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Homogenous charge compression ignition (HCCI) combustion is a low temperature combustion process which combines high combustion efficiency with ultra-low N O x raw emissions. Steep increases of the in-cylinder pressure and unstable combustion sequences at the limits of the operating range can damage the engine and limit the use of HCCI to part load operation. This can be done using closed loop combustion control based on combustion parameters like the indicated mean effective pressure and the combustion phasing. Since in-cylinder pressure sensors are expensive components and therefore not suitable for series application, ion current sensors can be used as an additional source of information about the combustion. Combustion analysis using methods similar to those used in pressure based measurements can be implemented using an online analysis of the ion current signal. In this study, the ion current sensor will be examined for its suitability for combustion control under HCCI conditions with lean air/fuel ratios and high compression ratios. Research has found that the ion current signal is strongly depended on the boundary conditions. Especially the air/fuel ratio which plays an important role for signal strength during the combustion process. When using valve timings with negative valve overlap in combination with a fuel pre-injection, a further peak of the ion current signal close to the gas exchange top dead center can be found in addition to the one during combustion. At the same time, it is hard to extract information from the cylinder pressure signal during NVO. Under lean conditions this peak even exceeds the signal during combustion. This study analyzes the ion current signal during NVO and its potential to be used for future combustion control concepts. The ion current signal shows potential to stabilize HCCI combustion at high loads. However, the prediction of late combustion cycles is still challenging. [ABSTRACT FROM AUTHOR]

Homogeneous charge compression ignition has proven to be both highly efficient and to operate with ultra-low NOx raw emissions. However, homogeneous charge compression ignition combustion is a dynamic process due to strong cycle-to-cycle coupling effects caused mainly by the residual gas. Compared to conventional spark-ignited and diesel engines, the lack of direct mixture composition and ignition control increases the challenge of combustion instabilities, especially at boundary conditions. To stabilize the combustion process, real-time in-cylinder combustion diagnostics and control are often used. In this study, for the first time, ion current detection technology and direct water injection are combined for homogeneous charge compression ignition combustion control. By analyzing the return map of the crank angle at 50% cumulative heat release under unstable conditions, it was identified that a misfire or incomplete combustion is usually followed by knocking-like early combustion with high cylinder pressure gradients. Through the correlation analysis between ion current and combustion, a cycle-to-cycle closed-loop control strategy was developed and implemented on a rapid control prototyping engine control unit. Real-time calculated ion current parameters were used to predict the 50% cumulative heat release position of the next cycle and prevent early combustion by direct water injection. The calculation results and controller performance were validated on a single-cylinder research engine. With the controller activated, the standard deviation of 50% cumulative heat release and dynamic programming to the max could be reduced by 19% and 11%, respectively. The coefficient of variation of indicated mean effective pressure was reduced by 12%. A slight increase in indicated mean effective pressure after activating the controller also shows the potential for efficiency improvement. Moreover, not only early combustion is controlled, but also late combustion is significantly reduced. [ABSTRACT FROM AUTHOR]

48V systems enable not only mild hybrid functionalities such as recuperation or torque assist by a belt-driven starter generator (BSG), but also electrification of accessories and the engine boosting system. To maximize the powertrain efficiency, a proper layout of the electrified system and an optimized distribution of the electric power during transient operation is essential. In this study, a vehicle co-simulation of a conventional powertrain with a downsized turbocharged gasoline engine is extended by a 48V system with an electric compressor (eC) and a BSG. The control functions of the eC and BSG are based on a state-of-the-art vehicle application and calibrated for transient operating conditions. The engine model, which is built using a one-dimensional crank angle resolved approach in GT-POWER, has been validated with measurement data and is used to predict the interaction between the eC and the engine air path. The investigations using the simulation platform show that the 48V eC and the BSG can significantly improve the fuel effïciency if the electric energy consumption is initially neglected. However, when considering the electric energy consumption within the vehicle co-simulation, efficient operation is particularly depending on driver torque demand, the battery state-of-charge and charging effïciency. Hence, intelligent operating strategies are necessary to take advantage of the better torque response and improve fuel consumption at the same time. [ABSTRACT FROM AUTHOR]

Homogeneous charge compression ignition (HCCI) offers a high potential in engine efficiency enhancement and ultra-low NOx raw emissions. However, the main difficulty in HCCI combustion is its controllability of the ignition, especially at boundary conditions. At these conditions, stochastic abnormal combustion may happen, such as incomplete combustion or knock. Traditional engine map-based control is not enough to overcome these problems. Real-time in-cylinder combustion diagnosis and cycle resolved combustion control are required. In this study, the ionization process during negative valve overlap (NVO) interval in HCCI engines is numerically studied. It is identified that the ion current can reflect the quality of fuel reforming, which has been validated in the experiments. Compared to other studies that only use a single sensor (pressure sensor or ion current sensor), here for the first time, two sensors are combined to enhance the diagnostic accuracy. Besides, for the first time, ion current during NVO is employed for control. The experiments were conducted both at light load and high load boundary conditions. For light load boundary condition, by combining two sensors, the diagnostic accuracy rate of stochastic incomplete combustion is about 91.3%, and the misjudgment rate is reduced by 30% compared to only use one of them. After the controller is activated, the standard deviations of CA50 (σ CA50) and IMEP (σ IMEP) are reduced by 14.6% and 11.3%, respectively. For high load boundary condition, σ CA50 and σ IMEP are reduced by 12.3% and 15.4% respectively. Besides, the knock intensity is reduced by 9%. Ultimately, IMEP of the minimal load is reduced from 0.23 MPa to 0.18 MPa with an extension of 22%, and IMEP of the maximum load is expanded from 0.33 MPa to 0.4 MPa with an expansion of 21%. [ABSTRACT FROM AUTHOR]

In this article, we analyze the interaction between powertrain technology, predictive driving functionalities, and inner-city traffic conditions. A model predictive velocity control algorithm is developed that utilizes dynamic traffic data as well as static route information to optimize the future trajectory of the considered ego-vehicle. This controller is then integrated into a state-of-the-art simulation environment for automated driving functionalities to calculate energy saving potentials for vehicles with a conventional gasoline engine powertrain and a P3-hybrid powertrain configuration as well as for a battery electric vehicle based on real driving measurements. The comparison of these powertrains under various traffic conditions shows that all three technologies profit from predictive driving functionalities. The determined reduction in energy demand ranges from 15% to more than 40%, but it is highly dependent on the boundary conditions and the selected powertrain technology. Specifically, it is shown that electrified powertrains can profit the most when the time-gap to the preceding vehicle is maintained at a high level. For a conventional powertrain, this effect is less pronounced and can be attributed to the efficiency characteristics of gasoline engines. It can be concluded that the development of advanced predictive driving functionalities requires microscopic simulation of inner-city traffic to achieve optimum results with regard to energy consumption. [ABSTRACT FROM AUTHOR]

Homogeneous charge compression ignition has the potential to significantly reduce NOx emissions, while maintaining a high fuel efficiency. Homogeneous charge compression ignition is characterized by compression-induced autoignition of a lean homogeneous air-fuel mixture. Combustion timing is highly dependent on the in-cylinder state including pressure, temperature and trapped mass. To control homogeneous charge compression ignition combustion, it is necessary to have an accurate representation of the gas exchange process. Currently, microprocessor-based engine control units require that the gas exchange process is linearized around a desired operating point to simplify the model for real-time implementation. This reduces the models' ability to handle disturbances and limits the flexibility of the model. However, using a field programmable gate array, a detailed simulation of the physical gas exchange process can be implemented in real time. This paper outlines the process of converting physical governing equations to an offline zero-dimensional gas exchange model. The process used to convert this model to a field programmable gate array capable model is described. This model is experimentally validated using a single cylinder research engine with electromagnetic valves to record realtime field programmable gate array gas exchange results and comparing to the offline zero-dimensional physical model. The field programmable gate array model is able to accurately calculate the cylinder temperature and cylinder mass at 0.1 CA intervals during the gas exchange process for a range of negative valve overlaps, boost conditions and engine speeds making the model useful for future real-time control applications. [ABSTRACT FROM AUTHOR]

By front-loading of the conventional vehicle testing to engine test bench or even further forward to offline simulations, it is possible to assess a large variation of powertrain design parameters and testing manoeuvres in the early development stages. This entails a substantial cost reduction compared to physical vehicle testing and hence an optimisation of the modern powertrain development process. This approach is often referred to as road-to-rig-to-desktop. To demonstrate the potential of this road-to-rig-to-desktop methodology as a seamless development process, a crank angle–resolved real-time engine model for a turbocharged gasoline engine was built with the simulation tool GT-POWER®. The model was validated with measurement data from an engine test bench and integrated into a vehicle co-simulation, which also includes a dual clutch transmission, the chassis, the environment and the automated driver. The most relevant functions of the engine and the transmission control systems were implemented in a Simulink-based software control unit. To verify the engine model in the transient vehicle simulation, two 900-s time windows from a 2-h real driving emission test, representing urban and motorway conditions, are simulated using the developed co-simulation platform. The simulation results are compared with the respective vehicle measurement data. The fuel consumption deviation caused by the combustion engine model is within 5%. The transient system behaviour and the dominant engine operation points could be predicted with a satisfying accuracy. [ABSTRACT FROM AUTHOR]