A Hadoop-Based Fuel Consumption Prediction Method for Petroleum Transportation Vehicles

Abstract

The invention relates to a Hadoop-based petroleum transport vehicle oil consumption prediction method which comprises the following steps: (1) a data collection step, (2) a data storage step, (3) a step of calculating an oil consumption influence factor correction coefficient and (4) prediction calculation of an oil consumption quota. According to the method disclosed in the invention, a petroleum transport vehicle is a research object; a relevant calculation model is built based on big data analyzing and processing technologies; vehicle oil consumption is analyzed and calculated, reference basis is provided for transport enterprises to set a reasonable oil consumption quota, a root reason for high oil consumption can be found during research, effective measures can be adopted for lowering oil consumption, costs can be reduced, and energy can be saved.

Description

technical field [0001] The invention relates to a Hadoop-based fuel consumption prediction method for petroleum transportation vehicles, in particular to a method for predicting the fuel consumption of petroleum transportation vehicles through big data analysis and processing, establishment of relevant calculation models, analysis and calculation, and belongs to the technical field of transportation vehicle management. Background technique [0002] Under the background of the country's implementation of energy conservation and emission reduction strategies, various industries are making various efforts to reduce carbon emissions. A very important aspect of energy efficiency improvement is to reduce gas consumption. The transportation industry accounts for the vast majority of energy consumption. and carbon emissions, in order to achieve energy conservation and emission reduction in the industry, breakthroughs should be found in management and technology. [0003] Petroleum t...

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Problems solved by technology

[0006] (1) The formulation of fuel consumption quotas is mostly obtained through experimental tests. Due to the limited test environment, various complex environments in practice cannot be widely considered, so the results of fuel consumption quotas do not conform to the actual situation to a large extent.

[0007] (2) The influence factors considered by the fuel consumption model calculation method are not comprehensive enough, and the correction values ​​of the influence factors are not accurate, part of which is based on reference to relevant standards, part of which is based on experience estimation, and the standard reference values ​​are only tested in the standard environment many years ago. Come on, it can be imagined that it can be used as a reference today after several years

[0008] (3) Fuel consumption analysis also needs to be targeted. For different companies, different vehicles, different transportation tasks and routes, the method of fuel consumption analysis cannot be the same. Therefore, it is not right to directly apply the results of fuel consumption research in other fields to petroleum transportation vehicles. realistic

[0009] With the development of OBD, Beidou / GPS, and big data analysis and processing technologies, traditional technical means can no longer meet the accuracy requirements of data in a large environment

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