A polluting gas emission prediction method for conventional energy and new energy public transport vehicles

Abstract

The invention discloses a polluting gas emission prediction method for conventional energy and new energy public vehicles, which overcomes the problem of inaccurate measurement and calculation in the prior art, through four steps of basic data collection, data preprocessing, data modeling and application analysis , based on the long-short-term memory neural network in the recurrent neural network, using a relatively simple and easy measurement method to study the operating characteristics and emission characteristics of the bus during the road section, fully considering the time-varying conditions, the vehicle itself The degree of influence of the state on the emission of pollutant gases, the exploration of the law of emission, and the realization of a more accurate prediction of the emission of conventional energy and new energy buses can provide theoretical guidance for the formulation of energy-saving and emission-reduction policies, and optimize the use of bus lanes. The construction provides guidance to enable managers and designers to better manage, adjust and optimize system operation and system design, and further reduce the greenhouse gas emissions of public transport vehicles.

Description

technical field [0001] The invention belongs to the technical field of traffic energy saving and emission reduction, and in particular relates to a method for predicting the emission of pollutant gas from conventional energy and new energy public transport vehicles. Background technique [0002] In recent years, climate change and air quality issues have become a worldwide problem. Many researchers have confirmed that traffic emissions are a major source of air pollution. Emissions such as particulates, carbon monoxide, carbon dioxide, hydrocarbons, and nitrogen oxides are produced during the movement of cars, which are very harmful to air quality and human health. At the same time, the increasing traffic demand has brought serious congestion, which will also increase emission pollution. In order to solve these problems, the role of the public transport system has been paid more and more attention by planning managers. [0003] Although the public transport system has been...

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Problems solved by technology

[0005] The present invention is aimed at the problems in the prior art, and provides a polluting gas emission prediction method for conventional energy and new energy public vehicles, which overcomes the problem of inaccurate measurement and calculation in the prior art, and through basic data collection and data preprocessing 1, data modeling and application analysis four steps, based on the long-term short-term memory neural network in the cyclic neural network, to achieve a more accurate prediction of the emissions of conventional energy and new energy buses, which can contribute to the formulation of energy-saving and emission-reduction policies Provide theoretical guidance and provide guidance for optimizing the construction of bus lanes, so that managers and designers can better manage, adjust and optimize system operation and system design

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