Cylinder-to-cylinder combustion dispersion in internal combustion engines might be caused by various factors (e.g. manufacturing variations of the injectors or nozzle coking) which can result in an increase in pollutant emissions. When dealing with low temperature combustion concepts such as premixed dual-fuel, the system might suffer from an additional source of dispersion due to port fuel injection distribution. Conventional cylinder fuel concentration estimation is based on look-up tables previously calibrated and saved in the ECU. The aging and the fuel distribution characterization of the injectors are a challenging task when relying only on a single UEGO sensor placed at the exhaust. In-cylinder pressure sensors offer a powerful solution to evaluate the energy released by the fuel with one cycle resolution. The present work proposes to combine the information provided by such sensor together with conventional sensors, in this case air mass flow and lambda sensor, for estimating the fuel concentration and blending ratio entering each cylinder in a heavy-duty dual-fuel engine. A Kalman filter was designed to tackle the dynamics of the system, e.g. lambda sensor delay and port fuel distribution, and validated in both conventional diesel and dual-fuel combustion. The output of the filter was then used to update the injectors look-up table in order to cope with aging and possible bias over time.

内燃发动机中的气缸间燃烧分散可能是由多种因素引起的（例如，喷油嘴的制造变化或喷嘴焦化），这可能导致污染物排放量增加。当处理低温燃烧概念（例如预混合双燃料）时，由于进气道燃料喷射分配，系统可能会遭受其他分散源的困扰。传统的汽缸燃油浓度估算是基于事先校准并保存在ECU中的查询表。当仅依赖于放置在排气口的单个UEGO传感器时，喷油器的老化和燃料分配特性是一项艰巨的任务。缸内压力传感器提供了一种强大的解决方案，以一个周期的分辨率评估燃料释放的能量。本工作提出将由这种传感器提供的信息与常规传感器（在这种情况下为空气质量流量和λ传感器）结合起来，以估计进入重型双燃料发动机中每个气缸的燃料浓度和混合比。卡尔曼滤波器的设计旨在解决系统的动力学问题，例如lambda传感器延迟和端口燃料分配，并已在常规柴油和双燃料燃烧中得到验证。然后使用滤波器的输出来更新喷油器查询表，以应对老化和随时间推移可能出现的偏差。卡尔曼滤波器的设计旨在解决系统的动力学问题，例如lambda传感器延迟和端口燃料分配，并已在常规柴油和双燃料燃烧中得到验证。然后使用滤波器的输出来更新喷油器查询表，以应对老化和随时间推移可能出现的偏差。卡尔曼滤波器设计用于解决系统的动力学问题，例如lambda传感器延迟和端口燃料分配，并已在常规柴油和双燃料燃烧中得到验证。然后使用滤波器的输出来更新喷油器查询表，以应对老化和随时间推移可能出现的偏差。