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Research

  • Statistical Analysis of Knock Intensity Probability Distribution and Development of 0-D Predictive Knock Model for a SI TC Engine

    Year: 2018

    Author: Nicolo Cavina, Alessandro Brusa, Nahuel Rojo, Enrico Corti

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    Knock is a non-deterministic phenomenon and its intensity is typically defined by a non-symmetrical distribution, under fixed operating conditions. A statistical approach is therefore the correct way to study knock features. Typically, intrinsically deterministic knock models need to artificially introduce Cycle-to-Cycle Variation (CCV) of relevant combustion parameters, or of cycle initial conditions, to generate different knock intensity values for a given operating condition. Their output is limited to the percentage of knocking cycles, once the user imposes an arbitrary knock intensity threshold to define the correlation between the number of knocking events and the Spark Advance (SA).
    In the first part of the paper, a statistical analysis of knock intensity is carried out: for different values of SA, the probability distributions of an experimental Knock Index (KI) are self-compared, and the characteristics of some percentiles are highlighted.
    The innovative contribution of this work is to correlate such KI probability curves with mean combustion parameters (like maximum in-cylinder pressure or combustion phase) through an analytical function. In this way, KI distributions can be predicted by a fully deterministic combustion model, ignoring CCV. In the final part of the paper such relations are implemented in a 1-D environment and tested using a combustion model, previously calibrated via Three Pressure Analysis (TPA) for knock-free operating conditions. Validation is carried out by comparing experimental and simulated KI distributions.

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  • Model-Based Test Bench Conditioning Systems Control

    Year: 2018

    Author: Enrico Corti, Michele Taccioli, Fabrizio Ponti

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    Engine test benches are crucial instruments to perform tests on internal combustion engines. Possible purposes of these tests are detecting engine performance, checking the reliability of engine components or making a proper calibration of engine control systems managing the actuations. Since many factors affect tests results in terms of performance, emissions and components durability, an engine test bench is equipped with several conditioning systems (oil, water and air temperature, air humidity, etc.), in order to maintain the controlled variables to the target values, throughout the test duration.
    The conditioning systems are often independently controlled by means of dedicated Programmable Logic Controllers (PLC), but a centralized model-based management approach could offer several advantages in terms of promptness and accuracy. This work presents the application of such control methodology to oil, water and HVAC (Heating, Ventilating and Air Conditioning) conditioning systems, where each actuator is managed coupling model-based open-loop controls to closed-loop actions. The main advantage of integrating the management of several actuators is that the control actions can be coordinated, similarly to what has been achieved in engine management systems with torque-based control: the risk of conflicts in the control actions on different actuators can be reduced, while the introduction in the control loops of other actuators is easier.
    The control methodology has been validated on an engine test bench where the automation system has been developed on an open software Real-Time compatible platform, allowing the integration of the conditioning system control with all other functionalities concerning the test management. The paper shows the plant layout, details the control strategy and finally analyzes experimental results obtained on the test bench, highlighting the benefits of the proposed management approach.

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