A vehicle specific power (VSP) modal model and the MOtor Vehicle Emission Simulator (MOVES) Operating Mode (OpMode) model have been used to evaluate and quantify the fuel use and emission rates (FUERs) for on-road vehicles. These models bin second-by-second FUERs based on factors such as VSP, speed, and others. The validity of binning approaches depends on their precision and accuracy in predicting variability in cycle-average emission rates (CAERs). The objective is to quantify the precision and accuracy of the two modeling methods. Since 2008, North Carolina State University has used portable emission measurement systems to measure tailpipe emission rates for 214 light duty gasoline vehicles on 1,677 driving cycles, including 839 outbound cycles and 838 inbound cycles on the same routes. These vehicles represent a wide range of characteristics and emission standards. For each vehicle, the models were calibrated based on outbound cycles and were validated based on inbound cycles. The goodness-of-fit of the calibrated models was assessed using linear least squares regression without intercept between model-predicted versus empirical CAERs for individual vehicles. Based on model calibration and validation, the coefficients of determination (R²) typically range from 0.60 to 0.97 depending on the vehicle group and pollutant, indicating moderate to high precision, with precision typically higher for higher-emitting vehicle groups. The slopes of parity plots for each vehicle group and all vehicles typically range from 0.90 to 1.10, indicating good accuracy. The two modeling approaches are similar to each other at the microscopic and macroscopic levels.

车辆特定功率（VSP）模态模型和机动车排放模拟器（MOVES）运行模式（OpMode）模型已用于评估和量化公路车辆的燃料使用率和排放率（FUER）。这些模型根据诸如VSP，速度等因素对秒级FUER进行分级。分级方法的有效性取决于它们在预测循环平均发射率（CAER）变异性方面的精度和准确性。目的是量化两种建模方法的精度和准确性。自2008年以来，北卡罗莱纳州立大学一直使用便携式排放测量系统来测量214辆轻型汽油车在1677个驾驶循环中的尾气排放率，其中包括在相同路线上的839个出站循环和838个入站循环。这些车辆代表了广泛的特性和排放标准。对于每辆车，都基于出站周期对模型进行了校准，并根据进站周期进行了验证。使用线性最小二乘回归评估校准模型的拟合优度，而各个车辆的模型预测CAER与经验CAER之间没有截距。基于模型校准和验证，确定系数（R ²）通常在0.60至0.97的范围内变化，具体取决于车辆组和污染物，表示中等到高精度，对于排放量较高的车辆组，其精度通常较高。每个车辆组和所有车辆的奇偶校验图的斜率通常在0.90至1.10的范围内，这表明精度很高。两种建模方法在微观和宏观层面上彼此相似。