Research on the prediction of carbon emissions in the whole life cycle of electric vehicles considering time correlation

doi:10.19799/j.cnki.2095-4239.2021.0715

Abstract

Abstract:

Because of several contributing factors, it is difficult to correctly anticipate electric vehicle carbon emissions. As a result, a strategy for predicting carbon emissions from electric cars during their whole life cycle is suggested, taking into account temporal correlation. On the whole life cycle theory, measuring marginal electricity, and coal production line loss, suggestions produce carbon emissions, and the carbon emissions formed by coal transportation link power link's carbon footprint, and applies time correlation to the analysis of characteristics of the electric car driving, calculate direct carbon emissions, to complete consideration of time correlation prediction in the whole life cycle of the electric car carbon emissions. The experimental findings reveal that the proposed measuring technique has high accuracy in carbon emission forecast under vehicle uphill, downhill, congestion, and regular driving scenarios, which satisfies the requirement for electric vehicle carbon emission prediction.

Key words: time correlation, electric vehicles, full life cycle, carbon emissions, forecast, marginal power generation

CLC Number:

U 491

Guanghua WU, Hongsheng LI, Fei LI, Bo CHEN, Shike ZHANG. Research on the prediction of carbon emissions in the whole life cycle of electric vehicles considering time correlation[J]. Energy Storage Science and Technology, 2022, 11(7): 2206-2212.

Figures/Tables 9

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序号	名称	参数
1	单位	ppm^①、mg/m³、ppb^②、pphm^③、%VOL、 %LEL(部分可切换)
2	响应时间	≤20 s
3	测量精度	≤±3%
4	回复时间	≤20 s
5	零点漂移	≤±1%
6	重复性	≤±1%
7	测量方式	泵吸式，内置微型抽气泵
8	检测方式	实时检测、定时检测可设置
9	存储模式	实时存储、定时存储可设置；可存储数据 120000组，可在屏幕上查看历史数据

时间	累计碳排放量/kg
时间	实际值	预测值
9∶00	4.144	4.143
9∶30	3.543	3.541
10∶00	3.612	3.611
10∶30	3.857	3.855
11∶00	3.896	3.896
11∶30	4.265	4.265
12∶00	6.033	6.032
12∶30	6.193	6.193
13∶00	5.812	5.812
13∶30	4.179	4.177
14∶00	3.537	3.536
14∶30	3.471	3.471
15∶00	3.645	3.643

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