基于便携式排放测量系统数据和人工智能方法的欧6启停车辆即时CO2排放建模
1Faculty of Mechanical Engineering and Aeronautics, Rzeszow University of Technology, 35-959, Rzeszow, Poland. mmadziel@prz.edu.pl.
Environmental science and pollution research international
|December 28, 2023
概括
启停技术可以降低车辆的燃油消耗. 这项研究开发了一个AI模型,使用车辆数据准确预测二氧化碳 (CO2) 排放,帮助环境分析.
科学领域:
- 汽车工程 汽车工程
- 环境科学 环境科学
- 人工智能的人工智能
背景情况:
- 启停技术越来越多地被采用,以提高车辆的燃油效率.
- 准确的二氧化碳排放建模对于环境影响评估至关重要.
- 现有的方法可能需要大量的数据或复杂的模拟.
研究的目的:
- 开发一种用于测量和建模具有启动停止技术的车辆二氧化碳排放的新方法.
- 利用人工智能技术,根据最小的车辆数据预测二氧化碳排放.
- 为微观环境分析验证开发的计算模型.
主要方法:
- 收集的测量数据包括车辆的速度,加速度和道路坡度.
- 应用并比较了三种机器学习技术:梯度增强等.
- 使用确定系数,平均平方误差和排放图表和地图的视觉分析,验证了模型性能.
主要成果:
- 梯度增强方法证明了二氧化碳排放的最佳预测准确性.
- 开发的模型仅使用速度,加速度和道路梯度数据成功预测了二氧化碳排放.
- 经过验证的模型通过统计指标和视觉评估显示出可靠的性能.
结论:
- 已经建立了一种新的AI驱动的 CO2 排放建模方法,用于使用启动停止技术的车辆.
- 开发的模型提供了微观环境分析的实用方法,数据要求最小.
- 这种方法可以支持有针对性的减少车辆排放和改善空气质量的战略.
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