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Optimization of Engine Piston Performance Based on Multi-Method Coupling: Sensitivity Analysis, Response Surface
Bin Zheng1, Qintao Shui1, Zhecheng Luo1
1School of Intelligent Manufacturing, Panzhihua University, Panzhihua 617000, China.
Materials (Basel, Switzerland)
|July 12, 2025
Summary
Advanced optimization strategies improved engine piston performance by enhancing stiffness, strength, and dynamic characteristics. This resulted in reduced working temperature and increased natural frequencies, extending component life and improving thermal efficiency.
Area of Science:
- Mechanical Engineering
- Materials Science
- Computational Engineering
Background:
- Engine pistons are critical components influencing engine efficiency and reliability.
- Structural design and optimization are essential for improving piston performance and service life.
- Existing designs may face limitations in stiffness, strength, and dynamic characteristics under operational stress.
Purpose of the Study:
- To enhance the stiffness, strength, and dynamic characteristics of engine pistons through advanced optimization design strategies.
- To improve the overall performance, efficiency, and service life of engine pistons.
- To investigate the impact of design variables on piston performance under complex working conditions.
Main Methods:
- Construction of a 3D piston model and finite element analysis using ANSYS Workbench.
- Thermomechanical coupling analysis to simulate thermal and deformation states under operational conditions.
- Dynamic characteristic analysis to determine displacement-frequency curves and predict resonance behavior.
- Response surface methodology (RSM) and design of experiments (DOE) to model and evaluate optimization goals.
- Sensitivity analysis to identify critical design variables.
- Multi-objective genetic algorithm (MOGA) for comprehensive optimization.
Main Results:
- Optimized piston design showed a decrease in working temperature from 312.75 °C to 308.07 °C.
- Natural frequencies increased: first from 1651.60 Hz to 1671.80 Hz, second from 1656.70 Hz to 1665.70 Hz, and third from 1752.90 Hz to 1776.50 Hz.
- Piston mass and deformation remained relatively stable post-optimization.
- Response surface models demonstrated high significance and predictive accuracy.
- Sensitivity analysis identified key geometric dimensions impacting performance.
Conclusions:
- Advanced optimization techniques, integrating RSM and MOGA, successfully improved engine piston performance.
- The optimized design enhances dynamic stability, vibration resistance, and thermal efficiency, contributing to extended component life.
- The study provides a robust framework for multi-objective optimization of critical engine components.
Keywords:
ANOVAharmonic response analysismodal analysisoptimization designpistonresponse surface analysisthermal–mechanical coupling analysisMore Related Videos
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