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Simulating data mining method for electric vehicle charging station system

A system data and charging station technology, applied in the information field, can solve problems such as data disasters, incomplete data information, and difficulty in finding useful information, and achieve the goals of meeting charging needs, maximizing scheduling benefits, and ensuring data reliability and effectiveness Effect

Active Publication Date: 2015-07-15
芜湖楚睿智能科技有限公司
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AI Technical Summary

Problems solved by technology

But a large amount of data is also prone to "data disaster", making it difficult for managers to find useful information quickly and effectively
Moreover, the traditional monitoring method is to set the threshold by the staff to check the data information, which may lead to incomplete data information and information defects.

Method used

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  • Simulating data mining method for electric vehicle charging station system

Examples

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Embodiment 1

[0026] Example 1: Provide a data mining method suitable for new urban electric vehicle charging stations. This method is based on fuzzy mathematics and probability statistics theory, including the following steps:

[0027] Step 1: Establish a data warehouse of the charging station system, and obtain data from the charging station, mobile charging vehicle, vehicle battery and electric vehicle users in the form of data packets.

[0028] Step 2: According to the data attribute, the data in the data warehouse is pre -processed, that is, discrete division, and extract the required feature set.

[0029] Step 3: Evaluate the subordinates of the element in the feature set and set the parameterization settings.

[0030] Step 4: Use fuzzy mathematics and probability statistics theory, set up data mining computing, dig data mining, and obtain the required user charging needs information.

[0031] Step 5: Output the data obtained from the excavation and feedback to the management of the charg...

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Abstract

The invention provides a method for mining data of a novel urban electric vehicle charging station system. The method comprises the following steps of establishing a data warehouse, and collecting and recording the data of the charging station system and an electric vehicle user in real time; classifying, pre-processing and discretizing the collected and recorded data, and extracting a required feature data set; evaluating the element membership of the feature set by a fuzzy mathematic and probability statistics theory, and parameterizing; calculating the parameterized set, and obtaining a relation matrix of the user charging demand, the charging area and the charging time; extracting and evaluating the results, and feeding and outputting the evaluation conclusion to a management center of the charging station system and a user mobile terminal, so as to assist to make a decision. The method has the advantages that the benefits of the charging station planning and the movable electric vehicle scheduling are maximized, and the charging requirement of the user is met.

Description

Technical field [0001] The invention involves a data mining method, especially the simulation data mining method of an electric vehicle charging station system, which is the field of information technology. Background technique [0002] In recent years, with the increasing exhaustion of oil energy and the intensification of environmental pollution, the development of the automotive industry has faced major challenges.The electric vehicle uses electricity as the energy basis. Because its energy utilization rate is higher than that of fuel vehicles, and the advantages of pollutant emissions are lower than that of ordinary internal combustion engines, the industrialization of electric vehicles has a broad market prospect. It is the main direction of the future development of the automotive industry in the future.EssenceAs the energy supply station of electric vehicles, the charging station system is an indispensable infrastructure that promotes the development of electric vehicle in...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q50/06
Inventor 李衍飞
Owner 芜湖楚睿智能科技有限公司
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