Optimization with OMSimulator

1. Parameter Optimization of a Dual Mass Oscillator

• Objective: Minimize the oscillation amplitude by optimizing the damping coefficient.
• Approach: Use an optimization algorithm (e.g., gradient descent, genetic algorithms) to adjust damping parameters and simulate the system using FMI.
• Evaluation: Compare optimized and non-optimized results in terms of settling time and oscillation reduction.

2. Suspension Tuning in the Quarter Car Model

• Objective: Optimize suspension stiffness and damping for ride comfort and handling.
• Approach: Use SSP-based co-simulation to iteratively test different spring and damper values, minimizing acceleration forces felt by the chassis.
• Evaluation: Compare different configurations based on ride comfort (vertical acceleration) and stability.