Model-based pre-ignition diagnostics in a race car application

Since 2014, Formula 1 engines have been turbocharged spark-ignited engines. In this scenario, the maximum engine power available in full-load conditions can be achieved only by optimizing combustion phasing within the cycle, i.e., by advancing the center of combustion until the limit established by the occurrence of abnormal combustion. High in-cylinder pressure peaks and the possible occurrence of knocking combustion significantly increase the heat transfer to the walls and might generate hot spots inside the combustion chamber. This work presents a methodology suitable to properly diagnose and control the occurrence of pre-ignition events that emanate from hot spots. The methodology is based on a control-oriented model of the ignition delay, which is compared to the actual ignition delay calculated from the real-time processing of the in-cylinder pressure trace. When the measured ignition delay becomes significantly smaller than that modeled, it means that ignition has been activated by a hot spot instead of the spark plug. In this case, the presented approach, implemented in the electronic control unit (ECU) that manages the whole hybrid power unit, detects a pre-ignition event and corrects the injection pattern to avoid the occurrence of further abnormal combustion

Development of a Control-Oriented Ignition Delay Model for GCI Combustion

Increasingly stringent pollutant emission limits and CO2 reduction policies are forcing the automotive industry toward cleaner and decarbonized mobility. The goal is to achieve carbon neutrality within 2050 and limit global warming to 2 degrees C (possibly 1.5 degrees C) with respect to pre-industrial levels as stated in both the European Green Deal and the Paris Agreement and further reiterated at the COP26. With the aim of simultaneously reducing both pollutants and CO2 emissions, a large amount of research is currently carried out on low-temperature highly efficient combustions (LTC). Among these advanced combustions, one of the most promising is Gasoline Compression Ignition (GCI), based on the spontaneous ignition of a gasoline-like fuel. Nevertheless, despite GCI proving to be effective in reducing both pollutants and CO2 emissions, GCI combustion controllability represents the main challenge that hinders the diffusion of this methodology for transportation. Several works in the literature demonstrated that to properly control GCI combustion, a multiple injections strategy is needed. The rise of pressure and temperature generated by the spontaneous ignition of small amounts of early-injected fuel reduces the ignition delay of the following main injection, responsible for the torque production of the engine. Since the combustion of the pre-injections is chemically driven, the ignition delay might be strongly affected by a slight variation in the engine control parameters and, consequently, lead to misfire or knocking. The goal of this work was to develop a control-oriented ignition delay model suitable to improve the GCI combustion stability through the proper management of the pilot injections. After a thorough analysis of the quantities affecting the ignition delay, this quantity was modeled as a function of both a thermodynamic and a chemical-physical index. The comparison between the measured and modeled ignition delay shows an accuracy compatible with the requirements for control purposes (the average root mean squared error between the measured and estimated start of combustion is close to 1.3 deg), over a wide range of operating conditions. As a result, the presented approach proved to be appropriate for the development of a model-based feed-forward contribution for a closed-loop combustion control strategy

Review of combustion indexes remote sensing applied to different combustion types

This paper summarizes the main studies carried out by the authors for the development of indexes for remote combustion sensing applicable to different combustion types, i.e. conventional gasoline and diesel combustions, diesel PCCI and dual fuel gasoline-diesel RCCI. It is well-known that the continuous development of modern Internal Combustion Engine (ICE) management systems is mainly aimed at complying with upcoming increasingly stringent regulations throughout the world, both for pollutants and CO2 emissions. Performing an efficient combustion control is crucial for efficiency increase and pollutant emissions reduction. Over the past years, the authors of this paper have developed several techniques to estimate the most important combustion indexes for combustion control, without using additional cylinder pressure sensors but only using the engine speed sensor (always available on board) and accelerometers (usually available on-board for gasoline engines). In addition, a low-cost sensor based on acoustic sensing can be integrated to support combustion indexes evaluation and other engine relevant information. The real-time calculation of combustion indexes is even more crucial for innovative Low Temperature Combustions (such as diesel PCCI or dual fuel gasoline-diesel RCCI), mainly due to the high instability and the high sensitivity to slight variations of the injection parameters that characterize this kind of combustions. Therefore, the authors of this paper have applied the developed techniques not only to conventional engines (gasoline and diesel combustion), but also to engines modified for Low Temperature Combustions, with promising results in terms of validation and applicability for real-time combustion control. The developed methodologies have been tested and validated through a large amount of experimental tests. To run the estimation algorithms in real-time, they have been all implemented in a specifically designed rapid control prototyping system, the goal being to quantify the accuracy of the estimations and optimize the strategy implementations for the extensive use (in the near future) in modern Engine Control Modules (ECM)

Zero-Dimensional Model for Dynamic Behavior of Engineered Rubber in Automotive Applications

Abstract This paper presents a zero-dimensional model for the simulation of the mechanical behavior of automotive engineered rubber components, such as flexible couplings. The objective is to develop a real-time-capable model, able to simulate the behavior of a driveline containing elastomer components: the engineered rubber model has to correlate stretch to stress, the mechanical behavior being represented by means of a hysteresis cycle. The study presents the implementation of Maxwell and Voigt models, showing their limits in the representation of the material behavior: elastomers present a nonlinear response in the relationship stress-strain. A combination of Maxwell and Voigt models, with stiffness and damping variable according to the stress and strain rate, to represent nonlinear material responses, is coupled to a relaxation model, in order to represent the Mullins effect (the rubber mechanical behavior also depends on load history). Experimental tests have been carried out with different pre-load settings, stress amplitudes and stress frequencies. Tests results have been used to calibrate the parameters defining the simulation model, comparing the model outputs to experimental data: an optimization algorithm has been applied, with the aim of minimizing the results discrepancy with respect to experimental results. The optimization tool has been also used to reduce the number of parameters defining the model, in order to simplify the required computational power, avoiding at the same time over-parametrization. In the second section of the paper, the model is used for the simulation of a different rubber component, whose behavior is identified using quasi-static load ramps, frequency and amplitude sweeps, steps and random cycles. An alternative model formulation, minimizing the degrees of freedom is then applied to the new dataset. The model parameters are separately optimized using different tests, in order to capture the specific mechanical behavior. Finally, the identified parameters are used to simulate the elastomer response in random tests, comparing the results to experimental data, to evaluate the simulation quality in terms of RMSE

Injection Pattern Investigation for Gasoline Partially Premixed Combustion Analysis

Nowadays, compression-ignited engines are considered the most efficient and reliable technology for automotive applications. However, mainly due to the current emission regulations, that require increasingly stringent reductions of NOx and particulate matter, the use of diesel-like fuels is becoming a critical issue. For this reason, a large amount of research and experimentation is being carried out to investigate innovative combustion techniques suitable to simultaneously mitigate the production of NOx and soot, while improving engine efficiency. In this scenario, the combined use of compression-ignited engines and gasoline-like fuels proved to be very promising, especially in case the fuel is directly-injected in the combustion chamber at high pressure. The presented study analyzes the combustion process produced by the direct injection of small amounts of gasoline in a compression-ignited light-duty engine. The engine under investigation has been modified to guarantee a stable engine operation over its whole operating range, that is achieved controlling boost pressure and temperature, together with the design of the injection pattern. Experimental tests have been performed to highlight the impact of several control variables on the combustion effectiveness, i.e. on combustion efficiency and ignition delay. To identify the main mechanisms which impact the start of the combustion process and the sensitivity to the variation of the main control parameters, several tests have been run, directly-injecting constant amounts of gasoline in a compression ignited engine. These tests have been performed changing intake pressure and temperature (when suitable to maintain combustion stability), fuel pressure and injection timing within the cycle

automotive turbochargers power estimation based on speed fluctuation analysis

Turbocharging technology will play a crucial role in the near future as a way to meet the requirements for pollutant emissions and fuel consumption reduction. However, optimal turbocharger control is still an issue, especially for downsized engines fitted with a low number of cylinders. As a matter of fact, automotive turbochargers are characterized by wide operating range and unsteady gas flow through the turbine, while only steady flow maps are usually provided by the manufacturer. In addition, in passenger cars applications, real-time turbocharger optimal control is even more difficult because of the lack of information about pressure/temperature in turbine upstream/downstream circuits and turbocharger rotational speed. In order to overcome these unknowns, this work presents a methodology for instantaneous turbocharger rotational speed determination through a proper processing of the signal coming from one accelerometer mounted on the compressor diffuser, or one microphone facing the compressor. The presented approach can be used to evaluate both turbocharger speed mean value and the amplitude of turbocharger speed fluctuations caused by the pulsating gas flow in turbine upstream and downstream circuits. Once turbocharger speed has been determined, it can be used to estimate power delivered by the turbine. The whole estimation algorithm has been developed and validated for a light duty turbocharged Common-Rail Diesel engine mounted in a test cell. However, the developed methodology is general and can be applied to different turbochargers, both for Spark Ignited and Diesel applications. © 2015 Published by Elsevier Ltd

Investigation of Gasoline Partially Premixed Combustion with External Exhaust Gas Recirculation

The stringent emission regulations for Internal Combustion Engines (ICEs) spawned a great amount of research in the field of innovative combustion approaches characterized by high efficiency and low emissions. Previous research demonstrate that such promising techniques, named Low-Temperature Combustion (LTC), combine the benefits of Compression Ignition (CI) engines, such as high compression ratio and unthrottled lean mixture, with low engine-out emissions using a properly premixed air-fuel mixture. Due to longer ignition delay and high volatility compared to diesel, gasoline-like fuels show good potential for the generation of a highly premixed charge, which is needed to reach LTC characteristics. In this scenario, gasoline Partially Premixed Combustion (PPC), characterized by the high-pressure direct injection of gasoline, showed good potential for the simultaneous reduction of pollutants and emissions in CI engines. However, previous research on gasoline CI highlight that a key factor for the optimization of both efficiency and pollutants is the proper management of Exhaust Gas Recirculation (EGR). This work presents the experimental investigation performed running a light-duty CI engine, operated with gasoline PPC, and varying the mass of recirculated gases trapped in the combustion chamber. To guarantee the stability of gasoline autoignition in all the tested conditions, a specific experimental layout has been developed to accurately quantify the amount of trapped residual gases due to the internal and external EGR. The obtained results clearly highlight the impact of EGR on the combustion process and emissions, demonstrating that optimization of charge dilution with EGR is fundamental to guarantee the optimal compromise between efficiency and emissions over the whole operating range

Accelerometer-based SOC estimation methodology for combustion control applied to Gasoline Compression Ignition

The European Community's recent decision to suspend the marketing of cars with conventional fossil-fueled internal combustion engines from 2035 requires new solutions, based on carbon-neutral technologies, that ensure equivalent performances in terms of reliability, trip autonomy, refueling times and end-of-life disposal of components compared to those of current gasoline or diesel cars. The use of bio-fuels and hydrogen, which can be obtained by renewable energy sources, coupled with high-efficiency combustion methodologies might allow to reach the carbon neutrality of transports (net-zero carbon dioxide emissions) even using the well-known internal combustion engine technology. Bearing this in mind, experiments were carried out on compression ignited engines running on gasoline (GCI) with a high thermal efficiency which, in the future, could be easily adapted to run on a bio-fuel. Despite the well-reported benefits of GCI engines in terms of efficiency and pollutant emissions, combustion instability hinders the diffusion of these engines for industrial applications. A possible solution to stabilize GCI combustion is the use of multiple injections strategies, typically composed by 2 early injected fuel jests followed by the main injection. The heat released by the combustion of the earlier fuel jets allows to reduce the ignition delay of the main injection, directly affecting both delivered torque and center of combustion. As a result, to properly manage GCI engines, a stable and reliable combustion of the pre-injections is mandatory. In this paper, an estimation methodology of the start of combustion (SOC) position, based on the analysis of the signal coming from an accelerometer sensor mounted on the engine block, is presented (the optimal sensor positioning is also discussed). A strong correlation between the SOC calculated from the accelerometer and that obtained from the analysis of the rate of heat release (RoHR) was identified. As a result, the estimated SOC could be used to feedback an adaptive closed-loop combustion control algorithm, suitable to improve the stability of the whole combustion process

1D-3D coupled approach for the evaluation of the in-cylinder conditions for Gasoline Compression Ignition Combustion

Nowadays, progressive improvements of engine performance must be performed to reduce fuel consumption, which directly affects the amount of CO2 released in the atmosphere. For this purpose, considering modern technologies in the automotive scenario, Gasoline Compression Ignition (GCI) combustion might represent one promising solution, since it experiences high thermal efficiency of Compression Ignited (CI) engines and pollutant emission mitigation. This paper shows the first step of a project aimed at reproducing the combustion behavior of a Diesel engine running with GCI combustion by means of CFD simulations. In particular, this work presents a methodology used to reconstruct the mixing process inside the cylinder before the combustion event, since those engines are dramatically sensitive to the global and local mixture quality. Firstly, a reverse-engineering procedure aimed at generating the CAD model of the engine was performed. Afterwards, the discharge coefficients of the intake and exhaust valves through specifically designed 3D CFD simulations were determined, which was necessary due to the customized intake/exhaust line. Eventually, to reasonably reconstruct the in-cylinder state, the Rate of Heat Release (RoHR) curve, calculated from the analysis of the in-cylinder pressure signal running the engine in GCI mode, was imposed in GT-Power by means of a combination of Wiebe functions with the purpose of generating representative trends of pressure, temperature, and mass flow to properly define the domains of the CFD model

automatic calibration of control parameters based on merit function spectral analysis

Abstract The number of actuations influencing the combustion is increasing, and, as a consequence, the calibration of control parameters is becoming challenging. One of the most effective factors influencing performance and efficiency is the combustion phasing: for gasoline engines control variables such as Spark Advance (SA), Air-to-Fuel Ratio (AFR), Variable Valve Timing (VVT), Exhaust Gas Recirculation (EGR) are mostly used to set the combustion phasing. The optimal control setting can be chosen according to a cost function, taking into account performance indicators, such as Indicated Mean Effective Pressure (IMEP), Brake Specific Fuel Consumption (BSFC), pollutant emissions, or other indexes inherent to reliability issues, such as exhaust gas temperature, or knock intensity. The paper proposes the use of the extremum seeking approach during the calibration process. The main idea consists in changing the values of each control parameter at the same time, identifying its effect on the monitored cost function, allowing to shift automatically the control setting towards the optimum solution throughout the calibration procedure. Obviously, the nodal point is to establish how the various control parameters affect the monitored cost function and to determine the direction of the required variation, in order to approach the optimum. This task is carried out by means of a spectral analysis of the cost function: each control variable is varied according to a sine wave, thus its effect on the cost function can be determined by evaluating the amplitude of the Fast Fourier Transform (FFT) of the cost function, for the given excitation frequency. The FFT amplitude is representative of the cost function sensitivity to the control variable variations, while the phase can be used to assess the direction of the variation that must be applied to the control settings in order to approach the optimum configuration. Each control parameter is excited with a different frequency, thus it is possible to recognize the effect of a single parameter by analyzing the spectrum of the cost function for the given excitation frequency. The methodology has been applied to data referring to a PFI engine, trying to maximize IMEP, while limiting the knock intensity and exhaust gas temperature, using SA and AFR as control variables. The approach proved to be efficient in reaching the optimum control setting, showing that the optimal setting can be achieved rapidly and consistently