Optimizing Methanol Blending Performance of Electronically Controlled Diesel Engines through Fuzzy Analysis

• Published in: E3S web of conferences 2023-01, Vol.423, p.1003
• Main Authors: Cai, Zheng, Yang, Chenxi, Fan, Jinyu, Li, Pinfang, Huang, Zhaoxia, Huang, Jialiang
• Format: Article
• Language: English
• ISSN: 2267-1242; 2267-1242
• DOI: 10.1051/e3sconf/202342301003

This paper presents a comprehensive optimization approach for enhancing the performance of a methanol/diesel Exhaust Gas Recirculation (EGR) engine. Initially, a hybrid fuel engine combustion chamber model was developed using AVL-FIRE software, and the simulated results were compared with the values obtained from bench tests. An orthogonal experimental design was employed to optimize five key factors, namely methanol blending ratio, EGR rate, injection advance angle, intake pressure, and intake temperature. Evaluation indexes were established, with indicated power and NO emissions assigned weights of 0.35 and 0.65, respectively. The optimal parameter combinations were determined as follows: methanol blending ratio (a1=20%), EGR rate (a2=12.5%), injection advance angle (a3=16.6°CA), intake temperature (a4 = 315.15 K), and intake pressure (a5=0.173 MPa). The indicated power of the optimized configuration reached 47.8 kW, slightly lower than the original 55 kW, while the NO emission mass fraction decreased to 1.9×10 -4 %, representing a significant reduction of 77.6% compared to the original value of 8.5×10 -4 %. This optimization methodology demonstrates the effective reduction of NO emissions without compromising power performance in methanol/diesel EGR engines.