MATLAB Implementation of Internal Combustion Engine Rotor Simulation

Rotor simulation for internal combustion engines serves as a crucial method for studying the dynamic characteristics of rotor systems. Using MATLAB enables efficient simulation of rotor motion states, particularly the impact of defects like cracks on rotor performance. First, establish the rotor's dynamic model. Typically, the finite element method or lumped mass method is employed to simplify the rotor into a multi-degree-of-freedom system, accounting for parameters such as rotor mass, stiffness, and damping. In MATLAB, this involves defining mass matrices (M), stiffness matrices (K), and damping matrices (C) using appropriate functions like sparse() for efficient large-scale system handling. For rotors containing cracks, the stiffness at the crack location changes, requiring modification of the stiffness matrix in the model. This is implemented by introducing a correction term to the stiffness matrix, often through a stiffness reduction factor or a time-varying stiffness function to reflect the crack's influence on dynamic characteristics. Next, solve the rotor's equations of motion using MATLAB. Numerical integration methods such as ode45 can be utilized to compute the transient response of the rotor. The implementation involves defining a function that represents the system of differential equations, typically in the form M*d2x/dt2 + C*dx/dt + K*x = F(t), where F(t) is the external force vector. For eigenvalue analysis, functions like eig() can be used to determine natural frequencies and mode shapes. The presence of cracks leads to asymmetric stiffness, triggering nonlinear vibration phenomena such as subharmonic resonance, which may require specialized solvers like ode15s for stiff systems or custom implementations for nonlinear terms. Finally, analyze the impact of cracks on rotor performance. By comparing vibration responses between healthy and cracked rotors, the severity of cracks and their effect on rotor stability can be assessed. Common analysis metrics include amplitude, phase, and spectral characteristics. In MATLAB, this involves using FFT (fft()) for frequency domain analysis, plotting tools for time-domain response visualization, and statistical functions for quantitative comparison. Parameters like root mean square (RMS) amplitude or harmonic ratios can be computed to quantify crack effects. Through MATLAB simulation, the influence of cracks on rotor dynamic behavior can be visually demonstrated, providing a theoretical basis for fault diagnosis and health management of internal combustion engine rotors. Code implementation typically includes modular scripts for model definition, solver execution, and results analysis, facilitating parameter studies and validation against experimental data.