Investigation of the top compression ring power loss and energy consumption for different engine conditions

The paper presents transient thermal-mixed-hydrodynamics of piston compression ring–cylinder liner conjunction for a 4-cylinder 4-stroke gasoline engine during a part of the New European Drive Cycle (NEDC). Analyses are carried out with and without cylinder de-activation technology in order to investigate its effect upon the generated tribological conditions. In particular, the effect of cylinder deactivation upon frictional power loss is studied. The predictions show that overall power losses in the piston–ring cylinder system worsen by as much as 10% because of the increased combustion pressures and liner temperatures in the active cylinders of an engine operating under cylinder deactivation. This finding shows the down-side of this progressively employed technology, which otherwise is effective in terms of combustion efficiency with additional benefits for operation of catalytic converters. The expounded approach has not hitherto been reported in literature.

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Interpretation of Urban Power Consumers Behaviors to Predict Power Loss in Summer

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.a9684.109119 ◽

2019 ◽

Vol 9 (1) ◽

pp. 563-565 ◽

Cited By ~ 1

Keyword(s):

Data Mining ◽

Support Vector Machine ◽

Energy Consumption ◽

High Temperature ◽

Power Loss ◽

Electricity Consumption ◽

Sequential Machine ◽

Support Vector ◽

Data Mining Techniques ◽

Electricity Theft

High Temperature In The Summer Of India. Interpretation Of Electricity Consumption Is Crucial In Summer For Urban Consumers. We Are Focus Here For Only Indian Summer Urban Customers Energy Consumption To Analysis And Predict Behavior Of Electricity Theft. Data Mining Techniques Are Employing To Analyses Indian Summer Urban Customers. Online Sequential Machine And Support Vector Machine Is Used For This Behaviors Classification And Prediction.Mainly we focus Support vector machine to classified consumers and online sequential machine is used to detect and predict consumers behaviors.

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Optimal reconfiguration/distributed generation integration in distribution system using adaptive weighted improved discrete particle swarm optimization

COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering ◽

10.1108/compel-08-2017-0344 ◽

2019 ◽

Vol 38 (1) ◽

pp. 247-262 ◽

Cited By ~ 4

Author(s):

Manikandan Subramaniyan ◽

Sasitharan Subramaniyan ◽

Moorthy Veeraswamy ◽

Viswanatha Rao Jawalkar

Keyword(s):

Particle Swarm Optimization ◽

Energy Consumption ◽

Distributed Generation ◽

Distribution System ◽

Power Loss ◽

Energy Resources ◽

Discrete Particle Swarm Optimization ◽

Swarm Optimization ◽

Content Type ◽

Discrete Particle

Purpose This paper aims to address not only technical and economic challenges in electrical distribution system but also environmental impact and the depletion of conventional energy resources due to rapidly growing economic development, results rising energy consumption. Design/methodology/approach Generally, the network reconfiguration (NR) problem is designed for minimizing power loss. Particularly, it is devised for maximizing power loss reduction by simultaneous NR and distributed generation (DG) placement. A loss sensitivity factor procedure is incorporated in the problem formulation that has identified sensitivity nodes for DG optimally. An adaptive weighted improved discrete particle swarm optimization (AWIDPSO) is proposed for ascertaining a feasible solution. Findings In AWIDPSO, the adaptively varying inertia weight increases the possible solution in the global search space and it has obtained the optimum solution within lesser iteration. Moreover, it has provided a solution for integrating more amount of DG optimally in the existing distribution network (DN). Practical implications The AWIDPSO seems to be a promising optimization tool for optimal DG placement in the existing DN, DG placement after NR and simultaneous NR and DG sizing and placement. Thus, a strategic balance is derived among economic development, energy consumption, environmental impact and depletion of conventional energy resources. Originality/value In this study, a standard 33-bus distribution system has been analyzed for optimal NR in the presence of DG using the developed framework. The power loss in the DN has reduced considerably by indulging a new and innovative approaches and technologies.

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Analysis of the Energy Efficiency Grades Detection for Power Transformers

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.328-330.1003 ◽

2011 ◽

Vol 328-330 ◽

pp. 1003-1007

Author(s):

Jing Dai ◽

Zhi Hua Li

Keyword(s):

Energy Efficiency ◽

Energy Consumption ◽

Power Loss ◽

Power Transmission ◽

Power Transformer ◽

High Energy ◽

Power Transformers ◽

Energy Consuming

There is a lot of power loss in the power transmission, and the loss comes from power transformers contribute very much to this. So the implement of energy efficiency grade for power transformers has great significance to the development of power transformer, which can wash out the high energy-consuming transformer, decrease the power loss, and increase the efficiency of power transmission. The energy consumption of transformer consists of no load loss and load loss. In this test, I analyze the experiments for no load loss and load loss with the “Minimum allowable values of energy efficiency and energy efficiency grades for power transformers”, ascertaining the transformer’s efficiency grade.

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Energy modeling and a method for reducing energy loss due to cutting load during machining operations

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture ◽

10.1177/0954405418769922 ◽

2018 ◽

Vol 233 (3) ◽

pp. 699-710 ◽

Cited By ~ 11

Author(s):

Jingxiang Lv ◽

Tao Peng ◽

Renzhong Tang

Keyword(s):

Energy Consumption ◽

Power Consumption ◽

Energy Loss ◽

Power Loss ◽

Numerical Control ◽

Mechanical Transmission ◽

Significant Saving ◽

Cutting Power ◽

Machining Operations ◽

Reducing Energy

In a typical part manufacturing system, machining operations represent a major proportion of the total energy consumption. The energy consumption (in the form of electricity power) of a machining operation can be divided into four types, that is, standby power, operational power, cutting power and power loss due to cutting load. Power loss due to cutting load includes the power loss caused by the friction of mechanical transmission and the power lost in the motor when the cutting load is applied to the spindle system. While the first three types of power consumption have been studied intensively by previous researchers, the power loss due to cutting load, which accounts for up to 20% of the cutting power consumption during machining operations, has received relatively less attention. This article proposes a novel model to characterize power loss due to cutting load, in which the power lost in the mechanical transmission and in the spindle motor are analyzed and modeled separately. Cutting tests have been carried out to validate the proposed model using two numerical control lathe machines. And a method has been developed for reducing energy loss caused by cutting load, which includes cutting force prediction, power loss due to cutting load prediction and decision making. The method was evaluated through its application in the process design for a shaft part, and the results show a significant saving of up to 70.8% of energy loss caused by cutting load.

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