Nitrogen oxides (NO_x) are one of the main harmful emissions from diesel engines. Regulations on emissions are becoming more stringent; consequently, research should aim at reducing both engine-out NO_x and tail-pipe NO_x emissions. Exhaust gas recirculation is mainly used to reduce engine-out NO_x emissions. After-treatment methods such as lean NO_x trap systems and selective catalyst reduction are used to minimize tail-pipe NO_x emissions. Real-time feedback control during transient conditions can further reduce these emissions and be utilized when information about real-time engine-out NO_x emissions is available. It would be helpful to evaluate the proportion of NO₂ in NO_x emissions because the conversion efficiency of an after-treatment system is affected by temperature and the NO-to-NO₂ ratio. Therefore, a semi-empirical NO_x model considering NO and NO₂ separately was developed for a diesel engine in this study. The NO estimation model was established based on the extended Zeldovich mechanism. The NO₂ estimation model focused on chemical reactions between NO and other species and was based on formation and decomposition mechanisms. This NO_x model can contribute to the cost reduction of engine systems by replacing existing NO_x sensors and can also be applied to real-time feedback control strategies to minimize NO_x emissions.

氮氧化物 (NO _x ) 是柴油发动机的主要有害排放物之一。排放法规越来越严格；因此，研究应着眼于减少发动机排出的 NO _x和尾管 NO _x排放。废气再循环主要用于减少发动机排出的NO _X排放物。后处理方法，如贫NO _X捕集器系统和选择性催化还原被用于最小化尾管NO _X排放。瞬态条件下的实时反馈控制可以进一步减少这些排放，并在有关实时发动机排出 NO _{x 的信息时使用}排放量可用。由于后处理系统的转化效率受温度和 NO 与 NO _{2 之}比的影响，因此评估 NO ₂在 NO _x排放物中的比例会有所帮助。因此，在本研究中为柴油发动机开发了分别考虑 NO 和 NO ₂的半经验 NO _x模型。NO估计模型是基于扩展的Zeldovich机制建立的。NO ₂估计模型侧重于NO 与其他物种之间的化学反应，并基于形成和分解机制。这种NO _x模型可以通过替换现有的NO _{x 为}降低发动机系统的成本做出贡献传感器，并且还可以应用到实时反馈控制策略以尽量减少NO _X排放。