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This paper investigates the FPGA resources for the implementation of in-cycle closed-loop combustion control algorithms. Closed-loop combustion control obtains feedback from fast in-cylinder pressure measurements for accurate and reliable information about the combustion progress, synchronized with the flywheel encoder. In-cycle combustion control requires accurate and fast computations for their real-time execution. A compromise between accuracy and computation complexity must be selected for an effective combustion control. The requirements on the signal processing (evaluation rate and digital resolution) are investigated. A common practice for the combustion supervision is to monitor the heat release rate. For its calculation, different methods for the computation of the cylinder volume and heat capacity ratio are compared. Combustion feedback requires of virtual sensors for the misfire detection, burnt fuel mass and pressure prediction.

Pilot injections are normally used for the reduction of diesel engine emissions and combustion noise. Nonetheless, with a penalty on the indicated thermal efficiency. The cost is reduced by the minimization of the pilot mass, which on its counterpart increases the risk of pilot misfire. Pilot misfire can have a higher penalty on the indicated efficiency if it is not compensated adequately. This paper investigates how in-cycle closed-loop combustion control techniques can reduce the effects of pilot misfire events. By closed-loop combustion control, pilot misfire can be detected and counteracted in-cycle. Two injection strategies are investigated. The first is the control of the main injection, the second includes an additional second pilot injection. Based on the in-cycle misfire diagnose, two architectures are investigated. The first uses a cycle-to-cycle controller to set the main injection under each scenario.

In the last couple of decades, countries have enacted new laws concerning environmental pollution caused by heavy-duty commercial and passenger vehicles. This is done mainly in an effort to reduce smog and health impacts caused by the different pollutions. One of the legislated pollutions, among a wide range of regulated pollutions, is nitrogen oxides (commonly abbreviated as NOx). The SCR (Selective Catalytic Reduction) was introduced in the automotive industry to reduce NOx emissions leaving the vehicle. The basic idea is to inject a urea solution (AdBlue™) in the exhaust gas before the gas enters the catalyst. The optimal working temperature for the catalyst is somewhere in the range of 300 to 400 °C. For the reactions to occur without a catalyst, the gas temperature has to be at least 800 °C. These temperatures only occur in the engine cylinder itself, during and after the combustion.

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).