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Adaptation of predictive combustion models for their use in in-cycle closed-loop combustion control of a multi-cylinder engine is studied in this article. Closed-loop combustion control can adjust the operation of the engine closer to the optimal point despite production tolerances, component variations, normal disturbances, ageing or fuel type. In the fastest loop, in-cycle closed-loop combustion control was proved to reduce normal variations around the operational point to increase the efficiency. However, these algorithms require highly accurate predictive models, whilst having low complexity for their implementation. Three models were used to exemplify the proposed adaptation methods: the pilot injection’s ignition delay, the pilot burned mass, and the main injection’s ignition delay. Different approaches for the adaptation of the models are studied to obtain the demanded accuracy under the implementation constraints.

Factors influencing the effect of pilot-injection on main-injection combustion were investigated using heat release analysis in a heavy-duty diesel engine fuelled with standard diesel fuel, and included the effect of those factors on engine performance and emissions. Combinations of pilot injection parameters i.e. pilot start of injection, pilot mass, pilot-main injection separation, and rail pressure were studied for various operating conditions and combustion phases. It was concluded that the effect of pilot-injection combustion on main injection can be studied based on the phase of pilot combustion at the start of main injection. Four cases were identified: a) main injection during the mixing phase of pilot injection; b) main injection during the premixed phase of pilot combustion; c) main injection during the diffusive phase of pilot combustion and d) main injection after pilot combustion was completed.

Factors influencing pilot-injection combustion were investigated using heat release analysis in a heavy-duty diesel engine fuelled with standard diesel fuel. Combinations of pilot-injection parameters i.e. pilot start of injection, pilot mass, pilot-main injection separation, and rail pressure were studied for various operating conditions and combustion phases. An experiment was designed to investigate the factors influencing the combustion of the pilot. For improved injected fuel-mass accuracy, reference data for the injectors were measured in a spray rig prior to the engine experiments. Results show that cycle-to-cycle variations and cylinder-to-cylinder variations influence pilot autoignition and the amount of heat released. Rail pressure and injected pilot mass affect the obtained variance depending on the chamber conditions. The obtained combustion modes (premixed, diffusive) of pilot combustion were found to be a function of the injected mass and rail pressure.

The emission control in heavy-duty vehicles today is based on predefined injection strategies and after-treatment systems such as SCR (selective catalytic reduction) and DPF (diesel particulate filter). State-of-the-art engine control is presently based on cycle-to-cycle resolution. The introduction of the crank angle resolved pressure measurement, from a piezo-based pressure sensor, enables the possibility to control the fuel injection based on combustion feedback while the combustion is occurring. In this paper a study is presented on the possibility to control NOx (nitrogen oxides) formation with a crank angle resolved NOx estimator as feedback. The estimator and the injection control are implemented on an FPGA (Field-Programmable Gate Array) to manage the inherent time constraints. The FPGA is integrated with the rest of the engine control system for injection control and measurement.

In the automotive industry, the piezo-based in-cylinder pressure sensor is getting commercialized and used in production vehicles. For example, the pressure sensor offers the opportunity to design algorithms for estimation of engine emissions, such as soot and NO , during a combustion cycle. In this paper a zero-dimensional NO model for a diesel engine is implemented that will be used in real time. The model is based on the thermal NO formation and the Zeldovich mechanism using two non-geometrical zones: burned and unburned zone. The influence of EGR on combustion temperature was modeled using a well-known thermodynamic identity where specific heat at constant pressure is included. Specific heat will vary with temperature and the gas composition. The model was implemented in LabVIEW using tools specific for an FPGA (Field-Programmable Gate Array).