fuel feed irregularity to zero. Significant fuel consumption reduction was revealed with the motor testing of the low power diesel-generator unit with electronically controlled fuel feed system (the reduction reaches 10% on low loading operation modes). As mentioned by authors, transition to electronic control of operation modes of diesel engines of autonomous electrical power units does not require major engine design change only to dismantle a mechanical controller and to set an adapter with electronically controlled bypass valve at a section of the high-pressure fuel pump. Electronic control unit supplies current to the valve. For autonomous electrical power units, transition to this control method can be done in typical repair workshop conditions, and an update of one unit (e.g. the KIPOR KDE19AE3) costs 13 950 rubles. By doing so, one electrical power unit may save up to 1191 liters of fuel and more than 63.96 thousands rubles at a cost of 53.7 rubles per liter.

The Use of Hydrogen for Traction in Freight Transport: Estimating the Reduction in Fuel Consumption and Emissions in a Regional Context

The Italian National Recovery and Resilience Plan (NRRP) includes, among other measures, investments in hydrogen vehicle refuelling stations, intending to promote the use of fuel cell electric vehicles (FCEVs) for long-haul freight transport. This paper evaluates the impact that this action could have on CO2 emissions and fuel consumption, focusing on a case study of the Campania region. The proposed approach, which can also be transferred to other geographical contexts, requires the implementation of a freight road transport simulation model; this model is based on the construction of a supply model, the estimation of road freight demand, and an assignment procedure for computing traffic flows. This study covers the period from 2025 to 2040, according to the forecasts of the NRRP and some assumptions on the action effects; moreover, it is assumed that hydrogen is entirely produced from renewable sources (green hydrogen). The key findings from three different scenarios show that savings between 423,832 and 778,538 tonnes of CO2, and between 144 and 264 million litres of diesel could be obtained.

Povećanje efikasnosti guseničnog vozila optimizacijom prenosnih odnosa i strategije promene stepena prenosa

Introduction/purpose: Tracked vehicles play a vital role across various domains, from military operations to construction and agriculture. This study focuses on improving the efficiency of tracked vehicles by optimizing both gear ratios and gear-shifting strategies while preserving other performance aspects. Methods: The optimization process involves a genetic algorithm for determining optimal gear ratios, considering performance constraints. Furthermore, the paper introduces a gear-shifting optimization algorithm aimed at enhancing fuel economy to the maximum, while allowing for a valid comparison between two sets of gear ratios. Results: Optimizing gear ratios leads to substantial reductions in fuel consumption, as the engine operates within more efficient regions. Additionally, the optimized gear-shifting strategy further enhances efficiency, resulting in a fuel consumption reduction exceeding 12%, when combined with the optimized gear ratios. Conclusions: This paper offers a direct and robust approach for optimizing powertrain gear ratios and gear-shifting strategies in tracked vehicles. The results demonstrate significant improvements in fuel efficiency without compromising other critical vehicle performance parameters.

Research on the Prediction of Dual Credit Situation of Passenger Car Enterprises Based on Multiple Factors

Currently, China's new energy vehicle industry has entered a new stage of rapid development on a large scale. In order to ensure the advancement and innovation of the "Dual Credit Policy", the key assessment indicators such as the requirement ratio of NEV credits are in an urgent need to be made stricter. The strictness of the key assessment indicators is closely related to the development of China's energy-saving and new energy vehicle industry. However, currently, there is still a lack of systematic prediction methods for the mediumand long-term dual credit situation of passenger car enterprises in China. In this paper, a database for the prediction of the dual credit situation of passenger car enterprises is constructed using a combined "top-down" and "bottom-up" approach. Specifically, the NEV penetration rate in the industry is quantitatively evaluated using a multivariate regression model under the assumption of a discrete choice model, with the consideration of constraints such as resource endowment, charging infrastructure, and transformation costs of enterprises. The potential for fuel consumption reduction in conventional energy passenger cars of enterprises is determined using an optimal energy-saving technology choice model, which provides the annual decline in fuel consumption for enterprises. The calculation of the credits for NEV models and energy consumption is estimated using the rules of policy development and a simple conversion method. In order to make the prediction database more applicable to the real-world scenarios, it is also embedded with out-of-cycle energy-saving technologies, and research advancements in the latest policies and standards. This prediction database will greatly support the evaluation of the effectiveness of the "Dual Credit Policy" in the medium and long run, and assist enterprises in formulating credit compliance strategies.

Reduction of Fuel Consumption Using HHO Cell on Gasoline Engine

Hydrogen as clean energy will certainly allow a significant reduction in the problems associated with pollution. Hydrogen is a source of future energy because it represents one of the forms of energy that is less polluting to the environment. In this paper, the main objectives of this research are to increase the efficiency of the gasoline engine using an HHO generator by decreasing fuel consumption and CO2 emissions. It was designed hydrogen fuel cell and attached to a motor Hyundai Sonata 2009 with 2000cc. According to the results, integrating a HHO cell into the engine, it was reduced fuel consumption for a motor vehicle in the city by up to 31.4 %, and 32.9 % for the combined drive between the city and highways. The use of cut-outs showed no increase in ampere consumption and no increase in temperature on the HHO cell.

Green Technology Adoption and Fleet Deployment for New and Aged Ships Considering Maritime Decarbonization

Maritime decarbonization and strict international regulations have forced liner companies to find new solutions for reducing fuel consumption and greenhouse gas emissions in recent years. Green technology is regarded as one of the most promising alternatives to achieve environmental benefits despite its high initial investment costs. Therefore, a scientific method is required to assess the possibility of green technology adoption for liner companies. This study formulates a mixed-integer nonlinear programming model to determine whether to retrofit their ship fleets with green technology and how to deploy ships while taking maritime decarbonization into account. To convert the nonlinear model into a linear model that can be solved directly by off-the-shelf solvers, several linearization techniques are applied in this study. Sensitivity analyses involving the influences of the initial investment cost, fuel consumption reduction rate of green technology, unit fuel cost, and fixed operating cost of a ship on operation decisions are conducted. Green technology may become more competitive when modern technology development makes it efficient and economical. As fuel and fixed operating costs increase, more ships retrofitted with green technology will be deployed on all shipping routes.

A Review of Renewable Energy and Storage Technologies for Automotive Applications

Review A Review of Renewable Energy and Storage Technologies for Automotive Applications Xiangnan Yu 1, Yuhai Jin 1, Heli Liu 1, Arnav Rai 1, Michelle Kostin 1, Dimitrios Chantzis 1, Denis J. Politis 2, and Liliang Wang 1,* 1 Department of Mechanical Engineering, Imperial College London, London SW7 2AZ, UK 2 Department of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia, 1678, Cyprus * Correspondence: liliang.wang@imperial.ac.uk Received: 29 September 2022 Accepted: 9 November 2022 Published: 25 December 2022 Abstract: Transportation, as the backbone of the modern economy, continues to be a significant contributing factor to environmental pollution and poor air quality. Whilst numerous efforts have been made to address energy consumption and emissions through the manufacturing and end use stages, the use of fossil fuels continues to grow at an exponential rate. A key target area to assist with fuel consumption reduction targets is the implementation of renewable energy combined with energy storage technologies. The aim of this review is to investigate various means of production for renewable energy and energy storage technologies with the specific focus on the automotive industry.

Building a Digital Twin Simulator Checking the Effectiveness of TEG-ICE Integration in Reducing Fuel Consumption Using Spatiotemporal Thermal Filming Handled by Neural Network Technique

Scholars seek to recycle wasted energy to produce electricity by integrating thermoelectric generators (TEGs) with internal combustion engines (ICE), which rely on the electrical conductivity, β, of the thermal conductor strips. The TEG legs are alloyed from iron, aluminum and copper in a strip shape with specific characteristics that guarantee maximum thermo-electric transformation, which has fluctuated between a uniform, Gaussian, and exponential distribution according to the structure of the alloy. The ICE exhaust and intake gates were chosen as the TEG sides. The digital simulator twin model checks the integration efficiency through two sequential stages, beginning with recording the causes of thermal conductivity failure via filming and extracting their data by neural network procedures in the feed of the second stage, which reveal that the cracks are a major obstacle in reducing the TEG-generated power. Therefore, the interest of the second stage is predicting the cracks’ positions, Pi,j, and their intensity, QP, based on the ant colony algorithm which recruits imaging data (STTF-NN-ACO) to install the thermal conductors far away from the cracks’ positions. The proposed metaheuristic (STTF-NN-ACO) verification shows superiority in the prediction over [Mat-ACO] by 8.2% and boosts the TEGs’ efficiency by 32.21%. Moreover, increasing the total generated power by 12.15% and working hours of TEG by 20.39%, reflects reduced fuel consumption by up to 19.63%.

End-to-End Deep Neural Network Based Nonlinear Model Predictive Control: Experimental Implementation on Diesel Engine Emission Control

In this paper, a deep neural network (DNN)-based nonlinear model predictive controller (NMPC) is demonstrated using real-time experimental implementation. First, the emissions and performance of a 4.5-liter 4-cylinder Cummins diesel engine are modeled using a DNN model with seven hidden layers and 24,148 learnable parameters created by stacking six Fully Connected layers with one long-short term memory (LSTM) layer. This model is then implemented as the plant model in an NMPC. For real-time implementation of the LSTM-NMPC, an open-source package acados with the quadratic programming solver HPIPM (High-Performance Interior-Point Method) is employed. This helps LSTM-NMPC run in real time with an average turnaround time of 62.3 milliseconds. For real-time controller prototyping, a dSPACE MicroAutoBox II rapid prototyping system is used. A Field-Programmable Gate Array is employed to calculate the in-cylinder pressure-based combustion metrics online in real time. The developed controller was tested for both step and smooth load reference changes, which showed accurate tracking performance while enforcing all input and output constraints. To assess the robustness of the controller to data outside the training region, the engine speed is varied from 1200 rpm to 1800 rpm. The experimental results illustrate accurate tracking and disturbance rejection for the out-of-training data region. At 5 bar indicated mean effective pressure and a speed of 1200 rpm, the comparison between the Cummins production controller and the proposed LSTM-NMPC showed a 7.9% fuel consumption reduction, while also decreasing both nitrogen oxides (NOx) and Particle Matter (PM) by up to 18.9% and 40.8%.

Study on the control targets and measures for total diesel consumption from mobile sources in Beijing, China

Based on the current air pollution control and CO2 emission reduction policies, this study analyzed the energy structure, number of motor vehicles and nonroad mobile machinery, energy consumption and pollutant emissions in Beijing. Furthermore, the diesel consumption characteristics and challenges for emission reduction in key fields were investigated, such as medium- and heavy-duty diesel trucks, long-distance passenger and tourist diesel vehicles, and nonroad machinery, which are areas with difficult-to-reduce diesel consumption. Control targets and measures for total diesel consumption were also proposed. The results indicated that the higher diesel consumption per unit area in Beijing is related to the larger passenger car and freight truck populations. In recent decades, the number of diesel vehicles has increased, the vehicle type structure has been optimized, the proportion of vehicles with high emission standards has increased, and the absolute pollutant emissions have decreased. Among these, nitrogen oxides (NOx), fine particulate matter (PM2.5) and volatile organic compound (VOC) emissions of different models decreased by 39.5%, 75.3% and 42.8%, respectively, while carbon dioxide (CO2) emissions from diesel combustion decreased by 32%. Moreover, medium and large passenger vehicles, medium- and heavy-duty trucks and construction machinery are the main contributors to diesel consumption. These vehicle types are also difficult to control and reduce, and their replacement by new-energy vehicles is relatively limited. The main control measures for diesel consumption are as follows. First, a green transportation mode can be adopted for goods that can be converted from roads to railways. Second, fuel consumption reduction for nonroad mobile machinery can be realized by tightening fuel consumption limits, setting appropriate maximum retirement life, establishing low- or ultralow-emission zones, and establishing demonstration plots for electric vehicle (EV) substitution for mobile machinery. To improve the air quality and take the lead in carbon neutrality in the future, Beijing must further accelerate the energy structure adjustment and the development of new-energy vehicles in the transportation sector. Carbon neutralization is an important opportunity for diesel consumption reduction, and the synergistic control of atmospheric pollution and carbon emissions from diesel combustion must be strengthened.

Cooling Potential of Ship Engine Intake Air Cooling and Its Realization on the Route Line

A fuel efficiency of a ship engine increases with cooling inlet air. This might be performed by the chillers, which transform the heat of engine exhaust gas and scavenge air for refrigeration. The effect gained due to cooling depends on the intake air temperature drop and the time of engine operation at decreased intake air temperature. Thus, the cooling degree hour (CDH) number, calculated as air temperature depression multiplied by the duration of engine operation at reduced intake air temperature, is used as a primary criterion to estimate the engine fuel efficiency enhancement due to intake air cooling over the ship routes. The engine intake air cooling potential is limited by its value, available according to engine exhaust heat and the efficiency of heat conversion to refrigeration in the chiller, evaluated by the coefficient of performance (COP). Therefore, it should be determined by comparing both the needed and available values of CDH. The ejector chiller (ECh) was chosen for engine exhaust gas heat recovery to refrigeration as the simplest and cheapest, although it has a relatively low COP of about 0.3 to 0.35. However, the ECh generally consists of heat exchanges which are mostly adapted to be placed in free spaces and can be mounted on the transverse and board side bulkheads in the ship engine room. The values of sucked air temperature depression and engine fuel consumption reduction at varying temperatures and humidity of ambient air on the route were evaluated.

Towards Fuel Consumption Reduction Based on the Optimum Contra-Rotating Propeller

This paper presents the effect of selecting a contra-rotating propeller (CRP) for a bulk carrier at the engine operating point with minimum fuel consumption, as well as ensuring the safety of the propeller in terms of cavitation and noise. Using a developed optimization model, the geometry of a CRP was selected for different propeller diameters, the same propeller diameter as that of a fixed pitch propeller (FPP) installed on the bulk carrier, and at 90% of the FPP diameter. Additionally, each case was optimized with both no-cup and heavy-cup configurations. In general, the CRP showed better performance than the FPP in terms of efficiency, cavitation, and fuel economy. At the same time, the level of performance was increased when considering the CRP cupping percentage. It was concluded that the CRP can achieve a gain in fuel economy of up to 6.2% in a no-cup configuration when compared to an FPP, and up to 11.7% with a cupped configuration.

Performance and emission evaluation of CI engine fueled with ethanol diesel emulsion using NiZnFe2O4 nanoparticle additive

Diesel engines are widely used due to their higher thermal efficiency and lower Hydrocarbon (HC) emissions. The price fluctuation of petroleum fuel; the none-renewability and different hazardous emissions from petro-diesel, researchers are searching for a suitable renewable energy source for diesel engine. Ethanol is one of the promising alternative fuels that could be used to power diesel engine. Some of the techniques so far tried are ethanol fumigation, dual injection and blending. The former techniques need different engine modification to enable the additional systems to work on the existing engines. Blending is the best technique to substitute the existing diesel fuel as long as we prepare it as per the current diesel fuel minimum requirement. For this specific case micro emulsion of ethanol in diesel fuel with emulsifier is prepared by using magnetic stirrer and bath type ultrasonicator. Nickel Zinc Iron Oxide (NiZnFe2O4) nanoparticle is added in one of the selected emulsion which is having 10% ethanol in three different dose as additive to see the effect on the performance and emission variation of the emulsion compared with diesel fuel. The performance of the prepared sample fuels are tested on a test rig with single cylinder diesel engine. The emission is measured by using exhaust gas analyzer and smoke opacity meter. The specific fuel consumption, brake torque and brake power of E5 (95% diesel and 5% ethanol), E10 (90% diesel and 10% ethanol) and E15 (85% diesel and 15% ethanol) are evaluated and the result showed 27, 34 and 37% increment in fuel consumption; 15, 5 and 15% reduction in brake torque and the power reduction is 19, 7 and 12% respectively. E10 is selected for further test with addition of the nanoparticle with 25, 50 and 100ppm named as E103N25 (E10 with 25ppm NiZnFe2O4 nanoparticle), E103N50 (E10 with 50ppm NiZnFe2O4 nanoparticle) and E102N100 (E10 with 100 ppm NiZnFe2O4 nanoparticle). The result showed fuel consumption reduction by 16, 27 and 27% torque output increment of 1, 2 and 2% and power output increment of 5, 7 and 7% respectively compared with E10. The emission result revealed that the HC emission reduced by 50, 58 and 71% for E103N25, E103N50 and E103N100 fuel samples respectively, Carbon monoxide (CO) emission reduced by 67, 80 and 81% for E103N25, E103N50 and E103N100 fuel samples respectively. The reduction in smoke emission is reduced by 60, 69 and 61% for E103N25, E103N50 and E103N100 fuel samples respectively. Nitrogen oxide (NOX) and Carbon dioxide (CO2) emissions increased with the amount of nanoparticle added in to the fuel.

A novel degree-hour method for rational design loading

Cooling degree-hours (CDH) received the broadest application in evaluation of the ambient air cooling efficiency in power engineering (engine intake air cooling systems) and air conditioning. The current CDH numbers are defined as a drop in air temperature multiplied by associated time duration of performance and their summarized annual number is used to estimate the annual effect achieved due to sucked air cooling in power plants based on combustion engines (fuel saving, power output increment) and in air conditioning (refrigeration energy generation according to needs). A majority of approaches to designing ambient air cooling systems is proceeding from the cooling capacity of the chillers selected to provide a maximum current or annual CDH number with corresponding maximum current or annual effect (additional energy produced or fuel consumption reduction) in site climate location. But such approaches lead to inevitable oversizing the chillers and cooling systems in the whole. The analysis of intake air cooling efficiency in site varying climatic conditions, accompanied by quite a simple numerical simulation, enabled to reveal the potential of its enhancement and evaluate numerically the results of each step of designing in logical sequence. The new approaches to cooling system rational designing were introduced, that enables to synthesize and substantiate innovative principal decisions to exclude unproductive waste of installed (design) cooling capacity in actual operation. The innovative findings of methodological approaches include the use of the rate of annual CDH number increment as an indicator for selecting the optimum and rational values of design cooling capacity. The optimum cooling capacity corresponds to maximum rate of summarized annual CDH increment and maximum level of thermal loading accordingly, which provides minimum sizes of the chiller. In reality, it is a minimum permissible value of cooling capacity of the chiller installed and the overall ambient air cooling system. The rational cooling capacity, that enables to achieve practically maximum value of annual CDH and avoid chiller oversizing, is determined as the second, local, maximum of the rate in the summarized annual CDH over the range above the first one, global, maximum. A rational design cooling capacity determined by applying the novel methodology allows to decrease the ambient air cooling system sizes by 15 to 20% compared with traditional designing issuing from the peaked thermal load during a year. With this practically a maximum annual effect in fuel saving (energy generation or others) can be achieved too.

Cylinder deactivation strategy for fuel consumption reduction

Cylinder deactivation strategy for fuel consumption reduction