Analysis of the correlation between effective compression ratio and effective expansion ratio and multi-parameters optimization in an asynchronous intake valve Miller cycle spark-ignition engine

Zhipeng Yuan, Huimin Zhou, Zhichao Chen, Jingping Liu, Dazi Shen, Shuqian Wang and Xiongbo Duan

Energy, 2025, vol. 336, issue C

Abstract: For Miller cycle engines with variable effective compression ratio (ECR), selecting the appropriate ECR under different operating conditions is a critical consideration, especially during the conceptual design and bench calibration phases. Consequently, the internal relationship between the ECR and effective expansion ratio (EER) is thoroughly investigated in an asynchronous intake valve Miller cycle engine through both experimental and simulation methods in this study. Then, a modified gross indicated thermal efficiency equation (GITE) is proposed to optimize the ECR and predict the performance of a variable compression ratio (CR) engine. The results show that the ECR and the 50 % combustion position (CA50) exhibit a positive correlation, especially at high loads. In addition, altering EER has a greater effect on gross indicated thermal efficiency compared to ECR. Moreover, the ECR-EER decoupling is achieved by the Miller cycle with an asynchronous intake valve (AIVMC) engine through interval angle control of the intake valve. This configuration enables a higher geometric compression ratio (GCR) while maintaining the adjustability of the ECR, resulting in a maximum GITE improvement of 4.7 % for AIVMC-CR12 compared to OC-CR10.5, and a 1.58 % reduction in the proportion of pump loss when the BMEP is 20 bar. Finally, a simulation model of the AIVMC-CR14.5 engine is established, and its performance is optimized using the NSGA-II algorithm. A notable improvement in fuel economy is achieved as evidenced by a brake specific fuel consumption reduction exceeding 4.5 %.

Keywords: Effective compression ratio; Modified gross indicated thermal efficiency equation; Thermal efficiency; Miller cycle; NSGA-II algorithm (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:336:y:2025:i:c:s0360544225042069

DOI: 10.1016/j.energy.2025.138564

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