Modeling the Influence of Engine Dynamics on Its Indicator Diagram

Area of Science:

• Mechanical Engineering
• Automotive Engineering
• Vibration Analysis

Background:

• Accurate modeling of engine combustion pressure is crucial for analyzing crankshaft torsional vibrations.
• Existing models may not adequately capture dynamic changes during acceleration.
• Understanding pressure variations is key to designing effective vibration dampers.

Purpose of the Study:

• To develop a model describing combustion chamber pressure changes relative to crankshaft angle during acceleration.
• To enable precise calculation of variable piston forces for torsional vibration simulations.
• To enhance the simulation of crankshaft behavior with vibration dampers under dynamic conditions.

Main Methods:

• Utilizing a Fourier series to represent continuous pressure changes within a single work cycle.
• Determining Fourier series coefficients via Fourier transform of averaged, discrete indicator diagrams.
• Recording pressure waveforms and shaft angle signals on a chassis dynamometer.
• Analyzing the impact of the number of series coefficients on signal energy representation.
• Incorporating work cycle uniqueness through random coefficient variations based on standard deviations.
• Modeling engine rotational speed changes for PID controller simulation.

Main Results:

• A novel model for describing engine combustion pressure as a function of crankshaft angle during acceleration.
• The model successfully integrates variable rotational speeds and unique work cycle characteristics.
• Analysis confirmed the influence of the number of Fourier series coefficients on signal energy.
• The model's accuracy in determining instantaneous rotational speed was assessed.

Conclusions:

• The proposed Fourier series model provides a robust method for simulating engine combustion pressure dynamics.
• This approach enhances the accuracy of torsional vibration analysis in crankshafts, particularly during acceleration.
• The model's ability to account for cycle-to-cycle variations improves simulation fidelity.
• Further research can explore limitations related to digital signal recording parameters.