Four-Objective Optimization of Irreversible Atkinson Cycle Based on NSGA-II

Area of Science:

• Thermodynamics
• Mechanical Engineering
• Energy Systems

Background:

• The Atkinson cycle (AC) is a key engine design for improved thermal efficiency.
• Understanding the interplay between power density and thermal efficiency is crucial for engine optimization.
• Previous models established the foundation for analyzing irreversible thermodynamic cycles.

Purpose of the Study:

• To analyze the variation trends of dimensionless power density (PD) with compression ratio and thermal efficiency (TE) in an irreversible Atkinson cycle.
• To compare key performance parameters at maximum power output (PO) versus maximum PD.
• To perform multi-objective optimization (MOO) for dimensionless PO, TE, dimensionless PD, and dimensionless ecological function (EF).

Main Methods:

• Utilized an established irreversible Atkinson cycle model.
• Analyzed performance variations with compression ratio and thermal efficiency.
• Employed the non-dominated sorting genetic algorithm-II (NSGA-II) for multi-objective optimization.

Main Results:

• An optimal compression ratio exists that maximizes dimensionless PD, exhibiting a parabolic relationship.
• Dimensionless PD and TE show a loop-shaped relationship.
• Engines operating at maximum PD condition exhibit smaller size and higher TE compared to maximum PO conditions.
• Increased TE leads to decreased dimensionless PO, increased dimensionless PD, and a non-monotonic change in dimensionless EF.

Conclusions:

• The study identifies an optimal compression ratio for maximizing power density in Atkinson cycle engines.
• Multi-objective optimization reveals trade-offs between power output, thermal efficiency, power density, and ecological function.
• Findings provide theoretical guidance for optimizing the design of actual Atkinson heat engines.