Model-based torsional vibration control of internal combustion engines

The rotation of a crankshaft in piston combustion engines results from the acting of tangential forces on the crank, whose value changes with the change of the angle of shaft rotation. This results in torsional vibrations. These vibrations become especially dangerous when the frequency of changes of any components of tangential force is near or equal to the natural frequency of the shaft. It leads to resonant amplification of vibration amplitude and to exceeding the limit values of the angle of shaft torsion. Most often in such cases, various types of torsional vibration dampers are used. In automotive industry, these are usually rubber vibration dampers. Typical torsional vibration damper is an example of a resonant damper, which is designed for the most dangerous resonant frequency of the crankshaft related to the first form of vibration for which the torsional vibrations usually have the greatest amplitude. The design of such a damper involves choosing the inertia moment of the flywheel and the parameters of viscouselastic element. The article describes the model and the simulation research, which allowed for creating the procedure of designing rubber dampers of torsional vibrations. This procedure can help to reduce the costs of operation tests for the design of optimal torsional vibration damper.

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“…After analysis of different solutions [5,7,8,10,16] the following model of torsional vibration damper was developed (Fig. 4).…”

Section: The Model Of Torsional Vibration Dampermentioning

confidence: 99%

Model Aided Design of Tuned Rubber TVD

Pankiewicz

Chiliński

Wądołowski

2016

Journal of KONES. Powertrain and Transport

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“…These vibrations can be the result of eccentric masses [1] or be excited by the propulsion itself, e.g. a combustion engine [2,3,4] or an electric drive [5,6]. Another commonly occurring cause is the transformation of the rotational motion of the propulsion into a translational motion.…”

Section: Motivationmentioning

confidence: 99%

“…Active damping based on learning control is presented in [16]. In [4] the main target is to reduce the torsional vibrations of a crankshaft by adjusting the fuel injection duration by minimizing a cost function.…”

Section: Motivationmentioning

confidence: 99%

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Active control of speed fluctuations in rotating machines using feedback linearization

Holm

Ballesteros

Beitler

et al. 2012

Proceedings of 2012 UKACC International Conference on Control

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This paper presents a method for actively controlling torsional vibrations in rotating machines caused by angledependent parameters. The work is motivated by rotating machines with crank or cam gear mechanisms that cause fluctuations in the angular speed when the machine is driven by a constant load torque or when the speed is controlled with conventional controllers. A very general model for such a system is introduced and used to derive a control law by feedback linearization. With this control law, the speed fluctuations are completely eliminated and desired linear dynamics can be prescribed for the system. The method is tested in a simulation study with a model of a real industrial machine. Although the proposed method works well, the study is preliminary in the sense that the method has not been applied experimentally and its robustness has not been assessed.

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“…A new technique for failure prediction in a plant controlled by computerized SCADA system (Mayadevi, Vinodchandra, & Ushakumari, 2012), A method that detects combustion failures caused by a fuel deficiency in a cylinder, even in its early stages is presented by Nieto (Nieto, Blazquez, Platero, & Casado, 2017). A cylinder balancing method is disclosed which minimizes the crankshaft torsional vibrations at medium speed internal combustion engines (Ostman & Toivonen, 2008 detection in fossil power plants operation using recurrent neural networks (Sanchez, Suarez, & Ruz, 2004). This paper proposes a fuzzy inference model for detection and modeling of incipient faults in combustion engine components of the power generators.…”

Section: Introductionmentioning

confidence: 99%