Predictive models for vehicle energy consumption are crucial for sustainable development in urban road traffic systems. This paper comprehensively reviews classic predictive models and develops a novel statistical-dynamical energy consumption prediction framework called Vehicle Energy Conservation Equation (VECE). VECE is constructed based on the principles of vehicle energy flow and regression analysis, employing a continuous and concise mathematical formulation. Its coefficients possess clear physical interpretations, allowing for application in various vehicle categories. To validate VECE, this study collected energy consumption data from 28 vehicles, including 9 diesel vehicles, 16 gasoline vehicles, 1 ethanol gasoline vehicle, and 2 battery electric vehicles. A rigorous data processing procedure was designed. Data analysis revealed that the VECE coefficients are correlated with vehicle type, speed, and acceleration. VECE's predictive performance is minimally impacted by the number of vehicle categories, effectively modeling energy consumption for vehicles of the same fuel type or size category. Comparative analysis with E-EcoGest, VT-Micro, PERE, and CMEM demonstrates the moderate accuracy of VECE in predicting instantaneous vehicle energy consumption while excelling in predicting cumulative energy consumption. The minimum relative percentage error for the cumulative predicted values is 4.2%. Overall, VECE demonstrates outstanding performance in computational simplicity, coefficient interpretability, adaptability, and extensibility, making it a crucial tool for achieving energy-efficient road transport systems.

中文翻译：

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预测能耗的统计动态框架的验证：车辆节能方程的研究

车辆能耗预测模型对于城市道路交通系统的可持续发展至关重要。本文全面回顾了经典的预测模型，并开发了一种新颖的统计动态能耗预测框架，称为车辆节能方程（VECE）。 VECE基于车辆能量流和回归分析原理，采用连续且简洁的数学公式构建。其系数具有清晰的物理解释，可应用于各种车辆类别。为了验证VECE，本研究收集了28辆汽车的能耗数据，其中包括9辆柴油车、16辆汽油车、1辆乙醇汽油车和2辆纯电动汽车。设计了严格的数据处理程序。数据分析表明，VECE系数与车辆类型、速度和加速度相关。 VECE 的预测性能受车辆类别数量的影响极小，可以有效地对相同燃料类型或尺寸类别的车辆的能耗进行建模。与 E-EcoGest、VT-Micro、PERE 和 CMEM 的比较分析表明，VECE 在预测车辆瞬时能耗方面具有中等精度，但在预测累积能耗方面表现出色。累积预测值的最小相对百分比误差为 4.2%。总体而言，VECE 在计算简单性、系数可解释性、适应性和可扩展性方面表现出出色的性能，使其成为实现节能道路运输系统的关键工具。