Abstract
The free-piston engine generator shows broad application prospects in highly mobile platforms and advanced equipment where compact spatial configuration is required. Considering the unique coupling between the engine and the linear generator, a coupled iterative method is proposed to validate and refine the simulation model of the system working process. The validation results demonstrate that the model can accurately reflect the thermodynamic processes and dynamic response characteristics of the system. Based on the developed model, the effects of key coupling parameters on engine performance are further investigated. The results indicate that, in the high-speed operating region, the linear relationship between the electromagnetic force of the motor and the mover velocity is enhanced, providing an important reference for correcting the electromagnetic damping coefficient in the system working process simulation model. With increasing scavenging pressure, the peak piston speed, compression ratio, and indicated thermal efficiency increase, while heat transfer loss and specific fuel consumption decrease. When the scavenging pressure reaches 1.33 bar, the indicated thermal efficiency attains 42.42%. As the electromagnetic damping coefficient increases, the heat transfer loss first decreases and then increases, reaching a minimum value of 80.60 J at an electromagnetic damping coefficient of 240. Comprehensive analysis shows that maintaining the scavenging pressure above 1.19 bar and controlling the electromagnetic damping coefficient below 280 are beneficial for reducing specific fuel consumption and heat transfer loss, while improving indicated thermal efficiency and indicated cycle work.
| Original language | English |
|---|---|
| Article number | 130443 |
| Journal | Applied Thermal Engineering |
| Volume | 293 |
| DOIs | |
| Publication status | Published - May 2026 |
| Externally published | Yes |
Keywords
- Multi-field coupling
- Numerical model
- Opposed-piston, free-piston engine generator
- Parameter analysis
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