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Modern spark-ignited (SI) engines offer excellent emission reduction when operated with a stoichiometric mixture and a three-way catalytic converter. A challenge with stoichiometric compared to diluted operation is the knock propensity due to the high reactivity of the mixture. This limits the compression ratio, thus reducing engine efficiency and increasing exhaust temperature. The current work evaluated a model of conditions at inlet valve closing (IVC) and top dead center (TDC) for steady state operation. The IVC temperature model is achieved by a cycle-to-cycle resolved residual gas fraction estimator. Due to the potential charge cooling effect from methanol, a method was proposed to determine the fraction of fuel sourced from a wall film. Determining the level of charge cooling is important as it heavily impacts the IVC and TDC temperatures.

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.

The constrained indicated efficiency optimization of the set-point reference for in-cycle closed-loop combustion regulators is investigated in this article. Closed-loop combustion control is able to reduce the stochastic cyclic variations of the combustion by the adjustment of multiple-injections, a pilot and main injection in this work. The set-point is determined by the demand on engine load, burned pilot mass reference and combustion timing. Two strategies were investigated, the regulation of the start of combustion (SOC) and the center of combustion (CA50). The novel approach taken in this investigation consists of including the effect of the controlled variables on the combustion dispersion, instead of using mean-value models, and solve the stochastic optimization problem. A stochastic heat release model is developed for simulation and calibrated with extensive data from a Scania D13 six-cylinder engine. A Monte Carlo approach is taken for the simulations.

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.

For the reduction of emissions and combustion noise in an internal combustion diesel engine, multiple injections are normally used. A pilot injection reduces the ignition delay of the main injection and hence the combustion noise. However, normal variations of the operating conditions, component tolerances, and aging may result in the lack of combustion i.e. pilot misfire. The result is a lower indicated thermal efficiency, higher emissions, and louder combustion noise. Closed-loop combustion control techniques aim to monitor in real-time these variations and act accordingly to counteract their effect. To ensure the in-cycle controllability of the main injection, the misfire diagnosis must be performed before the start of the main injection. This paper focuses on the development and evaluation of in-cycle algorithms for the pilot misfire detection. Based on in-cylinder pressure measurements, different approaches to the design of the detectors are compared.

Global warming and climate change have led to a greater interest in the implementation of biofuels in internal combustion engines. In spark ignited engines, biofuels have been shown to improve efficiency and knock resistance while decreasing emissions of unburned hydrocarbons, carbon monoxide and particles. This study investigates the effect of biofuels on SI engine combustion through a graphical compilation of previously reported results. Experimental data from 88 articles were used to evaluate the trends of the addition of different biofuels in gasoline. Graphs illustrating engine performance, combustion phasing and emissions are presented in conjunction with data on the physiochemical properties of each biofuel component to understand the observed trends. Internal combustion engines have the ability to handle a wide variety of fuels resulting in a broad range of biofuel candidates.

Gaseous methane fuel for internal combustion engines have proved to be a competitive source of propulsion energy for heavy duty truck engines. Using biogas can even reduce the carbon footprint of the truck to near-zero levels, creating fully environmentally friendly transport. Gas engines have already been on the market and proved to be a popular alternative for buses and waste transport. However, for long haulage these gas engines have not been on par with the equivalent diesel engines. To improve the power and efficiency of EURO VI gas engines running stoichiometrically, a direct way forward is adding more boost pressure and spark advance in combination with more EGR to mitigate knock. Using in-cylinder turbulence to achieve higher mixing rate, the fuel can still be combusted efficiently despite the increased fraction of inert gases.

Clean combustion is one of the inherent benefits of using a high methane content fuel, natural gas or biogas. A single carbon atom in the fuel molecule results, to a large extent, in particle-free combustion. This is due to the high energy required for binding multiple carbon atoms together during the combustion process, required to form soot particles. When scaling up this process and applying it in the internal combustion engine, the resulting emissions from the engine have not been observed to be as particle free as the theory on methane combustion indicates. These particles stem from the combustion of engine oil and its ash content. One common practice has been to lower the ash content to regulate the particulate emissions, as was done for diesel engines. For a gas engine, this approach has been difficult to apply, as the piston and valvetrain lubrication becomes insufficient.

Typically the combustion in a direct injected compression ignited internal combustion engine is open-loop controlled. The introduction of a cylinder pressure sensor opens up the possibility of a virtual combustion sensor which could enable closed-loop combustion control and thus the potential to counteract effects such as engine part to part variation, component ageing and fuel quality diversity. Closed-loop combustion control requires precise, robust and preferably cheap sensors. This paper presents a virtual cylinder pressure sensor based on the signal from the inexpensive but well proven knock sensor. The method used to convert the knock sensor signal into a pressure estimate included the stages: Phase correcting the raw signal, Filtering the raw signal, Scaling the signal to known thermodynamic laws and provided engine sensors signals and Reconstructing parts of the signal with other known models and assumptions.

In this article, a virtual sensor for the estimation of the injected pilot mass in-cycle is proposed. The method provides an early estimation of the pilot mass before its combustion is finished. Furthermore, the virtual sensor can also estimate pilot masses when its combustion is incomplete. The pilot mass estimation is conducted by comparing the calculated heat release from in-cylinder pressure measurements to a model of the vaporization delay, ignition delay, and the combustion dynamics. A new statistical approach is proposed for the detection of the start of vaporization and the start of combustion. The discrete estimations, obtained at the start of vaporization and the start of combustion, are optimally combined and integrated in a Kalman Filter that estimates the pilot mass during the vaporization and combustion. The virtual sensor was programmed in a field programmable gate array (FPGA), and its performance tested in a Scania D13 Diesel engine.

The combustion in a direct injected internal combustion engine is normally open-loop controlled. The introduction of cylinder pressure sensors enables a virtual combustion sensor which in turn enables closed-loop combustion control, and the possibility to counteract effects such as engine part-to-part variation, component ageing and fuel quality diversity. Closed-loop combustion control requires precise, robust and preferably cheap sensors. This paper presents an investigation of the robustness and the limitation of a knock sensor based virtual combustion sensor. This virtual combustion sensor utilize the common heat release analysis using a knock sensor based virtual cylinder pressure signal. Major virtual sensor error sources in a heavy-duty engine were identified as: the specific heat ratio model, the boost pressure and the crank angle phasing. The virtual sensor errors were quantified in relation to both the measured cylinder pressure and the total virtual sensor error.

Improving turbocharger performance to increase engine efficiency has the potential to help meet current and upcoming exhaust legislation. One limiting factor is compressor surge, an air flow instability phenomenon capable of causing severe vibration and noise. To avoid surge, the turbocharger is operated with a safety margin (surge margin) which, as well as avoiding surge in steady state operation, unfortunately also lowers engine performance. This paper investigates the possibility of detecting compressor surge with a conventional engine knock sensor. It further recommends a surge detection algorithm based on their signals during transient engine operation. Three knock sensors were mounted on the turbocharger and placed along the axes of three dimensions of movement. The engine was operated in load steps starting from steady state. The steady state points of operation covered the vital parts of the engine speed and load range.

Typically, the combustion in an internal combustion engine is open-loop controlled. The introduction of a cylinder pressure sensor opens the possibility to introduce a virtual combustion sensor. This virtual sensor is a possible enabler for closed-loop combustion control and thus the possibility to counteract the effects of engine part to part variation, component ageing and fuel quality diversity. The extent to which these effects can be counteracted is determined by the detection limits of the virtual combustion sensor. To determine the limitation of the virtual combustion sensor, a virtual combustion sensor system was implemented based on a one-zone heat-release analysis, including the signal processing of the pressure sensor input. The typical error sources in a heavy-duty engine were identified and quantified. The virtual combustion sensor system was presented with flawed signals and the sensor’s sensitivities to the errors were quantified.

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.

In engine management systems many calculations and actuator actions are performed in the crank angle domain. Most of these actions and calculations benefit from an improved accuracy of the crank angle measurement. Improved estimation of crank angle, based on pulse signals from an induction sensor placed on the flywheel of a heavy duty CI engine is thus of great importance. To estimate the crank angle the torque balance on the crankshaft is used. This torque balance is based on Newton’s second law. The net torque gives the flywheel acceleration which in turn gives engine speed and crank angle position. The described approach was studied for two crankshaft models: A rigid crankshaft approach and a lumped mass approach, the latter having the benefit of being able to capture the torsional effects of the crankshaft twisting and bending due to torques acting on it. These methods were then compared to a linear extrapolation of the engine speed, a common method to estimate crank angle today.

Due to demanding legislation on exhaust emissions for internal combustion engines and increasing fuel prices, automotive manufacturers have focused their efforts on optimizing turbocharging systems. Turbocharger system control optimization is difficult: Unsteady flow conditions combined with not very accurate compressor maps make the real time turbocharger rotational speed one of the most important quantities in the optimization process. This work presents a methodology designed to obtain the turbocharger rotational speed via vibration analysis. Standard knock sensors have been employed in order to achieve a robust and accurate, yet still a low-cost solution capable of being mounted on-board. Results show that the developed method gives an estimation of the turbocharger rotational speed, with errors and accuracy acceptable for the proposed application. The method has been evaluated on a heavy duty diesel engine.

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.

The amount of emitted pollutants from an internal combustion engine is regulated by emission legislation. Commonly regulated pollutants for the diesel engine are NOx and PM. Exhaust gas recirculation (EGR) is one efficient way of controlling the NOx emissions, and to control PM emissions an accurate lambda control is used. Both EGR- and lambda control requires good knowledge of the gas flows in the engine. The gas flows of interest are inlet air, EGR, total gas flow through the engine and total amount of exhaust gas. There are several possible concepts to measure and/or model these gas flows, all with their pros and cons. Flow and concentration based measurement concepts for determining the gas flows in a heavy duty diesel engine with EGR are investigated. The flow based concepts measures the amount of gas directly with a flow meter such as a hot-film air meter, ultrasonic flow meter or an orifice plate.

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).