Investigation on the applicability for reaction rates adjustment of the optimized biodiesel skeletal mechanism

Bài báo do nhóm tác giả Teng Liu, Jiaqiang E, W.M. Yang , Yuangwang Deng,H.An, Zhiqing Zhang , Minhhieu Pham Trường Đại Học Hồ Nam Trung Quốc – Đại Học công nghiệp Hà Nội được đăng tải trên tạp chí Energy Conversion and Management (IF:5.589) nhà xuất bản Elsever số 150 năm 2018 (1031-1038)

Abstract

In order to reduce the blindness in developing a new skeletal mechanism, a chaos genetic algorithm (CGA) is proposed for optimizing the progress of reaction rates adjustment against traditional manual operator. By this way, an optimized mechanism has been generated from a skeletal mechanism including 112 species and 498 reactions, which was reduced from a detailed mechanism consisting of 3299 species and 10806 reactions. CGA is composed by important reactions determination, fitness function building, and chaos genetic compilation. To test the applicability of the optimized biodiesel skeletal mechanism, it has been validated by 0-D ignition delay prediction and 3-D engine simulation and experiment data. Results indicate that the ignition delay error of the optimized mechanism is smaller than the skeletal mechanism by comparing with the detailed mechanism. The optimized mechanism can simulate MD and MD9D ignition behavior over a wide range of common conditions. The 3-D engine prediction results also indicated that the optimized mechanism can better present the in-cylinder combustion characteristics.

Keywords: Chaos genetic algorithm, Ignition delay time, Reaction rates adjustme, Biodiesel mechanism